From 219e9369198b4db169aad97871cba76c135720e2 Mon Sep 17 00:00:00 2001 From: kndiaye Date: Thu, 6 Mar 2014 17:21:15 +0100 Subject: [PATCH] Initial commit --- .gitignore | 2 + 3rdparty/dualcursor.m | 846 ++ 3rdparty/findjobj.m | 2793 ++++ 3rdparty/jewelersLoupe.m | 122 + 3rdparty/m2googlevis.m | 105 + 3rdparty/magnify.m | 139 + @int32/sparse.m | 11 + FindConstInMFiles.m | 58 + MRslice.m | 214 + Plot2dHist.m | 37 + Tr2event.m | 35 + WhatsThisImage.m | 74 + WilcoxonSRPVs.m | 104 + absolutepath.m | 156 + affinetransform.m | 72 + allhandles.m | 47 + allthesame.m | 60 + allunique.m | 31 + aprime.m | 150 + argouts.m | 13 + art/rectpix.m | 18 + art/rotbar.m | 43 + art/test.jpg | Bin 0 -> 99700 bytes avevar.m | 17 + bardata.m | 22 + barerrorbar.m | 107 + barstem.m | 84 + barweb.m | 170 + baseline_correction.m | 33 + beamformerkernel.m | 25 + between.m | 41 + bibliography/hindex.m | 176 + bibliography/pmid2bib.m | 16 + bit.m | 12 + bitget2.m | 26 + blackguis.m | 15 + bootstrap.m | 47 + 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100644 zscore.m create mode 100644 ztransform.m diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..241bda6 --- /dev/null +++ b/.gitignore @@ -0,0 +1,2 @@ +.svn +.DS_Store \ No newline at end of file diff --git a/3rdparty/dualcursor.m b/3rdparty/dualcursor.m new file mode 100644 index 0000000..cfcf989 --- /dev/null +++ b/3rdparty/dualcursor.m @@ -0,0 +1,846 @@ +function val = dualcursor(state,deltalabelpos,marker_color,datalabelformatfcnh,axh) +%dualcursor Add dual vertical cursors to a plot +% +%Syntax +% dualcursor +% dualcursor('state'); +% dualcursor([X1 X2]); +% dualcursor('state',deltalabelpos); +% dualcursor([X1 X2],deltalabelpos); +% dualcursor('update', ...) %Updates existing cursors when data has changed +% dualcursor(..., ..., marker_color_spec); +% dualcursor(..., ..., ..., fcnhandle); +% dualcursor(..., ..., ..., ..., axh); +% val = dualcursor %return values of the 2 cursors on the current axis +% val = dualcursor(h) %return values of the 2 cursors on the axis or line w/handle h +% +%Description +% Easy Mode: +% dualcursor on %Turns on data cursors +% dualcursor off %Turns off data cursors +% dualcursor %Toggles the state of data cursors +% val = dualcursor %Return the coordinates of the 2 cursors +% val = [x1 y1 x2 y2] +% +% Interaction: +% Click on the cursors to drag them around. +% Click on the cursor label to reposition. +% If multiple lines are plotted, click on a line to make it active. +% Right click on a cursor to: +% - Export the selected region to the workspace +% (exports as a structure named cursors) +% - Export the selected region to a new figure +% - Export cursor data to workspace +% (exports as a variable named cursordata = [x1 y1 x2 y2]) +% - Remove the cursors from the plot +% Click on the delta calculation labels to reposition them. +% +% Advanced Options: +% 1. Specify initial x-coordinates for the cursors +% dualcursor([x1 x2]); %Adds cursors at x1, x2 +% +% 2. Specify the location of the text label for displaying x2-x1, y2-y1 results +% dualcursor([],deltalabelpos); %Specifies the location to display DeltaX +% %and DeltaY calculations +% deltalabelpos = [DeltaX_x, DeltaX_y; DeltaY_x, DeltaY_y] in normalized axis units +% default = [.65 -.08;.9 -.08] puts them just below the lower right-hand corner. +% If this is too hard, you can also reposition the labels with your mouse! +% +% 3. Specifying the color and marker for the cursors +% dualcursor([],[],marker_color_spec); +% %Turns on data cursor, using specified marker and color +% %marker_color_spec is a one or two element string, specifying color and/or marker +% %style. >>help plot for valid marker and color specifiers +% ex 'go' - red circles +% 's' - squares, with default color (red) +% +% 4. Update the existing cursors when the data in the plot has changed. +% dualcursor('update'); +% This mode is useful when using the cursors on a live data stream. +% +% This simply updates the appropriate values to reflect the latest data. Here's +% how to do this: +% - When you initialize the graphics before taking data, make your initial call +% to dualcursor (dualcursor on, for instance) +% - In the code that updates the graphics display with new data, call +% dualcursor update +% +% 5. Specify custom formatting for the data label showing individual cursor values +% This is implemented with a function handle (@). You provide a handle to a +% specifically formatted function: +% dualcursor(..., ..., ..., fcnhandle) +% %Specifies the text and formatting for the data label +% %fcnhandle is a handle to the function that defines the formatting. This function +% %must have the following argument syntax: +% function textstring = mytextstring(xv,yv); +% Input: +% xv (scalar) The x cursor value +% yv (scalar) The y cursor value +% Output: +% textstring (string) The formatted text string +% {'string'} Cell array of strings for multi-line display +% +% Example +% Create the following function. save as frequencystring.m +% function textstring = frequencystring(xv,yv); +% textstring = {['Amp: ' num2str(yv,'%2g') ' dB'] +% ['f: ' num2str(xv,'%2g') ' Hz'];}; +% %Use this code when you are ready to call dualcursor +% fcnhandle = @frequencystring; %Create handle to your function +% dualcursor(..., ..., ..., fcnhandle) +% +% 6. Add cursors to a specific axis (not necessarily current axis). +% dualcursor(..., ..., ..., ..., axh); +% Adds the cursors to the axis with handle axh +% This mode is useful when axis handles might be hidden +% +% +% Example +% %Set up some interesting data +% load handel +% Ns = 2^12; +% Y = fft(y,Ns); +% Y = 2/Ns*abs(Y(1:Ns/2)); +% df = Fs/Ns; +% f = (0:1:Ns/2-1)*df; +% %Plot it +% figure; +% plot(f,100*[Y sqrt(Y)]) +% title('My cursor example'); +% xlabel('Frequency (Hz)'); +% ylabel('Amplitude'); +% axis([0 1200 0 inf]); +% +% %Turn on cursors +% dualcursor +% +% %Turn off cursors +% dualcursor off +% +% %Place cursors at x=300 and x=400, place DeltaX/DeltaY display in the upper left +% % hand corner, and use a green square for the cursor. +% dualcursor([300 400],[.05 1.05; .25 1.05],'gs'); +% +% %Move the cursors around. Try moving the data label, too +% +% %Now, wasn't that fun? Finally, get the current cursor positions +% val = dualcursor; +% %val = [x1 y1 x2 y2] +% +% +% NOTE: HandleVisibility of axis must be set to 'on' or 'callback' +% +% see also: DATALABEL, LINELABEL + +% This function is provided as an example only. It has not been +% tested, and therefore, it is not officially supported by The +% MathWorks, Inc. + +% Written by Scott Hirsch +% shirsch@mathworks.com +% Copyright (c) by The MathWorks, Inc. 1985-2002 +% This is a (major) modfication of datalabel, available at MATLAB Central + +%Parse input arguments +%If output argument, return the cursor values + +%See if the user specified a formatting function for the datalabel + + +if nargin<4 || isempty(datalabelformatfcnh) %Nope. Use the default one included here. + datalabelformatfcnh = @local_maketextstring; +end; + +if nargout + if nargin==0 %Use current axis + h = gca; + else + h = state; + if strcmp(get(h,'Type'),'line'); + h = get(h,'Parent'); + end; + end; + cursors = findobj(h,'Tag','Cursor'); + if length(cursors)==2 %Should be empty (no cursors), or length=2 + for ii=1:2 + cn = getappdata(cursors(ii),'CursorNumber'); + ind = (cn-1)*2+1:cn*2; %Index into val + val(ind) = getappdata(cursors(ii),'Coordinates'); + end; + else + val = []; + warning('I could not find any cursors'); + end; + return +elseif nargin<5 || isempty(axh) %Did the user specify a handle? + axh = gca; +end; + + +%If no input arguments, switch state (turn off/on) +if (nargin==0 & nargout==0) | isempty(state) %Switch state. Check current state + dots = findobj(axh,'Type','line','Tag','Cursor'); %See if there are any cursors + if isempty(dots) %None found. Turn cursors on + state = 'on'; + else + state = 'off'; + end; +end; + +%Check if the first argument is numeric. The user is specifying +% the initial x-coordinates of the markers +if nargin>=1 & isnumeric(state) %First input is x coordinates of markers + x_init = state(:); + + %error check + if length(x_init)~=2 + error('First input must be 2 element vector of x coordinates'); + end; + state = 'on'; %Turn on data cursors. +else %Default position = 1/3, 2/3 x axis limits + % xl = xlim; %X Limits. this is the letter L, not the number 1 + if strcmp(get(axh,'Type'),'figure') || strcmp(get(axh,'Type'),'uipanel') || strcmp(get(axh,'Type'),'root'); %user clicked on the axis itself; do nothing + return + end; + + + xl = xlim(axh); + lim = localObjbounds(axh); % Problem using objbounds with hggroup objects, so I have a simple version of my own + lim = lim(1:2); %x values only + xl(isinf(xl)) = lim(isinf(xl)); + width = diff(xl); %Axis width + x_init = xl(1)+[1/3 2/3]*width; + +end; + +% Get handle to figure just once +hFig = ancestor(axh,'figure'); + + +switch state + case 'on' + %Initialization + % Set the WindowButtonDownFcn + % Add the cursors. + + %If there are already some data cursors on this plot, delete them! + dualcursor('off',[],[],[],axh); + + %Parse user inputs + + %Check for user input of position for delta labels + if nargin<2 | isempty(deltalabelpos) + deltalabelpos = [.65 -.08;.9 -.08]; %Use defaults + %[x1 y1; x2 y2] + end; + + + %Marker and color specification + if nargin >= 3 , + %Parse marker string. User might specify color, marker, or both + colors = 'bgrcmyk'; + markers = '+o*.xsdv^>=6.5 + set(th1,'BackgroundColor','y'); + set(th2,'BackgroundColor','y'); + end; + + yl = ylim(axh); + lim = localObjbounds(axh); + lim = lim(3:4); %y values only + yl(isinf(yl)) = lim(isinf(yl)); + + %Add the cursors + ph1 = line([xv1 xv1 xv1],[yl(1) yv1 yl(2)], ... + 'Color',color, ... + 'Marker',marker, ... + 'Tag','Cursor', ... + 'UserData',[lineh th1], ... + 'LineStyle','-', ... + 'Parent',axh); + ph2 = line([xv2 xv2 xv2],[yl(1) yv2 yl(2)], ... + 'Color',color, ... + 'Marker',marker, ... + 'Tag','Cursor', ... + 'UserData',[lineh th2], ... + 'LineStyle','-', ... + 'Parent',axh); + + %Add context menu to the cursors +% cmenu = uicontextmenu('Parent',get(axh,'Parent')); + cmenu = uicontextmenu('Parent',hFig); + set([ph1 ph2],'UIContextMenu',cmenu); + + % Define the context menu items + item1 = uimenu(cmenu, 'Label', 'Export region to workspace', ... + 'Callback', 'dualcursor(''exportws'',[],[],[],get(gco,''Parent''))'); + item2 = uimenu(cmenu, 'Label', 'Export region to new figure', ... + 'Callback', 'dualcursor(''exportfig'',[],[],[],get(gco,''Parent''))'); + item3 = uimenu(cmenu, 'Label', 'Export cursor data to workspace', ... + 'Callback', 'dualcursor(''exportcursor'',[],[],[],get(gco,''Parent''));'); + item4 = uimenu(cmenu, 'Label', 'Turn cursors off', ... + 'Callback', 'dualcursor(''off'',[],[],[],get(gco,''Parent''))', ... + 'Separator','on'); + + + setappdata(th1,'Coordinates',[xv1 yv1]); + setappdata(ph1,'Coordinates',[xv1 yv1]); + setappdata(th2,'Coordinates',[xv2 yv2]); + setappdata(ph2,'Coordinates',[xv2 yv2]); + setappdata(th1,'CursorNumber',1); + setappdata(ph1,'CursorNumber',1); + setappdata(th2,'CursorNumber',2); + setappdata(ph2,'CursorNumber',2); + setappdata(th1,'FormatFcnH',datalabelformatfcnh); + setappdata(th2,'FormatFcnH',datalabelformatfcnh); + setappdata(th1,'Offset',[0 0]); %Offset for the text label from the data value + setappdata(th2,'Offset',[0 0]); %Offset for the text label from the data value + + % mh = uicontextmenu('Tag','DeleteObject', ... + % 'Callback','ud = get(gco,''UserData'');delete([gco ud(2)]);'); + % set([th1 th2],'UIContextMenu',mh); + + set(th1,'UserData',[lineh ph1]); %Store handle to line + set(th2,'UserData',[lineh ph2]); %Store handle to line + + + %Calculate Difference + dx = xv2 - xv1; + dy = yv2 - yv1; + + %Add display for cursor deltas + deltah(1) = text(deltalabelpos(1,1),deltalabelpos(1,2),['({x}_{2}-{x}_{1}) = ' num2str(dx,'%+.2f')], ... + 'Units','Normalized', ... + 'HorizontalAlignment','left', ... + 'Tag','CursorDeltaText', ... + 'FontSize',8, ... + 'Interpreter','tex', ... + 'Parent',axh); %dx + deltah(2) = text(deltalabelpos(2,1),deltalabelpos(2,2),['{y}_{2}-{y}_{1} = ' num2str(dy,'%+.2f')], ... + 'Units','Normalized', ... + 'HorizontalAlignment','left', ... + 'Tag','CursorDeltaText', ... + 'FontSize',8, ... + 'Interpreter','tex', ... + 'Parent',axh); %dy + + %Set Application Data. + setappdata(axh,'Delta_Handle',deltah); + setappdata(axh,'Marker',marker); + setappdata(axh,'Color',color); + + set(hFig,'WindowButtonDownFcn','dualcursor(''down'',[],[],[],get(gco,''Parent''))') + set(hFig,'DoubleBuffer','on'); %eliminate flicker + + case 'down' % Execute the WindowButtonDownFcn + htype = get(gco,'Type'); + tag = get(gco,'Tag'); + marker = getappdata(axh,'Marker'); + color = getappdata(axh,'Color'); + + %If it's a movable object (Cursor, CursorText label, or Cursor Delta Text + %label), make it movable. + if strcmp(tag,'CursorText') | strcmp(tag,'Cursor') | strcmp(tag,'CursorDeltaText') + set(gco,'EraseMode','xor') + set(gcf,'WindowButtonMotionFcn','dualcursor(''move'',[],[],[],get(gco,''Parent''))', ... + 'WindowButtonUpFcn','dualcursor(''up'',[],[],[],get(gco,''Parent''))'); + end; + + if strcmp(tag,'Cursor') %If clicked on a cursor + %Label the cursor we are moving. Add a text label just above the plot + CursorNumber = getappdata(gco,'CursorNumber'); + cnstr = num2str(CursorNumber); + + xl = xlim(axh); + lim = localObjbounds(axh); + lim = lim(1:2); %x values only + xl(isinf(xl)) = lim(isinf(xl)); + % yl = lim(3:4); + + + xv = getappdata(gco,'Coordinates'); + xv = xv(1); + + %Convert to normalized + xn = (xv - xl(1))/(xl(2) - xl(1)); + yn = 1.05; + + CNh = text(xn,yn,cnstr, ... + 'Units','Normalized', ... + 'HorizontalAlignment','center', ... + 'Parent',axh); %dx + + %For R13 or higher (MATLAB 6.5), use a background color on the text string + v=ver('MATLAB'); + v=str2num(v.Version); + if v>=6.5 + set(CNh,'BackgroundColor','y'); + end; + setappdata(gco,'CNh',CNh); + + end + + case 'move' % Execute the WindowButtonMotionFcn + htype = get(gco,'Type'); + tag = get(gco,'Tag'); + if ~isempty(gco) + + %Special (simple) case - just repositioning the delta labels + if strcmp(tag,'CursorDeltaText') %The cursor delta labels. + cp = get(axh,'CurrentPoint'); + pt = cp(1,[1 2]); + + %Put into normalized units + ax = axis; + lim = localObjbounds(axh); + ax(isinf(ax)) = lim(isinf(ax)); + + pt(1) = (pt(1) - ax(1))/(ax(2)-ax(1)); + pt(2) = (pt(2) - ax(3))/(ax(4)-ax(3)); + + set(gco,'Position', [pt 0]) + drawnow + return + end; + + %Is this the cursor or the text + if strcmp(tag,'CursorText') %The text + th = gco; + handles = get(gco,'UserData'); + ph = handles(2); + slide = 0; %Don't slide along line; just reposition text + else %The marker + ph = gco; + handles = get(gco,'UserData'); + th = handles(2); + slide = 1; %Slide along line to next data point + end; + + offset = getappdata(th,'Offset'); %Offset from data value + + cp = get(axh,'CurrentPoint'); + pt = cp(1,[1 2]); + + %Constrain to Line + lh = getappdata(get(th,'Parent'),'SelectedLine'); + % lh = handles(1); %Line + + x = cp(1,1); %first xy values + y = cp(1,2); %first xy values + + if slide %Move to new data value + xl = get(lh,'XData'); + yl = get(lh,'YData'); + + + %Get nearest value + [xv,yv]=local_nearest(x,xl,yl); + + + %If we are moving a cursor, must move the cursor number label, too + if strcmp(tag,'Cursor') + %Move the Cursor Number label, too + CNh = getappdata(gco,'CNh'); + pos = get(CNh,'Position'); + xlm = xlim(axh); + lim = localObjbounds(axh); + lim = lim(1:2); %x values only + xlm(isinf(xlm)) = lim(isinf(xlm)); + xn = (xv - xlm(1))/(xlm(2)-xlm(1)); + set(CNh,'Position',[xn pos(2:3)]) + end; + + yl = ylim(axh); + lim = localObjbounds(get(lh,'Parent')); + lim = lim(3:4); %y values only + yl(isinf(yl)) = lim(isinf(yl)); + datalabelformatfcnh = getappdata(th,'FormatFcnH'); + + textstring = feval(datalabelformatfcnh,xv,yv); + set(th,'Position', [xv yv 0] + [offset 0],'String',textstring) + set(ph,'XData',[xv xv xv],'YData',[yl(1) yv yl(2)]); + + setappdata(ph,'Coordinates',[xv yv]); + setappdata(th,'Coordinates',[xv yv]); + + %Update delta calculation + cursors = findobj(axh,'Tag','Cursor'); + cn1 = getappdata(cursors(1),'CursorNumber'); + if cn1==2 %Switch order + temp = cursors(1); + cursors(1) = cursors(2); + cursors(2) = temp; + end; + + + deltah = getappdata(axh,'Delta_Handle'); %Handle to cursors + + %Positions of two dualcursors + xy1 = getappdata(cursors(1),'Coordinates'); + xy2 = getappdata(cursors(2),'Coordinates'); + + + %Calculate Difference + dx = xy2(1) - xy1(1); + dy = xy2(2) - xy1(2); + + set(deltah(1),'String',['({x}_{2}-{x}_{1}) = ' num2str(dx,'%+.2f')]); + set(deltah(2),'String',['({y}_{2}-{y}_{1}) = ' num2str(dy,'%+.2f')]); + + else %Just move text around. + set(th,'Position', [x y 0]) + end; + drawnow + end; + + case 'up' % Execute the WindowButtonUpFcn + htype = get(gco,'Type'); + tag = get(gco,'Tag'); + if strcmp(tag,'CursorText') | strcmp(tag,'Cursor') | strcmp(tag,'CursorDeltaText'); + set(gco,'EraseMode','Normal') + set(gcf,'WindowButtonMotionFcn','') + + if strcmp(tag,'CursorText') %If the text label, record it's relative position + cp = get(axh,'CurrentPoint'); + pt = cp(1,[1 2]); + + coords = getappdata(gco,'Coordinates'); + offset(1) = pt(1) - coords(1); + offset = pt - coords; + setappdata(gco,'Offset',offset); + end; + + + if strcmp(tag,'Cursor') %Delete the temporary cursor number label + CNh = getappdata(gco,'CNh'); + delete(CNh); + end; + + end; + + case 'selectline' % User selected a new line to be active + %Make the selected line bold + lh = getappdata(axh,'SelectedLine'); + lw = get(lh,'LineWidth'); + set(lh,'LineWidth',5*lw); + drawnow + + %Update the cursors + dualcursor('update',deltalabelpos,marker_color,datalabelformatfcnh,axh); + + %Put the line back the way you found it! + set(lh,'LineWidth',lw); + + case 'update' %Update the cursor value + %Find the position of the existing cursors + + cursors = findobj(axh,'Tag','Cursor'); + cd1 = getappdata(cursors(1),'Coordinates'); + cd2 = getappdata(cursors(2),'Coordinates'); + cn1 = getappdata(cursors(1),'CursorNumber'); + cn2 = getappdata(cursors(2),'CursorNumber'); + clear x + x(cn1) = cd1(1); %x value of cursor number cn1 + x(cn2) = cd2(1); %x value of cursor number cn2 + + lh = getappdata(axh,'SelectedLine'); + + handles = get(cursors(cn1),'UserData'); + th1 = handles(2); + handles = get(cursors(cn2),'UserData'); + th2 = handles(2); + + offset1 = getappdata(th1,'Offset'); %Offset from data value + offset2 = getappdata(th2,'Offset'); %Offset from data value + + + ylm = ylim(axh); + lim = localObjbounds(get(lh,'Parent')); + lim = lim(3:4); %y values only + ylm(isinf(ylm)) = lim(isinf(ylm)); + + + xl = get(lh,'XData'); + yl = get(lh,'YData'); + + + %Get nearest value + [xv1,yv1]=local_nearest(x(1),xl,yl); + [xv2,yv2]=local_nearest(x(2),xl,yl); + + datalabelformatfcnh = getappdata(th1,'FormatFcnH'); + + % textstring1 = {['x=' num2str(xv1)];['y=' num2str(yv1)]}; + % textstring2 = {['x=' num2str(xv2)];['y=' num2str(yv2)]}; + textstring1 = feval(datalabelformatfcnh,xv1,yv1); + textstring2 = feval(datalabelformatfcnh,xv2,yv2); + set(th1,'Position', [xv1 yv1 0] + [offset1 0],'String',textstring1) + set(th2,'Position', [xv2 yv2 0] + [offset2 0],'String',textstring2) + set(cursors(cn1),'XData',[xv1 xv1 xv1],'YData',[ylm(1) yv1 ylm(2)]); + set(cursors(cn2),'XData',[xv2 xv2 xv2],'YData',[ylm(1) yv2 ylm(2)]); + %Update delta calculation + deltah = getappdata(axh,'Delta_Handle'); %Handle to delta calculation + + % %Positions of two dualcursors + xy1 = getappdata(cursors(1),'Coordinates'); + xy2 = getappdata(cursors(2),'Coordinates'); + + %Calculate Difference + dx = xv2 - xv1; + dy = yv2 - yv1; + + set(deltah(1),'String',['{x}_{2}-{x}_{1} ' num2str(dx,'%+.2f')]); + set(deltah(2),'String',['{y}_{2}-{y}_{1} ' num2str(dy,'%+.2f')]); + + case 'exportws' %Export selected region to workspace + [xd,yd] = local_extractregion(axh); + + %If there's only one line, don't make the user hassle with cell arrays + if length(xd)==1 + xd = xd{1}; + yd = yd{1}; + end; + + cursors.xd = xd; + cursors.yd = yd; + + assignin('base','cursors',cursors); + disp('Variable: cursors created in workspace'); + + case 'exportfig' %Export selected region to a new figure + % [xd,yd,proplist,props] = local_extractregion; + [xd,yd,hgS] = local_extractregion(axh); + + %Create new plot + fh = figure; + ax = axes; + struct2handle(hgS,ax); + + %Get labels from axes, too + %Clunky, but it seems to work + %First, create empty title, xlabel, ylabel + newhandles(1) = title(''); + newhandles(2) = xlabel(''); + newhandles(3) = ylabel(''); + + %Get strings from original plot + props = {'Title','xlabel','ylabel'}; + vals = get(axh,props); + handles = [vals{:}]; + str = get(handles,'String'); + + %Set the new strings to match + set(newhandles,{'String'},str) + + case 'exportcursor' + % Get cursor coordinates + cursordata = dualcursor(axh); + + % Push the data into the base workspace. + assignin('base','cursordata',cursordata); + disp('Variable: cursordata created in workspace'); + + case 'off' % Unset the WindowButton...Fcns + % set(get(axh,'Parent'),'WindowButtonDownFcn','','WindowButtonUpFcn','') + set(hFig,'WindowButtonDownFcn','','WindowButtonUpFcn','') + + h1 = findobj(axh,'Tag','CursorText'); %All text + h2 = findobj(axh,'Tag','Cursor'); %The cursors + h3 = findobj(axh,'Tag','CursorDeltaText'); %The cursors + + lineh = local_findlines(axh); + set(lineh,'ButtonDownFcn',''); + + % erasemode = getappdata(axh,'OriginalEraseMode'); + % if isempty(erasemode), erasemode = 'normal'; end; %handles first time + % set(local_findlines(axh),'EraseMode',erasemode); + + delete([h1;h2;h3]); + +end %switch/case on action +end + +% function hFig = figHandle(axh) +% % Get the handle to the parent figure +% hFig = ancestor(axh,'figure'); +% end + +function [xv,yv]=local_nearest(x,xl,yl) +%Inputs: +% x Selected x value +% xl Line Data (x) + +%Find nearest value of [xl] to (x) +%Special Case: Line has a single non-singleton value +if sum(isfinite(xl))==1 + fin = find(isfinite(xl)); + xv = xl(fin); + yv = yl(fin); +else + %Normalize axes + xlmin = min(xl); + xlmax = max(xl); + xln = (xl - xlmin)./(xlmax - xlmin); + xn = (x - xlmin)./(xlmax - xlmin); + + + %Find nearest x value only. + c = abs(xln - xn); + + [junk,ind] = min(c); + + %Nearest value on the line + xv = xl(ind); + yv = yl(ind); +end; +end + +function textstring = local_maketextstring(xv,yv) +textstring = {['x = ' num2str(xv,'%2g')]; + ['y = ' num2str(yv,'%2.2g')]}; +end + +function [xd,yd,hgS] = local_extractregion(axh) +val = dualcursor(axh); + +%Find all lines +lineh = local_findlines(axh); + +Nl = length(lineh); + +%Get all line properties, so we can reproduce the appearance +hgS = handle2struct(lineh); %Get properties + +xd = get(lineh,'XData'); +yd = get(lineh,'YData'); + +%Figure out the index into these lines that val corresponds to +x1ind = zeros(Nl,1); +x2ind = zeros(Nl,1); + +%Special handling for single line case +if Nl==1 + xd= {xd}; + yd = {yd}; +end; + +for ii = 1:Nl + x1ind(ii) = max(find(xd{ii}<=val(1))); + x2ind(ii) = max(find(xd{ii}<=val(3))); + + %Keep data from this region only + xd{ii} = xd{ii}(x1ind(ii):x2ind(ii)); + yd{ii} = yd{ii}(x1ind(ii):x2ind(ii)); + + %Update handle structure, to make plotting really easy + hgS(ii).properties.XData = xd{ii}; + hgS(ii).properties.YData = yd{ii}; + +end; +end + +function lineh = local_findlines(axh); +lineh = findobj(axh,'Type','line'); %Find a line to add cursor to +dots = findobj(axh,'Type','line','Tag','Cursor'); %Ignore existing cursors +lineh = setdiff(lineh,dots); + +%Ignore lines with only one or two values - these are probably annotations of some +%sort +xdtemp = get(lineh,'XData'); +linehtemp = lineh; +lineh=[]; +if ~iscell(xdtemp) %If there's only one line, force data into a cell array + xdtemp = {xdtemp}; +end; + +for ii=1:length(xdtemp); + if length(xdtemp{ii})>2 + lineh = [lineh; linehtemp(ii)]; + end; +end; +end + +function lim = localObjbounds(axh); +% Get x limits of all data in axes axh +kids = get(axh,'Children'); +xmin = Inf; xmax = -Inf; +ymin = Inf; ymax = -Inf; +for ii=1:length(kids) + try % Pass through if can't get data. hopefully we hit at least one + xd = get(kids(ii),'XData'); + xmin = min([xmin min(xd(:))]); + xmax = max([xmax max(xd(:))]); + + yd = get(kids(ii),'YData'); + ymin = min([ymin min(yd(:))]); + ymax = max([ymax max(yd(:))]); + end +end +% Nuclear option, in case things went really bad +xmin(xmin==Inf) = 0; xmax(xmax==-Inf) = 1; +ymin(ymin==Inf) = 0; ymax(ymax==-Inf) = 1; + +lim = [xmin xmax ymin ymax]; +end diff --git a/3rdparty/findjobj.m b/3rdparty/findjobj.m new file mode 100644 index 0000000..324940f --- /dev/null +++ b/3rdparty/findjobj.m @@ -0,0 +1,2793 @@ +function [handles,levels,parentIdx,listing] = findjobj(container,varargin) +%findjobj Find java objects contained within a specified java container or Matlab GUI handle +% +% Syntax: +% [handles, levels, parentIds, listing] = findjobj(container, 'PropName',PropValue(s), ...) +% +% Input parameters: +% container - optional handle to java container uipanel or figure. If unsupplied then current figure will be used +% 'PropName',PropValue - optional list of property pairs (case insensitive). PropName may also be named -PropName +% 'position' - filter results based on those elements that contain the specified X,Y position or a java element +% Note: specify a Matlab position (X,Y = pixels from bottom left corner), not a java one +% 'size' - filter results based on those elements that have the specified W,H (in pixels) +% 'class' - filter results based on those elements that contain the substring (or java class) PropValue +% Note1: filtering is case insensitive and relies on regexp, so you can pass wildcards etc. +% Note2: '-class' is an undocumented findobj PropName, but only works on Matlab (not java) classes +% 'property' - filter results based on those elements that possess the specified case-insensitive property string +% Note1: passing a property value is possible if the argument following 'property' is a cell in the +% format of {'propName','propValue'}. Example: FINDJOBJ(...,'property',{'Text','click me'}) +% Note2: partial property names (e.g. 'Tex') are accepted, as long as they're not ambiguous +% 'depth' - filter results based on specified depth. 0=top-level, Inf=all levels (default=Inf) +% 'flat' - same as specifying: 'depth',0 +% 'not' - negates the following filter: 'not','class','c' returns all elements EXCEPT those with class 'c' +% 'persist' - persist figure components information, allowing much faster results for subsequent invocations +% 'print' - display all java elements in a hierarchical list, indented appropriately +% Note1: optional PropValue of element index or handle to java container +% Note2: normally this option would be placed last, after all filtering is complete. Placing this +% option before some filters enables debug print-outs of interim filtering results. +% Note3: output is to the Matlab command window unless the 'listing' (4th) output arg is requested +% 'list' - same as 'print' +% 'nomenu' - skip menu processing, for "lean" list of handles & much faster processing; +% This option is the default for HG containers but not for figure, Java or no container +% 'debug' - list found component positions in the Command Window +% +% Output parameters: +% handles - list of handles to java elements +% levels - list of corresponding hierarchy level of the java elements (top=0) +% parentIds - list of indexes (in unfiltered handles) of the parent container of the corresponding java element +% listing - results of 'print'/'list' options (empty if these options were not specified) +% +% Note: If no output parameter is specified, then an interactive window will be displayed with a +% ^^^^ tree view of all container components, their properties and callbacks. +% +% Examples: +% findjobj; % display list of all javaelements of currrent figure in an interactive GUI +% handles = findjobj; % get list of all java elements of current figure (inc. menus, toolbars etc.) +% findjobj('print'); % list all java elements in current figure +% findjobj('print',6); % list all java elements in current figure, contained within its 6th element +% handles = findjobj(hButton); % hButton is a matlab button +% handles = findjobj(gcf,'position',getpixelposition(hButton,1)); % same as above but also return hButton's panel +% handles = findjobj(hButton,'persist'); % same as above, persist info for future reuse +% handles = findjobj('class','pushbutton'); % get all pushbuttons in current figure +% handles = findjobj('class','pushbutton','position',123,456); % get all pushbuttons at the specified position +% handles = findjobj(gcf,'class','pushbutton','size',23,15); % get all pushbuttons with the specified size +% handles = findjobj('property','Text','not','class','button'); % get all non-button elements with 'text' property +% handles = findjobj('-property',{'Text','click me'}); % get all elements with 'text' property = 'click me' +% +% Sample usage: +% hButton = uicontrol('string','click me'); +% jButton = findjobj(hButton,'nomenu'); +% % or: jButton = findjobj('property',{'Text','click me'}); +% jButton.setFlyOverAppearance(1); +% jButton.setCursor(java.awt.Cursor.getPredefinedCursor(java.awt.Cursor.HAND_CURSOR)); +% set(jButton,'FocusGainedCallback',@myMatlabFunction); % some 30 callback points available... +% jButton.get; % list all changeable properties... +% +% hEditbox = uicontrol('style',edit'); +% jEditbox = findjobj(hEditbox,'nomenu'); +% jEditbox.setCaretColor(java.awt.Color.red); +% jEditbox.KeyTypedCallback = @myCallbackFunc; % many more callbacks where this came from... +% jEdit.requestFocus; +% +% Known issues/limitations: +% - Cannot currently process multiple container objects - just one at a time +% - Initial processing is a bit slow when the figure is laden with many UI components (so better use 'persist') +% - Passing a simple container Matlab handle is currently filtered by its position+size: should find a better way to do this +% - Matlab uipanels are not implemented as simple java panels, and so they can't be found using this utility +% - Labels have a write-only text property in java, so they can't be found using the 'property',{'Text','string'} notation +% +% Warning: +% This code heavily relies on undocumented and unsupported Matlab functionality. +% It works on Matlab 7+, but use at your own risk! +% +% Bugs and suggestions: +% Please send to Yair Altman (altmany at gmail dot com) +% +% Change log: +% 2009-10-27: Fixed auto-collapse of invisible container nodes; added dynamic tree tooltips & context-menu; minor fix to version-check display +% 2009-09-30: Fix for Matlab 7.0 as suggested by Oliver W; minor GUI fix (classname font) +% 2009-08-07: Fixed edge-case of missing JIDE tables +% 2009-05-24: Added support for future Matlab versions that will not support JavaFrame +% 2009-05-15: Added sanity checks for axes items +% 2009-04-28: Added 'debug' input arg; increased size tolerance 1px => 2px +% 2009-04-23: Fixed location of popupmenus (always 20px high despite what's reported by Matlab...); fixed uiinspect processing issues; added blog link; narrower action buttons +% 2009-04-09: Automatic 'nomenu' for uicontrol inputs; significant performance improvement +% 2009-03-31: Fixed position of some Java components; fixed properties tooltip; fixed node visibility indication +% 2009-02-26: Indicated components visibility (& auto-collapse non-visible containers); auto-highlight selected component; fixes in node icons, figure title & tree refresh; improved error handling; display FindJObj version update description if available +% 2009-02-24: Fixed update check; added dedicated labels icon +% 2009-02-18: Fixed compatibility with old Matlab versions +% 2009-02-08: Callbacks table fixes; use uiinspect if available; fix update check according to new FEX website +% 2008-12-17: R2008b compatibility +% 2008-09-10: Fixed minor bug as per Johnny Smith +% 2007-11-14: Fixed edge case problem with class properties tooltip; used existing object icon if available; added checkbox option to hide standard callbacks +% 2007-08-15: Fixed object naming relative property priorities; added sanity check for illegal container arg; enabled desktop (0) container; cleaned up warnings about special class objects +% 2007-08-03: Fixed minor tagging problems with a few Java sub-classes; displayed UIClassID if text/name/tag is unavailable +% 2007-06-15: Fixed problems finding HG components found by J. Wagberg +% 2007-05-22: Added 'nomenu' option for improved performance; fixed 'export handles' bug; fixed handle-finding/display bugs; "cleaner" error handling +% 2007-04-23: HTMLized classname tooltip; returned top-level figure Frame handle for figure container; fixed callbacks table; auto-checked newer version; fixed Matlab 7.2 compatibility issue; added HG objects tree +% 2007-04-19: Fixed edge case of missing figure; displayed tree hierarchy in interactive GUI if no output args; workaround for figure sub-menus invisible unless clicked +% 2007-04-04: Improved performance; returned full listing results in 4th output arg; enabled partial property names & property values; automatically filtered out container panels if children also returned; fixed finding sub-menu items +% 2007-03-20: First version posted on the MathWorks file exchange: http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=14317 +% +% See also: +% java, handle, findobj, findall, javaGetHandles, uiinspect (on the File Exchange) + +% License to use and modify this code is granted freely to all interested, as long as the original author is +% referenced and attributed as such. The original author maintains the right to be solely associated with this work. + +% Programmed and Copyright by Yair M. Altman: altmany(at)gmail.com +% $Revision: 1.23 $ $Date: 2009/10/27 21:07:32 $ + + % Ensure Java AWT is enabled + error(javachk('awt')); + + persistent pContainer pHandles pLevels pParentIdx pPositions + + try + % Initialize + handles = handle([]); + levels = []; + parentIdx = []; + positions = []; % Java positions start at the top-left corner + %sizes = []; + listing = ''; + hg_levels = []; + hg_handles = handle([]); % HG handles are double + hg_parentIdx = []; + nomenu = false; + menuBarFoundFlag = false; + + % Default container is the current figure's root panel + if nargin + if isempty(container) % empty container - bail out + return; + elseif ischar(container) % container skipped - this is part of the args list... + varargin = {container, varargin{:}}; + origContainer = getCurrentFigure; + [container,contentSize] = getRootPanel(origContainer); + elseif isequal(container,0) % root + origContainer = handle(container); + container = com.mathworks.mde.desk.MLDesktop.getInstance.getMainFrame; + contentSize = [container.getWidth, container.getHeight]; + elseif ishghandle(container) % && ~isa(container,'java.awt.Container') + container = container(1); % another current limitation... + hFig = ancestor(container,'figure'); + origContainer = handle(container); + if isa(origContainer,'uimenu') + % getpixelposition doesn't work for menus... - damn! + varargin = {'class','MenuPeer', 'property',{'Label',strrep(get(container,'Label'),'&','')}, varargin{:}}; + elseif ~isa(origContainer, 'figure') && ~isempty(hFig) + % See limitations section above: should find a better way to directly refer to the element's java container + try + % Note: 'PixelBounds' is undocumented and unsupported, but much faster than getpixelposition! + % ^^^^ unfortunately, its Y position is inaccurate in some cases - damn! + %size = get(container,'PixelBounds'); + pos = fix(getpixelposition(container,1)); + %varargin = {'position',pos(1:2), 'size',pos(3:4), 'not','class','java.awt.Panel', varargin{:}}; + catch + try + figName = get(hFig,'name'); + if strcmpi(get(hFig,'number'),'on') + figName = regexprep(['Figure ' num2str(hFig) ': ' figName],': $',''); + end + mde = com.mathworks.mde.desk.MLDesktop.getInstance; + jFig = mde.getClient(figName); + if isempty(jFig), error('dummy'); end + catch + warning('off','MATLAB:HandleGraphics:ObsoletedProperty:JavaFrame'); % R2008b compatibility + jFig = get(get(hFig,'JavaFrame'),'FigurePanelContainer'); + end + pos = []; + try + pxsize = get(container,'PixelBounds'); + pos = [pxsize(1)+5, jFig.getHeight - (pxsize(4)-5)]; + catch + % never mind... + end + end + if size(pos,2) == 2 + pos(:,3:4) = 0; + end + if ~isempty(pos) + if isa(handle(container),'uicontrol') && strcmp(get(container,'style'),'popupmenu') + % popupmenus (combo-box dropdowns) are always 20px high + pos(2) = pos(2) + pos(4) - 20; + pos(4) = 20; + end + %varargin = {'position',pos(1:2), 'size',size(3:4)-size(1:2)-10, 'not','class','java.awt.Panel', varargin{:}}; + varargin = {'position',pos(1:2)+[0,pos(4)], 'size',pos(3:4), 'not','class','java.awt.Panel', 'nomenu', varargin{:}}; + end + elseif isempty(hFig) + hFig = handle(container); + end + [container,contentSize] = getRootPanel(hFig); + elseif isjava(container) + % Maybe a java container obj (will crash otherwise) + origContainer = container; + contentSize = [container.getWidth, container.getHeight]; + else + error('YMA:findjobj:IllegalContainer','Input arg does not appear to be a valid GUI object'); + end + else + % Default container = current figure + origContainer = getCurrentFigure; + [container,contentSize] = getRootPanel(origContainer); + end + + % Check persistency + if isequal(pContainer,container) + % persistency requested and the same container is reused, so reuse the hierarchy information + [handles,levels,parentIdx,positions] = deal(pHandles, pLevels, pParentIdx, pPositions); + else + % Pre-allocate space of complex data containers for improved performance + handles = repmat(handles,1,1000); + positions = zeros(1000,2); + + % Check whether to skip menu processing + nomenu = paramSupplied(varargin,'nomenu'); + + % Traverse the container hierarchy and extract the elements within + traverseContainer(container,0,1); + + % Remove unnecessary pre-allocated elements + dataLen = length(levels); + handles (dataLen+1:end) = []; + positions(dataLen+1:end,:) = []; + end + + % Process persistency check before any filtering is done + if paramSupplied(varargin,'persist') + [pContainer, pHandles, pLevels, pParentIdx, pPositions] = deal(container,handles,levels,parentIdx,positions); + end + + % Save data for possible future use in presentObjectTree() below + allHandles = handles; + allLevels = levels; + allParents = parentIdx; + selectedIdx = 1:length(handles); + %[positions(:,1)-container.getX, container.getHeight - positions(:,2)] + + % Debug-list all found compponents and their positions + if paramSupplied(varargin,'debug') + for handleIdx = 1 : length(allHandles) + pos = sprintf('%d,%d %dx%d',[positions(handleIdx,:) getXY(handles(handleIdx))]); + disp([repmat(' ',1,levels(handleIdx)) '[' pos(1:end-1) '] ' char(toString(handles(handleIdx)))]); + end + end + + % Process optional args + % Note: positions is NOT returned since it's based on java coord system (origin = top-left): will confuse Matlab users + processArgs(varargin{:}); %#ok + + % De-cell and trim listing, if only one element was found (no use for indented listing in this case) + if iscell(listing) && length(listing)==1 + listing = strtrim(listing{1}); + end + + % If no output args and no listing requested, present the FINDJOBJ interactive GUI + if nargout == 0 && isempty(listing) + presentObjectTree(); + + % Display the listing, if this was specifically requested yet no relevant output arg was specified + elseif nargout < 4 && ~isempty(listing) + if ~iscell(listing) + disp(listing); + else + for listingIdx = 1 : length(listing) + disp(listing{listingIdx}); + end + end + end + + return; %debug point + + catch + % 'Cleaner' error handling - strip the stack info etc. + err = lasterror; + err.message = regexprep(err.message,'Error using ==> [^\n]+\n',''); + if isempty(findstr(mfilename,err.message)) + % Indicate error origin, if not already stated within the error message + err.message = [mfilename ': ' err.message]; + end + rethrow(err); + end + + + %% Check existence of a (case-insensitive) optional parameter in the params list + function [flag,idx] = paramSupplied(paramsList,paramName) + %idx = find(~cellfun('isempty',regexpi(paramsList(cellfun(@ischar,paramsList)),['^-?' paramName]))); + idx = find(~cellfun('isempty',regexpi(paramsList(cellfun('isclass',paramsList,'char')),['^-?' paramName]))); % 30/9/2009 fix for ML 7.0 suggested by Oliver W + flag = any(idx); + end + + %% Get current figure (even if its 'HandleVisibility' property is 'off') + function curFig = getCurrentFigure + oldShowHidden = get(0,'ShowHiddenHandles'); + set(0,'ShowHiddenHandles','on'); % minor fix per Johnny Smith + curFig = gcf; + set(0,'ShowHiddenHandles',oldShowHidden); + end + + %% Get Java reference to top-level (root) panel - actually, a reference to the java figure + function [jRootPane,contentSize] = getRootPanel(hFig) + try + contentSize = [0,0]; % initialize + jRootPane = hFig; + figName = get(hFig,'name'); + if strcmpi(get(hFig,'number'),'on') + figName = regexprep(['Figure ' num2str(hFig) ': ' figName],': $',''); + end + mde = com.mathworks.mde.desk.MLDesktop.getInstance; + jFigPanel = mde.getClient(figName); + jRootPane = jFigPanel; + jRootPane = jFigPanel.getRootPane; + catch + try + jFrame = get(hFig,'JavaFrame'); + jFigPanel = get(jFrame,'FigurePanelContainer'); + jRootPane = jFigPanel; + jRootPane = jFigPanel.getComponent(0).getRootPane; + catch + % Never mind + end + end + try + % If invalid RootPane, retry up to N times + tries = 10; + while isempty(jRootPane) && tries>0 % might happen if figure is still undergoing rendering... + drawnow; pause(0.001); + tries = tries - 1; + jRootPane = jFigPanel.getComponent(0).getRootPane; + end + + % If still invalid, use FigurePanelContainer which is good enough in 99% of cases... (menu/tool bars won't be accessible, though) + if isempty(jRootPane) + jRootPane = jFigPanel; + end + contentSize = [jRootPane.getWidth, jRootPane.getHeight]; + + % Try to get the ancestor FigureFrame + jRootPane = jRootPane.getTopLevelAncestor; + catch + % Never mind - FigurePanelContainer is good enough in 99% of cases... (menu/tool bars won't be accessible, though) + end + end + + %% Traverse the container hierarchy and extract the elements within + function traverseContainer(jcontainer,level,parent) + persistent figureComponentFound menuRootFound + + % Record the data for this node + %disp([repmat(' ',1,level) '<= ' char(jcontainer.toString)]) + thisIdx = length(levels) + 1; + levels(thisIdx) = level; + parentIdx(thisIdx) = parent; + handles(thisIdx) = handle(jcontainer,'callbackproperties'); + try + positions(thisIdx,:) = getXY(jcontainer); + %sizes(thisIdx,:) = [jcontainer.getWidth, jcontainer.getHeight]; + catch + positions(thisIdx,:) = [0,0]; + %sizes(thisIdx,:) = [0,0]; + end + if level>0 + positions(thisIdx,:) = positions(thisIdx,:) + positions(parent,:); + if ~figureComponentFound && ... + strcmp(jcontainer.getName,'fComponentContainer') && ... + isa(jcontainer,'com.mathworks.hg.peer.FigureComponentContainer') % there are 2 FigureComponentContainers - only process one... + + % restart coordinate system, to exclude menu & toolbar areas + positions(thisIdx,:) = positions(thisIdx,:) - [jcontainer.getRootPane.getX, jcontainer.getRootPane.getY]; + figureComponentFound = true; + end + elseif level==1 + positions(thisIdx,:) = positions(thisIdx,:) + positions(parent,:); + else + % level 0 - initialize flags used later + figureComponentFound = false; + menuRootFound = false; + end + parentId = length(parentIdx); + + % Traverse Menu items, unless the 'nomenu' option was requested + if ~nomenu + try + for child = 1 : getNumMenuComponents(jcontainer) + traverseContainer(jcontainer.getMenuComponent(child-1),level+1,parentId); + end + catch + % Probably not a Menu container, but maybe a top-level JMenu, so discard duplicates + %if isa(handles(end).java,'javax.swing.JMenuBar') + if ~menuRootFound && strcmp(handles(end).java.class,'javax.swing.JMenuBar') %faster... + if removeDuplicateNode(thisIdx) + menuRootFound = true; + return; + end + end + end + end + + % Now recursively process all this node's children (if any), except menu items if so requested + %if isa(jcontainer,'java.awt.Container') + try % try-catch is faster than checking isa(jcontainer,'java.awt.Container')... + %if jcontainer.getComponentCount, jcontainer.getComponents, end + if ~nomenu || menuBarFoundFlag || isempty(strfind(jcontainer.class,'FigureMenuBar')) + lastChildComponent = java.lang.Object; + child = 0; + while (child < jcontainer.getComponentCount) + childComponent = jcontainer.getComponent(child); + % Looping over menus sometimes causes jcontainer to get mixed up (probably a JITC bug), so identify & fix + if isequal(childComponent,lastChildComponent) + child = child + 1; + childComponent = jcontainer.getComponent(child); + end + lastChildComponent = childComponent; + %disp([repmat(' ',1,level) '=> ' num2str(child) ': ' char(childComponent.class)]) + traverseContainer(childComponent,level+1,parentId); + child = child + 1; + end + else + menuBarFoundFlag = true; % use this flag to skip further testing for FigureMenuBar + end + catch + % do nothing - probably not a container + %dispError + end + + % ...and yet another type of child traversal... + try + for child = 1 : jcontainer.java.getChildCount + traverseContainer(jcontainer.java.getChildAt(child-1),level+1,parentId); + end + catch + % do nothing - probably not a container + %dispError + end + + % TODO: Add axis (plot) component handles + end + + %% Get the XY location of a Java component + function xy = getXY(jcontainer) + % Note: getX/getY are better than get(..,'X') (mem leaks), + % ^^^^ but sometimes they fail and revert to getx.m ... + % Note2: try awtinvoke() catch is faster than checking ismethod()... + % Note3: using AWTUtilities.invokeAndWait() directly is even faster than awtinvoke()... + try %if ismethod(jcontainer,'getX') + %positions(thisIdx,:) = [jcontainer.getX, jcontainer.getY]; + cls = getClass(jcontainer); + location = com.mathworks.jmi.AWTUtilities.invokeAndWait(jcontainer,getMethod(cls,'getLocation',[]),[]); + x = location.getX; + y = location.getY; + catch %else + try + x = com.mathworks.jmi.AWTUtilities.invokeAndWait(jcontainer,getMethod(cls,'getX',[]),[]); + y = com.mathworks.jmi.AWTUtilities.invokeAndWait(jcontainer,getMethod(cls,'getY',[]),[]); + catch + try + x = awtinvoke(jcontainer,'getX()'); + y = awtinvoke(jcontainer,'getY()'); + catch + x = get(jcontainer,'X'); + y = get(jcontainer,'Y'); + end + end + end + %positions(thisIdx,:) = [x, y]; + xy = [x,y]; + end + + %% Get the number of menu sub-elements + function numMenuComponents = getNumMenuComponents(jcontainer) + + % The following line will raise an Exception for anything except menus + numMenuComponents = jcontainer.getMenuComponentCount; + + % No error so far, so this must be a menu container... + % Note: Menu subitems are not visible until the top-level (root) menu gets initial focus... + % Try several alternatives, until we get a non-empty menu (or not...) + % TODO: Improve performance - this takes WAY too long... + if jcontainer.isTopLevelMenu && (numMenuComponents==0) + jcontainer.requestFocus; + numMenuComponents = jcontainer.getMenuComponentCount; + if (numMenuComponents == 0) + drawnow; pause(0.001); + numMenuComponents = jcontainer.getMenuComponentCount; + if (numMenuComponents == 0) + jcontainer.setSelected(true); + numMenuComponents = jcontainer.getMenuComponentCount; + if (numMenuComponents == 0) + drawnow; pause(0.001); + numMenuComponents = jcontainer.getMenuComponentCount; + if (numMenuComponents == 0) + jcontainer.doClick; % needed in order to populate the sub-menu components + numMenuComponents = jcontainer.getMenuComponentCount; + if (numMenuComponents == 0) + drawnow; %pause(0.001); + numMenuComponents = jcontainer.getMenuComponentCount; + jcontainer.doClick; % close menu by re-clicking... + if (numMenuComponents == 0) + drawnow; %pause(0.001); + numMenuComponents = jcontainer.getMenuComponentCount; + end + else + % ok - found sub-items + % Note: no need to close menu since this will be done when focus moves to the FindJObj window + %jcontainer.doClick; % close menu by re-clicking... + end + end + end + jcontainer.setSelected(false); % de-select the menu + end + end + end + end + + %% Remove a specific tree node's data + function nodeRemovedFlag = removeDuplicateNode(thisIdx) + nodeRemovedFlag = false; + for idx = 1 : thisIdx-1 + if isequal(handles(idx),handles(thisIdx)) + levels(thisIdx) = []; + parentIdx(thisIdx) = []; + handles(thisIdx) = []; + positions(thisIdx,:) = []; + %sizes(thisIdx,:) = []; + nodeRemovedFlag = true; + return; + end + end + end + + %% Process optional args + function processArgs(varargin) + + % Initialize + invertFlag = false; + listing = ''; + + % Loop over all optional args + while ~isempty(varargin) && ~isempty(handles) + + % Process the arg (and all its params) + foundIdx = 1 : length(handles); + if iscell(varargin{1}), varargin{1} = varargin{1}{1}; end + if ~isempty(varargin{1}) && varargin{1}(1)=='-' + varargin{1}(1) = []; + end + switch lower(varargin{1}) + case 'not' + invertFlag = true; + case 'position' + [varargin,foundIdx] = processPositionArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case 'size' + [varargin,foundIdx] = processSizeArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case 'class' + [varargin,foundIdx] = processClassArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case 'property' + [varargin,foundIdx] = processPropertyArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case 'depth' + [varargin,foundIdx] = processDepthArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case 'flat' + varargin = {'depth',0, varargin{min(2:end):end}}; + [varargin,foundIdx] = processDepthArgs(varargin{:}); + if invertFlag, foundIdx = ~foundIdx; invertFlag = false; end + case {'print','list'} + [varargin,listing] = processPrintArgs(varargin{:}); + case {'persist','nomenu','debug'} + % ignore - already handled in main function above + otherwise + error('YMA:findjobj:IllegalOption',['Option ' num2str(varargin{1}) ' is not a valid option. Type ''help ' mfilename ''' for the full options list.']); + end + + % If only parent-child pairs found + foundIdx = find(foundIdx); + if ~isempty(foundIdx) && isequal(parentIdx(foundIdx(2:2:end)),foundIdx(1:2:end)) + % Return just the children (the parent panels are uninteresting) + foundIdx(1:2:end) = []; + end + + % Filter the results + selectedIdx = selectedIdx(foundIdx); + handles = handles(foundIdx); + levels = levels(foundIdx); + parentIdx = parentIdx(foundIdx); + positions = positions(foundIdx,:); + + % Remove this arg and proceed to the next one + varargin(1) = []; + + end % Loop over all args + end + + %% Process 'print' option + function [varargin,listing] = processPrintArgs(varargin) + if length(varargin)<2 || ischar(varargin{2}) + % No second arg given, so use the first available element + listingContainer = handles(1); %#ok - used in evalc below + else + % Get the element to print from the specified second arg + if isnumeric(varargin{2}) && (varargin{2} == fix(varargin{2})) % isinteger doesn't work on doubles... + if (varargin{2} > 0) && (varargin{2} <= length(handles)) + listingContainer = handles(varargin{2}); %#ok - used in evalc below + elseif varargin{2} > 0 + error('YMA:findjobj:IllegalPrintFilter','Print filter index %g > number of available elements (%d)',varargin{2},length(handles)); + else + error('YMA:findjobj:IllegalPrintFilter','Print filter must be a java handle or positive numeric index into handles'); + end + elseif ismethod(varargin{2},'list') + listingContainer = varargin{2}; %#ok - used in evalc below + else + error('YMA:findjobj:IllegalPrintFilter','Print filter must be a java handle or numeric index into handles'); + end + varargin(2) = []; + end + + % use evalc() to capture output into a Matlab variable + %listing = evalc('listingContainer.list'); + + % Better solution: loop over all handles and process them one by one + listing = cell(length(handles),1); + for componentIdx = 1 : length(handles) + listing{componentIdx} = [repmat(' ',1,levels(componentIdx)) char(handles(componentIdx).toString)]; + end + end + + %% Process 'position' option + function [varargin,foundIdx] = processPositionArgs(varargin) + if length(varargin)>1 + positionFilter = varargin{2}; + %if (isjava(positionFilter) || iscom(positionFilter)) && ismethod(positionFilter,'getLocation') + try % try-catch is faster... + % Java/COM object passed - get its position + positionFilter = positionFilter.getLocation; + filterXY = [positionFilter.getX, positionFilter.getY]; + catch + if ~isscalar(positionFilter) + % position vector passed + if (length(positionFilter)>=2) && isnumeric(positionFilter) + % Remember that java coordinates start at top-left corner, Matlab coords start at bottom left... + %positionFilter = java.awt.Point(positionFilter(1), container.getHeight - positionFilter(2)); + filterXY = [container.getX + positionFilter(1), container.getY + contentSize(2) - positionFilter(2)]; + + % Check for full Matlab position vector (x,y,w,h) + %if (length(positionFilter)==4) + % varargin{end+1} = 'size'; + % varargin{end+1} = fix(positionFilter(3:4)); + %end + else + error('YMA:findjobj:IllegalPositionFilter','Position filter must be a java UI component, or X,Y pair'); + end + elseif length(varargin)>2 + % x,y passed as separate arg values + if isnumeric(positionFilter) && isnumeric(varargin{3}) + % Remember that java coordinates start at top-left corner, Matlab coords start at bottom left... + %positionFilter = java.awt.Point(positionFilter, container.getHeight - varargin{3}); + filterXY = [container.getX + positionFilter, container.getY + contentSize(2) - varargin{3}]; + varargin(3) = []; + else + error('YMA:findjobj:IllegalPositionFilter','Position filter must be a java UI component, or X,Y pair'); + end + else + error('YMA:findjobj:IllegalPositionFilter','Position filter must be a java UI component, or X,Y pair'); + end + end + + % Compute the required element positions in order to be eligible for a more detailed examination + % Note: based on the following constraints: 0 <= abs(elementX-filterX) + abs(elementY+elementH-filterY) < 7 + baseDeltas = [positions(:,1)-filterXY(1), positions(:,2)-filterXY(2)]; % faster than repmat()... + %baseHeight = - baseDeltas(:,2);% -abs(baseDeltas(:,1)); + %minHeight = baseHeight - 7; + %maxHeight = baseHeight + 7; + %foundIdx = ~arrayfun(@(b)(invoke(b,'contains',positionFilter)),handles); % ARGH! - disallowed by Matlab! + %foundIdx = repmat(false,1,length(handles)); + %foundIdx(length(handles)) = false; % faster than repmat()... + foundIdx = (abs(baseDeltas(:,1)) < 7) & (abs(baseDeltas(:,2)) < 7); % & (minHeight >= 0); + %fi = find(foundIdx); + %for componentIdx = 1 : length(fi) + %foundIdx(componentIdx) = handles(componentIdx).getBounds.contains(positionFilter); + + % Search for a point no farther than 7 pixels away (prevents rounding errors) + %foundIdx(componentIdx) = handles(componentIdx).getLocationOnScreen.distanceSq(positionFilter) < 50; % fails for invisible components... + + %p = java.awt.Point(positions(componentIdx,1), positions(componentIdx,2) + handles(componentIdx).getHeight); + %foundIdx(componentIdx) = p.distanceSq(positionFilter) < 50; + + %foundIdx(componentIdx) = sum(([baseDeltas(componentIdx,1),baseDeltas(componentIdx,2)+handles(componentIdx).getHeight]).^2) < 50; + + % Following is the fastest method found to date: only eligible elements are checked in detailed + % elementHeight = handles(fi(componentIdx)).getHeight; + % foundIdx(fi(componentIdx)) = elementHeight > minHeight(fi(componentIdx)) && ... + % elementHeight < maxHeight(fi(componentIdx)); + %disp([componentIdx,elementHeight,minHeight(fi(componentIdx)),maxHeight(fi(componentIdx)),foundIdx(fi(componentIdx))]) + %end + + varargin(2) = []; + else + foundIdx = []; + end + end + + %% Process 'size' option + function [varargin,foundIdx] = processSizeArgs(varargin) + if length(varargin)>1 + sizeFilter = lower(varargin{2}); + %if (isjava(sizeFilter) || iscom(sizeFilter)) && ismethod(sizeFilter,'getSize') + try % try-catch is faster... + % Java/COM object passed - get its size + sizeFilter = sizeFilter.getSize; + filterWidth = sizeFilter.getWidth; + filterHeight = sizeFilter.getHeight; + catch + if ~isscalar(sizeFilter) + % size vector passed + if (length(sizeFilter)>=2) && isnumeric(sizeFilter) + %sizeFilter = java.awt.Dimension(sizeFilter(1),sizeFilter(2)); + filterWidth = sizeFilter(1); + filterHeight = sizeFilter(2); + else + error('YMA:findjobj:IllegalSizeFilter','Size filter must be a java UI component, or W,H pair'); + end + elseif length(varargin)>2 + % w,h passed as separate arg values + if isnumeric(sizeFilter) && isnumeric(varargin{3}) + %sizeFilter = java.awt.Dimension(sizeFilter,varargin{3}); + filterWidth = sizeFilter; + filterHeight = varargin{3}; + varargin(3) = []; + else + error('YMA:findjobj:IllegalSizeFilter','Size filter must be a java UI component, or W,H pair'); + end + else + error('YMA:findjobj:IllegalSizeFilter','Size filter must be a java UI component, or W,H pair'); + end + end + %foundIdx = ~arrayfun(@(b)(invoke(b,'contains',sizeFilter)),handles); % ARGH! - disallowed by Matlab! + foundIdx(length(handles)) = false; % faster than repmat()... + for componentIdx = 1 : length(handles) + %foundIdx(componentIdx) = handles(componentIdx).getSize.equals(sizeFilter); + % Allow a 2-pixel tollerance to account for non-integer pixel sizes + foundIdx(componentIdx) = abs(handles(componentIdx).getWidth - filterWidth) <= 2 && ... % faster than getSize.equals() + abs(handles(componentIdx).getHeight - filterHeight) <= 2; + end + varargin(2) = []; + else + foundIdx = []; + end + end + + %% Process 'class' option + function [varargin,foundIdx] = processClassArgs(varargin) + if length(varargin)>1 + classFilter = varargin{2}; + %if ismethod(classFilter,'getClass') + try % try-catch is faster... + classFilter = char(classFilter.getClass); + catch + if ~ischar(classFilter) + error('YMA:findjobj:IllegalClassFilter','Class filter must be a java object, class or string'); + end + end + + % Now convert all java classes to java.lang.Strings and compare to the requested filter string + try + foundIdx(length(handles)) = false; % faster than repmat()... + jClassFilter = java.lang.String(classFilter).toLowerCase; + for componentIdx = 1 : length(handles) + % Note: JVM 1.5's String.contains() appears slightly slower and is available only since Matlab 7.2 + foundIdx(componentIdx) = handles(componentIdx).getClass.toString.toLowerCase.indexOf(jClassFilter) >= 0; + end + catch + % Simple processing: slower since it does extra processing within opaque.char() + for componentIdx = 1 : length(handles) + % Note: using @toChar is faster but returns java String, not a Matlab char + foundIdx(componentIdx) = ~isempty(regexpi(char(handles(componentIdx).getClass),classFilter)); + end + end + + varargin(2) = []; + else + foundIdx = []; + end + end + + %% Process 'property' option + function [varargin,foundIdx] = processPropertyArgs(varargin) + if length(varargin)>1 + propertyName = varargin{2}; + if iscell(propertyName) + if length(propertyName) == 2 + propertyVal = propertyName{2}; + propertyName = propertyName{1}; + elseif length(propertyName) == 1 + propertyName = propertyName{1}; + else + error('YMA:findjobj:IllegalPropertyFilter','Property filter must be a string (case insensitive name of property) or cell array {propName,propValue}'); + end + end + if ~ischar(propertyName) + error('YMA:findjobj:IllegalPropertyFilter','Property filter must be a string (case insensitive name of property) or cell array {propName,propValue}'); + end + propertyName = lower(propertyName); + %foundIdx = arrayfun(@(h)isprop(h,propertyName),handles); % ARGH! - disallowed by Matlab! + foundIdx(length(handles)) = false; % faster than repmat()... + + % Split processing depending on whether a specific property value was requested (ugly but faster...) + if exist('propertyVal','var') + for componentIdx = 1 : length(handles) + try + % Find out whether this element has the specified property + % Note: findprop() and its return value schema.prop are undocumented and unsupported! + prop = findprop(handles(componentIdx),propertyName); % faster than isprop() & enables partial property names + + % If found, compare it to the actual element's property value + foundIdx(componentIdx) = ~isempty(prop) && isequal(get(handles(componentIdx),prop.Name),propertyVal); + catch + % Some Java classes have a write-only property (like LabelPeer with 'Text'), so we end up here + % In these cases, simply assume that the property value doesn't match and continue + foundIdx(componentIdx) = false; + end + end + else + for componentIdx = 1 : length(handles) + try + % Find out whether this element has the specified property + % Note: findprop() and its return value schema.prop are undocumented and unsupported! + foundIdx(componentIdx) = ~isempty(findprop(handles(componentIdx),propertyName)); + catch + foundIdx(componentIdx) = false; + end + end + end + varargin(2) = []; + else + foundIdx = []; + end + end + + %% Process 'depth' option + function [varargin,foundIdx] = processDepthArgs(varargin) + if length(varargin)>1 + level = varargin{2}; + if ~isnumeric(level) + error('YMA:findjobj:IllegalDepthFilter','Depth filter must be a number (=maximal element depth)'); + end + foundIdx = (levels <= level); + varargin(2) = []; + else + foundIdx = []; + end + end + + %% Convert property data into a string + function data = charizeData(data) + if isa(data,'com.mathworks.hg.types.HGCallback') + data = get(data,'Callback'); + end + if ~ischar(data) + newData = strtrim(evalc('disp(data)')); + try + newData = regexprep(newData,' +',' '); + newData = regexprep(newData,'Columns \d+ through \d+\s',''); + newData = regexprep(newData,'Column \d+\s',''); + catch + %never mind... + end + if iscell(data) + newData = ['{ ' newData ' }']; + elseif isempty(data) + newData = ''; + elseif isnumeric(data) || islogical(data) || any(ishandle(data)) || numel(data) > 1 %&& ~isscalar(data) + newData = ['[' newData ']']; + end + data = newData; + elseif ~isempty(data) + data = ['''' data '''']; + end + end % charizeData + + %% Get callbacks table data + function [cbData, cbHeaders, cbTableEnabled] = getCbsData(obj, stripStdCbsFlag) + classHdl = classhandle(handle(obj)); + cbNames = get(classHdl.Events,'Name'); + if ~isempty(cbNames) && ~iscom(obj) %only java-based please... + cbNames = strcat(cbNames,'Callback'); + end + propNames = get(classHdl.Properties,'Name'); + propCbIdx = []; + if ~isempty(propNames) + propCbIdx = find(~cellfun(@isempty,regexp(propNames,'(Fcn|Callback)$'))); + cbNames = unique([cbNames; propNames(propCbIdx)]); %#ok logical is faster but less debuggable... + end + if ~isempty(cbNames) + if stripStdCbsFlag + cbNames = stripStdCbs(cbNames); + end + if iscell(cbNames) + cbNames = sort(cbNames); + end + hgHandleFlag = 0; try hgHandleFlag = ishghandle(obj); catch, end %#ok + try + obj = handle(obj,'CallbackProperties'); + catch + hgHandleFlag = 1; + end + if hgHandleFlag + % HG handles don't allow CallbackProperties - search only for *Fcn + cbNames = propNames(propCbIdx); + end + if iscom(obj) + cbs = obj.eventlisteners; + if ~isempty(cbs) + cbNamesRegistered = cbs(:,1); + cbData = setdiff(cbNames,cbNamesRegistered); + %cbData = charizeData(cbData); + if size(cbData,2) > size(cbData(1)) + cbData = cbData'; + end + cbData = [cbData, cellstr(repmat(' ',length(cbData),1))]; + cbData = [cbData; cbs]; + [sortedNames, sortedIdx] = sort(cbData(:,1)); + sortedCbs = cellfun(@charizeData,cbData(sortedIdx,2),'un',0); + cbData = [sortedNames, sortedCbs]; + else + cbData = [cbNames, cellstr(repmat(' ',length(cbNames),1))]; + end + elseif iscell(cbNames) + cbNames = sort(cbNames); + %cbData = [cbNames, get(obj,cbNames)']; + cbData = cbNames; + for idx = 1 : length(cbNames) + try + cbData{idx,2} = charizeData(get(obj,cbNames{idx})); + catch + cbData{idx,2} = '(callback value inaccessible)'; + end + end + else % only one event callback + %cbData = {cbNames, get(obj,cbNames)'}; + %cbData{1,2} = charizeData(cbData{1,2}); + try + cbData = {cbNames, charizeData(get(obj,cbNames))}; + catch + cbData = {cbNames, '(callback value inaccessible)'}; + end + end + cbHeaders = {'Callback name','Callback value'}; + cbTableEnabled = true; + else + cbData = {'(no callbacks)'}; + cbHeaders = {'Callback name'}; + cbTableEnabled = false; + end + end % getCbsData + + %% Get relative (0.0-1.0) divider location + function divLocation = getRalativeDivlocation(jDiv) + divLocation = jDiv.getDividerLocation; + if divLocation > 1 % i.e. [pixels] + visibleRect = jDiv.getVisibleRect; + if jDiv.getOrientation == 0 % vertical + start = visibleRect.getY; + extent = visibleRect.getHeight - start; + else + start = visibleRect.getX; + extent = visibleRect.getWidth - start; + end + divLocation = (divLocation - start) / extent; + end + end % getRalativeDivlocation + + %% Try to set a treenode icon based on a container's icon + function setTreeNodeIcon(treenode,container) + try + iconImage = []; + iconImage = container.getIcon; + if ~isempty(findprop(handle(iconImage),'Image')) % get(iconImage,'Image') is easier but leaks memory... + iconImage = iconImage.getImage; + else + a=b; %#ok cause an error + end + catch + try + iconImage = container.getIconImage; + catch + try + if ~isempty(iconImage) + ge = java.awt.GraphicsEnvironment.getLocalGraphicsEnvironment; + gd = ge.getDefaultScreenDevice; + gc = gd.getDefaultConfiguration; + image = gc.createCompatibleImage(iconImage.getIconWidth, iconImage.getIconHeight); % a BufferedImage object + g = image.createGraphics; + iconImage.paintIcon([], g, 0, 0); + g.dispose; + iconImage = image; + end + catch + % never mind... + end + end + end + if ~isempty(iconImage) + iconImage = setIconSize(iconImage); + treenode.setIcon(iconImage); + end + end % setTreeNodeIcon + + %% Present the object hierarchy tree + function presentObjectTree() + import java.awt.* + import javax.swing.* + hTreeFig = findall(0,'tag','findjobjFig'); + iconpath = [matlabroot, '/toolbox/matlab/icons/']; + cbHideStd = 0; % Initial state of the cbHideStdCbs checkbox + if isempty(hTreeFig) + % Prepare the figure + hTreeFig = figure('tag','findjobjFig','menuBar','none','toolBar','none','Name','FindJObj','NumberTitle','off','handleVisibility','off','IntegerHandle','off'); + figIcon = ImageIcon([iconpath 'tool_legend.gif']); + drawnow; + try + mde = com.mathworks.mde.desk.MLDesktop.getInstance; + jTreeFig = mde.getClient('FindJObj').getTopLevelAncestor; + jTreeFig.setIcon(figIcon); + catch + jTreeFig = get(hTreeFig,'JavaFrame'); + jTreeFig.setFigureIcon(figIcon); + end + vsplitPaneLocation = 0.8; + hsplitPaneLocation = 0.5; + else + % Remember cbHideStdCbs checkbox & dividers state for later + userdata = get(hTreeFig, 'userdata'); + try cbHideStd = userdata.cbHideStdCbs.isSelected; catch, end %#ok + vsplitPaneLocation = getRalativeDivlocation(userdata.vsplitPane); + hsplitPaneLocation = getRalativeDivlocation(userdata.hsplitPane); + + % Clear the figure and redraw + clf(hTreeFig); + figure(hTreeFig); % bring to front + end + + % Traverse all HG children, if root container was a HG handle + if ishghandle(origContainer) %&& ~isequal(origContainer,container) + traverseHGContainer(origContainer,0,0); + end + + % Prepare the tree pane + warning('off','MATLAB:uitreenode:MigratingFunction'); % R2008b compatibility + tree_h = com.mathworks.hg.peer.UITreePeer; + hasChildren = sum(allParents==1) > 1; + icon = [iconpath 'upfolder.gif']; + [rootName, rootTitle] = getNodeName(container); + try + root = uitreenode('v0', handle(container), rootName, icon, ~hasChildren); + catch % old matlab version don't have the 'v0' option + root = uitreenode(handle(container), rootName, icon, ~hasChildren); + end + setTreeNodeIcon(root,container); % constructor must accept a char icon unfortunately, so need to do this afterwards... + if ~isempty(rootTitle) + set(hTreeFig, 'Name',['FindJObj - ' char(rootTitle)]); + end + nodedata.idx = 1; + nodedata.obj = container; + set(root,'userdata',nodedata); + root.setUserObject(container); + setappdata(root,'childHandle',container); + tree_h.setRoot(root); + treePane = tree_h.getScrollPane; + treePane.setMinimumSize(Dimension(50,50)); + jTreeObj = treePane.getViewport.getComponent(0); + jTreeObj.setShowsRootHandles(true) + jTreeObj.getSelectionModel.setSelectionMode(javax.swing.tree.TreeSelectionModel.DISCONTIGUOUS_TREE_SELECTION); + %jTreeObj.setVisible(0); + %jTreeObj.getCellRenderer.setLeafIcon([]); + %jTreeObj.getCellRenderer.setOpenIcon(figIcon); + %jTreeObj.getCellRenderer.setClosedIcon([]); + treePanel = JPanel(BorderLayout); + treePanel.add(treePane, BorderLayout.CENTER); + progressBar = JProgressBar(0); + progressBar.setMaximum(length(allHandles) + length(hg_handles)); % = # of all nodes + treePanel.add(progressBar, BorderLayout.SOUTH); + + % Prepare the image pane +%disable for now, until we get it working... +%{ + try + hFig = ancestor(origContainer,'figure'); + [cdata, cm] = getframe(hFig); %#ok cm unused + tempfname = [tempname '.png']; + imwrite(cdata,tempfname); % don't know how to pass directly to BufferedImage, so use disk... + jImg = javax.imageio.ImageIO.read(java.io.File(tempfname)); + try delete(tempfname); catch end + imgPanel = JPanel(); + leftPanel = JSplitPane(JSplitPane.VERTICAL_SPLIT, treePanel, imgPanel); + leftPanel.setOneTouchExpandable(true); + leftPanel.setContinuousLayout(true); + leftPanel.setResizeWeight(0.8); + catch + leftPanel = treePanel; + end +%} + leftPanel = treePanel; + + % Prepare the inspector pane + classNameLabel = JLabel([' ' char(container.class)]); + classNameLabel.setForeground(Color.blue); + updateNodeTooltip(container, classNameLabel); + inspectorPanel = JPanel(BorderLayout); + inspectorPanel.add(classNameLabel, BorderLayout.NORTH); + % TODO: Maybe uncomment the following when we add the HG tree - in the meantime it's unused (java properties are un-groupable) + %objReg = com.mathworks.services.ObjectRegistry.getLayoutRegistry; + %toolBar = awtinvoke('com.mathworks.mlwidgets.inspector.PropertyView$ToolBarStyle','valueOf(Ljava.lang.String;)','GROUPTOOLBAR'); + %inspectorPane = com.mathworks.mlwidgets.inspector.PropertyView(objReg, toolBar); + inspectorPane = com.mathworks.mlwidgets.inspector.PropertyView; + identifiers = disableDbstopError; %#ok "dbstop if error" causes inspect.m to croak due to a bug - so workaround + inspectorPane.setObject(container); + inspectorPane.setAutoUpdate(true); + % TODO: Add property listeners + % TODO: Display additional props + inspectorTable = inspectorPane; + while ~isa(inspectorTable,'javax.swing.JTable') + inspectorTable = inspectorTable.getComponent(0); + end + toolTipText = 'hover mouse over the red classname above to see the full list of properties'; + inspectorTable.setToolTipText(toolTipText); + jideTableUtils = []; + try + % Try JIDE features - see http://www.jidesoft.com/products/JIDE_Grids_Developer_Guide.pdf + com.mathworks.mwswing.MJUtilities.initJIDE; + jideTableUtils = eval('com.jidesoft.grid.TableUtils;'); % prevent JIDE alert by run-time (not load-time) evaluation + jideTableUtils.autoResizeAllColumns(inspectorTable); + inspectorTable.setRowAutoResizes(true); + inspectorTable.getModel.setShowExpert(1); + catch + % JIDE is probably unavailable - never mind... + end + inspectorPanel.add(inspectorPane, BorderLayout.CENTER); + % TODO: Add data update listeners + + % Prepare the callbacks pane + callbacksPanel = JPanel(BorderLayout); + classHdl = classhandle(handle(container)); + eventNames = get(classHdl.Events,'Name'); + if ~isempty(eventNames) + cbNames = sort(strcat(eventNames,'Callback')); + cbData = [cbNames, get(container,cbNames)']; + cbTableEnabled = true; + else + cbData = {'(no callbacks)',''}; + cbTableEnabled = false; + end + cbHeaders = {'Callback name','Callback value'}; + try + % Use JideTable if available on this system + %callbacksTableModel = javax.swing.table.DefaultTableModel(cbData,cbHeaders); %#ok + %callbacksTable = eval('com.jidesoft.grid.PropertyTable(callbacksTableModel);'); % prevent JIDE alert by run-time (not load-time) evaluation + callbacksTable = eval('com.jidesoft.grid.TreeTable(cbData,cbHeaders);'); % prevent JIDE alert by run-time (not load-time) evaluation + callbacksTable.setRowAutoResizes(true); + callbacksTable.setColumnAutoResizable(true); + callbacksTable.setColumnResizable(true); + jideTableUtils.autoResizeAllColumns(callbacksTable); + callbacksTable.setTableHeader([]); % hide the column headers since now we can resize columns with the gridline + callbacksLabel = JLabel(' Callbacks:'); % The column headers are replaced with a header label + %callbacksPanel.add(callbacksLabel, BorderLayout.NORTH); + + % Add checkbox to show/hide standard callbacks + callbacksTopPanel = JPanel; + callbacksTopPanel.setLayout(BoxLayout(callbacksTopPanel, BoxLayout.LINE_AXIS)); + callbacksTopPanel.add(callbacksLabel); + callbacksTopPanel.add(Box.createHorizontalGlue); + jcb = JCheckBox('Hide standard callbacks', cbHideStd); + set(jcb, 'ActionPerformedCallback',@cbHideStdCbs_Callback, 'userdata',callbacksTable, 'tooltip','Hide standard Swing callbacks - only component-specific callbacks will be displayed'); + callbacksTopPanel.add(jcb); + callbacksPanel.add(callbacksTopPanel, BorderLayout.NORTH); + catch + % Otherwise, use a standard Swing JTable (keep the headers to enable resizing) + callbacksTable = JTable(cbData,cbHeaders); + end + cbToolTipText = 'Callbacks may be ''strings'', @funcHandle or {@funcHandle,arg1,...}'; + callbacksTable.setToolTipText(cbToolTipText); + callbacksTable.setGridColor(inspectorTable.getGridColor); + cbNameTextField = JTextField; + cbNameTextField.setEditable(false); % ensure that the callback names are not modified... + cbNameCellEditor = DefaultCellEditor(cbNameTextField); + cbNameCellEditor.setClickCountToStart(intmax); % i.e, never enter edit mode... + callbacksTable.getColumnModel.getColumn(0).setCellEditor(cbNameCellEditor); + if ~cbTableEnabled + callbacksTable.getColumnModel.getColumn(1).setCellEditor(cbNameCellEditor); + end + set(callbacksTable.getModel, 'TableChangedCallback',@tbCallbacksChanged, 'UserData',container); + cbScrollPane = JScrollPane(callbacksTable); + cbScrollPane.setVerticalScrollBarPolicy(cbScrollPane.VERTICAL_SCROLLBAR_AS_NEEDED); + callbacksPanel.add(cbScrollPane, BorderLayout.CENTER); + callbacksPanel.setToolTipText(cbToolTipText); + + % Prepare the top-bottom JSplitPanes + vsplitPane = JSplitPane(JSplitPane.VERTICAL_SPLIT, inspectorPanel, callbacksPanel); + vsplitPane.setOneTouchExpandable(true); + vsplitPane.setContinuousLayout(true); + vsplitPane.setResizeWeight(0.8); + + % Prepare the left-right JSplitPane + hsplitPane = JSplitPane(JSplitPane.HORIZONTAL_SPLIT, leftPanel, vsplitPane); + hsplitPane.setOneTouchExpandable(true); + hsplitPane.setContinuousLayout(true); + hsplitPane.setResizeWeight(0.6); + pos = getpixelposition(hTreeFig); + + % Prepare the bottom pane with all buttons + lowerPanel = JPanel(FlowLayout); + blogUrlLabel = 'Undocumented
Matlab.com'; + jWebsite = createJButton(blogUrlLabel, @btWebsite_Callback, 'Visit the UndocumentedMatlab.com blog'); + jWebsite.setContentAreaFilled(0); + lowerPanel.add(jWebsite); + lowerPanel.add(createJButton('Refresh
tree', {@btRefresh_Callback, origContainer, hTreeFig}, 'Rescan the component tree, from the root down')); + lowerPanel.add(createJButton('Export to
workspace', {@btExport_Callback, jTreeObj, classNameLabel}, 'Export the selected component handles to workspace variable findjobj_hdls')); + lowerPanel.add(createJButton('Request
focus', {@btFocus_Callback, jTreeObj, root}, 'Set the focus on the first selected component')); + lowerPanel.add(createJButton('Inspect
object', {@btInspect_Callback, jTreeObj, root}, 'View the signature of all methods supported by the first selected component')); + lowerPanel.add(createJButton('Check for
updates', {@btCheckFex_Callback}, 'Check the MathWorks FileExchange for the latest version of FindJObj')); + + % Display everything on-screen + globalPanel = JPanel(BorderLayout); + globalPanel.add(hsplitPane, BorderLayout.CENTER); + globalPanel.add(lowerPanel, BorderLayout.SOUTH); + [obj, hcontainer] = javacomponent(globalPanel, [0,0,pos(3:4)], hTreeFig); + set(hcontainer,'units','normalized'); + drawnow; + hsplitPane.setDividerLocation(hsplitPaneLocation); % this only works after the JSplitPane is displayed... + vsplitPane.setDividerLocation(vsplitPaneLocation); % this only works after the JSplitPane is displayed... + %restoreDbstopError(identifiers); + + % Refresh & resize the screenshot thumbnail +%disable for now, until we get it working... +%{ + try + hAx = axes('Parent',hTreeFig, 'units','pixels', 'position',[10,10,250,150], 'visible','off'); + axis(hAx,'image'); + image(cdata,'Parent',hAx); + axis(hAx,'off'); + set(hAx,'UserData',cdata); + set(imgPanel, 'ComponentResizedCallback',{@resizeImg, hAx}, 'UserData',lowerPanel); + imgPanel.getGraphics.drawImage(jImg, 0, 0, []); + catch + % Never mind... + end +%} + % If all handles were selected (i.e., none were filtered) then only select the first + if (length(selectedIdx) == length(allHandles)) && ~isempty(selectedIdx) + selectedIdx = 1; + end + + % Store handles for callback use + userdata.handles = allHandles; + userdata.levels = allLevels; + userdata.parents = allParents; + userdata.hg_handles = hg_handles; + userdata.hg_levels = hg_levels; + userdata.hg_parents = hg_parentIdx; + userdata.initialIdx = selectedIdx; + userdata.userSelected = false; % Indicates the user has modified the initial selections + userdata.inInit = true; + userdata.jTree = jTreeObj; + userdata.jTreePeer = tree_h; + userdata.vsplitPane = vsplitPane; + userdata.hsplitPane = hsplitPane; + userdata.classNameLabel = classNameLabel; + userdata.inspectorPane = inspectorPane; + userdata.callbacksTable = callbacksTable; + userdata.jideTableUtils = jideTableUtils; + try + userdata.cbHideStdCbs = jcb; + catch + userdata.cbHideStdCbs = []; + end + + set(tree_h, 'userdata',userdata); + set(hTreeFig, 'userdata',userdata); + set(callbacksTable,'userdata',userdata); + + % Select the root node if requested + % Note: we must do so here since all other nodes except the root are processed by expandNode + if any(selectedIdx==1) + tree_h.setSelectedNode(root); + end + + % Set the initial cbHideStdCbs state + try + if jcb.isSelected + drawnow; + evd.getSource.isSelected = jcb.isSelected; + cbHideStdCbs_Callback(jcb,evd); + end + catch + % never mind... + end + + % Set the callback functions + set(tree_h, 'NodeExpandedCallback', {@nodeExpanded, tree_h}); + set(tree_h, 'NodeSelectedCallback', {@nodeSelected, tree_h}); + + % Set the tree mouse-click callback + % Note: default actions (expand/collapse) will still be performed? + % Note: MousePressedCallback is better than MouseClickedCallback + % since it fires immediately when mouse button is pressed, + % without waiting for its release, as MouseClickedCallback does + handleTree = tree_h.getScrollPane; + jTreeObj = handleTree.getViewport.getComponent(0); + set(jTreeObj, 'MousePressedCallback', {@treeMousePressedCallback,tree_h}); % context (right-click) menu + set(jTreeObj, 'MouseMovedCallback', @treeMouseMovedCallback); % mouse hover tooltips + + % Pre-expand all rows + expandNode(progressBar, jTreeObj, tree_h, root, 0); + %jTreeObj.setVisible(1); + + % Hide the progressbar now that we've finished expanding all rows + try + hsplitPane.getLeftComponent.setTopComponent(treePane); + catch + % Probably not a vSplitPane on the left... + hsplitPane.setLeftComponent(treePane); + end + hsplitPane.setDividerLocation(hsplitPaneLocation); % need to do it again... + + % Update userdata + userdata.inInit = false; + set(tree_h, 'userdata',userdata); + set(hTreeFig,'userdata',userdata); + + % Set keyboard focus on the tree + jTreeObj.requestFocus; + drawnow; + + % Check for a newer version + checkVersion(); + + % Reset the last error + lasterr(''); + end + + %% Rresize image pane + function resizeImg(varargin) %#ok - unused (TODO: waiting for img placement fix...) + try + hPanel = varargin{1}; + hAx = varargin{3}; + lowerPanel = get(hPanel,'UserData'); + newJPos = cell2mat(get(hPanel,{'X','Y','Width','Height'})); + newMPos = [1,get(lowerPanel,'Height'),newJPos(3:4)]; + set(hAx, 'units','pixels', 'position',newMPos, 'Visible','on'); + uistack(hAx,'top'); % no good... + set(hPanel,'Opaque','off'); % also no good... + catch + % Never mind... + dispError + end + return; + end + + %% "dbstop if error" causes inspect.m to croak due to a bug - so workaround by temporarily disabling this dbstop + function identifiers = disableDbstopError + dbStat = dbstatus; + idx = find(strcmp({dbStat.cond},'error')); + identifiers = [dbStat(idx).identifier]; + if ~isempty(idx) + dbclear if error; + msgbox('''dbstop if error'' had to be disabled due to a Matlab bug that would have caused Matlab to crash.', 'FindJObj', 'warn'); + end + end + + %% Restore any previous "dbstop if error" + function restoreDbstopError(identifiers) %#ok + for itemIdx = 1 : length(identifiers) + eval(['dbstop if error ' identifiers{itemIdx}]); + end + end + + %% Recursively expand all nodes (except toolbar/menubar) in startup + function expandNode(progressBar, tree, tree_h, parentNode, parentRow) + try + if nargin < 5 + parentPath = javax.swing.tree.TreePath(parentNode.getPath); + parentRow = tree.getRowForPath(parentPath); + end + tree.expandRow(parentRow); + progressBar.setValue(progressBar.getValue+1); + numChildren = parentNode.getChildCount; + if (numChildren == 0) + pause(0.0002); % as short as possible... + drawnow; + end + nodesToUnExpand = {'FigureMenuBar','MLMenuBar','MJToolBar','Box','uimenu','uitoolbar','ScrollBar'}; + numChildren = parentNode.getChildCount; + for childIdx = 0 : numChildren-1 + childNode = parentNode.getChildAt(childIdx); + + % Expand child node if not leaf & not toolbar/menubar + if childNode.isLeafNode + progressBar.setValue(progressBar.getValue+1); + + % Pre-select the node based upon the user's FINDJOBJ filters + try + nodedata = get(childNode, 'userdata'); + userdata = get(tree_h, 'userdata'); + if ~ishghandle(nodedata.obj) && ~userdata.userSelected && any(userdata.initialIdx == nodedata.idx) + pause(0.0002); % as short as possible... + drawnow; + if isempty(tree_h.getSelectedNodes) + tree_h.setSelectedNode(childNode); + else + newSelectedNodes = [tree_h.getSelectedNodes, childNode]; + tree_h.setSelectedNodes(newSelectedNodes); + end + end + catch + % never mind... + dispError + end + + else + % Expand all non-leaves + expandNode(progressBar, tree, tree_h, childNode); + + % Re-collapse toolbar/menubar etc., and also invisible containers + % Note: if we simply did nothing, progressbar would not have been updated... + try + childHandle = getappdata(childNode,'childHandle'); %=childNode.getUserObject + visible = childHandle.isVisible; + catch + visible = 1; + end + visible = visible && isempty(findstr(get(childNode,'Name'),'color="gray"')); + %if any(strcmp(childNode.getName,nodesToUnExpand)) + %name = char(childNode.getName); + if any(cellfun(@(s)~isempty(strmatch(s,char(childNode.getName))),nodesToUnExpand)) || ~visible + childPath = javax.swing.tree.TreePath(childNode.getPath); + childRow = tree.getRowForPath(childPath); + tree.collapseRow(childRow); + end + end + end + catch + % never mind... + dispError + end + end + + %% Create utility buttons + function hButton = createJButton(nameStr, handler, toolTipText) + try + jButton = javax.swing.JButton(['
' nameStr]); + jButton.setCursor(java.awt.Cursor.getPredefinedCursor(java.awt.Cursor.HAND_CURSOR)); + jButton.setToolTipText(toolTipText); + minSize = jButton.getMinimumSize; + jButton.setMinimumSize(java.awt.Dimension(minSize.getWidth,35)); + hButton = handle(jButton,'CallbackProperties'); + set(hButton,'ActionPerformedCallback',handler); + catch + % Never mind... + end + end + + %% Flash a component off/on for the specified duration + % note: starts with 'on'; if numTimes is odd then ends with 'on', otherwise with 'off' + function flashComponent(jComps,delaySecs,numTimes) + persistent redBorder redBorderPanels + try + % Handle callback data from right-click (context-menu) + if iscell(numTimes) + [jComps,delaySecs,numTimes] = deal(numTimes{:}); + end + + if isempty(redBorder) % reuse if possible + redBorder = javax.swing.border.LineBorder(java.awt.Color.red,2,0); + end + for compIdx = 1 : length(jComps) + try + oldBorder{compIdx} = jComps(compIdx).getBorder; %#ok grow + catch + oldBorder{compIdx} = []; %#ok grow + end + isSettable(compIdx) = ismethod(jComps(compIdx),'setBorder'); %#ok grow + if isSettable(compIdx) + try + % some components prevent border modification: + oldBorderFlag = jComps(compIdx).isBorderPainted; + if ~oldBorderFlag + jComps(compIdx).setBorderPainted(1); + isSettable(compIdx) = jComps(compIdx).isBorderPainted; %#ok grow + jComps(compIdx).setBorderPainted(oldBorderFlag); + end + catch + % do nothing... + end + end + if compIdx > length(redBorderPanels) + redBorderPanels{compIdx} = javax.swing.JPanel; + redBorderPanels{compIdx}.setBorder(redBorder); + redBorderPanels{compIdx}.setOpaque(0); % transparent interior, red border + end + try + redBorderPanels{compIdx}.setBounds(jComps(compIdx).getBounds); + catch + % never mind - might be an HG handle + end + end + for idx = 1 : 2*numTimes + if idx>1, pause(delaySecs); end % don't pause at start + visible = mod(idx,2); + for compIdx = 1 : length(jComps) + try + jComp = jComps(compIdx); + + % Prevent Matlab crash (java buffer overflow...) + if jComp.isa('com.mathworks.mwswing.desk.DTSplitPane') || ... + jComp.isa('com.mathworks.mwswing.MJSplitPane') + continue; + end + + % HG handles are highlighted by setting their 'Selected' property + if isa(jComp,'uimenu') + if visible + oldColor = get(jComp,'ForegroundColor'); + setappdata(jComp,'findjobj_oldColor',oldColor); + set(jComp,'ForegroundColor','red'); + else + oldColor = getappdata(jComp,'findjobj_oldColor'); + set(jComp,'ForegroundColor',oldColor); + rmappdata(jComp,'ForegroundColor'); + end + + elseif ishghandle(jComp) + if visible + set(jComp,'Selected','on'); + else + set(jComp,'Selected','off'); + end + + else %if isjava(jComp) + + jParent = jComps(compIdx).getParent; + + % Most Java components allow modifying their borders + if isSettable(compIdx) + if visible + jComp.setBorder(redBorder); + try jComp.setBorderPainted(1); catch, end %#ok + else %if ~isempty(oldBorder{compIdx}) + jComp.setBorder(oldBorder{compIdx}); + end + jComp.repaint; + + % The other Java components are highlighted by a transparent red-border + % panel that is placed on top of them in their parent's space + elseif ~isempty(jParent) + if visible + jParent.add(redBorderPanels{compIdx}); + jParent.setComponentZOrder(redBorderPanels{compIdx},0); + else + jParent.remove(redBorderPanels{compIdx}); + end + jParent.repaint + end + end + catch + % never mind - try the next component (if any) + end + end + drawnow; + end + catch + % never mind... + dispError; + end + return; % debug point + end % flashComponent + + %% Select tree node + function nodeSelected(src, evd, tree) %#ok + try + if iscell(tree) + [src,node] = deal(tree{:}); + else + node = evd.getCurrentNode; + end + %nodeHandle = node.getUserObject; + nodedata = get(node,'userdata'); + nodeHandle = nodedata.obj; + userdata = get(src,'userdata'); + if ~isempty(nodeHandle) && ~isempty(userdata) + numSelections = userdata.jTree.getSelectionCount; + selectionPaths = userdata.jTree.getSelectionPaths; + if (numSelections == 1) + % Indicate that the user has modified the initial selection (except if this was an initial auto-selected node) + if ~userdata.inInit + userdata.userSelected = true; + set(src,'userdata',userdata); + end + + % Update the fully-qualified class name label + numInitialIdx = length(userdata.initialIdx); + thisHandle = nodeHandle; + try + if ~ishghandle(thisHandle) + thisHandle = java(nodeHandle); + end + catch + % never mind... + end + if ~userdata.inInit || (numInitialIdx == 1) + userdata.classNameLabel.setText([' ' char(thisHandle.class)]); + else + userdata.classNameLabel.setText([' ' num2str(numInitialIdx) 'x handles (some handles hidden by unexpanded tree nodes)']); + end + if ishghandle(thisHandle) + userdata.classNameLabel.setText(userdata.classNameLabel.getText.concat(' (HG handle)')); + end + userdata.inspectorPane.dispose; % remove props listeners - doesn't work... + updateNodeTooltip(nodeHandle, userdata.classNameLabel); + + % Update the data properties inspector pane + % Note: we can't simply use the evd nodeHandle, because this node might have been DE-selected with only one other node left selected... + %nodeHandle = selectionPaths(1).getLastPathComponent.getUserObject; + nodedata = get(selectionPaths(1).getLastPathComponent,'userdata'); + nodeHandle = nodedata.obj; + %identifiers = disableDbstopError; % "dbstop if error" causes inspect.m to croak due to a bug - so workaround + userdata.inspectorPane.setObject(thisHandle); + + % Update the callbacks table + try + stripStdCbsFlag = getappdata(userdata.callbacksTable,'hideStdCbs'); + [cbData, cbHeaders, cbTableEnabled] = getCbsData(nodeHandle, stripStdCbsFlag); %#ok cbTableEnabled unused + callbacksTableModel = javax.swing.table.DefaultTableModel(cbData,cbHeaders); + set(callbacksTableModel, 'TableChangedCallback',@tbCallbacksChanged, 'UserData',nodeHandle); + userdata.callbacksTable.setModel(callbacksTableModel) + userdata.callbacksTable.setRowAutoResizes(true); + userdata.jideTableUtils.autoResizeAllColumns(userdata.callbacksTable); + catch + % never mind... + dispError + end + pause(0.005); + drawnow; + %restoreDbstopError(identifiers); + + % Highlight the selected object (if visible) + flashComponent(nodeHandle,0.2,3); + + elseif (numSelections > 1) % Multiple selections + + % Get the list of all selected nodes + jArray = javaArray('java.lang.Object', numSelections); + toolTipStr = ''; + sameClassFlag = true; + for idx = 1 : numSelections + %jArray(idx) = selectionPaths(idx).getLastPathComponent.getUserObject; + nodedata = get(selectionPaths(idx).getLastPathComponent,'userdata'); + try + jArray(idx) = java(nodedata.obj); + catch + jArray(idx) = nodedata.obj; + end + toolTipStr = [toolTipStr ' ' jArray(idx).class ' ']; %#ok grow + if (idx < numSelections), toolTipStr = [toolTipStr '
']; end %#ok grow + if (idx > 1) && sameClassFlag && ~isequal(jArray(idx).getClass,jArray(1).getClass) + sameClassFlag = false; + end + end + toolTipStr = [toolTipStr '']; + + % Update the fully-qualified class name label + if sameClassFlag + classNameStr = jArray(1).class; + else + classNameStr = 'handle'; + end + if all(ishghandle(jArray)) + if strcmp(classNameStr,'handle') + classNameStr = 'HG handles'; + else + classNameStr = [classNameStr ' (HG handles)']; + end + end + classNameStr = [' ' num2str(numSelections) 'x ' classNameStr]; + userdata.classNameLabel.setText(classNameStr); + userdata.classNameLabel.setToolTipText(toolTipStr); + + % Update the data properties inspector pane + %identifiers = disableDbstopError; % "dbstop if error" causes inspect.m to croak due to a bug - so workaround + userdata.inspectorPane.getRegistry.setSelected(jArray, true); + + % Update the callbacks table + try + % Get intersecting callback names & values + stripStdCbsFlag = getappdata(userdata.callbacksTable,'hideStdCbs'); + [cbData, cbHeaders, cbTableEnabled] = getCbsData(jArray(1), stripStdCbsFlag); %#ok cbHeaders & cbTableEnabled unused + if ~isempty(cbData) + cbNames = cbData(:,1); + for idx = 2 : length(jArray) + [cbData2, cbHeaders2] = getCbsData(jArray(idx), stripStdCbsFlag); %#ok cbHeaders2 unused + if ~isempty(cbData2) + newCbNames = cbData2(:,1); + [cbNames, cbIdx, cb2Idx] = intersect(cbNames,newCbNames); %#ok cb2Idx unused + cbData = cbData(cbIdx,:); + for cbIdx = 1 : length(cbNames) + newIdx = find(strcmp(cbNames{cbIdx},newCbNames)); + if ~isequal(cbData2{newIdx,2}, cbData{cbIdx,2}) + cbData{cbIdx,2} = ''; + end + end + else + cbData = cbData([],:); %=empty cell array + end + if isempty(cbData) + break; + end + end + end + cbHeaders = {'Callback name','Callback value'}; + callbacksTableModel = javax.swing.table.DefaultTableModel(cbData,cbHeaders); + set(callbacksTableModel, 'TableChangedCallback',@tbCallbacksChanged, 'UserData',jArray); + userdata.callbacksTable.setModel(callbacksTableModel) + userdata.callbacksTable.setRowAutoResizes(true); + userdata.jideTableUtils.autoResizeAllColumns(userdata.callbacksTable); + catch + % never mind... + dispError + end + + pause(0.005); + drawnow; + %restoreDbstopError(identifiers); + + % Highlight the selected objects (if visible) + flashComponent(jArray,0.2,3); + end + + % TODO: Auto-highlight selected object (?) + %nodeHandle.requestFocus; + end + catch + dispError + end + end + + %% IFF utility function for annonymous cellfun funcs + function result = iff(test,trueVal,falseVal) %#ok + try + if test + result = trueVal; + else + result = falseVal; + end + catch + result = false; + end + end + + %% Get an HTML representation of the object's properties + function dataFieldsStr = getPropsHtml(nodeHandle, dataFields) + try + % Get a text representation of the fieldnames & values + dataFieldsStr = ''; % just in case the following croaks... + if isempty(dataFields) + return; + end + dataFieldsStr = evalc('disp(dataFields)'); + if dataFieldsStr(end)==char(10), dataFieldsStr=dataFieldsStr(1:end-1); end + + % Strip out callbacks + dataFieldsStr = regexprep(dataFieldsStr,'^\s*\w*Callback(Data)?:[^\n]*$','','lineanchors'); + dataFieldsStr = regexprep(dataFieldsStr,'\n\n','\n'); + + % HTMLize tooltip data + % First, set the fields' font based on its read-write status + nodeHandle = handle(nodeHandle); % ensure this is a Matlab handle, not a java object + fieldNames = fieldnames(dataFields); + undefinedStr = ''; + for fieldIdx = 1 : length(fieldNames) + thisFieldName = fieldNames{fieldIdx}; + accessFlags = get(findprop(nodeHandle,thisFieldName),'AccessFlags'); + if isfield(accessFlags,'PublicSet') && strcmp(accessFlags.PublicSet,'on') + % Bolden read/write fields + thisFieldFormat = ['' thisFieldName ':$2']; + elseif ~isfield(accessFlags,'PublicSet') + % Undefined - probably a Matlab-defined field of com.mathworks.hg.peer.FigureFrameProxy... + thisFieldFormat = ['' thisFieldName ':$2']; + undefinedStr = ', undefined'; + else % PublicSet=='off' + % Gray-out & italicize any read-only fields + thisFieldFormat = ['' thisFieldName ':$2']; + end + dataFieldsStr = regexprep(dataFieldsStr, ['([\s\n])' thisFieldName ':([^\n]*)'], ['$1' thisFieldFormat]); + end + catch + % never mind... - probably an ambiguous property name + %dispError + end + + % Method 1: simple
list + %dataFieldsStr = strrep(dataFieldsStr,char(10),' 
  '); + + % Method 2: 2x2-column + dataFieldsStr = regexprep(dataFieldsStr, '^\s*([^:]+:)([^\n]*)\n^\s*([^:]+:)([^\n]*)$', '', 'lineanchors'); + dataFieldsStr = regexprep(dataFieldsStr, '^[^<]\s*([^:]+:)([^\n]*)$', '', 'lineanchors'); + dataFieldsStr = ['(modifiable' undefinedStr ' & read-only fields)

  

 $1 $2    $3 $4 
 $1 $2  
' dataFieldsStr '
']; + end + + %% Update tooltip string with a node's data + function updateNodeTooltip(nodeHandle, uiObject) + try + toolTipStr = nodeHandle.class; + dataFieldsStr = ''; + + % Add HG annotation if relevant + if ishghandle(nodeHandle) + hgStr = ' HG Handle'; + else + hgStr = ''; + end + + % Note: don't bulk-get because (1) not all properties are returned & (2) some properties cause a Java exception + % Note2: the classhandle approach does not enable access to user-defined schema.props + ch = classhandle(handle(nodeHandle)); + dataFields = []; + [sortedNames, sortedIdx] = sort(get(ch.Properties,'Name')); + for idx = 1 : length(sortedIdx) + sp = ch.Properties(sortedIdx(idx)); + % TODO: some fields (see EOL comment below) generate a Java Exception from: com.mathworks.mlwidgets.inspector.PropertyRootNode$PropertyListener$1$1.run + if strcmp(sp.AccessFlags.PublicGet,'on') % && ~any(strcmp(sp.Name,{'FixedColors','ListboxTop','Extent'})) + try + dataFields.(sp.Name) = get(nodeHandle, sp.Name); + catch + dataFields.(sp.Name) = 'Error!'; + end + else + dataFields.(sp.Name) = '(no public getter method)'; + end + end + dataFieldsStr = getPropsHtml(nodeHandle, dataFields); + catch + % Probably a non-HG java object + try + % Note: the bulk-get approach enables access to user-defined schema-props, but not to some original classhandle Properties... + dataFields = get(nodeHandle); + dataFieldsStr = getPropsHtml(nodeHandle, dataFields); + catch + % Probably a missing property getter implementation + try + % Inform the user - bail out on error + err = lasterror; + dataFieldsStr = ['

' strrep(err.message, char(10), '
')]; + catch + % forget it... + end + end + end + + % Set the object tooltip + if ~isempty(dataFieldsStr) + toolTipStr = [' ' char(toolTipStr) '' hgStr ': ' dataFieldsStr '']; + end + uiObject.setToolTipText(toolTipStr); + end + + %% Expand tree node + function nodeExpanded(src, evd, tree) %#ok + % tree = handle(src); + % evdsrc = evd.getSource; + evdnode = evd.getCurrentNode; + + if ~tree.isLoaded(evdnode) + + % Get the list of children TreeNodes + childnodes = getChildrenNodes(tree, evdnode); + + % Add the HG sub-tree (unless already included in the first tree) + childHandle = getappdata(evdnode.handle,'childHandle'); %=evdnode.getUserObject + if evdnode.isRoot && ~isempty(hg_handles) && ~isequal(hg_handles(1).java, childHandle) + childnodes = [childnodes, getChildrenNodes(tree, evdnode, true)]; + end + + % If we have a single child handle, wrap it within a javaArray for tree.add() to "swallow" + if (length(childnodes) == 1) + chnodes = childnodes; + childnodes = javaArray('com.mathworks.hg.peer.UITreeNode', 1); + childnodes(1) = java(chnodes); + end + + % Add child nodes to the current node + tree.add(evdnode, childnodes); + tree.setLoaded(evdnode, true); + end + end + + %% Get an icon image no larger than 16x16 pixels + function iconImage = setIconSize(iconImage) + try + iconWidth = iconImage.getWidth; + iconHeight = iconImage.getHeight; + if iconWidth > 16 + newHeight = fix(iconHeight * 16 / iconWidth); + iconImage = iconImage.getScaledInstance(16,newHeight,iconImage.SCALE_SMOOTH); + elseif iconHeight > 16 + newWidth = fix(iconWidth * 16 / iconHeight); + iconImage = iconImage.getScaledInstance(newWidth,16,iconImage.SCALE_SMOOTH); + end + catch + % never mind... - return original icon + end + end % setIconSize + + %% Get list of children nodes + function nodes = getChildrenNodes(tree, parentNode, isRootHGNode) + try + iconpath = [matlabroot, '/toolbox/matlab/icons/']; + nodes = handle([]); + userdata = get(tree,'userData'); + hdls = userdata.handles; + nodedata = get(parentNode,'userdata'); + if nargin < 3 + %isJavaNode = ~ishghandle(parentNode.getUserObject); + isJavaNode = ~ishghandle(nodedata.obj); + isRootHGNode = false; + else + isJavaNode = ~isRootHGNode; + end + + % Search for this parent node in the list of all nodes + parents = userdata.parents; + nodeIdx = nodedata.idx; + + if isJavaNode && isempty(nodeIdx) % Failback, in case userdata doesn't work for some reason... + for hIdx = 1 : length(hdls) + %if isequal(handle(parentNode.getUserObject), hdls(hIdx)) + if isequal(handle(nodedata.obj), hdls(hIdx)) + nodeIdx = hIdx; + break; + end + end + end + if ~isJavaNode + if isRootHGNode % =root HG node + thisChildHandle = userdata.hg_handles(1); + childName = getNodeName(thisChildHandle); + hasGrandChildren = any(parents==1); + icon = []; + if hasGrandChildren && length(hg_handles)>1 + childName = childName.concat(' - HG root container'); + icon = [iconpath 'figureicon.gif']; + end + try + nodes = uitreenode('v0', thisChildHandle, childName, icon, ~hasGrandChildren); + catch % old matlab version don't have the 'v0' option + try + nodes = uitreenode(thisChildHandle, childName, icon, ~hasGrandChildren); + catch + % probably an invalid handle - ignore... + end + end + + % Add the handler to the node's internal data + % Note: could also use 'userdata', but setUserObject() is recommended for TreeNodes + % Note2: however, setUserObject() sets a java *BeenAdapter object for HG handles instead of the required original class, so use setappdata + %nodes.setUserObject(thisChildHandle); + setappdata(nodes,'childHandle',thisChildHandle); + nodedata.idx = 1; + nodedata.obj = thisChildHandle; + set(nodes,'userdata',nodedata); + return; + else % non-root HG node + parents = userdata.hg_parents; + hdls = userdata.hg_handles; + end % if isRootHGNode + end % if ~isJavaNode + + % If this node was found, get the list of its children + if ~isempty(nodeIdx) + %childIdx = setdiff(find(parents==nodeIdx),nodeIdx); + childIdx = find(parents==nodeIdx); + childIdx(childIdx==nodeIdx) = []; % faster... + numChildren = length(childIdx); + for cIdx = 1 : numChildren + thisChildIdx = childIdx(cIdx); + thisChildHandle = hdls(thisChildIdx); + childName = getNodeName(thisChildHandle); + try + visible = thisChildHandle.Visible; + if visible + try visible = thisChildHandle.Width > 0; catch, end %#ok + end + if ~visible + childName = ['' char(childName) '']; %#ok grow + end + catch + % never mind... + end + hasGrandChildren = any(parents==thisChildIdx); + try + isaLabel = isa(thisChildHandle.java,'javax.swing.JLabel'); + catch + isaLabel = 0; + end + if hasGrandChildren && ~any(strcmp(thisChildHandle.class,{'axes'})) + icon = [iconpath 'foldericon.gif']; + elseif isaLabel + icon = [iconpath 'tool_text.gif']; + else + icon = []; + end + try + nodes(cIdx) = uitreenode('v0', thisChildHandle, childName, icon, ~hasGrandChildren); + catch % old matlab version don't have the 'v0' option + try + nodes(cIdx) = uitreenode(thisChildHandle, childName, icon, ~hasGrandChildren); + catch + % probably an invalid handle - ignore... + end + end + + % Use existing object icon, if available + try + setTreeNodeIcon(nodes(cIdx),thisChildHandle); + catch + % probably an invalid handle - ignore... + end + + % Pre-select the node based upon the user's FINDJOBJ filters + try + if isJavaNode && ~userdata.userSelected && any(userdata.initialIdx == thisChildIdx) + pause(0.0002); % as short as possible... + drawnow; + if isempty(tree.getSelectedNodes) + tree.setSelectedNode(nodes(cIdx)); + else + newSelectedNodes = [tree.getSelectedNodes, nodes(cIdx).java]; + tree.setSelectedNodes(newSelectedNodes); + end + end + catch + % never mind... + end + + % Add the handler to the node's internal data + % Note: could also use 'userdata', but setUserObject() is recommended for TreeNodes + % Note2: however, setUserObject() sets a java *BeenAdapter object for HG handles instead of the required original class, so use setappdata + % Note3: the following will error if invalid handle - ignore + try + if isJavaNode + thisChildHandle = thisChildHandle.java; + end + %nodes(cIdx).setUserObject(thisChildHandle); + setappdata(nodes(cIdx),'childHandle',thisChildHandle); + nodedata.idx = thisChildIdx; + nodedata.obj = thisChildHandle; + set(nodes(cIdx),'userdata',nodedata); + catch + % never mind (probably an invalid handle) - leave unchanged (like a leaf) + end + end + end + catch + % Never mind - leave unchanged (like a leaf) + %error('YMA:findjobj:UnknownNodeType', 'Error expanding component tree node'); + dispError + end + end + + %% Get a node's name + function [nodeName, nodeTitle] = getNodeName(hndl,charsLimit) + try + % Initialize (just in case one of the succeding lines croaks) + nodeName = ''; + if ~ismethod(hndl,'getClass') + try + nodeName = hndl.class; + catch + nodeName = hndl.type; % last-ditch try... + end + else + nodeName = hndl.getClass.getSimpleName; + end + + % Strip away the package name, leaving only the regular classname + if ~isempty(nodeName) && ischar(nodeName) + nodeName = java.lang.String(nodeName); + nodeName = nodeName.substring(nodeName.lastIndexOf('.')+1); + end + if (nodeName.length == 0) + % fix case of anonymous internal classes, that do not have SimpleNames + try + nodeName = hndl.getClass.getName; + nodeName = nodeName.substring(nodeName.lastIndexOf('.')+1); + catch + % never mind - leave unchanged... + end + end + + % Get any unique identifying string (if available in one of several fields) + labelsToCheck = {'label','title','text','string','displayname','toolTipText','TooltipString','actionCommand','name','Tag','style'}; %,'UIClassID'}; + nodeTitle = ''; + strField = ''; %#ok - used for debugging + while ((~isa(nodeTitle,'java.lang.String') && ~ischar(nodeTitle)) || isempty(nodeTitle)) && ~isempty(labelsToCheck) + try + nodeTitle = get(hndl,labelsToCheck{1}); + strField = labelsToCheck{1}; %#ok - used for debugging + catch + % never mind - probably missing prop, so skip to next one + end + labelsToCheck(1) = []; + end + if length(nodeTitle) ~= numel(nodeTitle) + % Multi-line - convert to a long single line + nodeTitle = nodeTitle'; + nodeTitle = nodeTitle(:)'; + end + if nargin<2, charsLimit = 25; end + extraStr = regexprep(nodeTitle,{sprintf('(.{%d,%d}).*',charsLimit,min(charsLimit,length(nodeTitle)-1)),' +'},{'$1...',' '},'once'); + if ~isempty(extraStr) + if ischar(extraStr) + nodeName = nodeName.concat(' (''').concat(extraStr).concat(''')'); + else + nodeName = nodeName.concat(' (').concat(num2str(extraStr)).concat(')'); + end + %nodeName = nodeName.concat(strField); + end + catch + % Never mind - use whatever we have so far + %dispError + end + end + + %% Strip standard Swing callbacks from a list of events + function evNames = stripStdCbs(evNames) + try + stdEvents = {'AncestorAdded', 'AncestorMoved', 'AncestorRemoved', 'AncestorResized', ... + 'CaretPositionChanged', 'ComponentAdded', 'ComponentRemoved', ... + 'ComponentHidden', 'ComponentMoved', 'ComponentResized', 'ComponentShown', ... + 'PropertyChange', 'FocusGained', 'FocusLost', ... + 'HierarchyChanged', 'InputMethodTextChanged', ... + 'KeyPressed', 'KeyReleased', 'KeyTyped', ... + 'MouseClicked', 'MouseDragged', 'MouseEntered', 'MouseExited', ... + 'MouseMoved', 'MousePressed', 'MouseReleased', 'MouseWheelMoved', ... + 'VetoableChange'}; + stdEvents = [stdEvents, strcat(stdEvents,'Callback'), strcat(stdEvents,'Fcn')]; + evNames = setdiff(evNames,stdEvents)'; + catch + % Never mind... + dispError + end + end + + %% Callback function for checkbox + function cbHideStdCbs_Callback(src, evd, varargin) %#ok + try + % Store the current checkbox value for later use + callbacksTable = get(src,'userdata'); + if evd.getSource.isSelected + setappdata(callbacksTable,'hideStdCbs',1); + else + setappdata(callbacksTable,'hideStdCbs',[]); + end + + % Rescan the current node + userdata = get(callbacksTable,'userdata'); + ed.getCurrentNode = userdata.jTree.getSelectionModel.getSelectionPath.getLastPathComponent; + nodeSelected(userdata.jTreePeer,ed,[]); + catch + % Never mind... + dispError + end + end + + %% Callback function for button + function btWebsite_Callback(src, evd, varargin) %#ok + try + web('http://UndocumentedMatlab.com/'); + catch + % Never mind... + dispError + end + end + + %% Callback function for button + function btRefresh_Callback(src, evd, varargin) %#ok + try + % Set cursor shape to hourglass until we're done + hTreeFig = varargin{2}; + set(hTreeFig,'Pointer','watch'); + drawnow; + object = varargin{1}; + + % Re-invoke this utility to re-scan the container for all children + findjobj(object); + catch + % Never mind... + end + + % Restore default cursor shape + set(hTreeFig,'Pointer','arrow'); + end + + %% Callback function for button + function btExport_Callback(src, evd, varargin) %#ok + try + % Get the list of all selected nodes + if length(varargin) > 1 + jTree = varargin{1}; + numSelections = jTree.getSelectionCount; + selectionPaths = jTree.getSelectionPaths; + hdls = handle([]); + for idx = 1 : numSelections + %hdls(idx) = handle(selectionPaths(idx).getLastPathComponent.getUserObject); + nodedata = get(selectionPaths(idx).getLastPathComponent,'userdata'); + hdls(idx) = handle(nodedata.obj,'CallbackProperties'); + end + + % Assign the handles in the base workspace & inform user + assignin('base','findjobj_hdls',hdls); + classNameLabel = varargin{2}; + msg = ['Exported ' char(classNameLabel.getText.trim) ' to base workspace variable findjobj_hdls']; + else + % Right-click (context-menu) callback + data = varargin{1}; + obj = data{1}; + varName = data{2}; + if isempty(varName) + varName = inputdlg('Enter workspace variable name','FindJObj'); + if isempty(varName), return; end % bail out on + varName = varName{1}; + if isempty(varName) || ~ischar(varName), return; end % bail out on empty/null + varName = genvarname(varName); + end + assignin('base',varName,handle(obj,'CallbackProperties')); + msg = ['Exported object to base workspace variable ' varName]; + end + msgbox(msg,'FindJObj','help'); + catch + % Never mind... + dispError + end + end + + %% Callback function for button + function btFocus_Callback(src, evd, varargin) %#ok + try + % Request focus for the specified object + object = getTopSelectedObject(varargin{:}); + object.requestFocus; + catch + try + object = object.java.getPeer.requestFocus; + object.requestFocus; + catch + % Never mind... + %dispError + end + end + end + + %% Callback function for button + function btInspect_Callback(src, evd, varargin) %#ok + try + % Inspect the specified object + if length(varargin) == 1 + object = varargin{1}; + else + object = getTopSelectedObject(varargin{:}); + end + if isempty(which('uiinspect')) + + % If the user has not indicated NOT to be informed about UIInspect + if ~ispref('FindJObj','dontCheckUIInspect') + + % Ask the user whether to download UIINSPECT (YES, no, no & don't ask again) + answer = questdlg({'The object inspector requires UIINSPECT from the MathWorks File Exchange. UIINSPECT was created by Yair Altman, like this FindJObj utility.','','Download & install UIINSPECT?'},'UIInspect','Yes','No','No & never ask again','Yes'); + switch answer + case 'Yes' % => Yes: download & install + try + % Download UIINSPECT + baseUrl = 'http://www.mathworks.com/matlabcentral/fileexchange/17935'; + fileUrl = [baseUrl '?controller=file_infos&download=true']; + file = urlread(fileUrl); + file = regexprep(file,[char(13),char(10)],'\n'); %convert to OS-dependent EOL + + % Install... + newPath = fullfile(fileparts(which(mfilename)),'uiinspect.m'); + fid = fopen(newPath,'wt'); + fprintf(fid,'%s',file); + fclose(fid); + catch + % Error downloading: inform the user + msgbox(['Error in downloading: ' lasterr], 'UIInspect', 'warn'); + web(baseUrl); + end + + % ...and now run it... + %pause(0.1); + drawnow; + dummy = which('uiinspect'); %#ok used only to load into memory + uiinspect(object); + return; + + case 'No & never ask again' % => No & don't ask again + setpref('FindJObj','dontCheckUIInspect',1); + + otherwise + % forget it... + end + end + drawnow; + + % No UIINSPECT available - run the good-ol' METHODSVIEW()... + methodsview(object); + else + uiinspect(object); + end + catch + try + if isjava(object) + methodsview(object) + else + methodsview(object.java); + end + catch + % Never mind... + dispError + end + end + end + + %% Callback function for button + function btCheckFex_Callback(src, evd, varargin) %#ok + try + % Check the FileExchange for the latest version + web('http://www.mathworks.com/matlabcentral/fileexchange/loadFile.do?objectId=14317'); + catch + % Never mind... + dispError + end + end + + %% Check for existence of a newer version + function checkVersion() + try + % If the user has not indicated NOT to be informed + if ~ispref('FindJObj','dontCheckNewerVersion') + + % Get the latest version date from the File Exchange webpage + baseUrl = 'http://www.mathworks.com/matlabcentral/fileexchange/'; + webUrl = [baseUrl '14317']; % 'loadFile.do?objectId=14317']; + webPage = urlread(webUrl); + modIdx = strfind(webPage,'>Updates<'); + if ~isempty(modIdx) + webPage = webPage(modIdx:end); + % Note: regexp hangs if substr not found, so use strfind instead... + %latestWebVersion = regexprep(webPage,'.*?>(20[\d-]+).*','$1'); + dateIdx = strfind(webPage,'class="date">'); + if ~isempty(dateIdx) + latestDate = webPage(dateIdx(end)+13 : dateIdx(end)+23); + try + startIdx = dateIdx(end)+27; + descStartIdx = startIdx + strfind(webPage(startIdx:startIdx+999),''); + descEndIdx = startIdx + strfind(webPage(startIdx:startIdx+999),''); + descStr = webPage(descStartIdx(1)+3 : descEndIdx(1)-2); + descStr = regexprep(descStr,'',''); + catch + descStr = ''; + end + + % Get this file's latest date + thisFileName = which(mfilename); %#ok + try + thisFileData = dir(thisFileName); + try + thisFileDatenum = thisFileData.datenum; + catch % old ML versions... + thisFileDatenum = datenum(thisFileData.date); + end + catch + thisFileText = evalc('type(thisFileName)'); + thisFileLatestDate = regexprep(thisFileText,'.*Change log:[\s%]+([\d-]+).*','$1'); + thisFileDatenum = datenum(thisFileLatestDate,'yyyy-mm-dd'); + end + + % If there's a newer version on the File Exchange webpage (allow 2 days grace period) + if (thisFileDatenum < datenum(latestDate,'dd mmm yyyy')-2) + + % Ask the user whether to download the newer version (YES, no, no & don't ask again) + msg = {['A newer version (' latestDate ') of FindJObj is available on the MathWorks File Exchange:'], '', ... + ['\color{blue}' descStr '\color{black}'], '', ... + 'Download & install the new version?'}; + createStruct.Interpreter = 'tex'; + createStruct.Default = 'Yes'; + answer = questdlg(msg,'FindJObj','Yes','No','No & never ask again',createStruct); + switch answer + case 'Yes' % => Yes: download & install newer file + try + %fileUrl = [baseUrl '/download.do?objectId=14317&fn=findjobj&fe=.m']; + fileUrl = [baseUrl '/14317?controller=file_infos&download=true']; + file = urlread(fileUrl); + file = regexprep(file,[char(13),char(10)],'\n'); %convert to OS-dependent EOL + fid = fopen(thisFileName,'wt'); + fprintf(fid,'%s',file); + fclose(fid); + catch + % Error downloading: inform the user + msgbox(['Error in downloading: ' lasterr], 'FindJObj', 'warn'); + web(webUrl); + end + case 'No & never ask again' % => No & don't ask again + setpref('FindJObj','dontCheckNewerVersion',1); + otherwise + % forget it... + end + end + end + else + % Maybe webpage not fully loaded or changed format - bail out... + end + end + catch + % Never mind... + end + end + + %% Get the first selected object (might not be the top one - depends on selection order) + function object = getTopSelectedObject(jTree, root) + try + object = []; + numSelections = jTree.getSelectionCount; + if numSelections > 0 + % Get the first object specified + %object = jTree.getSelectionPath.getLastPathComponent.getUserObject; + nodedata = get(jTree.getSelectionPath.getLastPathComponent,'userdata'); + else + % Get the root object (container) + %object = root.getUserObject; + nodedata = get(root,'userdata'); + end + object = nodedata.obj; + catch + % Never mind... + dispError + end + end + + %% Update component callback upon callbacksTable data change + function tbCallbacksChanged(src, evd) + try + % exit if invalid handle or already in Callback + if ~ishandle(src) || ~isempty(getappdata(src,'inCallback')) % || length(dbstack)>1 %exit also if not called from user action + return; + end + setappdata(src,'inCallback',1); % used to prevent endless recursion + + % Update the object's callback with the modified value + modifiedColIdx = evd.getColumn; + modifiedRowIdx = evd.getFirstRow; + if modifiedColIdx==1 && modifiedRowIdx>=0 %sanity check - should always be true + table = evd.getSource; + object = get(src,'userdata'); + cbName = strtrim(table.getValueAt(modifiedRowIdx,0)); + try + cbValue = strtrim(char(table.getValueAt(modifiedRowIdx,1))); + if ~isempty(cbValue) && ismember(cbValue(1),'{[@''') + cbValue = eval(cbValue); + end + if (~ischar(cbValue) && ~isa(cbValue, 'function_handle') && (iscom(object(1)) || iscell(cbValue))) + revertCbTableModification(table, modifiedRowIdx, modifiedColIdx, cbName, object, ''); + else + for objIdx = 1 : length(object) + if ~iscom(object(objIdx)) + set(object(objIdx), cbName, cbValue); + else + cbs = object(objIdx).eventlisteners; + if ~isempty(cbs) + cbs = cbs(strcmpi(cbs(:,1),cbName),:); + object(objIdx).unregisterevent(cbs); + end + if ~isempty(cbValue) + object(objIdx).registerevent({cbName, cbValue}); + end + end + end + end + catch + revertCbTableModification(table, modifiedRowIdx, modifiedColIdx, cbName, object, lasterr) + end + end + catch + % never mind... + end + setappdata(src,'inCallback',[]); % used to prevent endless recursion + end + + %% Revert Callback table modification + function revertCbTableModification(table, modifiedRowIdx, modifiedColIdx, cbName, object, errMsg) %#ok + try + % Display a notification MsgBox + msg = 'Callbacks must be a ''string'', or a @function handle'; + if ~iscom(object(1)), msg = [msg ' or a {@func,args...} construct']; end + if ~isempty(errMsg), msg = {errMsg, '', msg}; end + msgbox(msg, ['Error setting ' cbName ' callback'], 'warn'); + + % Revert to the current value + curValue = ''; + try + if ~iscom(object(1)) + curValue = charizeData(get(object(1),cbName)); + else + cbs = object(1).eventlisteners; + if ~isempty(cbs) + cbs = cbs(strcmpi(cbs(:,1),cbName),:); + curValue = charizeData(cbs(1,2)); + end + end + catch + % never mind... - clear the current value + end + table.setValueAt(curValue, modifiedRowIdx, modifiedColIdx); + catch + % never mind... + end + end % revertCbTableModification + + %% Traverse an HG container hierarchy and extract the HG elements within + function traverseHGContainer(hcontainer,level,parent) + try + % Record the data for this node + thisIdx = length(hg_levels) + 1; + hg_levels(thisIdx) = level; + hg_parentIdx(thisIdx) = parent; + hg_handles(thisIdx) = handle(hcontainer); + parentId = length(hg_parentIdx); + + % Now recursively process all this node's children (if any) + %if ishghandle(hcontainer) + try % try-catch is faster than checking ishghandle(hcontainer)... + allChildren = allchild(handle(hcontainer)); + for childIdx = 1 : length(allChildren) + traverseHGContainer(allChildren(childIdx),level+1,parentId); + end + catch + % do nothing - probably not a container + %dispError + end + + % TODO: Add axis (plot) component handles + catch + % forget it... + end + end + + %% Debuggable "quiet" error-handling + function dispError + err = lasterror; + msg = err.message; + for idx = 1 : length(err.stack) + filename = err.stack(idx).file; + if ~isempty(regexpi(filename,mfilename)) + funcname = err.stack(idx).name; + line = num2str(err.stack(idx).line); + msg = [msg ' at ' funcname ' line #' line '']; %#ok grow + break; + end + end + disp(msg); + return; % debug point + end + + %% ML 7.0 - compatible ischar() function + function flag = ischar(data) + try + flag = builtin('ischar',data); + catch + flag = isa(data,'char'); + end + end + + %% Set up the uitree context (right-click) menu + function jmenu = setTreeContextMenu(obj,node,tree_h) + % Prepare the context menu (note the use of HTML labels) + import javax.swing.* + titleStr = getNodeTitleStr(obj,node); + titleStr = regexprep(titleStr,'

.*',''); + menuItem0 = JMenuItem(titleStr); + set(menuItem0,'Enabled','off','Armed','off'); + menuItem1 = JMenuItem('Export handle to findjobj_hdls'); + menuItem2 = JMenuItem('Export handle to...'); + menuItem3 = JMenuItem('Request focus (bring to front)'); + menuItem4 = JMenuItem('Flash component borders'); + menuItem5 = JMenuItem('Display properties & callbacks'); + menuItem6 = JMenuItem('Inspect object'); + + % Set the menu items' callbacks + set(menuItem1,'ActionPerformedCallback',{@btExport_Callback,{obj,'findjobj_hdls'}}); + set(menuItem2,'ActionPerformedCallback',{@btExport_Callback,{obj,[]}}); + set(menuItem3,'ActionPerformedCallback',{@requestFocus,obj}); + set(menuItem4,'ActionPerformedCallback',{@flashComponent,{obj,0.2,3}}); + set(menuItem5,'ActionPerformedCallback',{@nodeSelected,{tree_h,node}}); + set(menuItem6,'ActionPerformedCallback',{@btInspect_Callback,obj}); + + % Add all menu items to the context menu (with internal separator) + jmenu = JPopupMenu; + jmenu.add(menuItem0); + jmenu.addSeparator; + handleValue=[]; try handleValue = double(obj); catch, end; %#ok + if ~isempty(handleValue) + % For valid HG handles only + menuItem0a = JMenuItem('Copy handle value to clipboard'); + set(menuItem0a,'ActionPerformedCallback',sprintf('clipboard(''copy'',%.99g)',handleValue)); + jmenu.add(menuItem0a); + end + jmenu.add(menuItem1); + jmenu.add(menuItem2); + jmenu.addSeparator; + jmenu.add(menuItem3); + jmenu.add(menuItem4); + jmenu.add(menuItem5); + jmenu.add(menuItem6); + end % setTreeContextMenu + + %% Set the mouse-press callback + function treeMousePressedCallback(hTree, eventData, tree_h) %#ok hTree is unused + if eventData.isMetaDown % right-click is like a Meta-button + % Get the clicked node + clickX = eventData.getX; + clickY = eventData.getY; + jtree = eventData.getSource; + treePath = jtree.getPathForLocation(clickX, clickY); + try + % Modify the context menu based on the clicked node + node = treePath.getLastPathComponent; + userdata = get(node,'userdata'); + obj = userdata.obj; + jmenu = setTreeContextMenu(obj,node,tree_h); + + % TODO: remember to call jmenu.remove(item) in item callback + % or use the timer hack shown here to remove the item: + % timerFcn = {@menuRemoveItem,jmenu,item}; + % start(timer('TimerFcn',timerFcn,'StartDelay',0.2)); + + % Display the (possibly-modified) context menu + jmenu.show(jtree, clickX, clickY); + jmenu.repaint; + + % This is for debugging: + userdata.tree = jtree; + setappdata(gcf,'findjobj_hgtree',userdata) + catch + % clicked location is NOT on top of any node + % Note: can also be tested by isempty(treePath) + end + end + end % treeMousePressedCallback + + %% Remove the extra context menu item after display + function menuRemoveItem(hObj,eventData,jmenu,item) %#ok unused + jmenu.remove(item); + end % menuRemoveItem + + %% Get the title for the tooltip and context (right-click) menu + function nodeTitleStr = getNodeTitleStr(obj,node) + try + % Display the full classname and object name in the tooltip + %nodeName = char(node.getName); + %nodeName = strrep(nodeName, '',''); + %nodeName = strrep(nodeName, '',''); + nodeName = char(getNodeName(obj,99)); + [objClass,objName] = strtok(nodeName); + objName = objName(3:end-1); % strip leading ( and trailing ) + if isempty(objName), objName = '(none found)'; end + nodeName = char(node.getName); + objClass = char(obj.getClass.getName); + nodeTitleStr = sprintf('Class name: %s
Text/title: %s',objClass,objName); + + % If the component is invisible, state this in the tooltip + if ~isempty(strfind(nodeName,'color="gray"')) + nodeTitleStr = [nodeTitleStr '
*** Invisible ***']; + end + nodeTitleStr = [nodeTitleStr '
Right-click for context-menu']; + catch + % Possible not a Java object - try treating as an HG handle + try + handleValueStr = sprintf('#: %.99g',double(obj)); + try + type = ''; + type = get(obj,'type'); + type(1) = upper(type(1)); + catch + if ~ishandle(obj) + type = ['Invalid ' char(node.getName) '']; + handleValueStr = '!!!
Perhaps this handle was deleted after this UIInspect tree was
already drawn. Try to refresh by selecting any valid node handle'; + end + end + nodeTitleStr = sprintf('%s handle %s',type,handleValueStr); + try + % If the component is invisible, state this in the tooltip + if strcmp(get(obj,'Visible'),'off') + nodeTitleStr = [nodeTitleStr '
Invisible']; + end + catch + % never mind... + end + catch + % never mind... - ignore + end + end + end % getNodeTitleStr + + %% Handle tree mouse movement callback - used to set the tooltip & context-menu + function treeMouseMovedCallback(hTree, eventData) + try + x = eventData.getX; + y = eventData.getY; + jtree = eventData.getSource; + treePath = jtree.getPathForLocation(x, y); + try + % Set the tooltip string based on the hovered node + node = treePath.getLastPathComponent; + userdata = get(node,'userdata'); + obj = userdata.obj; + tooltipStr = getNodeTitleStr(obj,node); + set(hTree,'ToolTipText',tooltipStr) + catch + % clicked location is NOT on top of any node + % Note: can also be tested by isempty(treePath) + end + catch + dispError; + end + return; % denug breakpoint + end % treeMouseMovedCallback + + %% Request focus for a specific object handle + function requestFocus(hTree, eventData, obj) %#ok hTree & eventData are unused + % Ensure the object handle is valid + if isjava(obj) + obj.requestFocus; + return; + elseif ~ishandle(obj) + msgbox('The selected object does not appear to be a valid handle as defined by the ishandle() function. Perhaps this object was deleted after this hierarchy tree was already drawn. Refresh this tree by selecting a valid node handle and then retry.','FindJObj','warn'); + beep; + return; + end + + try + foundFlag = 0; + while ~foundFlag + if isempty(obj), return; end % sanity check + type = get(obj,'type'); + obj = double(obj); + foundFlag = any(strcmp(type,{'figure','axes','uicontrol'})); + if ~foundFlag + obj = get(obj,'Parent'); + end + end + feval(type,obj); + catch + % never mind... + dispError; + end + end % requestFocus + + +end % FINDJOBJ + + +%% TODO TODO TODO +%{ +- Enh: Improve performance - esp. expandNode() (performance solved in non-nteractive mode) +- Enh: Add property listeners - same problem in MathWork's inspect.m +- Enh: Display additional properties - same problem in MathWork's inspect.m +- Enh: Add axis (plot, Graphics) component handles +- Enh: Group callbacks according to the first word (up to 2nd cap letter) +- Enh: Add figure thumbnail image below the java tree (& indicate corresponding jObject when selected) +- Enh: scroll initially-selected node into view (problem because treenode has no pixel location) +- Fix: java exceptions when getting some fields (com.mathworks.mlwidgets.inspector.PropertyRootNode$PropertyListener$1$1.run) +- Fix: use EDT if available (especially in flashComponent) +%} \ No newline at end of file diff --git a/3rdparty/jewelersLoupe.m b/3rdparty/jewelersLoupe.m new file mode 100644 index 0000000..dc222c2 --- /dev/null +++ b/3rdparty/jewelersLoupe.m @@ -0,0 +1,122 @@ +function jewelersLoupe(hFig) +%JEWELERSLOUPE modifies a figure to enable a Jeweler's Loupe tool. +% JEWELERSLOUPE(FIG) will modify the figure with handle FIG to allow a +% jeweler's loupe tool, which magnifies the axes by a factor of 4, to +% appear whenever a user clicks on an axes. Dragging will cause the loupe +% to follow the cursor. The tool assumes that any axes clicked will be a +% linear 2-D axes. Performance will degrade as the amount of data in the +% axes increates. If no figure is given, the loupe will appear in the +% current figure. +% +% Example: +% plot(magic(3)); +% jewelersLoupe(gcf); +% +% See also PAN, ZOOM. + +% Copyright 2008 The MathWorks, Inc. + +% If a figure has not been passed in, +if nargin < 1 + hFig = gcf; +end + +% Make sure we have a valid figure: +if ~ishandle(hFig) || ~strcmpi(get(hFig,'Type'),'figure') + error('JEWELERSLOUPE:INVALIDFIGURE',... + 'The first input argument must be a valid figure.'); +end + +% Set up the callback for the loupe: +set(hFig,'WindowButtonDownFcn',@localCreateLoupe); + +%------------------------------------------------------------------------% +function localCreateLoupe(hFig,evd) %#ok +% The loupe will appear for the current axes. +hAx = get(hFig,'CurrentAxes'); + +% If the axes is empty, we won't do anything. +if isempty(hAx) + return; +end + +% The loupe is implemented in terms of a separate axes: +hLoupe = axes('Parent',hFig,'Tag','loupe','HandleVisibility','off',... + 'XTickLabel','','YTickLabel','','XTick',[],'YTick',[],'Box','on'); +% Set up the initial loupe position: +localUpdateLoupePosition(hFig,hLoupe); + +% Copy the contents of the axes into the loupe: +copyobj(get(hAx,'Children'),hLoupe); + +% We will zoom by a factor of 4 into the loupe based on the current point +% in the axes. +localDoZoom(hLoupe,hAx); + +% Set callbacks for motion and button up: +set(hFig,'WindowButtonMotionFcn',{@localMoveLoupe,hAx,hLoupe}); +set(hFig,'WindowButtonUpFcn',{@localCleanUp,hLoupe}); + +%------------------------------------------------------------------------% +function localMoveLoupe(hFig,evd,hAx,hLoupe) %#ok +% Move the loupe based on the current point: +localUpdateLoupePosition(hFig,hLoupe); + +% Perform the zoom operation on the axes: +localDoZoom(hLoupe,hAx); + +%------------------------------------------------------------------------% +function localCleanUp(hFig,evd,hLoupe) %#ok +% Clean up after the loupe has finished execution: + +% Remove the callbacks: +set(hFig,'WindowButtonMotionFcn',''); +set(hFig,'WindowButtonUpFcn',''); + +% Delete the loupe: +delete(hLoupe); + +%------------------------------------------------------------------------% +function localUpdateLoupePosition(hFig,hLoupe) +% Moves the loupe based on the current point in the figure: + +% The loupe should be centered on the current location and take up 25% of +% the figure space. +oldUnits = get(hFig,'Units'); +set(hFig,'Units','Normalized'); +mousePoint = get(hFig,'CurrentPoint'); +set(hFig,'Units',oldUnits); +loupePosition = [(mousePoint-.125) .25 .25]; +set(hLoupe,'Position',loupePosition); + +%------------------------------------------------------------------------% +function localDoZoom(hLoupe,hAx) +% First, calculate the center based on the current point in the axes: +newCenter = get(hAx,'CurrentPoint'); +% We are assuming a 2-D axes, so we will take the first two coordinates. +newCenter = newCenter(1,1:2); + +% Zoom in by a factor of 4 around the given center point. +center_x = newCenter(1); +center_y = newCenter(2); + +% Start by zooming the X-limits: +origXLim = get(hAx,'XLim'); +xmin = origXLim(1); +xmax = origXLim(2); +dx = diff(origXLim); +newdx = dx * (1/4); +newdx = min(newdx,xmax-xmin); +newXLim = [center_x-newdx/2 center_x+newdx/2]; + +% Next, zoom the Y-limits: +origYLim = get(hAx,'YLim'); +ymin = origYLim(1); +ymax = origYLim(2); +dy = diff(origYLim); +newdy = dy * (1/4); +newdy = min(newdy,ymax-ymin); +newYLim = [center_y-newdy/2 center_y+newdy/2]; + +% Update the limits: +set(hLoupe,'XLim',newXLim,'YLim',newYLim); diff --git a/3rdparty/m2googlevis.m b/3rdparty/m2googlevis.m new file mode 100644 index 0000000..211794a --- /dev/null +++ b/3rdparty/m2googlevis.m @@ -0,0 +1,105 @@ +function htmlStr = m2googlevis(varargin) +%M2GOOGLEVIS creates html code for Google's visualization API +% +% htmlstr = m2googlevis('style','parm1',data1,...,'parmn',datan [,opts]) +% +% Inputs: +% ------- +% 'style' is a string from the following list which will choose the Google +% Visualization API package to use +% 'lineChart' +% 'scatterChart' +% +% 'parm' is a string giving the name of the variable to be plotted +% +% data is a vector (either a cell array of strings or a double) giving the +% corresponding data to be plotted +% +% opts is an optional structure with the following fields: +% legendLocn = location of the legend +% ('bottom','left','top','right','none') +% title = The title of the plot +% +% Outputs: +% -------- +% htmlStr is a a character string which can be saved directly to an HTML +% file for web display + +% title - m2googlevis.m author - Adam Leadbetter (alead@bodc.ac.uk) +% version - 0.2 date - 2008Dec18 +% +% Revisions +% --------- +% 0.2 2008Dec22 Adam Leadbetter - Added scatterChart +% + a = ['''' repmat('%s ', 1, 5) '''']; +% +% Check the invocation +% TODO: Check that all the inputs are of the same length +% + if(isstruct(varargin{end})) + opts = varargin{end}; + varargin(end) = []; + else + opts.legendLocn = 'right'; + opts.title = ''; + end + htmlStr = ['']; + htmlStr = [htmlStr '
']; \ No newline at end of file diff --git a/3rdparty/magnify.m b/3rdparty/magnify.m new file mode 100644 index 0000000..e9350fd --- /dev/null +++ b/3rdparty/magnify.m @@ -0,0 +1,139 @@ +function magnify(f1) +% +%magnify(f1) +% +% Figure creates a magnification box when under the mouse +% position when a button is pressed. Press '+'/'-' while +% button pressed to increase/decrease magnification. Press +% '>'/'<' while button pressed to increase/decrease box size. +% Hold 'Ctrl' while clicking to leave magnification on figure. +% +% Example: +% plot(1:100,randn(1,100),(1:300)/3,rand(1,300)), grid on, +% magnify; + +% Rick Hindman - 7/29/04 + +if (nargin == 0), f1 = gcf; end; +set(f1, ... + 'WindowButtonDownFcn', @ButtonDownCallback, ... + 'WindowButtonUpFcn', @ButtonUpCallback, ... + 'WindowButtonMotionFcn', @ButtonMotionCallback, ... + 'KeyPressFcn', @KeyPressCallback); +return; + +function ButtonDownCallback(src,eventdata) + f1 = src; + a1 = get(f1,'CurrentAxes'); + a2 = copyobj(a1,f1); + + set(f1, ... + 'UserData',[f1,a1,a2], ... + 'Pointer','fullcrosshair', ... + 'CurrentAxes',a2); + set(a2, ... + 'UserData',[2,0.2], ... %magnification, frame size + 'Color',get(a1,'Color'), ... + 'Box','on'); + xlabel(''); ylabel(''); zlabel(''); title(''); + set(get(a2,'Children'), ... + 'LineWidth', 2); + set(a1, ... + 'Color',get(a1,'Color')*0.95); + set(f1, ... + 'CurrentAxes',a1); + ButtonMotionCallback(src); +return; + +function ButtonUpCallback(src,eventdata) + H = get(src,'UserData'); + f1 = H(1); a1 = H(2); a2 = H(3); + set(a1, ... + 'Color',get(a2,'Color')); + set(f1, ... + 'UserData',[], ... + 'Pointer','arrow', ... + 'CurrentAxes',a1); + if ~strcmp(get(f1,'SelectionType'),'alt'), + delete(a2); + end; +return; + +function ButtonMotionCallback(src,eventdata) + H = get(src,'UserData'); + if ~isempty(H) + f1 = H(1); a1 = H(2); a2 = H(3); + a2_param = get(a2,'UserData'); + f_pos = get(f1,'Position'); + a1_pos = get(a1,'Position'); + + [f_cp, a1_cp] = pointer2d(f1,a1); + + set(a2,'Position',[(f_cp./f_pos(3:4)) 0 0]+a2_param(2)*a1_pos(3)*[-1 -1 2 2]); + a2_pos = get(a2,'Position'); + + set(a2,'XLim',a1_cp(1)+(1/a2_param(1))*(a2_pos(3)/a1_pos(3))*diff(get(a1,'XLim'))*[-0.5 0.5]); + set(a2,'YLim',a1_cp(2)+(1/a2_param(1))*(a2_pos(4)/a1_pos(4))*diff(get(a1,'YLim'))*[-0.5 0.5]); + end; +return; + +function KeyPressCallback(src,eventdata) + H = get(gcf,'UserData'); + if ~isempty(H) + f1 = H(1); a1 = H(2); a2 = H(3); + a2_param = get(a2,'UserData'); + if (strcmp(get(f1,'CurrentCharacter'),'+') | strcmp(get(f1,'CurrentCharacter'),'=')) + a2_param(1) = a2_param(1)*1.2; + elseif (strcmp(get(f1,'CurrentCharacter'),'-') | strcmp(get(f1,'CurrentCharacter'),'_')) + a2_param(1) = a2_param(1)/1.2; + elseif (strcmp(get(f1,'CurrentCharacter'),'<') | strcmp(get(f1,'CurrentCharacter'),',')) + a2_param(2) = a2_param(2)/1.2; + elseif (strcmp(get(f1,'CurrentCharacter'),'>') | strcmp(get(f1,'CurrentCharacter'),'.')) + a2_param(2) = a2_param(2)*1.2; + end; + set(a2,'UserData',a2_param); + ButtonMotionCallback(src); + end; +return; + + + +% Included for completeness (usually in own file) +function [fig_pointer_pos, axes_pointer_val] = pointer2d(fig_hndl,axes_hndl) +% +%pointer2d(fig_hndl,axes_hndl) +% +% Returns the coordinates of the pointer (in pixels) +% in the desired figure (fig_hndl) and the coordinates +% in the desired axis (axes coordinates) +% +% Example: +% figure(1), +% hold on, +% for i = 1:1000, +% [figp,axp]=pointer2d; +% plot(axp(1),axp(2),'.','EraseMode','none'); +% drawnow; +% end; +% hold off + +% Rick Hindman - 4/18/01 + +if (nargin == 0), fig_hndl = gcf; axes_hndl = gca; end; +if (nargin == 1), axes_hndl = get(fig_hndl,'CurrentAxes'); end; + +set(fig_hndl,'Units','pixels'); + +pointer_pos = get(0,'PointerLocation'); %pixels {0,0} lower left +fig_pos = get(fig_hndl,'Position'); %pixels {l,b,w,h} + +fig_pointer_pos = pointer_pos - fig_pos([1,2]); +set(fig_hndl,'CurrentPoint',fig_pointer_pos); + +if (isempty(axes_hndl)), + axes_pointer_val = []; +elseif (nargout == 2), + axes_pointer_line = get(axes_hndl,'CurrentPoint'); + axes_pointer_val = sum(axes_pointer_line)/2; +end; + diff --git a/@int32/sparse.m b/@int32/sparse.m new file mode 100644 index 0000000..e26bda1 --- /dev/null +++ b/@int32/sparse.m @@ -0,0 +1,11 @@ +function [varargout]=sparse(varargin) +switch nargin + case 1 + varargout={sparse(double(varargin{1}))}; + case 2 + varargout{1}=sparse(double(varargin{1}),double(varargin{2})); + case 3 + varargout{1}=sparse(double(varargin{1}),double(varargin{2}),double(varargin{3})); + case 5 + varargout{1}=sparse(double(varargin{1}),double(varargin{2}),double(varargin{3}),double(varargin{4}),double(varargin{5})); +end diff --git a/FindConstInMFiles.m b/FindConstInMFiles.m new file mode 100644 index 0000000..a8b2d20 --- /dev/null +++ b/FindConstInMFiles.m @@ -0,0 +1,58 @@ +function FindConstInMFiles +%FindConstInMFiles() finds the contant variables in .m files +% FindConstInMFiles() searches in all the .m files under a chosen directory and +% writes to an output file (results.txt) all the assignments of constant +% values to variables. The core of the programme is the regular expression. +% Everything else is just a recursive algorithm to search all the files. +% Regular expression: [a-zA-Z][\.\w+]*\s*=\s*[\.\d]+([eE][\+\-]?\d+)?\s*[;\n] +% [a-zA-Z] : variables have to start with a letter +% [\.\w+]* : to take into account structure variables +% *\s*=\s* : multiple spaces before and/or after the '=' sign +% [\.\d]+ : number with or without decimal separation +% ([eE][\+\-]?\d+)? : exponential symbol, +/- characters, number +% \s*[;\n] : white-spaces, end of statement, end of line + +clc; +clear; +DirPath = uigetdir(); % Get directory where to search +if ~DirPath, return, end +fid = fopen('results.txt','wt'); % open output file +if fid == -1 + disp('Error creating output file') + return +end +StartFind(DirPath,fid); %start search for files +fclose(fid); % close output file + +%% StartFind +function StartFind(DirPath,fid) +DirContent = dir(DirPath); % gets the content of the current directory +files = {DirContent(~[DirContent.isdir]').name}; % gets only the files +folders = {DirContent([DirContent.isdir]').name}; % gets only the directories +for i = 1:length(files) % for all the files + file = fullfile(DirPath,files{i}); % get the full file name + [pathstr, name, ext] = fileparts(files{i}); % get the extension + if ~strcmp(ext,'.m') % Test for .m extension and continue to next file if it's not + continue + end + FileContent = fileread(file); % read to a string the contents of the files + [str ind] = regexp(FileContent,'[a-zA-Z][\.\w+]*\s*=\s*[\.\d]+([eE][\+\-]?\d+)?\s*[;\n]','match','start'); % regular expression + if ~isempty(str) % if there are valid results... + fprintf(fid,'\n%s\n',file); % Print the file name + endofline = regexp(FileContent,'\n','start'); % Get all the indexes of all the lines + for j = 1:length(str) % for all valid results... + fprintf(fid,'Line %d: %s\n',find(ind(j)0)) +set(hp, 'FaceAlpha', 'interp') +axis image +if NewAxes + view(60,30) +end + +end + + +% Axial View -------------------------------- +if get(mriHandles.axial3D,'value') + + X = linspace(0,MRI.FOV(1),size(MRI.Cube,1)); + Y = linspace(0,MRI.FOV(2),size(MRI.Cube,2)); + Z = mriCoord(3)*ones(length(X), length(Y)); + hhh = surf(X,Y,Z); + set(hhh,'visible','off') + %set(hhh,'visible','on','Cdata',double(MRI.Cube(:,:,newIndices(3)))','edgecolor','none') + %hold on + x = get(hhh,'xdata'); + y = get(hhh,'ydata'); + X = repmat(x,length(y),1); + Y = repmat(y',1,length(x)); + x = X(:); y = Y(:); z = Z(:); + + [transf,scsCoord] = mri2scs(MRI,[x,y,z]'); + scsCoord = scsCoord/1000; + + X = (reshape(scsCoord(1,:),size(MRI.Cube,1),size(MRI.Cube,2))); + Y = (reshape(scsCoord(2,:),size(MRI.Cube,1),size(MRI.Cube,2))); + Z = (reshape(scsCoord(3,:),size(MRI.Cube,1),size(MRI.Cube,2))); + % figure, hold on + hhh = surf(X,Y,Z); + set(hhh,'visible','off') + + if isempty(mriImages.Axial) % Fisrt time 3D visualization of MR slices was called + figure(h3D), hold on + mriImages.Axial = surf(X,Y,Z); + %setappdata(h3D,'mriImages',mriImages) + else + mriImages = getappdata(h3D,'mriImages'); + end + + CData = double(MRI.Cube(:,:,newIndices(3)))'; + CData = CData/max(CData(:)); + CData(CData < (min(CData(:))+1*std(CData(:)))) = NaN; + set(mriImages.Axial,'Xdata',X,'Ydata',Y,'ZData',Z,'Cdata',CData,'edgecolor','none','facelighting','none') + +else + if ~isempty(mriImages.Axial) % Remove from visualization + delete(mriImages.Axial) + mriImages.Axial = []; + end +end + +% Sagittal View -------------------------------- +if get(mriHandles.sagittal3D,'value') + + Y = linspace(0,MRI.FOV(2),size(MRI.Cube,2)); + Z = linspace(0,MRI.FOV(3),size(MRI.Cube,3)); + X = mriCoord(1)*ones(length(Y), length(Z)); + + hhh = surf(Y,Z,X); + set(hhh,'visible','off') + %set(hhh,'visible','on','Cdata',double(MRI.Cube(:,:,newIndices(3)))','edgecolor','none') + %hold on + y = get(hhh,'xdata'); + z = get(hhh,'ydata'); + Y = repmat(y,length(z),1); + Z = repmat(z',1,length(y)); + x = X(:); y = Y(:); z = Z(:); + + [transf,scsCoord] = mri2scs(MRI,[x,y,z]'); + scsCoord = scsCoord/1000; + + X = (reshape(scsCoord(1,:),size(MRI.Cube,2),size(MRI.Cube,3))); + Y = (reshape(scsCoord(2,:),size(MRI.Cube,2),size(MRI.Cube,3))); + Z = (reshape(scsCoord(3,:),size(MRI.Cube,2),size(MRI.Cube,3))); + % figure, hold on + hhh = surf(X,Y,Z); + set(hhh,'visible','off') + + if isempty(mriImages.Sagittal) % Fisrt time 3D visualization of MR slices was called + figure(h3D), hold on + mriImages.Sagittal = surf(X,Y,Z); + %setappdata(h3D,'mriImages',mriImages) + else + mriImages = getappdata(h3D,'mriImages'); + end + CData = double(squeeze(MRI.Cube(newIndices(1),:,:)))'; + CData = CData/max(CData(:)); + CData(CData < (min(CData(:))+1*std(CData(:)))) = NaN; + set(mriImages.Sagittal,'Xdata',X,'Ydata',Y,'ZData',Z,'Cdata',CData,'edgecolor','none','facelighting','none') + +else + if ~isempty(mriImages.Sagittal) % Remove from visualization + delete(mriImages.Sagittal) + mriImages.Sagittal = []; + end +end + + +% Coronal View -------------------------------- +if get(mriHandles.coronal3D,'value') + + X = linspace(0,MRI.FOV(1),size(MRI.Cube,1)); + Z = linspace(0,MRI.FOV(3),size(MRI.Cube,3)); + Y = mriCoord(2)*ones(length(X), length(Z)); + + hhh = surf(X,Z,Y); + set(hhh,'visible','off') + %set(hhh,'visible','on','Cdata',double(MRI.Cube(:,:,newIndices(3)))','edgecolor','none') + %hold on + x = get(hhh,'xdata'); + z = get(hhh,'ydata'); + X = repmat(x,length(z),1); + Z = repmat(z',1,length(x)); + x = X(:); y = Y(:); z = Z(:); + + [transf,scsCoord] = mri2scs(MRI,[x,y,z]'); + scsCoord = scsCoord/1000; + + X = (reshape(scsCoord(1,:),size(MRI.Cube,2),size(MRI.Cube,3))); + Y = (reshape(scsCoord(2,:),size(MRI.Cube,2),size(MRI.Cube,3))); + Z = (reshape(scsCoord(3,:),size(MRI.Cube,2),size(MRI.Cube,3))); + % figure, hold on + hhh = surf(X,Y,Z); + set(hhh,'visible','off') + + if isempty(mriImages.Coronal) % Fisrt time 3D visualization of MR slices was called + figure(h3D), hold on + mriImages.Coronal = surf(X,Y,Z); + %setappdata(h3D,'mriImages',mriImages) + else + mriImages = getappdata(h3D,'mriImages'); + end + + CData = double(squeeze(MRI.Cube(:,newIndices(2),:)))'; + CData = CData/max(CData(:)); + CData(CData < (min(CData(:))+1*std(CData(:)))) = NaN; + set(mriImages.Coronal,'Xdata',X,'Ydata',Y,'ZData',Z,'Cdata',CData,'edgecolor','none','facelighting','none') + + +else + if ~isempty(mriImages.Coronal) % Remove from visualization + delete(mriImages.Coronal) + mriImages.Coronal = []; + end +end +set(h3D, 'colormap',bone(ngray)) diff --git a/Plot2dHist.m b/Plot2dHist.m new file mode 100644 index 0000000..f388cf9 --- /dev/null +++ b/Plot2dHist.m @@ -0,0 +1,37 @@ +%function Plot2dHist(mHist2d, vEdgeX, vEdgeY, strLabelX, strLabelY, strTitle) +%Shows 2d histogram in p-color map +%Example +% mYX = rand(10000,2); +% vXEdge = linspace(0,1,100); +% vYEdge = linspace(0,1,200); +% mHist2d = hist2d(mYX,vYEdge,vXEdge); +% +% Plot2dHist(mHist2d, vXEdge, vYEdge, 'X', 'Y', 'Example'); colorbar +function Plot2dHist(mHist2D, vEdgeX, vEdgeY, strLabelX, strLabelY, strTitle) + +nEdgeX = length(vEdgeX)-1; +nEdgeY = length(vEdgeY)-1; + +rMinX = min(vEdgeX); +rMaxX = max(vEdgeX); + +rMinY = min(vEdgeY); +rMaxY = max(vEdgeY); + +rDeltaX = (vEdgeX(2)-vEdgeX(1)); +rDeltaY = (vEdgeY(2)-vEdgeY(1)); + +vLabelX = (rMinX+0.5*rDeltaX):rDeltaX:(rMaxX-0.5*rDeltaX); +vLabelY = (rMinY+0.5*rDeltaY):rDeltaY:(rMaxY-0.5*rDeltaY); + +pcolor (vLabelX, vLabelY, mHist2D); +shading interp; colorbar; + +grid on; + +xlabel(strLabelX); +ylabel(strLabelY); + +axis([rMinX, rMaxX, rMinY, rMaxY]); + +title(strTitle) diff --git a/Tr2event.m b/Tr2event.m new file mode 100644 index 0000000..57c8e19 --- /dev/null +++ b/Tr2event.m @@ -0,0 +1,35 @@ +function [event]=Tr2event(Tr) + +disp('Calculating events...') +for i=1:Tr(1).nb + event(i).ref=Tr(1).a(i); + event(i).tstim=Tr(2).t(i); + event(i).tresp=0; + event(i).choice=0; + event(i).bad=1; %Eventually BAD, if not answered +end + +% Scanning responses +for i=1:Tr(10).nb + j=1+Tr(10).a(i); + event(j).tresp=Tr(10).t(i); + event(j).bad=0; % Not a bad one +end + + +% Which stim type was shown ? +for k=5:9 +for i=1:Tr(k).nb +j=1+Tr(k).a(i); +event(j).type=k; +event(j).length=k*.105-0.035; +end +end + +% Which answer was given ? +for k=3:4 +for i=1:Tr(k).nb +event(1+Tr(k).a(i)).choice=7-2*k; % No response = 0 ; ok = +1 ; no = -1 +end +end + diff --git a/WhatsThisImage.m b/WhatsThisImage.m new file mode 100644 index 0000000..9aa5be3 --- /dev/null +++ b/WhatsThisImage.m @@ -0,0 +1,74 @@ +function [html] = WhatsThisImage(filename,keywords,varargin) +%WHATSTHISIMAGE - Try to find a amtching image on the web +% [] = WhatsThisImage(filename) +% +% Example +% >> WhatsThisImage +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-02 Creation +% +% ----------------------------- Script History --------------------------------- + +filename = 'http://tbn2.google.com/images?q=tbn:PkiyfXuSo4dVIM:http://www.simpsonstrivia.com.ar/simpsons-photos/wallpapers/homer-simpson-wallpaper-brain-1024.jpg'; +keywords = 'brain' + +query = 'http://images.google.com/images?'; +params.q=keywords; +params.language = []; +params.tab = 'wi'; + +for f=fieldnames(params)' + if isfield(params, f{1}) && ~isempty(params.(f{1})) + query = [ query '&' f{1} '=' params.(f{1}) ]; + end +end +query +start=0 +for ipage = 1:2 + html = urlread(query); +end + +javaaddpath(fullfile(pwd,'googleapi','googleapi.jar')) + +%key = 'xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'; +setpref('google','key',key); + + +% Setup. +googleSearch = com.google.soap.search.GoogleSearch; +key = getpref('google','key',''); +if isempty(key) + error(sprintf('%s\n%s', ... +'No key set. You need to get an access key from Google and set it like this:', ... +'setpref(''google'',''key'',''xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx'');')); +end +googleSearch.setKey(key); +googleSearch.setQueryString(q); +googleSearch.setFilter(filter); + + + +function score = matching(im1,im2) +% Brutye foprce approach : pixel-based correlation in greyscale... +score = 0; +im1=normimage(im1); +im2=normimage(im2); +if ~isequal(size(im1),size(im2)) + return +end + + +sc = corrcoef(im1,im2) + +function x = normimage(im) +x = normalize(mean(double(im),3), 'unity', [1:2]); diff --git a/WilcoxonSRPVs.m b/WilcoxonSRPVs.m new file mode 100644 index 0000000..1476ca3 --- /dev/null +++ b/WilcoxonSRPVs.m @@ -0,0 +1,104 @@ +function [T,pvl,pvr,pvz,R,supp,cdf] = WilcoxonSRPVs(Z,Y); +% [T,pvl,pvr,pvzR,supp,cdf] = WilcoxonSRPVs(Z) +% computes for a data vector Z Wilcoxon's signed-rank +% test statistic +% T = sum_{i=1}^n sign(Z(i)) R(i) , +% where R(i) denotes the rank of |Z(i)| among the non-zero +% components of (|Z(1)|, |Z(2)|, |Z(3)|, ..., |Z(n)|). +% +% In case of Z(i) = 0 we set R(i) = 0, i.e. components equal +% to zero are ignored. +% +% In case of ties among the absolute values of Z's components, +% we use the usual convention of mean ranks. +% +% In case of two input arguments, say X and Y, the program +% WilcoxonSRPVs(X,Y) works with Z := X - Y. +% +% In addition we compute left-, right- and two-sided P-values +% pvl = Pr(T_o <= T) , +% pvr = Pr(T_o >= T) , +% pvz = 2 * min(pvl, pvr) . +% Here T_o = sum_{i=1}^n S(i)*R(i) with independent random signs +% S(1), S(2), ..., S(n), while R is viewed temporarily as a fixed +% vector. +% +% Additional output arguments are +% - supp : a vector containing all support points of the +% distribution function F(.) := Pr(T_o <= .), +% - cdf : a vector containing the numbers cdf(i) = F(supp(i)). +% +% Lutz Duembgen, March 26, 2003 + +if nargin == 2 + Z = Z - Y; +end + +R = abs(Z); +S = sign(Z); +JJ = find(R > 0); +R(JJ) = LocalRanks(R(JJ)); +T = sum(sign(Z).*R); + +N = length(JJ); +R2 = ceil(2*sort(R(JJ))); +h2 = N*(N+1); +h1 = ceil(h2/2); +% Now we work temporarily with the test statistic +% T2 = T + N(N+1)/2 +% = sum_{i=1}^N 1{Z(i) > 0} 2R(i) +% taking values in {0,1,...,N(N+1)}: +cdf = ones(1,h2+1); +m = 1; +for i=1:N + m_new = m+R2(i); + cdf(R2(i)+1:m_new) = (cdf(1:m) + cdf(R2(i)+1:m_new))/2; + cdf(1:R2(i)) = cdf(1:R2(i))/2; + m = m_new; +end + +if nargout >= 6 + supp = [0:h2] - h1; +end + +ind = h1 + T + 1; +pvl = cdf(ind); +if ind >= 2 + pvr = 1 - cdf(ind-1); +else + pvr = 1; +end +pvz = 2*min(pvl,pvr); + +if nargout==0 + fprintf(1,'Test statistic : %5.1f\n', T) + fprintf(1,'(standardized : %6.3f)\n', T/norm(R)) + fprintf(1,'Left-sided P-value : %6.4f\n', pvl) + fprintf(1,'Right-sided P-Value : %6.4f\n', pvr) + fprintf(1,'Two-sided P-Value : %6.4f\n', pvz) +end +return + + +function rv = LocalRanks(x); +% rv = LocalRanks(x) +% computes the vector rv of ranks of x with the usual +% convention of averaging ranks in case of ties. +% +% Lutz Duembgen, 23.02.1999 + +n = length(x); +rv = zeros(size(x)); + +[hv,ar] = sort(x); + +a = 1; +for b=2:n + if hv(b) > hv(a) + hv(a:b-1) = (a+b-1)/2; + a = b; + end; +end; +hv(a:n) = (a+n)/2; +rv(ar) = hv; +return diff --git a/absolutepath.m b/absolutepath.m new file mode 100644 index 0000000..1a07179 --- /dev/null +++ b/absolutepath.m @@ -0,0 +1,156 @@ +function [a] = absolutepath(r,p,c) +%ABSOLUTEPATH() - Returns the absolute path +% +% a = absolutepath(r,p) returns a char array a giving absolute path of r +% (relatively to path p, if not given relatively to current path ) +% +% a = absolutepath(r,p,c) indicates the computer type to work in +% c can be 'PCWIN'|'GLNX86' (see: computer). Default is to use current +% environment. +% If [c] == 1, absolutepath will try to move in the resulting path [a] so +% as to clean of any relative (e.g., '..') and symbolic links in [a] +if nargin < 3 + c = computer; +end +if nargin < 2 + p = cd; +end +a=p; +if nargin<1 + return +end + +if ispc + % Windows is not case-sensitive! + p=lower(p); + r=lower(r); +end +if isabsolute(r,c) + % if nargin < 2 + warning('Input path is already an absolute path: %s', r) + % else + % error('Cannot set r relatively to path p for it is already an absolute path: %s', r) + % end + a = r; +else + if isequal(c, 'PCWIN') || (isequal(c,1) && ispc) + filesep = '\'; + if length(r)>1 && isequal(r(1), filesep) + % In windows '\bla' is ambiguous about the drive + if isequal(p(2), ':') + p=p(1:2); + else isequal(p(1:2), [filesep filesep]) + p=[ filesep filesep strtok(p, filesep)]; + end + end + else + a=fullfile(p,r); +end + +if isequal(c,1) + lcd=cd; + cd(a); + a=cd; + cd(lcd); +end + +return + +function tf = isabsolute(p,c) +% Test if path p is an absolute path in the current environment +tf = true; +if isequal(c,1) + c = computer; +end +switch c + case 'GLNX86' + filesep = '/'; + if ~isempty(p) && ( isequal(p(1), filesep) || isequal(p(1), '~')) + % In Unix /bla is absolute as well as '~/bla' + % (whereas in Windows \bla doesn't specify the drive) + return; + end + case 'PCWIN' + filesep = '\'; + if length(p)>1 && ... + ( isequal(p(1:2),[ filesep filesep ]) || ... + isequal(p(1:2),[ ':' filesep ]) ) + % C:\bla\... or \\network\... schemes in windows + return; + end +end +tf=false; +return + + +if ispc + if length(p)>0 && isequal(p(1), filesep) + p = strtok(cd, filesep); + end +end + + + +if ispc + if length(p)>1 && isequal(p(2), ':') + + elseif length(p)>1 && isequal(p(2), filesep) + % network location + + end + +end + +% Predefine return string: +abs_path = ''; + +% Make sure strings end by a filesep character: +if length(act_path) == 0 | ~isequal(act_path(end),filesep) + act_path = [act_path filesep]; +end +if length(rel_path) == 0 | ~isequal(rel_path(end),filesep) + rel_path = [rel_path filesep]; +end + +% Convert to all lowercase: +[act_path] = fileparts( lower(act_path) ); +[rel_path] = fileparts( lower(rel_path) ); + +% Create a cell-array containing the directory levels: +act_path_cell = pathparts(act_path); +rel_path_cell = pathparts(rel_path); +abs_path_cell = act_path_cell; + +% Combine both paths level by level: +while length(rel_path_cell) > 0 + if isequal( rel_path_cell{1} , '.' ) + rel_path_cell( 1) = []; + elseif isequal( rel_path_cell{1} , '..' ) + abs_path_cell(end) = []; + rel_path_cell( 1) = []; + else + abs_path_cell{end+1} = rel_path_cell{1}; + rel_path_cell(1) = []; + end +end + +% Put cell array into string: +for i = 1 : length(abs_path_cell) + abs_path = [abs_path abs_path_cell{i} filesep]; +end + +return + +% ------------------------------------------------- + +function path_cell = pathparts(path_str) + +path_str = [filesep path_str filesep]; +path_cell = {}; + +sep_pos = findstr( path_str, filesep ); +for i = 1 : length(sep_pos)-1 + path_cell{i} = path_str( sep_pos(i)+1 : sep_pos(i+1)-1 ); +end + +return \ No newline at end of file diff --git a/affinetransform.m b/affinetransform.m new file mode 100644 index 0000000..3a47d81 --- /dev/null +++ b/affinetransform.m @@ -0,0 +1,72 @@ +function [varargout]=affinetransform(x,varargin) +% affinetransform - Apply affine transformation to 3D points +% [y,m,m2]=affinetransform(x,m) +% [y,m,m2]=affinetransform(x,r,t) +% [x,m,m2]=affinetransform(y,-1,m) or affinetransform(y,-1,r,t) +% [m,m2]=affinetransform([],r,t) +% x and y are the Nx3 coordinates +% r is the TRANSPOSED rotation matrix (see infra) or the rotation vector: [ux uy uz angle] +% t is the transposed (i.e. horizontal) translation vector +% m is the rotation/translation matrix: m = [r ; t] = [R' ; T'] +% m2 is the inverse transformation: m2 = [r'; -t*r'] +% the [-1] flag will apply the inverse transfo m2 (see infra) +% +% The classical formula for vertical vectors: +% Y = R * X + T +% is simplified into the following: +% y = [x 1]*m = [x*r]+t = [X'*R]+T' +% with: +% y and x are N-by-3 matrices (i.e. horizontal vectors) +% r = R' +% t = T' +% m = [r ; t] = [R T]' +% +% The [-1] flag apply the inverse transformation so that: +% X = R^-1 * ( Y - T) +% i.e: +% x = r' * [y' - t'] + +ninput=nargin-1; +if isequal(varargin{1}, -1) + InverseTransfo = 1; + varargin(1)=[]; + ninput=ninput-1; +else + InverseTransfo = 0; +end + +switch ninput + case 1 + m=varargin{1}; + r=m(1:3,:); + t=m(4,:); + case 2 + if isequal(size(varargin{1}), [1 4]) + u=varargin{1}; + cosa = cos(u(4)); + sina = sin(u(4)); + vera = 1 - cosa; + x = u(1); y = u(2); z = u(3); + r = [cosa+x^2*vera , x*y*vera-z*sina , x*z*vera+y*sina; ... + x*y*vera+z*sina , cosa+y^2*vera , y*z*vera-x*sina; ... + x*z*vera-y*sina , y*z*vera+x*sina , cosa+z^2*vera]'; + else + r=varargin{1}; + end + t = varargin{2}; + + otherwise + error('Invalid number of inputs') +end +m=[r ; t]; +m2 = [r'; -t*r']; +if isempty(x) + varargout={m,m2}; + return +end +if InverseTransfo + y=[x ones(size(x,1),1)]*m2; +else + y=[x ones(size(x,1),1)]*m; +end +varargout={y,m,m2}; \ No newline at end of file diff --git a/allhandles.m b/allhandles.m new file mode 100644 index 0000000..11f4f80 --- /dev/null +++ b/allhandles.m @@ -0,0 +1,47 @@ +function [H,exclude] = allhandles(A,varargin) +%ALLHANDLES - Handles of existing objects only +% [H] = allhandles(A) +% Returns in vector H only handles to existing objects from A +% +% [H,exclude] = allhandles(A, 'Property', Value, ...) +% Retrieves only those handles whose Property/ies match the Value(s) + +% Example +% >> allhandles(0:10) +% >> allhandles(findobj(0), 'type', 'line') +% +% See also: ishandle, nonzeros + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-22 Creation +% +% ----------------------------- Script History --------------------------------- + +% to do: varargin : only handles matching some criterion. +% eg. (tag, 'something') or ('visible', 'on') + +H=A(ishandle(A)); +exclude = []; +if nargin>1 + exclude=zeros(size(H)); + for i=1:numel(H) + for j=1:2:(nargin-1) + try + if ~isequal(get(H(i),varargin{j}), varargin{j+1}) + exclude(i) = j; + break + end + catch + exclude(i)=-1; + end + end + end + H=H(~exclude); +end \ No newline at end of file diff --git a/allthesame.m b/allthesame.m new file mode 100644 index 0000000..60843ac --- /dev/null +++ b/allthesame.m @@ -0,0 +1,60 @@ +function tf = allthesame(A,dim) +%ALLTHESAME - True if all elements are identical +% [TF] = allthesame(A) +% [TF] = allthesame(A,dim) +% Works only on numerical/char array (not cells) +% +% Example +% >> allthesame +% +% See also: unique, nonunique + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-10 Creation +% +% ----------------------------- Script History --------------------------------- + +s=size(A); +if nargin<2 + dim=[]; +end +if isempty(dim) + if sum(s)==max(s) + [ign,dim]=max(s); + else + dim=1; + end +end +if dim>1 + p=[dim setdiff(1:ndims(A),dim)]; + A=permute(A,p); + s=[s(p) 1]; +end +if iscell(A) + ncol=prod(s(2:end)); + tf = logical(zeros(s(1)-1,ncol)); + for j=1:ncol + for i=2:s(1) + tf(i-1,j)=isequal(A(1,j),A(i,j)); + if ~tf(i-1,j) + % don't explore the remaining lines for this column + break; + end + end + end +else + tf = A(2:end,:)==repmat(A(1,:),s(1)-1,1); +end +tf=all(tf,1); +tf=reshape(tf, [1 s(2:end)]); +if dim>1 + tf=ipermute(tf,p); +end +return diff --git a/allunique.m b/allunique.m new file mode 100644 index 0000000..0fc9a85 --- /dev/null +++ b/allunique.m @@ -0,0 +1,31 @@ +function [T,I,U] = allunique(X) +%ALLUNIQUE - Tests if all elements are unique (no duplicate) +% [T,I,U] = allunique(X) +% +% Inputs: +% X: matrix/vector +% Outputs: +% T: is 1 if there is no duplicated element in X +% I: indices of the non-unique elements +% U: list of unique elements: U =unique(X) +% Example +% >> allunique +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-07-09 Creation +% +% ----------------------------- Script History --------------------------------- +U=unique(X(:)); +T=numel(U) == numel(X); +if nargout>0 + I = find(~ismember(U,X(:))); +end \ No newline at end of file diff --git a/aprime.m b/aprime.m new file mode 100644 index 0000000..f7b2282 --- /dev/null +++ b/aprime.m @@ -0,0 +1,150 @@ +function [A,U,Z] = aprime(X1,X2,dim) +%APRIME - Compute A' (A-prime), i.e. non-parametric under ROC curve +% [] = aprime(X1,X2[,dim]) +% Default dim = 1 +% Example +% >> aprime +% +% See also: +% Reference: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-09 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<3 + dim = 1; +end +s=[ size(X1) ; size(X2) ]; +n1=s(1,dim); +n2=s(2,dim); +ranks = tiedrank(cat(dim,X1,X2),dim); +n1n2 = n1.*n2; +A = (sum(ranks(1:n1,:),dim)-n1*(n1+1)/2)/n1n2; +if nargout > 2 + U =A*n1n2; + Z = (U-n1*(n1+n2+1)/2)/sqrt(n1n2*(n1+n2+1)/12); +end +return + +function [r, tieadj] = tiedrank(x, tieflag, bidirectional) +%TIEDRANK Compute the ranks of a sample, adjusting for ties. +% [R, TIEADJ] = TIEDRANK(X) computes the ranks of the values in the +% vector X. If any X values are tied, TIEDRANK computes their average +% rank. The return value TIEADJ is an adjustment for ties required by +% the nonparametric tests SIGNRANK and RANKSUM, and for the computation +% of Spearman's rank correlation. +% +% [R, TIEADJ] = TIEDRANK(X,1) computes the ranks of the values in the +% vector X. TIEADJ is a vector of three adjustments for ties required +% in the computation of Kendall's tau. TIEDRANK(X,0) is the same as +% TIEDRANK(X). +% +% [R, TIEADJ] = TIEDRANK(X,0,1) computes the ranks from each end, so +% that the smallest and largest values get rank 1, the next smallest +% and largest get rank 2, etc. These ranks are used for the +% Ansari-Bradley test. +% +% See also ANSARIBRADLEY, CORR, PARTIALCORR, RANKSUM, SIGNRANK. + +% Copyright 1993-2005 The MathWorks, Inc. +% $Revision: 1.5.2.6 $ $Date: 2005/07/29 11:42:04 $ + +if nargin < 2 + tieflag = false; +end +if nargin < 3 + bidirectional = 0; +end + +if isvector(x) + [r,tieadj] = tr(x,tieflag,bidirectional); +else + if isa(x,'single') + outclass = 'single'; + else + outclass = 'double'; + end + + % Operate on each column vector of the input (possibly > 2 dimensional) + sz = size(x); + ncols = sz(2:end); % for 2x3x4, ncols will be [3 4] + r = zeros(sz,outclass); + if tieflag + tieadj = zeros([3,ncols],outclass); + else + tieadj = zeros([1,ncols],outclass); + end + for j=1:prod(ncols) + [r(:,j),tieadj(:,j)] = tr(x(:,j),tieflag,bidirectional); + end +end + +% -------------------------------- +function [r,tieadj] = tr(x,tieflag,bidirectional) +%TR Local tiedrank function to compute results for one column + +% Sort, then leave the NaNs (which are sorted to the end) alone +[sx, rowidx] = sort(x(:)); +numNaNs = sum(isnan(x)); +xLen = numel(x) - numNaNs; + +if bidirectional + % Use ranks counting from both low and high ends + if mod(xLen,2)==0 + ranks = [(1:xLen/2), (xLen/2:-1:1), NaN(1,numNaNs)]'; + else + ranks = [(1:(xLen+1)/2), ((xLen-1)/2:-1:1), NaN(1,numNaNs)]'; + end +else + % Use ranks counting from low end + ranks = [1:xLen NaN(1,numNaNs)]'; +end + +if tieflag + tieadj = [0; 0; 0]; +else + tieadj = 0; +end +if isa(x,'single') + ranks = single(ranks); + tieadj = single(tieadj); +end + +% Adjust for ties. Avoid using diff(sx) here in case there are infs. +ties = (sx(1:xLen-1) == sx(2:xLen)); +tieloc = [find(ties); xLen+2]; +maxTies = numel(tieloc); + +tiecount = 1; +while (tiecount < maxTies) + tiestart = tieloc(tiecount); + ntied = 2; + while(tieloc(tiecount+1) == tieloc(tiecount)+1) + tiecount = tiecount+1; + ntied = ntied+1; + end + + if tieflag + n2minusn = ntied*(ntied-1); + tieadj = tieadj + [n2minusn/2; n2minusn*(ntied-2); n2minusn*(2*ntied+5)]; + else + tieadj = tieadj + ntied*(ntied-1)*(ntied+1)/2; + end + + % Compute mean of tied ranks + ranks(tiestart:tiestart+ntied-1) = ... + sum(ranks(tiestart:tiestart+ntied-1)) / ntied; + tiecount = tiecount + 1; +end + +% Broadcast the ranks back out, including NaN where required. +r(rowidx) = ranks; +r = reshape(r,size(x)); diff --git a/argouts.m b/argouts.m new file mode 100644 index 0000000..a6d2e30 --- /dev/null +++ b/argouts.m @@ -0,0 +1,13 @@ +function [X] = argouts(f,N) +% argouts - retrieves N outputs from an evaluated expression f into a cell array +% [X]=argouts(f,N) +% +% Useful if outputs of f depends on the number of argout, e.g. +% E.g., [x{1},x{2}] = find(rand(2)>.5) +% is not the same as: x = {find(rand(2)>.5)} +% but (tada!) can be written: x = argouts('find(rand(2)>.5)',2) + +ev=sprintf('X{%d},', 1:N); +ev(end)=[]; +ev=[ '[' ev '] = ' f ';']; +eval(ev); diff --git a/art/rectpix.m b/art/rectpix.m new file mode 100644 index 0000000..392ed1d --- /dev/null +++ b/art/rectpix.m @@ -0,0 +1,18 @@ +function [z]=rectpix(fg, bgz, angle) +angle=-angle; +bgz = bgz-1; +[x,y]=meshgrid(-bgz(1)/2:bgz(1)/2 , -bgz(2)/2:bgz(2)/2); +ca=cos(angle); +sa=sin(angle); + +ca(abs(ca).1 + imshow(hh([1:sq(1)]+(ih-1)*sq(1),[1:sq(2)]+(iv-1)*sq(2))) + title(num2str(sh(ih,iv))) + pause + end + end +end + + +figure(2); +colormap(gray) +subplot(1,2,1); imagesc(sh); axis image; axis off +subplot(1,2,2); imagesc(hh); axis image; axis off +imwrite(hh, 'test.jpg') \ No newline at end of file diff --git a/art/test.jpg b/art/test.jpg new file 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zqJL|b^;T*=*ipXu`)R$iE%Ta05;mP#9{c+8t@@`#$#1=v zQ1HjQ=tlj$-4=40ey#%VIyT4T+s(H*5t9~_=9&ERi{0}@W~cbSM;0BXM;tULoK>WWE#7ZhIiBC^0an8>xNv$XW?Tcn*V3uY+58M;Yz<_Sl=_eJ(#041` z!aW%nL{N;{3A7+331pH>Vo731YHmSJVhMPgH6G*cyni!eLLdXf$qeEbGsZa_y4_lX>gFoO`=(ShLv+Kvthc2+h}+^_-R MAz)O^a0SH|00z@ROaK4? literal 0 HcmV?d00001 diff --git a/brainstorm3/bst_batch.m b/brainstorm3/bst_batch.m new file mode 100644 index 0000000..4702a8d --- /dev/null +++ b/brainstorm3/bst_batch.m @@ -0,0 +1,1276 @@ +function bst_batch(OPTIONS) +% BST_BATCH: Apply a process defined with panel_statRun, to a list a file. +% +% USAGE: bst_batch('CreatePanel', OPTIONS) +% +% INPUTS: (OPTIONS structure) +% - Conditions : Structure describing the files to process (from panel_stat and panel_process) +% - sProcess : Process to apply (defined in panel_statRun/GetProcessesList) +% - isData : 1 if files to process are recordings, 0 if they are cortical sources +% - Comment : Default comment for output files +% - isAbsoluteValues : For sources, apply "abs" before applying the process +% - nbPermutation : Number of permutations to perform +% - isOverwriteFiles : For filters, if 1 the input files will be replaced +% - OutputType : {'database', 'file', 'matlab'} +% - isCluster : If 1, use the clusters/scouts (only for data extraction functions) +% - isClusterAverage : If 1, merge the input clusters/scouts +% - sClusters : Clusters/scouts to apply (if isCluster = 1) +% - ClustersOptions : Structure that describes the way to compute the clusters/scouts values +% - Time : Time bounds to compute values +% - Baseline : Baseline bounds +% - iTime : Indices of the time samples to process +% - iBaseline : Indices of the baseline + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2009 +% ----------------------------- Script History --------------------------------- +% FT 17-Jul-2009 Creation +% ------------------------------------------------------------------------------ + +% Get samples lists +SamplesA = OPTIONS.Conditions.SamplesA; +SamplesB = OPTIONS.Conditions.SamplesB; + +% ===== APPLY PROCESS ===== +sProcess = OPTIONS.sProcess; +% Switch according to category +switch (sProcess.Category) + case 'Filter' + iStudyToRedraw = BatchFilter(SamplesA, OPTIONS); + isNewConditions = 0; + case 'Extract' + iStudyToRedraw = BatchExtract(SamplesA, OPTIONS); + isNewConditions = 0; + case 'Filter2' + iStudyToRedraw = BatchFilter2(SamplesA, SamplesB, OPTIONS); + isNewConditions = 0; + case 'Average' + % === Grand-average (by condition) === + % Call several time the average function (once per condition) + if strcmpi(sProcess.Name, 'GAVE') + % Initial values + iStudyToRedraw = []; + isNewConditions = 0; + % Process each condition independently + uniqueConditions = unique({SamplesA.Condition}); + for i = 1:length(uniqueConditions) + % Process the average of condition #i + iSampCond = find(strcmpi(uniqueConditions{i}, {SamplesA.Condition})); + [tmpStudyToRedraw, tmpNewConditions] = BatchAverage(SamplesA(iSampCond), OPTIONS); + % Save the results + iStudyToRedraw = [iStudyToRedraw tmpStudyToRedraw]; + isNewConditions = isNewConditions || tmpNewConditions; + end + + % === Average by subject === + % Call several time the average function (once per condition) + elseif strcmpi(sProcess.Name, 'SubjAvg') + % Initial values + iStudyToRedraw = []; + isNewConditions = 0; + % Process each subject independently + uniqueSubjects = unique({SamplesA.SubjectFile}); + for i = 1:length(uniqueSubjects) + % Process the average of subject #i + iSampSubj = find(strcmpi(uniqueSubjects{i}, {SamplesA.SubjectFile})); + [tmpStudyToRedraw, tmpNewConditions] = BatchAverage(SamplesA(iSampSubj), OPTIONS); + % Save the results + iStudyToRedraw = [iStudyToRedraw tmpStudyToRedraw]; + isNewConditions = isNewConditions || tmpNewConditions; + end + + % Else, just call function once to average everything + else + [iStudyToRedraw, isNewConditions] = BatchAverage(SamplesA, OPTIONS); + end + + case {'Spectral'} + [iStudyToRedraw, isNewConditions] = BatchSpectralDecomposition(SamplesA, OPTIONS); + + case {'Recurrence'} + [iStudyToRedraw, isNewConditions] = BatchRecurrenceMaps(SamplesA, OPTIONS); + + case {'TTest', 'PermTest'} + iStudyToRedraw = BatchStat(SamplesA, SamplesB, OPTIONS); + isNewConditions = 0; + + case {'Anova'} + iStudyToRedraw = BatchStat(SamplesA,[],OPTIONS); + isNewConditions = 0; +end + +% ===== UPDATE INTERFACE ===== +% OUTPUT TYPE: DATABASE ONLY +if strcmpi(OPTIONS.OutputType, 'database') && ~isempty(iStudyToRedraw) + iStudyToRedraw = unique(iStudyToRedraw); + % Unload all datasets + bst_dataSetsManager('UnloadAll', 'Forced'); + % Update results links in target study + db_updateLinkResults('Study', iStudyToRedraw); + % Update tree model + if isNewConditions + tree_updateModel(); + else + tree_updateNode('Study', iStudyToRedraw); + end + % Select target study as current node + tree_selectStudyNode( iStudyToRedraw(1) ); + % Save database + bst_saveDatabase(); +end + +% Hide waitbar +bst_progressBar('stop'); + + +end + + + +%% ====================================================================================== +% ===== BATCH FUNCTIONS ================================================================ +% ====================================================================================== + +%% ===== BATCH: FILTERS ===== +function iStudyToRedraw = BatchFilter(SamplesA, OPTIONS) + % === SOME VERIFICATIONS === + % OUTPUT: DATABASE ONLY + if ~strcmpi(OPTIONS.OutputType, 'database') + error('Filtering results can only be stored in database.'); + end + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + % Prepare OPTIONS structure for process_apply function + filterOPTIONS = struct('fcnFilter', str2func(['process_' sProcess.Name]), ... + 'FileA', '', ... + 'iTime', OPTIONS.iTime, ... + 'iBaseline', OPTIONS.iBaseline, ... + 'FileTag', sProcess.Name, ... + 'Comment', OPTIONS.Comment, ... + 'isAbsoluteValues', OPTIONS.isAbsoluteValues, ... + 'blockDimension', sProcess.blockDimension, ... + 'isAvgRef', sProcess.isAvgRef); + + % === FILES LOOP === + bst_progressBar('start', ['Apply process: ' sProcess.Name], 'Initialization...', 0, nbSamplesA); + % Process all the files + for i = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(i).FileName]); + bst_progressBar('inc', 1); + % Output study: same as input file + iTargetStudy = SamplesA(i).iStudy; + sTargetStudy = bst_getContext('Study', iTargetStudy); + % Ignore computation for files that are already processed + if ~isempty(strfind(SamplesA(i).FileName, ['_' sProcess.Name])) + res = java_dialog('confirm', ['The following file has already been processed with this filter: ' 10 SamplesA(i).FileName '.' 10 10 'Apply this process again ?'], 'Processes'); + if ~res + continue + end + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === COMPUTE FILTER === + % Complete filter configuration + filterOPTIONS.FileA = SamplesA(i).FullFileName; + % Apply process + [sNewFile, filterOPTIONS] = process_apply(filterOPTIONS); + % If process cancelled + if isempty(sNewFile) + return + end + + % === UPDATE STUDY === + % Overwrite initial file + if OPTIONS.isOverwriteFiles + % Delete the intial file + io_deleteFile(SamplesA(i).FullFileName, 1); + end + % Add new file to database + if OPTIONS.isData + if OPTIONS.isOverwriteFiles + iItem = SamplesA(i).iItem; + else + iItem = length(sTargetStudy.Data) + 1; + end + % Add new descriptor it to study + sTargetStudy.Data(iItem) = sNewFile; + else + if OPTIONS.isOverwriteFiles + iResult = SamplesA(i).iItem; + else + iResult = length(sTargetStudy.Result) + 1; + end + % Add new descriptor it to study + sTargetStudy.Result(iResult) = sNewFile; + end + bst_setContext('Study', iTargetStudy, sTargetStudy); + end +end + + +%% ===== BATCH: EXTRACT ===== +function iStudyToRedraw = BatchExtract(SamplesA, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + isOneOutputMat = ~strcmpi(OPTIONS.OutputType, 'database'); + initTimeVector = []; + ProtocolInfo = bst_getContext('ProtocolInfo'); + + % === FILES LOOP === + bst_progressBar('start', 'Data extraction', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Output study: same as input file + iTargetStudy = SamplesA(iSample).iStudy; + sTargetStudy = bst_getContext('Study', iTargetStudy); + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILE === + if sProcess.isAvgRef + [matValues, matName, ChannelFlag, TimeVector] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, []); + else + [matValues, matName, ChannelFlag, TimeVector] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, [], 'NoAvgRef'); + end + + % === TIME === + % Check time vectors + if (iSample == 1) + initTimeVector = TimeVector; + elseif (length(initTimeVector) ~= length(TimeVector)) || ~all(abs(initTimeVector - TimeVector) < 1e-6) + filedesc = fullfile(fileparts(SamplesA(iSample).FileName), SamplesA(iSample).Comment); + bst_error(['Time definition should be the same for all the files.' 10 10 'Ignoring file: "' filedesc '"'], 'bst_batch', 0); + return + end + % Keep only required time indices + matValues = matValues(:, OPTIONS.iTime); + TimeVector = TimeVector(OPTIONS.iTime); + + % === PROCESSES === + % Absolute values + if OPTIONS.isAbsoluteValues + matValues = abs(matValues); + end + % Process to apply to this block of data + switch (sProcess. Name) + case 'timemean' + % Compute the average of all the time samples on the defined time window + matValues = mean(matValues, 2); + isTimeMean = 1; + case 'timevar' + % Compute the variance of all the time samples on the defined time window + matValues = var(matValues, 0, 2); + isTimeMean = 1; + case 'extract' + % Nothing to do + isTimeMean = 0; + end + % TimeMean: Keep only the time window from which was computed the result + if isTimeMean + OPTIONS.iTime = OPTIONS.iTime([1,end]); + TimeVector = TimeVector([1, end]); + end + + % === APPLY CLUSTER === + if OPTIONS.isCluster + % Process each cluster + nbClusters = length(OPTIONS.Clusters); + tmpMatValues = zeros(nbClusters, size(matValues, 2)); + DescCluster = cell(nbClusters, 1); + for i = 1:nbClusters + sCluster = OPTIONS.Clusters(i); + % === GET ROWS INDICES === + if OPTIONS.isData + % Get channel file + [sStudy, iStudy] = bst_getContext('DataFile', SamplesA(iSample).FileName); + sChannel = bst_getContext('ChannelForStudy', iStudy); + % Load channel file + ChannelFile = fullfile(ProtocolInfo.STUDIES, sChannel.FileName); + ChannelMat = load(ChannelFile, 'Channel'); + % CLUSTERS: Get cluster channels + iRows = panel_clusters('GetChannelsInCluster', sCluster, ChannelMat.Channel, ChannelFlag); + if isempty(iRows) + return; + end + else + % SCOUTS: Get the indices of the sources of this scout + iRows = sCluster.Vertices; + end + + % === COMPUTE CLUSTER VALUES === + % Scouts: absolute or relative values + isDifference = strcmpi(sProcess.Name, 'diffAB'); + % If computing a difference : FORCE RELATIVE VALUES + if ~OPTIONS.ClustersOptions.isAbsolute || isDifference + tmp = matValues(iRows, :); + else + tmp = abs(matValues(iRows, :)); + end + % Scouts computation operation : mean or max + switch (OPTIONS.ClustersOptions.function) + case 'Max' + tmpMatValues(i,:) = max(tmp, [], 1); + case 'Power' + tmpMatValues(i,:) = sum(tmp .^ 2, 1); + case 'Mean' + tmpMatValues(i,:) = mean(tmp, 1); + otherwise + bst_error(['Cannot extract automatically all values.' 10 ... + 'Please change scout options: "Scouts" panel > View > Time series options'], ... + 'bst_batch', 0); + return; + end + % Save the name of the scout + DescCluster{i} = sCluster.Label; + end + % Return results matrix averaged by scout + matValues = tmpMatValues; + else + DescCluster = {}; + end + + % ===== OUTPUT STRUCTURE ==== + % Create new output structure + if ~isOneOutputMat || (iSample == 1) + newFileMat = CreateDefaultStruct(sProcess, SamplesA(iSample).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, isOneOutputMat, 1); + % Append comment + newFileMat.Comment = [newFileMat.Comment, ' ', OPTIONS.Comment]; + end + % If new file to be saved at each loop: copy matValues + if ~isOneOutputMat + if isTimeMean + newFileMat.(matName) = repmat(matValues, [1, 2]); + else + newFileMat.(matName) = matValues; + end + else + % Get new matrix + prevMat = newFileMat.(matName); + % Check the orientation in which the new data should be appended: + % - Time mean : dimension 2 (time) + % - Channels mean : dimension 1 (channels) + if isTimeMean + % Check the number of electrodes + if ~isempty(prevMat) && (size(prevMat,1) ~= size(matValues,1)) + error(['The data files in samples set A do not have the same number of channels.' 10 ... + 'It is impossible to store their averages in the same matrix.']); + end + % Concatenate the results matrices & add description fields + newFileMat.(matName) = cat(2, prevMat, matValues); + newFileMat.DescFileName = cat(2, newFileMat.DescFileName, repmat({SamplesA(iSample).FileName}, [1, size(matValues,2)])); + newFileMat.DescCluster = cat(2, newFileMat.DescCluster, DescCluster); + else + if ~isempty(prevMat) && (size(prevMat,2) ~= size(matValues,2)) + error(['The files in samples set A do not have the same number of time samples.' 10 ... + 'It is impossible to store their averages in the same matrix.']); + end + % Concatenate the results matrices & add description fields + newFileMat.(matName) = cat(1, prevMat, matValues); + newFileMat.DescFileName = cat(1, newFileMat.DescFileName, repmat({SamplesA(iSample).FileName}, [size(matValues,1), 1])); + newFileMat.DescCluster = cat(1, newFileMat.DescCluster, DescCluster); + end + % Add bad channels from current ChannelFlag + newFileMat.ChannelFlag(ChannelFlag == -1) = -1; + end + + % ===== SAVE FILE ===== + if ~isOneOutputMat + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(iSample).FileName); + end + end + + % === EXPORT DATA === + if isOneOutputMat + % Display waitbar + bst_progressBar('start', 'Processes', 'Saving results...'); + % Save file + switch(OPTIONS.OutputType) + case 'file' + % Save in a user defined file + if OPTIONS.isData || OPTIONS.isCluster + export_data(newFileMat); + else + export_result(newFileMat); + end + case 'matlab' + % Export to Matlab workspace + export_matlab(newFileMat); + end + end +end + + +%% ===== BATCH: AVERAGE ===== +function [iStudyToRedraw, isNewConditions] = BatchAverage(SamplesA, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA,repmat(SamplesA, 0),OPTIONS); + % Update this study + iStudyToRedraw = iTargetStudy; + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + + % === PROCESS AVERAGE === + bst_progressBar('start', ['Apply process: ' sProcess.Name], 'Initialization...', 0, length(SamplesA)); + % If absolute values + if OPTIONS.isAbsoluteValues + strAbsolute = 'AbsoluteValues'; + else + strAbsolute = []; + end + Stat = bst_statFiles('mean', {SamplesA.FullFileName}, OPTIONS.iTime, 'PercentProgressBar', strAbsolute); + + % === SAVE RESULTS === + % Get default file structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, Stat.Time, OPTIONS.iTime, Stat.ChannelFlag, 0, 0); + % Add averaged values in it + newFileMat.(Stat.MatName) = Stat.mean; + % Comment + if isempty(OPTIONS.Comment) && isempty(Comment) + % Use default commet: "ProcessName: date" + c = clock; + strTime = sprintf('%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + newFileMat.Comment = [sProcess.Name ': ' strTime]; + elseif isempty(OPTIONS.Comment) + newFileMat.Comment = Comment; + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save and register file + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); +end + + +%% ===== BATCH: FILTER2 ===== +function [iStudyToRedraw, isNewConditions] = BatchFilter2(SamplesA, SamplesB, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),SamplesB(iSample),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + if sProcess.isAvgRef + % Sample A + [matValuesA, matNameA, ChannelFlagA, TimeVectorA] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, []); + % Sample B + [matValuesB, matNameB, ChannelFlagB, TimeVectorB] = bst_readMatrixInFile(SamplesB(iSample).FullFileName, []); + else + % Sample A + [matValuesA, matNameA, ChannelFlagA, TimeVectorA] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, [], 'NoAvgRef'); + % Sample B + [matValuesB, matNameB, ChannelFlagB, TimeVectorB] = bst_readMatrixInFile(SamplesB(iSample).FullFileName, [], 'NoAvgRef'); + end + + % === TIME === + % Check time vectors + if (length(TimeVectorA) ~= length(TimeVectorB)) || ~all(abs(TimeVectorA - TimeVectorB) < 1e-6) + bst_error('Each couple of files (A,B) must have the same time definition.', 'bst_batch', 0); + return + elseif (length(ChannelFlagA) ~= length(ChannelFlagB)) + bst_error('Each couple of files (A,B) must have the same number of channels.', 'bst_batch', 0); + return + end + % Keep only required time indices + matValuesA = matValuesA(:, OPTIONS.iTime); + matValuesB = matValuesB(:, OPTIONS.iTime); + TimeVector = TimeVectorA(OPTIONS.iTime); + % Combine bad channels + ChannelFlag = ones(size(ChannelFlagA)); + ChannelFlag((ChannelFlagA == -1) | (ChannelFlagB == -1)) = -1; + + % === PROCESSES === + % Absolute values + if OPTIONS.isAbsoluteValues + matValuesA = abs(matValuesA); + matValuesB = abs(matValuesB); + end + % Apply process + switch (sProcess.Name) + case 'diffAB' + matValues = matValuesA - matValuesB; + case 'meanAB' + matValues = (matValuesA + matValuesB) / 2; + end + + % ===== SAVE FILE ==== + % Create default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(iSample).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 1); + % Add averaged values in it + newFileMat.(matNameA) = matValues; + % Comment + if isempty(OPTIONS.Comment) + if ~isempty(Comment) + newFileMat.Comment = Comment; + else + % Build comments based on the samples couple + localCond = struct('SamplesA',SamplesA(iSample), 'SamplesB',SamplesB(iSample)); + newFileMat.Comment = panel_statRun('FormatComment', sProcess, localCond, OPTIONS.Time); + end + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save file + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(iSample).FileName); + end +end + + +%% ===== BATCH: STAT ===== +function iStudyToRedraw = BatchStat(SamplesA, SamplesB, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + testType = sProcess.Name; + isPermTest = strcmpi(sProcess.Category, 'PermTest'); + % For old Karim t-test + isOldSimpleTest = ~isempty(strfind(sProcess.Name, 'old')); + if isOldSimpleTest + testType = strrep(testType, 'old_', ''); + end + isAnova = strcmpi(sProcess.Category, 'Anova'); + + + % Display progress bar + bst_progressBar('start', 'Statistical test', 'Initialization...', 0, length(SamplesA)); + % Get output study + if isAnova + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess, SamplesA, SamplesA([]), OPTIONS); + else + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess, SamplesA, SamplesB, OPTIONS); + end + iStudyToRedraw = iTargetStudy; + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + + % === Load all the samples === + % Needed only for permutation t-test, and OLD KARIM T-TEST + if isPermTest || isOldSimpleTest + % Samples set A + [X1, ChannelFlagA, TimeVector] = buildDataArray({SamplesA.FullFileName}, OPTIONS.iTime); + % Samples set B + [X2, ChannelFlagB] = buildDataArray({SamplesB.FullFileName}, OPTIONS.iTime); + % If is absolute values + if OPTIONS.isAbsoluteValues + X1 = abs(X1); + X2 = abs(X2); + end + % Combine channel flag + ChannelFlag = ChannelFlagA; + ChannelFlag(ChannelFlagB == -1) = -1; + end + + if isAnova + %knd: to do + warning('manually changed anova factors!') + [pmap,Fmap,fx,ChannelFlag, TimeVector] = knd_rmanova_files(SamplesA,OPTIONS); + + % === SIMPLE TESTS (OLD) === + elseif ~isPermTest && isOldSimpleTest + % Remove the "old" tag + testType = strrep(testType, 'old_', ''); + % Set permutation dimension + dim_p = 1; + % Display waitbar + bst_progressBar('start', 'Processes', 'Computing t-test...'); + % Compute test + [pmap,tmap] = knd_ttest(X1, X2, dim_p, testType); + + % === SIMPLE TESTS === + elseif ~isPermTest + % Compute test + if OPTIONS.isAbsoluteValues + [pmap,tmap,ChannelFlag, TimeVector] = knd_ttest_files({SamplesA.FullFileName}, {SamplesB.FullFileName}, testType, OPTIONS.iTime, OPTIONS.iTime, 'AbsoluteValues'); + else + [pmap,tmap,ChannelFlag, TimeVector] = knd_ttest_files({SamplesA.FullFileName}, {SamplesB.FullFileName}, testType, OPTIONS.iTime, OPTIONS.iTime); + end + + % === PERMUTATIONS TESTS === + elseif isPermTest + tic + % Set permutation dimension + if sProcess.isPaired + dim_p = 1; + else + dim_p = -1; + end + + % Compute test + [pmap,tmap] = permtest(X1, X2, {testType}, dim_p, [], OPTIONS.nbPermutation); + % Display computation time + timeLength = toc(); + bst_message_window(sprintf('\nTook: %3.2f secs', timeLength)); + + + end + + % === BUILD NEW FILES === + % Display waitbar + bst_progressBar('start', 'Processes', 'Saving results...'); + + if isAnova + Factors.N = 3; + NS = numel(unique({SamplesA.SubjectName})) + [u,i,j] = unique([SamplesA.iItem]) + if numel(u)>1 + SelectedItem = listdlg('ListString', [strvcat({SamplesA(i).Condition}) repmat(' : ',length(u),1) strvcat({SamplesA(i).Comment})],'SelectionMode','single'); + if isempty(SelectedItem) + return + end + SamplesA = SamplesA(j == SelectedItem); + end + f = {SamplesA.Condition}; + f=reshape(f(1+[0:3]*NS),[2 2]) + fa=sprintf('%s+',f{1,:}); + fb=sprintf('%s+',f{2,:}); + Factors.Names{1}=sprintf('%s vs. %s',fa(1:end-1),fb(1:end-1)); + fa=sprintf('%s+',f{:,1}); + fb=sprintf('%s+',f{:,2}); + Factors.Names{2}=sprintf('%s vs. %s',fa(1:end-1),fb(1:end-1)); + + %Factors.Names = { 'FB' 'Conf' 'Subj'}; + Factors.NLevels = [2 2 NS] + Factors.Levels = { {'C' 'I'} {'H' 'L'} [] }; + Factors.X = []; + %must loop on maps + for i_fx=1:size(pmap,1) + % Get default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 0); + % Comment + newFileMat.Comment = OPTIONS.Comment ; + if numel(fx{i_fx}) == 1 + newFileMat.Comment = [newFileMat.Comment ' - Main effect of ']; + else + newFileMat.Comment = [newFileMat.Comment ' - Interaction of ']; + end + newFileMat.Comment = [newFileMat.Comment sprintf('%s * ',Factors.Names{fx{i_fx}})]; + newFileMat.Comment(end-2:end)=[]; + % Save P and F maps + sz=[size(pmap) 1]; + newFileMat.pmap = single(reshape(pmap(i_fx,:),sz(2:end))); + newFileMat.tmap = single(reshape(Fmap(i_fx,:),sz(2:end))); + % Save new file and register in database + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + end + else + % Get default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 0); + % Comment + if isempty(OPTIONS.Comment) + newFileMat.Comment = Comment; + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save P and T maps + newFileMat.pmap = single(pmap); + newFileMat.tmap = single(tmap); + % Save new file and register in database + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + end +end + + +%% ===== BATCH: SPECTRAL ANALYSIS ====== +function [iStudyToRedraw, isNewConditions] = BatchSpectralDecomposition(SamplesA, OPTIONS) + % Frequency bands of interest + freqBands = ... + [1 3.9;... + 4,7.9;... + 8,12.9;... + 13,34.9;... + 35,54.9;... + 65,85;... + 200,250]; + NamesFreqBands = {... + 'delta_1_4Hz',... + 'theta_4_8Hz',... + 'alpha_8_13Hz',... + 'beta_13_35Hz',... + 'gamma_35_55Hz',... + 'gamma_65_85Hz',... + 'gamma_200_250Hz'}; + + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),repmat(SamplesA, 0),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + % Resolve link + [FileName, DataFile] = resolveResultsLink(SamplesA(iSample).FullFileName); + % Load results file + kernelMat = load(FileName); +% dataMat = load(DataFile,'F', 'Time'); + dataMat = in_data_bst( DataFile, [], 'Time', 'F'); + + %iMEG = good_channel(kernelMat.Channel,kernelMat.ChannelFlag, 'MEG'); %CBB: need to expand to EEG as well + iMEG = kernelMat.OPTIONS.GoodChannel; + dataMat.F = dataMat.F(iMEG, :); + + if iSample == 1 + F_RMS = zeros(size(kernelMat.ImagingKernel,1),length(NamesFreqBands),nbSamplesA); + end + sRate = abs(1/(dataMat.Time(2)-dataMat.Time(1))); + nTime = size(dataMat.F,2); + NFFT = 2^nextpow2(nTime); % Next power of 2 from length of y + freqVec = sRate/2*linspace(0,1,NFFT/2); + + fftF = fft(dataMat.F,NFFT,2)/nTime; + %powfftF = 2*abs(fftF(:,1:end/2)); + clear dataMat; + for ifreq = 1:length(NamesFreqBands) + VecInd = findclosest(freqBands(ifreq,:),freqVec); + %F = bandpassFilter_all(dataMat.F,sRate,freqBands(ifreq,1),freqBands(ifreq,2)); + F_RMS(:,ifreq,iSample) = sum(2*abs(kernelMat.ImagingKernel * fftF(:, VecInd(1):VecInd(2))),2)... + /length(VecInd(1):VecInd(2)); + % ImageGridAmp = sqrt(sum(ImageGridAmp.^2,2)/size(ImageGridAmp,2)); % compute root mean square power in current frequency band + end + end + + clear dataMat fftF + % Compute statistics + %F_RMS(F_RMS<.05*max(F_RMS(:)))=0; + aveStat = mean(F_RMS,3); + stdStat = std(F_RMS,0,3); + clear F_RMS + for ifreq = 1:length(NamesFreqBands) + current_aveStat = aveStat(:,ifreq); + tmp_current_aveStat = current_aveStat; + tmp_current_aveStat(tmp_current_aveStat<.5*max(tmp_current_aveStat))=0; + current_stdStat = stdStat(:,ifreq); + tStat = (tmp_current_aveStat./current_stdStat)*sqrt(nbSamplesA-1); + %tStat(isnan(tStat))=0; + + % === SAVE RESULTS === + kernelMat.ImageGridAmp = repmat(current_aveStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('GAVE: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + kernelMat.ImageGridAmp = repmat(current_stdStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('STD: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + + kernelMat.ImageGridAmp = repmat(tStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('T: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + end + +end + +%% ===== BATCH: RECURRENCE MAPS ====== +function [iStudyToRedraw, isNewConditions] = BatchRecurrenceMaps(SamplesA, OPTIONS) + % Frequency bands of interest + ampThresh = .75; %Binarization Threshold + timeWindow = 30; % time window within which binarization is processed + bandPass1 = 1; + bandPass2 = 250; + + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),repmat(SamplesA, 0),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + % Resolve link + [FileName, DataFile] = resolveResultsLink(SamplesA(iSample).FullFileName); + % Load results file + kernelMat = load(FileName); +% dataMat = load(DataFile,'F', 'Time'); + dataMat = in_data_bst( DataFile, [], 'Time', 'F'); + iMEG = good_channel(kernelMat.Channel,kernelMat.ChannelFlag, 'MEG'); %CBB: need to expand to EEG as well + dataMat.F = dataMat.F(iMEG, :); + + sRate = abs(1/(dataMat.Time(2)-dataMat.Time(1))); + nTime = size(dataMat.F,2); + + VecInd = findclosest([-timeWindow,timeWindow]/1000,dataMat.Time); + timeVec = VecInd(1):VecInd(2); + dataMat.F = bandpassFilter_all(dataMat.F,sRate, bandPass1,bandPass2); + ImageGridAmp = abs(kernelMat.ImagingKernel * dataMat.F(:, VecInd(1):VecInd(2))); + + % Thresholding + if iSample == 1; + iMask = zeros(size(ImageGridAmp,1),1); + iTimeMask = zeros(size(ImageGridAmp,1),nbSamplesA); + end + %tmp = zeros(size(ImageGridAmp)); + %tmp(find(ImageGridAmp>ampThresh*max(ImageGridAmp(:)))) = 1; + + % time-relative max + % maxx = max(ImageGridAmp); + % maxx = repmat(maxx,size(ImageGridAmp,1),1); + % time-absolute max + maxx = max(ImageGridAmp(:)); + maxx = maxx*ones(size(ImageGridAmp)); + + iMaxtmp = ImageGridAmp > (ampThresh * maxx); + iTimeMask(:,iSample) = min(... + iMaxtmp .* repmat(dataMat.Time(timeVec),size(ImageGridAmp,1),1), ... + [],2); + iMaxtmp = sum(iMaxtmp,2); + + iMask(find(iMaxtmp)) = iMask(find(iMaxtmp)) + 1; + %[I,J] = find(ImageGridAmp>ampThresh*max(ImageGridAmp(:))); + %iMask(I) = iMask(I) + 1; + %iTimeMask(I,iSample) = dataMat.Time(timeVec(J)); + end + clear dataMat + iMask = 100*iMask/nbSamplesA; + iTimeMask = 1000*mean(iTimeMask,2).*(iMask>0); + + % === SAVE RESULTS === + kernelMat.ImageGridAmp = repmat(iMask,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('Recurrence Map'); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + kernelMat.ImageGridAmp = repmat(iTimeMask,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('Recurrence Map (latencies)'); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + +end + +%% ====================================================================================== +% ===== HELPERS ======================================================================== +% ====================================================================================== +%% ===== CREATE DEFAULT OUTPUT STRUCTURE ===== +function sFileMat = CreateDefaultStruct(sProcess, FileName, isData, TimeVector, iTime, ChannelFlag, isOneOutputMat, isSampleBySample) +% Default structures for stat +isStat = ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); +if isStat + sStat = struct(... + 'Type', '', ... + 'Comment', '', ... + 'Time', TimeVector, ... + 'ChannelFlag', ChannelFlag, ... + 'pmap', [], ... + 'tmap', [], ... + 'pThreshold', 0.05); + end + + % If recordings + if isData + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'data'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + % Data + else + sFileMat.Time = TimeVector; + sFileMat.F = []; + end + % Else: sources + else + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Resolve link, if it is a link + [FileName, DataFile] = resolveResultsLink(FileName); + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'results'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + else + % Time + sFileMat.Time = iTime; + sFileMat.ImageGridTime = TimeVector; + % Reset some fields + sFileMat.OPTIONS.Data = []; + sFileMat.Fsynth = []; + sFileMat.ImagingKernel = []; + sFileMat.ImageGridAmp = []; + if ~isSampleBySample + sFileMat.DataFile = []; + elseif ~isempty(DataFile) + sFileMat.DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + end + end + % Remove "Kernel" indications in the Comment field + sFileMat.Comment = strrep(sFileMat.Comment, '(Kernel)', ''); + sFileMat.Comment = strrep(sFileMat.Comment, 'Kernel', ''); + end + % Bad channels list + sFileMat.ChannelFlag = ChannelFlag; + + % Add some fields for exported results + if isOneOutputMat + sFileMat.DescFileName = {}; + sFileMat.DescCluster = {}; + sFileMat.DescProcessType= sProcess.Name; + end +end + + +%% ===== SAVE NEW FILE ===== +function sTargetStudy = SaveNewFile(newFileMat, sProcess, isData, iTargetStudy, sTargetStudy, InputFile) + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get default output file + OutputDir = fullfile(ProtocolInfo.STUDIES, fileparts(sTargetStudy.FileName)); + FullFileName = GetDefaultFileName(sProcess, isData, OutputDir, InputFile); + % Save in database + save(FullFileName, '-struct', 'newFileMat'); + % Register in database + isStat = ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); + FileName = strrep(FullFileName, ProtocolInfo.STUDIES, ''); + sTargetStudy = RegisterNewFile(newFileMat, FileName, isData, isStat, iTargetStudy); +end + + +%% ===== GET DEFAULT FILE NAME ===== +function OutputFile = GetDefaultFileName(sProcess, isData, OutputDir, InputFile) + % Get date and time for filename + c = clock; + strTime = sprintf('_%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + + % Output file tag + if ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}) + if isData + fileTag = 'pdata'; + else + fileTag = 'presults'; + end + else + if isData + fileTag = 'data'; + else + fileTag = 'results'; + end + end + + % Other tags present in input file + if ~isempty(strfind(InputFile, '_zscore')) + strInputTags = '_zscore'; + else + strInputTags = ''; + end + + % Default filename + defFileName = [fileTag '_' sProcess.Name strTime strInputTags '.mat']; + % File in the target study + OutputFile = fullfile(OutputDir, defFileName); + % Make filename unique + OutputFile = io_makeUniqueFilename(OutputFile); +end + + +%% ===== REGISTER NEW FILE ===== +function sStudy = RegisterNewFile(FileMat, FileName, isData, isStat, iStudy) + % Get study + sStudy = bst_getContext('Study', iStudy); + % Stat + if isStat + % Create new stat file descriptor + sNewStat = db_getDataTemplate('Stat'); + sNewStat.FileName = FileName; + sNewStat.Comment = FileMat.Comment; + sNewStat.Type = FileMat.Type; + sNewStat.pThreshold = FileMat.pThreshold; + % Add it to study + sStudy.Stat(end+1) = sNewStat; + % Data + elseif isData + % Create new data descriptor + sNewData = db_getDataTemplate('Data'); + sNewData.FileName = FileName; + sNewData.Comment = FileMat.Comment; + % Add it to study + sStudy.Data(end+1) = sNewData; + % Results + else + % Create new results descriptor + sNewResult = db_getDataTemplate('Results'); + sNewResult.FileName = FileName; + sNewResult.Comment = FileMat.Comment; + sNewResult.DataFile = FileMat.DataFile; + % Add it to study + sStudy.Result(end+1) = sNewResult; + end + % Update database + bst_setContext('Study', iStudy, sStudy); +end + + +% ===== GET OUTPUT STUDY ===== +function [sOutputStudy, iOutputStudy, isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA,SamplesB,OPTIONS) + % Get some properties of the filter + isMixedSubjectsAB = isempty(SamplesB) || ~isequal({SamplesA.SubjectFile}, {SamplesB.SubjectFile}); + isSampleBySample = ismember(sProcess.Category, {'Filter2', 'Filter', 'Extract'}); + isConditionByCondition = strcmpi(sProcess.Name, 'GAVE'); + isNewConditions = 0; + % Get the list of involved studies + uniqueStudiesInd = unique([SamplesA.iStudy, SamplesB.iStudy]); +% Comment = OPTIONS.Comment; + Comment = ''; + + % ===== CHECK SUBJECT UNICITY ===== + % Get full subjects list without repetitions + uniqueSubjectFiles = unique(cat(2, {SamplesA.SubjectFile}, {SamplesB.SubjectFile})); + % For stat on sources: all the results files must be computed on the same surface. + % => else, the number of sources might be different between different files + % => user should realign surfaces before going on + if (length(uniqueSubjectFiles) > 1) + isUniqueSubject = 0; + if ~isSampleBySample && ~OPTIONS.isData + % If there is more than one subjects involved: need to check that all + % the subjects use the default anatomy + for i = 1:length(uniqueSubjectFiles) + sSubject = bst_getContext('Subject', uniqueSubjectFiles{i}); + if ~sSubject.UseDefaultAnat + gui_hidePanel('panel_statRun'); + sOutputStudy = []; + iOutputStudy = []; + bst_error(['The sources files you selected use different anatomies.' 10 ... + 'In order to perform any computation on sources, all the files' 10 ... + 'should use the same anatomy.' 10 10 ... + 'You have to project all your results on a template anatomy.' 10 ... + 'Popup menu: "Project sources on default anatomy".'], 'Processes', 0); + return; + end + end + end + else + isUniqueSubject = 1; + end + + % ===== GET OUTPUT STUDY ===== + % SUBJECT AVERAGE + if strcmpi(sProcess.Name, 'SubjAvg') + % Get subject + [sSubject, iSubject] = bst_getContext('Subject', SamplesA(1).SubjectFile); + % Get "intra" study for this subject + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisIntraStudy', iSubject); + % Comment + Comment = ['SubjectAvg(' SamplesA(1).SubjectName ')']; + % UNIQUE STUDY (OR OVERWRITE) + elseif (length(uniqueStudiesInd) == 1) || OPTIONS.isOverwriteFiles + % Get this unique study + [sOutputStudy, iOutputStudy] = bst_getContext('Study', uniqueStudiesInd(1)); + % MULTIPLE STUDIES : SAMPLE BY SAMPLE + elseif isSampleBySample && ~isMixedSubjectsAB + % Target study is a new condition (name = test comment) + % Get subject path + newCondPath = fileparts(SamplesA(1).SubjectFile); + % Get new condition name + localCond = struct('SamplesA',SamplesA,'SamplesB',SamplesB); + newCondName = panel_statRun('FormatComment', sProcess, localCond, OPTIONS.Time); + newCondName = io_standardizeFileName(newCondName); + % Comment + Comment = sProcess.FileTag; + Comment = strrep(Comment, '#A#', localCond.SamplesA(1).Comment); + Comment = strrep(Comment, '#B#', localCond.SamplesB(1).Comment); + % Try to get an existing condition with this path + [sOutputStudy, iOutputStudy] = bst_getContext('StudyWithCondition', fullfile(newCondPath,newCondName)); + % If does not exist: Create a new condition + if isempty(sOutputStudy) + iOutputStudy = db_addCondition(newCondPath, newCondName, 'NoRefresh'); + sOutputStudy = bst_getContext('Study', iOutputStudy); + isNewConditions = 1; + end + % MULTIPLE STUDIES : CONDITION BY CONDITION + elseif isConditionByCondition + Comment = ['GAVE(' SamplesA(1).Condition ')']; + % Grand average: stored in 'analysis-inter' node + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisInterStudy'); + % MULTIPLE STUDIES : GLOBAL + else + % UNIQUE SUBJECT : 'analysis-intra' + if isUniqueSubject + % Subject file is the same for all the studies => find common subject + [sSubject, iSubject] = bst_getContext('Subject', SamplesA(1).SubjectFile); + % Get 'analysis-intra' node of this subject + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisIntraStudy', iSubject); + % MULTIPLE SUBJECTS : 'analysis-inter' + else + % Get 'analysis-inter' node in current protocol + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisInterStudy'); + end + end + % Error ? + if isempty(sOutputStudy) + error('Cannot find an analysis study to store the results.'); + end + + % ===== COMBINE CHANNEL FILES ===== + % If source and target studies are not the same + if ~isequal(uniqueStudiesInd, iOutputStudy) + % Destination study for new channel file + [tmp__, iChanStudyDest] = bst_getContext('ChannelForStudy', iOutputStudy); + % Source channel files studies + [tmp__, iChanStudySrc] = bst_getContext('ChannelForStudy', uniqueStudiesInd); + % If target study has no channel file: create a new one by combination of the others + isNewChannelFile = db_combineChannelFiles(unique(iChanStudySrc), iChanStudyDest, [], ~OPTIONS.isData); + % Reload target study if it changed (new channel file) + if isNewChannelFile + sOutputStudy = bst_getContext('Study', iOutputStudy); + tree_updateModel(); + end + end +end + + +%% ===== BUILD DATA ARRAY ===== +function [X, ChannelFlag, Time] = buildDataArray(sampleFiles, iTime) + % Read out the data from multiple files and store in larger array X + % Parameters: + % - sampleFiles : cell array of data file names + % - Time : time values of the samples to extract + % - isData : a flag; 0 means read from Results file, 1 from surface data file + + % Open progress bar + isNewProgressBar = ~bst_progressBar('isvisible'); + if isNewProgressBar + bst_progressBar('start', 'Loading samples...', 'Processes', 0, length(sampleFiles)); + end + ChannelFlag = []; + + % Process all the samples files + for k = 1:length(sampleFiles) + % Progress bar + bst_progressBar('inc', 1); + bst_progressBar('text', ['File: ' sampleFiles{k}]); + % Read matrix + [matValues, matName, tmpChannelFlag, TimeVector] = bst_readMatrixInFile(sampleFiles{k}, iTime); + % Get time for the specified indices + % Bug: Time = TimeVector(iTime); + Time = TimeVector; + % Add bad channels to list of bad channels + if isempty(ChannelFlag) + ChannelFlag = tmpChannelFlag; + else + ChannelFlag(tmpChannelFlag == -1) = -1; + end + % Initialize large array + if (k == 1) + X = zeros(length(sampleFiles), size(matValues,1), size(matValues,2)); + end + + % Store read values in full data array + try + X(k,:,:) = matValues; + catch + error('Please first check that all the files in your samples have the same of channels/sources. Consider registering the MEG/EEG data to the same sensor cap'); + end + end + + if isNewProgressBar + bst_progressBar('stop'); + end +end + +function [p,F,fx,ChannelFlag, TimeVector] = knd_rmanova_files(SamplesA,OPTIONS) +% knd_rmanova_files - repeated measure anova +%SamplesA = SamplesA([SamplesA.iItem]== 4) +%OPTIONS.iTime = 599:630 +[X1, ChannelFlag, TimeVector] = buildDataArray({SamplesA.FullFileName}, OPTIONS.iTime); +if OPTIONS.isAbsoluteValues + X1 = abs(X1); +end +%TimeVector=round(mean(TimeVector)); +% X1=mean(X1,3); +sX=size(X1); +% X= subj * C/I * H/L +X1=reshape(X1,[15 2 2 sX(2:end)]); +% X= C/I * H/L * Subj * vertices +X1=permute(X1,[2 3 1 4:ndims(X1)]); +[p,F,fx]=myrmanova(X1,2,1:2,[],0); +return \ No newline at end of file diff --git a/brainstorm3/bst_rmanova.m b/brainstorm3/bst_rmanova.m new file mode 100644 index 0000000..1c43171 --- /dev/null +++ b/brainstorm3/bst_rmanova.m @@ -0,0 +1,5 @@ +function [varargout] = fun(varargin) +% 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sStudy.Result(iItems(i)).FileName; + end + % Compare with saved filename + if ~io_compareFileNames(CurFile, SamplesFiles{i}) + return + end + end + isOk = 1; +end + + +%% ===== TREE KEYBOARD CALLBACK ===== +function TreeKeyboard_Callback(hObj, ev) + % Switch between actions + switch (ev.getKeyCode()) + % DELETE/BACKSPACE : DELETE NODE CALLBACK + case {ev.VK_DELETE, ev.VK_BACK_SPACE} + DeleteSelectedNodes(ev.getSource()); + end +end + + +%% ===== GET SELECTED DATA TYPE ===== +function DataType = GetDataType(panelName) + % Get panel controls + ctrl = bst_getContext('PanelControls', panelName); + % Get DataType + if ctrl.jButtonRecordings.isSelected() + DataType = 'data'; + else + DataType = 'results'; + end +end + + +%% ===== DELETE SELECTED NODES ===== +function DeleteSelectedNodes(bstTree) + % Get selected nodes + treeModel = awtinvoke(bstTree, 'getModel()'); + treeSelPaths = awtinvoke(bstTree, 'getSelectionPaths()'); + % Delete each selected node + for iNode = 1:length(treeSelPaths) + awtinvoke(treeModel, 'removeNodeFromParent(Ljavax.swing.tree.MutableTreeNode;)', ... + treeSelPaths(iNode).getLastPathComponent()); + end + awtinvoke(bstTree, 'refresh()'); +end + + +%% ===== GET NODES IN TREE ===== +function bstNodes = GetTreeNodes(bstTree) + % Get root node + nodeRoot = bstTree.getModel.getRoot(); + if (nodeRoot.getChildCount() == 0) + bstNodes = []; + return + end + % Get all the children + bstNodes = javaArray('org.brainstorm.tree.BstNode', nodeRoot.getChildCount()); + for i = 1:nodeRoot.getChildCount() + bstNodes(i) = nodeRoot.getChildAt(i-1); + end +end + + +%% ===== UPDATE ITEM COUNTS ===== +function UpdateItemProperties(bstTree, listName, isForced) + global GlobalData; + % Parse inputs + if (nargin < 3) + isForced = 0; + end + + % === COUNT ITEMS DEPENDENCIES === + % Get nodes in target tree + bstNodes = GetTreeNodes(bstTree); + % Get options + if strcmpi(listName, 'SampleFilesA') + DataType = GetDataType('Processes'); + else + DataType = GetDataType('Statistics'); + end + iAllStudies = []; + iAllItems = []; + % For each node: update item count in comment + for iNode = 1:length(bstNodes) + % Get number of dependent items + [iDepStudies, iDepItems] = tree_getDependencies(bstNodes(iNode), DataType); + iAllStudies = [iAllStudies, iDepStudies]; + iAllItems = [iAllItems, iDepItems]; + % Ignore nodes that were already processed + nodeComment = char(bstNodes(iNode).getComment()); + if ~isempty(strfind(nodeComment, '[')) && ~isForced + continue; + end + % Remove previous items count + nodeComment = strRemoveParenthesis(nodeComment, '['); + % Add items count + nodeComment = sprintf('%s [%d]', nodeComment, length(iDepItems)); + % Update node comment + awtinvoke(bstNodes(iNode), 'setComment(Ljava.lang.String;)', nodeComment); + end + % Compute total number of items + totalNbItems = length(iAllItems); + % Save the sample filenames (to be able to check for database modifications later) + SampleFiles = bst_getContext('GetFileNames', iAllStudies, iAllItems, DataType); + GlobalData.Stat.(listName) = SampleFiles; + + % === UPDATE TREE DISPLAY (items and title) === + jParentPanel = bstTree.getParent.getParent.getParent(); + titledBorder = jParentPanel.getBorder(); + strTitle = strRemoveParenthesis(char(titledBorder.getTitle()), '['); + strTitle = sprintf('%s [%d]', strTitle, totalNbItems); + awtinvoke(titledBorder, 'setTitle(Ljava.lang.String;)', strTitle); + %jParentPanel.updateUI(); + awtinvoke(bstTree, 'updateUI()'); + awtinvoke(jParentPanel, 'updateUI()'); +end + + +%% ===== GET SAMPLES ===== +% USAGE: sSamples = GetSamples(jTree, DataType, FilterFileTag) : Return all the samples in JTree +% sSamples = GetSamples() : Return an empty samples structure +function sSamples = GetSamples(jTree, DataType, FilterFileTag) + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Samples structure + sSamples = repmat(struct('iStudy', 0, ... + 'iItem', 0, ... + 'FileName', '', ... + 'FullFileName', '', ... + 'Comment', '', ... + 'Condition', '', ... + 'SubjectFile', ''), 0); + % If no argment: return the empty structure + if (nargin == 0) || isempty(jTree) + return + end + + % === GET FILES IN TREE === + % Get tree nodes + bstNodes = gui_stat_common('GetTreeNodes', jTree); + % For each node: get dependencies + iStudies = []; + iItems = []; + for iNode = 1:length(bstNodes) + [iNewStudies, iNewItems] = tree_getDependencies(bstNodes(iNode), DataType, FilterFileTag); + iStudies = [iStudies, iNewStudies]; + iItems = [iItems, iNewItems]; + end + + % === GET SAMPLES DESCRIPTION === + for i = 1:length(iStudies) + % Get study + sStudy = bst_getContext('Study', iStudies(i)); + sSamples(i).iStudy = iStudies(i); + sSamples(i).iItem = iItems(i); + % Get subject + sSamples(i).SubjectFile = sStudy.BrainStormSubject; + sSubject = bst_getContext('Subject', sSamples(i).SubjectFile); + sSamples(i).SubjectName = sSubject.Name; + % Data or results + switch lower(DataType) + case 'data' + sSamples(i).FileName = sStudy.Data(iItems(i)).FileName; + sSamples(i).Comment = sStudy.Data(iItems(i)).Comment; + case 'results' + sSamples(i).FileName = sStudy.Result(iItems(i)).FileName; + sSamples(i).Comment = sStudy.Result(iItems(i)).Comment; + otherwise + error('???'); + end + % Full filename + sSamples(i).FullFileName = fullfile(ProtocolInfo.STUDIES, sSamples(i).FileName); + % Condition + if ~isempty(sStudy.Condition) + sSamples(i).Condition = sStudy.Condition{1}; + else + sSamples(i).Condition = sStudy.Name; + end + end +end + +%% ===== GET CONDITIONS ===== +% Return the current Conditions structure: +% |- DataType: {'data', 'results'} +% |- SamplesA: +% | |- iStudies: Array of study indices +% | |- iItems: Array of data or results indices +% |- SamplesB: (NULL if only one condition) +% |- iStudies: Array of study indices +% |- iItems: Array of data or results indices +% +% USAGE: Cond = GetConditions() +% Cond = GetConditions(FilterFileTag) +% +% INPUT: +% - FilterFileTag: Put a condition to the filenames to be selected +% 'normal' excludes file tags : 'zscore', 'timemean' +function Conditions = GetConditions(PanelName, FilterFileTag) + % Parse inputs + if (nargin < 2) + FilterFileTag = ''; + end + % Get data type + Conditions.DataType = GetDataType(PanelName); + % Get panel controls + ctrl = bst_getContext('PanelControls', PanelName); + + % What is the calling panel: stat or processes + switch (PanelName) + case 'Processes' + Conditions.NbSamplesSets = 1; + Conditions.SamplesA = GetSamples(ctrl.jTreeFiles, Conditions.DataType, FilterFileTag); + Conditions.SamplesB = GetSamples(); + case 'Statistics' + Conditions.NbSamplesSets = 2; + Conditions.SamplesA = GetSamples(ctrl.jTreeFilesA, Conditions.DataType, FilterFileTag); + Conditions.SamplesB = GetSamples(ctrl.jTreeFilesB, Conditions.DataType, FilterFileTag); + %Allow one-sample stats + if isempty(Conditions.SamplesB) + Conditions.NbSamplesSets = 1; + end + otherwise + error('???'); + end +end + + + diff --git a/brainstorm3/import_anova.m b/brainstorm3/import_anova.m new file mode 100644 index 0000000..266a838 --- /dev/null +++ b/brainstorm3/import_anova.m @@ -0,0 +1,438 @@ +function [sTargetStudy] = import_anova(Conditions, sProcess, OPTIONS, TimeVector, pmap, tmap) +% [] = import_anova(Conditions, sProcess, OPTIONS, TimeVector,pmap, fmap) + +SamplesA = Conditions.SamplesA; + +% % Get condition StimRightThumb +% [sStudy, iStudy] = bst_getContext('StudyWithCondition', 'Subject01/StimRightThumb'); +% +% +% %% ===== SELECT FILES ===== +% % Get the two kernels computed in tutorial #7: the regular and the shared one +% iRes1 = find(~cellfun(@(c)isempty(strfind(c, 'MN: kernel')), {sStudy.Result.Comment})); +% iRes2 = find(~cellfun(@(c)isempty(strfind(c, 'MN: shared')), {sStudy.Result.Comment}) & ... +% io_compareFileNames({sStudy.Result.DataFile}, sStudy.Data(1).FileName)); +% % Define the two sets of files, A and B +% FilesA = {sStudy.Result(iRes1(1)).FileName}; +% FilesB = {sStudy.Result(iRes2(1)).FileName}; +% + + + +% === BUILD NEW FILES === +% Display waitbar +% bst_progressBar('start', 'Processes', 'Saving results...'); + +% NB: Format de la structure des arguments : +% +% sProcess = +% Name: 'RM-Anova' +% Comment: 'Anova (under dev.)' +% Description: 'Repeated measures parametric Analysis of Variance' +% FileTag: 'Anova' +% Category: 'Anova' +% UseBaseline: 0 +% DefaultOverwrite: 0 +% isSourceAbsolute: 1 +% isPaired: 0 +% blockDimension: 0 +% isAvgRef: 1 +% +% SamplesA = +% 1x60 struct array with fields: +% iStudy +% iItem +% FileName +% FullFileName +% Comment +% Condition +% SubjectFile +% DataFile +% SubjectName +% +% SamplesA(1) +% ans = +% iStudy: 5 +% iItem: 1 +% FileName: 'S11\avg_HighCorrect\data_lena_CONFINUM.mat' +% FullFileName: 'I:\data\confinum\brainstorm\data\S11\avg_HighCorrect\data_lena_CONFINUM.mat' +% Comment: 'avg_HighCorrect' +% Condition: 'avg_HighCorrect' +% SubjectFile: 'S11/brainstormsubject.mat' +% DataFile: [] +% SubjectName: 'S11' +% SamplesA(2) +% ans = +% iStudy: 14 +% iItem: 1 +% FileName: 'S12\avg_HighCorrect\data_lena_CONFINUM.mat' +% FullFileName: 'I:\data\confinum\brainstorm\data\S12\avg_HighCorrect\data_lena_CONFINUM.mat' +% Comment: 'avg_HighCorrect' +% Condition: 'avg_HighCorrect' +% SubjectFile: 'S12/brainstormsubject.mat' +% DataFile: [] +% SubjectName: 'S12' +% SamplesA(15) +% ans = +% iStudy: 131 +% iItem: 1 +% FileName: 'S27\avg_HighCorrect\data_lena_CONFINUM.mat' +% FullFileName: 'I:\data\confinum\brainstorm\data\S27\avg_HighCorrect\data_lena_CONFINUM.mat' +% Comment: 'avg_HighCorrect' +% Condition: 'avg_HighCorrect' +% SubjectFile: 'S27/brainstormsubject.mat' +% DataFile: [] +% SubjectName: 'S27' +% SamplesA(16) +% ans = +% iStudy: 6 +% iItem: 1 +% FileName: 'S11\avg_HighIncorrect\data_lena_CONFINUM_05.mat' +% FullFileName: 'I:\data\confinum\brainstorm\data\S11\avg_HighIncorrect\data_lena_CONFINUM_05.mat' +% Comment: 'avg_HighIncorrect' +% Condition: 'avg_HighIncorrect' +% SubjectFile: 'S11/brainstormsubject.mat' +% DataFile: [] +% SubjectName: 'S11' +% +% +% OPTIONS = +% isData: 1 +% Comment: 'Anova' +% isAbsoluteValues: 0 +% sProcess: [1x1 struct] +% nbPermutation: 10000 +% Factors: [] +% isOverwriteFiles: 0 +% OutputType: 'database' +% ForceOutputCond: [] +% isCluster: 0 +% isClusterAverage: 0 +% sClusters: [] +% ClustersOptions: [] +% Time: [-0.2998 0.5996] +% Baseline: [-0.2998 3.3000e-004] +% iTime: [1x921 double] +% iBaseline: [1x308 double] +% Conditions: [1x1 struct] + + + +% load bst_stat_struct.mat + + +sProcess.Name = 'RM-ANOVA' + +[sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess, SamplesA, SamplesA([]), OPTIONS); + +ChannelFlag = []; +% Get default structure +newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 0); + +% Comment +newFileMat.Comment = OPTIONS.Comment ; +% if 0% numel(fx{i_fx}) == 1 +% newFileMat.Comment = [newFileMat.Comment ' - Main effect of ']; +% else +% newFileMat.Comment = [newFileMat.Comment ' - Interaction of ']; +% end +%newFileMat.Comment = [newFileMat.Comment sprintf('%s * ',Factors.Names{fx{i_fx}})]; + +% Save P and F maps + +newFileMat.pmap = pmap; +newFileMat.tmap = tmap; +% Save new file and register in database +sTargetStudy = SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); +end + +%% ====================================================================================== +% ===== HELPERS ======================================================================== +% ====================================================================================== +%% ===== CREATE DEFAULT OUTPUT STRUCTURE ===== +function sFileMat = CreateDefaultStruct(sProcess, FileName, isData, TimeVector, iTime, ChannelFlag, isOneOutputMat, isSampleBySample) +% Default structures for stat +isStat = 1% ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); +if isStat + sStat = struct(... + 'Type', '', ... + 'Comment', '', ... + 'Time', TimeVector, ... + 'ChannelFlag', ChannelFlag, ... + 'pmap', [], ... + 'tmap', [], ... + 'pThreshold', 0.05); +end + +% If recordings +if isData + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'data'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + % Data + else + sFileMat.Time = TimeVector; + sFileMat.F = []; + end + % Else: sources +else + % Get protocol directories + ProtocolInfo = bst_get('ProtocolInfo'); + % Resolve link, if it is a link + [FileName, DataFile] = resolveResultsLink(FileName); + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'presults'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + else + % Time + sFileMat.Time = iTime; + sFileMat.ImageGridTime = TimeVector; + % Reset some fields + sFileMat.OPTIONS.Data = []; + sFileMat.Fsynth = []; + sFileMat.ImagingKernel = []; + sFileMat.ImageGridAmp = []; + if ~isSampleBySample + sFileMat.DataFile = []; + elseif ~isempty(DataFile) + sFileMat.DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + end + end + % Remove "Kernel" indications in the Comment field + sFileMat.Comment = strrep(sFileMat.Comment, '(Kernel)', ''); + sFileMat.Comment = strrep(sFileMat.Comment, 'Kernel', ''); +end +% Bad channels list +sFileMat.ChannelFlag = ChannelFlag; + +% Add some fields for exported results +if isOneOutputMat + sFileMat.DescFileName = {}; + sFileMat.DescCluster = {}; + sFileMat.DescProcessType= sProcess.Name; +end + +end + + +%% ===== SAVE NEW FILE ===== +function sTargetStudy = SaveNewFile(newFileMat, sProcess, isData, iTargetStudy, sTargetStudy, InputFile) +% Get protocol directories +ProtocolInfo = bst_get('ProtocolInfo'); +% Get default output file +OutputDir = fullfile(ProtocolInfo.STUDIES, fileparts(sTargetStudy.FileName)); +FullFileName = GetDefaultFileName(sProcess, isData, OutputDir, InputFile); +% Save in database +save(FullFileName, '-struct', 'newFileMat'); +% Register in database +isStat = 1 % ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); + +% why removing the path ?? +FileName = strrep(FullFileName, ProtocolInfo.STUDIES, ''); +sTargetStudy = RegisterNewFile(newFileMat, FileName, isData, isStat, iTargetStudy); + +end + + +% ===== GET OUTPUT STUDY ===== +function [sOutputStudy, iOutputStudy, isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA,SamplesB,OPTIONS) +% Get some properties of the filter +isMixedSubjectsAB = isempty(SamplesB) || ~isequal({SamplesA.SubjectFile}, {SamplesB.SubjectFile}); +isSampleBySample = ismember(sProcess.Category, {'Filter2', 'Filter', 'Extract'}); +isConditionByCondition = strcmpi(sProcess.Name, 'GAVE'); +isNewConditions = 0; +% Get the list of involved studies +uniqueStudiesInd = unique([SamplesA.iStudy, SamplesB.iStudy]); +% Comment = OPTIONS.Comment; +Comment = ''; + +% ===== CHECK SUBJECT UNICITY ===== +% Get full subjects list without repetitions +uniqueSubjectFiles = unique(cat(2, {SamplesA.SubjectFile}, {SamplesB.SubjectFile})); +% For stat on sources: all the results files must be computed on the same surface. +% => else, the number of sources might be different between different files +% => user should realign surfaces before going on +if (length(uniqueSubjectFiles) > 1) + isUniqueSubject = 0; + if ~isSampleBySample && ~OPTIONS.isData + % If there is more than one subjects involved: need to check that all + % the subjects use the default anatomy + for i = 1:length(uniqueSubjectFiles) + sSubject = bst_get('Subject', uniqueSubjectFiles{i}); + if ~sSubject.UseDefaultAnat + gui_hidePanel('panel_statRun'); + sOutputStudy = []; + iOutputStudy = []; + bst_error(['The sources files you selected use different anatomies.' 10 ... + 'In order to perform any computation on sources, all the files' 10 ... + 'should use the same anatomy.' 10 10 ... + 'You have to project all your results on a template anatomy.' 10 ... + 'Popup menu: "Project sources on default anatomy".'], 'Processes', 0); + return; + end + end + end +else + isUniqueSubject = 1; +end + +% ===== GET OUTPUT STUDY ===== +% SUBJECT AVERAGE +if strcmpi(sProcess.Name, 'SubjAvg') + % Get subject + [sSubject, iSubject] = bst_get('Subject', SamplesA(1).SubjectFile); + % Get "intra" study for this subject + [sOutputStudy, iOutputStudy] = bst_get('AnalysisIntraStudy', iSubject); + % Comment + Comment = ['SubjectAvg(' SamplesA(1).SubjectName ')']; + % UNIQUE STUDY (OR OVERWRITE) +elseif (length(uniqueStudiesInd) == 1) || OPTIONS.isOverwriteFiles + % Get this unique study + [sOutputStudy, iOutputStudy] = bst_get('Study', uniqueStudiesInd(1)); + % MULTIPLE STUDIES : SAMPLE BY SAMPLE +elseif isSampleBySample && ~isMixedSubjectsAB + % Target study is a new condition (name = test comment) + % Get subject path + newCondPath = fileparts(SamplesA(1).SubjectFile); + % Get new condition name + localCond = struct('SamplesA',SamplesA,'SamplesB',SamplesB); + newCondName = panel_statRun('FormatComment', sProcess, localCond, OPTIONS.Time); + newCondName = io_standardizeFileName(newCondName); + % Comment + Comment = sProcess.FileTag; + Comment = strrep(Comment, '#A#', localCond.SamplesA(1).Comment); + Comment = strrep(Comment, '#B#', localCond.SamplesB(1).Comment); + % Try to get an existing condition with this path + [sOutputStudy, iOutputStudy] = bst_get('StudyWithCondition', fullfile(newCondPath,newCondName)); + % If does not exist: Create a new condition + if isempty(sOutputStudy) + iOutputStudy = db_addCondition(newCondPath, newCondName, 'NoRefresh'); + sOutputStudy = bst_get('Study', iOutputStudy); + isNewConditions = 1; + end + % MULTIPLE STUDIES : CONDITION BY CONDITION +elseif isConditionByCondition + Comment = ['GAVE(' SamplesA(1).Condition ')']; + % Grand average: stored in 'analysis-inter' node + [sOutputStudy, iOutputStudy] = bst_get('AnalysisInterStudy'); + % MULTIPLE STUDIES : GLOBAL +else + % UNIQUE SUBJECT : 'analysis-intra' + if isUniqueSubject + % Subject file is the same for all the studies => find common subject + [sSubject, iSubject] = bst_get('Subject', SamplesA(1).SubjectFile); + % Get 'analysis-intra' node of this subject + [sOutputStudy, iOutputStudy] = bst_get('AnalysisIntraStudy', iSubject); + % MULTIPLE SUBJECTS : 'analysis-inter' + else + % Get 'analysis-inter' node in current protocol + [sOutputStudy, iOutputStudy] = bst_get('AnalysisInterStudy'); + end +end +% Error ? +if isempty(sOutputStudy) + error('Cannot find an analysis study to store the results.'); +end + +% ===== COMBINE CHANNEL FILES ===== +% If source and target studies are not the same +if ~isequal(uniqueStudiesInd, iOutputStudy) + % Destination study for new channel file + [tmp__, iChanStudyDest] = bst_get('ChannelForStudy', iOutputStudy); + % Source channel files studies + [tmp__, iChanStudySrc] = bst_get('ChannelForStudy', uniqueStudiesInd); + % If target study has no channel file: create a new one by combination of the others + isNewChannelFile = db_combineChannelFiles(unique(iChanStudySrc), iChanStudyDest, [], ~OPTIONS.isData); + % Reload target study if it changed (new channel file) + if isNewChannelFile + sOutputStudy = bst_get('Study', iOutputStudy); + tree_updateModel(); + end +end +end + + +%% ===== GET DEFAULT FILE NAME ===== +function OutputFile = GetDefaultFileName(sProcess, isData, OutputDir, InputFile) + % Get date and time for filename + c = clock; + strTime = sprintf('_%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + + % Output file tag + + if ismember(sProcess.Category, {'TTest', 'PermTest', 'ANOVA'}) + if isData + fileTag = 'pdata'; + else + fileTag = 'presults'; + end + else + if isData + fileTag = 'data'; + else + fileTag = 'results'; + end + end + + % Other tags present in input file + if ~isempty(strfind(InputFile, '_zscore')) + strInputTags = '_zscore'; + else + strInputTags = ''; + end + + % Default filename + defFileName = [fileTag '_' sProcess.Name strTime strInputTags '.mat']; + % File in the target study + OutputFile = fullfile(OutputDir, defFileName); + % Make filename unique + OutputFile = io_makeUniqueFilename(OutputFile); +end + + + + +%% ===== REGISTER NEW FILE ===== +function sStudy = RegisterNewFile(FileMat, FileName, isData, isStat, iStudy) + % Get study + sStudy = bst_get('Study', iStudy); + % Stat + if isStat + % Create new stat file descriptor + % sNewStat = db_getDataTemplate('Stat'); + sNewStat = db_template('stat'); + sNewStat.FileName = FileName; + sNewStat.Comment = FileMat.Comment; + sNewStat.Type = FileMat.Type; + sNewStat.pThreshold = FileMat.pThreshold; + % Add it to study + sStudy.Stat(end+1) = sNewStat; + % Data + elseif isData + % Create new data descriptor + sNewData = db_template('data'); + sNewData.FileName = FileName; + sNewData.Comment = FileMat.Comment; + % Add it to study + sStudy.Data(end+1) = sNewData; + % Results + else + % Create new results descriptor + sNewResult = db_template('results'); + sNewResult.FileName = FileName; + sNewResult.Comment = FileMat.Comment; + sNewResult.DataFile = FileMat.DataFile; + % Add it to study + sStudy.Result(end+1) = sNewResult; + end + % Update database + bst_set('Study', iStudy, sStudy); +end \ No newline at end of file diff --git a/brainstorm3/knd_rmanova_files.m b/brainstorm3/knd_rmanova_files.m new file mode 100644 index 0000000..a08596d --- /dev/null +++ b/brainstorm3/knd_rmanova_files.m @@ -0,0 +1,180 @@ +function [p,F,fx,ChannelFlag, TimeVector] = knd_rmanova_files(SamplesA,OPTIONS) +% knd_rmanova_files - repeated measure anova + +%SamplesA = SamplesA([SamplesA.iItem]== 4) + +%OPTIONS.iTime = 599:630 + +[X1, ChannelFlag, TimeVector] = buildDataArray({SamplesA.FullFileName}, OPTIONS.iTime); +if OPTIONS.isAbsoluteValues + X1 = abs(X1); +end +%TimeVector=round(mean(TimeVector)); +% X1=mean(X1,3); +sX=size(X1); +% X= subj * C/I * H/L +X1=reshape(X1,[15 2 2 sX(2:end)]); +% X= C/I * H/L * Subj * vertices +X1=permute(X1,[2 3 1 4:ndims(X1)]); +[p,F,fx]=myrmanova(X1,2,1:2,[],0); +return + + + +% %% Get conditions common to all subjects +% function [isCommon]=GetCommonConditions(Samples) +% [C,iC,jC] = unique({Conditions.Samples.Condition}'); +% [S,jS,jS] = unique({Samples.SubjectName}); +% isCommon(iC) = 0*jC; +% for i = 1:numel(C) +% if isempty(setdiff(1:NS,jS(jC==i))) +% isCommon(jC==i) = 1; +% end +% end +% end +% + +%% ===== BUILD DATA ARRAY ===== +function [X, ChannelFlag, Time] = buildDataArray(sampleFiles, iTime) +% Read out the data from multiple files and store in larger array X +% Parameters: +% - sampleFiles : cell array of data file names +% - Time : time values of the samples to extract +% - isData : a flag; 0 means read from Results file, 1 from surface data file + +% Open progress bar +isNewProgressBar = ~bst_progressBar('isvisible'); +if isNewProgressBar + bst_progressBar('start', 'Loading samples...', 'Processes', 0, length(sampleFiles)); +end +ChannelFlag = []; + +% Process all the samples files +for k = 1:length(sampleFiles) + % Progress bar + bst_progressBar('inc', 1); + bst_progressBar('text', ['File: ' sampleFiles{k}]); + % Read matrix + [matValues, matName, tmpChannelFlag, TimeVector] = bst_readMatrixInFile(sampleFiles{k}, iTime); + % Get time for the specified indices + % Bug: Time = TimeVector(iTime); + Time = TimeVector; + % Add bad channels to list of bad channels + if isempty(ChannelFlag) + ChannelFlag = tmpChannelFlag; + else + ChannelFlag(tmpChannelFlag == -1) = -1; + end + % Initialize large array + if (k == 1) + X = zeros(length(sampleFiles), size(matValues,1), size(matValues,2)); + end + + % Store read values in full data array + try + X(k,:,:) = matValues; + catch + error('Please first check that all the files in your samples have the same of channels/sources. Consider registering the MEG/EEG data to the same sensor cap'); + end +end + +if isNewProgressBar + bst_progressBar('stop'); +end + +return + + +%function [p, t, ChannelFlag, TimeA, TimeB] = knd_ttest_files(FilesListA, FilesListB, wtest, iTimeA, iTimeB, varargin) + +% KND_TTEST_FILES: Student's t-tests for EEG/MEG recordings or sources, across trials or subjects. +% +% USAGE: [p, t, ChannelFlag, TimeA, TimeB] = knd_ttest_files(FilesListA, FilesListB, wtest, iTimeA, iTimeB) +% [p, t, ChannelFlag, TimeA, TimeB] = knd_ttest_files(FilesListA, FilesListB, wtest) +% [p, t, ChannelFlag, TimeA, TimeB] = knd_ttest_files(FilesListA, FilesListB) +% [p, t, ChannelFlag, TimeA, TimeB] = knd_ttest_files(..., 'AbsoluteValues'); + + + +% +% DESCRIPTION: +% Gives the probability that Student's t calculated on sets A and B, sampled from two +% distributions is higher than observed, i.e. the "significance" level. +% This is used to test whether two samples have significantly different means. +% +% INPUT: +% - FilesListA : Cell-array of paths to brainstorm recordings or sources files. +% - FilesListB : Cell-array of paths to brainstorm recordings or sources files. +% - wtest : String that specifies the test to be used. Possible values: +% - 'ttest' : t-test for equal variances [default] +% - 'uttest' : t-test for unequal variances +% - 'pttest' : t-test for paired samples +% - iTimeA : Time indices used from samples A +% - iTimeB : Time indices used from samples B +% - AbsoluteValues : Use absolute values of samples +% +% OUTPUT: +% - P : Probability map +% The smaller P is, the more significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the two sets are +% sampled from distributions with different means. +% - T : Value of Student's t +% - ChannelFlag : Array with one entry per channel: +% -1 means that the channel was marked as bad in at least one of the input files +% 1 means that the channel was marked as good in all the input files + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: K. N'Diaye, 2005 (Adapted from C. Goutte's functions) +% ----------------------------- Script History --------------------------------- +% KND 20-Apr-2005 Creation +% FT 24-Jun-2008 Adaptation for brainstorm3 +% ------------------------------------------------------------------------------ + + + + + + +%% ===== PARSE INPUTS ===== +if (nargin < 5) + iTimeA = []; + iTimeB = []; +end +% OPTIONS +isAbsoluteValues = 0; +if (length(varargin) >= 1) + if any(strcmpi(varargin, 'AbsoluteValues')) + isAbsoluteValues = 1; + end +end +% Dimensions +n1 = length(FilesListA); +n2 = length(FilesListB); +% There must be at least two samples in each set +if (n1 <= 1) || (n2 <= 1) + error('There must be at least two samples in each set.'); +end +% If paired test: number of samples must be equal +if strcmpi(wtest, 'pttest') && (n1 ~= n2) + error('For a paired t-test, number of samples must be equal in the two datasets'); +end +if (length(iTimeA) ~= length(iTimeB)) + error('You must specify the same numer of time samples for both datasets.'); +end \ No newline at end of file diff --git a/brainstorm3/om_load_full.m b/brainstorm3/om_load_full.m new file mode 100644 index 0000000..94c82f7 --- /dev/null +++ b/brainstorm3/om_load_full.m @@ -0,0 +1,6 @@ +function data = om_load_full(filename) + file = fopen(filename,'r'); + dims = fread(file,2,'uint32','ieee-le'); + data = fread(file,prod(dims),'double','ieee-le'); + data = reshape(data,dims'); + fclose(file); diff --git a/brainstorm3/private/gui_setEnabledControls.m b/brainstorm3/private/gui_setEnabledControls.m new file mode 100755 index 0000000..a614faf --- /dev/null +++ b/brainstorm3/private/gui_setEnabledControls.m @@ -0,0 +1,62 @@ +function gui_setEnabledControls( controls, status, isRecursive ) +% GUI_SETENABLEDCONTROLS: Enable/disable control and control's children. +% +% USAGE: gui_setEnabledControls( controls, status, isRecursive); +% +% INPUT: +% - controls : array of java components handles +% - status : {0,1} - If 1, controls are enabled +% - isRecursive : enable/disable component's children recursively + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + + +if (nargin < 3) + isRecursive = 1; +end +for iControl = 1:length(controls) + ctrl1 = controls(iControl); + % Enable/Disable component + ctrl1.setEnabled(status); + % And all its children components + if isRecursive && ~isa(ctrl1, 'javax.swing.JList') + for iChild = 1:ctrl1.getComponentCount() + ctrl2 = ctrl1.getComponent(iChild - 1); + % Enable/Disable component child + ctrl2.setEnabled(status); + % And all its sub-children components + for iChildChild = 1:ctrl2.getComponentCount() + ctrl3 = ctrl2.getComponent(iChildChild - 1); + ctrl3.setEnabled(status); + for iChildChildChild = 1:ctrl3.getComponentCount() + ctrl4 = ctrl3.getComponent(iChildChildChild - 1); + ctrl4.setEnabled(status); + end + end + end + end +end + + + diff --git a/brainstorm3/private/gui_stat_common.m b/brainstorm3/private/gui_stat_common.m new file mode 100755 index 0000000..57b4a85 --- /dev/null +++ b/brainstorm3/private/gui_stat_common.m @@ -0,0 +1,311 @@ +function varargout = gui_stat_common(varargin) +% GUI_STAT_COMMON: Support functions, common to all the stat GUI. + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2009 +% ----------------------------- Script History --------------------------------- +% FT 10-Jul-2009 Creation +% ------------------------------------------------------------------------------ + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CHECK CONDITIONS ===== +function isOk = CheckConditions(PanelName) + global GlobalData; + isOk = 0; + + % ===== GET SAMPLES ===== + % Get conditions + Conditions = gui_stat_common('GetConditions', PanelName); + if isempty(Conditions) + return + end + isData = strcmpi(Conditions.DataType, 'data'); + % Check samples number + switch lower(PanelName) + case 'statistics' + iStudies = [Conditions.SamplesA.iStudy, Conditions.SamplesB.iStudy]; + iItems = [Conditions.SamplesA.iItem, Conditions.SamplesB.iItem]; + SamplesFiles = cat(2, GlobalData.Stat.SampleFilesAA, GlobalData.Stat.SampleFilesAB); + case 'processes' + iStudies = [Conditions.SamplesA.iStudy]; + iItems = [Conditions.SamplesA.iItem]; + SamplesFiles = GlobalData.Stat.SampleFilesA; + end + + % ===== CHECK FOR MODIFICATIONS ===== + % Check number of elements + if (length(SamplesFiles) ~= length(iStudies)) + return + end + % Check all the samples + for i = 1:length(SamplesFiles) + % Get study + sStudy = bst_getContext('Study', iStudies(i)); + if isempty(sStudy) + return + end + % Get filenames + if isData + if (iItems(i) > length(sStudy.Data)) + return + end + CurFile = sStudy.Data(iItems(i)).FileName; + else + if (iItems(i) > length(sStudy.Result)) + return + end + CurFile = sStudy.Result(iItems(i)).FileName; + end + % Compare with saved filename + if ~io_compareFileNames(CurFile, SamplesFiles{i}) + return + end + end + isOk = 1; +end + + +%% ===== TREE KEYBOARD CALLBACK ===== +function TreeKeyboard_Callback(hObj, ev) + % Switch between actions + switch (ev.getKeyCode()) + % DELETE/BACKSPACE : DELETE NODE CALLBACK + case {ev.VK_DELETE, ev.VK_BACK_SPACE} + DeleteSelectedNodes(ev.getSource()); + end +end + + +%% ===== GET SELECTED DATA TYPE ===== +function DataType = GetDataType(panelName) + % Get panel controls + ctrl = bst_getContext('PanelControls', panelName); + % Get DataType + if ctrl.jButtonRecordings.isSelected() + DataType = 'data'; + else + DataType = 'results'; + end +end + + +%% ===== DELETE SELECTED NODES ===== +function DeleteSelectedNodes(bstTree) + % Get selected nodes + treeModel = awtinvoke(bstTree, 'getModel()'); + treeSelPaths = awtinvoke(bstTree, 'getSelectionPaths()'); + % Delete each selected node + for iNode = 1:length(treeSelPaths) + awtinvoke(treeModel, 'removeNodeFromParent(Ljavax.swing.tree.MutableTreeNode;)', ... + treeSelPaths(iNode).getLastPathComponent()); + end + awtinvoke(bstTree, 'refresh()'); +end + + +%% ===== GET NODES IN TREE ===== +function bstNodes = GetTreeNodes(bstTree) + % Get root node + nodeRoot = bstTree.getModel.getRoot(); + if (nodeRoot.getChildCount() == 0) + bstNodes = []; + return + end + % Get all the children + bstNodes = javaArray('org.brainstorm.tree.BstNode', nodeRoot.getChildCount()); + for i = 1:nodeRoot.getChildCount() + bstNodes(i) = nodeRoot.getChildAt(i-1); + end +end + + +%% ===== UPDATE ITEM COUNTS ===== +function UpdateItemProperties(bstTree, listName, isForced) + global GlobalData; + % Parse inputs + if (nargin < 3) + isForced = 0; + end + + % === COUNT ITEMS DEPENDENCIES === + % Get nodes in target tree + bstNodes = GetTreeNodes(bstTree); + % Get options + if strcmpi(listName, 'SampleFilesA') + DataType = GetDataType('Processes'); + else + DataType = GetDataType('Statistics'); + end + iAllStudies = []; + iAllItems = []; + % For each node: update item count in comment + for iNode = 1:length(bstNodes) + % Get number of dependent items + [iDepStudies, iDepItems] = tree_getDependencies(bstNodes(iNode), DataType); + iAllStudies = [iAllStudies, iDepStudies]; + iAllItems = [iAllItems, iDepItems]; + % Ignore nodes that were already processed + nodeComment = char(bstNodes(iNode).getComment()); + if ~isempty(strfind(nodeComment, '[')) && ~isForced + continue; + end + % Remove previous items count + nodeComment = strRemoveParenthesis(nodeComment, '['); + % Add items count + nodeComment = sprintf('%s [%d]', nodeComment, length(iDepItems)); + % Update node comment + awtinvoke(bstNodes(iNode), 'setComment(Ljava.lang.String;)', nodeComment); + end + % Compute total number of items + totalNbItems = length(iAllItems); + % Save the sample filenames (to be able to check for database modifications later) + SampleFiles = bst_getContext('GetFileNames', iAllStudies, iAllItems, DataType); + GlobalData.Stat.(listName) = SampleFiles; + + % === UPDATE TREE DISPLAY (items and title) === + jParentPanel = bstTree.getParent.getParent.getParent(); + titledBorder = jParentPanel.getBorder(); + strTitle = strRemoveParenthesis(char(titledBorder.getTitle()), '['); + strTitle = sprintf('%s [%d]', strTitle, totalNbItems); + awtinvoke(titledBorder, 'setTitle(Ljava.lang.String;)', strTitle); + %jParentPanel.updateUI(); + awtinvoke(bstTree, 'updateUI()'); + awtinvoke(jParentPanel, 'updateUI()'); +end + + +%% ===== GET SAMPLES ===== +% USAGE: sSamples = GetSamples(jTree, DataType, FilterFileTag) : Return all the samples in JTree +% sSamples = GetSamples() : Return an empty samples structure +function sSamples = GetSamples(jTree, DataType, FilterFileTag) + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Samples structure + sSamples = repmat(struct('iStudy', 0, ... + 'iItem', 0, ... + 'FileName', '', ... + 'FullFileName', '', ... + 'Comment', '', ... + 'Condition', '', ... + 'SubjectFile', ''), 0); + % If no argment: return the empty structure + if (nargin == 0) || isempty(jTree) + return + end + + % === GET FILES IN TREE === + % Get tree nodes + bstNodes = gui_stat_common('GetTreeNodes', jTree); + % For each node: get dependencies + iStudies = []; + iItems = []; + for iNode = 1:length(bstNodes) + [iNewStudies, iNewItems] = tree_getDependencies(bstNodes(iNode), DataType, FilterFileTag); + iStudies = [iStudies, iNewStudies]; + iItems = [iItems, iNewItems]; + end + + % === GET SAMPLES DESCRIPTION === + for i = 1:length(iStudies) + % Get study + sStudy = bst_getContext('Study', iStudies(i)); + sSamples(i).iStudy = iStudies(i); + sSamples(i).iItem = iItems(i); + % Get subject + sSamples(i).SubjectFile = sStudy.BrainStormSubject; + sSubject = bst_getContext('Subject', sSamples(i).SubjectFile); + sSamples(i).SubjectName = sSubject.Name; + % Data or results + switch lower(DataType) + case 'data' + sSamples(i).FileName = sStudy.Data(iItems(i)).FileName; + sSamples(i).Comment = sStudy.Data(iItems(i)).Comment; + case 'results' + sSamples(i).FileName = sStudy.Result(iItems(i)).FileName; + sSamples(i).Comment = sStudy.Result(iItems(i)).Comment; + otherwise + error('???'); + end + % Full filename + sSamples(i).FullFileName = fullfile(ProtocolInfo.STUDIES, sSamples(i).FileName); + % Condition + if ~isempty(sStudy.Condition) + sSamples(i).Condition = sStudy.Condition{1}; + else + sSamples(i).Condition = sStudy.Name; + end + end +end + +%% ===== GET CONDITIONS ===== +% Return the current Conditions structure: +% |- DataType: {'data', 'results'} +% |- SamplesA: +% | |- iStudies: Array of study indices +% | |- iItems: Array of data or results indices +% |- SamplesB: (NULL if only one condition) +% |- iStudies: Array of study indices +% |- iItems: Array of data or results indices +% +% USAGE: Cond = GetConditions() +% Cond = GetConditions(FilterFileTag) +% +% INPUT: +% - FilterFileTag: Put a condition to the filenames to be selected +% 'normal' excludes file tags : 'zscore', 'timemean' +function Conditions = GetConditions(PanelName, FilterFileTag) + % Parse inputs + if (nargin < 2) + FilterFileTag = ''; + end + % Get data type + Conditions.DataType = GetDataType(PanelName); + % Get panel controls + ctrl = bst_getContext('PanelControls', PanelName); + + % What is the calling panel: stat or processes + switch (PanelName) + case 'Processes' + Conditions.NbSamplesSets = 1; + Conditions.SamplesA = GetSamples(ctrl.jTreeFiles, Conditions.DataType, FilterFileTag); + Conditions.SamplesB = GetSamples(); + case 'Statistics' + Conditions.NbSamplesSets = 2; + Conditions.SamplesA = GetSamples(ctrl.jTreeFilesA, Conditions.DataType, FilterFileTag); + Conditions.SamplesB = GetSamples(ctrl.jTreeFilesB, Conditions.DataType, FilterFileTag); + otherwise + error('???'); + end +end + + + diff --git a/brainstorm3/sTargetStudy_struct.mat b/brainstorm3/sTargetStudy_struct.mat new file mode 100644 index 0000000000000000000000000000000000000000..64ec1016c0d0f8be72e981dc079f1c3a4afc4e9c GIT binary patch literal 1336 zcmb8ci$Bu|00401b=1i`N=^LMr*exihJ+8+qK|IE4pVJ3XC4_DHVqpo3bmC;VR49Z z2*X8KsXW4l6y-5x&b*Vy7{9r{;l5utv=uXD&1_peV$X(@vZxDDe_%Ok;ewRyI{R^nC3A2c?5qdHc7A87RvVgM>wr6xWmO}^RL~Cj-1@tOqr(l54*b~g zLAYyEZn9M_y65|T93T>Ssf4Ab@Pos;SIAvNw7JOHN3cQ+5Ut9xzSuR*kc>ihFz2@7 z3&ECW;HI+j9Io2*Js6@X$e3L$k+Am0JV)gGL{O&p)DrH-h?TfMzSG+1r>cl5b=^ty zI=R1OjjF!&7qzjSGJC)Ox78Q9R(hAUHx9v8l2aZ^uv%8R=pwC+jkLwDsr08ry_YF& zLs5dN`D%4BFUw*v(ywleueLHZM79yx^|W>i5A;N4Udy~EF}uRMHhWLG)L>rji=Qed zcsF=G^{5(nmU~p-xVvf4VK5#9TS^_Pa@1B*@+Aqp9tTVxzh6t5aU?^gY&EO;>-<_J z+n;CZtI8gS6pP)qr3vO=5)BKN<(JM*Zl8^YBAlDzi}Lu9;C5CUX#AS{wWokxAS38H zO7$xjoc$2l|0EO4D_O;j2uK4?5FVD=0t1iNm`0`4+DG!?1H!vqt9&KdAWI)Ru^grt zb$aIwt?sqFXkk8!%2aK4UWiut44A5aTdz(#+)`qH z06$(*T8so3aPjsZYWOLFhK6)$>r?VATx~R=D}v9C{CH2y1NF}lz_+@AuC zh?Pn^pM)|Pj9TfN$?*p@%j~*>WBgl}_4gS~-~)~7LxpcAH$R#1pqlxKtoOG?meV2a z`zTxBMh2{C2d{s;nSaM7xsv2r)xKo*@#kQ2AwP-Do-W|v(l_mY@8>^fb`n-9-r4(? pNJO6*OT=%zj;hBuiNU#|nh0DDhchQ(S^MN9+NJj;Mz^)9{09JoozegR literal 0 HcmV?d00001 diff --git a/brainstorm3/script_anova.m b/brainstorm3/script_anova.m new file mode 100644 index 0000000..807f8e5 --- /dev/null +++ b/brainstorm3/script_anova.m @@ -0,0 +1,52 @@ +sModel = struct('Name', '', ... + 'Comment', '', ... + 'Description', '', ... + 'FileTag', '', ... + 'Category', '', ... + 'UseBaseline', 0, ... + 'DefaultOverwrite', 0, ... + 'isSourceAbsolute', 1, ... % If value=2, absolute value for sources is FORCED + 'isPaired', 0, ... + 'blockDimension', 0, ... % Dimension in which the data matrix can be split (0=none, 1=channels, 2=time) + 'isAvgRef', 1); % Compute EEG average reference before processing + +sTest = sModel; +sTest.Name = 'RM-Anova'; +sTest.Comment = 'Anova (under dev.)'; +sTest.FileTag = 'Anova'; +sTest.Description = 'Repeated measures parametric Analysis of Variance'; +sTest.Category = 'Anova'; +sAnova(end + 1) = sTest; + +OPTIONS = struct(); + +isData = 0; + +% Is processing recordings or results +OPTIONS.isData = isData; + + +% Get new file comment +OPTIONS.Comment = deblank(strtrim(char(jTextComment.getText()))); +% Is absolute values (for sources only) +OPTIONS.isAbsoluteValues = 0 ; % ~isData && jCheckAbsoluteValues.isSelected(); +% Get selected process +[OPTIONS.sProcess, selectedTab] = GetSelectedProcess(); + +OPTIONS.Factors = []; + +OPTIONS.isOverwriteFiles = 0; + +OPTIONS.OutputType = 'database'; +OPTIONS.ForceOutputCond = []; +OPTIONS.sClusters = []; +OPTIONS.ClustersOptions = []; + +% Get time +[OPTIONS.Time, OPTIONS.Baseline, OPTIONS.iTime, OPTIONS.iBaseline] = GetTimeWindows(TimeUnit); + +% Get files to batch +OPTIONS.Conditions = Conditions; + +bst_batch(OPTIONS); +panel_stat('ResetPanel'); \ No newline at end of file diff --git a/brainstorm3/script_import_Fmap.m b/brainstorm3/script_import_Fmap.m new file mode 100644 index 0000000..9fdbe26 --- /dev/null +++ b/brainstorm3/script_import_Fmap.m @@ -0,0 +1,135 @@ +% import des r?sultats de l'anovabst de Lydia dans BrainSotmr +% inspir? de TUTORIAL_10_STAT: Script that follows Brainstorm online +% tutorial #10: "Statistics" +%Auteurs: Karim N'Diaye, CTB + +%Alancer avec BrainSorm ouvert, onglet Statistics actif et case "cources" +%coch?e +% Appel import_anova + +%%% constantes +CONDITIONS = {'all_gdavg', 'anova'} + +%CONDITIONS = {'UNIT_EURO' 'UNIT_DOLLAR' 'UNIT_FRANC' 'UNIT_MARK' ... +% 'CENT_EURO' 'CENT_DOLLAR' 'CENT_FRANC' 'CENT_MARK'... +% 'SCR_UNIT_EURO' 'SCR_UNIT_DOLLAR' 'SCR_UNIT_FRANC' 'SCR_UNIT_MARK' ... +% 'SCR_CENT_EURO' 'SCR_CENT_DOLLAR' 'SCR_CENT_FRANC' 'SCR_CENT_MARK'}; + +%Pour ANOVA 3WAY +SUBJECTS = {'ALL'}; + +%Pour ANOVA 4WAY +%SUBJECTS = {'Subject01' 'Subject02' 'Subject03' 'Subject04' 'Subject05' 'Subject06' ... +% 'Subject08' 'Subject09' 'Subject10' 'Subject11' 'Subject12' 'Subject13' ... +% 'Subject21' 'Subject22' 'Subject23' 'SubjectPilot'}; + +path2bst='/data/brainstorm/confinum/data' +%path2bst='/pclxserver/raid6/data/MONEY/BrainStormData/MONEY_4WAY/data/' +path2anovares='.' +StructName='StatSources'; +FilesToFind='MN: MEG(Constr)'; %'MN: MEG(Full,Constr) | zscore' +FileComment='Anova1'; %%% Attention: nom sous lequel le fichier apparaitra dans la base BST +liste_effects=[1 2 12]; +%liste_effects=[1 2 3 12 13 23 123]; +%liste_effects=[1 2 3 4 12 13 14 23 24 34 123 124 134 234 1234]; + +%% Creat File List +i= 1; +clear FilesA +for i_sub=1:length(SUBJECTS) + for i_cond = 1:length(CONDITIONS) + + % Get condition StimRightThumb + [sStudy, iStudy] = bst_get('StudyWithCondition', [ SUBJECTS{i_sub} '/' CONDITIONS{i_cond}]); + + %% ===== SELECT FILES ===== + % Get the two kernels computed in tutorial #7: the regular and the shared one + iRes1 = find(~cellfun(@(c)isempty(strfind(c, FilesToFind)), {sStudy.Result.Comment})) + + iRes1 = iRes1(1); + % Define the list of files A + FilesA(i) = {[path2bst sStudy.Result(iRes1(1)).FileName]}; + i=i+1; + end +end +%% Panel +% Remove previous nodes in the Statistics panel +panel_stat('ResetPanel'); +% Add files to the Statistics panel +nFilesA = gui_stat_common('SetFilesToProcess', 'StatA', FilesA); + +% Set types of files to process: data/results +isData = 0; +if isData + panel_stat('SetFileType', 'data'); +else + panel_stat('SetFileType', 'presults'); +end +% Conditions: structure that define the files in the Processes list +Conditions = gui_stat_common('GetConditions', 'Statistics'); +% Set types of files to process: data/results/timefreq +DataType = 'results'; +panel_processes('SetFileType', DataType); + +%% ===== GET PROCESS ===== +% Get processes list, and pick a process in it +[sProcessesList, sSimpleTests, sPermTests] = panel_statRun('GetProcessesList', 'All'); +% Find a process using its name +ProcessName = 'diffAB'; +iProc = find(strcmpi({sProcessesList.Name}, ProcessName)); +if isempty(iProc) + error('Process not found.'); +end +% Process to use +sProcess = sProcessesList(iProc); + +sProcess.Name='ANOVA' +sProcess.Description = ''; +sProcess.Category = 'ANOVA'; +sProcess.FileTag = '' + +%% ===== TIME ===== +% Use all the time samples +TimeVector = panel_statRun('GetFileTimeVector', Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, DataType); +Time = [TimeVector(1), TimeVector(end)]; +iTime = 1:length(TimeVector); + + +Baseline =[]; +iBaseline =[]; +%% ===== DEFINE OPTIONS ===== +OPTIONS.Conditions = Conditions; % Files to process +OPTIONS.sProcess = sProcess; % Process to apply +OPTIONS.isData = isData; % Process data or recordings +OPTIONS.Comment = 'myanova'; % Default comment for output files (might be overridden) +OPTIONS.OutputType = 'database'; % Where o store the results: {database, file, matlab} +OPTIONS.ForceOutputCond = []; % When you want to store the result in a specific condition (used only when OutputType='database')=> Ex. 'Subject01/@intra' +OPTIONS.isOverwriteFiles = 0; % Overwrite input files, only in the case of filters (one input file = one output file) +OPTIONS.isAbsoluteValues = 1; % Compute the absolute value of the data before applying the process (usually 1 for sources, 0 for recordings) +OPTIONS.Time = Time; % Time window to process [tStart, tStop] in seconds +OPTIONS.iTime = iTime; % Time window: Indices in time vector for the full file +OPTIONS.Baseline = Baseline; % Some processes requires a baseline definition (it is the case for the zscore) +OPTIONS.iBaseline = iBaseline; % => Baseline and iBaseline work exactly the same way as Time and iTime +% Other options we do not use here: +OPTIONS.nbPermutation = 0; % For permuation tests only +OPTIONS.isCluster = 0; % Extract only some clusters/scouts values +OPTIONS.isClusterAverage = 0; % If 1, group all the clusters/scouts; If 0, consider they are separate +OPTIONS.sClusters = []; % Array of scouts/clusters structures +OPTIONS.ClustersOptions = []; % Structure that defines how the clusters/scouts values are computed (fields: function, isAbsolute) +OPTIONS.Baseline = []; +OPTIONS.iBaseline = []; + + +n_effects=size(liste_effects,2); +for i_effects = 1:n_effects + % Call processing function + %OutputFiles = bst_batch(OPTIONS); + load (strcat(path2anovares, StructName, 'F', num2str(liste_effects(i_effects)),'.mat')) + load (strcat(path2anovares, StructName, 'p', num2str(liste_effects(i_effects)),'.mat')) + p = tempStructp.ImageGridAmp; + F = tempStructF.ImageGridAmp; + OPTIONS.Comment=strcat(FileComment,'_F',num2str(liste_effects(i_effects))) + [sTargetStudy] = import_anova(Conditions, sProcess, OPTIONS, TimeVector, p, F); +end + + diff --git a/brainstorm3/script_import_anova.m b/brainstorm3/script_import_anova.m new file mode 100644 index 0000000..b015b76 --- /dev/null +++ b/brainstorm3/script_import_anova.m @@ -0,0 +1,136 @@ +% import des r?sultats de l'anovabst de Lydia dans BrainSotmr +% inspir? de TUTORIAL_10_STAT: Script that follows Brainstorm online +% tutorial #10: "Statistics" +%Auteurs: Karim N'Diaye, CTB + +%Alancer avec BrainSorm ouvert, onglet Statistics actif et case "cources" +%coch?e +% Appel import_anova + +%%% constantes +CONDITIONS = {''} + +%CONDITIONS = {'UNIT_EURO' 'UNIT_DOLLAR' 'UNIT_FRANC' 'UNIT_MARK' ... +% 'CENT_EURO' 'CENT_DOLLAR' 'CENT_FRANC' 'CENT_MARK'... +% 'SCR_UNIT_EURO' 'SCR_UNIT_DOLLAR' 'SCR_UNIT_FRANC' 'SCR_UNIT_MARK' ... +% 'SCR_CENT_EURO' 'SCR_CENT_DOLLAR' 'SCR_CENT_FRANC' 'SCR_CENT_MARK'}; + +%Pour ANOVA 3WAY +SUBJECTS = {'sujet_01' 'sujet_02' 'sujet_03' 'sujet_04' 'sujet_05' 'sujet_06' ... + 'sujet_08' 'sujet_09' 'sujet_10' 'sujet_11' 'sujet_12' 'sujet_13' ... + 'sujet_21' 'sujet_22' 'sujet_23' 'sujet_pilote'}; + +%Pour ANOVA 4WAY +%SUBJECTS = {'Subject01' 'Subject02' 'Subject03' 'Subject04' 'Subject05' 'Subject06' ... +% 'Subject08' 'Subject09' 'Subject10' 'Subject11' 'Subject12' 'Subject13' ... +% 'Subject21' 'Subject22' 'Subject23' 'SubjectPilot'}; + +path2bst='/pclxserver/raid6/data/MONEY/BrainStormData/MONEY/data/' +%path2bst='/pclxserver/raid6/data/MONEY/BrainStormData/MONEY_4WAY/data/' +path2anovares='/pclxserver/raid6/data/MONEY/Analyze16suj/StatSources/RawAbsolute/' +StructName='Sources3way'; +FilesToFind='MN: MEG(Full,Constr)'; %'MN: MEG(Full,Constr) | zscore' +FileComment='AbsRaw_An3F'; %%% Attention: nom sous lequel le fichier apparaitra dans la base BST +%liste_effects=[1 2 12]; +liste_effects=[1 2 3 12 13 23 123]; +%liste_effects=[1 2 3 4 12 13 14 23 24 34 123 124 134 234 1234]; + +%% Creat File List +i= 1; +clear FilesA +for i_sub=1:length(SUBJECTS) + for i_cond = 1:length(CONDITIONS) + + % Get condition StimRightThumb + [sStudy, iStudy] = bst_get('StudyWithCondition', [ SUBJECTS{i_sub} '/' CONDITIONS{i_cond}]); + + %% ===== SELECT FILES ===== + % Get the two kernels computed in tutorial #7: the regular and the shared one + iRes1 = find(~cellfun(@(c)isempty(strfind(c, FilesToFind)), {sStudy.Result.Comment})); + + iRes1 = iRes1(1); + % Define the list of files A + FilesA(i) = {[path2bst sStudy.Result(iRes1(1)).FileName]}; + i=i+1; + end +end +% Remove previous nodes in the Statistics panel +panel_stat('ResetPanel'); +% Add files to the Statistics panel +nFilesA = gui_stat_common('SetFilesToProcess', 'StatA', FilesA); + +% Set types of files to process: data/results +isData = 0; +if isData + panel_stat('SetFileType', 'data'); +else + panel_stat('SetFileType', 'presults'); +end +% Conditions: structure that define the files in the Processes list +Conditions = gui_stat_common('GetConditions', 'Statistics'); +% Set types of files to process: data/results/timefreq +DataType = 'results'; +panel_processes('SetFileType', DataType); + +%% ===== GET PROCESS ===== +% Get processes list, and pick a process in it +[sProcessesList, sSimpleTests, sPermTests] = panel_statRun('GetProcessesList', 'All'); +% Find a process using its name +ProcessName = 'diffAB'; +iProc = find(strcmpi({sProcessesList.Name}, ProcessName)); +if isempty(iProc) + error('Process not found.'); +end +% Process to use +sProcess = sProcessesList(iProc); + +sProcess.Name='ANOVA' +sProcess.Description = ''; +sProcess.Category = 'ANOVA'; +sProcess.FileTag = '' + +%% ===== TIME ===== +% Use all the time samples +TimeVector = panel_statRun('GetFileTimeVector', Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, DataType); +Time = [TimeVector(1), TimeVector(end)]; +iTime = 1:length(TimeVector); + + +Baseline =[]; +iBaseline =[]; +%% ===== DEFINE OPTIONS ===== +OPTIONS.Conditions = Conditions; % Files to process +OPTIONS.sProcess = sProcess; % Process to apply +OPTIONS.isData = isData; % Process data or recordings +OPTIONS.Comment = 'anovalena'; % Default comment for output files (might be overridden) +OPTIONS.OutputType = 'database'; % Where o store the results: {database, file, matlab} +OPTIONS.ForceOutputCond = []; % When you want to store the result in a specific condition (used only when OutputType='database')=> Ex. 'Subject01/@intra' +OPTIONS.isOverwriteFiles = 0; % Overwrite input files, only in the case of filters (one input file = one output file) +OPTIONS.isAbsoluteValues = 1; % Compute the absolute value of the data before applying the process (usually 1 for sources, 0 for recordings) +OPTIONS.Time = Time; % Time window to process [tStart, tStop] in seconds +OPTIONS.iTime = iTime; % Time window: Indices in time vector for the full file +OPTIONS.Baseline = Baseline; % Some processes requires a baseline definition (it is the case for the zscore) +OPTIONS.iBaseline = iBaseline; % => Baseline and iBaseline work exactly the same way as Time and iTime +% Other options we do not use here: +OPTIONS.nbPermutation = 0; % For permuation tests only +OPTIONS.isCluster = 0; % Extract only some clusters/scouts values +OPTIONS.isClusterAverage = 0; % If 1, group all the clusters/scouts; If 0, consider they are separate +OPTIONS.sClusters = []; % Array of scouts/clusters structures +OPTIONS.ClustersOptions = []; % Structure that defines how the clusters/scouts values are computed (fields: function, isAbsolute) +OPTIONS.Baseline = []; +OPTIONS.iBaseline = []; + + +n_effects=size(liste_effects,2); +for i_effects = 1:n_effects + % Call processing function + %OutputFiles = bst_batch(OPTIONS); + load (strcat(path2anovares, StructName, 'F', num2str(liste_effects(i_effects)),'.mat')) + load (strcat(path2anovares, StructName, 'p', num2str(liste_effects(i_effects)),'.mat')) + p = tempStructp.ImageGridAmp; + F = tempStructF.ImageGridAmp; + OPTIONS.Comment=strcat(FileComment,'_F',num2str(liste_effects(i_effects))) + [sTargetStudy] = import_anova(Conditions, sProcess, OPTIONS, TimeVector, p, F); +end + + diff --git a/brainstorm3/script_import_anova_New1.m b/brainstorm3/script_import_anova_New1.m new file mode 100644 index 0000000..526c307 --- /dev/null +++ b/brainstorm3/script_import_anova_New1.m @@ -0,0 +1,132 @@ +% TUTORIAL_10_STAT: Script that follows Brainstorm online tutorial #10: "Statistics" +% +% USAGE: +% 1) Run first the previous tutorials (#2, #3, #5, #6, #7) +% 2) Run this script + +% DESCRIPTION: Compute the difference between the two sources files that were computed in tutorial #7. + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Author: Francois Tadel, 2010 + + +%% ===== START BRAINSTORM ===== +% Add brainstorm.m path to the path +addpath(fileparts(fileparts(fileparts(mfilename('fullpath'))))); +% If brainstorm is not running yet: Start brainstorm without the GUI +if ~brainstorm('status') + brainstorm nogui +end + +CONDITIONS = {'avg_HighCorrect' 'avg_HighIncorrect' 'avg_LowCorrect' 'avg_LowIncorrect' } +SUBJECTS = cellstr(reshape(sprintf('S%02d',[11 12 14:23 25:27]),3,[])'); +%% Creat File List +i= 1; +clear FilesA +for i_sub=1:length(SUBJECTS) + for i_cond = 1:4 + + % Get condition StimRightThumb + [sStudy, iStudy] = bst_getContext('StudyWithCondition', [ SUBJECTS{i_sub} '/' CONDITIONS{i_cond}]); + + %% ===== SELECT FILES ===== + % Get the two kernels computed in tutorial #7: the regular and the shared one + iRes1 = find(~cellfun(@(c)isempty(strfind(c, 'MN: EEG (scalp)(Kernel)')), {sStudy.Result.Comment})); + + iRes1 = iRes1(1); + % Define the list of files A + FilesA(i) = {['I:\data\confinum\brainstorm\data' sStudy.Result(iRes1(1)).FileName]}; + i=i+1; + end +end +% Remove previous nodes in the Statistics panel +panel_stat('ResetPanel'); +% Add files to the Statistics panel +nFilesA = gui_stat_common('SetFilesToProcess', 'StatA', FilesA); + + % Set types of files to process: data/results +isData = 0; +if isData + panel_stat('SetFileType', 'data'); +else + panel_stat('SetFileType', 'presults'); +end +% Conditions: structure that define the files in the Processes list +Conditions = gui_stat_common('GetConditions', 'Statistics'); + + +%% ===== GET PROCESS ===== +% Get processes list, and pick a process in it +[sProcessesList, sSimpleTests, sPermTests] = panel_statRun('GetProcessesList', 'All'); +% Find a process using its name +ProcessName = 'diffAB'; +iProc = find(strcmpi({sProcessesList.Name}, ProcessName)); +if isempty(iProc) + error('Process not found.'); +end +% Process to use +sProcess = sProcessesList(iProc); + +sProcess.Name='ANOVA' +sProcess.Description = ''; +sProcess.Category = 'ANOVA'; +sProcess.FileTag = '' + +%% ===== TIME ===== +% Use all the time samples +TimeVector = panel_statRun('GetFileTimeVector', Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, isData); +Time = [TimeVector(1), TimeVector(end)]; +iTime = 1:length(TimeVector); + + +Baseline =[] +iBaseline =[] +%% ===== DEFINE OPTIONS ===== +OPTIONS.Conditions = Conditions; % Files to process +OPTIONS.sProcess = sProcess; % Process to apply +OPTIONS.isData = isData; % Process data or recordings +OPTIONS.Comment = 'anovalena'; % Default comment for output files (might be overridden) +OPTIONS.OutputType = 'database'; % Where o store the results: {database, file, matlab} +OPTIONS.ForceOutputCond = []; % When you want to store the result in a specific condition (used only when OutputType='database')=> Ex. 'Subject01/@intra' +OPTIONS.isOverwriteFiles = 0; % Overwrite input files, only in the case of filters (one input file = one output file) +OPTIONS.isAbsoluteValues = 1; % Compute the absolute value of the data before applying the process (usually 1 for sources, 0 for recordings) +OPTIONS.Time = Time; % Time window to process [tStart, tStop] in seconds +OPTIONS.iTime = iTime; % Time window: Indices in time vector for the full file +OPTIONS.Baseline = Baseline; % Some processes requires a baseline definition (it is the case for the zscore) +OPTIONS.iBaseline = iBaseline; % => Baseline and iBaseline work exactly the same way as Time and iTime +% Other options we do not use here: +OPTIONS.nbPermutation = 0; % For permuation tests only +OPTIONS.isCluster = 0; % Extract only some clusters/scouts values +OPTIONS.isClusterAverage = 0; % If 1, group all the clusters/scouts; If 0, consider they are separate +OPTIONS.sClusters = []; % Array of scouts/clusters structures +OPTIONS.ClustersOptions = []; % Structure that defines how the clusters/scouts values are computed (fields: function, isAbsolute) +OPTIONS.Baseline = []; +OPTIONS.iBaseline = []; + +n_effects=1 +for i_effects = 1:n_effects +% Call processing function +%OutputFiles = bst_batch(OPTIONS); +p = rand(15028,921); +F = rand(15028,921); +[sTargetStudy] = import_anova(Conditions, sProcess, OPTIONS, TimeVector, p, F) +end + + diff --git a/brainstorm3/script_import_anova_Old1.m b/brainstorm3/script_import_anova_Old1.m new file mode 100644 index 0000000..558982f --- /dev/null +++ b/brainstorm3/script_import_anova_Old1.m @@ -0,0 +1,118 @@ +% import des r?sultats de l'anovabst de Lydia dans BrainSotmr +% inspir? de TUTORIAL_10_STAT: Script that follows Brainstorm online +% tutorial #10: "Statistics" +%Auteurs: Karim N'Diaye, CTB + +%Alancer avec BrainSorm ouvert, onglet Statistics actif et case "cources" +%coch?e +% Appel import_anova + +%%% constantes +CONDITIONS = {'ALL_EURO' 'ALL_DOLLAR' 'ALL_FRANC' 'ALL_MARK' 'ALL_SCR_EURO' 'ALL_SCR_DOLLAR' 'ALL_SCR_FRANC' 'ALL_SCR_MARK'} +SUBJECTS = {'sujet_01' 'sujet_02' 'sujet_03' 'sujet_04' 'sujet_05' 'sujet_06' ... + 'sujet_08' 'sujet_09' 'sujet_10' 'sujet_11' 'sujet_12' 'sujet_13' ... + 'sujet_21' 'sujet_22' 'sujet_23' 'sujet_pilote'}; +path2bst='/pclxserver/raid6/data/MONEY/BrainStormData/MONEY/data/' +path2anovares='/pclxserver/raid6/data/MONEY/Analyze16suj/StatSources/Raw/' +StructName='Sources3way'; +FilesToFind='MN: MEG(Full,Constr)' +liste_effects=[1 2 3 12 13 23 123]; +FileComment='Raw_An3F'; %%% Attention: nom sous lequel le fichier apparaitra dans la base BST + +%% Creat File List +i= 1; +clear FilesA +for i_sub=1:length(SUBJECTS) + for i_cond = 1:length(CONDITIONS) + + % Get condition StimRightThumb + [sStudy, iStudy] = bst_getContext('StudyWithCondition', [ SUBJECTS{i_sub} '/' CONDITIONS{i_cond}]); + + %% ===== SELECT FILES ===== + % Get the two kernels computed in tutorial #7: the regular and the shared one + iRes1 = find(~cellfun(@(c)isempty(strfind(c, FilesToFind)), {sStudy.Result.Comment})); + + iRes1 = iRes1(1); + % Define the list of files A + FilesA(i) = {[path2bst sStudy.Result(iRes1(1)).FileName]}; + i=i+1; + end +end +% Remove previous nodes in the Statistics panel +panel_stat('ResetPanel'); +% Add files to the Statistics panel +nFilesA = gui_stat_common('SetFilesToProcess', 'StatA', FilesA); + + % Set types of files to process: data/results +isData = 0; +if isData + panel_stat('SetFileType', 'data'); +else + panel_stat('SetFileType', 'presults'); +end +% Conditions: structure that define the files in the Processes list +Conditions = gui_stat_common('GetConditions', 'Statistics'); + + +%% ===== GET PROCESS ===== +% Get processes list, and pick a process in it +[sProcessesList, sSimpleTests, sPermTests] = panel_statRun('GetProcessesList', 'All'); +% Find a process using its name +ProcessName = 'diffAB'; +iProc = find(strcmpi({sProcessesList.Name}, ProcessName)); +if isempty(iProc) + error('Process not found.'); +end +% Process to use +sProcess = sProcessesList(iProc); + +sProcess.Name='ANOVA' +sProcess.Description = ''; +sProcess.Category = 'ANOVA'; +sProcess.FileTag = '' + +%% ===== TIME ===== +% Use all the time samples +TimeVector = panel_statRun('GetFileTimeVector', Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, isData); +Time = [TimeVector(1), TimeVector(end)]; +iTime = 1:length(TimeVector); + + +Baseline =[]; +iBaseline =[]; +%% ===== DEFINE OPTIONS ===== +OPTIONS.Conditions = Conditions; % Files to process +OPTIONS.sProcess = sProcess; % Process to apply +OPTIONS.isData = isData; % Process data or recordings +OPTIONS.Comment = 'anovalena'; % Default comment for output files (might be overridden) +OPTIONS.OutputType = 'database'; % Where o store the results: {database, file, matlab} +OPTIONS.ForceOutputCond = []; % When you want to store the result in a specific condition (used only when OutputType='database')=> Ex. 'Subject01/@intra' +OPTIONS.isOverwriteFiles = 0; % Overwrite input files, only in the case of filters (one input file = one output file) +OPTIONS.isAbsoluteValues = 1; % Compute the absolute value of the data before applying the process (usually 1 for sources, 0 for recordings) +OPTIONS.Time = Time; % Time window to process [tStart, tStop] in seconds +OPTIONS.iTime = iTime; % Time window: Indices in time vector for the full file +OPTIONS.Baseline = Baseline; % Some processes requires a baseline definition (it is the case for the zscore) +OPTIONS.iBaseline = iBaseline; % => Baseline and iBaseline work exactly the same way as Time and iTime +% Other options we do not use here: +OPTIONS.nbPermutation = 0; % For permuation tests only +OPTIONS.isCluster = 0; % Extract only some clusters/scouts values +OPTIONS.isClusterAverage = 0; % If 1, group all the clusters/scouts; If 0, consider they are separate +OPTIONS.sClusters = []; % Array of scouts/clusters structures +OPTIONS.ClustersOptions = []; % Structure that defines how the clusters/scouts values are computed (fields: function, isAbsolute) +OPTIONS.Baseline = []; +OPTIONS.iBaseline = []; + + +n_effects=size(liste_effects,2); +for i_effects = 1:n_effects +% Call processing function +%OutputFiles = bst_batch(OPTIONS); +load (strcat(path2anovares, StructName, 'F', num2str(liste_effects(i_effects)),'.mat')) +load (strcat(path2anovares, StructName, 'p', num2str(liste_effects(i_effects)),'.mat')) +p = tempStructp.ImageGridAmp; +F = tempStructF.ImageGridAmp; +OPTIONS.Comment=strcat(FileComment,'_F',num2str(liste_effects(i_effects))) +[sTargetStudy] = import_anova(Conditions, sProcess, OPTIONS, TimeVector, p, F); +end + + diff --git a/brainstorm3/svn_diff.csh b/brainstorm3/svn_diff.csh new file mode 100755 index 0000000..96c9d8c --- /dev/null +++ b/brainstorm3/svn_diff.csh @@ -0,0 +1,22 @@ +#!/bin/tcsh -xfv + +foreach mine ( *.m ) + set updated = ` find ../../../mtoolbox/brainstorm3 -name $mine:t ` + echo "Files: " + echo " :" + echo " :" + echo $updated ":" $mine + echo " :" + echo " :" + diff -dby --suppress-common-lines $updated $mine + echo " [c]ompare / [s]kip / [q]uit ?" + + set action=$< + if ($action == "q" ) then + exit(1); + endif + if ($action == "c" ) then + kdiff3 $updated $mine -m -o $mine + endif + echo " " +end diff --git a/brainstorm3/svn_diff.csh~ b/brainstorm3/svn_diff.csh~ new file mode 100755 index 0000000..aba5f08 --- /dev/null +++ b/brainstorm3/svn_diff.csh~ @@ -0,0 +1,11 @@ +#!/bin/tcsh -xfv + +foreach mine ( *.m ) + echo $mine:t + set updated = ` find ../../../mtoolbox/brainstorm3 -name $mine:t ` + echo "Comparing "$updated $mine + kdiff3 $updated $mine -m -o $mine + if ($? == 1 ) then + exit(1) + end +end diff --git a/brainstorm3/toolbox/core/bst_getContext.m b/brainstorm3/toolbox/core/bst_getContext.m new file mode 100644 index 0000000..ee7811a --- /dev/null +++ b/brainstorm3/toolbox/core/bst_getContext.m @@ -0,0 +1,2006 @@ +function [bstContext, bstIndex, bstSubIndex] = bst_getContext( varargin ) +% BST_GETCONTEXT: Get a Brainstorm structure. +% This function is used to abstract the way that these structures are stored. +% +% USAGE : +% ====== DIRECTORIES ================================================================== +% - bst_getContext('UserDir') : User home directory +% - bst_getContext('BrainStormHomeDir') : Application directory of brainstorm +% - bst_getContext('BrainStormUserDir') : User home directory for brainstorm (/.brainstorm/) +% - bst_getContext('BrainStormTmpDir') : User brainstorm temporary directory (Default: /.brainstorm/tmp/) +% - bst_getContext('BrainStormTmpDir', isForcedDefault) : User DEFAULT brainstorm temporary directory (/.brainstorm/tmp/) +% - bst_getContext('BrainStormMexDir') : User brainstorm temporary directory (/.brainstorm/mex/) +% - bst_getContext('BrainStormDbFile') : User brainstorm.mat file (/.brainstorm/brainstorm.mat) +% - bst_getContext('BrainStormDbDir') : User database directory (contains all the brainstorm protocols) +% - bst_getContext('DirDefaultSubject') : Directory name of the default subject +% - bst_getContext('DirDefaultStudy') : Directory name of the default study for each subject +% - bst_getContext('DirAnalysisInter') : Directory name of the inter-subject analysis study +% - bst_getContext('DirAnalysisIntra') : Directory name of the intra-subject analysis study (for each subject) +% - bst_getContext('NormalizedSubjectName') : Name of the subject with a normalized anatomy +% - bst_getContext('AnatomyDefaults') : Get the contents of directory bstDir/defaults/anatomy +% - bst_getContext('EEGDefaults') : Get the contents of directory bstDir/defaults/eeg +% - bst_getContext('LastUsedDirs') : Structure with all the last used directories (last used) +% +% ====== PROTOCOLS ==================================================================== +% - bst_getContext('ProtocolsListInfo') : List of protocols (definition) +% - bst_getContext('ProtocolsListSubjects') : List of protocols (subjects) +% - bst_getContext('ProtocolsListStudies') : List of protocols (studies) +% - bst_getContext('iProtocol') : Indice of current protocol +% - bst_getContext('ProtocolInfo') : Definition structure for current protocol +% - bst_getContext('ProtocolSubjects') : Subjects list for current protocol +% - bst_getContext('ProtocolStudies') : Studies list for current protocol +% +% ====== STUDIES ====================================================================== +% - bst_getContext('Study', StudyFileName) : Get one study in current protocol with its file name +% - bst_getContext('Study', iStudies) : Get one or more studies +% - bst_getContext('Study') : Get current study in current protocol +% - bst_getContext('StudyCount') : Get number of studies in the current protocol +% - bst_getContext('StudyWithSubject', SubjectFile) : Find studies associated with a given subject file (WITHOUT the system studies ('intra_subject', 'default_study')) +% - bst_getContext('StudyWithSubject', ..., 'intra_subject') : Find studies ... INCLUDING 'intra_subject' study +% - bst_getContext('StudyWithSubject', ..., 'default_study') : Find studies ... INCLUDING 'default_study' study +% - bst_getContext('StudyWithCondition', ConditionPath) : Find studies for a given condition path +% - bst_getContext('StudyWithSubjectAndCondition', SubjectFile, ConditionsList) +% - bst_getContext('ChannelStudiesWithSubject', iSubjects) : Get all the studies where there should be a channel file for a list of subjects +% - bst_getContext('AnalysisIntraStudy', iSubject) : Get the default analysis study for target subject +% - bst_getContext('AnalysisInterStudy') : Get the default analysis study for inter-subject analysis +% - bst_getContext('DefaultStudy', iSubject) : Get the default study for target subject (by subject indice) +% - bst_getContext('DefaultStudy') : Get the global default study (common to all subjects) +% - bst_getContext('DefaultStudy', BrainStormSubject) : Get the default study for target subject (by filename) +% - bst_getContext('ChannelFile', ChannelFile) : Find a channel file in current protocol +% - bst_getContext('ChannelFileForStudy', StudyFile/DataFile) : Find a channel file in current protocol +% - bst_getContext('ChannelForStudy', iStudies) : Return current Channel struct for target study +% - bst_getContext('HeadModelForStudy', iStudy) : Return current HeadModel struct for target study +% - bst_getContext('DataFile', DataFile) : Find a DataFile in current protocol +% - bst_getContext('DataForDataList', iStudy, DataListName) : Find all the DataFiles grouped by a data list +% - bst_getContext('DataForStudy', iStudy) : Find all the Data files that are dependent on the channel/headmodel of a given study +% - bst_getContext('DataForStudies', iStudies) +% - bst_getContext('DataForChannelFile', ChannelFile) : Find all the DataFiles that use the given ChannelFile +% - bst_getContext('ResultsFile', ResultsFile) : Find a ResultsFile in current protocol +% - bst_getContext('ResultsForDataFile', DataFile) : Find all results computed based on DataFile +% - bst_getContext('StatFile', StatFile) : Find a StatFile in current protocol +% - bst_getContext('StatForDataFile', DataFile, iStudies) +% - bst_getContext('StatForDataFile', DataFile) +% - bst_getContext('GetFileNames') +% - bst_getContext('BestFittingSphere', ChannelFile) : Get a spherical approximation to head shape in the headmodels +% +% ====== SUBJECTS ====================================================================== +% - bst_getContext('Subject', SubjectFileName, isRaw) : Find a subject in current protocol with its file name +% - bst_getContext('Subject', SubjectDir, isRaw) : Find a subject in current protocol with its directory +% - bst_getContext('Subject', iSubject) : Get a subject (normal or default if iSubject==0) +% - bst_getContext('Subject') : Get current subject in current protocol +% - bst_getContext('SubjectWithName', Name) : Find a subject in current protocol with its name +% - bst_getContext('SubjectCount') : Get number of studies in the current protocol +% - bst_getContext('ConditionsForSubject', SubjectFile) : Find all conditions for a given subject +% - bst_getContext('SurfaceFile', SurfaceFile) : Find a surface in current protocol +% - bst_getContext('SurfaceFileByType', iSubject, SurfaceType) : Find the default surface for subject #i +% - bst_getContext('SurfaceFileByType', SurfaceName, SurfaceType) : Find the default surface for subject that also has surface SurfaceName +% - bst_getContext('SurfaceFileByType', MriName, SurfaceType) : Find the default surface for subject that also has MRI MriName +% - bst_getContext('MriFile', MriFile) : Find a MRI in current protocol +% +% ====== GUI ================================================================= +% - bst_getContext('GUI') : Get GUI structure (handles of Java panels and windows) +% - bst_getContext('Layout') : Configuration of the main Brainstorm window +% - bst_getContext('LayoutManager') : Name of the function that re-arrange automatically the figures +% - bst_getContext('ProgressBar') : Handle to Brainstorm progress bar +% - bst_getContext('PanelContainer') : Display list of registered panel containers +% - bst_getContext('PanelContainer', ContainerName) : Get a panel container handle +% - bst_getContext('Panel') : Display list of registered panels +% - bst_getContext('Panel', PanelName) : Find a panel with its name +% - bst_getContext('PanelControls', PanelName) : Get the controls of a panel +% - bst_getContext('PanelElement', PanelName, ElementName) : Get an element (control, callback, ...) in a panel +% - bst_getContext('PanelElement', ElementName) : Search for an element (control, callback, ...) in all the panels +% +% ====== CONFIGURATION ================================================================= +% - bst_getContext('Version') : Brainstorm version +% - bst_getContext('ByteOrder') : {'l','b'} - Byte order used to read and save binary files +% - bst_getContext('DisplayGFP') : {0,1} - If 1, the GFP is displayed on all the time series figures +% - bst_getContext('ExpandTrialsLists') : {0,1} - If 1, the trials lists are automatically expanded in the tree +% - bst_getContext('DefaultFormats') : Default formats for importing/exporting data, channels, ... (last used) +% - bst_getContext('BEMOptions') : BEM options +% - bst_getContext('BFSProperties') : Conductivities and thicknesses for 3-shell spherical forward model +% - bst_getContext('ImportCTFOptions') : Importation options for CTF format +% - bst_getContext('ImportFIFOptions') : Importation options for FIF format +% - bst_getContext('ImportEegRawOptions') : Importation options for RAW EEG format +% - bst_getContext('BugReportOptions') : Bug reporter options +% - bst_getContext('InverseOptions') : Importation options for RAW EEG format +% - bst_getContext('DefaultSurfaceDisplay') : Default display options for surfaces (smooth, data threshold, curvature) +% - bst_getContext('MagneticExtrapOptions') : Structure with the options for magnetic field extrapolation +% - bst_getContext('UniformizeTimeSeriesScales') : {0,1} - If 1, the Y-axis of all the time series figures have the scale +% - bst_getContext('DisplayAverageReference') : {0,1} - If 1, the EEG recordings will be displayed in average reference +% - bst_getContext('ReloadDbAtStartup') : {0,1} - If 1, reload automatically database at each startup +% - bst_getContext('UseDoubleScreen') : {0,1} - If 1, if two available display, use both; else use only the first one +% - bst_getContext('UseSigProcToolbox') : Use Matlab's Signal Processing Toolbox when available +% +% SEE ALSO bst_setContext + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + + +%% ==== PARSE INPUTS ==== +if ((nargin >= 1) && ischar(varargin{1})) + contextName = varargin{1}; +else + return +end +% Initialize returned variable +bstContext = []; +bstIndex = []; +bstSubIndex = []; + + +% Get required context structure +switch lower(contextName) +%% ==== BRAINSTORM CONFIGURATION ==== + case 'version' + if ispref('BrainStorm', 'Version') + bstContext = getpref('BrainStorm', 'Version'); + else + bstContext = []; + end + + case 'brainstormhomedir' + if ispref('BrainStorm', 'brainstormHomeDir') + bstContext = getpref('BrainStorm', 'brainstormHomeDir'); + else + bstContext = []; + end + + case 'userdir' + try + userDir = char(java.lang.System.getProperty('user.home')); + catch + userDir = ''; + end + if isempty(userDir) + userDir = bst_getContext('BrainstormHomeDir'); + end + bstContext = userDir; + + case 'brainstormuserdir' + bstUserDir = fullfile(bst_getContext('UserDir'), '.brainstorm'); + if ~isdir(bstUserDir) + res = mkdir(bstUserDir); + if ~res + error(['Cannot create Brainstorm user directory: "' bstUserDir '".']); + end + end + bstContext = bstUserDir; + + case 'brainstormtmpdir' + tmpDir = ''; + isForcedDefault = ((nargin >= 2) && varargin{2}); + % If temporary directory is set in the preferences + if ~isForcedDefault && ispref('BrainStorm', 'BrainstormTempDir') + tmpDir = getpref('BrainStorm', 'BrainstormTempDir'); + end + % Else: use directory userdir/tmp + if isempty(tmpDir) + tmpDir = fullfile(bst_getContext('BrainStormUserDir'), 'tmp'); + end + % Create directory if it does not exist yet + if ~isdir(tmpDir) + res = mkdir(tmpDir); + if ~res + error(['Cannot create Brainstorm temporary directory: "' tmpDir '".']); + end + end + bstContext = tmpDir; + + case 'brainstormmexdir' + mexDir = fullfile(bst_getContext('BrainStormUserDir'), 'mex'); + if ~isdir(mexDir) + res = mkdir(mexDir); + if ~res + error(['Cannot create Brainstorm mex-files directory: "' mexDir '".']); + end + end + bstContext = mexDir; + + case 'brainstormdbfile' + bstContext = fullfile(bst_getContext('BrainStormUserDir'), 'brainstorm.mat'); + + case 'brainstormdbdir' + BrainStormDbDir = getappdata(0, 'BrainStormDbDir'); + if ~isempty(BrainStormDbDir); + bstContext = BrainStormDbDir; + bstIndex = 1; + else + % Ask user where is located + bstContext = fullfile(bst_getContext('UserDir'), 'brainstorm_db'); + bstIndex = 0; + end + + +%% ==== PROTOCOLS LIST ==== + case 'protocolslistinfo' + bstContext = getappdata(0, 'ProtocolInfo'); + case 'protocolslistsubjects' + bstContext = getappdata(0, 'ProtocolSubjects'); + case 'protocolsliststudies' + bstContext = getappdata(0, 'ProtocolStudies'); + + +%% ==== PROTOCOL ==== + case 'iprotocol' + bstContext = getappdata(0, 'iProtocol'); + if isempty(bstContext) + bstContext = 0; + end + case {'protocolinfo', 'protocolsubjects', 'protocolstudies'} + % Get protocols list (if empty : return) + ProtocolsList = getappdata(0, contextName); + if isempty(ProtocolsList) + return + end; + % Get protocol index + bstIndex = getappdata(0, 'iProtocol'); + % Check index integrity + if ((bstIndex <= 0) || (bstIndex > length(ProtocolsList))), warning('Brainstorm:InvalidIndex', 'Invalid index'), return, end + % Get requested protocol structure + bstContext = ProtocolsList(bstIndex); + + +%% ==== STUDY ==== + % Usage: [sStudy, iStudy] = bst_getContext('Study', StudyFileName) + % [sStudy, iStudy] = bst_getContext('Study') + % [sStudy, iStudy] = bst_getContext('Study', iStudies) + case 'study' + % Get list of current protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get list of current protocol studies + ProtocolStudies = bst_getContext('ProtocolStudies'); + if isempty(ProtocolStudies) || isempty(ProtocolInfo) % || isempty(ProtocolInfo.iStudy) + return; + end + % ===== PARSE INPUTS ===== + if (nargin < 2) + % Call: bst_getContext('Study'); + iStudies = ProtocolInfo.iStudy; + StudyFileName = []; + elseif (isnumeric(varargin{2})) + iStudies = varargin{2}; + StudyFileName = []; + elseif (ischar(varargin{2})) + iStudies = []; + StudyFileName = strrep(varargin{2}, ProtocolInfo.STUDIES, ''); + end + % Indices + iAnalysisStudy = -2; % CANNOT USE -1 => DISABLES SEARCH FUNCTIONS + iDefaultStudy = -3; + % Indices > 0: normal studies indiced in ProtocolStudies.Study array + + % ===== GET STUDY BY INDEX ===== + % Call: bst_getContext('Study', iStudies); + if ~isempty(iStudies) + bstContext = repmat(db_getDataTemplate('Study'), 0); + % Get analysis study + iTargetAnalysis = find(iStudies == iAnalysisStudy); + if ~isempty(iTargetAnalysis) + bstContext(iTargetAnalysis) = repmat(ProtocolStudies.AnalysisStudy, size(iTargetAnalysis)); + bstIndex(iTargetAnalysis) = repmat(iAnalysisStudy, size(iTargetAnalysis)); + end + % Get default study + iTargetDefault = find(iStudies == iDefaultStudy); + if ~isempty(iTargetDefault) + try + bstContext(iTargetDefault) = repmat(ProtocolStudies.DefaultStudy, size(iTargetDefault)); + catch ME + if isempty(bstContext) + bstContext= repmat(ProtocolStudies.DefaultStudy, size(iTargetDefault)); + else + rethrow(ME) + end + end + bstIndex(iTargetDefault) = repmat(iDefaultStudy, size(iTargetDefault)); + end + % Get normal studies + iTargetNormal = find((iStudies >= 1) & (iStudies <= length(ProtocolStudies.Study))); + if ~isempty(iTargetNormal) + bstContext(iTargetNormal) = ProtocolStudies.Study(iStudies(iTargetNormal)); + bstIndex(iTargetNormal) = iStudies(iTargetNormal); + end + % Error + if isempty(bstContext) + %warning('Brainstorm:InvalidIndex', 'Invalid study indice.'); + bstContext = []; + ProtocolInfo.iStudy = []; + bst_setContext('ProtocolInfo', ProtocolInfo); + end + + % ===== GET STUDY BY FILENAME ===== + % Call: bst_getContext('Study', StudyFileName); + elseif ~isempty(StudyFileName) + % NORMAL STUDY + iStudy = find(io_compareFileNames({ProtocolStudies.Study.FileName}, StudyFileName), 1); + % If a study is found : return it + if ~isempty(iStudy) + bstContext = ProtocolStudies.Study(iStudy); + bstIndex = iStudy; + % DEFAULT STUDY + elseif ~isempty(ProtocolStudies.DefaultStudy) && io_compareFileNames({ProtocolStudies.DefaultStudy.FileName}, StudyFileName) + bstContext = ProtocolStudies.DefaultStudy; + bstIndex = iDefaultStudy; + % ANALYSIS STUDY + elseif ~isempty(ProtocolStudies.AnalysisStudy) && io_compareFileNames({ProtocolStudies.AnalysisStudy.FileName}, StudyFileName) + bstContext = ProtocolStudies.AnalysisStudy; + bstIndex = iAnalysisStudy; + end + else + return + end + + +%% ==== STUDY WITH SUBJECT FILE ==== + % Usage : [sStudies, iStudies] = bst_getContext('StudyWithSubject', SubjectFile) : WITHOUT the system studies ('intra_subject', 'default_study') + % [sStudies, iStudies] = bst_getContext(..., 'intra_subject', 'default_study') : WITH the system studies: 'intra_subject' | 'default_study' + case 'studywithsubject' + % Parse inputs + if (nargin < 2) || ~ischar(varargin{2}) + error('Invalid call to bst_getContext()'); + end + if (nargin > 2) + IntraStudies = any(strcmpi(varargin(3:end), 'intra_subject')); + DefaultStudies = any(strcmpi(varargin(3:end), 'default_study')); + else + IntraStudies = 0; + DefaultStudies = 0; + end + SubjectFile = {varargin{2}}; + + % Get list of current protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + ProtocolStudies = bst_getContext('ProtocolStudies'); + if isempty(ProtocolStudies) || isempty(ProtocolInfo) + return; + end + + % Get default subject + sDefaultSubject = bst_getContext('Subject', 0); + % If SubjectFile is the default subject filename + if ~isempty(sDefaultSubject) && ~isempty(sDefaultSubject.FileName) && io_compareFileNames( SubjectFile{1}, sDefaultSubject.FileName) + % Get all the subjects files that use default anatomy + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + iSubjectUseDefaultAnat = find([ProtocolSubjects.Subject.UseDefaultAnat]); + if isempty(iSubjectUseDefaultAnat) + return + end + SubjectFile = {ProtocolSubjects.Subject(iSubjectUseDefaultAnat).FileName}; + % Also updates inter-subject node + isInterSubject = 1; + else + isInterSubject = 0; + end + % Search all the current protocol's studies + iStudies = []; + for i=1:length(SubjectFile) + iStudies = [iStudies, find(io_compareFileNames({ProtocolStudies.Study.BrainStormSubject}, SubjectFile{i}))]; + end + % Return results + if ~isempty(iStudies) + % Remove "analysis_intra" and "default_study" studies from list + if ~IntraStudies + iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_getContext('DirAnalysisIntra'))) = []; + end + if ~DefaultStudies + iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_getContext('DirDefaultStudy'))) = []; + end + % Return studies + bstContext = ProtocolStudies.Study(iStudies); + bstIndex = iStudies; + else + bstContext = repmat(db_getDataTemplate('Study'), 0); + bstIndex = []; + end + % Add inter-subject node, if needed + if isInterSubject + [sInterStudy, iInterStudy] = bst_getContext('AnalysisInterStudy'); + bstContext = [bstContext, sInterStudy]; + bstIndex = [bstIndex, iInterStudy]; + end + + +%% ==== STUDY WITH CONDITION PATH ==== + % Usage : [sStudies, iStudies] = bst_getContext('StudyWithCondition', ConditionPath) + % Condition path can have two formats : + % - 'subjectName/condition1/subCondition1...' : target condition for the specified subject + % - '*/condition1/subCondition1...' : target condition for all the subjects + case 'studywithcondition' + % Parse inputs + if (nargin ~= 2) || ~ischar(varargin{2}) + error('Invalid call to bst_getContext()'); + end + ConditionPath = varargin{2}; + % Get list of current protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + ProtocolStudies = bst_getContext('ProtocolStudies'); + if isempty(ProtocolStudies) || isempty(ProtocolInfo) + return; + end + + % Split Condition path string + Conditions = strSplit(ConditionPath); + if (length(Conditions) < 2) + % If only one element in condition path + % => consider as if there were a '*/' before (all subjects) + iStudies = 1:length(ProtocolStudies.Study); + else + % If first element is '*', search for condition in all the studies + if (Conditions{1}(1) == '*') + iStudies = 1:length(ProtocolStudies.Study); + % Else : search for condition only in studies that are linked to the subject specified in the ConditionPath + else + iStudies = find(cellfun(@(f)strcmpi(fileparts(f), Conditions{1}), {ProtocolStudies.Study.BrainStormSubject})); + end + Conditions = Conditions(2:end); + end + + % Search all the current protocol's studies + iStudies = iStudies(cellfun(@(c)isequal(Conditions, c), {ProtocolStudies.Study(iStudies).Condition})); + % Return results + if ~isempty(iStudies) + % Remove "analysis_intra" and "default_study" studies from list + iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_getContext('DirAnalysisIntra'))) = []; + iStudies(strcmpi({ProtocolStudies.Study(iStudies).Name}, bst_getContext('DirDefaultStudy'))) = []; + % Sort by subject + if (length(iStudies) > 1) + SubjNameList = cell(1,length(iStudies)); + % For each study, get subject name + for i = 1:length(iStudies) + sSubject = bst_getContext('Subject', ProtocolStudies.Study(iStudies(i)).BrainStormSubject); + SubjNameList{i} = sSubject.Name; + end + % Sort subjects names + [sortSubjList, iSort] = sort(SubjNameList); + % Apply same sorting to studies + iStudies = iStudies(iSort); + end + % Return studies + bstContext = ProtocolStudies.Study(iStudies); + bstIndex = iStudies; + else + bstContext = repmat(db_getDataTemplate('Study'), 0); + bstIndex = []; + end + + +%% ==== STUDY WITH CONDITION AND SUBJECT ==== + % Usage: [sNewStudy, iNewStudy, ConditionPath] = bst_getContext('StudyWithSubjectAndCondition', SubjectFile, ConditionList) + case 'studywithsubjectandcondition' + % Parse inputs + if (nargin ~= 3) || ~ischar(varargin{2}) || ~iscell(varargin{3}) + error('Invalid call to bst_getContext()'); + end + SubjectFile = varargin{2}; + ConditionList = varargin{3}; + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % === VERSION 1 : USE SUBJECTS DIR === + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Get subject's base subdirectory + subjectsSubDir = fileparts(SubjectFile); + iFirstSlash = min([findstr(subjectsSubDir, '/'), findstr(subjectsSubDir, '\')]); + if ~isempty(iFirstSlash) + subjectsSubDir(iFirstSlash:end) = []; + end + % Get study with subject AND condition + ConditionPath = fullfile(subjectsSubDir, ConditionList{:}); + [sStudy, iStudy] = bst_getContext('StudyWithCondition', ConditionPath); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % === VERSION 2 : USE STUDIES DIR === + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if isempty(sStudy) + % Get a study associated to subject (to get the studies subdirectory) + [sStudy, iStudy] = bst_getContext('StudyWithSubject', SubjectFile); + if ~isempty(sStudy) + % Get subject's studies base subdirectory + studiesSubDir = fileparts(sStudy(1).FileName); + iFirstSlash = min([findstr(studiesSubDir, '/'), findstr(studiesSubDir, '\')]); + if ~isempty(iFirstSlash) + studiesSubDir(iFirstSlash:end) = []; + end + % Get study with subject AND condition + ConditionPath = fullfile(studiesSubDir, ConditionList{:}); + [sStudy, iStudy] = bst_getContext('StudyWithCondition', ConditionPath); + end + end + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Returned values + bstContext = sStudy; + bstIndex = iStudy; + if isempty(sStudy) + bstSubIndex = ''; + else + bstSubIndex = ConditionPath; + end + +%% ==== CHANNEL STUDIES WITH SUBJECT ==== + % Usage: iStudies = bst_getContext('ChannelStudiesWithSubject', iSubjects, 'NoIntra') + case 'channelstudieswithsubject' + % Parse inputs + if (nargin >= 2) && isnumeric(varargin{2}) + iSubjects = varargin{2}; + else + error('Invalid call to bst_getContext()'); + end + if (nargin == 3) && strcmpi(varargin{3}, 'NoIntra') + NoIntra = 1; + else + NoIntra = 0; + end + % Process all subjects + iStudies = []; + for i=1:length(iSubjects) + iSubject = iSubjects(i); + sSubject = bst_getContext('Subject', iSubject, 1); + % No subject: error + if isempty(sSubject) + continue + % If subject uses default channel file + elseif (sSubject.UseDefaultChannel ~= 0) + % Get default study for this subject + [tmp___, iStudiesNew] = bst_getContext('DefaultStudy', iSubject); + iStudies = [iStudies, iStudiesNew]; + % Else: get all the studies belonging to this subject + else + if NoIntra + [tmp___, iStudiesNew] = bst_getContext('StudyWithSubject', sSubject.FileName); + else + [tmp___, iStudiesNew] = bst_getContext('StudyWithSubject', sSubject.FileName, 'intra_subject'); + end + iStudies = [iStudies, iStudiesNew]; + end + end + bstContext = iStudies; + +%% ==== CHANNEL STUDY WITH STUDY ==== + % Usage: iStudies = bst_getContext('ChannelStudiesWithSubject', iSubjects, 'NoIntra') + case 'channelstudieswithsubject' + % Parse inputs + if (nargin >= 2) && isnumeric(varargin{2}) + iSubjects = varargin{2}; + else + error('Invalid call to bst_getContext()'); + end + if (nargin == 3) && strcmpi(varargin{3}, 'NoIntra') + NoIntra = 1; + else + NoIntra = 0; + end + % Process all subjects + iStudies = []; + for i=1:length(iSubjects) + iSubject = iSubjects(i); + sSubject = bst_getContext('Subject', iSubject, 1); + % No subject: error + if isempty(sSubject) + continue + % If subject uses default channel file + elseif (sSubject.UseDefaultChannel ~= 0) + % Get default study for this subject + [tmp___, iStudiesNew] = bst_getContext('DefaultStudy', iSubject); + iStudies = [iStudies, iStudiesNew]; + % Else: get all the studies belonging to this subject + else + if NoIntra + [tmp___, iStudiesNew] = bst_getContext('StudyWithSubject', sSubject.FileName); + else + [tmp___, iStudiesNew] = bst_getContext('StudyWithSubject', sSubject.FileName, 'intra_subject'); + end + iStudies = [iStudies, iStudiesNew]; + end + end + bstContext = iStudies; + + +%% ==== STUDIES COUNT ==== + % Usage: [nbStudies] = bst_getContext('StudyCount') + case 'studycount' + % Get list of current protocol studies + ProtocolStudies = bst_getContext('ProtocolStudies'); + bstContext = length(ProtocolStudies.Study); + +%% ==== SUBJECTS COUNT ==== + % Usage: [nbSubjects] = bst_getContext('SubjectCount') + case 'subjectcount' + % Get list of current protocol studies + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + bstContext = length(ProtocolSubjects.Subject); + +%% ==== ANALYSIS STUDY (INTRA) ==== + % Usage: [sAnalStudy, iAnalStudy] = bst_getContext('AnalysisIntraStudy', iSubject) + case 'analysisintrastudy' + % Parse inputs + if (nargin == 2) && isnumeric(varargin{2}) + iSubject = varargin{2}; + else + error('Invalid call to bst_getContext()'); + end + % Get subject + sSubject = bst_getContext('Subject', iSubject, 1); + % Get studies related to subject + [sSubjStudies, iSubjStudies] = bst_getContext('StudyWithSubject', sSubject.FileName, 'intra_subject'); + % Look for the 'AnalysisIntra' study + iFound = find(cellfun(@(c)ismember(bst_getContext('DirAnalysisIntra'), c), {sSubjStudies.Condition})); + iAnalStudy = iSubjStudies(iFound); + sAnalStudy = sSubjStudies(iFound); + % If no study found: need to create one + if isempty(iAnalStudy) + % Build new study + iAnalStudy = db_addCondition(fileparts(sSubject.FileName), bst_getContext('DirAnalysisIntra')); + sAnalStudy = bst_getContext('Study', iAnalStudy); + end + bstContext = sAnalStudy; + bstIndex = iAnalStudy; + + +%% ==== ANALYSIS STUDY (INTER) ==== + % Usage: [sAnalStudyInter, iAnalStudyInter] = bst_getContext('AnalysisInterStudy') + case 'analysisinterstudy' + iAnalStudyInter = -2; + [bstContext, bstIndex] = bst_getContext('Study', iAnalStudyInter); + + +%% ==== DEFAULT STUDY ==== + % Usage: [sDefaulStudy, iDefaultStudy] = bst_getContext('DefaultStudy', iSubject) + % [sDefaulStudy, iDefaultStudy] = bst_getContext('DefaultStudy') : iSubject=0 + % [sDefaulStudy, iDefaultStudy] = bst_getContext('DefaultStudy', BrainStormSubject) + case 'defaultstudy' + % Parse inputs + if (nargin == 1) + iSubject = 0; + elseif (nargin == 2) && isnumeric(varargin{2}) + iSubject = varargin{2}; + elseif (nargin == 2) && ischar(varargin{2}) + BrainStormSubject = varargin{2}; + % Get subject attached to study + [sSubject, iSubject] = bst_getContext('Subject', BrainStormSubject, 1); + if isempty(sSubject) || ~sSubject.UseDefaultChannel + return; + end + else + error('Invalid call to bst_getContext()'); + end + % === DEFAULT SUBJECT === + % => Return global default study + if (iSubject == 0) + % Get protocol's studies + ProtocolStudies = bst_getContext('ProtocolStudies'); + % Return Global default study + bstContext = ProtocolStudies.DefaultStudy; + bstIndex = -3; + % === NORMAL SUBJECT === + else + % Get subject + sSubject = bst_getContext('Subject', iSubject, 1); + % === GLOBAL DEFAULT STUDY === + if sSubject.UseDefaultChannel == 2 + % Get protocol's studies + ProtocolStudies = bst_getContext('ProtocolStudies'); + % Return Global default study + bstContext = ProtocolStudies.DefaultStudy; + bstIndex = -3; + % === SUBJECT'S DEFAULT STUDY === + elseif sSubject.UseDefaultChannel == 1 + % Get studies related to subject + [sSubjStudies, iSubjStudies] = bst_getContext('StudyWithSubject', sSubject.FileName, 'default_study'); + % Look for the 'DefaultStudy' study + iFound = find(cellfun(@(c)ismember(bst_getContext('DirDefaultStudy'), c), {sSubjStudies.Condition})); + iDefaultStudy = iSubjStudies(iFound); + sDefaultStudy = sSubjStudies(iFound); + % If no study found: need to create one + if isempty(iDefaultStudy) + % Build new study + iDefaultStudy = db_addCondition(fileparts(sSubject.FileName), bst_getContext('DirDefaultStudy')); + sDefaultStudy = bst_getContext('Study', iDefaultStudy); + end + bstContext = sDefaultStudy; + bstIndex = iDefaultStudy; + end + end + + + +%% ==== SUBJECT ==== + % Usage : [sSubject, iSubject] = bst_getContext('Subject', iSubject, isRaw) + % [sSubject, iSubject] = bst_getContext('Subject', SubjectFileName, isRaw); + % [sSubject, iSubject] = bst_getContext('Subject'); + % If isRaw is set: force to return the real brainstormsubject description + % (ignoring wether it uses protocol's default anatomy or not) + case 'subject' + % Get list of current protocol subjects + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + if isempty(ProtocolSubjects) + return + end + sSubject = []; + % ISRAW parameter + if (nargin < 3) + isRaw = 0; + else + isRaw = varargin{3}; + end + % Call: bst_getContext('subject', iSubject, isRaw); + if (nargin >= 2) && isnumeric(varargin{2}) + iSubject = varargin{2}; + if (iSubject > length(ProtocolSubjects.Subject)) + error('Invalid subject indice.'); + end + % If required subject is default subject (iSubject = 0) + if (iSubject == 0) + % Default subject available + if ~isempty(ProtocolSubjects.DefaultSubject) + sSubject = ProtocolSubjects.DefaultSubject; + % Default subject not available + else + return + end + % Normal subject + else + sSubject = ProtocolSubjects.Subject(iSubject); + end + + % Call: bst_getContext('subject', SubjectFileName, isRaw); + % Call: bst_getContext('subject', SubjectDir, isRaw); + elseif (nargin >= 2) && isempty(varargin{2}) + % If study name is empty: use DefaultSubject + SubjectFileName = ProtocolSubjects.DefaultSubject.FileName; + elseif (nargin >= 2) && (ischar(varargin{2})) + [fName, fBase, fExt] = fileparts(varargin{2}); + % Argument is a Matlab .mat filename + if strcmpi(fExt, '.mat') + SubjectFileName = varargin{2}; + % Else : assume argument is a directory + else + % Find subject file in this directory + ProtocolInfo = bst_getContext('ProtocolInfo'); + subjPath = strrep(varargin{2}, ProtocolInfo.SUBJECTS, ''); + subjFile = dir(fullfile(ProtocolInfo.SUBJECTS, subjPath, '*brainstormsubject*.*')); + if (length(subjFile) == 1) + SubjectFileName = fullfile(subjPath, subjFile.name); + else + return + end + end + + % Call: bst_getContext('subject'); => looking for current subject + elseif (nargin < 2) + % Get current subject filename in current study + sStudy = bst_getContext('Study'); + if isempty(sStudy) + return + end + SubjectFileName = sStudy.BrainStormSubject; + % If study's subject is not defined, get DefaultSubject + if isempty(SubjectFileName) && ~isempty(ProtocolSubjects.DefaultSubject) + SubjectFileName = ProtocolSubjects.DefaultSubject.FileName; + end + else + error('Invalid call to bst_getContext()'); + end + + % If Subject is defined by its filename + if isempty(sSubject) + % Look in Default Subject + if ~isempty(ProtocolSubjects.DefaultSubject) && io_compareFileNames(ProtocolSubjects.DefaultSubject.FileName, SubjectFileName) + sSubject = ProtocolSubjects.DefaultSubject; + iSubject = 0; + % If not found : find target subject file name in normal subjects + else + iSubject = find(io_compareFileNames({ProtocolSubjects.Subject.FileName}, SubjectFileName), 1); + sSubject = ProtocolSubjects.Subject(iSubject); + end + end + + % Return found subject + if ~isempty(iSubject) && ~isempty(sSubject) + % If subject uses default subject + if sSubject.UseDefaultAnat && ~isRaw && ~isempty(ProtocolSubjects.DefaultSubject) && ~isempty(ProtocolSubjects.DefaultSubject.FileName) + % Return default subject (WITH REAL SUBJECT'S NAME) + bstContext = ProtocolSubjects.DefaultSubject; + bstContext.Name = sSubject.Name; + bstContext.UseDefaultAnat = sSubject.UseDefaultAnat; + bstContext.UseDefaultChannel = sSubject.UseDefaultChannel; + bstIndex = iSubject; + % Else, return found subject + else + bstContext = sSubject; + bstIndex = iSubject; + end + end + +%% ==== SUBJECT WITH NAME ==== + % Usage : [sSubject, iSubject] = bst_getContext('Subject', SubjectName) + case 'subjectwithname' + % Parse inputs + if (nargin ~= 2) || ~ischar(varargin{2}) + error('Invalid call to bst_getContext()'); + end + SubjectName = varargin{2}; + % Get list of current protocol subjects + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + if isempty(ProtocolSubjects) + return + end + % Search all subjects + iSubject = find(strcmpi({ProtocolSubjects.Subject.Name}, SubjectName), 1); + if ~isempty(iSubject) + bstContext = ProtocolSubjects.Subject(iSubject); + bstIndex = iSubject; + end + + +%% ==== SURFACE FILE ==== + % Usage : [sSubject, iSubject, iSurface] = bst_getContext('SurfaceFile', SurfaceFile) + case 'surfacefile' + % Get list of current protocol subjects + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + ProtocolInfo = bst_getContext('ProtocolInfo'); + if isempty(ProtocolSubjects) + return + end; + + % Parse inputs + if (nargin == 2) + SurfaceFile = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + + % Remove SUBJECTS path from SurfaceFile + SurfaceFile = strrep(SurfaceFile, ProtocolInfo.SUBJECTS, ''); + % Look for surface file in DefaultSubject + if ~isempty(ProtocolSubjects.DefaultSubject) + % Find the first surface that matches the SurfaceFile + iSurface = find(io_compareFileNames(SurfaceFile, {ProtocolSubjects.DefaultSubject.Surface.FileName}), 1); + % If a surface was found in default subject : return it + if ~isempty(iSurface) + bstContext = ProtocolSubjects.DefaultSubject; + bstIndex = 0; + bstSubIndex = iSurface; + return + end + end + % Look for surface file in all the surfaces of all subjects + for iSubj = 1:length(ProtocolSubjects.Subject) + % Find the first surface that matches the SurfaceFile + iSurface = find(io_compareFileNames(SurfaceFile, {ProtocolSubjects.Subject(iSubj).Surface.FileName}), 1); + % If a surface was found in current subject : return it + if ~isempty(iSurface) + bstContext = ProtocolSubjects.Subject(iSubj); + bstIndex = iSubj; + bstSubIndex = iSurface; + return + end + end + + +%% ==== SURFACE FILE BY TYPE ==== + % Usage : [sSurface, iSurface] = bst_getContext('SurfaceFileByType', iSubject, SurfaceType) + % [sSurface, iSurface] = bst_getContext('SurfaceFileByType', SurfaceFile, SurfaceType) + % [sSurface, iSurface] = bst_getContext('SurfaceFileByType', MriFile, SurfaceType) + case 'surfacefilebytype' + % Get subject + if ischar(varargin{2}) + FileName = varargin{2}; + [fileFormat, fileTypes] = io_getFileType(FileName); + if ismember('tess', fileTypes) + [sSubject, iSubject] = bst_getContext('SurfaceFile', FileName); + else + [sSubject, iSubject] = bst_getContext('MriFile', FileName); + end + else + iSubject = varargin{2}; + sSubject = bst_getContext('Subject', iSubject); + end + SurfaceType = varargin{3}; + % Look for required surface type + field = ['i' SurfaceType]; + if ~isfield(sSubject, field) || isempty(sSubject.(field)) + return + end + bstContext = sSubject.Surface(sSubject.(field)); + bstIndex = sSubject.(field); + + +%% ==== MRI FILE ==== + % Usage : [sSubject, iSubject, iMri] = bst_getContext('MriFile', MriFile) + case 'mrifile' + % Get list of current protocol subjects + ProtocolSubjects = bst_getContext('ProtocolSubjects'); + ProtocolInfo = bst_getContext('ProtocolInfo'); + if isempty(ProtocolSubjects) + return + end; + + % Parse inputs + if (nargin == 2) + MriFile = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + + % Remove SUBJECTS path from MriFile + MriFile = strrep(MriFile, ProtocolInfo.SUBJECTS, ''); + % Look for MRI file in DefaultSubject + if ~isempty(ProtocolSubjects.DefaultSubject) + % Find the first MRI that matches the MriFile + iMri = find(io_compareFileNames(MriFile, {ProtocolSubjects.DefaultSubject.Anatomy.FileName}), 1); + % If a MRI was found in default subject : return it + if ~isempty(iMri) + bstContext = ProtocolSubjects.DefaultSubject; + bstIndex = 0; + bstSubIndex = iMri; + return + end + end + % Look for MRI file in all the MRIs of all subjects + for iSubj = 1:length(ProtocolSubjects.Subject) + % Find the first MRI that matches the MriFile + iMri = find(io_compareFileNames(MriFile, {ProtocolSubjects.Subject(iSubj).Anatomy.FileName}), 1); + % If a MRI was found in current subject : return it + if ~isempty(iMri) + bstContext = ProtocolSubjects.Subject(iSubj); + bstIndex = iSubj; + bstSubIndex = iMri; + return + end + end + + +%% ==== CHANNEL FILE ==== + % Usage: [sStudy, iStudy, iChannel] = bst_getContext('ChannelFile', ChannelFile) + case 'channelfile' + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Parse inputs + if (nargin == 2) + ChannelFile = varargin{2}; + ChannelFile = strrep(ChannelFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Look for Channel file in all the surfaces of all subjects + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Channel.FileName', ChannelFile); + + +%% ==== CHANNEL FILE FOR STUDY ==== + % Usage: [ChannelFile] = bst_getContext('ChannelFileForStudy', StudyFile/DataFile) + case 'channelfileforstudy' + % Parse inputs + if (nargin == 2) + StudyFile = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + % Get study in database + sStudy = bst_getContext('Study', StudyFile); + % Look if it is a DataFile + if isempty(sStudy) + sStudy = bst_getContext('DataFile', StudyFile); + end + if ~isempty(sStudy) && ~isempty(sStudy.Channel) + % Study has a channel file defined + ChannelFile = sStudy.Channel.FileName; + % Study not in database: look in StudyFile directory + else + % Get absolute path to StudyFile + ProtocolInfo = bst_getContext('ProtocolInfo'); + StudyFile = strrep(StudyFile, ProtocolInfo.STUDIES, ''); + dirPath = fileparts(fullfile(ProtocolInfo.STUDIES, StudyFile)); + % Get the directory to the data file + + % List all channel files in this dir + channelFileNames = dir(fullfile(dirPath, '*channel*.mat')); + % Check number of Channel files + if isempty(channelFileNames) + warning('Brainstorm:DBError', ['No channel file in directory "' strrep(dirPath,'\','\\') '".']); + ChannelFile = []; + elseif (length(channelFileNames) > 1) + warning('Brainstorm:DBError', ['Multiple channel files in "' strrep(dirPath,'\','\\') '".' 10 ... + 'Please alter this folder''s content so that it contains a single channel file.']); + ChannelFile = []; + else + ChannelFile = fullfile(fileparts(StudyFile), channelFileNames(1).name); + end + end + % Return Channel filename (relative) + bstContext = ChannelFile; + + +%% ==== CHANNEL STRUCT FOR STUDY ==== + % Usage: [sChannel, iChanStudy] = bst_getContext('ChannelForStudy', iStudies) + case 'channelforstudy' + % Parse inputs + if (nargin == 2) + iStudies = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + iChanStudies = []; + sListChannel = []; + for i = 1:length(iStudies) + % Get study + iStudy = iStudies(i); + sStudy = bst_getContext('Study', iStudy); + iChanStudy = iStudy; + % === Analysis-Inter node === + iAnalysisInter = -2; + iGlobalDefaultStudy = -3; + if (iStudy == iAnalysisInter) + % If no channel file is defined in 'Analysis-intra' node: look in + if isempty(sStudy.Channel) + % Get global default study + sStudy = bst_getContext('Study', iGlobalDefaultStudy); + iChanStudy = iGlobalDefaultStudy; + end + % === All other nodes === + else + % Get subject attached to study + [sSubject, iSubject] = bst_getContext('Subject', sStudy.BrainStormSubject, 1); + if isempty(sSubject) + return; + end + % Subject uses default channel/headmodel + if (sSubject.UseDefaultChannel ~= 0) + [sStudy, iChanStudy] = bst_getContext('DefaultStudy', iSubject); + if isempty(sStudy) + return + end + end + end + iChanStudies = [iChanStudies, iChanStudy]; + sListChannel = [sListChannel, sStudy.Channel]; + end + % Return Channel structure + bstContext = sListChannel; + bstIndex = iChanStudies; + + +%% ==== HEADMODEL STRUCT FOR STUDY ==== + % Usage: [sHeadModel] = bst_getContext('HeadModelForStudy', iStudy) + case 'headmodelforstudy' + % Parse inputs + if (nargin == 2) + iStudy = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + % Get study + sStudy = bst_getContext('Study', iStudy); + % === Analysis-Inter node === + iAnalysisInter = -2; + iGlobalDefaultStudy = -3; + if (iStudy == iAnalysisInter) + % If no channel file is defined in 'Analysis-intra' node: look in + if isempty(sStudy.iHeadModel) + % Get global default study + sStudy = bst_getContext('Study', iGlobalDefaultStudy); + end + % === All other nodes === + else + % Get subject attached to study + [sSubject, iSubject] = bst_getContext('Subject', sStudy.BrainStormSubject, 1); + if isempty(sSubject) + return; + end + % Subject uses default channel/headmodel + if (sSubject.UseDefaultChannel ~= 0) + sStudy = bst_getContext('DefaultStudy', iSubject); + if isempty(sStudy) + return + end + end + end + % Return HeadModel structure + if ~isempty(sStudy.iHeadModel) + bstContext = sStudy.HeadModel(sStudy.iHeadModel(1)); + else + bstContext = []; + end + + +%% ==== DATA FILE ==== + % Usage: [sStudy, iStudy, iData] = bst_getContext('DataFile', DataFile) + case 'datafile' + % Parse inputs + ProtocolInfo = bst_getContext('ProtocolInfo'); + if (nargin == 2) + DataFile = varargin{2}; + DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Look for surface file in all the surfaces of all subjects + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Data.FileName', DataFile); + + +%% ==== DATA FOR DATA LIST ==== + % Usage: [iFoundData] = bst_getContext('DataForDataList', iStudy, DataListName) + case 'datafordatalist' + iStudy = varargin{2}; + DataListName = varargin{3}; + % Get study structure + sStudy = bst_getContext('Study', iStudy); + % Get all the data files held by this datalist + removedTrialsFiles = cellfun(@strRemoveTrialTag, {sStudy.Data.FileName}, 'UniformOutput', 0); + iFoundData = find(strcmpi(removedTrialsFiles, DataListName)); + % Return found data files + bstContext = iFoundData; + + +%% ==== DATA FOR STUDY (INCLUDING SHARED STUDIES) ==== + % Usage: [iStudies, iDatas] = bst_getContext('DataForStudy', iStudy) + case 'dataforstudy' + % Get target study + iStudy = varargin{2}; + sStudy = bst_getContext('Study', iStudy); + isDefaultStudy = strcmpi(sStudy.Name, bst_getContext('DirDefaultStudy')); + isGlobalDefault = (iStudy == -3); + + % If study is the global default study + sStudies = []; + iStudies = []; + if isGlobalDefault + % Get all the subjects of the protocol + nbSubjects = bst_getContext('SubjectCount'); + for iSubject = 1:nbSubjects + sSubject = bst_getContext('Subject', iSubject, 1); + if sSubject.UseDefaultChannel + [tmp_sStudies, tmp_iStudies] = bst_getContext('StudyWithSubject', sSubject.FileName); + sStudies = [sStudies, tmp_sStudies]; + iStudies = [iStudies, tmp_iStudies]; + end + end + % Else, if study is a subject's default study (ie. channel file is shared by all studies of one subject) + elseif isDefaultStudy + % Get all the subject's studies + [sStudies, iStudies] = bst_getContext('StudyWithSubject', sStudy.BrainStormSubject, 'intra_subject', 'default_study'); + else + % Normal: one channel per condition + sStudies = sStudy; + iStudies = iStudy; + end + % Get all the DataFiles for all these studies + for i = 1:length(sStudies) + nData = length(sStudies(i).Data); + bstContext = [bstContext, repmat(iStudies(i), [1,nData])]; + bstIndex = [bstIndex, 1:nData]; + end + + +%% ==== DATA FOR STUDIES (INCLUDING SHARED STUDIES) ==== + % Usage: [iStudies, iDatas] = bst_getContext('DataForStudies', iStudies) + case 'dataforstudies' + iStudies = varargin{2}; + for i = 1:length(iStudies) + [tmp_iStudies, tmp_iDatas] = bst_getContext('DataForStudy', iStudies(i)); + bstContext = [bstContext, tmp_iStudies]; + bstIndex = [bstIndex, tmp_iDatas]; + end + +%% ==== DATA FILE FOR CHANNEL FILE ==== + % Usage: DataFiles = bst_getContext('DataForChannelFile', ChannelFile) + case 'dataforchannelfile' + ChannelFile = varargin{2}; + DataFiles = {}; + % Get study for the given channel file + [sStudy, iStudy] = bst_getContext('ChannelFile', ChannelFile); + if isempty(sStudy) + return; + end + % Get dependent data files + [iStudies, iDatas] = bst_getContext('DataForStudy', iStudy); + % Get all the Data filenames + for i = 1:length(iStudies) + sStudy = bst_getContext('Study', iStudies(i)); + DataFiles = cat(2, DataFiles, {sStudy.Data(iDatas(i)).FileName}); + end + bstContext = DataFiles; + + +%% ==== RESULTS FILE ==== + % Usage: [sStudy, iStudy, iResult] = bst_getContext('ResultsFile', ResultsFile) + case 'resultsfile' + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Parse inputs + if (nargin == 2) + ResultsFile = varargin{2}; + ResultsFile = strrep(ResultsFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Look for surface file in all the surfaces of all subjects + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Result.FileName', ResultsFile); + + +%% ==== RESULTS FOR DATA FILE ==== + % Usage: [sStudy, iStudy, iResults] = bst_getContext('ResultsForDataFile', DataFile) : search the whole protocol + % Usage: [sStudy, iStudy, iResults] = bst_getContext('ResultsForDataFile', DataFile, iStudies) : search only the specified studies + case 'resultsfordatafile' + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Parse inputs + if (nargin >= 2) + DataFile = varargin{2}; + DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Determine in which studies to search for ResultsFile + if (nargin >= 3) + % Studies specified in argument + iStudies = varargin{3}; + else + % Get study in which DataFile is located + [sStudies, iStudies] = bst_getContext('DataFile', DataFile); + if isempty(iStudies) + return; + end + end + % Search selected studies + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Result.DataFile', DataFile, iStudies); + + + +%% ==== STAT FILE ==== + % Usage: [sStudy, iStudy, iData] = bst_getContext('StatFile', StatFile) + case 'statfile' + % Parse inputs + ProtocolInfo = bst_getContext('ProtocolInfo'); + if (nargin == 2) + StatFile = varargin{2}; + StatFile = strrep(StatFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Look for surface file in all the surfaces of all subjects + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Stat.FileName', StatFile); + + + +%% ==== STAT FOR DATA FILE ==== + % Usage: [sStudy, iStudy, iResults] = bst_getContext('StatForDataFile', DataFile) : search the whole protocol + % Usage: [sStudy, iStudy, iResults] = bst_getContext('StatForDataFile', DataFile, iStudies) : search only the specified studies + case 'resultsfordatafile' + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Parse inputs + if (nargin >= 2) + DataFile = varargin{2}; + DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + else + error('Invalid call to bst_getContext().'); + end + % Determine in which studies to search for ResultsFile + if (nargin >= 3) + % Studies specified in argument + iStudies = varargin{3}; + else + % Get study in which DataFile is located + [sStudies, iStudies] = bst_getContext('DataFile', DataFile); + if isempty(iStudies) + return; + end + end + % Search selected studies + [bstContext, bstIndex, bstSubIndex] = findFileInStudies('Stat.DataFile', DataFile, iStudies); + + +%% ==== ALL CONDITIONS FOR ONE SUBJECT ==== + % Usage: [Conditions] = bst_getContext('ConditionsForSubject', SubjectFile) + case 'conditionsforsubject' + % Parse inputs + if (nargin == 2) + SubjectFile = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + % Get list of studies associated with subject + sStudies = bst_getContext('StudyWithSubject', SubjectFile); + % Get Conditions for each study + Conditions = {}; + for i = 1:length(sStudies) + % Test if the condition of this study was not added previously + isNewCondition = 1; + for iCond = 1:length(Conditions) + % If new condition is found + % (and excludes DirAnalysisIntra and DirDefaultSubject from list) + if isequal(sStudies(i).Condition, Conditions(iCond)) || ... + strcmpi(sStudies(i).Condition{1}, bst_getContext('DirAnalysisIntra')) || ... + strcmpi(sStudies(i).Condition{1}, bst_getContext('DirDefaultSubject')) + isNewCondition = 0; + break; + end + end + % If Condition is not added yet : add it to the list + if isNewCondition + Conditions{end+1} = sStudies(i).Condition; + end + end + % Return conditions list + bstContext = Conditions; + + +%% ==== ANATOMY DEFAULTS ==== + % Returns an array of struct(fullpath, dir, name) of all the Brainstorm anatomy defaults + case 'anatomydefaults' + % Get template directory + baseDir = fullfile(bst_getContext('BrainStormHomeDir'), 'defaults', 'anatomy'); + % Get subdirectories + fileList = dir(baseDir); + defaultsList = repmat(struct('fullpath','', 'dir','', 'name',''), 0); + % Find all the valid defaults (subdirectory with a brainstormsubject.mat in it) + for i=1:length(fileList) + % Entry is a directory W/ a name that does not start with a '.' + if fileList(i).isdir && (fileList(i).name(1) ~= '.') + tmpDir = fileList(i).name; + tmpFullpath = fullfile(baseDir, tmpDir); + % Look for a 'brainstormsubject.mat' + SubjectFileList = dir(fullfile(tmpFullpath, '*brainstormsubject*.mat')); + % If there is only brainstorm subject file : accept template as valid + if (length(SubjectFileList) == 1) + tmpFile = fullfile(tmpFullpath, SubjectFileList(1).name); + % Load the 'Name' field of the 'brainstormsubject.mat' file (default subject's name) + try + % Load file + SubjectMat = load(tmpFile, 'Name'); + % Add an entry to the defaults list + defaultsList(end + 1) = struct('fullpath', tmpFullpath, ... + 'dir', tmpDir, ... + 'name', SubjectMat.Name); + catch + % Error loading file => go to next iteration + continue + end + end + end + end + % Return defaults list + bstContext = defaultsList; + + +%% ==== EEG DEFAULTS ==== + % Returns an array of struct(fullpath, name) of all the Brainstorm eeg nets defaults + % Usage: eegDefaults = bst_getContext('EEGDefaults') + case 'eegdefaults' + fullDefaultsList = repmat(struct('contents','', 'name',''), 0); + % Get template directory + eegDefaultsDir = fullfile(bst_getContext('BrainStormHomeDir'), 'defaults', 'eeg'); + % Get directory + dirList = dir(fullfile(eegDefaultsDir, '*')); + % For each template directory + for iDir = 1:length(dirList) + % Excludes '.' and '..' + if (dirList(iDir).name(1) == '.') + continue; + end + % Get full dir + fulldirName = fullfile(eegDefaultsDir, dirList(iDir).name); + if isdir(fulldirName) + % Get files list + fileList = dir(fullfile(fulldirName, '*channel*.mat')); + defaultsList = repmat(struct('fullpath','', 'name',''), 0); + % Find all the valid defaults (channel files) + for iFile = 1:length(fileList) + defaultsList(iFile).fullpath = fullfile(fulldirName, fileList(iFile).name); + [tmp__, baseName] = fileparts(fileList(iFile).name); + defaultsList(iFile).name = strrep(baseName, 'channel_', ''); + defaultsList(iFile).name = strrep(defaultsList(iFile).name, '_channel', ''); + defaultsList(iFile).name = strrep(defaultsList(iFile).name, '_', ' '); + end + % Add files list to defaults list + if ~isempty(defaultsList) + fullDefaultsList(end + 1) = struct('contents', defaultsList, ... + 'name', dirList(iDir).name); + end + end + end + + % Return defaults list + bstContext = fullDefaultsList; + + +%% ==== GET FILENAMES ==== + case 'getfilenames' + iStudies = varargin{2}; + iItems = varargin{3}; + DataType = varargin{4}; + FileNames = cell(1, length(iStudies)); + for i = 1:length(iStudies) + % Get study definition + sStudy = bst_getContext('Study', iStudies(i)); + % Recordings or sources + if strcmpi(DataType, 'data') + FileNames{i} = sStudy.Data(iItems(i)).FileName; + else + FileNames{i} = sStudy.Result(iItems(i)).FileName; + end + end + bstContext = FileNames; + + +%% ==== BEST FITTING SPHERE ==== + % Get a spherical approximation to head shape in the headmodels + % USAGE: [bfs_center, bfs_radius] = bst_getContext('BestFittingSphere', ChannelFile) + case 'bestfittingsphere' + % Parse inputs + if (nargin == 2) + ChannelFile = varargin{2}; + else + error('Invalid call to bst_getContext().'); + end + % Find study associated with this channel file + sStudy = bst_getContext('ChannelFile', ChannelFile); + if isempty(sStudy) || isempty(sStudy.HeadModel) + return + end + % Get protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Load channel file + ChannelMat = load(fullfile(ProtocolInfo.STUDIES, sStudy.Channel.FileName)); + % Get MEG and EEG channels indices + iMeg = good_channel(ChannelMat.Channel, [], 'MEG'); + iEeg = good_channel(ChannelMat.Channel, [], 'EEG'); + % Get the list of head models to process (starting with the default one) + listHeadModels = [sStudy.iHeadModel, setdiff(1:length(sStudy.HeadModel), sStudy.iHeadModel)]; + % Initialize returned values + bfs_center = []; + bfs_radius = []; + % Process all the headmodels + for i = 1:length(listHeadModels) + iHeadModel = listHeadModels(i); + % Load "Param" structure from headmodel file + HeadModelFile = fullfile(ProtocolInfo.STUDIES, sStudy.HeadModel(iHeadModel).FileName); + warning off + HeadModelMat = load(HeadModelFile, 'Param', 'MEGMethod', 'EEGMethod'); + warning on + % Find a MEG spherical model in headmodel + if isfield(HeadModelMat, 'MEGMethod') && strcmpi(HeadModelMat.MEGMethod, 'meg_sphere') && ~isempty(iMeg) + bfs_center = HeadModelMat.Param(iMeg(1)).Center; + bfs_radius = max(HeadModelMat.Param(iMeg(1)).Radii); + break; + end + % Find an EEG spherical model in headmodel + if isfield(HeadModelMat, 'EEGMethod') && ismember(HeadModelMat.EEGMethod, {'eeg_sphere','eeg_3sphereBerg', 'eeg_3sphere'}) && ~isempty(iEeg) + bfs_center = HeadModelMat.Param(iEeg(1)).Center; + bfs_radius = max(HeadModelMat.Param(iEeg(1)).Radii); + break; + end + end + % Return BFS if found somewhere + bstContext = bfs_center; + bstIndex = bfs_radius; + + +%% ==== GUI ==== + case 'gui' + bstContext = getappdata(0, 'BrainStormGUI'); + + case 'progressbar' + bstContext = getappdata(0, 'BrainStormProgressBar'); + + case 'layout' + if ispref('BrainStorm', 'sLayout') + bstContext = getpref('BrainStorm', 'sLayout'); + else + bstContext = []; + end + + case 'layoutmanager' + if ispref('BrainStorm', 'LayoutManager') + bstContext = getpref('BrainStorm', 'LayoutManager'); + else + bstContext = 'TileWindows'; + end + + case 'byteorder' + if ispref('BrainStorm', 'ByteOrder') + bstContext = getpref('BrainStorm', 'ByteOrder'); + else + bstContext = 'l'; + end + + case 'uniformizetimeseriesscales' + if ispref('BrainStorm', 'UniformizeTimeSeriesScales') + bstContext = getpref('BrainStorm', 'UniformizeTimeSeriesScales'); + else + bstContext = 1; + end + + case 'displayaveragereference' + if ispref('BrainStorm', 'DisplayAverageReference') + bstContext = getpref('BrainStorm', 'DisplayAverageReference'); + else + bstContext = 1; + end + + case 'autoupdates' + if ispref('BrainStorm', 'AutoUpdates') + bstContext = getpref('BrainStorm', 'AutoUpdates'); + else + bstContext = 1; + end + case 'displaygfp' + if ispref('BrainStorm', 'DisplayGFP') + bstContext = getpref('BrainStorm', 'DisplayGFP'); + else + bstContext = 1; + end + + + case 'tsdisplaymode' + if ispref('BrainStorm', 'TSDisplayMode') + bstContext = getpref('BrainStorm', 'TSDisplayMode'); + else + bstContext = 'Butterfly'; + end + + case 'expandtrialslists' + if ispref('BrainStorm', 'ExpandTrialsLists') + bstContext = getpref('BrainStorm', 'ExpandTrialsLists'); + else + bstContext = 0; + end + + case 'reloaddbatstartup' + if ispref('BrainStorm', 'ReloadDbAtStartup') + bstContext = getpref('BrainStorm', 'ReloadDbAtStartup'); + else + bstContext = 0; + end + + case 'usedoublescreen' + if ispref('BrainStorm', 'UseDoubleScreen') + bstContext = getpref('BrainStorm', 'UseDoubleScreen'); + else + bstContext = 1; + end + + case 'usesigproctoolbox' + % Check if Signal Processing Toolbox is installed + isToolboxInstalled = exist('fir2') || exist('myfir2'); + % Return user preferences + if ~isToolboxInstalled + bstContext = 0; + elseif ispref('BrainStorm', 'UseSigProcToolbox') + bstContext = getpref('BrainStorm', 'UseSigProcToolbox'); + else + bstContext = 1; + end + + case 'lastuseddirs' + LastUsedDirs = struct('ImportData', '', ... + 'ImportChannel', '', ... + 'ImportAnat', '', ... + 'Export', ''); + % Check if preference is weel defined + if ispref('BrainStorm', 'LastUsedDirs') && all(ismember(fieldnames(LastUsedDirs), fieldnames(getpref('BrainStorm', 'LastUsedDirs')))) + bstContext = getpref('BrainStorm', 'LastUsedDirs'); + % Check if directories still exist + if ~exist(bstContext.ImportData, 'dir') + bstContext.ImportData = ''; + end + if ~exist(bstContext.ImportChannel, 'dir') + bstContext.ImportChannel = ''; + end + if ~exist(bstContext.ImportAnat, 'dir') + bstContext.ImportAnat = ''; + end + if ~ischar(bstContext.Export) + bstContext.Export = ''; + warning('*** LastUsedDirs.Export = 0 ***'); + elseif ~exist(bstContext.Export, 'dir') + bstContext.Export = ''; + end + else + bstContext = LastUsedDirs; + setpref('BrainStorm', 'LastUsedDirs', LastUsedDirs); + end + + case 'defaultformats' + bstContext = struct('DataIn', '', ... + 'DataOut', '', ... + 'ChannelIn', '', ... + 'ChannelOut', '', ... + 'NoiseCovIn', '', ... + 'ResultsIn', '', ... + 'ResultsOut', '', ... + 'MriIn', '', ... + 'MriOut', '', ... + 'SurfaceIn', '', ... + 'SurfaceOut', ''); + if ispref('BrainStorm', 'DefaultFormats') + bstPref = getpref('BrainStorm', 'DefaultFormats'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'bemoptions' + bstContext = struct(... + 'Interpolative', 0, ... + 'Basis', 'linear', ... + 'Test', 'collocation', ... + 'ISA', 1, ... + 'checksurf', 1, ... + 'NVertMax', 1000, ... + 'ForceXferComputation', 1); + if ispref('BrainStorm', 'BEMOptions') + bstPref = getpref('BrainStorm', 'BEMOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'bfsproperties' + if ispref('BrainStorm', 'BFSProperties') && ~isempty(getpref('BrainStorm', 'BFSProperties')) + bstContext = getpref('BrainStorm', 'BFSProperties'); + else + bstContext = [.33 .0042 .33 .88 .93]; + end + + case 'importctfoptions' + bstContext = struct('UseAllTrials', 1, ... + 'TrialsTimeRange', [], ... + 'MarkersTimeRange', [-.05, .2], ... + 'KeepNativeFormat', 0, ... + 'UseMarkers', 1, ... + ... 'EEGRef', 0, ... + 'MarkersSelection', 'all', ... {'all', 'common', 'individual'} + 'DCOffset', 0 ... {0:do no remove, 1:remove/whole, 2:remove/pretrigger} + ); + if ispref('BrainStorm', 'ImportCTFOptions') + bstPref = getpref('BrainStorm', 'ImportCTFOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'importfifoptions' + bstContext = struct('UseEvents', 1, ... + 'EventsTimeRange', [-.05, .2], ... + 'SplitRaw', 1, ... + 'SplitLength', 4, ... + 'KeepNativeFormat', 0, ... + 'Resample', 0, ... + 'ResampleFreq', 0, ... + 'UseCtfCompensators', 0, ... + 'LastCtfCompensator', 3, ... + 'UseNeuromagSSP', 0); + if ispref('BrainStorm', 'ImportFifOptions') + bstPref = getpref('BrainStorm', 'ImportFifOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'importeegrawoptions' + bstContext = struct('isCanceled', 0, ... + 'BaselineDuration', 0, ... + 'SamplingRate', 1000, ... + 'MatrixOrientation', 'channelXtime', ... % {'channelXtime', 'timeXchannel'} + 'VoltageUnits', 'V', ... % {'\muV', 'mV', 'V'} + 'SkipLines', 0); + if ispref('BrainStorm', 'ImportEegRawOptions') + bstPref = getpref('BrainStorm', 'ImportEegRawOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'bugreportoptions' + bstContext = struct('isEnabled', 0, ... + 'SmtpServer', 'mailhost.chups.jussieu.fr', ... + 'UserEmail', ''); + if ispref('BrainStorm', 'BugReportOptions') + bstPref = getpref('BrainStorm', 'BugReportOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'inverseoptions' + if ispref('BrainStorm', 'InverseOptions') && ~isempty(getpref('BrainStorm', 'InverseOptions')) + bstContext = getpref('BrainStorm', 'InverseOptions'); + end + if isempty(bstContext) || ~isfield(bstContext.LMMS, 'UseNoiseCov') + bstContext = struct('LMMS', struct(... + 'FFNormalization', 1, ... + 'Tikhonov', 10, ... + 'ComputeKernel', 1, ... + 'UseNoiseCov', 1), ... + 'LCMV', struct(... + 'NNormalization', 0, ... + 'Tikhonov', 10, ... + 'isConstrained', 1, ... + 'OutputFormat', 2)); + end + + case 'defaultsurfacedisplay' + bstContext = struct('SurfShowCurvature', 0, ... + 'SurfSmoothValue', 0, ... + 'DataIntThreshold', 0.5,... + 'DataExtThreshold', 0); + if ispref('BrainStorm', 'DefaultSurfaceDisplay') + bstPref = getpref('BrainStorm', 'DefaultSurfaceDisplay'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + case 'magneticextrapoptions' + bstContext = struct('ForceWhitening', 0, ... + 'EpsilonValue', 0.0001); + if ispref('BrainStorm', 'MagneticExtrapOptions') + bstPref = getpref('BrainStorm', 'MagneticExtrapOptions'); + if ~isempty(bstPref) && all(isfield(bstPref, fieldnames(bstContext))) + bstContext = bstPref; + end + end + + +%% ==== PANEL CONTAINERS ==== + case 'panelcontainer' + % Get Brainstorm GUI context structure + bst_GUI = getappdata(0, 'BrainStormGUI'); + if (isempty(bst_GUI) || ~isfield(bst_GUI, 'panelContainers')) + error('Brainstorm GUI is not yet initialized'); + end + + % Get ContainerName in argument + if ((nargin >= 2) && (ischar(varargin{2}))) + ContainerName = varargin{2}; + % If no container name in argument : just display all the container names + else + disp('Registered panel containers :'); + for iContainer = 1:length(bst_GUI.panelContainers) + disp([' - ' bst_GUI.panelContainers(iContainer).name]); + end + return + end + + % Look for containerName in all the registered panel containers + iContainer = 1; + found = 0; + while (~found (iContainer <= length(bst_GUI.panelContainers))) + if (strcmpi(ContainerName, bst_GUI.panelContainers(iContainer).name)) + found = 1; + else + iContainer = iContainer + 1; + end + end + % If container is found : return it + if (found) + bstContext = bst_GUI.panelContainers(iContainer).jHandle; + else + warning('Brainstorm:InvalidContainer', 'Container ''%s'' could not be found.', ContainerName); + end + + +%% ==== PANELS ==== + case 'panel' + % Get Brainstorm GUI context structure + bst_GUI = getappdata(0, 'BrainStormGUI'); + if (isempty(bst_GUI) || ~isfield(bst_GUI, 'panels')) + return + end + % Get Panel in argument + if ((nargin >= 2) && (ischar(varargin{2}))) + PanelName = varargin{2}; + % If no panel name in argument : just display all the panels names + else + disp('Registered panels :'); + for iContainer = 1:length(bst_GUI.panels) + disp([' - ' get(bst_GUI.panels(iContainer), 'name')]); + end + return + end + % Look for panelName in all the registered panels + iPanel = find(strcmpi(PanelName, get(bst_GUI.panels, 'name')), 1); + if ~isempty(iPanel) + bstContext = bst_GUI.panels(iPanel); + bstIndex = iPanel; + end + + +%% ==== PANEL CONTROLS ==== +% Calls : bst_getContext('PanelControls', PanelName) + case 'panelcontrols' + % Get Panel name in argument + if ((nargin >= 2) && (ischar(varargin{2}))) + PanelName = varargin{2}; + else + error('Invalid call to bst_getContext()'); + end + % Find BstPanel with this name + bstPanel = bst_getContext('Panel', PanelName); + % If panel was found : return its controls + if ~isempty(bstPanel) + bstContext = get(bstPanel, 'sControls'); + end + + +%% ==== PANEL ELEMENTS ==== +% Calls : bst_getContext('PanelElement', PanelName, ElementName) +% bst_getContext('PanelElement', ElementName) + case 'panelelement' + % Get Panel name in argument + if ((nargin == 2) && (ischar(varargin{2}))) + panelName = ''; + objectName = varargin{2}; + elseif ((nargin == 3) && (ischar(varargin{2}) && (ischar(varargin{2})))) + panelName = varargin{2}; + objectName = varargin{3}; + else + error('Invalid call to bst_getContext()'); + end + + % Look for control + % If panel name is known + if ~isempty(panelName) + % Get panel that holds the object + bstPanel = bst_getContext('Panel', panelName); + if (isempty(bstPanel)), return, end + % Get the object name in the objects referenced in this panel + panelElement = get(bstPanel, objectName); + if (isempty(panelElement)) + warning('Brainstorm:InvalidElement', 'Object ''%s'' could not be found in panel ''%s''.', objectName, panelName); + return + end + + % If panel name is not defined : need to search all panels + else + % Get Brainstorm GUI context structure + bst_GUI = bst_getContext('GUI'); + if (isempty(bst_GUI) || ~isfield(bst_GUI, 'panels')) + error('Brainstorm GUI is not yet initialized'); + end + % Process all panels + [panelElement, bstPanel] = get(bst_GUI.panels, objectName); + end + + % If element was found : return object and panel + if (~isempty(panelElement)) + bstContext = panelElement; + bstIndex = bstPanel; + end + + +%% ==== DIRECTORIES ==== + case 'dirdefaultsubject' + bstContext = '@default_subject'; + case 'dirdefaultstudy' + bstContext = '@default_study'; + case 'diranalysisintra' + bstContext = '@intra'; + case 'diranalysisinter' + bstContext = '@inter'; + case 'normalizedsubjectname' + bstContext = 'Group analysis'; + % bstContext = 'Default subject'; + + + +%% ==== ERROR ==== + otherwise + error(sprintf('Invalid context : "%s"', contextName)); +end +end + + + + +%% ==== HELPERS ==== +% Return all the protocol studies that have a given file in its structures +% Possible field names: Result.DataFile, Result.FileName, Data.FileName, Channel.FileName +% +% USAGE: [sFoundStudy, iFoundStudy, iItems] = findFileInStudies(fieldName, fieldFile, iStudiesList) +% [sFoundStudy, iFoundStudy, iItems] = findFileInStudies(fieldName, fieldFile) +function [sFoundStudy, iFoundStudy, iItems] = findFileInStudies(fieldName, fieldFile, iStudiesList) + sFoundStudy = []; + iFoundStudy = []; + iItems = []; + % Get protocol information + ProtocolInfo = bst_getContext('ProtocolInfo'); + ProtocolStudies = bst_getContext('ProtocolStudies'); + % Remove STUDIES path from fieldFile + fieldFile = strrep(fieldFile, ProtocolInfo.STUDIES, ''); + % List studies to process + if (nargin < 3) + iStudiesList = 1:length(ProtocolStudies.Study); + else + % Remove default studies (processed anyway) + iStudiesList = setdiff(iStudiesList, [-2 -3]); + end + + try + % NORMAL STUDIES: Look for surface file in all the surfaces of all subjects + for iStudy = iStudiesList + % Get list of fields of this study + try + studyList = eval(['{ProtocolStudies.Study(iStudy).', fieldName, '}']); + catch + continue + end + % Nothing found: continue with next study + if isempty(studyList) + continue; + end + % Replace empty cells with empty strings + iEmtpyCells = find(cellfun(@isempty, studyList)); + for i = 1:length(iEmtpyCells) + studyList{iEmtpyCells(i)} = ''; + end + % Remove STUDIES path from all elements in list + studyList = strrep(studyList, ProtocolInfo.STUDIES, ''); + % Find target in this list + iItems = find(io_compareFileNames(studyList, fieldFile)); + if ~isempty(iItems) + sFoundStudy = ProtocolStudies.Study(iStudy); + iFoundStudy = iStudy; + return + end + end + % SPECIAL INDICES + iAnalysisStudy = -2; + iDefaultStudy = -3; + % ANALYSIS STUDY + if isempty(iItems) && ~isempty(ProtocolStudies.AnalysisStudy) + % Get list of fields of this study + studyList = eval(['{ProtocolStudies.AnalysisStudy.', fieldName, '}']); + % Remove STUDIES path from all elements in list + studyList = strrep(studyList, ProtocolInfo.STUDIES, ''); + % Find target in this list + iItems = find(io_compareFileNames(studyList, fieldFile)); + if ~isempty(iItems) + sFoundStudy = ProtocolStudies.AnalysisStudy; + iFoundStudy = iAnalysisStudy; + return + end + end + % DEFAULT STUDY + if isempty(iItems) && ~isempty(ProtocolStudies.DefaultStudy) + % Get list of fields of this study + studyList = eval(['{ProtocolStudies.DefaultStudy.', fieldName, '}']); + % Remove STUDIES path from all elements in list + studyList = strrep(studyList, ProtocolInfo.STUDIES, ''); + % Find target in this list + iItems = find(io_compareFileNames(studyList, fieldFile)); + if ~isempty(iItems) + sFoundStudy = ProtocolStudies.DefaultStudy; + iFoundStudy = iDefaultStudy; + return + end + end + catch + warning('Database error. Please reload all the protocol.'); + end +end + + + + + + + diff --git a/brainstorm3/toolbox/core/bst_safeCall.m b/brainstorm3/toolbox/core/bst_safeCall.m new file mode 100644 index 0000000..b4d722f --- /dev/null +++ b/brainstorm3/toolbox/core/bst_safeCall.m @@ -0,0 +1,46 @@ +function varargout = bst_safeCall( varargin ) +% BST_SAFECALL: Call any function with an error catching. + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +try + if (nargout) + [varargout{1:nargout}] = feval(varargin{:}); + else + feval(varargin{:}); + end +catch + bst_error(); + if (nargout > 0) + varargout(1:nargout) = cell(1, nargout); + end +end + +end + + + + + + diff --git a/brainstorm3/toolbox/db/db_getDataTemplate.m b/brainstorm3/toolbox/db/db_getDataTemplate.m new file mode 100644 index 0000000..aee8b4c --- /dev/null +++ b/brainstorm3/toolbox/db/db_getDataTemplate.m @@ -0,0 +1,538 @@ +function [ template ] = db_getDataTemplate(structureName) +% DB_GETDATATEMPLATE: Defines a template structure for all the Brainstorm data types. +% +% USAGE : [template] = db_getDataTemplate(structureName); +% +% INPUT: String - {'Anatomy', 'Surface', 'Channel', 'Data', 'HeadModel', 'Results', 'Stat', +% 'Subject', 'Study', 'ProtocolInfo', 'ProtocolSubjects', 'ProtocolStudies', +% 'Layout', 'Colormap', 'Measures', 'LoadedResults', 'FigureId', +% 'Figure', 'Dataset', 'DisplayHandlesTimeSeries', 'DisplayHandlesTopography', +% 'DisplayHandles3DViz', 'Scout', 'GlobalData', 'Landmark', +% 'SCS', 'NCS', 'TessInfo', ...} + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% Define templates that might be used in different ways +templateAnatomy = struct(... + 'Comment', '', ... + 'FileName', ''); + +templateSurface = struct(... + 'Comment', '', ... + 'FileName', '', ... + 'SurfaceType', ''); + +templateChannel = struct(... + 'FileName', '', ... + 'Comment', '', ... + 'nbChannels', 0, ... + 'Modalities', [], ... + 'DisplayableSensorTypes', []); +templateData = struct(... + 'FileName', '', ... + 'Comment', ''); +templateImage = struct(... + 'FileName', '', ... + 'Comment', ''); +templateNoiseCov = struct(... + 'FileName', '', ... + 'Comment', ''); +templateHeadModel = struct(... + 'FileName', '', ... + 'HeadModelName', '', ... + 'HeadModelType', '', ... + 'MEGMethod', '', ... + 'EEGMethod', '', ... + 'GridName', ''); +templateResult = struct(... + 'FileName', '', ... + 'Comment', '', ... + 'DataFile', '', ... + 'isLink', 0); +templateStat = struct(... + 'FileName', '', ... + 'Comment', '', ... + 'Type', '', ... + 'pThreshold', '', ... + 'DataFile', ''); % FOR STATS ON RESULTS ONLY + +switch lower(structureName) + % ==== ANATOMY ==== + case 'anatomy' + template = templateAnatomy; + % ==== SURFACE ==== + case 'surface' + template = templateSurface; + + % ==== CHANNEL ==== + case 'channel' + template = templateChannel; + % ==== DATA ==== + case 'data' + template = templateData; + % ==== HEADMODEL ==== + case 'headmodel' + template = templateHeadModel; + % ==== RESULTS ==== + case 'results' + template = templateResult; + % ==== STAT ==== + case 'stat' + template = templateStat; + % ==== IMAGE ==== + case 'image' + template = templateImage; + % ==== NOISECOV ==== + case 'noisecov' + template = templateNoiseCov; + % ==== FILES ==== + case 'datamat' + template = struct('F', [], ... + 'Comment', '', ... + 'ChannelFlag', [], ... + 'Time', [], ... + 'Device', ''); + case 'channelmat' + template = struct(... + 'Comment', 'FIF channels', ... + 'MegRefCoef', [], ... % CTF compensators matrix, [nMeg x nMegRef] + 'Projector', [], ... % SSP matrix, [nChannels x nChannels] + 'TransfMeg', [], ... % MEG sensors: Successive transforms from device coord. system to brainstorm SCS + 'TransfEeg', [], ... % EEG sensors: Successive transforms from device coord. system to brainstorm SCS + 'HeadPoints', struct(...% Digitized head points + 'Loc', [], ... + 'Label', [], ... + 'Type', []), ... + 'Channel', []); % [nChannels] Structure array, one structure per sensor + % ==== SUBJECT ==== + case 'subject' + template = struct(... + 'Name', 'Unnamed', ... + 'Comments', '', ... + 'FileName', '', ... + 'DateOfAcquisition', '', ... + 'Anatomy', repmat(templateAnatomy,0), ... + 'Surface', repmat(templateSurface,0), ... + 'iAnatomy', [], ... + 'iScalp', [], ... + 'iCortex', [], ... + 'iInnerSkull', [], ... + 'iOuterSkull', [], ... + 'iOther', [], ... + 'UseDefaultAnat', 0 , ... + 'UseDefaultChannel', 1); + + % ==== STUDY ==== + case 'study' + template = struct(... + 'Name', 'Unnamed', ... + 'FileName', '', ... + 'DateOfStudy', '', ... + 'BrainStormSubject', '', ... + 'Condition', '', ... + 'Channel', repmat(templateChannel,0), ... + 'iChannel', [], ... + 'Data', repmat(templateData,0), ... + 'HeadModel', repmat(templateHeadModel,0), ... + 'iHeadModel', [], ... + 'Result', repmat(templateResult,0), ... + 'Stat', repmat(templateStat, 0), ... + 'Image', repmat(templateImage, 0), ... + 'NoiseCov', repmat(templateNoiseCov, 0)); + + % ==== PROTOCOLINFO ==== + case 'protocolinfo' + template = struct(... + 'Comment', 'default_protocol', ... + 'STUDIES', '', ... + 'SUBJECTS', '', ... + 'iStudy', [], ... + 'UseDefaultAnat', 0, ... + 'UseDefaultChannel', 1); + + case 'protocolsubjects' + template = struct(... + 'Subject', repmat(db_getDataTemplate('Subject'), 0), ... + 'DefaultSubject', []); + + case 'protocolstudies' + template = struct(... + 'Study', repmat(db_getDataTemplate('Study'), 0), ... + 'DefaultStudy', db_getDataTemplate('Study'), ... + 'AnalysisStudy', db_getDataTemplate('Study')); + + % ==== LAYOUT ==== + case 'layout' + template = struct(... + 'MainWindowPos', [0 0 0 0], ... + 'MainWindowSplitHorizontal', 0, ... + 'MainWindowExplorationMode', 'Subjects', ... + 'ScreensDef', [], ... + 'NoGUI', 0); + + % ==== FILE IMPORT ==== + case 'sfile' + template = struct(... + 'filename', '', ... % Full path to the file + 'format', '', ... % {fif,ctf,egi,neuroscan,brainamp,lena,cartool,...} + 'device', '', ... % {neuromag,ctf,egi,neuroscan,brainamp,...} + 'comment', '', ... + 'fid', [], ... % Matlab file identifier + 'prop', struct(... % Properties of the recordings + 'times', [], ... % [tStart, tStop] + 'samples', [], ... % [iStart, iStop] + 'sfreq', 0, ... % Sampling frequency + 'rejected_segments', [], ... % [nBadSeg,2], list of bad segments, defined in number of samples + 'currCtfComp', [], ... % {0,1,3} Current CTF compensation order already applied to the recordings + 'destCtfComp', [], ... % {0,1,3} Destination CTF compensation order + 'inactiveProjector', []), ... % SSP projectors that need to be applied to the recordings + 'epochs', repmat(struct(... + 'label', '', ... + 'samples', [], ... % [iStart, iStop] + 'times', [], ... % [tStart, tStop] + 'nave', 0, ... % Number of epochs averaged to produce this block + 'select', 1), 0), ... + 'events', repmat(struct(... + 'label', '', ... + 'epochs', [], ... % [list of epochs indices] + 'samples', [], ... % [list of time indices] + 'times', [], ... % [list of time values] + 'reactTimes', [], ... % [list of reaction times, when applicable] + 'select', 1), 0), ... + 'header', [], ... + 'channelmat', [], ... + 'channelflag', []); + + case 'importoptions' + template = struct(... + 'UseEvents', 0, ... % {0,1}: If 1, perform epoching around the selected events + 'EventsTimeRange', [-0.1000 0.3000], ... % Time range for epoching, zero is the event onset (if epoching is enabled) + 'GetAllEpochs', 0, ... % {0,1}: Import all arrays, no matter how many they are + 'iEpochs', 1, ... % Array of indices of epochs to import (if GetAllEpochs is not enabled) + 'SplitRaw', 0, ... % {0,1}: If 1, and if importing continuous recordings (no epoching, no events): split recordings in small time blocks + 'SplitLength', 2, ... % Duration of each split time block, in seconds + 'Resample', 0, ... % Enable resampling (requires Signal Processing Toolbox) + 'ResampleFreq', 0, ... % Resampling frequency (if resampling is enabled) + 'UseCtfComp', 1, ... % Get and apply CTF 3rd gradient correction if available + 'UseSsp', 1, ... % Get and apply SSP (Signal Space Projection) vectors if available + 'RemoveBaseline', 'no', ... % Method used to remove baseline of each channel: {no, all, time, sample} + 'BaselineRange', [], ... % [tStart,tStop] If RemoveBaseline is 'time'; [sampleStart,sampleStop] If RemoveBaseline is 'sample'; Else ignored + 'ImportMode', 'Epoch', ... % Import mode: {Epoch, Time, Event} + 'events', [], ... % Events structure: (label, epochs, samples, times, reactTimes, select) + 'AutoAnswer', 0, ... % Answer automatically to all the questions that can be asked to the user (USE CAREFULLY) + 'CreateConditions', 0); % {0,1} If 1, create new conditions in Brainstorm database if it is more convenient + + % ==== COLORMAPS ==== + case 'colormap' + template = struct(... + 'Name', '', ... + 'CMap', [], ... + 'isAbsoluteValues', 0, ... + 'isNormalized', 0, ... + 'DisplayColorbar', 0, ... + 'MaxValue', [], ... + 'MaxValueType', '', ... + 'Contrast', 0, ... + 'Brightness', 0); + + % ==== GLOBAL DATA ==== + case 'measures' + template = struct(... + 'Time', [], ... + 'NumberOfSamples', [], ... + 'ChannelFlag', [], ... + 'F', [], ... + 'isStatic', 0); + + case 'loadedresults' + template = struct(... + 'FileName', '', ... + 'Comment', '', ... + 'Time', [], ... + 'SamplingRate', [], ... + 'NumberOfSamples', [], ... + 'ChannelFlag', [], ... + 'ImageGridAmp', [], ... + 'ImagingKernel', [], ... + 'nbVertices', [], ... + 'SurfaceFile', '', ... + 'Fsynth', [], ... + 'GoodChannel', [], ... + 'isStatic', 0); %, ... + %'Residuals', []); + + case 'loadedsurface' + template = struct(... + 'FileName', '', ... + 'Name', '', ... + 'Comment', '', ... + 'Vertices', [], ... + 'Faces', [], ... + 'VertConn', [], ... + 'VertNormals', [], ... + 'Curvature', [], ... + 'tess2mri_interp', []); % Interpolation matrix (Surface -> MRI) + + case 'loadedmri' + template = struct(... + 'FileName', '', ... + 'Comment', '', ... + 'Cube', [], ... + 'Voxsize', [], ... + 'SCS', [], ... + 'NCS', [], ... + 'Histogram', [], ... + 'InitTransf', []); + + + case 'figureid' + template = struct(... + 'Type', '', ... + 'SubType', '', ... + 'Modality', ''); + + case 'figure' + template = struct(... + 'Id', db_getDataTemplate('FigureId'), ... + 'hFigure', 0, ... + 'Handles', struct(), ... + 'SelectedChannels', []); + + case 'channeldesc' + template = struct(... + 'Name', '', ... + 'Comment', '', ... + 'Type', '', ... + 'Loc', [], ... + 'Orient', [], ... + 'Weight', []); + + case 'dataset' + template = struct(... + 'DataFile', '', ... + 'StudyFile', '', ... + 'SubjectFile', '', ... + 'ChannelFile', '', ... + 'Surfaces', repmat(db_getDataTemplate('LoadedSurface'), 0), ... + 'Measures', db_getDataTemplate('Measures'), ... + 'Results', repmat(db_getDataTemplate('LoadedResults'), 0), ... + 'Channel', repmat(db_getDataTemplate('ChannelDesc'), 0), ... + 'HeadPoints', [], ... + 'MouseSelectedChannels', [], ... + 'Figure', repmat(db_getDataTemplate('Figure'), 0), ... + 'isStat', 0, ... + 'isZscore', 0); + + case 'displayhandlestimeseries' + template = struct(... + 'hTimeCursor', [], ... + 'hTextCursor', [], ... + 'hTimeZeroLine', [], ... + 'hLines', [], ... + 'LinesColor', [], ... + 'DataMinMax', [], ... + 'DisplayFactor', [], ... + 'DisplayMode', []); + case 'displayhandlestopography' + template = struct(... + 'hSurf', [], ... + 'Wmat', [], ... + 'DisplayMegGrad', '', ... % {'first','second','norm'} + 'DataMinMax', [], ... + 'hSensorMarkers', [], ... + 'hSensorLabels', [], ... + 'hSensorOrient', [], ... + 'hContours', [], ... + 'MarkersLocs', []); + + case 'displayhandles3dviz' + template = struct(... + 'hSensorMarkers', [], ... + 'hSensorLabels', [], ... + 'hSensorOrient', []); + + case 'scout' + template = struct(... + 'SurfaceFile', '', ... % File on which the scout is defined + 'Vertices', [], ... % Index of closest vertices to current scout + 'Seed', [], ... % Original vertex of the scout area + 'Area', [], ... % Scout area, in cm + 'Handles', repmat(struct( ... + 'hFig', [], ... % Figure handle in which the scout is displayed + 'hScout', [], ... % Handles to the graphical scout objects + 'hLabel', [], ... + 'hVertices', [], ... + 'hPatch', []), 0), ... + 'Color', [0 1 0], ... + 'Label', ''); + + case 'cluster' + template = struct(... + 'Sensors', '', ... % File on which the scout is defined + 'Label', ''); + + case 'globaldata' + template = struct(... + 'DataSet', repmat(db_getDataTemplate('DataSet'), 0), ... + 'Mri', repmat(db_getDataTemplate('LoadedMri'), 0), ... + 'Surface', repmat(db_getDataTemplate('LoadedSurface'), 0), ... + 'MaxTimeWindow', struct(... + 'Time', [], ... + 'SamplingRate', [], ... + 'NumberOfSamples', 0), ... + 'UserTimeWindow', struct(... + 'Time', [], ... + 'SamplingRate', [], ... + 'NumberOfSamples', 0, ... + 'CurrentTime', []), ... + 'ChannelEditor', struct(... + 'ChannelFile', '', ... + 'ChannelMat', [], ... + 'DataFile', [], ... + 'isPathAbsolute', 0, ... + 'LocColumns', [], ... + 'OrientColumns', [], ... + 'isModified', 0), ... + 'HeadModeler', struct(... + 'sSubject', [], ... + 'iStudies', [], ... + 'Channel', [], ... + 'isEEG', 0, ... + 'isMEG', 0, ... + 'HeadPoints', [], ... + 'nbSpheres', 0, ... + 'BFS', [], ... + 'GUI', struct(... + 'hFig', [], ... + 'Figure3DButtonDown_Bak', [], ... + 'Figure3DButtonMotion_Bak', [], ... + 'Figure3DButtonUp_Bak', [], ... + 'Figure3DCloseRequest_Bak', [], ... + 'selectedButton', [], ... + 'mouseClicked', [], ... + 'isClosing', [], ... + 'hButtonTransX', [], ... + 'hButtonTransY', [], ... + 'hButtonTransZ', [], ... + 'hButtonResize', [])), ... + 'InverseSolutions', struct(... + 'iStudyList', [], ... + 'iDataList', [], ... + 'isSurfHeadmodel', 1, ... + 'AvailableModalities', [], ... + 'Time', [], ... + 'SamplingRate', [], ... + 'TimeSegment', [], ... + 'BaselineSegment', [], ... + 'Modalities', {}), ... + 'Stat', struct(... + 'TimeWindowAA', [], ... + 'TimeWindowAB', [], ... + 'TimeWindowUnique', [], ... + 'SampleFilesA', [], ... + 'SampleFilesAA', [], ... + 'SampleFilesAB', [], ... + 'FilterFileTag', ''), ... + 'Scouts', repmat(db_getDataTemplate('Scout'), 0), ... + 'Clusters', repmat(db_getDataTemplate('Cluster'), 0), ... + 'CurrentFigure', struct(... + 'Type3D', [], ... + 'Type2D', [], ... + 'Last', []), ... + 'CurrentScoutsSurface', '', ... + 'VisualizationFilters', struct(... + 'LowPassEnabled', 0, ... + 'LowPassValue', 40, ... + 'HighPassEnabled', 0, ... + 'HighPassValue', 1), ... + 'MIP', struct(... + 'isMipAnatomy', 0, ... + 'isMipFunctional', 0), ... + 'Colormaps', [], ... + 'ChannelSelections', struct(... + 'CurrentSelection', [], ... + 'Selections', [], ... + 'DefaultFactor', 1)); + + + case 'landmark' + template = struct(... + 'Name', '', ... + 'mriLoc', ''); + case 'scs' + template = struct(... + 'NAS', [], ... + 'LPA', [], ... + 'RPA', [], ... + 'R', [], ... + 'T', []); + case 'ncs' + template = struct(... + 'AC', [], ... + 'PC', [], ... + 'IH', []); + + % ===== 3DViz appdata structure ===== + case 'tessinfo' + antomyColor = [.35*[1 1 1]; .6*[1 1 1]]; + %antomyColor = [.7*[0.93 0.82 0.80]; [0.93 0.82 0.80]]; + template = struct(... + 'SurfaceFile', '', ... + 'Name', '', ... + 'DataSource', struct(... + 'Type', '', ... % {'data', 'results', 'stats', ...} + 'FileName', '', ... + 'isStat', 0, ... + 'isZscore', 0), ... + 'hPatch', [], ... + 'nVertices', 0, ... + 'nFaces', 0, ... + 'SurfAlpha', 0, ... % Surface transparency + 'SurfShowCurvature', 0, ... % Toggle show/hide surface curvature viewing + 'SurfCurvatureThreshold', 0, ... % Threshold to apply to color coding of curvature values + 'SurfShowEdges', 0, ... % Toggle oon/off surface edges display + 'AnatomyColor', antomyColor, ... % RGB color for curvature encoding + 'SurfSmoothValue', 0, ... + 'Data', [], ... % MEG, EEG or current density for overlay to anatomy (needs to be compatible in size with FaceVertexCdata patch property) + 'DataMinMax', [], ... % Minimum and maximum of the DataSource.FileName file + 'DataWmat', [], ... % Interpolation matrix (transformation to map Data on hPatch surface) + 'OverlayCube', [], ... % Interpolated results in a MRI volume + 'DataAlpha', 0, ... % Alpha for blending of anatomy and surface data + 'DataIntThreshold', 0.5, ... % Threshold to apply to color coding of data values + 'DataExtThreshold', 0, ... % Hide activation cluster smaller than ... + 'DataLimitValue', [], ... % Relative limits for colormapping + 'CutsPosition', [0 0 0], ... % Position of the three orthogonal MRI slices + 'Resect', 'none', ... % Either [x,y,z] resect values, or {'left', 'right', 'none'} + 'MipAnatomy', [], ... % 3 cells: Maximum intensity power in each direction (MRI amplitudes) + 'MipFunctional', [] ... % 3 cellsMaximum intensity power in each direction (sources amplitudes) + ); + template.MipAnatomy = cell(3,1); + template.MipFunctional = cell(3,1); + otherwise + error('Unknown data template : %s', structureName); +end + + + + diff --git a/brainstorm3/toolbox/gui/gui_figure3DViz.m b/brainstorm3/toolbox/gui/gui_figure3DViz.m new file mode 100644 index 0000000..0a72054 --- /dev/null +++ b/brainstorm3/toolbox/gui/gui_figure3DViz.m @@ -0,0 +1,2183 @@ +function varargout = gui_figure3DViz( varargin ) +% GUI_FIGURE3DVIZ: Creation and callbacks for 3D visualization figures. +% +% USAGE: +% [hFig] = gui_figure3DViz() : Create default figure +% [hFig] = gui_figure3DViz(FigureId, figureName) : Create named figure +% [hFig] = gui_figure3DViz(FigureId) : Create unnamed figure +% gui_figure3DViz('CurrentTimeChangedCallback', iDS, iFig) +% gui_figure3DViz('ColormapChangedCallback', iDS, iFig, ColormapType) +% gui_figure3DViz('FigureClickCallback', hFig, event) +% gui_figure3DViz('FigureMouseMoveCallback', hFig, event) +% gui_figure3DViz('FigureMouseUpCallback', hFig, event) +% gui_figure3DViz('FigureMouseWheelCallback', hFig, event) +% gui_figure3DViz('FigureKeyPressedCallback', hFig, keyEvent) +% gui_figure3DViz('ResetView', hFig) +% gui_figure3DViz('SetStandardView', hFig, viewNames) +% gui_figure3DViz('DisplayFigurePopup', hFig) +% [Chan,ChanLoc]= gui_figure3DViz('GetSelectedChannels', iDS, iFig) +% gui_figure3DViz('UpdateSelectedChannels', iDS, iFig) +% gui_figure3DViz('UpdateSurfaceColor', hFig, iTess) +% gui_figure3DViz('ViewSensors', hFig, isMarkers, isLabels) +% gui_figure3DViz('ViewAxis', hFig, isVisible) +% [hFig,hs] = gui_figure3DViz('PlotSurface', hFig, faces, verts, cdata, dataCMap, transparency) + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +%% ===== CALL TO A SUBFUNCTION ===== +if (nargin >= 1) && ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end + return + +%% ===== CREATE FIGURE ===== +% Create default figure +% CALL: [hFig] = gui_figure3DViz() +elseif (nargin == 0) + % Create a new 3DViz figure + FigureId = db_getDataTemplate('FigureId'); + FigureId.Type = '3DViz'; + FigureId.SubType = ''; + FigureId.Modality = ''; + [hFig, hAxes] = gui_figure3DViz(FigureId, '3D'); + % Set figure visible + set(hFig, 'Visible', 'on'); + % Return values + if (nargout >= 1) + varargout{1} = hFig; + end + if (nargout >= 2) + varargout{2} = hAxes; + end + +% CALL: [hFig] = gui_figure3DViz(FigureId, figureName) : Create named figure +% [hFig] = gui_figure3DViz(FigureId) : Create unnamed figure +elseif isstruct(varargin{1}) + % Get FigureId and figure Name + FigureId = varargin{1}; + if (nargin >= 2) + figureName = varargin{2}; + else + figureName = '3D'; + end + % Get renderer name + rendererName = 'opengl'; + + % === CREATE FIGURE === + hFig = figure('Visible', 'off', ... + 'NumberTitle', 'off', ... + 'IntegerHandle', 'off', ... + 'MenuBar', 'none', ... + 'Toolbar', 'none', ... + 'DockControls', 'on', ... + 'Units', 'pixels', ... + 'Color', [0 0 0], ... + 'Tag', FigureId.Type, ... + 'Name', figureName, ... + 'Renderer', rendererName, ... + 'CloseRequestFcn', @(h,ev)gui_figuresManager('DeleteFigure',h,ev), ... + 'KeyPressFcn', @(h,ev)bst_safeCall(@FigureKeyPressedCallback,h,ev), ... + 'WindowButtonDownFcn', @FigureClickCallback, ... + 'WindowButtonMotionFcn', @FigureMouseMoveCallback, ... + 'WindowButtonUpFcn', @FigureMouseUpCallback, ... + 'ResizeFcn', @(h,ev)bst_colormaps('ResizeCallbackForColorbar', h, ev), ... + 'BusyAction', 'queue', ... + 'Interruptible', 'off'); + % Define Mouse wheel callback separately (not supported by old versions of Matlab) + bstVersion = bst_getContext('Version'); + if bstVersion.MatlabVersion >= 7.4 + set(hFig, 'WindowScrollWheelFcn', @FigureMouseWheelCallback); + end + + % === CREATE AXES === + hAxes = axes('Parent', hFig, ... + 'Units', 'normalized', ... + 'Position', [.05 .05 .9 .9], ... + 'Tag', 'Axes3D', ... + 'Visible', 'off', ... + 'BusyAction', 'queue', ... + 'Interruptible', 'off'); + axis vis3d + axis equal + axis off + + % === APPDATA STRUCTURE === + setappdata(hFig, 'Surface', repmat(db_getDataTemplate('TessInfo'), 0)); + setappdata(hFig, 'iSurface', []); + setappdata(hFig, 'StudyFile', []); + setappdata(hFig, 'SubjectFile', []); + setappdata(hFig, 'DataFile', []); + setappdata(hFig, 'ResultsFile', []); + setappdata(hFig, 'isSelectingCorticalSpot', 0); + setappdata(hFig, 'isSelectingCoordinates', 0); + setappdata(hFig, 'hasMoved', 0); + setappdata(hFig, 'isPlotEditToolbar', 0); + setappdata(hFig, 'AllChannelsDisplayed', 0); + setappdata(hFig, 'FigureId', FigureId); + setappdata(hFig, 'isStatic', 0); + + % === LIGHTING === + hl = []; + % Fixed lights + hl(1) = camlight( 0, 40, 'infinite'); + hl(2) = camlight(180, 40, 'infinite'); + hl(3) = camlight( 0, -90, 'infinite'); + hl(4) = camlight( 90, 0, 'infinite'); + hl(5) = camlight(-90, 0, 'infinite'); + % Moving camlight + hl(6) = light('Tag', 'FrontLight', 'Color', [1 1 1], 'Style', 'infinite', 'Parent', hAxes); + camlight(hl(6), 'headlight'); + % Mute the intensity of the lights + for i = 1:length(hl) + set(hl(i), 'color', .4*[1 1 1]); + end + + % Camera basic orientation + SetStandardView(hFig, 'top'); + + % Returned values + if (nargout >= 1) + varargout{1} = hFig; + end + if (nargout >= 2) + varargout{2} = hAxes; + end +end +end + + +%% ========================================================================================= +% ===== FIGURE CALLBACKS ================================================================== +% ========================================================================================= +function Compile() %#ok + % Nothing to do... just to force the compilation of the file +end + +%% ===== CURRENT TIME CHANGED ===== +function CurrentTimeChangedCallback(iDS, iFig) %#ok + global GlobalData; + panel_surface('UpdateSurfaceData', GlobalData.DataSet(iDS).Figure(iFig).hFigure); +end + +%% ===== COLORMAP CHANGED ===== +% Usage: ColormapChangedCallback(iDS, iFig, ColormapType) : Update display only if target colormap is used in figure +% ColormapChangedCallback(iDS, iFig) : Update display anyway +function ColormapChangedCallback(iDS, iFig, ColormapType) %#ok + global GlobalData; + panel_surface('UpdateSurfaceColormap', GlobalData.DataSet(iDS).Figure(iFig).hFigure); +end + + + +%% ========================================================================================= +% ===== KEYBOARD AND MOUSE CALLBACKS ====================================================== +% ========================================================================================= +% Complete mouse and keyboard management over the main axes +% Supports : - Customized 3D-Rotation (LEFT click) +% - Pan (SHIFT+LEFT click, OR MIDDLE click +% - Zoom (CTRL+LEFT click, OR RIGHT click, OR WHEEL) +% - Colorbar contrast/brightness +% - Restore original view configuration (DOUBLE click) + +%% ===== FIGURE CLICK CALLBACK ===== +function FigureClickCallback(hFig, varargin) +%disp('=== MouseDown ==='); + % Find axes + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + if isempty(hAxes) + warning('Brainstorm:NoAxes', 'Axes could not be found'); + return; + end + % Get figure type + FigureId = getappdata(hFig, 'FigureId'); + % Double click: reset view + if strcmpi(get(hFig, 'SelectionType'), 'open') + ResetView(hFig); + end + % Check if MouseUp was executed before MouseDown + if isappdata(hFig, 'clickAction') && strcmpi(getappdata(hFig,'clickAction'), 'MouseDownNotConsumed') + % Should ignore this MouseDown event + setappdata(hFig,'clickAction','MouseDownOk'); + return; + end + + % Start an action (pan, zoom, rotate, contrast, luminosity) + % Action depends on : + % - the mouse button that was pressed (LEFT/RIGHT/MIDDLE), + % - the keys that the user presses simultaneously (SHIFT/CTRL) + clickAction = ''; + switch(get(hFig, 'SelectionType')) + % Left click + case 'normal' + % 2DLayout: pan + if strcmpi(FigureId.SubType, '2DLayout') + clickAction = 'pan'; + % 2D: nothing + elseif ismember(FigureId.SubType, {'2DDisc', '2DSensorCap'}) + % Nothing to do + % Else (3D): rotate + else + clickAction = 'rotate'; + end + % CTRL+Mouse, or Mouse right + case 'alt' + clickAction = 'popup'; + % SHIFT+Mouse, or Mouse middle + case 'extend' + clickAction = 'pan'; + end + + % Record action to perform when the mouse is moved + setappdata(hFig, 'clickAction', clickAction); + setappdata(hFig, 'clickSource', hFig); + % Reset the motion flag + setappdata(hFig, 'hasMoved', 0); + % Record mouse location in the figure coordinates system + setappdata(hFig, 'clickPositionFigure', get(hFig, 'CurrentPoint')); + % Record mouse location in the axes coordinates system + setappdata(hFig, 'clickPositionAxes', get(hAxes, 'CurrentPoint')); +%disp('=== MouseDown: END ==='); +end + + +%% ===== FIGURE MOVE ===== +function FigureMouseMoveCallback(hFig, varargin) + % Get axes handle + hAxes = findobj(hFig, 'tag', 'Axes3D'); + % Get current mouse action + clickAction = getappdata(hFig, 'clickAction'); + clickSource = getappdata(hFig, 'clickSource'); + % If no action is currently performed + if isempty(clickAction) + % Colorbar help message +% ColorbarHelpMessage(hFig); + return + end + % If MouseUp was executed before MouseDown + if strcmpi(clickAction, 'MouseDownNotConsumed') || isempty(getappdata(hFig, 'clickPositionFigure')) + % Ignore Move event + return + end + % If source is not the same as the current figure: fire mouse up event + if (clickSource ~= hFig) + FigureMouseUpCallback(hFig); + FigureMouseUpCallback(clickSource); + return + end + + % Set the motion flag + setappdata(hFig, 'hasMoved', 1); + % Get current mouse location in figure + curptFigure = get(hFig, 'CurrentPoint'); + motionFigure = 0.3 * (curptFigure - getappdata(hFig, 'clickPositionFigure')); + % Get current mouse location in axes + curptAxes = get(hAxes, 'CurrentPoint'); + oldptAxes = getappdata(hFig, 'clickPositionAxes'); + if isempty(oldptAxes) + return + end + motionAxes = curptAxes - oldptAxes; + % Update click point location + setappdata(hFig, 'clickPositionFigure', curptFigure); + setappdata(hFig, 'clickPositionAxes', curptAxes); + % Get figure size + figPos = get(hFig, 'Position'); + + % Switch between different actions (Pan, Rotate, Zoom, Contrast) + switch(clickAction) + case 'rotate' + % Else : ROTATION + % Rotation functions : 5 different areas in the figure window + % ,---------------------------. + % | 2 | + % .75 |---------------------------| + % | 3 | 5 | 4 | + % | | | | + % .25 |---------------------------| + % | 1 | + % '---------------------------' + % .25 .75 + % + % ----- AREA 1 ----- + if (curptFigure(2) < .25 * figPos(4)) + camroll(hAxes, motionFigure(1)); + camorbit(hAxes, 0,-motionFigure(2), 'camera'); + % ----- AREA 2 ----- + elseif (curptFigure(2) > .75 * figPos(4)) + camroll(hAxes, -motionFigure(1)); + camorbit(hAxes, 0,-motionFigure(2), 'camera'); + % ----- AREA 3 ----- + elseif (curptFigure(1) < .25 * figPos(3)) + camroll(hAxes, -motionFigure(2)); + camorbit(hAxes, -motionFigure(1),0, 'camera'); + % ----- AREA 4 ----- + elseif (curptFigure(1) > .75 * figPos(3)) + camroll(hAxes, motionFigure(2)); + camorbit(hAxes, -motionFigure(1),0, 'camera'); + % ----- AREA 5 ----- + else + camorbit(hAxes, -motionFigure(1),-motionFigure(2), 'camera'); + end + camlight(findobj(hAxes, 'Tag', 'FrontLight'), 'headlight'); + + case 'pan' + % Get camera textProperties + pos = get(hAxes, 'CameraPosition'); + up = get(hAxes, 'CameraUpVector'); + target = get(hAxes, 'CameraTarget'); + % Calculate a normalised right vector + right = cross(up, target - pos); + up = up ./ realsqrt(sum(up.^2)); + right = right ./ realsqrt(sum(right.^2)); + % Calculate new camera position and camera target + panFactor = 0.001; + pos = pos + panFactor .* (motionFigure(1).*right - motionFigure(2).*up); + target = target + panFactor .* (motionFigure(1).*right - motionFigure(2).*up); + set(hAxes, 'CameraPosition', pos, 'CameraTarget', target); + + case 'zoom' + if (motionFigure(2) == 0) + return; + elseif (motionFigure(2) < 0) + % ZOOM IN + Factor = 1-motionFigure(2)./100; + elseif (motionFigure(2) > 0) + % ZOOM OUT + Factor = 1./(1+motionFigure(2)./100); + end + zoom(hFig, Factor); + + case {'moveSlices', 'popup'} + % Get MRI + [sMri,TessInfo,iTess] = panel_surface('GetSurfaceMri', hFig); + if isempty(iTess) + return + end + + % === DETECT ACTION === + % Is moving axis and direction are not detected yet : do it + if (~isappdata(hFig, 'moveAxis') || ~isappdata(hFig, 'moveDirection')) + % Guess which cut the user is trying to change + % Sometimes some problem occurs, leading to values > 800 + % for a 1-pixel movement => ignoring + if (max(motionAxes(1,:)) > 20) + return; + end + % Convert MRI-CS -> SCS + motionAxes = motionAxes * sMri.SCS.R; + % Get the maximum deplacement as the direction + [value, moveAxis] = max(abs(motionAxes(1,:))); + moveAxis = moveAxis(1); + % Get the directions of the mouse deplacement that will + % increase or decrease the value of the slice + [value, moveDirection] = max(abs(motionFigure)); + moveDirection = sign(motionFigure(moveDirection(1))) .* ... + sign(motionAxes(1,moveAxis)) .* ... + moveDirection(1); + % Save the detected movement direction and orientation + setappdata(hFig, 'moveAxis', moveAxis); + setappdata(hFig, 'moveDirection', moveDirection); + + % === MOVE SLICE === + else + % Get saved information about current motion + moveAxis = getappdata(hFig, 'moveAxis'); + moveDirection = getappdata(hFig, 'moveDirection'); + % Get the motion value + val = sign(moveDirection) .* motionFigure(abs(moveDirection)); + % Get the new position of the slice + oldPos = TessInfo(iTess).CutsPosition(moveAxis); + newPos = round(saturate(oldPos + val, [1 size(sMri.Cube, moveAxis)])); + + % Plot a patch that indicates the location of the cut + PlotSquareCut(hFig, TessInfo(iTess), moveAxis, newPos); + + % Draw a new X-cut according to the mouse motion + posXYZ = [NaN, NaN, NaN]; + posXYZ(moveAxis) = newPos; + panel_surface('PlotMri', hFig, posXYZ); + end + + case 'colorbar' + % Delete legend + % delete(findobj(hFig, 'Tag', 'ColorbarHelpMsg')); + % Get colormap name + [AllColormapTypes, ColormapType] = gui_figuresManager('GetDisplayedDataTypes', hFig); + % Changes contrast + sColormap = bst_colormaps('ColormapChangeModifiers', ColormapType, [motionFigure(1), motionFigure(2)] ./ 100, 0); + set(hFig, 'Colormap', sColormap.CMap); + end +%disp('=== MouseMove: END ==='); +end + + +%% ===== FIGURE MOUSE UP ===== +function FigureMouseUpCallback(hFig, varargin) +%disp('=== MouseUp ==='); + global GlobalData; + % === 3DViz specific commands === + % Get application data (current user/mouse actions) + clickAction = getappdata(hFig, 'clickAction'); + hasMoved = getappdata(hFig, 'hasMoved'); + hAxes = findobj(hFig, 'tag', 'Axes3D'); + isSelectingCorticalSpot = getappdata(hFig, 'isSelectingCorticalSpot'); + isSelectingCoordinates = getappdata(hFig, 'isSelectingCoordinates'); + + % Remove mouse appdata (to stop movements first) + setappdata(hFig, 'hasMoved', 0); + if isappdata(hFig, 'clickPositionFigure') + rmappdata(hFig, 'clickPositionFigure'); + end + if isappdata(hFig, 'clickPositionAxes') + rmappdata(hFig, 'clickPositionAxes'); + end + if isappdata(hFig, 'clickAction') + rmappdata(hFig, 'clickAction'); + else + setappdata(hFig, 'clickAction', 'MouseDownNotConsumed'); + end + if isappdata(hFig, 'moveAxis') + rmappdata(hFig, 'moveAxis'); + end + if isappdata(hFig, 'moveDirection') + rmappdata(hFig, 'moveDirection'); + end + % Remove SquareCut objects + PlotSquareCut(hFig); + % Get figure description + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(iDS) + return + end + Figure = GlobalData.DataSet(iDS).Figure(iFig); + % Update figure selection + if strcmpi(Figure.Id.Type, '3DViz') || strcmpi(Figure.Id.SubType, '3DSensorCap') + gui_figuresManager('SetCurrentFigure', hFig, '3D'); + else + gui_figuresManager('SetCurrentFigure', hFig); + end + + % ===== SIMPLE CLICK ===== + % If user did not move the mouse since the click + if ~hasMoved + % === POPUP === + if strcmpi(clickAction, 'popup') + DisplayFigurePopup(hFig); + + % === SELECTING CORTICAL SCOUTS === + elseif isSelectingCorticalSpot + panel_scouts('SelectCorticalSpot', hFig); + + % === SELECTING POINT (COORDINATES PANEL) === + elseif isSelectingCoordinates + panel_coordinates('SelectPoint', hFig); + + % === SELECTING SENSORS === + else + % Check if sensors are displayed in this figure + hSensorsPatch = findobj(hAxes, 'Tag', 'SensorsPatch'); + if (length(hSensorsPatch) == 1) + % Select the nearest sensor from the mouse + [p, v, vi] = select3d(hSensorsPatch); + % If sensor index is not valid + if isempty(vi) || (vi > length(Figure.SelectedChannels)) || (vi <= 0) + return + end + % If clicked point is too far away (5mm) from the closest sensor + % (Do not test Topography figures) + if ~strcmpi(Figure.Id.Type, 'Topography') + if (norm(p - v) > 0.005) + return + end + end + % Is figure used only to display channels + AllChannelsDisplayed = getappdata(hFig, 'AllChannelsDisplayed'); + % If not all the channels are displayed: need to convert the selected sensor indice + if ~AllChannelsDisplayed + % Get channel indice (in Channel array) + iChannel = Figure.SelectedChannels(vi); + else + AllModalityChannels = good_channel(GlobalData.DataSet(iDS).Channel, ... + [], Figure.Id.Modality); + iChannel = AllModalityChannels(vi); + end + % If channel is not selected + if ~ismember(iChannel, GlobalData.DataSet(iDS).MouseSelectedChannels) + % If data is not supposed to have more than one channel selected + if isappdata(hFig, 'UniqueChannelSelection') && (getappdata(hFig, 'UniqueChannelSelection') == 1) + newList = iChannel; + else + newList = [GlobalData.DataSet(iDS).MouseSelectedChannels, iChannel]; + end + % Add it to mouse-selected channels list + bst_dataSetsManager('SetMouseSelectedChannels', GlobalData.DataSet(iDS).ChannelFile, newList); + % Channel is already mouse-selected : unselect it + else + % Remove it from mouse-selected channels list + bst_dataSetsManager('SetMouseSelectedChannels', GlobalData.DataSet(iDS).ChannelFile, ... + setdiff(GlobalData.DataSet(iDS).MouseSelectedChannels, iChannel)); + end + end + end + % ===== MOUSE HAS MOVED ===== + else + % COLORMAP HAS CHANGED + if strcmpi(clickAction, 'colorbar') + % Apply new colormap to all figures + [AllColormapTypes, ColormapType] = gui_figuresManager('GetDisplayedDataTypes', hFig); + bst_colormaps('FireColormapChanged', ColormapType); + % SLICES WERE MOVED + elseif strcmpi(clickAction, 'popup') + % Update "Surfaces" panel + panel_surface('UpdateSurfaceProperties'); + end + end +%disp('=== MouseUp: END ==='); +end + + +%% ===== FIGURE MOUSE WHEEL ===== +function FigureMouseWheelCallback(hFig, event) + % ONLY FOR 3D AND 2DLayout + if isempty(event) + return; + elseif (event.VerticalScrollCount < 0) + % ZOOM IN + Factor = 1 - event.VerticalScrollCount ./ 20; + elseif (event.VerticalScrollCount > 0) + % ZOOM OUT + Factor = 1./(1 + event.VerticalScrollCount ./ 20); + end + zoom(Factor); +end + + +%% ===== KEYBOAD CALLBACK ===== +function FigureKeyPressedCallback(hFig, keyEvent) + global GlobalData TimeSliderMutex; + % Prevent multiple executions + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + set([hFig hAxes], 'BusyAction', 'cancel'); + % Get figure description + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(hFig) + return + end + FigureId = GlobalData.DataSet(iDS).Figure(iFig).Id; + % ===== GET SELECTED CHANNELS ===== + isMenuSelectedChannels = 0; + if ~isempty(iDS) + % Get channel selection + MouseSelection = GlobalData.DataSet(iDS).MouseSelectedChannels; + if ~isempty(MouseSelection) && ~isempty(FigureId.Modality) && (FigureId.Modality(1) ~= '$') + isMenuSelectedChannels = 1; + end + end + % Get if figure should contain all the modality sensors (display channel net) + AllChannelsDisplayed = getappdata(hFig, 'AllChannelsDisplayed'); + % Check if it is a realignment figure + isAlignFig = ~isempty(findobj(hFig, 'Tag', 'AlignToolbar')); + % If figure is 2D + is2D = ~strcmpi(FigureId.Type, '3DViz') && ~strcmpi(FigureId.SubType, '3DSensorCap'); + + % ===== PROCESS BY CHARACTERS ===== + switch (keyEvent.Character) + % === NUMBERS : VIEW SHORTCUTS === + case '1' + if ~is2D + SetStandardView(hFig, 'left'); + end + case '2' + if ~is2D + SetStandardView(hFig, 'bottom'); + end + case '3' + if ~is2D + SetStandardView(hFig, 'right'); + end + case '4' + if ~is2D + SetStandardView(hFig, 'front'); + end + case '5' + if ~is2D + SetStandardView(hFig, 'top'); + end + case '6' + if ~is2D + SetStandardView(hFig, 'back'); + end + case '7' + if ~isAlignFig && ~is2D + SetStandardView(hFig, {'left', 'right'}); + end + case '8' + if ~isAlignFig && ~is2D + SetStandardView(hFig, {'bottom', 'top'}); + end + case '9' + if ~isAlignFig && ~is2D + SetStandardView(hFig, {'front', 'back'}); + end + case '0' + if ~isAlignFig && ~is2D + SetStandardView(hFig, {'left', 'right', 'top'}); + end + case '=' + if ~isAlignFig && ~is2D + ApplyViewToAllFigures(hFig); + end + % === SCOUTS : GROW/SHRINK === + case '+' + panel_scouts('EditScoutsSize', 'Grow1'); + case '-' + panel_scouts('EditScoutsSize', 'Shrink1'); + + otherwise + % ===== PROCESS BY KEYS ===== + switch (keyEvent.Key) + % === LEFT, RIGHT, PAGEUP, PAGEDOWN : Processed by TimeWindow === + case {'leftarrow', 'rightarrow', 'pageup', 'pagedown'} + if isempty(TimeSliderMutex) || ~TimeSliderMutex + panel_timeWindow('SliderKeyCallback',hFig, keyEvent); + end + % === DATABASE NAVIGATOR === + case {'f1', 'f2', 'f3', 'f4'} + if ~isAlignFig + gui_figuresManager('NavigatorKeyPress', hFig, keyEvent); + end + % === DATA FILES : OTHER VIEWS === + % CTRL+A : View axis + case 'a' + if ismember('control', keyEvent.Modifier) + ViewAxis(hFig); + end + % CTRL+D : Dock figure + case 'd' + if ismember('control', keyEvent.Modifier) + isDocked = strcmpi(get(hFig, 'WindowStyle'), 'docked'); + gui_figuresManager('DockFigure', hFig, ~isDocked); + end + % CTRL+R : Recordings time series + case 'r' + if ismember('control', keyEvent.Modifier) + gui_figuresManager('ViewTimeSeries', hFig); + end + % CTRL+T : Default topography + case 't' + if ismember('control', keyEvent.Modifier) + gui_figuresManager('ViewTopography', hFig); + end + % CTRL+S : Sources (first results file) + case 's' + if ismember('control', keyEvent.Modifier) + gui_figuresManager('ViewResults', hFig); + end + % CTRL+I : Save as image + case 'i' + if ismember('control', keyEvent.Modifier) + out_figure_image(hFig); + end + % CTRL+E : Sensors and labels + case 'e' + if ~isAlignFig && ismember('control', keyEvent.Modifier) && ~strcmpi(FigureId.Modality, 'Fsynth') && ~strcmpi(FigureId.Modality, 'Residuals') + hLabels = findobj(hFig, 'Tag', 'SensorsLabels'); + isMarkers = ~isempty(findobj(hFig, 'Tag', 'SensorsPatch')) || ~isempty(findobj(hFig, 'Tag', 'SensorsMarkers')); + isLabels = ~isempty(hLabels); + % All figures, except "2DLayout" + if ~strcmpi(FigureId.SubType, '2DLayout') + % Cycle between three modes : Nothing, Sensors, Sensors+labels + if isMarkers && isLabels + ViewSensors(hFig, 0, 0); + elseif isMarkers + ViewSensors(hFig, 1, 1); + else + ViewSensors(hFig, 1, 0); + end + % "2DLayout" + elseif isLabels + isLabelsVisible = strcmpi(get(hLabels(1), 'Visible'), 'on'); + if isLabelsVisible + set(hLabels, 'Visible', 'off'); + else + set(hLabels, 'Visible', 'on'); + end + end + end + + % === CHANNELS === + % RETURN: VIEW SELECTED CHANNELS + case 'return' + if ~isAlignFig && isMenuSelectedChannels && ~AllChannelsDisplayed + gui_figureTimeSeries('DisplayDataSelectedChannels', iDS, MouseSelection, ... + FigureId.Modality, hFig); + end + % DELETE: SET SELECTED CHANNELS AS BAD + case 'delete' + if ~isAlignFig && isMenuSelectedChannels && ~AllChannelsDisplayed + ChannelFlagSelectionBad = GlobalData.DataSet(iDS).Measures.ChannelFlag; + ChannelFlagSelectionBad(MouseSelection) = -1; + panel_channelEditor('UpdateChannelFlag', GlobalData.DataSet(iDS).DataFile, ... + 0, ChannelFlagSelectionBad); + % Reset MouseSelectedChannels + bst_dataSetsManager('SetMouseSelectedChannels', GlobalData.DataSet(iDS).ChannelFile, []); + end + % ESCAPE: RESET CHANNELS SELECTION + case 'escape' + if ~isAlignFig && isMenuSelectedChannels && ~AllChannelsDisplayed + bst_dataSetsManager('SetMouseSelectedChannels', GlobalData.DataSet(iDS).ChannelFile, []); + end + end + end + % Restore events + if ~isempty(hFig) && ishandle(hFig) && ~isempty(hAxes) && ishandle(hAxes) + set([hFig hAxes], 'BusyAction', 'queue'); + end +end + + +%% ===== RESET VIEW ===== +% Restore initial camera position and orientation +function ResetView(hFig) + zoom out + % Get Axes handle + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + set(hFig, 'CurrentAxes', hAxes); + % Camera basic orientation + SetStandardView(hFig, 'top'); + % Try to find a light source. If found, align it with the camera + camlight(findobj(hAxes, 'Tag', 'FrontLight'), 'headlight'); +end + + +%% ===== SET STANDARD VIEW ===== +function SetStandardView(hFig, viewNames) + % Make sure that viewNames is a cell array + if ischar(viewNames) + viewNames = {viewNames}; + end + % Get Axes handle + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + % Get the data types displayed in this figure + listTypes = gui_figuresManager('GetDisplayedDataTypes', hFig); + R = eye(3); + % If MRI displayed in the figure, use the orientation of the slices, instead of the orientation of the axes + if ismember('Anatomy', listTypes) + % Get the mri surface + TessInfo = getappdata(hFig, 'Surface'); + iTess = find(strcmpi({TessInfo.Name}, 'Anatomy')); + if ~isempty(iTess) + sMri = bst_dataSetsManager('GetMri', TessInfo(iTess).SurfaceFile); + % Get the rotation to change orientation + R = [0 1 0;-1 0 0; 0 0 1] * pinv(sMri.SCS.R); + end + end + % Apply the first orientation to the target figure + switch lower(viewNames{1}) + case 'left' + newView = [0,1,0]; + newCamup = [0 0 1]; + case 'right' + newView = [0,-1,0]; + newCamup = [0 0 1]; + case 'back' + newView = [-1,0,0]; + newCamup = [0 0 1]; + case 'front' + newView = [1,0,0]; + newCamup = [0 0 1]; + case 'bottom' + newView = [0,0,-1]; + newCamup = [1 0 0]; + case 'top' + newView = [0,0,1]; + newCamup = [1 0 0]; + end + % Update camera position + view(hAxes, newView * R); + camup(hAxes, newCamup * R); + + % Update head light position + camlight(findobj(hAxes, 'Tag', 'FrontLight'), 'headlight'); + + % If there are other view to represent + if (length(viewNames) > 1) + hClones = gui_figuresManager('GetClones', hFig); + % Process the other required views + for i = 2:length(viewNames) + if ~isempty(hClones) + % Use an already cloned figure + hNewFig = hClones(1); + hClones(1) = []; + else + % Clone figure + hNewFig = gui_figuresManager('CloneFigure', hFig); + end + % Set orientation + SetStandardView(hNewFig, viewNames(i)); + end + % If there are some cloned figures left : close them + if ~isempty(hClones) + close(hClones); + % Update figures layout + gui_layout(); + end + end +end + + +%% ===== APPLY VIEW TO ALL FIGURES ===== +function ApplyViewToAllFigures(hSrcFig) + % Get Axes handle + hSrcAxes = findobj(hSrcFig, 'Tag', 'Axes3D'); + % Get surface descriptions + SrcTessInfo = getappdata(hSrcFig, 'Surface'); + % Get all figures + hAllFig = gui_figuresManager('GetFiguresByType', '3DViz'); + hAllFig = setdiff(hAllFig, hSrcFig); + % Process all figures + for i = 1:length(hAllFig) + % Get Axes handle + hDestFig = hAllFig(i); + hDestAxes = findobj(hDestFig, 'Tag', 'Axes3D'); + % === COPY CAMERA === + % Copy view angle + [az,el] = view(hSrcAxes); + view(hDestAxes, az, el); + % Copy camup + up = camup(hSrcAxes); + camup(hDestAxes, up); + % Update head light position + camlight(findobj(hDestAxes, 'Tag', 'FrontLight'), 'headlight'); + + % === COPY SURFACES PROPERTIES === + DestTessInfo = getappdata(hDestFig, 'Surface'); + % Process each surface of the figure + for iTess = 1:length(DestTessInfo) + % Find surface name in source figure + iTessInSrc = find(strcmpi(DestTessInfo(iTess).Name, {SrcTessInfo.Name})); + % If surface is also available in source figure + if ~isempty(iTessInSrc) + % Copy surf properties + iTessInSrc = iTessInSrc(1); + DestTessInfo(iTess).SurfAlpha = SrcTessInfo(iTessInSrc).SurfAlpha; + DestTessInfo(iTess).SurfShowCurvature = SrcTessInfo(iTessInSrc).SurfShowCurvature; + DestTessInfo(iTess).SurfCurvatureThreshold = SrcTessInfo(iTessInSrc).SurfCurvatureThreshold; + DestTessInfo(iTess).SurfShowEdges = SrcTessInfo(iTessInSrc).SurfShowEdges; + DestTessInfo(iTess).AnatomyColor = SrcTessInfo(iTessInSrc).AnatomyColor; + DestTessInfo(iTess).SurfSmoothValue = SrcTessInfo(iTessInSrc).SurfSmoothValue; + DestTessInfo(iTess).DataAlpha = SrcTessInfo(iTessInSrc).DataAlpha; + DestTessInfo(iTess).DataIntThreshold = SrcTessInfo(iTessInSrc).DataIntThreshold; + DestTessInfo(iTess).DataExtThreshold = SrcTessInfo(iTessInSrc).DataExtThreshold; + DestTessInfo(iTess).CutsPosition = SrcTessInfo(iTessInSrc).CutsPosition; + DestTessInfo(iTess).Resect = SrcTessInfo(iTessInSrc).Resect; + % Update surfaces structure + setappdata(hDestFig, 'Surface', DestTessInfo); + % Update display + if strcmpi(DestTessInfo(iTess).Name, 'Anatomy') + UpdateMriDisplay(hDestFig, [], DestTessInfo, iTess); + else + UpdateSurfaceAlpha(hDestFig, iTess); + UpdateSurfaceColor(hDestFig, iTess); + end + % Update scouts displayed on this surfce + panel_scouts('UpdateScoutsVertices', DestTessInfo(iTess).SurfaceFile); + end + end + end +end + + +%% ===== POPUP MENU ===== +% Show a popup dialog about the target 3DViz figure +function DisplayFigurePopup(hFig) + import javax.swing.*; + import java.awt.*; + import java.awt.event.KeyEvent; + import org.brainstorm.icon.IconLoader; + + global GlobalData; + % Get figure description + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(iDS) + return + end + % Get DataFile associated with this figure + ProtocolInfo = bst_getContext('ProtocolInfo'); + DataFile = GlobalData.DataSet(iDS).DataFile; + if ~isempty(ProtocolInfo) + DataFileFull = fullfile(ProtocolInfo.STUDIES, DataFile); + else + % Protocol not defined => running without without full brainstorm GUI + DataFileFull = []; + end + % Create popup menu + jPopup = JPopupMenu(); + + % ==== DISPLAY OTHER FIGURES ==== + % Only for MEG and EEG time series + Modality = GlobalData.DataSet(iDS).Figure(iFig).Id.Modality; + FigureType = GlobalData.DataSet(iDS).Figure(iFig).Id.Type; + if ~isempty(DataFile) && ~isempty(DataFileFull) + % === View RECORDINGS === + jItem = JMenuItem([Modality ' Recordings'], IconLoader.ICON_TS_DISPLAY); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_R, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('ViewTimeSeries',hFig)); + jPopup.add(jItem); + % === View TOPOGRAPHY === + if ~strcmpi(FigureType, 'Topography') + jItem = JMenuItem([Modality ' Topography'], IconLoader.ICON_TOPOGRAPHY); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_T, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('ViewTopography',hFig)); + jPopup.add(jItem); + end + % === View SOURCES === + if isempty(getappdata(hFig, 'ResultsFile')) + jItem = JMenuItem('View sources', IconLoader.ICON_RESULTS); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_S, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('ViewResults',hFig)); + jPopup.add(jItem); + end + jPopup.addSeparator(); + end + + % ==== CHANNELS MENU ===== + if ~isempty(DataFile) && ~isempty(DataFileFull) && ~strcmpi(Modality, 'Fsynth') && ~strcmpi(Modality, 'Residuals') + jMenuChannels = JMenu('Channels'); + jMenuChannels.setIcon(IconLoader.ICON_CHANNEL); + % ==== Selected channels submenu ==== + isMarkers = ~isempty(GlobalData.DataSet(iDS).Figure(iFig).Handles.hSensorMarkers); + MouseSelection = GlobalData.DataSet(iDS).MouseSelectedChannels; + % Excludes figures without selection and display-only figures (modality name starts with '$') + if ~isempty(DataFile) && ... + isMarkers && ... + ~isempty(MouseSelection) && ... + ~isempty(Modality) && ... + (Modality(1) ~= '$') + % === VIEW TIME SERIES === + jItem = JMenuItem('View selected', IconLoader.ICON_TS_DISPLAY); + jItem.setAccelerator(KeyStroke.getKeyStroke(int32(KeyEvent.VK_ENTER), 0)); % ENTER + set(jItem, 'ActionPerformedCallback', @(h, ev)gui_figuresManager('ViewTimeSeries', hFig, MouseSelection)); + jMenuChannels.add(jItem); + % === SET AS BAD CHANNELS === + ChannelFlagSelectionBad = GlobalData.DataSet(iDS).Measures.ChannelFlag; + ChannelFlagSelectionBad(MouseSelection) = -1; + jItem = JMenuItem('Mark selected as bad', IconLoader.ICON_BAD); + jItem.setAccelerator(KeyStroke.getKeyStroke(int32(KeyEvent.VK_DELETE), 0)); % DEL + set(jItem, 'ActionPerformedCallback', @(h, ev)panel_channelEditor('UpdateChannelFlag', ... + DataFile, 0, ChannelFlagSelectionBad)); + jMenuChannels.add(jItem); + % === RESET SELECTION === + jItem = JMenuItem('Reset selection', IconLoader.ICON_SURFACE); + jItem.setAccelerator(KeyStroke.getKeyStroke(int32(KeyEvent.VK_ESCAPE), 0)); % ESCAPE + set(jItem, 'ActionPerformedCallback', @(h, ev)bst_dataSetsManager('SetMouseSelectedChannels', ... + GlobalData.DataSet(iDS).ChannelFile, [])); + jMenuChannels.add(jItem); + end + % Separator if previous items + if (jMenuChannels.getItemCount() > 0) + jMenuChannels.addSeparator(); + end + + % ==== CHANNEL FLAG ===== + if ~isempty(DataFile) && isMarkers + % ==== MARK ALL CHANNELS AS GOOD ==== + ChannelFlagGood = ones(size(GlobalData.DataSet(iDS).Measures.ChannelFlag)); + jItem = JMenuItem('Mark all channels as good', IconLoader.ICON_GOOD); + set(jItem, 'ActionPerformedCallback', ... + @(h, ev)panel_channelEditor('UpdateChannelFlag', GlobalData.DataSet(iDS).DataFile, ... + 0, ChannelFlagGood)); + jMenuChannels.add(jItem); + % ==== EDIT CHANNEL FLAG ==== + jItem = JMenuItem('Edit good/bad channels...', IconLoader.ICON_GOODBAD); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_editChannelFlag(DataFile)); + jMenuChannels.add(jItem); + end + % Separator if previous items + if (jMenuChannels.getItemCount() > 0) + jMenuChannels.addSeparator(); + end + + % ==== View Sensors ==== + % Not for 2DLayout + if ~strcmpi(GlobalData.DataSet(iDS).Figure(iFig).Id.SubType, '2DLayout') + % Menu "View sensors" + jItem = JCheckBoxMenuItem('Display sensors', IconLoader.ICON_CHANNEL, isMarkers); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_E, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)ViewSensors(hFig, ~isMarkers, [])); + jMenuChannels.add(jItem); + % Menu "View sensor labels" + isLabels = ~isempty(GlobalData.DataSet(iDS).Figure(iFig).Handles.hSensorLabels); + jItem = JCheckBoxMenuItem('Display labels', IconLoader.ICON_CHANNEL_LABEL, isLabels); + set(jItem, 'ActionPerformedCallback', @(h,ev)ViewSensors(hFig, [], ~isLabels)); + jMenuChannels.add(jItem); + else + % Menu "View sensor labels" + isLabels = ~isempty(GlobalData.DataSet(iDS).Figure(iFig).Handles.hSensorLabels); + if isLabels + isLabelsVisible = strcmpi(get(GlobalData.DataSet(iDS).Figure(iFig).Handles.hSensorLabels(1), 'Visible'), 'on'); + jItem = JCheckBoxMenuItem('Display labels', IconLoader.ICON_CHANNEL_LABEL, isLabelsVisible); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_E, KeyEvent.CTRL_MASK)); + if isLabelsVisible + targetVisible = 'off'; + else + targetVisible = 'on'; + end + set(jItem, 'ActionPerformedCallback', @(h,ev)set(GlobalData.DataSet(iDS).Figure(iFig).Handles.hSensorLabels, 'Visible', targetVisible)); + jMenuChannels.add(jItem); + end + end + jPopup.add(jMenuChannels); + end + + + % ==== Menu colormaps ==== + % Get list of displayed data types + listTypes = gui_figuresManager('GetDisplayedDataTypes', hFig); + % Menu "Recordings (EEG/MEG) colormap" + if any(ismember({'data','eeg','meg'}, lower(listTypes))) && ~strcmpi(Modality, 'Residuals') + ColormapType = bst_colormaps('GetColormapType', Modality); + jMenuColormapsData = JMenu(['Colormap (' lower(ColormapType) ')']); + jMenuColormapsData.setIcon(IconLoader.ICON_COLORMAP_RECORDINGS); + set(jMenuColormapsData, 'MenuSelectedCallback', @(h,ev)bst_colormaps('CreateColormapMenu', ev.getSource(), ColormapType)); + jPopup.add(jMenuColormapsData); + end + % Menu "Sources colormap" + if ismember('Source', listTypes) || strcmpi(Modality, 'Residuals') + jMenuColormapsSource = JMenu('Colormap (sources)'); + jMenuColormapsSource.setIcon(IconLoader.ICON_COLORMAP_SOURCES); + set(jMenuColormapsSource, 'MenuSelectedCallback', @(h,ev)bst_colormaps('CreateColormapMenu', ev.getSource(), 'Source')); + jPopup.add(jMenuColormapsSource); + end + % Menu "Stat colormap" + if ismember('Stat', listTypes) + jMenuColormapsStat = JMenu('Colormap (stat)'); + jMenuColormapsStat.setIcon(IconLoader.ICON_COLORMAP_RECORDINGS); + set(jMenuColormapsStat, 'MenuSelectedCallback', @(h,ev)bst_colormaps('CreateColormapMenu', ev.getSource(), 'Stat')); + jPopup.add(jMenuColormapsStat); + end + % Menu "Anatomy colormap" + if ismember('Anatomy', listTypes) + jMenuColormapsSource = JMenu('Colormap (anatomy)'); + jMenuColormapsSource.setIcon(IconLoader.ICON_COLORMAP_ANATOMY); + set(jMenuColormapsSource, 'MenuSelectedCallback', @(h,ev)bst_colormaps('CreateColormapMenu', ev.getSource(), 'Anatomy')); + jPopup.add(jMenuColormapsSource); + end + + % ==== Maximum Intensity Projection ==== + if ismember('Anatomy', listTypes) + jMenuMIP = JMenu('Maximum Intensity Power'); + jMenuMIP.setIcon(IconLoader.ICON_RESULTS); + % MIP: Anatomy + jItem = JCheckBoxMenuItem('MIP: Anatomy', GlobalData.MIP.isMipAnatomy); + set(jItem, 'ActionPerformedCallback', @(h,ev)MipAnatomy_Callback(hFig,ev)); + jMenuMIP.add(jItem); + jPopup.add(jMenuMIP); + % MIP: Functional + if ismember('Source', listTypes) + jItem = JCheckBoxMenuItem('MIP: Functional', GlobalData.MIP.isMipFunctional); + set(jItem, 'ActionPerformedCallback', @(h,ev)MipFunctional_Callback(hFig,ev)); + jMenuMIP.add(jItem); + end + jPopup.add(jMenuMIP); + end + + % ==== Navigation submenu ==== + if ~isempty(DataFile) && ~isempty(DataFileFull) + jMenuNavigator = JMenu('Navigator'); + jMenuNavigator.setIcon(IconLoader.ICON_NEXT_SUBJECT); + bst_navigator('CreateNavigatorMenu', jMenuNavigator); + jPopup.add(jMenuNavigator); + jPopup.addSeparator(); + end + + % ==== Menu SNAPSHOT ==== + jMenuSave = JMenu('Snapshot'); + jMenuSave.setIcon(IconLoader.ICON_SNAPSHOT); + % Default output dir + LastUsedDirs = bst_getContext('LastUsedDirs'); + DefaultOutputDir = LastUsedDirs.Export; + % Is there a time window defined + isTime = ~isempty(GlobalData) && ~isempty(GlobalData.MaxTimeWindow.Time) ... + && ~isempty(GlobalData.UserTimeWindow.CurrentTime) && ~isempty(GlobalData.UserTimeWindow.Time) ... + && ~isempty(DataFileFull); + % === SAVE AS IMAGE === + jItem = JMenuItem('Save as image', IconLoader.ICON_SAVE); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_I, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_image(hFig)); + jMenuSave.add(jItem); + % === SAVE AS FIGURE === + jItem = JMenuItem('Save as Matlab figure', IconLoader.ICON_SAVE); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_matlab(hFig)); + jMenuSave.add(jItem); + % === MOVIES === + % WARNING: Windows ONLY (for the moment) + % And NOT for 2DLayout figures + if ispc && ~strcmpi(GlobalData.DataSet(iDS).Figure(iFig).Id.SubType, '2DLayout') + % Separator + jMenuSave.addSeparator(); + % === MOVIE (TIME) === + if isTime + jItem = JMenuItem('Movie (time)', IconLoader.ICON_MOVIE); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_movie(hFig, DefaultOutputDir, 'time')); + jMenuSave.add(jItem); + end + % If not topography + if ~strcmpi(FigureType, 'Topography') + % === MOVIE (HORIZONTAL) === + jItem = JMenuItem('Movie (horizontal)', IconLoader.ICON_MOVIE); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_movie(hFig, DefaultOutputDir, 'horizontal')); + jMenuSave.add(jItem); + % === MOVIE (VERTICAL) === + jItem = JMenuItem('Movie (vertical)', IconLoader.ICON_MOVIE); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_movie(hFig, DefaultOutputDir, 'vertical')); + jMenuSave.add(jItem); + end + end + % === CONTACT SHEETS === + % If time, and if not 2DLayout + if isTime && ~strcmpi(GlobalData.DataSet(iDS).Figure(iFig).Id.SubType, '2DLayout') + % Separator + jMenuSave.addSeparator(); + % === CONTACT SHEET (TIME) === + jItem = JMenuItem('Contact sheet (time)', IconLoader.ICON_CONTACTSHEET); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_contactSheet(hFig, DefaultOutputDir)); + jMenuSave.add(jItem); + end + % === CONTACT SHEET / SLICES === + if ismember('Anatomy', listTypes) + % === CONTACT SHEET (AXIAL) === + jItem = JMenuItem('Contact sheet (axial)', IconLoader.ICON_CONTACTSHEET); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_mriSlices(hFig, 'z', DefaultOutputDir)); + jMenuSave.add(jItem); + % === CONTACT SHEET (CORONAL) === + jItem = JMenuItem('Contact sheet (coronal)', IconLoader.ICON_CONTACTSHEET); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_mriSlices(hFig, 'y', DefaultOutputDir)); + jMenuSave.add(jItem); + % === CONTACT SHEET (SAGITTAL) === + jItem = JMenuItem('Contact sheet (sagittal)', IconLoader.ICON_CONTACTSHEET); + set(jItem, 'ActionPerformedCallback', @(h,ev)out_figure_mriSlices(hFig, 'x', DefaultOutputDir)); + jMenuSave.add(jItem); + end + jPopup.add(jMenuSave); + + % ==== Menu "Figure" ==== + jMenuFigure = JMenu('Figure'); + jMenuFigure.setIcon(IconLoader.ICON_LAYOUT_SHOWALL); + % Show axes + isAxis = ~isempty(findobj(hFig, 'Tag', 'AxisXYZ')); + jItem = JCheckBoxMenuItem('View axis', IconLoader.ICON_AXES, isAxis); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_A, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)ViewAxis(hFig, ~isAxis)); + jMenuFigure.add(jItem); + % Show Head points + isHeadPoints = ~isempty(GlobalData.DataSet(iDS).HeadPoints) && ~isempty(GlobalData.DataSet(iDS).HeadPoints.Loc); + if isHeadPoints + % Are head points visible + hHeadPointsMarkers = findobj(GlobalData.DataSet(iDS).Figure(iFig).hFigure, 'Tag', 'HeadPointsMarkers'); + isVisible = ~isempty(hHeadPointsMarkers) && strcmpi(get(hHeadPointsMarkers, 'Visible'), 'on'); + jItem = JCheckBoxMenuItem('View head points', IconLoader.ICON_CHANNEL, isVisible); + set(jItem, 'ActionPerformedCallback', @(h,ev)ViewHeadPoints(hFig, ~isVisible)); + jMenuFigure.add(jItem); + end + jMenuFigure.addSeparator(); + % Change background color + jItem = JMenuItem('Change background color', IconLoader.ICON_COLOR_SELECTION); + set(jItem, 'ActionPerformedCallback', @(h,ev)ChangeBackgroundColor(hFig)); + jMenuFigure.add(jItem); + jMenuFigure.addSeparator(); + % Show Matlab controls + isMatlabCtrl = ~strcmpi(get(hFig, 'MenuBar'), 'none') && ~strcmpi(get(hFig, 'ToolBar'), 'none'); + jItem = JCheckBoxMenuItem('Matlab controls', IconLoader.ICON_MATLAB_CONTROLS, isMatlabCtrl); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('ShowMatlabControls', hFig, ~isMatlabCtrl)); + jMenuFigure.add(jItem); + % Show plot edit toolbar + isPlotEditToolbar = getappdata(hFig, 'isPlotEditToolbar'); + jItem = JCheckBoxMenuItem('Plot edit toolbar', IconLoader.ICON_PLOTEDIT, isPlotEditToolbar); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('TogglePlotEditToolbar', hFig)); + jMenuFigure.add(jItem); + % Dock figure + isDocked = strcmpi(get(hFig, 'WindowStyle'), 'docked'); + jItem = JCheckBoxMenuItem('Dock figure', IconLoader.ICON_DOCK, isDocked); + jItem.setAccelerator(KeyStroke.getKeyStroke(KeyEvent.VK_D, KeyEvent.CTRL_MASK)); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('DockFigure', hFig, ~isDocked)); + jMenuFigure.add(jItem); + jPopup.add(jMenuFigure); + + % ==== Menu "Views" ==== + % Not for Topography + if ~strcmpi(FigureType, 'Topography') + jMenuView = JMenu('Views'); + jMenuView.setIcon(IconLoader.ICON_AXES); + % Check if it is a realignment figure + isAlignFigure = ~isempty(findobj(hFig, 'Tag', 'AlignToolbar')); + % STANDARD VIEWS + % Create items + jItemViewLeft = JMenuItem('Left'); + jItemViewBottom = JMenuItem('Bottom'); + jItemViewRight = JMenuItem('Right'); + jItemViewFront = JMenuItem('Front'); + jItemViewTop = JMenuItem('Top'); + jItemViewBack = JMenuItem('Back'); + % Callbacks + set(jItemViewLeft, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'left'})); + set(jItemViewBottom, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'bottom'})); + set(jItemViewRight, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'right'})); + set(jItemViewFront, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'front'})); + set(jItemViewTop, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'top'})); + set(jItemViewBack, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'back'})); + % Keyboard shortcuts + jItemViewLeft.setAccelerator( KeyStroke.getKeyStroke('1')); + jItemViewBottom.setAccelerator(KeyStroke.getKeyStroke('2')); + jItemViewRight.setAccelerator( KeyStroke.getKeyStroke('3')); + jItemViewFront.setAccelerator( KeyStroke.getKeyStroke('4')); + jItemViewTop.setAccelerator( KeyStroke.getKeyStroke('5')); + jItemViewBack.setAccelerator( KeyStroke.getKeyStroke('6')); + % Add items to menu + jMenuView.add(jItemViewLeft); + jMenuView.add(jItemViewBottom); + jMenuView.add(jItemViewRight); + jMenuView.add(jItemViewFront); + jMenuView.add(jItemViewTop); + jMenuView.add(jItemViewBack); + + % MULTIPLE VIEWS + if ~isAlignFigure + % Create items + jItemViewLR = JMenuItem('[Left, Right]'); + jItemViewTB = JMenuItem('[Top, Bottom]'); + jItemViewFB = JMenuItem('[Front, Back]'); + jItemViewLTR = JMenuItem('[Left, Top, Right]'); + % Callbacks + set(jItemViewLR, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'left', 'right'})); + set(jItemViewTB, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'top', 'bottom'})); + set(jItemViewFB, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'front','back'})); + set(jItemViewLTR, 'ActionPerformedCallback', @(h,ev)SetStandardView(hFig, {'left', 'top', 'right'})); + % Keyboard shortcuts + jItemViewLR.setAccelerator( KeyStroke.getKeyStroke('7')); + jItemViewTB.setAccelerator( KeyStroke.getKeyStroke('8')); + jItemViewFB.setAccelerator( KeyStroke.getKeyStroke('9')); + jItemViewLTR.setAccelerator( KeyStroke.getKeyStroke('0')); + % Add items to menu + jMenuView.add(jItemViewLR); + jMenuView.add(jItemViewTB); + jMenuView.add(jItemViewFB); + jMenuView.add(jItemViewLTR); + + % SET SAME VIEW FOR ALL FIGURES + jMenuView.addSeparator(); + jItem = JMenuItem('Apply this view to all figures'); + jItem.setAccelerator(KeyStroke.getKeyStroke('=')); + set(jItem, 'ActionPerformedCallback', @(h,ev)ApplyViewToAllFigures(hFig)); + jMenuView.add(jItem); + + % CLONE FIGURE + jMenuView.addSeparator(); + jItem = JMenuItem('Clone figure'); + set(jItem, 'ActionPerformedCallback', @(h,ev)gui_figuresManager('CloneFigure', hFig)); + jMenuView.add(jItem); + end + jPopup.add(jMenuView); + end + + % ==== Display menu ==== + gui_showPopup(jPopup); + +end + + +%% ===== FIGURE CONFIGURATION FUNCTIONS ===== +% CHECKBOX MIP ANATOMY +function MipAnatomy_Callback(hFig, ev) + global GlobalData; + GlobalData.MIP.isMipAnatomy = ev.getSource().isSelected(); + UpdateMriDisplay(hFig); +end +% CHECKBOX MIP FUNCTIONAL +function MipFunctional_Callback(hFig, ev) + global GlobalData; + GlobalData.MIP.isMipFunctional = ev.getSource().isSelected(); + UpdateMriDisplay(hFig); +end + +% %% ===== COLORBAR HELP MESSAGE ===== +% function ColorbarHelpMessage(hFig) +% % Get colorbar +% hColorbar = findobj(hFig, 'Tag', 'Colorbar'); +% % If a colorbar is found +% if ~isempty(hColorbar) && strcmpi(get(hColorbar,'Visible'), 'on') +% % Get mouse position and colorbar position +% barPos = get(hColorbar, 'Position'); +% curptFigure = get(hFig, 'CurrentPoint'); +% % Get previous legend +% hLabel = findobj(hFig, 'Tag', 'ColorbarHelpMsg'); +% % Check if mouse over the colorbar +% if (curptFigure(1) >= barPos(1)) +% % Display the help text for colorbar (only if not displayed yet) +% if isempty(hLabel) +% hLabel = uicontrol('Style', 'text', ... +% 'String', ['Click and move mouse to adjust colormap:' 10 'Horizontal: contrast, vertical:brightness'], ... +% 'Units', 'Pixels', ... +% 'Position', [6 0 220 28], ... +% 'HorizontalAlignment', 'left', ... +% 'FontUnits', 'points', ... +% 'FontSize', 7.5, ... +% 'ForegroundColor', [.3 1 .3], ... +% 'BackgroundColor', [0 0 0], ... +% 'Tag', 'ColorbarHelpMsg', ... +% 'Parent', hFig); +% end +% elseif ~isempty(hLabel) +% delete(hLabel); +% end +% end +% end + + +%% ============================================================================================== +% ====== SURFACES ============================================================================== +% ============================================================================================== +%% ===== GET SELECTED CHANNELS INDICES AND LOCATION ===== +function [SelectedChannels, PChanLocs, PChanOrient] = GetSelectedChannels(iDS, iFig) + global GlobalData; + PChanLocs = []; + PChanOrient = []; + Channel = GlobalData.DataSet(iDS).Channel; + + % Update selected channels + UpdateSelectedChannels(iDS, iFig); + % Get selected channels indices + SelectedChannels = GlobalData.DataSet(iDS).Figure(iFig).SelectedChannels; + % No channel available or locations not requested : return + if isempty(SelectedChannels) + return; + end + + % === CHANNELS LOCATIONS === + % If modality and selected channels are defined + if (nargout >= 2) + % Get channel locations + chanlocs = [Channel(SelectedChannels).Loc]'; + if isempty(chanlocs) + return + end + % Keep only one kind of sensors locations + nLocs = round(length(chanlocs) / length(SelectedChannels)); + chanlocs = chanlocs(1:nLocs:end,:); + % Check intergrity of Channel structure + if size(chanlocs,1) ~= length(SelectedChannels) + bst_error('Channel locations do not match the number of channels in Channel structure.','Perverted Channel structure.'); + return + end + % Get selected channels locations + PChanLocs = chanlocs; + end + + % === CHANNELS ORIENTATIONS === + if (nargout >= 3) + % Get channel locations + chanorient = [Channel(SelectedChannels).Orient]'; + if isempty(chanorient) + return + end + % Keep only one kind of sensors locations + nOrient = round(length(chanorient) / length(SelectedChannels)); + chanorient = chanorient(1:nOrient:end,:); + % Check intergrity of Channel structure + if size(chanorient,1) ~= length(SelectedChannels) + bst_error('Channel orientations do not match the number of channels in Channel structure.','Perverted Channel structure.'); + return + end + % Get selected channels locations + PChanOrient = chanorient; + end +end + + +%% ===== UPDATE SELECTED CHANNELS ===== +function UpdateSelectedChannels(iDS, iFig) + global GlobalData; + Channel = GlobalData.DataSet(iDS).Channel; + hFig = GlobalData.DataSet(iDS).Figure(iFig).hFigure; + Modality = GlobalData.DataSet(iDS).Figure(iFig).Id.Modality; + + % If Modality of the window is not defined yet : select EEG or MEG + if isempty(Modality) + % Get the possible modalities for this figure + %AvailableModalities = getChannelModalities(Channel, ones(length(Channel), 1)); + AvailableModalities = getChannelModalities(Channel); + Modality = ''; + + % If some modality is defined for this figure + if ~isempty(AvailableModalities) + % If both EEG and MEG are available for this figure + if all(ismember({'MEG', 'EEG'}, AvailableModalities)) + % Ask the user which one to display : MEG or EEG + button = java_dialog('question', 'Please select a modality for this figure.', ... + 'Get available modalities', [], {'MEG', 'EEG'}, 'MEG'); + % If user did not answer : abort... + if isempty(button) + return + else + Modality = button; + end + % Else if only MEG is available : set figure modality to MEG + elseif ismember('MEG', AvailableModalities) + Modality = 'MEG'; + % Else if only EEG is available : set figure modality to EEG + elseif ismember('EEG', AvailableModalities) + Modality = 'EEG'; + end + end + % If no modality is available : return + if isempty(Modality) + return; + end + % Else set this modality as the new window modality + GlobalData.DataSet(iDS).Figure(iFig).Id.Modality = Modality; + % Add '/modality' at the end of the figure title + set(hFig, 'Name', [get(hFig, 'Name'), '/', Modality]); + end + + % CHANNEL FLAG + ChannelFlag = GlobalData.DataSet(iDS).Measures.ChannelFlag; + if isempty(ChannelFlag) + ChannelFlag = ones(length(Channel), 1); + end + % SELECTED CHANNELS + GlobalData.DataSet(iDS).Figure(iFig).SelectedChannels = good_channel(... + Channel, ChannelFlag, Modality); + +end + + + +%% ===== PLOT SURFACE ===== +% Convenient function to consistently plot surfaces. +% USAGE : [hFig,hs] = PlotSurface(hFig, faces, verts, cdata, dataCMap, transparency) +% Parameters : +% - hFig : figure handle to use +% - faces : the triangle listing (array) +% - verts : the corresponding vertices (array) +% - surfaceColor : color data used to display the surface itself (CData for each vertex, or a unique color for all vertices) +% - dataColormap : colormap used to display the data on the surface +% - transparency : surface transparency ([0,1]) +% Returns : +% - hFig : figure handle used +% - hs : handle to the surface +function varargout = PlotSurface( hFig, faces, verts, surfaceColor, transparency) %#ok + % Check inputs + if (nargin ~= 5) + error('Invalid call to PlotSurface'); + end + % If vertices are assumed transposed (if the assumption is wrong, will crash below anyway) + if (size(verts,2) > 3) + verts = verts'; + end + % If vertices are assumed transposed (if the assumption is wrong, will crash below anyway) + if (size(faces,2) > 3) + faces = faces'; + end + % Set figure as current + set(0, 'CurrentFigure', hFig); + + % If cdata is a single RGB color + if isequal(size(surfaceColor), [1,3]) + % Create patch + hs = patch('Faces', faces, ... + 'Vertices', verts,... + 'FaceColor', surfaceColor, ... + 'FaceAlpha', 1 - transparency, ... + 'AlphaDataMapping', 'none', ... + 'EdgeColor', 'none', ... + 'BackfaceLighting', 'lit'); + else + surfaceColor = blend_anatomy_data(ones(size(verts,1),1), ... % Curvature + surfaceColor, ... % Current density + NaN, ... % Limit value + 0, ... % Current density transparency + [], ... % Anatomy color + []); % Data colormap + % Create patch + hs = patch('Faces', faces, ... + 'Vertices', verts,... + 'FaceVertexCData', surfaceColor, ... + 'FaceColor', 'interp', ... + 'FaceAlpha', 'flat', ... + 'AlphaDataMapping', 'none', ... + 'EdgeColor', 'none', ... + 'BackfaceLighting', 'lit'); + end + + % Configure patch material + material([ 0.5 0.50 0.20 1.00 0.5 ]) + lighting phong + + % Set output variables + if(nargout>0), + varargout{1} = hFig; + varargout{2} = hs; + end +end + + +%% ===== PLOT SQUARE/CUT ===== +% USAGE: PlotSquareCut(hFig, TessInfo, dim, pos) +% PlotSquareCut(hFig) : Remove all square cuts displayed +function PlotSquareCut(hFig, TessInfo, dim, pos) + % Get figure description and MRI + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + % Delete the previous patch + delete(findobj(hFig, 'Tag', 'squareCut')); + if (nargin < 4) + return + end + hAxes = findobj(hFig, 'tag', 'Axes3D'); + % Get maximum dimensions (MRI size) + sMri = bst_dataSetsManager('GetMri', TessInfo.SurfaceFile); + mriSize = size(sMri.Cube); + voxSize = sMri.Voxsize; + + % Get locations of the slice + nbPts = 50; + baseVect = linspace(-.01, 1.01, nbPts); + switch(dim) + case 1 + X = ones(nbPts) .* (pos + 2) .* voxSize(1); + Y = meshgrid(baseVect) .* mriSize(2) .* voxSize(2); + Z = meshgrid(baseVect)' .* mriSize(3) .* voxSize(3); + surfColor = [1 .5 .5]; + case 2 + X = meshgrid(baseVect) .* mriSize(1) .* voxSize(1); + Y = ones(nbPts) .* (pos + 2) .* voxSize(2) + .1; + Z = meshgrid(baseVect)' .* mriSize(3) .* voxSize(3); + surfColor = [.5 1 .5]; + case 3 + X = meshgrid(baseVect) .* mriSize(1) .* voxSize(1); + Y = meshgrid(baseVect)' .* mriSize(2) .* voxSize(2); + Z = ones(nbPts) .* (pos + 2) .* voxSize(3) + .1; + surfColor = [.5 .5 1]; + end + + % === Switch coordinates from MRI-CS to SCS === + % Apply Rotation/Translation + XYZ = [reshape(X, 1, []); + reshape(Y, 1, []); + reshape(Z, 1, [])]; + XYZ = mri2scs(sMri, XYZ); + % Convert to milimeters + XYZ = XYZ ./ 1000; + + % === PLOT SURFACE === + % Plot new surface + hCut = surface('XData', reshape(XYZ(1,:),nbPts,nbPts), ... + 'YData', reshape(XYZ(2,:),nbPts,nbPts), ... + 'ZData', reshape(XYZ(3,:),nbPts,nbPts), ... + 'CData', ones(nbPts), ... + 'FaceColor', surfColor, ... + 'FaceAlpha', .3, ... + 'EdgeColor', 'none', ... + 'AmbientStrength', .5, ... + 'DiffuseStrength', .9, ... + 'SpecularStrength', .1, ... + 'Tag', 'squareCut', ... + 'Parent', hAxes); +end + + +%% ===== UPDATE MRI DISPLAY ===== +% USAGE: UpdateMriDisplay(hFig, dims, TessInfo, iTess) +% UpdateMriDisplay(hFig, dims) +% UpdateMriDisplay(hFig) +function UpdateMriDisplay(hFig, dims, TessInfo, iTess) + % Parse inputs + if (nargin < 4) + [sMri,TessInfo,iTess] = panel_surface('GetSurfaceMri', hFig); + end + if (nargin < 2) || isempty(dims) + dims = [1 2 3]; + end + % Get the slices that need to be redrawn + newPos = [NaN, NaN, NaN]; + newPos(dims) = TessInfo(iTess).CutsPosition(dims); + % Redraw the three slices + panel_surface('PlotMri', hFig, newPos); +end + + + +%% ===== UPDATE SURFACE COLOR ===== +% Compute color RGB values for each vertex of the surface, taking in account : +% - the surface color, +% - the surface curvature and curvature threshold, +% - the data matrix displayed over the surface (and the data threshold), +% - the data colormap : RGB values, normalized?, absolute values?, limits +% - the data transparency +% Parameters : +% - hFig : handle to a 3DViz figure +% - iTess : indice of the surface to update +function UpdateSurfaceColor(hFig, iTess) + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + % Ignore empty surfaces and MRI slices + if isempty(TessInfo(iTess).hPatch) || ~any(ishandle(TessInfo(iTess).hPatch)) + return + end + % Get best colormap to display data + if ~isempty(TessInfo(iTess).DataSource) && TessInfo(iTess).DataSource.isStat || TessInfo(iTess).DataSource.isZscore + sColormap = bst_colormaps('GetColormap', 'Stat'); + else + sColormap = bst_colormaps('GetColormap', TessInfo(iTess).DataSource.Type); + end + + % === BUILD VALUES === + % If there is no data overlay + if isempty(TessInfo(iTess).Data) + tmp = []; + else + tmp = TessInfo(iTess).Data; + % Apply data threshold + % PERCENT OF LOCAL MAX + % tmp(abs(TessInfo(iTess).Data) < TessInfo(iTess).DataThreshold * max(abs(TessInfo(iTess).Data))) = 0; + % PERCENT OF GLOBAL MAX + tmp(abs(TessInfo(iTess).Data) < TessInfo(iTess).DataIntThreshold * max(abs(TessInfo(iTess).DataLimitValue))) = 0; + % Cluster size using DataExtThreshold + % knd: to do DataExtThreshold + if TessInfo(iTess).DataExtThreshold > 0 + sSurf = bst_dataSetsManager('GetSurface', TessInfo(iTess).SurfaceFile); + tmp = cluster_threshold(tmp,TessInfo(iTess).DataExtThreshold,sSurf.VertConn,1,0); + end + if sColormap.isAbsoluteValues + tmp = abs(tmp); + end + end + + % === MRI === + if strcmpi(TessInfo(iTess).Name, 'Anatomy') + % Update display + UpdateMriDisplay(hFig, [], TessInfo, iTess); + + % === SURFACE === + else + % SHOW CURVATURE + if TessInfo(iTess).SurfShowCurvature + % Get surface + sSurf = bst_dataSetsManager('GetSurface', TessInfo(iTess).SurfaceFile); + % Apply threshold to curvature mapping + curvTmp = sSurf.Curvature; + curvTmp( sSurf.Curvature >= TessInfo(iTess).SurfCurvatureThreshold) = .2; + curvTmp( sSurf.Curvature < TessInfo(iTess).SurfCurvatureThreshold) = -.2; + % DO NOT SHOW CURVATURE + else + % Set Curvature = 1 for all the vertices + curvTmp = ones(TessInfo(iTess).nVertices, 1); + end + + % Compute RGB values + FaceVertexCdata = blend_anatomy_data(curvTmp, ... % Curvature + tmp, ... % Current density + TessInfo(iTess).DataLimitValue, ... % Limit value + TessInfo(iTess).DataAlpha,... % Current density transparency + TessInfo(iTess).AnatomyColor([1,end], :), ... % Anatomy color + sColormap.CMap); % Data colormap + % Edge display : on/off + if ~TessInfo(iTess).SurfShowEdges + EdgeColor = 'none'; + else + EdgeColor = [0 .8 0]; + end + + set(TessInfo(iTess).hPatch, 'FaceVertexCdata', FaceVertexCdata, ... + 'FaceColor', 'interp', ... + 'EdgeColor', EdgeColor); + end +end + + +%% ===== SMOOTH SURFACE CALLBACK ===== +function SmoothSurface(hFig, iTess, smoothValue) + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + % Ignore MRI slices + if strcmpi(TessInfo(iTess).Name, 'Anatomy') + return + end + % Get surfaces vertices + sSurf = bst_dataSetsManager('GetSurface', TessInfo(iTess).SurfaceFile); + % If smoothValue is null: restore initial vertices + if (smoothValue == 0) + set(TessInfo(iTess).hPatch, 'Vertices', sSurf.Vertices); + return + end + + % ===== SMOOTH SURFACE ===== + gui_makeuswait('start'); + SurfSmoothIterations = 200 * smoothValue * length(sSurf.Vertices) / 100000; + % Calculate smoothed vertices locations + Vertices_sm = tess_smooth(sSurf.Vertices, ... + smoothValue, ... + SurfSmoothIterations, ... + sSurf.VertConn); + % Apply smoothed locations + set(TessInfo(iTess).hPatch, 'Vertices', Vertices_sm); + gui_makeuswait('stop'); +end + + + +%% ===== UPDATE SURFACE ALPHA ===== +% Update Alpha values for the given surface. +% Fields that are used from TessInfo: +% - SurfAlpha : Transparency of the surface patch +% - Resect : [x,y,z] doubles : Resect surfaces at these coordinates +% or string {'left', 'right', 'all'} : Display only selected part of the surface +function UpdateSurfaceAlpha(hFig, iTess) + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + Surface = TessInfo(iTess); + + % Ignore empty surfaces and MRI slices + if strcmpi(Surface.Name, 'Anatomy') || isempty(Surface.hPatch) || ~ishandle(Surface.hPatch) + return + end + % Apply current smoothing + SmoothSurface(hFig, iTess, Surface.SurfSmoothValue); + % Get surfaces vertices + Vertices = get(Surface.hPatch, 'Vertices'); + nbVertices = length(Vertices); + % Get vertex connectivity + sSurf = bst_dataSetsManager('GetSurface', TessInfo(iTess).SurfaceFile); + VertConn = sSurf.VertConn; + % Create Alpha data + FaceVertexAlphaData = ones(nbVertices,1) * (1-Surface.SurfAlpha); + + % ===== HEMISPHERE SELECTION (CHAR) ===== + if ischar(Surface.Resect) + % Assumptions for this process : + % - (Y,Z) plane represents more or less the inter-hemispheric plane + % - Y<0 : Right hemisphere + % - Y>0 : Left hemisphere + % - The two hemispheres are not connected (as they are extracted by BrainVisa) + % + % Get the start point + START_PERCENT = .3; + switch Surface.Resect + case 'right' + % Get maximal y value + [yMax, iHideVert] = max(Vertices(:,2)); + % Get all the vertices that are at more than START_PERCENT of the maximum + iNewVert = find(Vertices(:,2) > START_PERCENT * yMax)'; + iNewVert = setdiff(iNewVert, iHideVert); + case 'left' + % Get minimal y value + [yMin, iHideVert] = min(Vertices(:,2)); + % Get all the vertices that are at more than 40% of the maximum + iNewVert = find(Vertices(:,2) < START_PERCENT * yMin)'; + iNewVert = setdiff(iNewVert, iHideVert); + case 'none' + iHideVert = []; + end + + % If not displaying the whole brain + if ~isempty(iHideVert) + % Grow region until getting all the hemisphere + while ~isempty(iNewVert) + iHideVert = union(iHideVert, iNewVert); + iNewVert = patch_swell(iHideVert, VertConn); + end + % Check if we included all the brain (error...) + if length(iHideVert) >= .8 * nbVertices + %warning('The two hemispheres are connected. Cutting at y=0.'); + iHideVert = []; + % The two hemispheres are connected => Cut at y=0 + if strcmpi(Surface.Resect, 'left') + %iHideVert = find(Vertices(:,2) < 0); + Surface.Resect = [0 -0.0000001 0]; + else + %iHideVert = find(Vertices(:,2) > 0); + Surface.Resect = [0 0.0000001 0]; + end + end + end + % Update Alpha data + FaceVertexAlphaData(iHideVert) = 0; + end + + % ===== RESECT (DOUBLE) ===== + if isnumeric(Surface.Resect) && (length(Surface.Resect) == 3) && ~all(Surface.Resect == 0) + iNoModif = []; + % Get faces and vertices + Vertices = get(Surface.hPatch, 'Vertices'); + Faces = get(Surface.hPatch, 'Faces'); + % Compute mean and max of the coordinates + meanVertx = mean(Vertices, 1); + maxVertx = max(abs(Vertices), [], 1); + % Limit values + resectVal = Surface.Resect .* maxVertx + meanVertx; + % Get vertices that are kept in all the cuts + for iCoord = 1:3 + if Surface.Resect(iCoord) > 0 + iNoModif = union(iNoModif, find(Vertices(:,iCoord) < resectVal(iCoord))); + elseif Surface.Resect(iCoord) < 0 + iNoModif = union(iNoModif, find(Vertices(:,iCoord) > resectVal(iCoord))); + end + end + % Get all the faces that are partially visible + ShowVert = zeros(nbVertices,1); + ShowVert(iNoModif) = 1; + facesStatus = sum(ShowVert(Faces), 2); + iFacesVisible = find(facesStatus > 0); + + % Get the vertices of the faces that are partially visible + iVerticesVisible = Faces(iFacesVisible,:); + iVerticesVisible = unique(iVerticesVisible(:))'; + + % Get vertices to project + iVerticesToProject = [iVerticesVisible, patch_swell(iVerticesVisible, VertConn)]; + iVerticesToProject = setdiff(iVerticesToProject, iNoModif); + % If there are some vertices to project + if ~isempty(iVerticesToProject) + % === FIRST PROJECTION === + % For the projected vertices: get the distance from each cut + distToCut = abs(Vertices(iVerticesToProject, :) - repmat(resectVal, [length(iVerticesToProject), 1])); + % Set the distance to the cuts that are not required to infinite + distToCut(:,(Surface.Resect == 0)) = Inf; + % Get the closest cut + [minDist, closestCut] = min(distToCut, [], 2); + + % Project each vertex + Vertices(sub2ind(size(Vertices), iVerticesToProject, closestCut')) = resectVal(closestCut); + + % === SECOND PROJECTION === + % In the faces that have visible and invisible vertices: project the invisible vertices + % on the visible vertices + % + % Get the mixed faces (partially visible) + ShowVert = zeros(nbVertices,1); + ShowVert(iVerticesVisible) = 1; + facesStatus = sum(ShowVert(Faces), 2); + iFacesMixed = find((facesStatus > 0) & (facesStatus < 3)); + + % Get the + projectList = logical(ShowVert(Faces(iFacesMixed,:))); + for iFace = 1:length(iFacesMixed) + iVertVis = Faces(iFacesMixed(iFace), projectList(iFace,:)); + iVertHid = Faces(iFacesMixed(iFace), ~projectList(iFace,:)); + % Project hidden vertices on first visible vertex + Vertices(iVertHid, :) = repmat(Vertices(iVertVis(1), :), length(iVertHid), 1); + end + + % Update patch + set(Surface.hPatch, 'Vertices', Vertices); + end + % Hide some vertices + FaceVertexAlphaData(setdiff(1:nbVertices, iVerticesVisible)) = 0; + end + % Update surface + set(Surface.hPatch, 'FaceVertexAlphaData', FaceVertexAlphaData, ... + 'FaceAlpha', 'interp'); +end + + +%% ===== VIEW SENSORS ===== +%Display sensors markers and labels in a 3DViz figure. +% Usage: ViewSensors(hFig, isMarkers, isLabels) : Display selected channels of figure hFig +% ViewSensors(hFig, isMarkers, isLabels, Modality) : Display channels of target Modality in figure hFig +% Parameters : +% - hFig : target '3DViz' figure +% - isMarkers : Sensors markers status : {0 (hide), 1 (show), [] (ignore)} +% - isLabels : Sensors labels status : {0 (hide), 1 (show), [] (ignore)} +% - Modality : Sensor type to display ('EEG', 'MEG', ...) +function ViewSensors(hFig, isMarkers, isLabels, Modality) + global GlobalData; + % Parse inputs + if (nargin < 4) + Modality = ''; + end + % Get figure description + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(iDS) + return + end + PlotHandles = GlobalData.DataSet(iDS).Figure(iFig).Handles; + isTopography = strcmpi(get(hFig, 'Tag'), 'Topography'); + is2D = 0; + + % ===== MARKERS LOCATIONS ===== + % === TOPOGRAPHY === + if isTopography + % Markers locations where stored in the Handles structure while creating topography patch + if isempty(PlotHandles.MarkersLocs) + return + end + % Get a location to display the Markers + markersLocs = PlotHandles.MarkersLocs; + % Flag=1 if 2D display + is2D = ismember(GlobalData.DataSet(iDS).Figure(iFig).Id.SubType, {'2DDisc','2DSensorCap'}); + % Get selected channels + SelectedChannels = GlobalData.DataSet(iDS).Figure(iFig).SelectedChannels; + textLocs = markersLocs; + markersOrient = []; + % === 3DVIZ === + % Display selected channels + elseif isempty(Modality) + % Get selected channel indices and locations + [SelectedChannels, PChanLocs, PChanOrient] = GetSelectedChannels(iDS, iFig); + if isempty(SelectedChannels) + return + end + % Get locations to display the Markers + markersLocs = PChanLocs; + markersOrient = PChanOrient; + textLocs = markersLocs; + % Else : display sensors of the target modality + else + Channel = GlobalData.DataSet(iDS).Channel; + % Find sensors of the target modality, select and display them + % SelectedChannels = GetSelectedChannels(iDS, iFig); + % SelectedChannels = find(strcmpi({Channel.Type}, Modality)); + SelectedChannels = good_channel(Channel, [], Modality); + % If no channels for this modality + if isempty(SelectedChannels) + bst_error(['No "' Modality '" sensors in channel file: "' GlobalData.DataSet(iDS).ChannelFile '".'], 'View sensors', 0); + return + end + % VectorView306 / CTF: keep all the coils defintions + if ismember(Modality, {'Vectorview306', 'CTF'}) + markersLocs = cell2mat(cellfun(@(c)c(:,:), {Channel(SelectedChannels).Loc}, 'UniformOutput', 0))'; + textLocs = cell2mat(cellfun(@(c)c(:,1), {Channel(SelectedChannels).Loc}, 'UniformOutput', 0))'; + % Else: only keep the first location + else + markersLocs = cell2mat(cellfun(@(c)c(:,1), {Channel(SelectedChannels).Loc}, 'UniformOutput', 0))'; + textLocs = markersLocs; + end + % Markers orientations: only for MEG + if ismember(Modality, {'MEG', 'MEG GRAD', 'MEG MAG', 'Vectorview306', 'CTF'}) + markersOrient = cell2mat(cellfun(@(c)c(:,1), {Channel(SelectedChannels).Orient}, 'UniformOutput', 0))'; + else + markersOrient = []; + end + end + % Make sure that electrodes locations are in double precision + markersLocs = double(markersLocs); + markersOrient = double(markersOrient); + + % ===== DISPLAY MARKERS OBJECTS ===== + % Put focus on target figure +% figure(hFig); + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + % === SENSORS === + if ~isempty(isMarkers) + % Delete sensor markers + if ~isempty(PlotHandles.hSensorMarkers) && all(ishandle(PlotHandles.hSensorMarkers)) + delete(PlotHandles.hSensorMarkers); + delete(PlotHandles.hSensorOrient); + PlotHandles.hSensorMarkers = []; + PlotHandles.hSensorOrient = []; + end + + % Display sensors markers + if isMarkers + % Is display of a flat 2D topography map + if is2D + PlotHandles.hSensorMarkers = gui_plotSensors2D(hAxes, markersLocs); + % If VectorView306 + elseif strcmpi(Modality, 'Vectorview306') + [PlotHandles.hSensorMarkers, PlotHandles.hSensorOrient] = ... + gui_plotSensorsVectorview306(hAxes, markersLocs, markersOrient); + isLabels = 0; + % Display head points + ViewHeadPoints(hFig, 1); + % If CTF + elseif strcmpi(Modality, 'CTF') + [PlotHandles.hSensorMarkers, PlotHandles.hSensorOrient] = ... + gui_plotSensorsCTF(hAxes, markersLocs, markersOrient); + isLabels = 0; + % Display head points + ViewHeadPoints(hFig, 1); + % Define face and edge colors : + % If more than one patch : transparent sensor cap + elseif ~isempty(findobj(hAxes, 'type', 'patch')) || ~isempty(findobj(hAxes, 'type', 'surface')) + [PlotHandles.hSensorMarkers, PlotHandles.hSensorOrient] = ... + gui_plotSensorsNet(hAxes, markersLocs, 0, markersOrient); + % Else, sensor cap is the only patch => display its faces + else + [PlotHandles.hSensorMarkers, PlotHandles.hSensorOrient] = ... + gui_plotSensorsNet(hAxes, markersLocs, 1, markersOrient); + end + end + end + + % === LABELS === + if ~isempty(isLabels) + % Delete sensor labels + if ~isempty(PlotHandles.hSensorLabels) + delete(PlotHandles.hSensorLabels(ishandle(PlotHandles.hSensorLabels))); + PlotHandles.hSensorLabels = []; + end + % Display sensor labels + if isLabels + sensorNames = {GlobalData.DataSet(iDS).Channel.Name}'; + if ~isempty(sensorNames) + % Get the names of the seleected sensors + sensorNames = sensorNames(SelectedChannels); + PlotHandles.hSensorLabels = text(1.08*textLocs(:,1), 1.08*textLocs(:,2), 1.08*textLocs(:,3), ... + sensorNames, ... + 'Parent', hAxes, ... + 'HorizontalAlignment', 'center', ... + 'Fontsize', 10, ... + 'FontUnits', 'points', ... + 'FontWeight', 'normal', ... + 'Tag', 'SensorsLabels', ... + 'Color', [1,1,.2], ... + 'Interpreter', 'none'); + end + end + end + + GlobalData.DataSet(iDS).Figure(iFig).Handles = PlotHandles; + + % ===== Update MouseSelectedChannels ===== + bst_dataSetsManager('UpdateSelectionForFigure', iDS); +end + + + +%% ===== VIEW HEAD POINTS ===== +function ViewHeadPoints(hFig, isVisible) + global GlobalData; + % Get figure description + [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(iDS) + return + end + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + % If no head points are available: exit + if isempty(GlobalData.DataSet(iDS).HeadPoints) || ~isfield(GlobalData.DataSet(iDS).HeadPoints, 'Loc') || isempty(GlobalData.DataSet(iDS).HeadPoints.Loc) + return + end + HeadPoints = GlobalData.DataSet(iDS).HeadPoints; + % Else, get previous head points + hHeadPointsMarkers = findobj(hFig, 'Tag', 'HeadPointsMarkers'); + hHeadPointsLabels = findobj(hFig, 'Tag', 'HeadPointsLabels'); + % If head points graphic objects already exist: set the "Visible" property + if ~isempty(hHeadPointsMarkers) + if isVisible + set(hHeadPointsMarkers, 'Visible', 'on'); + set(hHeadPointsLabels, 'Visible', 'on'); + else + set(hHeadPointsMarkers, 'Visible', 'off'); + set(hHeadPointsLabels, 'Visible', 'off'); + end + % If head points objects were not created yet: create them + elseif isVisible + % Get digitized points locations + digLoc = double(HeadPoints.Loc)'; + % Display markers + hDigMark = line(digLoc(:,1), digLoc(:,2), digLoc(:,3), ... + 'Parent', hAxes, ... + 'LineWidth', 2, ... + 'LineStyle', 'none', ... + 'MarkerFaceColor', [.3 1 .3], ... + 'MarkerEdgeColor', [.4 .7 .4], ... + 'MarkerSize', 6, ... + 'Marker', 'o', ... + 'Tag', 'HeadPointsMarkers'); + % Prepare display names + digNames = cell(size(HeadPoints.Label)); + for i = 1:length(HeadPoints.Label) + switch upper(HeadPoints.Type{i}) + case 'CARDINAL' + digNames{i} = HeadPoints.Label{i}; +% case 'EXTRA' +% if isnumeric(HeadPoints.Label{i}) +% digNames{i} = num2str(HeadPoints.Label{i}); +% else +% digNames{i} = HeadPoints.Label{i}; +% end + otherwise + if isnumeric(HeadPoints.Label{i}) + digNames{i} = [HeadPoints.Type{i}, '-', num2str(HeadPoints.Label{i})]; + else + digNames{i} = [HeadPoints.Type{i}, '-', HeadPoints.Label{i}]; + end + end + end + % Only display the legends for points that are not "EXTRA" or "EEG" + iNotExtra = find(~strcmpi(HeadPoints.Type, 'EXTRA') & ~strcmpi(HeadPoints.Type, 'EEG')); + % Display labels + if ~isempty(iNotExtra) + hDigLabel = text(1.08*digLoc(iNotExtra,1), 1.08*digLoc(iNotExtra,2), 1.08*digLoc(iNotExtra,3), ... + digNames(iNotExtra)', ... + 'Parent', hAxes, ... + 'HorizontalAlignment', 'center', ... + 'Fontsize', 10, ... + 'FontUnits', 'points', ... + 'FontWeight', 'normal', ... + 'Tag', 'HeadPointsLabels', ... + 'Color', [1,1,.2], ... + 'Interpreter', 'none'); + end + end +end + + +%% ===== VIEW AXIS ===== +function ViewAxis(hFig, isVisible) + hAxes = findobj(hFig, 'Tag', 'Axes3D'); + if (nargin < 2) + isVisible = isempty(findobj(hAxes, 'Tag', 'AxisXYZ')); + end + if isVisible + line([0 0.15], [0 0], [0 0], 'Color', [1 0 0], 'Marker', '>', 'Parent', hAxes, 'Tag', 'AxisXYZ'); + line([0 0], [0 0.15], [0 0], 'Color', [0 1 0], 'Marker', '>', 'Parent', hAxes, 'Tag', 'AxisXYZ'); + line([0 0], [0 0], [0 0.15], 'Color', [0 0 1], 'Marker', '>', 'Parent', hAxes, 'Tag', 'AxisXYZ'); + text(0.151, 0, 0, 'X', 'Color', [1 0 0], 'Parent', hAxes, 'Tag', 'AxisXYZ'); + text(0, 0.151, 0, 'Y', 'Color', [0 1 0], 'Parent', hAxes, 'Tag', 'AxisXYZ'); + text(0, 0, 0.151, 'Z', 'Color', [0 0 1], 'Parent', hAxes, 'Tag', 'AxisXYZ'); + else + hAxisXYZ = findobj(hAxes, 'Tag', 'AxisXYZ'); + if ~isempty(hAxisXYZ) + delete(hAxisXYZ); + end + end +end + + +%% ===== CHANGE BACKGROUND COLOR ===== +function ChangeBackgroundColor(hFig) + % Use previous scout color + newColor = uisetcolor([0 0 0], 'Select scout color'); + % If no color was selected: exit + if (length(newColor) ~= 3) || all(newColor == [0 0 0]) + return + end + % Set background + set(hFig, 'Color', newColor); +end + + diff --git a/brainstorm3/toolbox/gui/panel_scouts.m b/brainstorm3/toolbox/gui/panel_scouts.m new file mode 100644 index 0000000..bc22807 --- /dev/null +++ b/brainstorm3/toolbox/gui/panel_scouts.m @@ -0,0 +1,2678 @@ +function varargout = panel_scouts(varargin) +% PANEL_SCOUTS: Create a panel to add/remove/edit scouts attached to a given 3DViz figure. +% +% USAGE: bstPanelNew = panel_scouts('CreatePanel') +% panel_scouts('UpdatePanel') +% panel_scouts('UpdateScoutsList', sScouts) +% panel_scouts('UpdateScoutProperties') +% panel_scouts('CurrentFigureChanged_Callback') +% panel_scouts('SetCurrentSurface', newSurfaceFile) +% sScouts = panel_scouts('GetScouts', iScouts) +% [sScouts, iScouts] = panel_scouts('GetScouts') +% [sScouts, iScouts] = panel_scouts('GetCurrentScouts') +% [sScouts, iScouts] = panel_scouts('GetScoutsWithSurface', SurfaceFile) +% [sScouts, iScouts] = panel_scouts('GetScoutsWithFigure', hFig) +% [sScouts, iScouts] = panel_scouts('GetSelectedScouts') +% [sScout, iScout] = panel_scouts('CreateNewScout', SurfaceFile, newVertices, newSeed) +% panel_scouts('SetSelectedScouts', iSelScouts) +% panel_scouts('SetSelectionState', isSelected) +% panel_scouts('SelectCorticalSpot', hFig) +% panel_scouts('StartNewScoutSurface') +% panel_scouts('StartNewScoutMri') +% panel_scouts('StartNewScoutMax') +% panel_scouts('EditExistingScoutSurface') +% panel_scouts('EditExistingScoutMri') +% panel_scouts('EditScoutLabel') +% panel_scouts('EditScoutsSize', action) +% panel_scouts('EditScoutsColor', newColor) +% panel_scouts('ScoutEditorInMri', ) +% panel_scouts('PlotAllScouts') +% panel_scouts('PlotScout', iScout) +% panel_scouts('RemoveScoutsFromFigure', hFig) +% panel_scouts('RemoveScouts', iScouts) : remove a list of scouts +% panel_scouts('RemoveScouts', ) : remove the scouts selected in the JList +% panel_scouts('RemoveUnusedScouts') +% panel_scouts('JoinScouts') +% panel_scouts('UpdateScoutsVertices', SurfaceFile) +% panel_scouts('SaveScouts') +% panel_scouts('LoadScouts') +% panel_scouts('ForwardModelForScout') +% panel_scouts('ViewInMriViewer') +% ColorTable = panel_scouts('GetScoutsColorTable') +% ScoutsOptions = panel_scouts('GetScoutDisplayType') + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CREATE PANEL ===== +function bstPanelNew = CreatePanel() %#ok + panelName = 'Scout'; + % Java initializations + import java.awt.*; + import javax.swing.*; + import org.brainstorm.icon.IconLoader; + import java.awt.event.KeyEvent; + + % CONSTANTS + DEFAULT_HEIGHT = 20; + HFILLED_WIDTH = 40; + BUTTON_SIZE_WIDTH = 26; + BUTTON_SIZE1_WIDTH = 22; + TOOLBUTTON_SIZE = Dimension(28,24); + CHECKBOX_MARGIN = Insets(3,10,3,10); + jFontText = java.awt.Font('Dialog', java.awt.Font.PLAIN, 11); + % The the better JList height + JLIST_MAX_HEIGHT = 180; + + % Create tools panel + jPanelNew = JPanel(BorderLayout()); + + % ===== Create toolbar/menubar ===== + % Create menubar + jMenuBar = JMenuBar(); + % === TOOLBAR === + % Toolbar embedded in the menubar, to display correctly the first icons (non-menus) + jToolbarScouts = JToolBar('Edit scouts'); + jToolbarScouts.setBorderPainted(0); + jToolbarScouts.setFloatable(0); + jToolbarScouts.setRollover(1); + % Button "Add scout" + jButtonAddScout = JToggleButton(IconLoader.ICON_SCOUT_NEW); + jButtonAddScout.setPreferredSize(TOOLBUTTON_SIZE); + jButtonAddScout.setMaximumSize(TOOLBUTTON_SIZE); + jButtonAddScout.setFocusable(0); + jButtonAddScout.setToolTipText('Select point:

- If a scout selected in the list: point is added to the scout
- Else, a new scout is created.
') + set(jButtonAddScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@SetSelectionState, ev.getSource.isSelected())); + jToolbarScouts.add(jButtonAddScout); + % Button "Display scouts" + jButtonDisplayScout = JButton(IconLoader.ICON_TS_DISPLAY); + jButtonDisplayScout.setPreferredSize(TOOLBUTTON_SIZE); + jButtonDisplayScout.setMaximumSize(TOOLBUTTON_SIZE); + jButtonDisplayScout.setFocusable(0); + set(jButtonDisplayScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@DisplayScouts)); + jButtonDisplayScout.setToolTipText('Display scouts time series    [ENTER]'); + jToolbarScouts.add(jButtonDisplayScout); + jMenuBar.add(jToolbarScouts); + + % === MENU NEW === + jMenuNew = JMenu('New'); + jMenuNew.setIcon(IconLoader.ICON_MENU); + % Menu "New scout (design on surface)" + jButtonNewScoutSurface = JMenuItem('Define in 3D view', IconLoader.ICON_SCOUT_NEW); + set(jButtonNewScoutSurface, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@StartNewScoutSurface)); + jMenuNew.add(jButtonNewScoutSurface); + % Menu "New scout (design on MRI)" + jButtonNewScoutMri = JMenuItem('Define in MRI slices', IconLoader.ICON_EDIT_SCOUT_IN_MRI); + set(jButtonNewScoutMri, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@StartNewScoutMri)); + jMenuNew.add(jButtonNewScoutMri); + % Menu "New scout (SurfaceTiling)" + jButtonSurfaceTiling = JMenuItem('Surface tiling', IconLoader.ICON_EDIT_SCOUT_IN_MRI); + set(jButtonSurfaceTiling, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@SurfaceTiling)); + jMenuNew.add(jButtonSurfaceTiling); + % Separator + jMenuNew.addSeparator(); + % Menu "Find vertex with maximal value" + jButtonNewScoutMax = JMenuItem('Find maximal value', IconLoader.ICON_FIND_MAX); + set(jButtonNewScoutMax, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@StartNewScoutMax)); + jMenuNew.add(jButtonNewScoutMax); + jMenuBar.add(jMenuNew); + + % === MENU EDIT === + jMenuEdit = JMenu('Edit'); + jMenuEdit.setIcon(IconLoader.ICON_MENU); + % Button "Rename scout" + jButtonRenameScout = JMenuItem('Rename', IconLoader.ICON_EDIT); + set(jButtonRenameScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@EditScoutLabel)); + jMenuEdit.add(jButtonRenameScout); + % Button "Edit scout color" + jButtonScoutColor = JMenuItem('Set color', IconLoader.ICON_COLOR_SELECTION); + set(jButtonScoutColor, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@EditScoutsColor)); + jMenuEdit.add(jButtonScoutColor); + % Button "Remove scout" + jButtonRemoveScout = JMenuItem('Remove', IconLoader.ICON_DELETE); + set(jButtonRemoveScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@RemoveScouts)); + jMenuEdit.add(jButtonRemoveScout); + % Button "Join scouts" + jButtonJoinScouts = JMenuItem('Merge', IconLoader.ICON_FUSION); + set(jButtonJoinScouts, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@JoinScouts)); + jMenuEdit.add(jButtonJoinScouts); + % Button "Deselect all scouts" + jButtonDeselect = JMenuItem('Deselect all', IconLoader.ICON_RELOAD); + set(jButtonDeselect, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@SetSelectedScouts, 0)); + jMenuEdit.add(jButtonDeselect); + % Separator + jMenuEdit.addSeparator(); + % Button "Add vertices" + jButtonAddVertices = JMenuItem('Add vertices', IconLoader.ICON_SCOUT_NEW); + set(jButtonAddVertices, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@EditExistingScoutSurface)); + jMenuEdit.add(jButtonAddVertices); + % Menu "Edit in MRI" + jButtonEditInMri = JMenuItem('Edit in MRI', IconLoader.ICON_EDIT_SCOUT_IN_MRI); + set(jButtonEditInMri, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@EditExistingScoutMri)); + jMenuEdit.add(jButtonEditInMri); + % Separator + jMenuEdit.addSeparator(); + % Menu "Expand with correlation" + jButtonCorrelation = JMenuItem('Expand (correlation)', IconLoader.ICON_RESIZE); + jButtonCorrelation.setToolTipText('Expand scout based on correlation with other sources.'); + set(jButtonCorrelation, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ExpandWithCorrelation)); + jMenuEdit.add(jButtonCorrelation); + % Menu "Find vertex with maximal value" + jButtonSelectMaximum = JMenuItem('Find maximal value', IconLoader.ICON_FIND_MAX); + set(jButtonSelectMaximum, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@EditExistingScoutMax)); + jMenuEdit.add(jButtonSelectMaximum); + % Separator + jMenuEdit.addSeparator(); + % Menu "Remove scout vertices from surface" + jButtonRemoveScout = JMenuItem('Remove vertices', IconLoader.ICON_DELETE); + set(jButtonRemoveScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@RemoveScoutFromSurface)); + jMenuEdit.add(jButtonRemoveScout); + % Separator + jMenuEdit.addSeparator(); + % Menu "Forward model" + jButtonForwardModel = JMenuItem('Simulation', IconLoader.ICON_SCOUT_FORWARDMODEL); + jButtonForwardModel.setToolTipText(['Simulation: Forward model of selected scouts:
' ... + '
Simulate the scalp data that would be recorded if
' ... + 'only the selected cortex region was activated.

' ... + 'If no scout is selected: simulate recordings produced
' ... + 'by the activity of the whole cortex.
']); + set(jButtonForwardModel, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ForwardModelForScout)); + jMenuEdit.add(jButtonForwardModel); + jMenuBar.add(jMenuEdit); + + % === MENU VIEW === + jMenuView = JMenu('View'); + jMenuView.setIcon(IconLoader.ICON_MENU); + % === FUNCTIONAL DISPLAY === + % Menu "View time series" + jButtonDisplayScout = JMenuItem('View time series', IconLoader.ICON_TS_DISPLAY); + set(jButtonDisplayScout, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@DisplayScouts)); + jMenuView.add(jButtonDisplayScout); + % === ANTOMICAL DISPLAY === + % Separator + jMenuView.addSeparator(); + % Menu "View scout on cortex" + jButtonViewOnCortex = JMenuItem('View on cortex', IconLoader.ICON_CORTEX); + set(jButtonViewOnCortex, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ViewOnCortex)); + jMenuView.add(jButtonViewOnCortex); + % Menu "View in MRI" + jButtonViewInMriViewer = JMenuItem('View in MRIViewer', IconLoader.ICON_VIEW_SCOUT_IN_MRI); + set(jButtonViewInMriViewer, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ViewInMriViewer)); + jMenuView.add(jButtonViewInMriViewer); + % Menu "Center 3D MRI on scout" + jButtonCenterMri = JMenuItem('Center MRI on scout', IconLoader.ICON_VIEW_SCOUT_IN_MRI); + set(jButtonCenterMri, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@CenterMriOnScout)); + jMenuView.add(jButtonCenterMri); + + % === DISPLAY OPTIONS === + % Separator + jMenuView.addSeparator(); + % Menu "Scouts displayed in 3D" + jMenuSelAll = JMenu('3D display options...'); + jMenuSelAll.setIcon(IconLoader.ICON_PROPERTIES); + % Display ALL/SELECTED scouts + jButtonGroup = ButtonGroup(); + jRadioScoutViewSelected = JRadioButtonMenuItem('Show selected scouts'); + jRadioScoutViewAll = JRadioButtonMenuItem('Show all scouts', 1); + set(jRadioScoutViewSelected, 'ActionPerformedCallback', @(h,ev)UpdateScoutsDisplay()); + set(jRadioScoutViewAll, 'ActionPerformedCallback', @(h,ev)UpdateScoutsDisplay()); + jRadioScoutViewSelected.setMargin(CHECKBOX_MARGIN); + jRadioScoutViewAll.setMargin(CHECKBOX_MARGIN); + jButtonGroup.add(jRadioScoutViewSelected); + jButtonGroup.add(jRadioScoutViewAll); + jMenuSelAll.add(jRadioScoutViewSelected); + jMenuSelAll.add(jRadioScoutViewAll); + % Separator + jMenuSelAll.addSeparator(); + % SHOW/HIDE SCOUTS PATCHES OVER MRI SLICES + jCheckViewPatchesInMri = JCheckBoxMenuItem('Show scout patch (in MRI/3D figures)', 0); + set(jCheckViewPatchesInMri, 'ActionPerformedCallback', @(h,ev)UpdateScoutsDisplay()); + jCheckViewPatchesInMri.setMargin(CHECKBOX_MARGIN); + jMenuSelAll.add(jCheckViewPatchesInMri); + % LIMIT MRI SCOURCES TO SCOUTS + jCheckLimitMriSources = JCheckBoxMenuItem('Limit MRI sources to scouts', 1); + set(jCheckLimitMriSources, 'ActionPerformedCallback', @(h,ev)LimitMriSourcesToScouts()); + jCheckLimitMriSources.setMargin(CHECKBOX_MARGIN); + jMenuSelAll.add(jCheckLimitMriSources); + + jMenuView.add(jMenuSelAll); + % Menu "Time series options" + jMenuTsOptions = JMenu('Time series options...'); + jMenuTsOptions.setIcon(IconLoader.ICON_PROPERTIES); + % OPTIONS : Sources values (Relative / Absolute) + jButtonGroupValues = ButtonGroup(); + jRadioValuesRelative = JRadioButtonMenuItem('Relative values', 0); + jRadioValuesAbsolute = JRadioButtonMenuItem('Absolute values', 1); + jRadioValuesRelative.setMargin(CHECKBOX_MARGIN); + jRadioValuesAbsolute.setMargin(CHECKBOX_MARGIN); + jButtonGroupValues.add(jRadioValuesRelative); + jButtonGroupValues.add(jRadioValuesAbsolute); + jMenuTsOptions.add(jRadioValuesRelative); + jMenuTsOptions.add(jRadioValuesAbsolute); + % Separator + jMenuTsOptions.addSeparator(); + % OPTIONS : Sources type (Mean, max, all) + jButtonGroupType = ButtonGroup(); + jRadioTypeMean = JRadioButtonMenuItem('Sources: Mean', 1); + jRadioTypeMax = JRadioButtonMenuItem('Sources: Max', 0); + jRadioTypePower= JRadioButtonMenuItem('Sources: Power', 0); + jRadioTypeAll = JRadioButtonMenuItem('Sources: All', 0); + jRadioTypeMean.setMargin(CHECKBOX_MARGIN); + jRadioTypeMax.setMargin( CHECKBOX_MARGIN); + jRadioTypePower.setMargin( CHECKBOX_MARGIN); + jRadioTypeAll.setMargin( CHECKBOX_MARGIN); + jButtonGroupType.add(jRadioTypeMean); + jButtonGroupType.add(jRadioTypeMax); + jButtonGroupType.add(jRadioTypePower); + jButtonGroupType.add(jRadioTypeAll); + set(jRadioTypeMean, 'ActionPerformedCallback', @SourcesTypeChanged_Callback); + set(jRadioTypeMax, 'ActionPerformedCallback', @SourcesTypeChanged_Callback); + set(jRadioTypePower,'ActionPerformedCallback', @SourcesTypeChanged_Callback); + set(jRadioTypeAll, 'ActionPerformedCallback', @SourcesTypeChanged_Callback); + jMenuTsOptions.add(jRadioTypeMean); + jMenuTsOptions.add(jRadioTypeMax); + jMenuTsOptions.add(jRadioTypePower); + jMenuTsOptions.add(jRadioTypeAll); + jMenuView.add(jMenuTsOptions); + jMenuBar.add(jMenuView); + jPanelNew.add(jMenuBar, BorderLayout.NORTH); + + + % ===== PANEL MAIN ===== + jPanelMain = JPanel(); + jPanelMain.setLayout(BoxLayout(jPanelMain, BoxLayout.Y_AXIS)); + jPanelMain.setBorder(BorderFactory.createEmptyBorder(7,7,7,7)); +% jPanelMain.setPreferredSize(Dimension()); + % ===== FIRST PART ===== + jPanelFirstPart = JPanel(BorderLayout()); + jPanelFirstPart.setPreferredSize(Dimension(100,JLIST_MAX_HEIGHT)); + jPanelFirstPart.setMaximumSize(Dimension(500,JLIST_MAX_HEIGHT)); + % Vertical Toolbar + jToolbarScouts2 = JToolBar('Edit scouts'); + jToolbarScouts2.setBorderPainted(0); + jToolbarScouts2.setFloatable(0); + jToolbarScouts2.setRollover(1); + jToolbarScouts2.setOrientation(jToolbarScouts2.VERTICAL); + % Button "Load scouts file" + jButtonLoadScouts = JButton(IconLoader.ICON_FOLDER_OPEN); + jButtonLoadScouts.setPreferredSize(TOOLBUTTON_SIZE); + jButtonLoadScouts.setFocusable(0); + jButtonLoadScouts.setToolTipText('Load scouts file'); + set(jButtonLoadScouts, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@LoadScouts)); + jToolbarScouts2.add(jButtonLoadScouts); + % Button "Save scouts file" + jButtonSaveScouts = JButton(IconLoader.ICON_SAVE); + jButtonSaveScouts.setPreferredSize(TOOLBUTTON_SIZE); + jButtonSaveScouts.setFocusable(0); + jButtonSaveScouts.setToolTipText('Save scouts file'); + set(jButtonSaveScouts, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@SaveScouts)); + jToolbarScouts2.add(jButtonSaveScouts); + jPanelFirstPart.add(jToolbarScouts2, BorderLayout.EAST); + + % ===== Scouts list ===== + jPanelScoutsList = JPanel(BorderLayout); + jPanelScoutsList.setBorder(BorderFactory.createTitledBorder('Available scouts')); + jListScouts = JList(); + set(jListScouts, 'ValueChangedCallback', @ScoutsListValueChanged_Callback, ... + 'KeyTypedCallback', @ScoutsListKeyTyped_Callback, ... + 'MouseClickedCallback', @ScoutsListClick_Callback); + jPanelScrollList = JScrollPane(); + jPanelScrollList.getLayout.getViewport.setView(jListScouts); + jPanelScrollList.setBorder([]); + jPanelScoutsList.add(jPanelScrollList); + jPanelFirstPart.add(jPanelScoutsList, BorderLayout.CENTER); + jPanelMain.add(jPanelFirstPart); + + % ===== Scouts options panel ===== + jPanelScoutOptions = getRiverPanel([0,3], [0,5,10,3], 'Scout size'); + % OPTIONS : Scout size +% jPanelScoutOptions.add('br', JLabel('Size: ')); + + % OPTIONS : Scout growth + jButtonSizeShrink = JButton('<<'); + jButtonSizeShrink1 = JButton('<'); + jButtonSizeGrow1 = JButton('>'); + jButtonSizeGrow = JButton('>>'); + jButtonSizeGrow.setPreferredSize( Dimension(BUTTON_SIZE_WIDTH, DEFAULT_HEIGHT)); + jButtonSizeGrow1.setPreferredSize( Dimension(BUTTON_SIZE1_WIDTH, DEFAULT_HEIGHT)); + jButtonSizeShrink.setPreferredSize( Dimension(BUTTON_SIZE_WIDTH, DEFAULT_HEIGHT)); + jButtonSizeShrink1.setPreferredSize(Dimension(BUTTON_SIZE1_WIDTH, DEFAULT_HEIGHT)); + jButtonSizeGrow.setFont(jFontText); + jButtonSizeGrow1.setFont(jFontText); + jButtonSizeShrink.setFont(jFontText); + jButtonSizeShrink1.setFont(jFontText); + jButtonSizeGrow.setMargin( Insets(0,0,0,0)); + jButtonSizeGrow1.setMargin( Insets(0,0,0,0)); + jButtonSizeShrink.setMargin( Insets(0,0,0,0)); + jButtonSizeShrink1.setMargin(Insets(0,0,0,0)); + jButtonSizeGrow.setFocusPainted(0); + jButtonSizeGrow1.setFocusPainted(0); + jButtonSizeShrink.setFocusPainted(0); + jButtonSizeShrink1.setFocusPainted(0); + jButtonSizeGrow.setToolTipText( 'Increase scout size'); + jButtonSizeGrow1.setToolTipText( 'Increase scout size (only one vertex)'); + jButtonSizeShrink.setToolTipText( 'Decrease scout size'); + jButtonSizeShrink1.setToolTipText('Decrease scout size (only one vertex)'); + set(jButtonSizeGrow, 'ActionPerformedCallback', @(h,ev)EditScoutsSize('Grow')); + set(jButtonSizeGrow1, 'ActionPerformedCallback', @(h,ev)EditScoutsSize('Grow1')); + set(jButtonSizeShrink, 'ActionPerformedCallback', @(h,ev)EditScoutsSize('Shrink')); + set(jButtonSizeShrink1,'ActionPerformedCallback', @(h,ev)EditScoutsSize('Shrink1')); + jPanelScoutOptions.add(jButtonSizeShrink); + jPanelScoutOptions.add(jButtonSizeShrink1); + jPanelScoutOptions.add(jButtonSizeGrow1); + jPanelScoutOptions.add(jButtonSizeGrow); + + % Separator + jPanelScoutOptions.add(JLabel(' ')); + + % OPTIONS : Constrained to data + jToggleConstrained = JToggleButton('Constrained'); + jToggleConstrained.setPreferredSize(Dimension(HFILLED_WIDTH, DEFAULT_HEIGHT)); + jToggleConstrained.setFont(jFontText); + jToggleConstrained.setMargin(Insets(0,0,0,0)); + jToggleConstrained.setFocusPainted(0); + jToggleConstrained.setToolTipText('Constrain patch growth to vertices with data above threshold.'); + jPanelScoutOptions.add('tab hfill', jToggleConstrained); + + % OPTIONS : Scout size in vertices/area + jPanelScoutOptions.add('br', JLabel('Number of vertices:')); + jLabelScoutSize = JLabel(''); +% jLabelScoutSize.setPreferredSize(Dimension(HFILLED_WIDTH, DEFAULT_HEIGHT)); + jPanelScoutOptions.add('tab hfill', jLabelScoutSize); + + + panelPrefSize = jPanelScoutOptions.getPreferredSize(); + jPanelScoutOptions.setMaximumSize(Dimension(32000, panelPrefSize.getHeight())); + jPanelMain.add(jPanelScoutOptions); + + % ===== Display options panel ===== + jPanelDisplayOptions = getRiverPanel([0,1], [2,4,4,0], 'Display options'); + % OPTIONS : Overlay scouts/conditions + jPanelDisplayOptions.add(JLabel('Overlay:')); + jCheckOverlayScouts = JCheckBox('Scouts', 0); + jCheckOverlayConditions = JCheckBox('Conditions', 0); + jCheckOverlayScouts.setMargin(Insets(0,0,0,0)); + jCheckOverlayConditions.setMargin(Insets(0,0,0,0)); + set(jCheckOverlayScouts, 'ActionPerformedCallback', @OverlayTypeChanged_Callback); + set(jCheckOverlayConditions, 'ActionPerformedCallback', @OverlayTypeChanged_Callback); + jPanelDisplayOptions.add('tab', jCheckOverlayScouts); + jPanelDisplayOptions.add(jCheckOverlayConditions); + panelPrefSize = jPanelDisplayOptions.getPreferredSize(); + jPanelDisplayOptions.setMaximumSize(Dimension(32000, panelPrefSize.getHeight())); + jPanelMain.add(jPanelDisplayOptions); + + jPanelMain.add(Box.createVerticalGlue()); + jPanelMain.setPreferredSize(Dimension(200,280)); + jScrollMain = JScrollPane(jPanelMain); + jScrollMain.setBorder([]); + jPanelNew.add(jScrollMain); + + % Create the BstPanel object that is returned by the function + % => constructor BstPanel(jHandle, panelName, sControls) + bstPanelNew = BstPanel(panelName, ... + jPanelNew, ... + struct('jPanelScoutsList', jPanelScoutsList, ... + 'jToolbarScouts', jToolbarScouts, ... + 'jButtonAddScout', jButtonAddScout, ... + 'jPanelScoutOptions', jPanelScoutOptions, ... + 'jLabelScoutSize', jLabelScoutSize, ... + 'jPanelDisplayOptions', jPanelDisplayOptions, ... + 'jRadioScoutViewSelected', jRadioScoutViewSelected, ... + 'jRadioScoutViewAll', jRadioScoutViewAll, ... + 'jCheckViewPatchesInMri', jCheckViewPatchesInMri, ... + 'jCheckLimitMriSources', jCheckLimitMriSources, ... + 'jToggleConstrained', jToggleConstrained, ... + 'jRadioTypeMean', jRadioTypeMean, ... + 'jRadioTypeMax', jRadioTypeMax, ... + 'jRadioTypePower', jRadioTypePower, ... + 'jRadioTypeAll', jRadioTypeAll, ... + 'jRadioValuesRelative', jRadioValuesRelative, ... + 'jRadioValuesAbsolute', jRadioValuesAbsolute, ... + 'jCheckOverlayScouts', jCheckOverlayScouts, ... + 'jCheckOverlayConditions', jCheckOverlayConditions, ... + 'jListScouts', jListScouts)); + + +%% ===== INTERNAL CALLBACKS ===== + % Sources type changed + function SourcesTypeChanged_Callback(varargin) + % If 'ALL' sources type: disable overlays options + if jRadioTypeAll.isSelected() + jCheckOverlayScouts.setEnabled(0); + jCheckOverlayConditions.setEnabled(0); + jCheckOverlayScouts.setSelected(0); + jCheckOverlayConditions.setSelected(0); + else + jCheckOverlayScouts.setEnabled(1); + jCheckOverlayConditions.setEnabled(1); + end + end + + % Overlay type changed + function OverlayTypeChanged_Callback(varargin) + % If an overlay is activated : disable 'ALL' sources type + if jCheckOverlayScouts.isSelected() || jCheckOverlayConditions.isSelected() + jRadioTypeAll.setEnabled(0); + if jRadioTypeAll.isSelected() + jRadioTypeMean.setSelected(1); + end + else + jRadioTypeAll.setEnabled(1); + end + end + + function LimitMriSourcesToScouts() +% global GlobalData; + % Update selected scouts + UpdateScoutsDisplay(); +% % Get all other figures +% hAllFig = []; +% for i = 1:length(GlobalData.Scouts) +% hAllFig = [hAllFig, [GlobalData.Scouts(i).Handles.hFig]]; +% end +% % Update all other figures +% panel_surface('UpdateOverlayCubes', unique(hAllFig)); + + end +end + + + +%% ================================================================================= +% === CONTROLS CALLBACKS ========================================================= +% ================================================================================= +%% ===== VIEW ONLY SELECTED SCOUTS ? ===== +function status = isViewOnlySelectedScouts() + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + status = ctrl.jRadioScoutViewSelected.isSelected(); +end + +%% ===== LIST SELECTION CHANGED CALLBACK ===== +function ScoutsListValueChanged_Callback(h, ev) + if ~ev.getValueIsAdjusting() + % Update panel "Scouts" fields + UpdateScoutProperties(); + % Display/hide scouts + if isViewOnlySelectedScouts() + UpdateScoutsDisplay(); + end + end +end + +%% ===== LIST KEY TYPED CALLBACK ===== +function ScoutsListKeyTyped_Callback(h, ev) + switch(uint8(ev.getKeyChar())) + % DELETE + case ev.VK_DELETE + RemoveScouts(); + case ev.VK_ENTER + gui_viewResultsScouts(); + case uint8('+') + EditScoutsSize('Grow1'); + case uint8('-') + EditScoutsSize('Shrink1'); + case ev.VK_ESCAPE + SetSelectedScouts(0); + end +end + +%% ===== LIST CLICK CALLBACK ===== +function ScoutsListClick_Callback(h, ev) + % If DOUBLE CLICK + if (ev.getClickCount() == 2) + % Rename selection + EditScoutLabel(); + end +end + + +%% ================================================================================= +% === EXTERNAL PANEL CALLBACKS =================================================== +% ================================================================================= +%% ===== UPDATE CALLBACK ===== +function UpdatePanel() + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % Get current scouts + sScouts = GetCurrentScouts(); + % If a surface is available for current figure + if ~isempty(sScouts) + % Enable all panels + gui_setEnabledControls([ctrl.jPanelScoutsList, ... + ctrl.jPanelDisplayOptions, ctrl.jPanelScoutOptions], 1); + % Else : no figure associated with the panel : disable all controls + else + gui_setEnabledControls([ctrl.jPanelScoutsList, ... + ctrl.jPanelDisplayOptions, ctrl.jPanelScoutOptions], 0); + % Release "Add scouts" button + ctrl.jButtonAddScout.setSelected(0); + end + % Update scouts JList + UpdateScoutsList(sScouts); +end + + +%% ===== UPDATE SCOUTS LIST ===== +function UpdateScoutsList(sScouts) + % If scouts list was not defined : get it + if (nargin < 1) + sScouts = GetCurrentScouts(); + end + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % Create a new empty list + listModel = awtcreate('javax.swing.DefaultListModel'); + % Add an item in list for each scout found for target figure + for iScout = 1:length(sScouts) + awtinvoke(listModel, 'addElement(Ljava.lang.Object;)', sScouts(iScout).Label); + end + % Update list model + awtinvoke(ctrl.jListScouts, 'setModel(Ljavax.swing.ListModel;)', listModel); + % Reset Scout comments + awtinvoke(ctrl.jLabelScoutSize, 'setText(Ljava.lang.String;)', ''); +end + + + +%% ===== UPDATE SCOUT PROPERTIES DISPLAY ===== +function UpdateScoutProperties() + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % Get selected scouts + sScouts = GetSelectedScouts(); + % Add all the selected scouts to compute : area, nbVertices +% scoutArea = 0; + nbVertices = 0; + for i = 1:length(sScouts) + % NbVertices + nbVertices = nbVertices + length(sScouts(i).Vertices); + % Area +% if ~isempty(sScouts(i).Area) +% scoutArea = scoutArea + sScouts(i).Area; +% end + end + % Format results (NbVertices / Area) + if (nbVertices == 0) + strSize = ''; + else +% elseif (scoutArea == 0) + strSize = sprintf(' [ %d ]', nbVertices); +% else +% strSize = sprintf('%d (%0.2f cm2)', nbVertices, scoutArea); + end + % Update panel + ctrl.jLabelScoutSize.setText(strSize); +end + + +%% ===== CURRENT FIGURE CHANGED ===== +function CurrentFigureChanged_Callback(oldFig, hFig) + global GlobalData; + % === NO NEW FIGURE === + % If no figure is available + if isempty(hFig) || ~ishandle(hFig) + % Reset current surface + GlobalData.CurrentScoutsSurface = ''; + return + end + % Get cortex surface for new figure + [iNewSurf, TessInfo] = panel_surface('GetSurfaceCortex', hFig); + % If no cortex defined, try to find a MRI surface + if isempty(iNewSurf) + [sMri, TessInfo, iNewSurf] = panel_surface('GetSurfaceMri', hFig); + end + + % === COMPARE OLD AND NEW FIG === + if ~isempty(oldFig) && ishandle(oldFig) && (oldFig ~= hFig) + % Get surfaces for old figure + [iOldSurf, oldTessInfo] = panel_surface('GetSurfaceCortex', oldFig); + % If no cortex defined, try to find a MRI surface + if isempty(iOldSurf) + [sMri, TessInfo, iOldSurf] = panel_surface('GetSurfaceMri', oldFig); + end + % If cortical surface did not change: ignore callback + if ~isempty(iOldSurf) && ~isempty(iNewSurf) && io_compareFileNames(oldTessInfo(iOldSurf).SurfaceFile, TessInfo(iNewSurf).SurfaceFile); + return + end + end + + % === UPDATE CURRENT SURFACE === + newSurfaceFile = ''; + % If no cortex surface is found in target figure + if ~isempty(iNewSurf) + % If anatomy surface : use correspondant cortex surface instead + if strcmpi(TessInfo(iNewSurf).Name, 'Anatomy') + sSurfCortex = bst_getContext('SurfaceFileByType', TessInfo(iNewSurf).SurfaceFile, 'Cortex'); + if ~isempty(sSurfCortex) + newSurfaceFile = sSurfCortex.FileName; + end + else + newSurfaceFile = TessInfo(iNewSurf).SurfaceFile; + end + end + % Update current surface + SetCurrentSurface(newSurfaceFile); + + % === UPDATE SELECTED SCOUTS === + % Get current scouts (for new figure) + [sScouts, iScouts] = GetCurrentScouts(); + % If 3D figure: scouts have graphic handles + FigureId = getappdata(hFig, 'FigureId'); + switch(FigureId.Type) + case 'MriViewer' + iVisibleScouts = iScouts; + case '3DViz' + % Process each scout, to get if it is displayed in this figure + iVisibleScouts = []; + for i = 1:length(iScouts) + % Get handles corresponding to this figure + allhandles = [sScouts(i).Handles]; + iFigHandles = find([allhandles.hFig] == hFig); + % If scout is displayed in this figure, and is VISIBLE in this figure: add it to the visible list + if ~isempty(iFigHandles) && strcmpi(get(sScouts(i).Handles(iFigHandles).hScout, 'Visible'), 'on') + iVisibleScouts = [iVisibleScouts, iScouts(i)]; + end + end + otherwise + iVisibleScouts = []; + end + % Select visible scouts + SetSelectedScouts(iVisibleScouts); +end + + +%% ===== FOCUS CHANGED ====== +function FocusChangedCallback(isFocused) %#ok + if ~isFocused + SetSelectionState(0); + end +end + + +%% ===== SET CURRENT SURFACE ===== +function SetCurrentSurface(newSurfaceFile) + global GlobalData; + % Get previously selected surface + oldSurfaceFile = GlobalData.CurrentScoutsSurface; + % If SurfaceFile did not change did not change : return + if strcmpi(newSurfaceFile, oldSurfaceFile) + return; + end + % Update current surface file + GlobalData.CurrentScoutsSurface = newSurfaceFile; + % Update panel display + UpdatePanel(); +end + +%% ===== UPDATE CURRENT SURFACE ===== +function UpdateCurrentSurface() %#ok + curFig = gui_figuresManager('GetCurrentFigure', '3D'); + CurrentFigureChanged_Callback(curFig, curFig); +end + + +%% ===== GET ALL SCOUTS ===== +function [sScouts, iScouts] = GetScouts(iScouts) + global GlobalData; + if (nargin < 1) + sScouts = GlobalData.Scouts; + iScouts = 1:length(sScouts); + else + sScouts = GlobalData.Scouts(iScouts); + end +end + + +%% ===== GET CURRENT SCOUTS ===== +function [sScouts, iScouts] = GetCurrentScouts() + global GlobalData; + sScouts = []; + iScouts = []; + % If no surface is defined : do nothing + if isempty(GlobalData.CurrentScoutsSurface) + return + end + % If surface is defined : return scouts associated to this surface + [sScouts, iScouts] = GetScoutsWithSurface(GlobalData.CurrentScoutsSurface); +end + + +%% ===== GET SCOUTS WITH SURFACE===== +function [sScouts, iScouts] = GetScoutsWithSurface(SurfaceFile) + global GlobalData; + sScouts = []; + % If surface is defined : return scouts associated to this surface + iScouts = find(io_compareFileNames({GlobalData.Scouts.SurfaceFile}, SurfaceFile)); + if isempty(iScouts) + return + end + sScouts = GlobalData.Scouts(iScouts); +end + + +%% ===== GET SCOUTS WITH FIGURE ===== +function [sScouts, iScouts] = GetScoutsWithFigure(hFig) + global GlobalData; + sScouts = []; + iScouts = []; + if isempty(hFig) + return + end + % If figure is defined : return scouts associated to this figure + for i = 1:length(GlobalData.Scouts) + if ismember(hFig, [GlobalData.Scouts(i).Handles.hFig]) + iScouts = [iScouts, i]; + end + end + sScouts = GlobalData.Scouts(iScouts); +end + + +%% ===== GET SELECTED SCOUTS ===== +% NB: Returned indices are indices in GlobalData.Scouts array +function [sSelScouts, iSelScouts] = GetSelectedScouts() + sSelScouts = []; + iSelScouts = []; + % Get current scouts + [sScouts, iScouts] = GetCurrentScouts(); + if isempty(sScouts) + return + end + % Get "Scouts" panel controls + jListScouts = bst_getContext('PanelElement', 'Scout', 'jListScouts'); + % Get JList selected indices + iSelScouts = uint16(jListScouts.getSelectedIndices())' + 1; + if isempty(iScouts) + return + end + sSelScouts = sScouts(iSelScouts); + iSelScouts = iScouts(iSelScouts); +end + + +%% ===== SET SELECTED SCOUTS ===== +% WARNING: Input indices are references in the GlobalData.Scouts array, not in the JList +function SetSelectedScouts(iSelScouts) + % === GET SCOUT INDICES === + % No selection + if isempty(iSelScouts) || (any(iSelScouts == 0)) + iSelItem = -1; + % Find the selected scouts in the JList + else + [sScouts,iScouts] = GetCurrentScouts(); + iSelItem = []; + for i=1:length(iSelScouts) + iSelItem = [iSelItem, find(iSelScouts(i) == iScouts)]; + end + if isempty(iSelItem) + iSelItem = -1; + else + iSelItem = iSelItem - 1; + end + end + % === CHECK FOR MODIFICATIONS === + % Get 3DViz figure information + jListScouts = bst_getContext('PanelElement', 'Scout', 'jListScouts'); + if isempty(jListScouts) + return + end + % Get previous selection + iPrevItems = jListScouts.getSelectedIndices(); + % If selection did not change: exit + if isequal(iPrevItems, iSelItem) || (isempty(iPrevItems) && isequal(iSelItem, -1)) + return + end + % === UPDATE SELECTION === + % Temporality disables JList selection callback + jListCallback_bak = get(jListScouts, 'ValueChangedCallback'); + set(jListScouts, 'ValueChangedCallback', []); + % Select items in JList + jListScouts.setSelectedIndices(iSelItem); + % Restore JList callback + set(jListScouts, 'ValueChangedCallback', jListCallback_bak); + % Update panel "Scouts" fields + UpdateScoutProperties(); + % Display/hide scouts + if isViewOnlySelectedScouts() + UpdateScoutsDisplay(); + end +end + + + +%% ===== GET SCOUT DISPLAY TYPE ===== +% ScoutsOptions: +% |- function : {'Mean','Max','Power','All'} ? +% |- overlayScouts : {0, 1} +% |- overlayConditions : {0, 1} +% |- isAbsolute : {0, 1} +function ScoutsOptions = GetScoutDisplayType() %#ok + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % Sources time series : MEAN, MAX, ALL + if ctrl.jRadioTypeMean.isSelected() + ScoutsOptions.function = 'Mean'; + elseif ctrl.jRadioTypeMax.isSelected() + ScoutsOptions.function = 'Max'; + elseif ctrl.jRadioTypePower.isSelected() + ScoutsOptions.function = 'Power'; + elseif ctrl.jRadioTypeAll.isSelected() + ScoutsOptions.function = 'All'; + end + % Overlay + ScoutsOptions.overlayScouts = ctrl.jCheckOverlayScouts.isSelected(); + ScoutsOptions.overlayConditions = ctrl.jCheckOverlayConditions.isSelected(); + % Display absolute values ? + ScoutsOptions.isAbsolute = ctrl.jRadioValuesAbsolute.isSelected(); +end + + +%% ===== CREATE NEW SCOUT ===== +function [sScout, iScout] = CreateNewScout(SurfaceFile, newVertices, newSeed) + global GlobalData; + % == NEW SCOUT == + % New scout structure + sScout = db_getDataTemplate('Scout'); + iScout = length(GlobalData.Scouts) + 1; + % Store current scout coordinates + sScout.SurfaceFile = SurfaceFile; + sScout.Vertices = newVertices; + sScout.Seed = newSeed; + + % == SCOUT LABEL == + % Get other scouts with same surface file + sOtherScouts = GetScoutsWithSurface(SurfaceFile); + % Define scouts labels (Label=index) + iDisplayIndice = length(sOtherScouts) + 1; + scoutLabel = int2str(iDisplayIndice); + % Check that the scout name does not exist yet (else, add a ') + if ~isempty(sOtherScouts) + while ismember(scoutLabel, {sOtherScouts.Label}) + scoutLabel = [scoutLabel, '''']; + end + end + sScout.Label = scoutLabel; + + % == SCOUT COLOR == + ColorTable = GetScoutsColorTable(); + iColor = mod(iDisplayIndice-1, length(ColorTable)) + 1; + sScout.Color = ColorTable(iColor,:); + % == Register new scout == + GlobalData.Scouts(iScout) = sScout; +end + + +%% ===== GET SCOUTS COLOR TABLE ===== +function ColorTable = GetScoutsColorTable() + ColorTable = [0 1 0 ; + 1 0 0 ; + .4 .4 1 ; + 1 .694 .392; + 0 1 1 ; + 1 0 1 ; + .4 0 0 ; + 0 .5 0]; +end + + +%% ===== VIEW SCOUT ===== +function DisplayScouts(varargin) + % Stop scout editing + SetSelectionState(0); + % Get selected scouts + [sSelScouts, iSelScouts] = GetSelectedScouts(); + % Warning message if no scout selected + if isempty(sSelScouts) + java_dialog('warning', 'No scout selected.', 'Display time series'); + return; + end + % Display scouts + gui_viewResultsScouts(); +end + + +%% =============================================================================== +% ====== POINTS SELECTION ======================================================= +% =============================================================================== +%% ===== SCOUT SELECTION : start/stop ===== +% Manual selection of a cortical spot : start(1), or stop(0) +function SetSelectionState(isSelected) + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + if isempty(ctrl) + return + end + % Get list of figures where it is possible to select a scout + hFigures = gui_figuresManager('GetFiguresForScouts'); + % No figure available + if isempty(hFigures) + if isSelected + java_dialog('warning', 'No 3D figure with sources available.', 'Select a cortical spot'); + end + % Release toolbar "AddScout" button + ctrl.jButtonAddScout.setSelected(0); + return + end + % Start scout selection + if isSelected + % Push toolbar "AddScout" button + ctrl.jButtonAddScout.setSelected(1); + % Unselect all the scouts in JList + SetSelectedScouts([]); + % Set 3DViz figures in 'SelectingCorticalSpot' mode + for hFig = hFigures + setappdata(hFig, 'isSelectingCorticalSpot', 1); + set(hFig, 'Pointer', 'cross'); + end + % Stop scout selection + else + % Release toolbar "AddScout" button + ctrl.jButtonAddScout.setSelected(0); + % Exit 3DViz figures from SelectingCorticalSpot mode + for hFig = hFigures + set(hFig, 'Pointer', 'arrow'); + setappdata(hFig, 'isSelectingCorticalSpot', 0); + end + end +end + + + +%% ===== SCOUT SELECTION : Selection performed ===== +% Usage : SelectCorticalSpot(hFig) : Scout location = user click in figure hFIg +% If only one scout is selected: add the selected point to the selected scout +% Else: Create a new scout +function SelectCorticalSpot(hFig) %#ok + global GlobalData; + % Get cortex and anatomy surface handle + [iCortex, TessInfo] = panel_surface('GetSurfaceCortex', hFig); + [sMri, TessInfo, iAnatomy] = panel_surface('GetSurfaceMri', hFig); + + + % === POINT SELECTION ON CORTEX === + if ~isempty(iCortex) + hSurface = TessInfo(iCortex).hPatch; + % Get mouse 3D selection + [pout vout vi] = select3d(hSurface); + % === POINT SELECTION ON MRI === + elseif ~isempty(iAnatomy) && ~isempty(TessInfo.DataSource.FileName) + % Get vertices + sSubject = bst_getContext('MriFile', sMri.FileName); + % If there is no cortex for this subject: exit + if isempty(sSubject.iCortex) + return + end + CortexFile = sSubject.Surface(sSubject.iCortex).FileName; + sSurfCortex = bst_dataSetsManager('LoadSurface', CortexFile); + + % Select a point in the MRI slices + [TessInfo, iTess, pout, vout, vi] = panel_coordinates('ClickPointInSurface', hFig, 'Anatomy'); + % Find the closest cortical point from this MRI coordinates + dist = (sSurfCortex.Vertices(:,1) - pout(1)) .^ 2 + ... + (sSurfCortex.Vertices(:,2) - pout(2)) .^ 2 + ... + (sSurfCortex.Vertices(:,3) - pout(3)) .^ 2; + [minDist, iMinDist] = min(dist); + % If selected point is too far away from cortical surface : return + if (sqrt(minDist) > 0.01) + return + end + % Select the closest point + vout = sSurfCortex.Vertices(iMinDist, :)'; + vi = iMinDist; + else + return; + end + % Check that a point was selected + if isempty(vout) + return + end + + % === CREATING SCOUT OR ADDING POINTS === + % Get selected scouts + [sSelScouts, iSelScouts] = GetSelectedScouts(); + % If there is more that one selected scout: select only the first one + if (length(iSelScouts) > 1) + SetSelectedScouts(iSelScouts(1)); + sSelScouts = sSelScouts(1); + iSelScouts = iSelScouts(1); + end + isNewScout = (length(sSelScouts) ~= 1); + + % ==== CHECK UNICITY OF VERTICES ==== + % Get current scouts + sScouts = GetCurrentScouts(); + if ~isempty(sScouts) + % Check unicity + scoutsVertices = [sScouts.Vertices]; + % If vertex was already set as a scout : return + if ismember(vi, scoutsVertices) + return + end + end + + % ==== NEW SCOUT ==== + if isNewScout + % Create new scout + [sScout, iScout] = CreateNewScout(GlobalData.CurrentScoutsSurface, vi, vi); + % ==== ADD POINT TO SELECTED SCOUT ==== + else + % Use selected scout + iScout = iSelScouts; + % Add clicked vertex + GlobalData.Scouts(iScout).Vertices = [GlobalData.Scouts(iScout).Vertices, vi]; + end + + % === UPDATE INTERFACE === + % Display scout patch + PlotScout(iScout); + % Update "Scouts" panel + UpdatePanel(); + % Select last scout in list + SetSelectedScouts(iScout); + % Deselect "AddScout" button + % (Only if creating new scout. If adding points to existing scouts, keep adding points) + if isNewScout + SetSelectionState(0); + end + % OverlayCube for 3D MRI display is not updated => Need to update it + UpdateScoutsDisplay(); +end + + +%% =============================================================================== +% ====== SCOUTS CREATION/EDITION ================================================ +% =============================================================================== +%% ===== START NEW SCOUT / SURFACE ===== +function StartNewScoutSurface() + % Start edition of a new scout + SetSelectionState(1); +end + +%% ===== START NEW SCOUT / MRI ===== +function StartNewScoutMri() + % Open MRI scout editor (for creation) + ScoutEditorInMri(-1); +end + +%% ===== START NEW SCOUT / MAX ===== +function StartNewScoutMax() + SelectMaximumValue(); +end + +%% ===== SURFACE TILING ===== +function SurfaceTiling() + nClust = 30; %Number of surface tiles (clusters); % CBB: Prompt user + VERBOSE = 1; % Turn on/off verbose of tiling process + + % Get cortex and anatomy surface handle + [iSurf, TessInfo] = panel_surface('GetSurfaceCortexOrAnatomy'); %CBB: works with only one 3D figure being displayed + infoProtocole = bst_getContext('ProtocolInfo'); + load(fullfile(infoProtocole.SUBJECTS,TessInfo.SurfaceFile),'VertConn'); + [CLASS, NumClass, nbre_zone] = cortex_cluster(VertConn,nClust,1:size(VertConn,1),1,VERBOSE); + + global GlobalData; + GlobalData = rmfield(GlobalData,'Scouts'); + for iNewScout=1:nbre_zone + GlobalData.Scouts(iNewScout) = db_getDataTemplate('Scout'); + GlobalData.Scouts(iNewScout).Vertices = find(CLASS{1}==iNewScout); + GlobalData.Scouts(iNewScout).Seed = GlobalData.Scouts(iNewScout).Vertices(1); + GlobalData.Scouts(iNewScout).SurfaceFile = TessInfo.SurfaceFile; + GlobalData.Scouts(iNewScout).Label = num2str(iNewScout); + GlobalData.Scouts(iNewScout).Color = rand(1,3); + PlotScout(iNewScout) + end + + UpdateScoutsDisplay(); +end + + +%% ===== EDIT EXISTING SCOUT / SURFACE ===== +function EditExistingScoutSurface() + % Get selected scouts + [sSelScouts, iSelScouts] = GetSelectedScouts(); + % Warning message if no scout selected + if isempty(sSelScouts) + java_dialog('warning', 'No scout selected.', 'Edit existing scout'); + return; + end + % Start edition of a scout (will deselect the scout) + SetSelectionState(1); + % Select again the first selected scout + SetSelectedScouts(iSelScouts(1)); +end + +%% ===== EDIT EXISTING SCOUT / MRI ===== +function EditExistingScoutMri() + % Get selected scouts + [sScout, iScout] = GetSelectedScouts(); + % Warning message if no scout selected + if isempty(sScout) + java_dialog('warning', 'No scout selected.', 'Edit existing scout'); + return; + % If more than one scout selected: keep only the first one + elseif (length(sScout) > 1) + sScout = sScout(1); + iScout = iScout(1); + SetSelectedScouts(iScout); + end + % Open MRI scout editor (for edition) + ScoutEditorInMri(iScout); +end + +%% ===== EDIT EXISTING SCOUT / MAX ===== +function EditExistingScoutMax() + % Get selected scouts + [sScouts, iScouts] = GetSelectedScouts(); + % Warning message if no scout selected + if isempty(sScouts) + java_dialog('warning', 'No scout selected.', 'Find maximum value'); + return; + end + % Process all the selected scouts + for i = 1:length(iScouts) + SelectMaximumValue(iScouts(i)); + end +end + + +%% =============================================================================== +% ====== SCOUTS OPERATIONS ====================================================== +% =============================================================================== +%% ===== PLOT ALL SCOUTS FOR CURRENT FIGURE ===== +function PlotAllScouts() %#ok + [tmp__, iScouts] = GetCurrentScouts(); + for i=iScouts + PlotScout(i); + end + UpdateScoutsDisplay(); +end + + +%% ===== DISPLAY SCOUT ===== +% Find all the figures where these scouts should be displayed, and plot them. +function PlotScout(iScout) + global GlobalData; + sScout = GlobalData.Scouts(iScout); + % Get cortex file + SurfaceFiles{1} = sScout.SurfaceFile; + % Get anatomy file + [sSubject, iSubject] = bst_getContext('SurfaceFile', SurfaceFiles{1}); + if ~isempty(sSubject) && ~isempty(sSubject.iAnatomy) + SurfaceFiles{2} = sSubject.Anatomy(sSubject.iAnatomy).FileName; + end + % Get all the figures concerned with Scout cortex and MRI surface + [hFigures, iFigures, iDataSets, iSurfaces] = gui_figuresManager('GetFigureWithSurface', SurfaceFiles); + if isempty(hFigures) + return + end + % Get Surface definition + TessInfo = getappdata(hFigures(1), 'Surface'); + iSurface = iSurfaces(1); + sSurface = TessInfo(iSurface); + % Get Faces and Vertices list of target surface + if strcmpi(sSurface.Name, 'Anatomy') + sDbCortex = bst_getContext('SurfaceFileByType', iSubject, 'Cortex'); + sSurfCortex = bst_dataSetsManager('LoadSurface', sDbCortex.FileName); + Faces = sSurfCortex.Faces; + Vertices = sSurfCortex.Vertices; + else + Faces = get(sSurface.hPatch, 'Faces'); + Vertices = get(sSurface.hPatch, 'Vertices'); + end + + % Process all figures + for hFig = hFigures + % Get indice of the target figure in the sScout.Handles array + iHnd = find([sScout.Handles.hFig] == hFig); + % If figure is not referenced yet : add it + if isempty(iHnd) + iHnd = length(sScout.Handles) + 1; + sScout.Handles(iHnd).hFig = hFig; + end + % Get axes handles + hAxes = findobj(hFig, 'tag', 'Axes3D'); + + % === SCOUT 3D MARKER === + % Force scout location to be XYZ because scouts may be dispatched on a smoothed surface, + % i.e. with surface vertices being away from true locations + MarkerLocation = double(Vertices(sScout.Seed, :)); + % Plot scout marker (if it does not exist yet) + if isempty(sScout.Handles(iHnd).hScout) || ~ishandle(sScout.Handles(iHnd).hScout) + sScout.Handles(iHnd).hScout = line(MarkerLocation(1), MarkerLocation(2), MarkerLocation(3), ... + 'Marker', 'o', ... + 'MarkerFaceColor', sScout.Color, ... + 'MarkerEdgeColor', sScout.Color, ... + 'MarkerSize', 5, ... + 'Tag', 'ScoutMarker', ... + 'Parent', hAxes); + % If scout marker already exist, just update its position + else + set(sScout.Handles(iHnd).hScout, 'XData', MarkerLocation(1), ... + 'YData', MarkerLocation(2), ... + 'ZData', MarkerLocation(3)); + end + % Plot scout label (if it does not exist yet) + if isempty(sScout.Handles(iHnd).hLabel) || ~ishandle(sScout.Handles(iHnd).hLabel) + try + sScout.Handles(iHnd).hLabel = text(1.1*MarkerLocation(1), 1.1*MarkerLocation(2), 1.1*MarkerLocation(3), ... + sScout.Label, ... + 'Fontname', 'helvetica', ... + 'FontUnits', 'Point', ... + 'FontSize', 10, ... + 'FontWeight', 'normal', ... + 'Color', [.9 1 .9], ... + 'HorizontalAlignment', 'center', ... + 'Tag', 'ScoutLabel', ... + 'Parent', hAxes, ... + 'Interpreter','none'); + catch + warning('Brainstorm:GraphicsError', 'Unknown error: could not display scout label.'); + end + % If label is already displayed: just update its position + else + set(sScout.Handles(iHnd).hLabel, 'Position', 1.1 .* MarkerLocation); + end + + % ===== SCOUT PATCH ===== + % === BUILD FACES/VERTICES === + % If there are more than one vertex available for the scout + if (length(sScout.Vertices) > 1) + % Get patch vertices + patchVertices = Vertices(sScout.Vertices, :) * 1.00001; + % Create a look-up table for the vertices indices + vertTable = zeros(size(Vertices, 1), 1); + vertTable(sScout.Vertices) = 1:length(sScout.Vertices); + % Replace the vertices indices in the Faces list + patchFaces = reshape(interp1(vertTable, Faces(:), 'nearest'), [], 3); + iPatchFaces = (sum(patchFaces>0, 2) == 3); + + patchFaces = patchFaces(iPatchFaces, :); +% % Compute scout area +% sScout.Area = sum(sSurface.TriArea(iPatchFaces)); + sScout.Area = 0; + else + patchFaces = []; + patchVertices = []; + sScout.Area = 0; + end + + % === DRAW VERTICES MARKERS === + if ~isempty(patchVertices) + % Plot scout vertices (if graphic object does not exist yet) + if isempty(sScout.Handles(iHnd).hVertices) || ~ishandle(sScout.Handles(iHnd).hVertices) + sScout.Handles(iHnd).hVertices = line(patchVertices(:,1), patchVertices(:,2), patchVertices(:,3), ... + 'Marker', '.', ... + 'MarkerFaceColor', sScout.Color, ... + 'MarkerEdgeColor', sScout.Color, ... + 'MarkerSize', 5, ... + 'LineStyle', 'none', ... + 'Tag', 'ScoutMarker', ... + 'Parent', hAxes); + else + set(sScout.Handles(iHnd).hVertices, 'XData', patchVertices(:,1), ... + 'YData', patchVertices(:,2), ... + 'ZData', patchVertices(:,3)); + end + else + delete(sScout.Handles(iHnd).hVertices); + sScout.Handles(iHnd).hVertices = []; + end + + % === DRAW PATCH === + % If a patch is available (enough faces and vertices) + if ~isempty(patchFaces) && ~isempty(patchVertices) + % If patch does not exist yet : create it + if isempty(sScout.Handles(iHnd).hPatch) || ~ishandle(sScout.Handles(iHnd).hPatch) + sScout.Handles(iHnd).hPatch = patch('Faces', patchFaces, ... + 'Vertices', patchVertices, ... + 'FaceVertexCData', sScout.Color, ... + 'FaceColor', sScout.Color, ... + 'EdgeColor', sScout.Color,... + 'FaceAlpha', .3, ... + 'BackFaceLighting','lit', ... + 'Tag', 'ScoutPatch', ... + 'Parent', hAxes) ; + % Else : only update vertices and faces + else + set(sScout.Handles(iHnd).hPatch, 'Faces', patchFaces, 'Vertices', patchVertices); + end + % Else : Remove previous scout patch, if it existed + elseif ishandle(sScout.Handles(iHnd).hPatch) + delete(sScout.Handles(iHnd).hPatch); + sScout.Handles(iHnd).hPatch = []; + end + + % === ALSO UPDATE 3D MRI SLICES === +% gui_figure3DViz('UpdateOverlayCube', hFig, iSurface); + end + % Update scout defintion + GlobalData.Scouts(iScout) = sScout; +end + + +%% ===== REMOVE SCOUTS FROM FIGURE ===== +function RemoveScoutsFromFigure(hFig) %#ok + global GlobalData; + % If removing scouts from a given figure + for iScout = 1:length(GlobalData.Scouts) + iHandles = 1; + while (iHandles <= length(GlobalData.Scouts(iScout).Handles)) + if (GlobalData.Scouts(iScout).Handles(iHandles).hFig == hFig) + GlobalData.Scouts(iScout).Handles(iHandles) = []; + else + iHandles = iHandles + 1; + end + end + end +end + +%% ===== REMOVE SCOUTS ===== +% Usage : RemoveScouts(iScouts) : remove a list of scouts +% RemoveScouts() : remove the scouts selected in the JList +function RemoveScouts(varargin) + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % If scouts list is not defined + if (nargin == 0) + % Get selected scouts + [sScouts, iScouts] = GetSelectedScouts(); + % Check whether a scout is selected + if isempty(sScouts) +% java_dialog('warning', 'No scout selected.', 'Remove scout'); + return + end + elseif (nargin == 1) + iScouts = varargin{1}; + sScouts = GlobalData.Scouts(iScouts); + else + error('Invalid call to RemoveScouts.'); + end + hAllFig = []; + % Delete graphical objects + for i = 1:length(sScouts) + hAllFig = [hAllFig, [sScouts(i).Handles.hFig]]; + % Delete graphical scout markers + hMarkers = [sScouts(i).Handles.hScout]; + delete(hMarkers(ishandle(hMarkers))); + % Delete graphical scout labels + hLabels = [sScouts(i).Handles.hLabel]; + delete(hLabels(ishandle(hLabels))); + % Delete graphical scout patches + hPatches = [sScouts(i).Handles.hPatch]; + delete(hPatches(ishandle(hPatches))); + % Delete graphical scout vertices + hVertices = [sScouts(i).Handles.hVertices]; + delete(hVertices(ishandle(hVertices))); + end + + % Remove scouts definitions from global data structure + GlobalData.Scouts(iScouts) = []; + % Update "Scouts Manager" panel + UpdateScoutsList(); + % Update MRI display in all figures + panel_surface('UpdateOverlayCubes', unique(hAllFig)); +end + + +%% ===== REMOVE SCOUTS VERTICES FROM SURFACE ===== +function RemoveScoutFromSurface() + % === GET VERTICES TO REMOVE === + % Get selected scouts + [sScouts, iScouts] = GetSelectedScouts(); + % Check whether a scout is selected + if isempty(sScouts) + java_dialog('warning', 'No scout selected.', 'Remove scout'); + return + end + % Ask for user confirmation + isConfirmed = java_dialog('confirm', ['Warning: This operation is going to alter permanently the surface.', 10 ... + 'If you have some results based on this surface, they will be unusable.' 10 10 ... + 'Remove vertices ?'], 'Remove scout vertices'); + if ~isConfirmed + return + end + % Join scouts to get vertices to remove + iRemoveVert = [sScouts.Vertices]; + % Get cortex file + SurfaceFile = sScouts(1).SurfaceFile; + + % === DELETE ALL SCOUTS === + % Get all available scouts for this surface + [sCurScouts, iCurScouts] = GetCurrentScouts(); + % Remove scouts + RemoveScouts(iCurScouts); + + % === REMOVE VERTICES FROM SURFACE FILE === + % Get full surface file path + ProtocolInfo = bst_getContext('ProtocolInfo'); + SurfaceFileFull = fullfile(ProtocolInfo.SUBJECTS, SurfaceFile); + % Load surface file + SurfaceMat = in_tess_bst(SurfaceFileFull); + % Remove vertices + [Vertices, Faces] = tess_removeVertices(SurfaceMat.Vertices, SurfaceMat.Faces, iRemoveVert); + % Build new surface + newSurfaceMat.Comment = SurfaceMat.Comment; + newSurfaceMat.Vertices = Vertices; + newSurfaceMat.Faces = Faces; + % Save file back + save(SurfaceFileFull, '-struct', 'newSurfaceMat'); + % Unload surface file + bst_dataSetsManager('UnloadSurface', SurfaceFile); + + % === REMOVE VERTICES FROM FIGURES === + % Get all the figures concerned with Scout cortex and MRI surface + [hFigures, iFigures, iDataSets, iSurfaces] = gui_figuresManager('GetFigureWithSurface', SurfaceFile); + if isempty(hFigures) + return + end + % Process all the figures + for i = 1:length(hFigures) + % Get surface definition + TessInfo = getappdata(hFigures(i), 'Surface'); + surfaceFile = TessInfo(iSurfaces(i)).SurfaceFile; + % Unload surface and load it again + panel_surface('RemoveSurface', hFigures(i), iSurfaces(i)); + panel_surface('AddSurface', hFigures(i), surfaceFile); + end +end + +%% ===== REMOVE UNSUSED SCOUTS ===== +function RemoveUnusedScouts() %#ok + global GlobalData; + % Get list of all the subjects currently usefull + UsefulSubjects = unique({GlobalData.DataSet.SubjectFile}); + % For each subject get the list list of useful surfaces + UsefulSurfaces = {}; + for i = 1:length(UsefulSubjects) + sSubject = bst_getContext('Subject', UsefulSubjects{i}); + if ~isempty(sSubject) + UsefulSurfaces = cat(2, UsefulSurfaces, {sSubject.Surface.FileName}); + end + end + UsefulSurfaces = unique(UsefulSurfaces); + + % For each scout, check if associated cortex file is in the UsefulSurfaces array + iScoutsToRemove = []; + for iScout = 1:length(GlobalData.Scouts) + if ~any(io_compareFileNames(GlobalData.Scouts(iScout).SurfaceFile, UsefulSurfaces)) + iScoutsToRemove(end + 1) = iScout; + end + end + % Remove useless scouts + if ~isempty(iScoutsToRemove) + RemoveScouts(iScoutsToRemove); + end +end + + +%% ===== JOIN SCOUTS ===== +% Join the scouts selected in the JList +function JoinScouts() + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % Get selected scouts + [sScouts, iScouts] = GetSelectedScouts(); + % Need TWO scouts + if (length(sScouts) < 2) + java_dialog('warning', 'You need to select at least two scouts.', 'Join selected scouts'); + return; + end + + % === Remove old scouts === + RemoveScouts(iScouts); + % === Join scouts === + % Create new scout + newScout = db_getDataTemplate('Scout'); + % Copy unmodified fields + newScout.SurfaceFile = sScouts(1).SurfaceFile; + newScout.Seed = sScouts(1).Seed; + % Vertices : concatenation + newScout.Vertices = unique([sScouts.Vertices]); + % Label : "Label1 & Label2 & ..." + newScout.Label = sScouts(1).Label; + for i = 2:length(sScouts) + newScout.Label = [newScout.Label ' & ' sScouts(i).Label]; + end + + % Add new scout to global structure + iNewScout = length(GlobalData.Scouts) + 1; + GlobalData.Scouts(iNewScout) = newScout; + % Display new scout + PlotScout(iNewScout); + % Update "Scouts Manager" panel + UpdateScoutsList(); + % Select last scout in list (new scout) + SetSelectedScouts(iNewScout); +end + + +%% ===== EDIT SCOUT LABEL ===== +% Rename one and only one selected scout +function EditScoutLabel() + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % Get selected scouts + [sScout, iScout] = GetSelectedScouts(); + % Warning message if no scout selected + if isempty(sScout) + java_dialog('warning', 'No scout selected.', 'Rename selected scout'); + return; + % If more than one scout selected: keep only the first one + elseif (length(sScout) > 1) + iScout = iScout(1); + sScout = sScout(1); + SetSelectedScouts(iScout); + end + % Ask user for a new Scout Label + newLabel = java_dialog('input', sprintf('Please enter a new label for scout "%s":', sScout.Label), ... + 'Rename selected scout', [], sScout.Label); + if isempty(newLabel) || strcmpi(newLabel, sScout.Label) + return + end + % Update Scout definition + GlobalData.Scouts(iScout).Label = newLabel; + % Update graphical objects + set([sScout.Handles.hLabel], 'String', newLabel); + % Update JList + UpdateScoutsList(); + % Select back selected scout + SetSelectedScouts(iScout); +end + + +%% ===== EDIT SCOUTS SIZE ===== +function EditScoutsSize(action) + global GlobalData mutexGrowScout; + % Stop scouts edition + SetSelectionState(0); + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % Use a mutex to prevent the function from being executed more than once at the same time + if isempty(mutexGrowScout) || (mutexGrowScout > 1) + % Entrance accepted + tic + mutexGrowScout = 0; + else + % Entrance rejected (another call is not finished,and was call less than 1 seconds ago) + mutexGrowScout = toc; + disp('Call to EditScoutsSize ignored...'); + return + end + + % Get selected scouts + [sScouts, iSelScouts] = GetSelectedScouts(); + % Can grow only scouts that are DISPLAYED IN AT LEAST ONE FIGURE + if isempty(sScouts) || isempty(sScouts(1).Handles) + return + end + % Get all current scouts + [sScouts, iAllScouts] = GetCurrentScouts(); + % Get figure + hFig = sScouts(1).Handles(1).hFig; + % Get cortex and anatomy surface handle + [iSurf, TessInfo] = panel_surface('GetSurfaceCortexOrAnatomy', hFig); + + % Process all the selected scouts + for iScout = iSelScouts + % Get cortex vertices + sDbCortex = bst_getContext('SurfaceFileByType', TessInfo(iSurf).SurfaceFile, 'Cortex'); + sSurfCortex = bst_dataSetsManager('LoadSurface', sDbCortex.FileName); + % Get cortex patch vertices + if strcmpi(TessInfo(iSurf).Name, 'Anatomy') + patchVertices = sSurfCortex.Vertices; + else + patchVertices = get(TessInfo(iSurf).hPatch, 'Vertices'); + end + % Get vertices of the scout (indices) + vi = GlobalData.Scouts(iScout).Vertices; + % Get coordinates of the seed + seedXYZ = patchVertices(GlobalData.Scouts(iScout).Seed, :); + % If constrained growth + isContrained = ctrl.jToggleConstrained.isSelected(); + % Get vertices with values below the data threshold + iUnderThresh = []; + if isContrained + if ~isempty( TessInfo(iSurf).Data ) + % iUnderThresh = find(abs(TessInfo(iSurf).Data) <= TessInfo(iSurf).DataThreshold * max(abs(TessInfo(iSurf).Data))); + iUnderThresh = find(abs(TessInfo(iSurf).Data) <= TessInfo(iSurf).DataIntThreshold * max(abs(TessInfo(iSurf).DataMinMax))); + % knd: to do: include DataExtThreshold + %cluster_threshold + iUnderThresh = [iUnderThresh ; ]; + + end + end + + % Now grow/shrink a patch around the selected probe by adding/removing a ring neighbors + switch (action) + case 'Grow' + viNew = patch_swell(vi, sSurfCortex.VertConn); + % Remove vertices under the threshold + viNew = setdiff(viNew, iUnderThresh); + if ~isempty(viNew) + % Get vertices of the scout (coordinates) + vXYZ = patchVertices(viNew, :); + % Compute the distance from each point to the seed + distFromSeed = sqrt((vXYZ(:,1)-seedXYZ(1)).^2 + (vXYZ(:,2)-seedXYZ(2)).^2 + (vXYZ(:,3)-seedXYZ(3)).^2); + % === LIMIT GROWTH WITH A SPHERE === + % Radius of the sphere = mean(dist(v, seed)) + 1.5*std + sphereRadius = mean(distFromSeed) + 1.5 * std(distFromSeed); + % Keep only vertices in a sphere around the Scout seed + vi = union(vi, viNew(distFromSeed <= sphereRadius)); + end + case 'Grow1' + % Get closest neighbours + viNew = setdiff(patch_swell(vi, sSurfCortex.VertConn), vi); + % Remove vertices under the threshold + viNew = setdiff(viNew, iUnderThresh); + if ~isempty(viNew) + % Get new vertices of the scout (coordinates) + vXYZ = patchVertices(viNew, :); + % Compute the distance from each point to the seed + distFromSeed = sqrt((vXYZ(:,1)-seedXYZ(1)).^2 + (vXYZ(:,2)-seedXYZ(2)).^2 + (vXYZ(:,3)-seedXYZ(3)).^2); + % === ADD ONLY THE CLOSEST VERTEX === + % Get the minimum distance + [minVal, iMin] = min(distFromSeed); + iMin = iMin(1); + % Add this vertex to scout vertices + vi = union(vi, viNew(iMin)); + end + + case 'Shrink1' + % Remove a layer of connected vertices + Expanded = patch_swell(vi, sSurfCortex.VertConn); + viToRemove = patch_swell(Expanded, sSurfCortex.VertConn); + viToRemove = intersect(viToRemove, vi); + % Get vertices of the scout (coordinates) + vXYZ = patchVertices(viToRemove, :); + % Compute the distance from each point to the seed + distFromSeed = sqrt((vXYZ(:,1)-seedXYZ(1)).^2 + (vXYZ(:,2)-seedXYZ(2)).^2 + (vXYZ(:,3)-seedXYZ(3)).^2); + % === REMOVE ONLY THE FAREST VERTEX === + % Get the maximum distance + [maxVal, iMax] = max(distFromSeed); + iMax = iMax(1); + % Remove this vertex from the scout vertices + vi = setdiff(vi, viToRemove(iMax)); + + case 'Shrink' + % Remove a layer of connected vertices + Expanded = patch_swell(vi, sSurfCortex.VertConn); + viToRemove = patch_swell(Expanded, sSurfCortex.VertConn); + % Get vertices of the scout (coordinates) + vXYZ = patchVertices(vi, :); + % Compute the distance from each point to the seed + distFromSeed = sqrt((vXYZ(:,1)-seedXYZ(1)).^2 + (vXYZ(:,2)-seedXYZ(2)).^2 + (vXYZ(:,3)-seedXYZ(3)).^2); + % === DEFINE SHRINK WITH A SPHERE === + % Radius of the sphere = mean(dist(v, seed)) + 1.5*std + sphereRadius = mean(distFromSeed); + % Keep only vertices in a sphere around the Scout seed + viOutsideSphere = vi(distFromSeed > sphereRadius); + % Remove only vertices that are removed by the two methods + viToRemove = intersect(viToRemove, viOutsideSphere); + vi = setdiff(vi, viToRemove); + end + + % Remove vertices that are already in other scouts + iOtherScouts = setdiff(iAllScouts, iScout); + vi = setdiff(vi, [GlobalData.Scouts(iOtherScouts).Vertices]); + + % Save new list of vertices + GlobalData.Scouts(iScout).Vertices = vi; + % If all the vertices were removed, keep initial scout vertex + if isempty(GlobalData.Scouts(iScout).Vertices) + GlobalData.Scouts(iScout).Vertices = GlobalData.Scouts(iScout).Seed; + end + % Display scout patch + PlotScout(iScout); + end + + % Release mutex + mutexGrowScout = []; + % Update panel "Scouts" fields + UpdateScoutProperties(); + % Display/hide scouts and update MRI overlay mask + UpdateScoutsDisplay(); +end + + +%% ===== EDIT SCOUTS COLOR ===== +function EditScoutsColor(newColor) + global GlobalData; + % Get selected scouts + [sSelScouts, iSelScouts] = GetSelectedScouts(); + if isempty(iSelScouts) + java_dialog('warning', 'No scout selected.', 'Edit scout color'); + return + end + % If color is not specified in argument : ask it to user + if (nargin < 1) + % Use previous scout color + newColor = uisetcolor(sSelScouts(1).Color, 'Select scout color'); + % If no color was selected: exit + if (length(newColor) ~= 3) || all(sSelScouts(1).Color == newColor) + return + end + end + % Update scouts color + for i = 1:length(iSelScouts) + GlobalData.Scouts(iSelScouts(i)).Color = newColor; + % Update color for all graphical instances + % Seed + set([sSelScouts(i).Handles.hScout], 'MarkerFaceColor', newColor, ... + 'MarkerEdgeColor', newColor); + % Patch + set([sSelScouts(i).Handles.hPatch], 'FaceVertexCData', newColor, ... + 'FaceColor', newColor, ... + 'EdgeColor', newColor); + % Vertices + set([sSelScouts(i).Handles.hVertices], 'MarkerFaceColor', newColor, ... + 'MarkerEdgeColor', newColor); + end +end + +%% ===== REDRAW SCOUTS ===== +% Update vertices of scouts for a given surface +function UpdateScoutsVertices(SurfaceFile) %#ok + global GlobalData; + % Get scouts to update + iScoutsToUpdate = find(io_compareFileNames({GlobalData.Scouts.SurfaceFile}, SurfaceFile) & ~cellfun(@isempty, {GlobalData.Scouts.Handles})); + if isempty(iScoutsToUpdate) || isempty(GlobalData.Scouts(iScoutsToUpdate(1)).Handles) + return; + end + % Get surface information in figure appdata + TessInfo = getappdata(GlobalData.Scouts(iScoutsToUpdate(1)).Handles(1).hFig, 'Surface'); + iSurface = find(io_compareFileNames({TessInfo.SurfaceFile}, SurfaceFile)); + if isempty(iSurface) + return; + end + % Get displayed vertices of surface + Vertices = get(TessInfo(iSurface).hPatch, 'Vertices'); + + % Update vertices of all scouts + for iScout = iScoutsToUpdate + sScout = GlobalData.Scouts(iScout); + % Update vertices for all graphical instances + for ihand = 1:length(sScout.Handles) + % Scout seed + set(sScout.Handles(ihand).hScout, 'XData', Vertices(sScout.Seed, 1), ... + 'YData', Vertices(sScout.Seed, 2), ... + 'ZData', Vertices(sScout.Seed, 3)); + % Scout vertices + set(sScout.Handles(ihand).hVertices, 'XData', Vertices(sScout.Vertices, 1), ... + 'YData', Vertices(sScout.Vertices, 2), ... + 'ZData', Vertices(sScout.Vertices, 3)); + % Scout label + set(sScout.Handles(ihand).hLabel, 'Position', 1.1 * Vertices(sScout.Seed, :)); + % Scout patch + set(sScout.Handles(ihand).hPatch, 'Vertices', Vertices(sScout.Vertices, :)); + end + end +end + + +%% ===== UPDATE SCOUTS DISPLAY ===== +% Display/hide scouts. +function UpdateScoutsDisplay() + % Get current scouts + [sScouts, iScouts] = GetCurrentScouts(); + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % View mode : VIEW SELECTED SCOUTS + if isViewOnlySelectedScouts() + % Get selected scouts + [sSelScouts, iSelScouts] = GetSelectedScouts(); + % Get JList selected indices + iVisibleScouts = []; + for i = 1:length(iSelScouts) + iVisibleScouts = [iVisibleScouts, find(iScouts == iSelScouts(i))]; + end +% iVisibleScouts = iSelScouts; +% iHiddenScouts = setdiff(1:length(iScouts), iVisibleScouts); + % View mode : VIEW ALL SCOUTS + else + % All scouts are visible + iVisibleScouts = 1:length(iScouts); +% iHiddenScouts = []; + end + hAllFig = []; + % Check if + isDisplayIfOnlyAnatomy = ctrl.jCheckViewPatchesInMri.isSelected(); + % Loop on all scouts + for i = 1:length(iScouts) + % Is this scout supposed to be visible + isVisibleGlobal = ismember(i, iVisibleScouts); + % Process each figure in which this scout is accessible + for iFig = 1:length(sScouts(i).Handles) + hFig = sScouts(i).Handles(iFig).hFig; + isVisibleLocal = isVisibleGlobal; + % === IS SCOUT VISIBLE ? === + % If scout is visible according to selection, but should be hidden if there is only an anatomy surface + if isVisibleGlobal && ~isDisplayIfOnlyAnatomy + % Find cortex and anatomy surfaces + iCortex = panel_surface('GetSurfaceCortex', hFig); + iAnatomy = panel_surface('GetSurfaceMri', hFig); + % If only anatomy is accessible : hide scout + if isempty(iCortex) && ~isempty(iAnatomy) + isVisibleLocal = 0; + end + end + % === SET THE VISIBILITIES === + hGlobal = [sScouts(i).Handles(iFig).hScout, sScouts(i).Handles(iFig).hLabel]; + hLocal = [sScouts(i).Handles(iFig).hPatch, sScouts(i).Handles(iFig).hVertices]; + % Set the visibility of all the scout elements + if ~isempty(hGlobal) + if isVisibleGlobal + set(hGlobal, 'Visible', 'on'); + else + set(hGlobal, 'Visible', 'off'); + end + end + if ~isempty(hLocal) + if isVisibleLocal + set(hLocal, 'Visible', 'on'); + else + set(hLocal, 'Visible', 'off'); + end + end + % Add figure to the list of updated figures + hAllFig = [hAllFig, hFig]; + end + end + + % Add the list of the MriViewer figures + hFigMriViewer = gui_figuresManager('GetFiguresByType', 'MriViewer'); + % List of all the figures that have proper scouts drawn in them + hAllFig = unique([hFigMriViewer, hAllFig]); + % Update overlay mask (for 3D MRI slices) for each figure + panel_surface('UpdateOverlayCubes', hAllFig); +end + + + +%% ===== SAVE SCOUT ===== +function SaveScouts() + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % Get protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get selected scouts + sScouts = GetSelectedScouts(); + if isempty(sScouts) + return + end + % Build a default file name + ScoutFile = fullfile(ProtocolInfo.SUBJECTS, fileparts(GlobalData.CurrentScoutsSurface), ... + ['scout', sprintf('_%s', sScouts.Label), '.mat']); + % Get filename where to store the filename + ScoutFile = java_fileSelector( 'save', 'Save selected scouts', ScoutFile, ... + 'single', 'files', ... + {{'_scout'}, 'Brainstorm cortical scouts (*scout*.mat)', 'BST'}, 1); + if isempty(ScoutFile) + return; + end + % Make sure that filename contains the 'scout' tag + if isempty(strfind(ScoutFile, '_scout')) && isempty(strfind(ScoutFile, 'scout_')) + [filePath, fileBase, fileExt] = fileparts(ScoutFile); + ScoutFile = fullfile(filePath, ['scout_' fileBase fileExt]); + end + + % Load tesselation vertices (just to get nb vertices) + SurfaceFile = strrep(sScouts(1).SurfaceFile, ProtocolInfo.SUBJECTS, ''); + sSurf = bst_dataSetsManager('LoadSurface', SurfaceFile); + % Prepare saved structure + ScoutMat.Tesselation = io_win2unix(SurfaceFile); + ScoutMat.TessNbVertices = length(sSurf.Vertices); + for i=1:length(sScouts) + ScoutMat.Scout(i).Vertices = sScouts(i).Vertices; + ScoutMat.Scout(i).Seed = sScouts(i).Seed; + ScoutMat.Scout(i).Label = sScouts(i).Label; + ScoutMat.Scout(i).Color = sScouts(i).Color; + end + % Save file + save(ScoutFile, '-struct', 'ScoutMat'); +end + + +%% ===== LOAD SCOUT ===== +function LoadScouts() + global GlobalData; + % === SELECT FILE TO LOAD === + % Stop scout edition + SetSelectionState(0); + % Get protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Build default scouts directory + if ~isempty(GlobalData.CurrentScoutsSurface) + scoutsSubDir = fileparts(GlobalData.CurrentScoutsSurface); + else + % Get current subject directory + sSubject = bst_getContext('Subject'); + % If no current subject (no recordings were loaded yet) + curFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(sSubject) && ~isempty(curFig) + % Get subject of current figure + SubjectFile = getappdata(curFig, 'SubjectFile'); + if ~isempty(SubjectFile) + sSubject = bst_getContext('Subject', SubjectFile); + end + end + if isempty(sSubject) + return; + end + scoutsSubDir = fileparts(sSubject.FileName); + end + scoutsDir = fullfile(ProtocolInfo.SUBJECTS, scoutsSubDir); + % Ask user which are the files to be loaded + ScoutFiles = java_fileSelector( 'open', 'Import scouts', scoutsDir, ... + 'multiple', 'files', ... + {{'_scout'}, 'Cortical scouts (*scout*.mat)', 'BST'}, 1); + if isempty(ScoutFiles) + return + end + + % ==== CREATE AND DISPLAY ==== + iNewScoutsList = []; + bst_progressBar('start', 'Load scouts', 'Load scout file'); + % Load all files selected by user + for iFile = 1:length(ScoutFiles) + % Try to load scout file + ScoutMat = load(ScoutFiles{iFile}); + + % === INTEGRATION WITH CURRENT DATA === + % Find an existing figure with the same number of vertices + [hFig,iFig,iDS,iSurf] = gui_figuresManager('GetFigureWithSurfaceNbVert', ScoutMat.TessNbVertices); + % If no figure found: import scouts ignoring figures and currently loaded data + if isempty(hFig) + iFound = []; + elseif (length(hFig) == 1) + iFound = 1; + % If there are more than one figure + elseif (length(hFig) > 1) + % Get current figure + hCurFig = gui_figuresManager('GetCurrentFigure', '3D'); + % Find current figure in valid candidates for loaded scout + iFound = find(hFig == hCurFig, 1); + % If current figure is found: use it, else use first figure in the list + if isempty(iFound) + iFound = 1; + end + hFig = hFig(iFound); + iSurf = iSurf(iFound); + end + % Replace scout tess field with the surface we've just found + if ~isempty(iFound) + TessInfo = getappdata(hFig, 'Surface'); + if strcmpi(TessInfo(iSurf).Name, 'Anatomy') + sSurfCortex = bst_getContext('SurfaceFileByType', TessInfo(iSurf).SurfaceFile, 'Cortex'); + ScoutMat.Tesselation = sSurfCortex.FileName; + else + ScoutMat.Tesselation = TessInfo(iSurf).SurfaceFile; + end + end + + % === AUTO-CORRECT TESSELATION FIELD === + % If Figure not found && Tesselation pointed by the Scout does not exist + if isempty(iFound) && ~exist(fullfile(ProtocolInfo.SUBJECTS, ScoutMat.Tesselation), 'file') + CorrectedTess = ''; + bst_progressBar('start', 'Load scouts', 'Finding a valid cortex surface...'); + % If NbVertices is not defined: cannot find file + if isfield(ScoutMat, 'TessNbVertices') && ~isempty(ScoutMat.TessNbVertices) + % Look for a tesselation file with the same number of vertices in the scout directory + dirTess = fileparts(ScoutFiles{iFile}); + listTessFiles = dir(fullfile(dirTess, '*tess*.mat')); + % Load each tess file and check the number of vertices + for iTess = 1:length(listTessFiles) + TessMat = in_tess_bst(fullfile(dirTess, listTessFiles(iTess).name)); + % If number of vertices is correct: keep this tess file + if (length(TessMat.Vertices) == ScoutMat.TessNbVertices) + CorrectedTess = fullfile(fileparts(ScoutFiles{iFile}), listTessFiles(iTess).name); + break + end + end + end + % If a replacing surface was found: save it + if ~isempty(CorrectedTess) + ScoutMat.Tesselation = strrep(CorrectedTess, ProtocolInfo.SUBJECTS, ''); + save(ScoutFiles{iFile}, '-struct', 'ScoutMat'); + % Else, no replacing surface was found: error + else + error(['This scout file need surface file "' ScoutMat.Tesselation '",' 10 ... + 'which cannot be found in anatomy directory.' 10 10 ... + 'Please check the Tesselation field of the scout file.']); + end + end + + % === CREATE ALL SCOUT PATCHES === + bst_progressBar('start', 'Load scouts', 'Create scouts patches...'); + try + % Each scout file may contain many scouts definitions + for i = 1:length(ScoutMat.Scout) + if ~isempty(ScoutMat.Scout(i).Seed) + % Create new scout + iNewScout = length(GlobalData.Scouts) + 1; + iNewScoutsList = [iNewScoutsList, iNewScout]; + GlobalData.Scouts(iNewScout) = db_getDataTemplate('Scout'); + % Copy needed fields + GlobalData.Scouts(iNewScout).SurfaceFile = ScoutMat.Tesselation; + GlobalData.Scouts(iNewScout).Vertices = ScoutMat.Scout(i).Vertices; + GlobalData.Scouts(iNewScout).Seed = ScoutMat.Scout(i).Seed; + GlobalData.Scouts(iNewScout).Label = ScoutMat.Scout(i).Label; + if isfield(ScoutMat.Scout(i), 'Color') + GlobalData.Scouts(iNewScout).Color = ScoutMat.Scout(i).Color; + else + GlobalData.Scouts(iNewScout).Color = [0 1 0]; + end + % Display scout + PlotScout(iNewScout); + end + end + % Update display (call only useful for 3D MRI slices) + UpdateScoutsDisplay(); + catch + warning('Brainstorm:BadScoutFile', 'Unable to load scout file : "%s".', ScoutFiles{iFile}); + end + end + + % ===== CHECK CURRENT SURFACE ===== + % If current scouts surface is not defined, use the first scout surface + if isempty(GlobalData.CurrentScoutsSurface) + GlobalData.CurrentScoutsSurface = GlobalData.Scouts(iNewScoutsList(1)).SurfaceFile; + end + + % ===== UPDATE PANEL ===== + % Update "Scouts" panel + if (length(iNewScoutsList) > 10) + % Many scouts: select and display only the first one + ctrl = bst_getContext('PanelControls', 'Scout'); + ctrl.jRadioScoutViewSelected.setSelected(1); + UpdatePanel(); + SetSelectedScouts(iNewScoutsList(1)); + elseif ~isempty(iNewScoutsList) + % Only few scouts : select and display all + UpdatePanel(); + SetSelectedScouts(iNewScoutsList); + end + bst_progressBar('stop'); +end + + +%% ===== FORWARD MODEL FOR SCOUTS ===== +% Simulate the surface data that could be recorded if only the selected scouts were activated +function ForwardModelForScout() + global GlobalData; + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Stop scout edition + SetSelectionState(0); + % ===== GET ALL ACCESSIBLE DATA ===== + % Get selected figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) || ~ishandle(hFig) || isempty(getappdata(hFig, 'ResultsFile')) + return + end + % Get ResultsFile and Surface + ResultsFile = getappdata(hFig, 'ResultsFile'); + + % Get selected scouts + sScouts = GetSelectedScouts(); + % Some scouts were found : get their vertices + if ~isempty(sScouts) && ~isempty(sScouts(1).Handles) + % Get all source vertices to perform simulation + iVertices = unique([sScouts.Vertices]); + % No scouts: use all vertices to do simulation + else + iVertices = []; + end + + % ===== LOAD GAIN MATRIX ===== + % Get study + [sStudy, iStudy, iResult] = bst_getContext('ResultsFile', ResultsFile); + % Get headmodel + sHeadModel = bst_getContext('HeadModelForStudy', iStudy); + if isempty(sHeadModel) + error('No headmodel available for this study.'); + end + % Load HeadModel file + HeadModelMat = load(fullfile(ProtocolInfo.STUDIES, sHeadModel.FileName), 'Gain'); + if isempty(HeadModelMat) + error('Invalid headmodel.'); + end + % Get gain file + if ischar(HeadModelMat.Gain{1}) + % Read gain matrix + gainfile = fullfile(ProtocolInfo.STUDIES, fileparts(sHeadModel.FileName), HeadModelMat.Gain{1}); + G = read_gain(gainfile); + elseif isnumeric(HeadModelMat.Gain{1}) + G = HeadModelMat.Gain{1}; + end + % If no vertices selected yet: use all + if isempty(iVertices) + iVertices = 1:size(G, 2); + end + % Keep only the vertices we want to project on surface + G = G(:,iVertices); + + % ===== GET RESULTS MATRIX ===== + % Load results matrix + [iDS, iResult] = bst_dataSetsManager('LoadResultsFileFull', ResultsFile); + if isempty(iDS) + return + end + % Progress bar + bst_progressBar('start', 'Simulation', 'Simulation of surface recordings...'); + % Get sources matrix + ResultsValues = bst_dataSetsManager('GetResultsValues', iDS, iResult, iVertices, 'UserTimeWindow'); + % Get ChannelFlag + ChannelFlag = GlobalData.DataSet(iDS).Results(iResult).ChannelFlag; + % Build time vector + timeWnd = round(10000 * GlobalData.DataSet(iDS).Measures.Time) / 10000; + smpRate = round(10000 * GlobalData.DataSet(iDS).Measures.SamplingRate) / 10000; + TimeVector = timeWnd(1) : smpRate : timeWnd(2); + + % ===== BUILD SIMULATED DATA FILE ===== + % Get a string to represent time + c = clock; + strTime = sprintf('%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + % Get a string to represent scouts + strScouts = ''; + if ~isempty(sScouts) + if (length(sScouts) > 1) + strScouts = '('; + end + for i=1:length(sScouts) + strScouts = [strScouts, sScouts(i).Label, ',']; + end + if (length(sScouts) > 1) + strScouts(end) = ')'; + else + strScouts(end) = []; + end + strScouts = [strScouts, '@']; + end + + % Build data file + DataMat = struct('Comment', ['Simulation: ' strScouts sStudy.Result(iResult).Comment ' (' strTime ')'], ... + 'Time', TimeVector, ... + 'F', G * ResultsValues, ... + 'ChannelFlag', ChannelFlag); + + % Output file + newDataFile = fullfile(ProtocolInfo.STUDIES, fileparts(ResultsFile), ... + ['data_simulation_', strTime, '.mat']); + newDataFile = io_makeUniqueFilename(newDataFile); + % Save file + save(newDataFile, '-struct', 'DataMat'); + % Hide progress bar + bst_progressBar('stop'); + + % ===== UPDATE DATABASE ===== + % Build data structure + sData = db_getDataTemplate('Data'); + sData.FileName = strrep(newDataFile, ProtocolInfo.STUDIES, ''); + sData.Comment = DataMat.Comment; + % Add it to study + sStudy.Data(end + 1) = sData; + bst_setContext('Study', iStudy, sStudy); + % Update display + tree_updateNode('Study', iStudy); + % Select node + tree_selectStudyNode(iStudy); +end + + +%% ===== VIEW SCOUT IN MRI ===== +function ViewInMriViewer() + % Stop scout edition + SetSelectionState(0); + % Get protocol description + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get selected scouts + [sScouts, iScouts] = GetSelectedScouts(); + if isempty(sScouts) + java_dialog('warning', 'No scout selected.', 'View scout in MRI.'); + return + elseif (length(sScouts) > 1) + % More than one scout selected: select only the first one + sScouts = sScouts(1); + iScouts = iScouts(1); + SetSelectedScouts(iScouts(1)); + end + % Get the subject associated with the first selected scout + sSubject = bst_getContext('SurfaceFile', sScouts.SurfaceFile); + % Get the anatomy file for this subject + if isempty(sSubject) || isempty(sSubject.iAnatomy) + error('No MRI defined for this subject'); + end + MriFile = fullfile(ProtocolInfo.SUBJECTS, sSubject.Anatomy(sSubject.iAnatomy).FileName); + % Build full surface path + SurfaceFile = fullfile(ProtocolInfo.SUBJECTS, sScouts.SurfaceFile); + + % Configure view to display only the scouts in MRI + ctrl = bst_getContext('PanelControls', 'Scout'); + ctrl.jCheckLimitMriSources.setSelected(1); + + % Progress bar + bst_progressBar('Start', 'MRI Viewer', 'Opening MRI Viewer...'); + % Display subject's anatomy in MRI Viewer + hFig = gui_viewMri(MriFile, SurfaceFile, 'ReadOnly'); + % Close progress bar + bst_progressBar('Stop'); + % Center view on first scout + CenterMriOnScout(); +end + + +%% ===== VIEW SCOUT ON CORTEX ===== +function ViewOnCortex() + % === Get selected scout === + [sScouts, iScouts] = GetSelectedScouts(); + if isempty(sScouts) + java_dialog('warning', 'No scout selected.', 'View scout on cortex.'); + return + elseif (length(sScouts) > 1) + % More than one scout selected: select only the first one + sScouts = sScouts(1); + iScouts = iScouts(1); + SetSelectedScouts(iScouts(1)); + end + % === Display associated surface === + gui_viewSurfaceFile(sScouts.SurfaceFile); +end + + +%% ===== EDIT SCOUT IN MRI ===== +function iScout = ScoutEditorInMri(iScout) + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % === GET SCOUT === + % Create new scout or edit existing one + isNewScout = isempty(iScout) || (iScout <= 0); + % Get existing scout + if ~isNewScout + sScout = GetScouts(iScout); + if isempty(sScout) + isNewScout = 1; + end + end + + % === GET FIGURE AND SURFACE === + % If a scout already exists: use its surface + if ~isNewScout + % Get surface for this scout + SurfaceFile = sScout.SurfaceFile; + % Get subject for this surface + [sSubject, iSubject] = bst_getContext('SurfaceFile', SurfaceFile); + % Else use current figure/surface + else + % Get current 3d figure + [hFig,iFig,iDS] = gui_figuresManager('GetCurrentFigure', '3D'); + % Get cortical surface + [iSurf, TessInfo] = panel_surface('GetSurfaceCortexOrAnatomy'); + if isempty(iSurf) + % Display warning message + java_dialog('warning', 'No cortex surface available.', 'Edit scout in MRI'); + return + end + % Build surface filename + if strcmpi(TessInfo(iSurf).Name, 'Anatomy') + % If anatomy surface : use correspondant cortex surface instead + sSurfCortex = bst_getContext('SurfaceFileByType', TessInfo(iSurf).SurfaceFile, 'Cortex'); + SurfaceFile = sSurfCortex.FileName; + else + SurfaceFile = TessInfo(iSurf).SurfaceFile; + end + % Get subject for this figure + [sSubject, iSubject] = bst_getContext('Subject', GlobalData.DataSet(iDS).SubjectFile); + end + + % === LOAD MRI AND SURFACE === + % Get the anatomy file for this subject + if isempty(sSubject) || isempty(sSubject.iAnatomy) + error('No MRI defined for this subject'); + end + % Progress bar + bst_progressBar('start', 'Edit mask', 'Initialization...'); + % Load Mri + sMri = bst_dataSetsManager('LoadMri', iSubject); + % Load Vertices from Surface + [sSurf, iSurf] = bst_dataSetsManager('LoadSurface', SurfaceFile); + % Get interpolation matrix MRI<->Surface + tess2mri_interp = bst_dataSetsManager('GetTess2MriInterp', iSurf); + % Compute the position of the vertices in MRI coordinates + mriVertices = scs2mri(sMri, sSurf.Vertices' * 1000) ./ repmat(sMri.Voxsize', 1, length(sSurf.Vertices)); + + % === BUILD INITIAL MASK === + % If scout already exist, generate a mask for it + if ~isNewScout + % Get vertices to display + iVertices = sScout.Vertices; + % Display only specified vertices + [iMri,iVert] = find(tess2mri_interp(:,iVertices)); + Values = round(sum(tess2mri_interp(:,iVertices),2) * 255); + Indices = unique(iMri); + Values = full(Values(Indices)); + + % Apply a threshold to the values + iUnderThreshold = (Values < 0.5 * 255); + Values(iUnderThreshold) = []; + Indices(iUnderThreshold) = []; + + % Create mask volume (same size than the MRI) + initMask = zeros(size(sMri.Cube), 'uint8'); + % Set values in the cube + initMask(Indices) = Values; + else + % No scout: empty initial mask + initMask = []; + end + + % === INITIAL POSITION === + % If scout already exist, + if ~isNewScout + % Orientation: Display in axial slices + initPosition(1) = 3; + % Position: mean of the scout vertices + initPosition(2) = round(mean(mriVertices(initPosition(1), sScout.Vertices))); + else + % No scout: Default display + initPosition = []; + end + + % === COLORMAP === + % Get colormap + sColormap = bst_colormaps('GetColormap', 'Anatomy'); + + % === EDIT MASK === + % Open mask editor + newMask = mri_editMask(sMri.Cube, sMri.Voxsize, initMask, initPosition, sColormap.Name); + if isempty(newMask) + return + end + % Dilatation of the mask + newMask = vol_dilate(newMask, 6); + % Mask was modified: find the vertices inside the new mask + rVertices = round(mriVertices); + iVerticesInMri = sub2ind(size(sMri.Cube), rVertices(1,:), rVertices(2,:), rVertices(3,:)); + % Find the vertices inside the mask + iVerticesInMask = find(newMask(iVerticesInMri)); + % If no vertices : cannot define a scout + if isempty(iVerticesInMask) + error(['The mask you designed does not contain any surface vertices.' 10 'It cannot be used to create a scout']); + end + + % === OUTPUT SCOUT === + % Create new scout + if isNewScout + [sScout, iScout] = CreateNewScout(SurfaceFile, iVerticesInMask, iVerticesInMask(1)); + % Update vertices + else + sScout.Vertices = iVerticesInMask; + % If seed is not anymore inside the scout : use the first vertex available + if ~ismember(sScout.Seed, sScout.Vertices) + sScout.Seed = sScout.Vertices(1); + end + end + % Save updated scout + GlobalData.Scouts(iScout) = sScout; + % Update scout display + PlotScout(iScout); + % Update display or Scouts properties + UpdatePanel(); + % Stop scout edition + SetSelectionState(0); + % Select new scout + SetSelectedScouts(iScout); + % Close progress bar + bst_progressBar('Stop'); +end + + +%% ===== CENTER MRI ON SCOUT ===== +function CenterMriOnScout() + % === GET SELECTED SCOUT === + % Get selected scouts + [sScout, iScout] = GetSelectedScouts(); + if isempty(sScout) + java_dialog('warning', 'No scout selected.', 'Center MRI on scout'); + return + elseif (length(sScout) > 1) + % More than one scout selected: select only the first one + sScout = sScout(1); + iScout = iScout(1); + SetSelectedScouts(iScout); + end + % === GET FIGURE === + % Get current 3D figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + java_dialog('warning', 'No 3D figure.', 'Center MRI on scout'); + return + end + % Get figure type + FigureId = getappdata(hFig, 'FigureId'); + % Get anatomy surface + [sMri, TessInfo, iAnatomy] = panel_surface('GetSurfaceMri', hFig); + if isempty(iAnatomy) + java_dialog('warning', 'No MRI displayed in current figure.', 'Center MRI on scout'); + return + end + % === CENTER MRI VIEW === + % Get MRI structure + sMri = bst_dataSetsManager('GetMri', TessInfo(iAnatomy).SurfaceFile); + % Get cortex surface + sDbCortex = bst_getContext('SurfaceFileByType', TessInfo(iAnatomy).SurfaceFile, 'Cortex'); + sSurfCortex = bst_dataSetsManager('LoadSurface', sDbCortex.FileName); + % Get new slices coordinates + newPosScs = sSurfCortex.Vertices(sScout.Seed,:); + newPosMri = scs2mri(sMri, newPosScs' * 1000)' ./ sMri.Voxsize; + % If figure is a MRIViewer + switch (FigureId.Type) + case 'MriViewer' + gui_figureMriViewer('SetLocation', 'mri', hFig, [], newPosMri); + case '3DViz' + TessInfo(iAnatomy).CutsPosition = round(newPosMri); + gui_figure3DViz('UpdateMriDisplay', hFig, [1 2 3], TessInfo, iAnatomy); + end +end + + +%% ===== EXPAND WITH CORRELATION ===== +function ExpandWithCorrelation() + global GlobalData; + % Stop scout edition + SetSelectionState(0); + % ===== GET ALL NEEDED INFO ===== + % Get selected scouts + [sScout, iScout] = GetSelectedScouts(); + if isempty(sScout) + java_dialog('warning', 'No scout selected.', 'Expand scout using correlation'); + return + elseif (length(sScout) > 1) + % More than one scout selected: select only the first one + sScout = sScout(1); + iScout = iScout(1); + SetSelectedScouts(iScout); + end + + % Get selected figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get results file + ResultsFile = getappdata(hFig, 'ResultsFile'); + if isempty(ResultsFile) + bst_error('No sources displayed in this figure.', 'Expand with correlation', 0); + return + end + + % ===== THRESHOLD ===== + % For selected scout, find sources that are strongly correlated + Threshold = 0.95; + % Ask confirmation of the thresolh level to the user + res = java_dialog('input', 'Thresold value for correlation', 'Sources correlation', [], num2str(Threshold)); + if isempty(res) + return; + end + Threshold = str2num(res); + if isempty(Threshold) + return; + end + + % ===== LOAD RESULTS ===== + % Progress bar + bst_progressBar('start', 'Sources correlation', 'Loading results...'); + % Load results file + [iDS, iResult] = bst_dataSetsManager('LoadResultsFileFull', ResultsFile); + % If no DataSet is accessible : error + if isempty(iDS) + warning(['Cannot load file : "', ResultsFile, '"']); + return + end + % Get results values over the current time window + ResultsValues = bst_dataSetsManager('GetResultsValues', iDS, iResult, [], 'UserTimeWindow'); + + % ===== CORRELATION BETWEEN SOURCES ===== + % Progress bar + nbSources = size(ResultsValues,1); + blockSize = round(nbSources / 100); + bst_progressBar('start', 'Sources correlation', 'Computing correlation...', 0, 100); + % Remove all vertices from initial scout + corrVertices = zeros(1,nbSources); + corrVertices(sScout.Seed) = 1; + % Process each vertex + for iVert = 1:nbSources + if (mod(iVert, blockSize) == 0) + bst_progressBar('inc', 1); + end + if (iVert == sScout.Seed) + continue + end + corr = corrcoef(ResultsValues([sScout.Seed iVert],:)'); + if (abs(corr(2,1)) > Threshold) + corrVertices(iVert) = 1; + end + end + % Final list of scouts + sScout.Vertices = find(corrVertices); + + % ===== DISPLAY ===== + % Update scout + GlobalData.Scouts(iScout) = sScout; + % Display scout patch + PlotScout(iScout); + % Update panel "Scouts" fields + UpdateScoutProperties(); + % Display/hide scouts and update MRI overlay mask + UpdateScoutsDisplay(); + % Hide progress bar + bst_progressBar('stop'); + +end + + +%% ===== SELECT MAXIMUM VALUE ===== +% Usage: SelectMaximumValue(iScout) : Keep only the maximum value in the selected scout +% SelectMaximumValue() : Create new scout with the vertex with maximum value at current time +function SelectMaximumValue(iScout) + global GlobalData; + % Parse input + if (nargin < 1) + isNewScout = 1; + else + isNewScout = 0; + sScout = GetScouts(iScout); + end + % Stop scouts edition + SetSelectionState(0); + % Get current cortical surface + [iSurf, TessInfo] = panel_surface('GetSurfaceCortexOrAnatomy'); + % If no cortex surface available + if isempty(iSurf) || isempty(TessInfo(iSurf).Data) || isempty(TessInfo(iSurf).DataSource.FileName) + java_dialog('warning', 'No 3D figure with sources avaialable.', 'Find maximum value'); + return; + end + + % Get the vertices with maximal value, at the present time ONLY + if isNewScout + % Get surface file to which the scout will be attached + if strcmpi(TessInfo(iSurf).Name, 'Anatomy') + % If anatomy surface : use correspondant cortex surface instead + sSurfCortex = bst_getContext('SurfaceFileByType', TessInfo(iSurf).SurfaceFile, 'Cortex'); + SurfaceFile = sSurfCortex.FileName; + else + SurfaceFile = TessInfo(iSurf).SurfaceFile; + end + % If creating scout: look for max in the whole surface + [valMax, iVertMax] = max(abs(TessInfo(iSurf).Data)); + % Create a new scout with the maximum (Keep only the FIRST maximal vertex) + [sScout, iScout] = CreateNewScout(SurfaceFile, iVertMax(1), iVertMax(1)); + else + % If editing scout: look for max only in the scout's vertices + [valMax, iVertMax] = max(abs(TessInfo(iSurf).Data(sScout.Vertices))); + iVertMax = sScout.Vertices(iVertMax); + % Update scout (Keep only the FIRST maximal vertex) + sScout.Vertices = iVertMax(1); + sScout.Seed = iVertMax(1); + GlobalData.Scouts(iScout) = sScout; + end + + % Display scout patch + PlotScout(iScout); + % Update "Scouts" panel + if isNewScout + UpdatePanel(); + % Select new scout + SetSelectedScouts(iScout); + else + % Update panel "Scouts" fields + UpdateScoutProperties(); + % Display/hide scouts and update MRI overlay mask + UpdateScoutsDisplay(); + end +end + + + + + + + + diff --git a/brainstorm3/toolbox/gui/panel_stat.m b/brainstorm3/toolbox/gui/panel_stat.m new file mode 100644 index 0000000..90ac134 --- /dev/null +++ b/brainstorm3/toolbox/gui/panel_stat.m @@ -0,0 +1,303 @@ +function varargout = panel_stat(varargin) +% PANEL_STAT: Creation and management of samples sets. +% +% USAGE: bstPanelNew = panel_statConditions('CreatePanel') +% panel_statConditions('ResetPanel') + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +fprintf('Karim''s version!!!'); + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CREATE PANEL ===== +function bstPanelNew = CreatePanel() + panelName = 'Statistics'; + % Java initializations + import java.awt.*; + import javax.swing.*; + import org.brainstorm.icon.IconLoader; + import org.brainstorm.tree.*; + import org.brainstorm.dnd.*; + + % CONSTANTS + TB_BUTTON = 23; + jFontText = java.awt.Font('Dialog', java.awt.Font.PLAIN, 10); + % Create topmost panel (BORDER LAYOUT) + jPanelNew = JPanel(BorderLayout()); + % === TOOLBAR === + % Toolbar itself + jToolbarStat = JToolBar('Statistics', JToolBar.VERTICAL); + jToolbarStat.setBorderPainted(0); + jToolbarStat.setFloatable(0); + jToolbarStat.setRollover(1); + jButtonGroupType = ButtonGroup(); + % Button "Recordings" + jButtonRecordings = JToggleButton(IconLoader.ICON_DATA_LIST, 1); + jButtonRecordings.setPreferredSize(Dimension(TB_BUTTON,TB_BUTTON)); + jButtonRecordings.setToolTipText('Process recordings'); + jButtonRecordings.setFocusable(0); + set(jButtonRecordings, 'ActionPerformedCallback', @DataType_Callback); + jButtonGroupType.add(jButtonRecordings); + jToolbarStat.add(jButtonRecordings); + % Button "Sources" + jButtonSources = JToggleButton(IconLoader.ICON_RESULTS_LIST); + jButtonSources.setPreferredSize(Dimension(TB_BUTTON, TB_BUTTON)); + jButtonSources.setToolTipText('Process sources'); + jButtonSources.setFocusable(0); + set(jButtonSources, 'ActionPerformedCallback', @DataType_Callback); + jButtonGroupType.add(jButtonSources); + jToolbarStat.add(jButtonSources); + jToolbarStat.addSeparator(); + + % Button "RUN" + jButtonRun = JButton(IconLoader.ICON_RUN); + jButtonRun.setPreferredSize(Dimension(TB_BUTTON, TB_BUTTON)); + jButtonRun.setToolTipText('Start test'); + jButtonRun.setFocusable(0); + set(jButtonRun, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ButtonRun_Callback)); + jToolbarStat.add(jButtonRun); + jPanelNew.add(jToolbarStat, BorderLayout.WEST); + + % === PANEL "A/B" === + jPanelAB = JPanel(); + jPanelAB.setLayout(BoxLayout(jPanelAB, BoxLayout.LINE_AXIS)); + % === CONDITION A === + jPanelA = JPanel(BorderLayout()); + jPanelA.setBorder(BorderFactory.createTitledBorder('Samples A')); + % Tree of Condition A + jTreeFilesA = BstTree(); + jTreeFilesA.setEditable(0); + % Keyboard callback + set(jTreeFilesA, 'MouseClickedCallback', @(h,ev)gui_stat_common('TreeClicked_Callback', h, ev), ... + 'KeyPressedCallback', @(h,ev)gui_stat_common('TreeKeyboard_Callback', h, ev), ... + 'FocusLostCallback', @(h,ev)jTreeFilesA.getSelectionModel.setSelectionPath([])); + % Configure selection model + jTreeSelModel = jTreeFilesA.getSelectionModel(); + jTreeSelModel.setSelectionMode(jTreeSelModel.DISCONTIGUOUS_TREE_SELECTION); + % Enable drag'n'drop + jTreeFilesA.setDragEnabled(1); + transfHandler = TreeDropTransferHandler(); + jTreeFilesA.setTransferHandler(transfHandler); + set(jTreeFilesA.getModel(), 'TreeStructureChangedCallback', @(h,ev)gui_stat_common('UpdateItemProperties', jTreeFilesA, 'SampleFilesAA')); + % Scroll panel + jScrollListFilesA = JScrollPane(jTreeFilesA); + jPanelA.add(jScrollListFilesA, BorderLayout.CENTER); + jPanelAB.add(jPanelA); + + % === CONDITION B === + jPanelB = JPanel(BorderLayout()); + jPanelB.setBorder(BorderFactory.createTitledBorder('Samples B')); + % Tree of Condition B + jTreeFilesB = BstTree(); + jTreeFilesB.setEditable(0); + % Keyboard callback + set(jTreeFilesB, 'MouseClickedCallback', @(h,ev)gui_stat_common('TreeClicked_Callback', h, ev), ... + 'KeyPressedCallback', @(h,ev)gui_stat_common('TreeKeyboard_Callback', h, ev), ... + 'FocusLostCallback', @(h,ev)jTreeFilesB.getSelectionModel.setSelectionPath([])); + % Configure selection model + jTreeSelModel = jTreeFilesB.getSelectionModel(); + jTreeSelModel.setSelectionMode(jTreeSelModel.DISCONTIGUOUS_TREE_SELECTION); + % Enable drag'n'drop + jTreeFilesB.setDragEnabled(1); + transfHandler = TreeDropTransferHandler(); + jTreeFilesB.setTransferHandler(transfHandler); + set(jTreeFilesB.getModel(), 'TreeStructureChangedCallback', @(h,ev)gui_stat_common('UpdateItemProperties', jTreeFilesB, 'SampleFilesAB')); + % Scroll panel + jScrollListFilesB = JScrollPane(jTreeFilesB); + jPanelB.add(jScrollListFilesB, BorderLayout.CENTER); + jPanelAB.add(jPanelB); + jPanelNew.add(jPanelAB, BorderLayout.CENTER); + + % Create the BstPanel object that is returned by the function + % => constructor BstPanel(jHandle, panelName, sControls) + bstPanelNew = BstPanel(panelName, ... + jPanelNew, ... + struct('jPanelTop', jPanelNew, ... + 'jButtonRecordings', jButtonRecordings, ... + 'jButtonSources', jButtonSources, ... + 'jPanelAB', jPanelAB, ... + 'jTreeFilesA', jTreeFilesA, ... + 'jTreeFilesB', jTreeFilesB)); + + +%% ========================================================================= +% ===== LOCAL CALLBACKS =================================================== +% ========================================================================= +%% ===== CHANGE DATA TYPE ===== + function DataType_Callback(hObject, ev) + bst_progressBar('start', 'Updating samples list', 'Updating samples list...'); + % Update items counts in all trees + gui_stat_common('UpdateItemProperties', jTreeFilesA, 'SampleFilesAA', 1); + gui_stat_common('UpdateItemProperties', jTreeFilesB, 'SampleFilesAB', 1); + bst_progressBar('stop'); + end +end + +%% ========================================================================= +% ===== PROCESSING FUNCTIONS ============================================== +% ========================================================================= +%% ===== RESET PANEL ===== +function ResetPanel(varargin) %#ok + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Statistics'); + % Remove all nodes from all the trees + awtinvoke(ctrl.jTreeFilesA.getModel.getRoot(), 'removeAllChildren()'); + awtinvoke(ctrl.jTreeFilesB.getModel.getRoot(), 'removeAllChildren()'); + % Update all trees + awtinvoke(ctrl.jTreeFilesA, 'refresh()'); + awtinvoke(ctrl.jTreeFilesB, 'refresh()'); +end + + +%% ===== RUN STATS ===== +function ButtonRun_Callback(varargin) +% bst_progressBar('start', 'Initialization', 'Initialization...'); + global GlobalData; + % ===== CHECK INPUTS ===== + % Get conditions + Conditions = gui_stat_common('GetConditions', 'Statistics'); + if isempty(Conditions) + return + end + + % Check samples number + if isempty(Conditions.SamplesA) %|| isempty(Conditions.SamplesB) + bst_error('Empty samples list.', 'Statistics', 0); + return + end + SampleFiles = cat(2, GlobalData.Stat.SampleFilesAA, GlobalData.Stat.SampleFilesAB); + % Check if nothing changed + if ~gui_stat_common('CheckConditions', 'Statistics') + % Empty all samples lists + ResetPanel(); + % Display error message + bst_error(['Database contents changed.' 10 ... + 'Please select again the files you want to process.'], 'Statistics', 0); + return + end + % Check if samples mix zscore and initial values + iZscore = find(~cellfun(@(c)isempty(strfind(c,'_zscore')), SampleFiles)); + iTimeMean = find(~cellfun(@(c)isempty(strfind(c,'_timemean')), SampleFiles)); + iTimeMean = setdiff(iTimeMean, iZscore); + iNormal = setdiff(1:length(SampleFiles), [iZscore, iTimeMean]); + + % If mixed input file types: warning + if (~isempty(iZscore) && ~isempty(iTimeMean)) || (~isempty(iZscore) && ~isempty(iNormal)) || (~isempty(iTimeMean) && ~isempty(iNormal)) + bst_progressBar('hide'); + % Build list of available file tags + fileTags = {'normal'}; + if ~isempty(iZscore) + fileTags{end + 1} = 'zscore'; + end + if ~isempty(iTimeMean) + fileTags{end + 1} = 'timemean'; + end + fileTags{end + 1} = 'all'; + % Ask user to choose between file tags + res = java_dialog('question', ['You mixed file types that cannot be processed together.' 10 ... + 'Please chose one in the list:' 10 10], ... + 'Statistics', [], fileTags, 'normal'); + % Record user selection, or exit if canceled + if isempty(res) + bst_progressBar('stop'); + return; + elseif strcmpi(res, 'all') + GlobalData.Stat.FilterFileTag = ''; + else + GlobalData.Stat.FilterFileTag = ['_' res]; + end + + bst_progressBar('show'); + else + GlobalData.Stat.FilterFileTag = ''; + end + + % ===== RUN TEST ===== + % Get samples + Conditions = gui_stat_common('GetConditions', 'Statistics', GlobalData.Stat.FilterFileTag); + % Display options panel + bstPanel = panel_statRun('CreatePanel', Conditions); + gui_showPanel(bstPanel, 'JavaWindow', 'Statistics', [], 'modal'); + + bst_progressBar('stop'); +end + + +%% ===== GET ROOT NODE ===== +function [nodeRoot, jTree] = GetRootNode(TreeName) %#ok + nodeRoot = []; + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Statistics'); + if isempty(ctrl) + return + end + % Get input tree + switch (TreeName) + case 'StatA' + jTree = ctrl.jTreeFilesA; + case 'StatB' + jTree = ctrl.jTreeFilesB; + end + % Get root node + treeModel = awtinvoke(jTree, 'getModel()'); + nodeRoot = awtinvoke(treeModel, 'getRoot()'); +end + + +%% ===== SET SOURCES/RECORDINGS ===== +% Usage: SetFileType('results') +% SetFileType('data') +function SetFileType(datatype) %#ok + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Statistics'); + % Select corect button + switch lower(datatype) + case 'results' + ctrl.jButtonSources.setSelected(1); + case 'data' + ctrl.jButtonRecordings.setSelected(1); + end +end + + + + + + + + + + \ No newline at end of file diff --git a/brainstorm3/toolbox/gui/panel_statRun.m b/brainstorm3/toolbox/gui/panel_statRun.m new file mode 100644 index 0000000..589b09a --- /dev/null +++ b/brainstorm3/toolbox/gui/panel_statRun.m @@ -0,0 +1,1555 @@ +function varargout = panel_statRun(varargin) +% PANEL_STATRUN: Selection and execution of the process to apply to the samples sets. +% +% USAGE: bstPanelNew = panel_statRun('CreatePanel', panelName) +% panel_statRun('CallBatch') +% panel_statRun('UpdatePanel') +% Comment = panel_statRun('FormatComment', ...) + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CREATE PANEL ===== +function bstPanelNew = CreatePanel(Conditions) %#ok + panelName = 'panel_statRun'; + % Java initializations + import java.awt.*; + import javax.swing.*; + % Constants + HFILLED_WIDTH = 10; + DEFAULT_HEIGHT = 20; + SPINNER_WIDTH = 70; + TEXT_WIDTH = 53; + JCOMBO_DM = java.awt.Dimension(10,25); + jFontText = java.awt.Font('Dialog', java.awt.Font.PLAIN, 10); + windowDim = [350, 0]; + isUpdateAvailable = 0; + + % Get some information about processes + isData = strcmpi(Conditions.DataType, 'data'); + nbSamplesA = length(Conditions.SamplesA); + nbSamplesB = length(Conditions.SamplesB); + [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(Conditions.NbSamplesSets, nbSamplesA, nbSamplesB); + + % ===== GET TIME DEFINITION ===== + % Get first input file time ranges + FileTimeVector = GetFileTimeVector(Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, isData); + % Get default values for baseline + if (FileTimeVector(1) < 0) && (FileTimeVector(end) > 0) + BaselineBounds = [FileTimeVector(1), 0]; + else +% BaselineBounds = [FileTimeVector(1), .8*FileTimeVector(1) + .2*FileTimeVector(end)]; + BaselineBounds = [FileTimeVector(1), FileTimeVector(end)]; + end + + % ===== CREATE PANEL ===== + jPanelNew = getRiverPanel([6,3], [5,5,0,10]); + % === COMMENT === + jPanelNew.add(JLabel('Comment:')); + jTextComment = JTextField(''); + jTextComment.setPreferredSize(Dimension(HFILLED_WIDTH, DEFAULT_HEIGHT)); + jPanelNew.add('hfill', jTextComment); + + % ===== PROCESSES PANEL ===== + jPanelOp = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboTestOp = JComboBox(); + jComboTestOp.setPreferredSize(JCOMBO_DM); + jComboTestOp.setMaximumRowCount(30); + % set(jComboTestOp, 'ItemStateChangedCallback', @UpdatePanel); + jPanelOp.add('hfill', jComboTestOp); + % Fill the combo box + FillProcessComboBox(jComboTestOp, sProcesses); + + % === DESCRIPTION === + jLabelDescriptionOp = JLabel('No process available.'); + jLabelDescriptionOp.setVerticalAlignment(JLabel.TOP); + jPanelOp.add('br hfill', jLabelDescriptionOp); + + jTextFactors = []; + % ===== TABBED PANEL ===== + % If no tests possible: create a flat titled panel + if (Conditions.NbSamplesSets == 1) + % Initialize unsed controls to "Null" + jTabbedStat = []; + jComboTestSimple = []; + jComboTestPermut = []; + jLabelDescriptionSimple = []; + jLabelDescriptionPermut = []; + jSpinnerNbPermut = []; + % Add a title to the panel + jPanelOp.setPreferredSize(Dimension(150,120)); + jPanelOp.setBorder(javax.swing.BorderFactory.createTitledBorder('Process selection')); + jPanelNew.add('br hfill', jPanelOp); + windowDim(2) = 470; + % Else: Tabbed pane + else + jTabbedStat = JTabbedPane(); + % set(jTabbedStat, 'StateChangedCallback', @UpdatePanel); + % PROCESSES PANEL + jTabbedStat.addTab('Processes', jPanelOp); + % ===== SIMPLE TESTS ===== + jPanelSimple = getRiverPanel([10,10], [0,20,5,20]); + % === TEST TYPE === + % Statistics type + jComboTestSimple = JComboBox(); + jComboTestSimple.setPreferredSize(JCOMBO_DM); + % set(jComboTestSimple, 'ItemStateChangedCallback', @UpdatePanel); + jPanelSimple.add('hfill', jComboTestSimple); + % Fill the combo box + FillProcessComboBox(jComboTestSimple, sSimpleTests); + + % === DESCRIPTION === + jLabelDescriptionSimple = JLabel('No test available.'); + jLabelDescriptionSimple.setVerticalAlignment(JLabel.TOP); + jPanelSimple.add('br hfill', jLabelDescriptionSimple); + jTabbedStat.addTab('Simple tests', jPanelSimple); + + % ===== PERMUTATION TESTS ===== + jPanelPermut = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboTestPermut = JComboBox(); + jComboTestPermut.setPreferredSize(JCOMBO_DM); + % set(jComboTestPermut, 'ItemStateChangedCallback', @UpdatePanel); + jPanelPermut.add('hfill', jComboTestPermut); + % Fill the combo box + FillProcessComboBox(jComboTestPermut, sPermTests); + + % === NUMBER OF PERMUTATIONS === + jPanelPermut.add('br', JLabel('Number of permutations: ')); + spinmodel = SpinnerNumberModel(10000, 1, 50000, 100); + jSpinnerNbPermut = JSpinner(spinmodel); + jSpinnerNbPermut.setPreferredSize(Dimension(SPINNER_WIDTH, DEFAULT_HEIGHT)); + jPanelPermut.add(jSpinnerNbPermut); + + % === DESCRIPTION === + jLabelDescriptionPermut = JLabel('No test available.'); + jLabelDescriptionPermut.setVerticalAlignment(JLabel.TOP); + jPanelPermut.add('br hfill', jLabelDescriptionPermut); + + jTabbedStat.addTab('Permutations', jPanelPermut); + + + % ===== ANOVA ===== + jPanelAnova = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboAnova= JComboBox(); + jComboAnova.setPreferredSize(JCOMBO_DM); + set(jComboAnova, 'ItemStateChangedCallback', @UpdatePanel); + jPanelPermut.add('hfill', jComboAnova); + % Fill the combo box + FillProcessComboBox(jComboAnova, sAnova); + + % === FACTORS === + jPanelAnova.add('br', JLabel('Factors: ')); + % # of subjects: + NS = numel(unique({Conditions.SamplesA.SubjectName})); + + [u,i,j] = unique([Conditions.SamplesA.iItem]) + if numel(u)>1 + Comments = bst_getContext('Study', [Conditions.SamplesA.iStudy]); + Comments = [Comments.Data]; + + cellfun2('getfield', cellfun2('fliplr', getfield2(bst_getContext('Study', [Conditions.SamplesA.iStudy]), 'Data')), 'Comment')' + + SelectedItem = listdlg('ListString', ... + [strvcat({Conditions.SamplesA(i).Condition}) repmat(' : ',length(u),1) strvcat({Conditions.SamplesA(i).Comment})],... + 'SelectionMode','single', 'Name', 'Pick an inverse model'); + if isempty(SelectedItem) + return + end + Conditions.SamplesA = Conditions.SamplesA(j == SelectedItem); + assignin('base', 'sA', Conditions.SamplesA); + end + % Get samples + %GlobalData.Stat.FilterFileTag = ['_timemean' ]; + %Conditions = gui_stat_common('GetConditions', 'Statistics', GlobalData.Stat.FilterFileTag); + + tbl.h{1}='Condition'; + tbl.t = {Conditions.SamplesA.Condition}; + tbl.t = tbl.t(:) + + if NS > 1 + tbl.t = tbl.t(1+[0:3]*NS) + end + %tbl.h{end+1}='Comment'; + %tbl.t(:,end+1) = {Conditions.SamplesA(1+[0:3]*15).Comment}; + tbl.h{end+1}='Factor 1'; + tbl.t(:,end+1)={ '1' ; '2' ; '1' ; '2' }; + tbl.h{end+1}='Factor 2'; + tbl.t(:,end+1)={ '1' ; '1' ; '2' ; '2' }; + + jTableFactors = JTable(tbl.t,tbl.h); + jTableFactors.setPreferredSize(Dimension(4*SPINNER_WIDTH, 5*DEFAULT_HEIGHT)); + jPanelAnova.add('br', jTableFactors); + + % === DESCRIPTION === + jLabelDescriptionAnova = JLabel('No option available.'); + jLabelDescriptionAnova.setVerticalAlignment(JLabel.TOP); + jPanelAnova.add('br hfill', jLabelDescriptionAnova); + + jTabbedStat.addTab('ANOVA', jPanelAnova); + jTabbedStat.setEnabledAt(3, 1); + + % Statistical tests : min two samples in each condition + if (nbSamplesA <= 1) || (nbSamplesB <= 1) + % Disable "simple tests" and "permutations" tabs if not enough samples + jTabbedStat.setEnabledAt(1, 0); + jTabbedStat.setEnabledAt(2, 0); + end + jTabbedStat.setPreferredSize(Dimension(150,175)); + jPanelNew.add('br hfill', jTabbedStat); + windowDim(2) = 350; + end + + % === TIME WINDOWS === + jPanelTimeWindows = getRiverPanel([2,3], [0,18,10,0], 'Time windows'); + % === WINDOW A === + jLabelTimeA = JLabel('Time window: '); + jPanelTimeWindows.add(jLabelTimeA); + % Time window A : START + jTextTimeStartA = JTextField(''); + jTextTimeStartA.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStartA.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStartA.setFont(jFontText); + jPanelTimeWindows.add('tab', jTextTimeStartA); + jLabelSeparatorA = JLabel('-'); + jPanelTimeWindows.add(jLabelSeparatorA); + % Time window A : STOP + jTextTimeStopA = JTextField(''); + jTextTimeStopA.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStopA.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStopA.setFont(jFontText); + jPanelTimeWindows.add(jTextTimeStopA); + + % Set time controls callbacks + TimeUnit = gui_validateText(jTextTimeStartA, [], [], FileTimeVector, [], jTextTimeStopA, FileTimeVector(1), @UpdatePanel); + TimeUnit = gui_validateText(jTextTimeStopA, [], [], FileTimeVector, jTextTimeStartA, [], FileTimeVector(end), @UpdatePanel); + % Display time unit + jLabelTimeUnitA = JLabel(TimeUnit); + jPanelTimeWindows.add(jLabelTimeUnitA); + + % === WINDOW B === + jLabelTimeB = JLabel('Baseline: '); + jPanelTimeWindows.add('br', jLabelTimeB); + % Time window B : START + jTextTimeStartB = JTextField(''); + jTextTimeStartB.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStartB.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStartB.setFont(jFontText); + jPanelTimeWindows.add('tab', jTextTimeStartB); + jLabelSeparatorB = JLabel('-'); + jPanelTimeWindows.add(jLabelSeparatorB); + % Time window B : STOP + jTextTimeStopB = JTextField(''); + jTextTimeStopB.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStopB.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStopB.setFont(jFontText); + jPanelTimeWindows.add(jTextTimeStopB); + + % Set time controls callbacks + gui_validateText(jTextTimeStartB, [], [], FileTimeVector, [], jTextTimeStopB, BaselineBounds(1), []); + gui_validateText(jTextTimeStopB, [], [], FileTimeVector, jTextTimeStartB, [], BaselineBounds(2), []); + % Display time unit + jLabelTimeUnitB = JLabel(TimeUnit); + jPanelTimeWindows.add(jLabelTimeUnitB); + jPanelNew.add('br hfill', jPanelTimeWindows); + + % ===== SOURCES PANEL ===== + jPanelSources = getRiverPanel([0,0], [0,0,0,0], 'Sources'); + jCheckAbsoluteValues = JCheckBox('Use absolute values of sources activations'); + jCheckAbsoluteValues.setMargin(Insets(0,10,0,0)); + set(jCheckAbsoluteValues, 'ActionPerformedCallback', @CheckAbsoluteValues_Callback); + jPanelSources.add(jCheckAbsoluteValues); + % Add panel only if processing sources (results) + if ~isData + jPanelNew.add('br hfill', jPanelSources); + jCheckAbsoluteValues.setSelected(1); + windowDim(2) = windowDim(2) + 70; + else + jCheckAbsoluteValues.setVisible(0); + jCheckAbsoluteValues.setSelected(0); + end + + % ===== CLUSTER PANEL CONFIG ===== + jCheckCluster = []; + jCheckAvgCluster = []; + jListCluster = []; + iScouts = []; + if (Conditions.NbSamplesSets == 1) + errMsg = ''; + % === ELECTRODES CLUSTERS === + if isData + clusterType = 'Cluster'; + % Get all available clusters for these results + [sClusters, iClusters] = GetClusters(Conditions); + % ERROR 1 + if isnumeric(sClusters) && (sClusters == -1) + errMsg = 'No channel file available for at least one file.'; + % ERROR 2 + elseif isnumeric(sClusters) && (sClusters == -2) + errMsg = 'No cluster available. Use "Cluster" tab to create one.'; + % SUCCESS: Get selected clusters + else + [tmp__, iSelect] = panel_clusters('GetSelectedClusters'); + end + + % === SCOUTS === + else + clusterType = 'Scout'; + % Get selected scouts + [sClusters, iClusters] = GetScouts(Conditions); + [sSelClusters, iSelClusters] = panel_scouts('GetSelectedScouts'); + % ERROR 1 + if isnumeric(sClusters) && (sClusters == -1) + errMsg = 'The sources files were not computed for the same cortical surface.'; + % ERROR 2 + elseif isnumeric(sClusters) && (sClusters == -2) + errMsg = 'No scout available. Use "Scout" tab to create one.'; + % SUCCESS: Get selected scouts + else + iSelect = find(ismember(iClusters, iSelClusters)); + end + end + + % Create panel + jPanelCluster = getRiverPanel([0,0], [0,12,0,12], [clusterType 's']); + % If error: just add show the error message + if ~isempty(errMsg) + windowDim(2) = windowDim(2) + 50; + jPanelCluster.add(JLabel([' ' errMsg])); + % Else: clusters are available + else + windowDim(2) = windowDim(2) + 120; + % Use only selected scouts/clusters + jCheckCluster = JCheckBox(['Use only selected ' clusterType 's']); + jPanelCluster.add(jCheckCluster); + % Average cluster checkbox + if (length(sClusters) > 1) + jCheckAvgCluster = JCheckBox(['Merge selected ' clusterType 's'], 0); + %jPanelCluster.setMargin(Insets(0,12,0,15)); + jPanelCluster.add(jCheckAvgCluster); + end + + % === JLIST: CLUSTERS === + % Create list (display labels of all clusters) + paddedLabels = cellfun(@(c)cat(2,' ',c,' '),{sClusters.Label}, 'UniformOutput', 0); + jListCluster = JList(paddedLabels); + jListCluster.setLayoutOrientation(jListCluster.HORIZONTAL_WRAP); + jListCluster.setVisibleRowCount(-1); + % Pre-select clusters that are selected in the GUI + if ~isempty(iSelect) + jListCluster.setSelectedIndices(iSelect - 1); + end + % Create scroll panel + jScrollPanelCluster = JScrollPane(jListCluster); + jPanelCluster.add('br hfill vfill', jScrollPanelCluster); + end + jPanelNew.add('br vfill hfill', jPanelCluster); + end + + % ===== OUTPUT PANEL ===== + if (Conditions.NbSamplesSets == 1) + jPanelOutput = getRiverPanel([0,3], [0,10,10,10], 'Output'); + buttonGroupOutput = ButtonGroup(); + % OUTPUT: Brainstorm Database + jRadioOutputDatabase = JRadioButton('Brainstorm database', 1); + jRadioOutputDatabase.setToolTipText(['Brainstorm database:
' ... + 'All the files that are generated are automatically added to database.

'... + ' - One output file:
' ... + 'Most of the processes produce only one file that is stored either,
' ... + 'in the original condition or in an "Analysis" node.

' ... + ' - Multiple output files:
' ... + 'The processes that are marked "[sample by sample]" produce one file
' ... + 'for each file A (or couple of files A/B) in the sample list.']); + buttonGroupOutput.add(jRadioOutputDatabase); + jPanelOutput.add(jRadioOutputDatabase); + % Overwrite original files + jPanelOutput.add('br', JLabel(' ')); + jCheckOverwriteFiles = JCheckBox('Overwrite initial files', 1); + jPanelOutput.add(jCheckOverwriteFiles); + % OUTPUT: Condition path (check) + jPanelOutput.add('br', JLabel(' ')); + jCheckOutputCond = JCheckBox('Select output condition'); + jPanelOutput.add(jCheckOutputCond); + % OUTPUT: Condition path (text) + jTextOutputCond = JTextField(''); + jTextOutputCond.setMargin(Insets(0,0,0,20)); + jPanelOutput.add('hfill', jTextOutputCond); + % OUTPUT: User file + jRadioOutputFile = JRadioButton('User defined file: All data is stored in one unique file'); + buttonGroupOutput.add(jRadioOutputFile); + jPanelOutput.add('br', jRadioOutputFile); + % OUTPUT: Matlab variable + jRadioOutputMatlab = JRadioButton('Export to a Matlab variable'); + buttonGroupOutput.add(jRadioOutputMatlab); + jPanelOutput.add('br', jRadioOutputMatlab); + jPanelNew.add('br hfill', jPanelOutput); + % Callbacks + set(jRadioOutputDatabase, 'ActionPerformedCallback', @UpdateOutput); + set(jRadioOutputFile, 'ActionPerformedCallback', @UpdateOutput); + set(jRadioOutputMatlab, 'ActionPerformedCallback', @UpdateOutput); + set(jCheckOverwriteFiles, 'ActionPerformedCallback', @UpdateOutput); + set(jCheckOutputCond, 'ActionPerformedCallback', @UpdateOutput); + else + jRadioOutputDatabase = []; + jRadioOutputFile = []; + jRadioOutputMatlab = []; + jCheckOverwriteFiles = []; + jCheckOutputCond = []; + jTextOutputCond = []; + end + + % ===== VALIDATION BUTTONS ===== + % Help + jButtonHelp = JButton('Help'); + jButtonHelp.setForeground(Color(.7, 0, 0)); + if (Conditions.NbSamplesSets == 1) + set(jButtonHelp, 'ActionPerformedCallback', @(h,ev)bst_help('PanelStatRunProcess.html', 1)); + else + set(jButtonHelp, 'ActionPerformedCallback', @(h,ev)bst_help('PanelStatRunStat.html', 1)); + end + jPanelNew.add('br right', jButtonHelp); + % Cancel + jButtonCancel = JButton('Cancel'); + set(jButtonCancel, 'ActionPerformedCallback', @ButtonCancel_Callback); + jPanelNew.add(jButtonCancel); + % Run + jButtonRun = JButton('Run'); + set(jButtonRun, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ButtonRun_Callback)); + jPanelNew.add(jButtonRun); + + % Set main panel size + jPanelNew.setPreferredSize(Dimension(windowDim(1), windowDim(2))); + + % Create the BstPanel object that is returned by the function + % => constructor BstPanel(jHandle, panelName, sControls) + bstPanelNew = BstPanel(panelName, ... + jPanelNew, ... + struct('jListCluster', jListCluster)); + + % Set UpdatePanel callbacks + set(jComboTestOp, 'ItemStateChangedCallback', @ComboUpdatePanel); + set(jComboTestPermut, 'ItemStateChangedCallback', @ComboUpdatePanel); + set(jComboTestSimple, 'ItemStateChangedCallback', @ComboUpdatePanel); + set(jCheckCluster, 'ActionPerformedCallback', @UpdatePanel); + set(jTabbedStat, 'StateChangedCallback', @UpdatePanel); + % Update panel + drawnow(); + isUpdateAvailable = 1; + UpdatePanel(); + + + +%% ================================================================================= +% === INTERNAL CALLBACKS ========================================================== +% ================================================================================= +%% ===== COMBOBOX : UPDATE PANEL ===== + function ComboUpdatePanel(hObject, ev) + if (ev.getStateChange() == ev.SELECTED) + UpdatePanel(); + end + end + +%% ===== CHECKBOX : "ABSOLUTE VALUES" ===== + function CheckAbsoluteValues_Callback(varargin) + if ~jCheckAbsoluteValues.isSelected() + isConfirmed = java_dialog('confirm', ['Please keep this option selected, unless you know exactly what you are doing.' 10 10 ... + 'Are you sure you want to use relative values for sources activations ?'], 'Processes'); + if ~isConfirmed + jCheckAbsoluteValues.setSelected(1); + end + end + end + +%% ===== UPDATE OUTPUT PANEL ===== + function UpdateOutput(varargin) + % Force condition path + isDatabase = jRadioOutputDatabase.isEnabled() && jRadioOutputDatabase.isSelected(); + jCheckOutputCond.setEnabled(isDatabase); + jTextOutputCond.setEnabled(isDatabase); + if ~isDatabase + jCheckOutputCond.setSelected(0); + end + % Condition path + isForceCond = jCheckOutputCond.isSelected(); + jTextOutputCond.setVisible(isForceCond); + % Cannot select both options at the same time + if isForceCond + jCheckOverwriteFiles.setSelected(0); + end + end + +%% ===== FILL PROCESSES COMBO BOX ===== + function FillProcessComboBox(jCombo, sList) + import org.brainstorm.list.BstListItem; + % Fill the combo box + for i = 1:length(sList) + % Convert labels to HTML + label = sList(i).Comment; + if isempty(sList(i).Name) + label = ['

' label]; + else + label = ['

' label]; + end + % Add item in combo list + jCombo.addItem(BstListItem(sList(i).Name, '', label, sList(i).Description)); + end + end + +%% ===== RUN ===== + function ButtonRun_Callback(varargin) + CallBatch(); + end + +%% ===== GET SELECTED PROCESS ===== + function [sProcess, selectedTab] = GetSelectedProcess() + % Get selected tab + if isempty(jTabbedStat) + selectedTab = 0; + else + selectedTab = jTabbedStat.getSelectedIndex(); + end + % Get the selected combo box + switch (selectedTab) + case 0 + jCombo = jComboTestOp; + sList = sProcesses; + case 1 + jCombo = jComboTestSimple; + sList = sSimpleTests; + case 2 + jCombo = jComboTestPermut; + sList = sPermTests; + case 3 + jCombo = jComboAnova; + sList = sAnova; + end + % Get selected process + jItem = jCombo.getSelectedItem(); + if isempty(jItem) + sProcess = []; + return + end + processName = jItem.getType(); + % Find in it in processes list + iProcess = find(strcmpi({sList.Name}, processName)); + sProcess = sList(iProcess(1)); + end + +%% ===== UPDATE PANEL ===== + function UpdatePanel(varargin) + if ~isUpdateAvailable + return + end + % Get selected process + [sProcess, selectedTab] = GetSelectedProcess(); + if isempty(sProcess) + return + end + isProcessTitle = isempty(sProcess.Category); + % Convert description to HTML + processDesc = ['' strrep(sProcess.Description, char(10), '
')]; + % Update tabbed panels + switch(selectedTab) + % === PROCESSES === + case 0 + jLabelDescriptionOp.setText(processDesc); + % === SIMPLE TESTS === + case 1 + jLabelDescriptionSimple.setText(processDesc); + % === PERM TESTS === + case 2 + jLabelDescriptionPermut.setText(processDesc); + % Compute maximum number of permutations + Na = nbSamplesA; + Nb = nbSamplesB; + if sProcess.isPaired + % nbPermMax = 2^(Na)-1; + nbPermMax = 2^(Na-1)-1; + else + nbPermMax = factorial(Na+Nb) / (factorial(Na)*factorial(Nb)) - 1; + end + % Limit default number of permutations + NB_PERM_LIMIT = 10000; + nbPerm = min(nbPermMax, NB_PERM_LIMIT); + % Update spinner model + spinmodel = awtinvoke(jSpinnerNbPermut, 'getModel()'); + awtinvoke(spinmodel, 'setValue(Ljava.lang.Object;)', java.lang.Double(nbPerm)); + awtinvoke(spinmodel, 'setMaximum(Ljava.lang.Comparable;)', java.lang.Double(nbPermMax)); + end + + % ===== UPDATE COMMENT ===== + % Get time + TimeRange = GetTimeWindows(TimeUnit); + % Format comment + Comment = FormatComment(sProcess, Conditions, TimeRange); + % Too long comment + if (length(Comment) > 80) + % Replace comment by date + c = clock; + strTime = sprintf('%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + Comment = [sProcess.Name ': ' strTime]; + end + % Update comment + awtinvoke(jTextComment, 'setText(Ljava.lang.String;)', Comment); + + % ===== UPDATE TIME WINDOW PANEL ===== + if ~isempty(jTextTimeStartB) + % Time window + jLabelTimeA.setEnabled(~isProcessTitle); + jTextTimeStartA.setEnabled(~isProcessTitle); + jTextTimeStopA.setEnabled(~isProcessTitle); + jLabelSeparatorA.setEnabled(~isProcessTitle); + jLabelTimeUnitA.setEnabled(~isProcessTitle); + % Baseline + jLabelTimeB.setEnabled(sProcess.UseBaseline); + jTextTimeStartB.setEnabled(sProcess.UseBaseline); + jTextTimeStopB.setEnabled(sProcess.UseBaseline); + jLabelSeparatorB.setEnabled(sProcess.UseBaseline); + jLabelTimeUnitB.setEnabled(sProcess.UseBaseline); + end + + % ===== UPDATE SOURCES PANEL ===== + jCheckAbsoluteValues.setSelected(sProcess.isSourceAbsolute > 0); + jCheckAbsoluteValues.setEnabled(sProcess.isSourceAbsolute ~= 2); + + % ===== UPDATE CLUSTER PANEL ===== + % Cluster checkbox + isAllowCluster = ismember(sProcess.Category, {'Extract'}); + if ~isempty(jCheckCluster) + jCheckCluster.setEnabled(isAllowCluster); + if ~isAllowCluster + jCheckCluster.setSelected(0); + end + % Cluster jlists + isCluster = ~isempty(jCheckCluster) && jCheckCluster.isSelected(); + if ~isempty(jListCluster) + jListCluster.setEnabled(isCluster); + end + if ~isempty(jCheckAvgCluster) + jCheckAvgCluster.setEnabled(isCluster); + end + else + isCluster = 0; + end + + % ===== UPDATE OUTPUT PANEL ===== + if ~isempty(jRadioOutputDatabase) + AllowExport = ismember(sProcess.Category, {'Extract'}); + % Enable Database: only if no cluster defined + jRadioOutputDatabase.setEnabled(~isCluster && ~isProcessTitle); + % Enable File/Matlab + jRadioOutputFile.setEnabled(AllowExport > 0); + jRadioOutputMatlab.setEnabled(AllowExport > 0); + % Select "File": if cluster, or time/mean, time/var, or extract + if (isCluster || AllowExport) + % Change selection only if Database is selected + if ~jRadioOutputMatlab.isSelected() + jRadioOutputFile.setSelected(1); + end + else + jRadioOutputDatabase.setSelected(1); + end + + % "Overwrite file" checkbox + AllowOverwrite = ismember(sProcess.Category, {'Filter'}); + isOverwriteEnabled = jRadioOutputDatabase.isEnabled() && AllowOverwrite; + jCheckOverwriteFiles.setEnabled(isOverwriteEnabled); + isOverwriteSelected = isOverwriteEnabled && sProcess.DefaultOverwrite; + jCheckOverwriteFiles.setSelected(isOverwriteSelected); + % Update object selections + UpdateOutput(); + end + end + + +%% ===== GET TIME WINDOWS ===== + function [Time, Baseline, iTime, iBaseline] = GetTimeWindows(TimeUnit) + % Get time window to process + Time = [getValue(jTextTimeStartA), getValue(jTextTimeStopA)]; + % Get baseline, if defined + if ~isempty(jTextTimeStartB) + Baseline = [getValue(jTextTimeStartB), getValue(jTextTimeStopB)]; + else + Baseline = []; + end + % Apply correct time units + switch(TimeUnit) + case 'ms' + % Convert miliseconds -> seconds + Time = Time / 1000; + Baseline = Baseline / 1000; + otherwise + % Nothing to do + end + % Get indices in intial FileTimeVector + iTimeBounds = findclosest(Time, FileTimeVector); + % If whole data wanted and sampling frequency very high: might lack of time precision... + % Try to correct this and select the last sample if it is obviously this that the user wants + if (iTimeBounds(2) ~= length(FileTimeVector)) && (FileTimeVector(end)-FileTimeVector(iTimeBounds(2)) < 1e-5) + iTimeBounds(2) = length(FileTimeVector); + end + % Build time indices + iTime = iTimeBounds(1) : iTimeBounds(2); + iBaselineBounds = findclosest(Baseline, FileTimeVector); + iBaseline = iBaselineBounds(1) : iBaselineBounds(2); + end + +%% ===== GET VALUES ===== + function val = getValue(jText) + % Get and check value + val = str2double(char(jText.getText())); + if isnan(val) || isempty(val) + val = []; + end + end + + +%% ===== COMPUTE TEST ===== + function CallBatch() + % ===== PREPARE OPTIONS ===== + OPTIONS = struct(); + % Is processing recordings or results + OPTIONS.isData = isData; + % Get new file comment + OPTIONS.Comment = deblank(strtrim(char(jTextComment.getText()))); + % Is absolute values (for sources only) + OPTIONS.isAbsoluteValues = ~isData && jCheckAbsoluteValues.isSelected(); + % Get selected process + [OPTIONS.sProcess, selectedTab] = GetSelectedProcess(); + if isempty(OPTIONS.sProcess) || isempty(OPTIONS.sProcess.Name) + bst_error('Please select a process.', 'Processes', 0); + return + end + % Get number of permutations + if ~isempty(jSpinnerNbPermut) + OPTIONS.nbPermutation = jSpinnerNbPermut.getValue(); + else + OPTIONS.nbPermutation = 0; + end + % List factors associated with each dataset + if ~isempty(jTextFactors) + OPTIONS.Factors= char(jTextFactors.getText()); + else + OPTIONS.Factors = []; + end + + % Overwrite initial files ? + OPTIONS.isOverwriteFiles = ~isempty(jCheckOverwriteFiles) && jCheckOverwriteFiles.isSelected(); + % Get output mode + if isempty(jRadioOutputDatabase) || jRadioOutputDatabase.isSelected() + OPTIONS.OutputType = 'database'; + elseif jRadioOutputFile.isSelected() + OPTIONS.OutputType = 'file'; + elseif jRadioOutputMatlab.isSelected() + OPTIONS.OutputType = 'matlab'; + end + % Force output condition + if ~isempty(jCheckOutputCond) && jCheckOutputCond.isSelected() + % Get the user defined condition name + outputCond = char(jTextOutputCond.getText()); + % Split condition path + condPath = strSplit(outputCond); + % Check if condition name is valid + if isempty(outputCond) || (~strcmpi(outputCond,'@inter') && (length(condPath) ~= 2)) + bst_error(['Invalid condition path.' 10 10 ... + 'Condition path must be one the following:' 10 ... + ' - SubjectName/ConditionName' 10 ... + ' - SubjectName/@intra' 10 ... + ' - @inter'], 'Processes', 0); + return + end + % === Convert SubjectName in SubjectPath === + if (length(condPath) == 2) + % Get subject and condition names + SubjectName = condPath{1}; + ConditionName = condPath{2}; + % Get subject + sSubject = bst_getContext('Subject', SubjectName, 1); + if isempty(sSubject) + bst_error(['Subject does not exist: "' SubjectName '"'], 'Processes', 0); + return + end + % Build new output condition path + SubjectPath = fileparts(sSubject.FileName); + outputCond = fullfile(SubjectPath, ConditionName); + end + % Valid + OPTIONS.ForceOutputCond = outputCond; + else + OPTIONS.ForceOutputCond = []; + end + % Is "Cluster" analysis + OPTIONS.isCluster = ~isempty(jCheckCluster) && jCheckCluster.isSelected(); + OPTIONS.isClusterAverage = OPTIONS.isCluster && ~isempty(jCheckAvgCluster) && jCheckAvgCluster.isSelected(); + % Get selected clusters + if OPTIONS.isCluster + if OPTIONS.isData + % Get selected clusters + iClusters = jListCluster.getSelectedIndices() + 1; + sClusters = panel_clusters('GetClusters', iClusters); + % If no cluster selected: ERROR + if isempty(iClusters) + error('No channel selected in cluster panel.'); + end + % If user asked to merge clusters + if OPTIONS.isClusterAverage + sClustersAvg.Sensors = unique(cat(2, sClusters.Sensors)); + sClustersAvg.Label = ['Clusters:', sprintf(' %s', sClusters.Label)]; + OPTIONS.Clusters = sClustersAvg; + else + OPTIONS.Clusters = sClusters; + end + % Get clusters options + OPTIONS.ClustersOptions = panel_clusters('GetClusterDisplayType'); + else + % Get selected scouts + iSelScouts = jListCluster.getSelectedIndices() + 1; + % If no scout selected: ERROR + if isempty(iSelScouts) + error('No scout selected in cluster panel.'); + end + % Get scouts description + [sScouts, iScouts] = panel_scouts('GetCurrentScouts'); + iScouts = iScouts(iSelScouts); + sScouts = panel_scouts('GetScouts', iScouts); + % If user asked to merge scouts + if OPTIONS.isClusterAverage + sScoutsAvg = sScouts(1); + sScoutsAvg.Vertices = unique([sScouts.Vertices]); + sScoutsAvg.Label = ['Scouts:', sprintf(' %s', sScouts.Label)]; + OPTIONS.Clusters = sScoutsAvg; + else + OPTIONS.Clusters = sScouts; + end + % Get scouts options + OPTIONS.ClustersOptions = panel_scouts('GetScoutDisplayType'); + end + else + OPTIONS.sClusters = []; + OPTIONS.ClustersOptions = []; + end + % Get time + [OPTIONS.Time, OPTIONS.Baseline, OPTIONS.iTime, OPTIONS.iBaseline] = GetTimeWindows(TimeUnit); + + % Get files to batch + OPTIONS.Conditions = Conditions; + % Close panel + gui_hidePanel('panel_statRun'); + + % ===== PERFORM SOME VERIFICATIONS ===== + % Not supposed to compute zscore on recordings + if OPTIONS.isData && strcmpi(OPTIONS.sProcess.Name, 'zscore') + res = java_dialog('confirm', ['Warning: You are about to compute the z-score normalization on recordings.' 10 10 ... + 'We recommand first to solve the inverse problem, and then to ' 10 ... + 'apply the zscore normalization on the cortical sources.' 10 10 ... + 'Are you sure you want to compute the z-score of the recordings ?'], 'Warning'); + if ~res + return; + end + end + + % ===== CALL BATCH FUNCTION ===== + bst_batch(OPTIONS); + + % Update "Processes" panels + if OPTIONS.isOverwriteFiles + panel_processes('ResetPanel'); + else + if (Conditions.NbSamplesSets == 1) && ~gui_stat_common('CheckConditions', 'Processes') + panel_processes('ResetPanel'); + elseif (Conditions.NbSamplesSets == 2) && ~gui_stat_common('CheckConditions', 'Statistics') + panel_stat('ResetPanel'); + end + end + end +end + + +%% ================================================================================= +% === EXTERNAL CALLBACKS ========================================================== +% ================================================================================= +%% ===== CANCEL ===== +function ButtonCancel_Callback(varargin) + % Close panel + gui_hidePanel('panel_statRun'); +end + + +%% ===== BUILD LIST OF PROCESSES ===== +% USAGE: [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(NbSamplesSets, nbSamplesA, nbSamplesB, isData) +% [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList('All') +function [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(NbSamplesSets, nbSamplesA, nbSamplesB, isData) + % If get all processes: ignore all other arguments + isAll = strcmpi(NbSamplesSets, 'All'); + % Initialize list + sModel = struct('Name', '', ... + 'Comment', '', ... + 'Description', '', ... + 'FileTag', '', ... + 'Category', '', ... + 'UseBaseline', 0, ... + 'DefaultOverwrite', 0, ... + 'isSourceAbsolute', 1, ... % If value=2, absolute value for sources is FORCED + 'isPaired', 0, ... + 'blockDimension', 0, ... % Dimension in which the data matrix can be split (0=none, 1=channels, 2=time) + 'isAvgRef', 1); % Compute EEG average reference before processing + sProcesses = repmat(sModel, 0); + sSimpleTests = repmat(sModel, 0); + sPermTests = repmat(sModel, 0); + sAnova = repmat(sModel, 0); + + % ===== "A" PROCESSES ===== + if isAll || (NbSamplesSets == 1) + % === FILTERS TO APPLY TO FILES === + sProcess = sModel; + sProcess.Comment = '==== PROCESS FILES ==========='; + sProcess.Description = 'Please select a process...'; + sProcess.isSourceAbsolute = 2; + sProcesses(end + 1) = sProcess; + % Z-SCORE + sProcess = sModel; + sProcess.Name = 'zscore'; + sProcess.Comment = ' Z-score noise normalization'; + sProcess.FileTag = '| zscore'; + sProcess.Description = ['For each channel:' 10 ... + '1) Compute mean m and variance v for baseline.' 10 ... + '2) For each time sample, substract m and divide by v.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.isSourceAbsolute = 2; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % BASELINE REMOVAL + sProcess = sModel; + sProcess.Name = 'baseline'; + sProcess.Comment = ' Remove baseline mean (DC offset)'; + sProcess.FileTag = '| bl'; + sProcess.Description = ['For each channel:' 10 ... + '1) Compute the mean m for the baseline.' 10 ... + '2) For all the time samples, substract m.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.isSourceAbsolute = 0; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % EEG AVERAGE REFERENCE + if isAll || isData + sProcess = sModel; + sProcess.Name = 'avgref'; + sProcess.Comment = ' EEG Average reference'; + sProcess.FileTag = '| avgref'; + sProcess.Description = ['Note that all the processes that are not in the "Process files" category use average reference by default. ' 10 ... + 'No effect on MEG recordings.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 0; + sProcess.isSourceAbsolute = 0; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 2; + sProcesses(end + 1) = sProcess; + end + % BANDPASS FILTERING + sProcess = sModel; + sProcess.Name = 'bandpass'; + sProcess.Comment = ' Bandpass filtering'; + sProcess.FileTag = '| bandpass'; + sProcess.Description = 'Apply a frenquency filter to all the files.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 0; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % SPATIAL SMOOTHING + if isAll || ~isData + sProcess = sModel; + sProcess.Name = 'ssmooth'; + sProcess.Comment = ' Spatial smoothing'; + sProcess.FileTag = '| ssmooth'; + sProcess.Description = 'Spatial smoothing of the sources.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 2; + sProcess.blockDimension = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % RESAMPLE + if isAll || isData + sProcess = sModel; + sProcess.Name = 'resample'; + sProcess.Comment = ' Resample recordings'; + sProcess.FileTag = '| resample'; + sProcess.Description = 'Resample all the files with a new sampling frequency.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 0; + % sProcess.blockDimension = 1; % PROBLEM WITH PROCESSING BY BLOCKS: DIMENSIONS CHANGE + sProcess.blockDimension = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % CUT STIMULATION ARTIFACT + if isAll || isData + sProcess = sModel; + sProcess.Name = 'cutstim'; + sProcess.Comment = ' Cut stimulation artifact'; + sProcess.FileTag = '| cutstim'; + sProcess.Description = ['Remove the values in the "baseline" time window.' 10 ... + 'Replace them with a linear interpolation.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % OPPOSITE VALUES + sProcess = sModel; + sProcess.Name = 'opposite'; + sProcess.Comment = ' Opposite values: -A'; + sProcess.FileTag = '| opposite'; + sProcess.Description = 'Save opposite values for A files.'; + sProcess.Category = 'Filter'; + sProcess.DefaultOverwrite = 1; + sProcess.isSourceAbsolute = 0; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + + % === AVERAGING === + if isAll || (nbSamplesA >= 2) + sProcess = sModel; + sProcess.Comment = '==== AVERAGING ============='; + sProcess.Description = 'Please select a process...'; + sProcess.isSourceAbsolute = 2; + sProcesses(end + 1) = sProcess; + % GRAND-AVERAGE A (MEAN/CONDITION) + sProcess = sModel; + sProcess.Name = 'GAVE'; + sProcess.Comment = ' Average by condition (Grand-average)'; + sProcess.FileTag = ''; + sProcess.Description = ['Grand averages for each condition' 10 ... + 'One output file per condition.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + % AVERAGE BY SUBJECT + sProcess = sModel; + sProcess.Name = 'SubjAvg'; + sProcess.Comment = ' Average by subject'; + sProcess.FileTag = ''; + sProcess.Description = ['Average all the recordings for each subject.' 10 ... + 'One output file per subject.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + % AVERAGE A + sProcess = sModel; + sProcess.Name = 'meanA'; + sProcess.Comment = ' Average everything'; + sProcess.FileTag = '<#A#>'; + sProcess.Description = ['Average of all files.' 10 'Only one output file.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + end + + % === DATA EXTRACTION === + sProcess = sModel; + sProcess.Comment = '==== EXTRACT DATA ==========='; + sProcess.Description = 'Please select a process...'; + sProcess.isSourceAbsolute = 2; + sProcesses(end + 1) = sProcess; + % MEAN FOR A TIME WINDOW + sProcess = sModel; + sProcess.Name = 'timemean'; + sProcess.Comment = ' Average over a time window'; + sProcess.FileTag = '| timemean#TIME#'; + sProcess.Description = ['Average for each file over the selected time window.' 10 ... + 'Use absolute values for sources.']; + sProcess.Category = 'Extract'; + sProcesses(end + 1) = sProcess; + % VARIANCE FOR A TIME WINDOW + sProcess = sModel; + sProcess.Name = 'timevar'; + sProcess.Comment = ' Variance over a time window'; + sProcess.FileTag = '| timevar#TIME#'; + sProcess.Description = 'Variance for each file over the selected time window.'; + sProcess.Category = 'Extract'; + sProcesses(end + 1) = sProcess; + % EXTRACT DATA FROM SAMPLES + sProcess = sModel; + sProcess.Name = 'extract'; + sProcess.Comment = ' Extract data block (cluster,time)'; + sProcess.FileTag = '| extract#TIME#'; + sProcess.Description = 'Get a block of data from each file.'; + sProcess.Category = 'Extract'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + + % === NEUROMAG RECORDINGS === + if isAll || isData + sProcess = sModel; + sProcess.Comment = '==== NEUROMAG RECORDINGS ====='; + sProcess.Description = 'Please select a process...'; + sProcess.isSourceAbsolute = 2; + sProcesses(end + 1) = sProcess; + % GRADIOMETERS NORM + sProcess = sModel; + sProcess.Name = 'gradnorm'; + sProcess.Comment = ' Norm of gradiometers couples'; + sProcess.FileTag = '| gradnorm'; + sProcess.Description = 'Compute the norm for each gradiometer couple.'; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + + % === SPECTRAL ANALYSIS === + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== SPECTRAL ANALYSIS ========'; + sProcess.isSourceAbsolute = 2; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % Frequency-Band SAMPLE SPECTRAL DECOMPOSITION + sProcess = sModel; + sProcess.Name = 'spectDecomp'; + sProcess.Comment = ' Spectral decomposition and statistics'; + sProcess.FileTag = ''; + sProcess.Description = ['Computes power in multiple, standard frequency bands.' 10 ... + 'Yields average, standard deviation and t-statistics across samples.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Spectral'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + + % Power spectrum analysis + sProcess = sModel; + sProcess.Name = 'powerSpectrum'; + sProcess.Comment = ' Fourier magnitude'; + sProcess.FileTag = ''; + sProcess.Description = ['Transforms each time series in file into spectral domain (modulus of Fourier transform). ' ... + 'Time vector is replaced by corresponding frequency bin used in Fourier tranform.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Spectral'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + end + + % === RECURRENCE MAPS=== + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== RECURRENCE MAPS ========'; + sProcess.isSourceAbsolute = 2; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + sProcess = sModel; + sProcess.Name = 'recMaps'; + sProcess.Comment = ' Recurrence maps of activations'; + sProcess.FileTag = ''; + sProcess.Description = ['Computes recurrence maps across samples.' 10 ... + 'Source maps above 75% activation are thresholded and binarized before being summed across samples.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Recurrence'; + sProcess.isSourceAbsolute = 1; + sProcesses(end + 1) = sProcess; + end + + % === SCOUTS functional Connectivity === + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== Scouts f-Connectivity ========'; + sProcess.isSourceAbsolute = 2; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + sProcess = sModel; + sProcess.Name = 'fScoutConnect'; + sProcess.Comment = ' Functional connectivity between cortical scouts'; + sProcess.FileTag = ''; + sProcess.Description = ['Evaluate functional connectivity between cortical scouts.' 10 ... + 'Under development: use with caution.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'fConnectivity'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + end + end + + % ===== "A/B" PROCESSES ===== + if isAll || (NbSamplesSets == 2) + % Differences : same number of samples in each set + if isAll || (nbSamplesA == nbSamplesB) + % DIFFERENCE: A - B + sProcess = sModel; + sProcess.Name = 'diffAB'; + sProcess.Comment = ' A - B'; + sProcess.FileTag = '#A#-#B#'; + sProcess.Description = ['Difference of each couple of samples (A-B).' 10 10 ... + 'Each pair must share the same anatomy.' 10 ... + 'Result is stored in a new condition.']; + sProcess.Category = 'Filter2'; + sProcesses(end + 1) = sProcess; + % AVERAGE: Average(A,B) + sProcess = sModel; + sProcess.Name = 'meanAB'; + sProcess.Comment = ' Average(A,B)'; + sProcess.FileTag = 'Average(#A#,#B#)'; + sProcess.Description = ['Average of each couple of samples (A,B).' 10 10 ... + 'Each pair must share the same anatomy.' 10 ... + 'Result is stored in a new condition.']; + sProcess.Category = 'Filter2'; + sProcesses(end + 1) = sProcess; + end + end + + + % ===== SIMPLE T-TESTS ===== + % NEW: t-test equal variance + sTest = sModel; + sTest.Name = 'ttest'; + sTest.Comment = ' t-test (equal variances)'; + sTest.FileTag = 'ttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for equal variances.' 10 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % NEW: t-test unequal variance + sTest = sModel; + sTest.Name = 'uttest'; + sTest.Comment = ' t-test (unequal variances)'; + sTest.FileTag = 'uttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for unequal variances.' 10 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % Paired t-test and old versions need the same number of samples in both sets + if isAll || (nbSamplesA == nbSamplesB) + % NEW: paired t-test + sTest = sModel; + sTest.Name = 'pttest'; + sTest.Comment = ' t-test (paired)'; + sTest.FileTag = 'pttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for paired samples.' 10 10 ... + 'Use for testing conditions across different subjects.' 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sTest.isPaired = 1; + sSimpleTests(end + 1) = sTest; + % OLD: t-test equal variances + sTest = sModel; + sTest.Name = 'old_ttest'; + sTest.Comment = ' OLD t-test (equal variances)'; + sTest.FileTag = 'old_ttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for equal variances.' 10 10 ... + 'Old version: might be faster and more precise.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % OLD: t-test unequal variance + sTest = sModel; + sTest.Name = 'old_uttest'; + sTest.Comment = ' OLD t-test (unequal variances)'; + sTest.FileTag = 'old_uttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for unequal variances.' 10 10 ... + 'Old version: might be faster and more precise.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % OLD: paired t-test + sTest = sModel; + sTest.Name = 'old_pttest'; + sTest.Comment = ' OLD t-test (paired)'; + sTest.FileTag = 'old_pttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for paired samples.' 10 10 ... + 'Use for testing conditions across different subjects.' 10 ... + 'Old version: might be faster and more precise.']; + sTest.isPaired = 1; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + end + + + % ===== PERMUTATION TESTS ===== + % PERM: t-test (independent) + sTest = sModel; + sTest.Name = 'ttest'; + sTest.Comment = ' t-test (independent)'; + sTest.FileTag = 'ttest: #A# vs. #B#'; + sTest.Description = 'Student''s t-test for independent samples.'; + sTest.Category = 'PermTest'; + sPermTests(end + 1) = sTest; + % PERM: t-test (paired) + sTest = sModel; + sTest.Name = 'pairedttest'; + sTest.Comment = ' t-test (paired)'; + sTest.FileTag = 'pairedttest: #A# vs. #B#'; + sTest.Description = 'Student''s t-test for paired samples.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Sign of the differences + sTest = sModel; + sTest.Name = 'signtest'; + sTest.Comment = ' signtest (paired)'; + sTest.FileTag = 'signtest: #A# vs. #B#'; + sTest.Description = 'Sign of the differences.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Wilcoxon + sTest = sModel; + sTest.Name = 'wilcoxon'; + sTest.Comment = ' wilcoxon (paired)'; + sTest.FileTag = 'wilcoxon: #A# vs. #B#'; + sTest.Description = 'Signed ranks.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Difference of the means + sTest = sModel; + sTest.Name = 'difftest'; + sTest.Comment = ' Difference of the means'; + sTest.FileTag = 'difftest: #A# vs. #B#'; + sTest.Description = 'Difference of the means.'; + sTest.Category = 'PermTest'; + sPermTests(end + 1) = sTest; + + % ===== ANOVA ===== + % + sTest = sModel; + sTest.Name = 'RM-Anova'; + sTest.Comment = 'Anova (under dev.)'; + sTest.FileTag = 'Anova'; + sTest.Description = 'Repeated measures parametric Analysis of Variance'; + sTest.Category = 'Anova'; + sAnova(end + 1) = sTest; + +end + + + +%% ===== FORMAT CONDITIONS STRING ===== +function str = FormatConditionsString(Samples, Default) + % If no samples + if isempty(Samples) + str = ''; + return + end + % Get the best way to display the sets names + uniqueCond = unique({Samples.Condition}); + uniqueSubj = unique({Samples.SubjectName}); + isUniqueCond = (length(uniqueCond) == 1); + isUniqueSubj = (length(uniqueSubj) == 1); + % Switch + if isUniqueCond && isUniqueSubj + str = fullfile(uniqueSubj{1}, uniqueCond{1}); + elseif isUniqueCond + str = uniqueCond{1}; + elseif isUniqueSubj + str = uniqueSubj{1}; + else + str = Default; + end +end + + +%% ===== FORMAT COMMENT ===== +function Comment = FormatComment(sProcess, Conditions, TimeRange) + % ===== BUILD COMMENT STRINGS ===== + sA = Conditions.SamplesA; + sB = Conditions.SamplesB; + CommentA = ''; + CommentB = ''; + % Extract some more information + isSampleBySample = ismember(sProcess.Category, {'Filter2', 'Filter', 'Extract'}); + + % === SAMPLE BY SAMPLE: A/B === + if isSampleBySample && (length(sA) == 1) && (length(sB) == 1) + if strcmpi(sA.SubjectFile, sB.SubjectFile) && strcmpi(sA.Condition, sB.Condition) + CommentA = sA.Comment; + CommentB = sB.Comment; + elseif io_compareFileNames(sA.SubjectFile, sB.SubjectFile) + CommentA = sA.Condition; + CommentB = sB.Condition; + elseif strcmpi(sA.Condition, sB.Condition) + CommentA = fullfile(sA.SubjectName, sA.Condition); + CommentB = fullfile(sB.SubjectName, sB.Condition); + else + CommentA = fullfile(sA.SubjectName, sA.Condition); + CommentB = fullfile(sB.SubjectName, sB.Condition); + end + % === AVERAGE === + elseif ~isSampleBySample + CommentA = FormatConditionsString(sA, 'A'); + CommentB = FormatConditionsString(sB, 'B'); + if strcmpi(CommentA, CommentB) + CommentA = ''; + CommentB = ''; + end + end + + % Build string for time interval + if (max(abs(TimeRange)) > 2) + strTime = sprintf('(%1.2fs,%1.2fs)', TimeRange); + else + strTime = sprintf('(%dms,%dms)', round(TimeRange * 1000)); + end + % Apply process naming + if ~isempty(CommentA) || isempty(sB) + Comment = sProcess.FileTag; + Comment = strrep(Comment, '#A#', CommentA); + Comment = strrep(Comment, '#B#', CommentB); + Comment = strrep(Comment, '#TIME#', strTime); + else + Comment = ''; + end +end + + +%% ===== GET CLUSTERS ===== +% OUTPUT: +% - sClusters : -1, if no channel file available for at least one sample +% -2, if no clusters available +% Else, return an array of Cluster structures +function [sClusters, iClusters] = GetClusters(Cond) + % Get unique list of studies + iStudies = unique([Cond.SamplesA.iStudy, Cond.SamplesB.iStudy]); + % Process all studies + for i = 1:length(iStudies) + % Get study structure + iStudy = iStudies(i); + %sStudy = bst_getContext('Study', iStudy); + sChannel = bst_getContext('ChannelForStudy', iStudy); + % Check that a ChannelFile is defined for this study + if isempty(sChannel) + sClusters = -1; + iClusters = []; + return + end + end + % Get the scouts available for this surface + [sClusters, iClusters] = panel_clusters('GetClusters'); + % If no scout avaialable: error + if isempty(sClusters) + sClusters = -2; + iClusters = []; + return; + end +end + + +%% ===== GET SCOUTS ===== +% OUTPUT: +% - sScouts : -1, if all samples do not refer to the same cortical surface +% -2, if no scout avaialable +% Else, return an array of scout structures +function [sScouts, iScouts] = GetScouts(Cond) + iScouts = []; + % Get studies and results indices + iStudies = [Cond.SamplesA.iStudy, Cond.SamplesB.iStudy]; + iResults = [Cond.SamplesA.iItem, Cond.SamplesB.iItem]; + SurfaceFile = []; + % Process all studies + for i = 1:length(iStudies) + iStudy = iStudies(i); + sStudy = bst_getContext('Study', iStudy); + % Get result file + ResultsMat = in_results_bst(sStudy.Result(iResults(i)).FileName, 0, 'SurfaceFile'); + % If it is first results: store the surface file + if isempty(SurfaceFile) + SurfaceFile = ResultsMat.SurfaceFile; + % If surface file is not the same than previous files: error + elseif ~io_compareFileNames(ResultsMat.SurfaceFile, SurfaceFile) + sScouts = -1; + return + end + end + % Get the scouts available for this surface + [sScouts, iScouts] = panel_scouts('GetScoutsWithSurface', SurfaceFile); + % If no scout avaialable: error + if isempty(sScouts) + sScouts = -2; + return; + end +end + + +%% ================================================================================================ +% ===== HELPERS ================================================================================== +% ================================================================================================ +%% ===== GET FILE TIME VECTOR ===== +function TimeVector = GetFileTimeVector(iStudy, iItem, isData) + TimeVector = []; + % Get protocols directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get study + sStudy = bst_getContext('Study', iStudy); + % Load time range from this file + if (isData) + % Build filename + filename = fullfile(ProtocolInfo.STUDIES, sStudy.Data(iItem).FileName); + % Load time vector + DataMat = load(filename, 'Time'); + if ~isempty(DataMat) && isfield(DataMat, 'Time') && ~isempty(DataMat.Time) + TimeVector = DataMat.Time; + end + else + % Build filename + refFilename = fullfile(ProtocolInfo.STUDIES, sStudy.Result(iItem).FileName); + % Resvole link + refFilename = resolveResultsLink(refFilename); + % Is results file is a kernel-only file + isKernel = ~isempty(strfind(refFilename, 'KERNEL')); + % KERNEL + if isKernel + % No time information available in file => Use DataMat results + DataFile = strrep(sStudy.Result(iItem).DataFile, ProtocolInfo.STUDIES, ''); + DataFileFull = fullfile(ProtocolInfo.STUDIES, DataFile); + DataMat = load(DataFileFull, 'Time'); + if ~isempty(DataMat) && isfield(DataMat, 'Time') && ~isempty(DataMat.Time) + TimeVector = DataMat.Time; + end + % FULL RESULTS FILE + else + % Load time vector + ResultMat = in_results_bst(refFilename, 0, 'ImageGridTime'); + if ~isempty(ResultMat) && isfield(ResultMat, 'ImageGridTime') + TimeVector = ResultMat.ImageGridTime; + end + end + end +end + + diff --git a/brainstorm3/toolbox/gui/panel_statRun.m.orig b/brainstorm3/toolbox/gui/panel_statRun.m.orig new file mode 100644 index 0000000..22c7715 --- /dev/null +++ b/brainstorm3/toolbox/gui/panel_statRun.m.orig @@ -0,0 +1,1547 @@ +function varargout = panel_statRun(varargin) +% PANEL_STATRUN: Selection and execution of the process to apply to the samples sets. +% +% USAGE: bstPanelNew = panel_statRun('CreatePanel', panelName) +% panel_statRun('CallBatch') +% panel_statRun('UpdatePanel') +% Comment = panel_statRun('FormatComment', ...) + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CREATE PANEL ===== +function bstPanelNew = CreatePanel(Conditions) %#ok + panelName = 'panel_statRun'; + % Java initializations + import java.awt.*; + import javax.swing.*; + % Constants + HFILLED_WIDTH = 10; + DEFAULT_HEIGHT = 20; + SPINNER_WIDTH = 70; + TEXT_WIDTH = 53; + JCOMBO_DM = java.awt.Dimension(10,25); + jFontText = java.awt.Font('Dialog', java.awt.Font.PLAIN, 10); + windowDim = [350, 0]; + + % Get some information about processes + isData = strcmpi(Conditions.DataType, 'data'); + nbSamplesA = length(Conditions.SamplesA); + nbSamplesB = length(Conditions.SamplesB); + [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(Conditions.NbSamplesSets, nbSamplesA, nbSamplesB); + + % ===== GET TIME DEFINITION ===== + % Get first input file time ranges + FileTimeVector = GetFileTimeVector(Conditions.SamplesA(1).iStudy, Conditions.SamplesA(1).iItem, isData); + % Get default values for baseline + if (FileTimeVector(1) < 0) && (FileTimeVector(end) > 0) + BaselineBounds = [FileTimeVector(1), 0]; + else +% BaselineBounds = [FileTimeVector(1), .8*FileTimeVector(1) + .2*FileTimeVector(end)]; + BaselineBounds = [FileTimeVector(1), FileTimeVector(end)]; + end + + % ===== CREATE PANEL ===== + jPanelNew = getRiverPanel([6,10], [5,5,0,10]); + % === COMMENT === + jPanelNew.add(JLabel('Comment:')); + jTextComment = JTextField(''); + jTextComment.setPreferredSize(Dimension(HFILLED_WIDTH, DEFAULT_HEIGHT)); + jPanelNew.add('hfill', jTextComment); + + % ===== PROCESSES PANEL ===== + jPanelOp = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboTestOp = JComboBox(); + jComboTestOp.setPreferredSize(JCOMBO_DM); + jComboTestOp.setMaximumRowCount(30); + set(jComboTestOp, 'ItemStateChangedCallback', @UpdatePanel); + jPanelOp.add('hfill', jComboTestOp); + % Fill the combo box + FillProcessComboBox(jComboTestOp, sProcesses); + + % === DESCRIPTION === + jLabelDescriptionOp = JLabel('No process available.'); + jLabelDescriptionOp.setVerticalAlignment(JLabel.TOP); + jPanelOp.add('br hfill', jLabelDescriptionOp); + + jTextFactors = []; + % ===== TABBED PANEL ===== + % If no tests possible: create a flat titled panel + if (Conditions.NbSamplesSets == 1) + % Initialize unsed controls to "Null" + jTabbedStat = []; + jComboTestSimple = []; + jComboTestPermut = []; + jLabelDescriptionSimple = []; + jLabelDescriptionPermut = []; + jSpinnerNbPermut = []; + % Add a title to the panel + jPanelOp.setPreferredSize(Dimension(150,120)); + jPanelOp.setBorder(javax.swing.BorderFactory.createTitledBorder('Process selection')); + jPanelNew.add('br hfill', jPanelOp); + windowDim(2) = 470; + % Else: Tabbed pane + else + jTabbedStat = JTabbedPane(); + set(jTabbedStat, 'StateChangedCallback', @UpdatePanel); + % PROCESSES PANEL + jTabbedStat.addTab('Processes', jPanelOp); + % ===== SIMPLE TESTS ===== + jPanelSimple = getRiverPanel([10,10], [0,20,5,20]); + % === TEST TYPE === + % Statistics type + jComboTestSimple = JComboBox(); + jComboTestSimple.setPreferredSize(JCOMBO_DM); + set(jComboTestSimple, 'ItemStateChangedCallback', @UpdatePanel); + jPanelSimple.add('hfill', jComboTestSimple); + % Fill the combo box + FillProcessComboBox(jComboTestSimple, sSimpleTests); + + % === DESCRIPTION === + jLabelDescriptionSimple = JLabel('No test available.'); + jLabelDescriptionSimple.setVerticalAlignment(JLabel.TOP); + jPanelSimple.add('br hfill', jLabelDescriptionSimple); + jTabbedStat.addTab('Simple tests', jPanelSimple); + + % ===== PERMUTATION TESTS ===== + jPanelPermut = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboTestPermut = JComboBox(); + jComboTestPermut.setPreferredSize(JCOMBO_DM); + set(jComboTestPermut, 'ItemStateChangedCallback', @UpdatePanel); + jPanelPermut.add('hfill', jComboTestPermut); + % Fill the combo box + FillProcessComboBox(jComboTestPermut, sPermTests); + + % === NUMBER OF PERMUTATIONS === + jPanelPermut.add('br', JLabel('Number of permutations: ')); + spinmodel = SpinnerNumberModel(10000, 1, 50000, 100); + jSpinnerNbPermut = JSpinner(spinmodel); + jSpinnerNbPermut.setPreferredSize(Dimension(SPINNER_WIDTH, DEFAULT_HEIGHT)); + jPanelPermut.add(jSpinnerNbPermut); + + % === DESCRIPTION === + jLabelDescriptionPermut = JLabel('No test available.'); + jLabelDescriptionPermut.setVerticalAlignment(JLabel.TOP); + jPanelPermut.add('br hfill', jLabelDescriptionPermut); + + jTabbedStat.addTab('Permutations', jPanelPermut); + + + % ===== ANOVA ===== + jPanelAnova = getRiverPanel([10,10], [0,20,5,20]); + % Statistics type + jComboAnova= JComboBox(); + jComboAnova.setPreferredSize(JCOMBO_DM); + set(jComboAnova, 'ItemStateChangedCallback', @UpdatePanel); + jPanelPermut.add('hfill', jComboAnova); + % Fill the combo box + FillProcessComboBox(jComboAnova, sAnova); + + % === FACTORS === + jPanelAnova.add('br', JLabel('Factors: ')); + % # of subjects: + NS = numel(unique({Conditions.SamplesA.SubjectName})); + + [u,i,j] = unique([Conditions.SamplesA.iItem]) + if numel(u)>1 + Comments = bst_getContext('Study', [Conditions.SamplesA.iStudy]); + Comments = [Comments.Data]; + + cellfun2('getfield', cellfun2('fliplr', getfield2(bst_getContext('Study', [Conditions.SamplesA.iStudy]), 'Data')), 'Comment')' + + SelectedItem = listdlg('ListString', ... + [strvcat({Conditions.SamplesA(i).Condition}) repmat(' : ',length(u),1) strvcat({Conditions.SamplesA(i).Comment})],... + 'SelectionMode','single'); + if isempty(SelectedItem) + return + end + Conditions.SamplesA = Conditions.SamplesA(j == SelectedItem); + assignin('base', 'sA', Conditions.SamplesA); + end + % Get samples + %GlobalData.Stat.FilterFileTag = ['_timemean' ]; + %Conditions = gui_stat_common('GetConditions', 'Statistics', GlobalData.Stat.FilterFileTag); + + tbl.h{1}='Condition'; + tbl.t = {Conditions.SamplesA.Condition}; + tbl.t = tbl.t(:) + tbl.t = tbl.t(1+[0:3]*NS) + %tbl.h{end+1}='Comment'; + %tbl.t(:,end+1) = {Conditions.SamplesA(1+[0:3]*15).Comment}; + tbl.h{end+1}='Factor 1'; + tbl.t(:,end+1)={ '1' ; '2' ; '1' ; '2' }; + tbl.h{end+1}='Factor 2'; + tbl.t(:,end+1)={ '1' ; '1' ; '2' ; '2' }; + + jTableFactors = JTable(tbl.t,tbl.h); + jTableFactors.setPreferredSize(Dimension(4*SPINNER_WIDTH, 5*DEFAULT_HEIGHT)); + jPanelAnova.add('br', jTableFactors); + + % === DESCRIPTION === + jLabelDescriptionAnova = JLabel('No option available.'); + jLabelDescriptionAnova.setVerticalAlignment(JLabel.TOP); + jPanelAnova.add('br hfill', jLabelDescriptionAnova); + + jTabbedStat.addTab('ANOVA', jPanelAnova); + jTabbedStat.setEnabledAt(3, 1); + + % Statistical tests : min two samples in each condition + if (nbSamplesA <= 1) || (nbSamplesB <= 1) + % Disable "simple tests" and "permutations" tabs if not enough samples + jTabbedStat.setEnabledAt(1, 0); + jTabbedStat.setEnabledAt(2, 0); + end + jTabbedStat.setPreferredSize(Dimension(150,175)); + jPanelNew.add('br hfill', jTabbedStat); + windowDim(2) = 350; + end + + % === TIME WINDOWS === + jPanelTimeWindows = getRiverPanel([2,3], [0,18,10,0], 'Time windows'); + % === WINDOW A === + jLabelTimeA = JLabel('Time window: '); + jPanelTimeWindows.add(jLabelTimeA); + % Time window A : START + jTextTimeStartA = JTextField(''); + jTextTimeStartA.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStartA.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStartA.setFont(jFontText); + jPanelTimeWindows.add('tab', jTextTimeStartA); + jLabelSeparatorA = JLabel('-'); + jPanelTimeWindows.add(jLabelSeparatorA); + % Time window A : STOP + jTextTimeStopA = JTextField(''); + jTextTimeStopA.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStopA.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStopA.setFont(jFontText); + jPanelTimeWindows.add(jTextTimeStopA); + + % Set time controls callbacks + TimeUnit = gui_validateText(jTextTimeStartA, [], [], FileTimeVector, [], jTextTimeStopA, FileTimeVector(1), @UpdatePanel); + TimeUnit = gui_validateText(jTextTimeStopA, [], [], FileTimeVector, jTextTimeStartA, [], FileTimeVector(end), @UpdatePanel); + % Display time unit + jLabelTimeUnitsA = JLabel(TimeUnit); + jPanelTimeWindows.add(jLabelTimeUnitsA); + + % === WINDOW B === + jLabelTimeB = JLabel('Baseline: '); + jPanelTimeWindows.add('br', jLabelTimeB); + % Time window B : START + jTextTimeStartB = JTextField(''); + jTextTimeStartB.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStartB.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStartB.setFont(jFontText); + jPanelTimeWindows.add('tab', jTextTimeStartB); + jLabelSeparatorB = JLabel('-'); + jPanelTimeWindows.add(jLabelSeparatorB); + % Time window B : STOP + jTextTimeStopB = JTextField(''); + jTextTimeStopB.setPreferredSize(Dimension(TEXT_WIDTH, DEFAULT_HEIGHT)); + jTextTimeStopB.setHorizontalAlignment(JTextField.RIGHT); + jTextTimeStopB.setFont(jFontText); + jPanelTimeWindows.add(jTextTimeStopB); + + % Set time controls callbacks + gui_validateText(jTextTimeStartB, [], [], FileTimeVector, [], jTextTimeStopB, BaselineBounds(1), []); + gui_validateText(jTextTimeStopB, [], [], FileTimeVector, jTextTimeStartB, [], BaselineBounds(2), []); + % Display time unit + jLabelTimeUnitB = JLabel(TimeUnit); + jPanelTimeWindows.add(jLabelTimeUnitB); + jPanelNew.add('br hfill', jPanelTimeWindows); + + % ===== SOURCES PANEL ===== + jPanelSources = getRiverPanel([0,0], [0,0,0,0], 'Sources'); + jCheckAbsoluteValues = JCheckBox('Use absolute values of sources activations'); + jCheckAbsoluteValues.setMargin(Insets(0,10,0,0)); + set(jCheckAbsoluteValues, 'ActionPerformedCallback', @CheckAbsoluteValues_Callback); + jPanelSources.add(jCheckAbsoluteValues); + % Add panel only if processing sources (results) + if ~isData + jPanelNew.add('br hfill', jPanelSources); + jCheckAbsoluteValues.setSelected(1); + windowDim(2) = windowDim(2) + 70; + else + jCheckAbsoluteValues.setVisible(0); + jCheckAbsoluteValues.setSelected(0); + end + + % ===== CLUSTER PANEL CONFIG ===== + jCheckCluster = []; + jCheckAvgCluster = []; + jListCluster = []; + iScouts = []; + Channel = []; + if (Conditions.NbSamplesSets == 1) + jPanelCluster = JPanel(BorderLayout()); + % === SCALP: ELECTRODES CLUSTER === + if isData + jPanelCluster.setBorder(javax.swing.BorderFactory.createTitledBorder('Clusters')); + % Get all available scouts for these results + [sClusters, iClusters] = GetClusters(Conditions); + % If all samples defined for the same cortical surface, and some scouts are defined for it + if isstruct(sClusters) + % Get selected scouts + jPanelClusterTop = JPanel(BorderLayout()); + % === ENABLE CHECK BOX === + jCheckCluster = JCheckBox('Use only selected clusters'); + jCheckCluster.setMargin(Insets(5,10,0,0)); + set(jCheckCluster, 'ActionPerformedCallback', @UpdatePanel); + jPanelClusterTop.add(jCheckCluster, BorderLayout.WEST); + + % === AVERAGE CLUSTER CHECKBOX === + if (length(sClusters) > 1) + jCheckAvgCluster = JCheckBox('Merge selected clusters', 0); + jCheckAvgCluster.setMargin(Insets(5,10,0,15)); + jPanelClusterTop.add(jCheckAvgCluster, BorderLayout.EAST); + end + jPanelCluster.add(jPanelClusterTop, BorderLayout.NORTH); + + % === JLIST: CLUSTERS === + % Create list (display labels of all clusters) + jListCluster = JList({sClusters.Label}); + % Pre-select clusters that are selected in the "Cluster" panel + [tmp__, iSelect] = panel_clusters('GetSelectedClusters'); + if ~isempty(iSelect) + jListCluster.setSelectedIndices(iSelect - 1); + end + % Create scroll panel + jScrollPanelCluster = JScrollPane(jListCluster); + jScrollPanelCluster.setBorder(BorderFactory.createCompoundBorder(... + BorderFactory.createEmptyBorder(5, 30, 5, 30), ... + jScrollPanelCluster.getBorder())); + jScrollPanelCluster.setPreferredSize(Dimension(250,300)); + jPanelCluster.add(jScrollPanelCluster, BorderLayout.WEST); + + % Set the dialog size + windowDim(2) = windowDim(2) + 80; + + % ERROR 1 + elseif isnumeric(sClusters) && (sClusters == -1) + jPanelCluster.add(JLabel(' No channel file available for at least one file.')); + % ERROR 2 + elseif isnumeric(sClusters) && (sClusters == -2) + jPanelCluster.add(JLabel(' No cluster available. Use "Cluster" tab to create one.'), BorderLayout.CENTER); + end + + % === SOURCES: VERTICES CLUSTER (=SCOUT) === + else + jPanelCluster.setBorder(javax.swing.BorderFactory.createTitledBorder('Scouts')); + % Get all available scouts for these results + [sScouts, iScouts] = GetScouts(Conditions); + % If all samples defined for the same cortical surface, and some scouts are defined for it + if isstruct(sScouts) + % Get selected scouts + [sSelScouts, iSelScouts] = panel_scouts('GetSelectedScouts'); + jPanelClusterTop = JPanel(BorderLayout()); + % === ENABLE CHECK BOX === + jCheckCluster = JCheckBox('Use only selected scouts'); + jCheckCluster.setMargin(Insets(5,10,0,0)); + set(jCheckCluster, 'ActionPerformedCallback', @UpdatePanel); + jPanelClusterTop.add(jCheckCluster, BorderLayout.WEST); + + % === AVERAGE CLUSTER CHECKBOX === + if (length(sScouts) > 1) + jCheckAvgCluster = JCheckBox('Merge selected scouts', 0); + jCheckAvgCluster.setMargin(Insets(5,10,0,15)); + jPanelClusterTop.add(jCheckAvgCluster, BorderLayout.EAST); + end + jPanelCluster.add(jPanelClusterTop, BorderLayout.NORTH); + + % === JLIST: CHANNELS === + % Create list (display labels of all scouts) + jListCluster = JList({sScouts.Label}); + % Pre-select scouts that are selected in the "Scouts" panel + iSelect = find(ismember(iScouts, iSelScouts)); + if ~isempty(iSelect) + jListCluster.setSelectedIndices(iSelect - 1); + end + % Create scroll panel + jScrollPanelCluster = JScrollPane(jListCluster); + jScrollPanelCluster.setBorder(BorderFactory.createCompoundBorder(... + BorderFactory.createEmptyBorder(5, 30, 5, 30), ... + jScrollPanelCluster.getBorder())); + jScrollPanelCluster.setPreferredSize(Dimension(250,300)); + jPanelCluster.add(jScrollPanelCluster, BorderLayout.WEST); + + % Set the dialog size + windowDim(2) = windowDim(2) + 80; + + % ERROR 1 + elseif isnumeric(sScouts) && (sScouts == -1) + jPanelCluster.add(JLabel(' The sources files were not computed for the same cortical surface.'), BorderLayout.CENTER); + % ERROR 2 + elseif isnumeric(sScouts) && (sScouts == -2) + jPanelCluster.add(JLabel(' No scout available for these files.'), BorderLayout.CENTER); + end + end + jPanelNew.add('br vfill hfill', jPanelCluster); + end + + % ===== OUTPUT PANEL ===== + if (Conditions.NbSamplesSets == 1) + jPanelOutput = getRiverPanel([0,3], [0,10,10,10], 'Output'); + buttonGroupOutput = ButtonGroup(); + % OUTPUT: Brainstorm Database + jRadioOutputDatabase = JRadioButton('Brainstorm database', 1); + jRadioOutputDatabase.setToolTipText(['Brainstorm database:

' ... + 'All the files that are generated are automatically added to database.

'... + ' - One output file:
' ... + 'Most of the processes produce only one file that is stored either,
' ... + 'in the original condition or in an "Analysis" node.

' ... + ' - Multiple output files:
' ... + 'The processes that are marked "[sample by sample]" produce one file
' ... + 'for each file A (or couple of files A/B) in the sample list.']); + buttonGroupOutput.add(jRadioOutputDatabase); + jPanelOutput.add(jRadioOutputDatabase); + % Overwrite original files + jPanelOutput.add('br', JLabel(' ')); + jCheckOverwriteFiles = JCheckBox('Overwrite initial files', 1); + jPanelOutput.add(jCheckOverwriteFiles); + % OUTPUT: Condition path (check) + jPanelOutput.add('br', JLabel(' ')); + jCheckOutputCond = JCheckBox('Select output condition'); + jPanelOutput.add(jCheckOutputCond); + % OUTPUT: Condition path (text) + jTextOutputCond = JTextField(''); + jTextOutputCond.setMargin(Insets(0,0,0,20)); + jPanelOutput.add('hfill', jTextOutputCond); + % OUTPUT: User file + jRadioOutputFile = JRadioButton('User defined file: All data is stored in one unique file'); + buttonGroupOutput.add(jRadioOutputFile); + jPanelOutput.add('br', jRadioOutputFile); + % OUTPUT: Matlab variable + jRadioOutputMatlab = JRadioButton('Export to a Matlab variable'); + buttonGroupOutput.add(jRadioOutputMatlab); + jPanelOutput.add('br', jRadioOutputMatlab); + jPanelNew.add('br hfill', jPanelOutput); + % Callbacks + set(jRadioOutputDatabase, 'ActionPerformedCallback', @UpdateOutput); + set(jRadioOutputFile, 'ActionPerformedCallback', @UpdateOutput); + set(jRadioOutputMatlab, 'ActionPerformedCallback', @UpdateOutput); + set(jCheckOverwriteFiles, 'ActionPerformedCallback', @UpdateOutput); + set(jCheckOutputCond, 'ActionPerformedCallback', @UpdateOutput); + else + jRadioOutputDatabase = []; + jRadioOutputFile = []; + jRadioOutputMatlab = []; + jCheckOverwriteFiles = []; + jCheckOutputCond = []; + jTextOutputCond = []; + end + + % ===== VALIDATION BUTTONS ===== + % Help + jButtonHelp = JButton('Help'); + jButtonHelp.setForeground(Color(.7, 0, 0)); + if (Conditions.NbSamplesSets == 1) + set(jButtonHelp, 'ActionPerformedCallback', @(h,ev)bst_help('PanelStatRunProcess.html', 1)); + else + set(jButtonHelp, 'ActionPerformedCallback', @(h,ev)bst_help('PanelStatRunStat.html', 1)); + end + jPanelNew.add('br right', jButtonHelp); + % Cancel + jButtonCancel = JButton('Cancel'); + set(jButtonCancel, 'ActionPerformedCallback', @ButtonCancel_Callback); + jPanelNew.add(jButtonCancel); + % Run + jButtonRun = JButton('Run'); + set(jButtonRun, 'ActionPerformedCallback', @(h,ev)bst_safeCall(@ButtonRun_Callback)); + jPanelNew.add(jButtonRun); + + % Set main panel size + jPanelNew.setPreferredSize(Dimension(windowDim(1), windowDim(2))); + + % Create the BstPanel object that is returned by the function + % => constructor BstPanel(jHandle, panelName, sControls) + bstPanelNew = BstPanel(panelName, ... + jPanelNew, ... + struct('jListCluster', jListCluster)); + % Update panel + UpdatePanel(); + + + +%% ================================================================================= +% === INTERNAL CALLBACKS ========================================================== +% ================================================================================= +%% ===== CHECKBOX : "ABSOLUTE VALUES" ===== + function CheckAbsoluteValues_Callback(varargin) + if ~jCheckAbsoluteValues.isSelected() + isConfirmed = java_dialog('confirm', ['Please keep this option selected, unless you know exactly what you are doing.' 10 10 ... + 'Are you sure you want to use relative values for sources activations ?'], 'Processes'); + if ~isConfirmed + jCheckAbsoluteValues.setSelected(1); + end + end + end + +%% ===== UPDATE OUTPUT PANEL ===== + function UpdateOutput(varargin) + % Force condition path + isDatabase = jRadioOutputDatabase.isSelected(); + jCheckOutputCond.setEnabled(isDatabase); + jTextOutputCond.setEnabled(isDatabase); + if ~isDatabase + jCheckOutputCond.setSelected(0); + end + % Condition path + isForceCond = jCheckOutputCond.isSelected(); + jTextOutputCond.setVisible(isForceCond); + % Cannot select both options at the same time + if isForceCond + jCheckOverwriteFiles.setSelected(0); + end + end + +%% ===== FILL PROCESSES COMBO BOX ===== + function FillProcessComboBox(jCombo, sList) + import org.brainstorm.list.BstListItem; + % Fill the combo box + for i = 1:length(sList) + % Convert labels to HTML + label = sList(i).Comment; + if isempty(sList(i).Name) + label = ['

' label]; + else + label = ['

' label]; + end + % Add item in combo list + jCombo.addItem(BstListItem(sList(i).Name, '', label, sList(i).Description)); + end + end + +%% ===== RUN ===== + function ButtonRun_Callback(varargin) + CallBatch(); + end + +%% ===== GET SELECTED PROCESS ===== + function [sProcess, selectedTab] = GetSelectedProcess() + % Get selected tab + if isempty(jTabbedStat) + selectedTab = 0; + else + selectedTab = jTabbedStat.getSelectedIndex(); + end + % Get the selected combo box + switch (selectedTab) + case 0 + jCombo = jComboTestOp; + sList = sProcesses; + case 1 + jCombo = jComboTestSimple; + sList = sSimpleTests; + case 2 + jCombo = jComboTestPermut; + sList = sPermTests; + case 3 + jCombo = jComboAnova; + sList = sAnova; + end + % Get selected process + jItem = jCombo.getSelectedItem(); + if isempty(jItem) + sProcess = []; + return + end + processName = jItem.getType(); + % Find in it in processes list + iProcess = find(strcmpi({sList.Name}, processName)); + sProcess = sList(iProcess(1)); + end + +%% ===== UPDATE PANEL ===== + function UpdatePanel(varargin) %#ok + % Get selected process + [sProcess, selectedTab] = GetSelectedProcess(); + if isempty(sProcess) + return + end + % Convert description to HTML + processDesc = ['' strrep(sProcess.Description, char(10), '
')]; + % Update tabbed panels + switch(selectedTab) + % === PROCESSES === + case 0 + jLabelDescriptionOp.setText(processDesc); + % === SIMPLE TESTS === + case 1 + jLabelDescriptionSimple.setText(processDesc); + % === PERM TESTS === + case 2 + jLabelDescriptionPermut.setText(processDesc); + % Compute maximum number of permutations + Na = nbSamplesA; + Nb = nbSamplesB; + if sProcess.isPaired + % nbPermMax = 2^(Na)-1; + nbPermMax = 2^(Na-1)-1; + else + nbPermMax = factorial(Na+Nb) / (factorial(Na)*factorial(Nb)) - 1; + end + % Limit default number of permutations + NB_PERM_LIMIT = 10000; + nbPerm = min(nbPermMax, NB_PERM_LIMIT); + % Update spinner model + spinmodel = awtinvoke(jSpinnerNbPermut, 'getModel()'); + awtinvoke(spinmodel, 'setValue(Ljava.lang.Object;)', java.lang.Double(nbPerm)); + awtinvoke(spinmodel, 'setMaximum(Ljava.lang.Comparable;)', java.lang.Double(nbPermMax)); + end + + % ===== UPDATE COMMENT ===== + % Get time + TimeRange = GetTimeWindows(TimeUnit); + % Format comment + Comment = FormatComment(sProcess, Conditions, TimeRange); + % Too long comment + if (length(Comment) > 80) + % Replace comment by date + c = clock; + strTime = sprintf('%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + Comment = [sProcess.Name ': ' strTime]; + end + % Update comment + awtinvoke(jTextComment, 'setText(Ljava.lang.String;)', Comment); + + % ===== UPDATE TIME WINDOW PANEL ===== + if ~isempty(jTextTimeStartB) + jLabelTimeB.setEnabled(sProcess.UseBaseline); + jTextTimeStartB.setEnabled(sProcess.UseBaseline); + jTextTimeStopB.setEnabled(sProcess.UseBaseline); + jLabelSeparatorB.setEnabled(sProcess.UseBaseline); + jLabelTimeUnitB.setEnabled(sProcess.UseBaseline); + end + + % ===== UPDATE SOURCES PANEL ===== + jCheckAbsoluteValues.setSelected(sProcess.isSourceAbsolute > 0); + jCheckAbsoluteValues.setEnabled(sProcess.isSourceAbsolute ~= 2); + + % ===== UPDATE CLUSTER PANEL ===== + % Cluster checkbox + isAllowCluster = ismember(sProcess.Category, {'Extract'}); + if ~isempty(jCheckCluster) + jCheckCluster.setEnabled(isAllowCluster); + if ~isAllowCluster + jCheckCluster.setSelected(0); + end + % Cluster jlists + isCluster = ~isempty(jCheckCluster) && jCheckCluster.isSelected(); + if ~isempty(jListCluster) + jListCluster.setEnabled(isCluster); + end + if ~isempty(jCheckAvgCluster) + jCheckAvgCluster.setEnabled(isCluster); + end + else + isCluster = 0; + end + + % ===== UPDATE OUTPUT PANEL ===== + if ~isempty(jRadioOutputDatabase) + AllowExport = ismember(sProcess.Category, {'Extract'}); + % Enable Database: only if no cluster defined + jRadioOutputDatabase.setEnabled(~isCluster); + % Enable File/Matlab + jRadioOutputFile.setEnabled(AllowExport > 0); + jRadioOutputMatlab.setEnabled(AllowExport > 0); + % Select "File": if cluster, or time/mean, time/var, or extract + if (isCluster || AllowExport) + % Change selection only if Database is selected + if ~jRadioOutputMatlab.isSelected() + jRadioOutputFile.setSelected(1); + end + else + jRadioOutputDatabase.setSelected(1); + end + + % "Overwrite file" checkbox + AllowOverwrite = ismember(sProcess.Category, {'Filter'}); + isOverwriteEnabled = jRadioOutputDatabase.isEnabled() && AllowOverwrite; + jCheckOverwriteFiles.setEnabled(isOverwriteEnabled); + isOverwriteSelected = isOverwriteEnabled && sProcess.DefaultOverwrite; + jCheckOverwriteFiles.setSelected(isOverwriteSelected); + % Update object selections + UpdateOutput(); + end + end + + +%% ===== GET TIME WINDOWS ===== + function [Time, Baseline, iTime, iBaseline] = GetTimeWindows(TimeUnit) + % Get time window to process + Time = [getValue(jTextTimeStartA), getValue(jTextTimeStopA)]; + % Get baseline, if defined + if ~isempty(jTextTimeStartB) + Baseline = [getValue(jTextTimeStartB), getValue(jTextTimeStopB)]; + else + Baseline = []; + end + % Apply correct time units + switch(TimeUnit) + case 'ms' + % Convert miliseconds -> seconds + Time = Time / 1000; + Baseline = Baseline / 1000; + otherwise + % Nothing to do + end + % Get indices in intial FileTimeVector + iTimeBounds = findclosest(Time, FileTimeVector); + % If whole data wanted and sampling frequency very high: might lack of time precision... + % Try to correct this and select the last sample if it is obviously this that the user wants + if (iTimeBounds(2) ~= length(FileTimeVector)) && (FileTimeVector(end)-FileTimeVector(iTimeBounds(2)) < 1e-5) + iTimeBounds(2) = length(FileTimeVector); + end + % Build time indices + iTime = iTimeBounds(1) : iTimeBounds(2); + iBaselineBounds = findclosest(Baseline, FileTimeVector); + iBaseline = iBaselineBounds(1) : iBaselineBounds(2); + end + +%% ===== GET VALUES ===== + function val = getValue(jText) + % Get and check value + val = str2double(char(jText.getText())); + if isnan(val) || isempty(val) + val = []; + end + end + + +%% ===== COMPUTE TEST ===== + function CallBatch() + % ===== PREPARE OPTIONS ===== + OPTIONS = struct(); + % Is processing recordings or results + OPTIONS.isData = isData; + % Get new file comment + OPTIONS.Comment = deblank(strtrim(char(jTextComment.getText()))); + % Is absolute values (for sources only) + OPTIONS.isAbsoluteValues = ~isData && jCheckAbsoluteValues.isSelected(); + % Get selected process + [OPTIONS.sProcess, selectedTab] = GetSelectedProcess(); + if isempty(OPTIONS.sProcess) || isempty(OPTIONS.sProcess.Name) + bst_error('Please select a process.', 'Processes', 0); + return + end + % Get number of permutations + if ~isempty(jSpinnerNbPermut) + OPTIONS.nbPermutation = jSpinnerNbPermut.getValue(); + else + OPTIONS.nbPermutation = 0; + end + % List factors associated with each dataset + if ~isempty(jTextFactors) + OPTIONS.Factors= char(jTextFactors.getText()); + else + OPTIONS.Factors = []; + end + + % Overwrite initial files ? + OPTIONS.isOverwriteFiles = ~isempty(jCheckOverwriteFiles) && jCheckOverwriteFiles.isSelected(); + % Get output mode + if isempty(jRadioOutputDatabase) || jRadioOutputDatabase.isSelected() + OPTIONS.OutputType = 'database'; + elseif jRadioOutputFile.isSelected() + OPTIONS.OutputType = 'file'; + elseif jRadioOutputMatlab.isSelected() + OPTIONS.OutputType = 'matlab'; + end + % Force output condition + if ~isempty(jCheckOutputCond) && jCheckOutputCond.isSelected() + % Get the user defined condition name + outputCond = char(jTextOutputCond.getText()); + % Split condition path + condPath = strSplit(outputCond); + % Check if condition name is valid + if isempty(outputCond) || (~strcmpi(outputCond,'@inter') && (length(condPath) ~= 2)) + bst_error(['Invalid condition path.' 10 10 ... + 'Condition path must be one the following:' 10 ... + ' - SubjectName/ConditionName' 10 ... + ' - SubjectName/@intra' 10 ... + ' - @inter'], 'Processes', 0); + return + end + % === Convert SubjectName in SubjectPath === + if (length(condPath) == 2) + % Get subject and condition names + SubjectName = condPath{1}; + ConditionName = condPath{2}; + % Get subject + sSubject = bst_getContext('Subject', SubjectName, 1); + if isempty(sSubject) + bst_error(['Subject does not exist: "' SubjectName '"'], 'Processes', 0); + return + end + % Build new output condition path + SubjectPath = fileparts(sSubject.FileName); + outputCond = fullfile(SubjectPath, ConditionName); + end + % Valid + OPTIONS.ForceOutputCond = outputCond; + else + OPTIONS.ForceOutputCond = []; + end + % Is "Cluster" analysis + OPTIONS.isCluster = ~isempty(jCheckCluster) && jCheckCluster.isSelected(); + OPTIONS.isClusterAverage = OPTIONS.isCluster && ~isempty(jCheckAvgCluster) && jCheckAvgCluster.isSelected(); + % Get selected clusters + if OPTIONS.isCluster + if OPTIONS.isData + % Get selected clusters + iClusters = jListCluster.getSelectedIndices() + 1; + sClusters = panel_clusters('GetClusters', iClusters); + % If no cluster selected: ERROR + if isempty(iClusters) + error('No channel selected in cluster panel.'); + end + % If user asked to merge clusters + if OPTIONS.isClusterAverage + sClustersAvg.Sensors = unique(cat(2, sClusters.Sensors)); + sClustersAvg.Label = ['Clusters:', sprintf(' %s', sClusters.Label)]; + OPTIONS.Clusters = sClustersAvg; + else + OPTIONS.Clusters = sClusters; + end + % Get clusters options + OPTIONS.ClustersOptions = panel_clusters('GetClusterDisplayType'); + else + % Get selected scouts + iSelScouts = jListCluster.getSelectedIndices() + 1; + % If no scout selected: ERROR + if isempty(iSelScouts) + error('No scout selected in cluster panel.'); + end + % Get scouts description + [sScouts, iScouts] = panel_scouts('GetCurrentScouts'); + iScouts = iScouts(iSelScouts); + sScouts = panel_scouts('GetScouts', iScouts); + % If user asked to merge scouts + if OPTIONS.isClusterAverage + sScoutsAvg = sScouts(1); + sScoutsAvg.Vertices = unique([sScouts.Vertices]); + sScoutsAvg.Label = ['Scouts:', sprintf(' %s', sScouts.Label)]; + OPTIONS.Clusters = sScoutsAvg; + else + OPTIONS.Clusters = sScouts; + end + % Get scouts options + OPTIONS.ClustersOptions = panel_scouts('GetScoutDisplayType'); + end + else + OPTIONS.sClusters = []; + OPTIONS.ClustersOptions = []; + end + % Get time + [OPTIONS.Time, OPTIONS.Baseline, OPTIONS.iTime, OPTIONS.iBaseline] = GetTimeWindows(TimeUnit); + + % Get files to batch + OPTIONS.Conditions = Conditions; + % Close panel + gui_hidePanel('panel_statRun'); + + % ===== PERFORM SOME VERIFICATIONS ===== + % Not supposed to compute zscore on recordings + if OPTIONS.isData && strcmpi(OPTIONS.sProcess.Name, 'zscore') + res = java_dialog('confirm', ['Warning: You are about to compute the z-score normalization on recordings.' 10 10 ... + 'We recommand first to solve the inverse problem, and then to ' 10 ... + 'apply the zscore normalization on the cortical sources.' 10 10 ... + 'Are you sure you want to compute the z-score of the recordings ?'], 'Warning'); + if ~res + return; + end + end + + % ===== CALL BATCH FUNCTION ===== + bst_batch(OPTIONS); + + % Update "Processes" panels + if OPTIONS.isOverwriteFiles + panel_processes('ResetPanel'); + else + if (Conditions.NbSamplesSets == 1) && ~gui_stat_common('CheckConditions', 'Processes') + panel_processes('ResetPanel'); + elseif (Conditions.NbSamplesSets == 2) && ~gui_stat_common('CheckConditions', 'Statistics') + panel_stat('ResetPanel'); + end + end + end +end + + +%% ================================================================================= +% === EXTERNAL CALLBACKS ========================================================== +% ================================================================================= +%% ===== CANCEL ===== +function ButtonCancel_Callback(varargin) + % Close panel + gui_hidePanel('panel_statRun'); +end + + +%% ===== BUILD LIST OF PROCESSES ===== +% USAGE: [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(NbSamplesSets, nbSamplesA, nbSamplesB, isData) +% [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList('All') +function [sProcesses, sSimpleTests, sPermTests, sAnova] = GetProcessesList(NbSamplesSets, nbSamplesA, nbSamplesB, isData) + % If get all processes: ignore all other arguments + isAll = strcmpi(NbSamplesSets, 'All'); + % Initialize list + sModel = struct('Name', '', ... + 'Comment', '', ... + 'Description', '', ... + 'FileTag', '', ... + 'Category', '', ... + 'UseBaseline', 0, ... + 'DefaultOverwrite', 0, ... + 'isSourceAbsolute', 1, ... % If value=2, absolute value for sources is FORCED + 'isPaired', 0, ... + 'blockDimension', 0, ... % Dimension in which the data matrix can be split (0=none, 1=channels, 2=time) + 'isAvgRef', 1); % Compute EEG average reference before processing + sProcesses = repmat(sModel, 0); + sSimpleTests = repmat(sModel, 0); + sPermTests = repmat(sModel, 0); + + % ===== "A" PROCESSES ===== + if isAll || (NbSamplesSets == 1) + % === FILTERS TO APPLY TO FILES === + sProcess = sModel; + sProcess.Comment = '==== PROCESS FILES ==========='; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % Z-SCORE + sProcess = sModel; + sProcess.Name = 'zscore'; + sProcess.Comment = ' Z-score noise normalization'; + sProcess.FileTag = '| zscore'; + sProcess.Description = ['For each channel:' 10 ... + '1) Compute mean m and variance v for baseline.' 10 ... + '2) For each time sample, substract m and divide by v.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.isSourceAbsolute = 2; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % BASELINE REMOVAL + sProcess = sModel; + sProcess.Name = 'baseline'; + sProcess.Comment = ' Remove baseline mean (DC offset)'; + sProcess.FileTag = '| bl'; + sProcess.Description = ['For each channel:' 10 ... + '1) Compute the mean m for the baseline.' 10 ... + '2) For all the time samples, substract m.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.isSourceAbsolute = 0; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % EEG AVERAGE REFERENCE + if isAll || isData + sProcess = sModel; + sProcess.Name = 'avgref'; + sProcess.Comment = ' EEG Average reference'; + sProcess.FileTag = '| avgref'; + sProcess.Description = ['Note that all the processes that are not in the "Process files" category use average reference by default. ' 10 ... + 'No effect on MEG recordings.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 0; + sProcess.isSourceAbsolute = 0; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 2; + sProcesses(end + 1) = sProcess; + end + % BANDPASS FILTERING + sProcess = sModel; + sProcess.Name = 'bandpass'; + sProcess.Comment = ' Bandpass filtering'; + sProcess.FileTag = '| bandpass'; + sProcess.Description = 'Apply a frenquency filter to all the files.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 0; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + % SPATIAL SMOOTHING + if isAll || ~isData + sProcess = sModel; + sProcess.Name = 'ssmooth'; + sProcess.Comment = ' Spatial smoothing'; + sProcess.FileTag = '| ssmooth'; + sProcess.Description = 'Spatial smoothing of the sources.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 2; + sProcess.blockDimension = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % RESAMPLE + if isAll || isData + sProcess = sModel; + sProcess.Name = 'resample'; + sProcess.Comment = ' Resample recordings'; + sProcess.FileTag = '| resample'; + sProcess.Description = 'Resample all the files with a new sampling frequency.'; + sProcess.Category = 'Filter'; + sProcess.isSourceAbsolute = 0; + % sProcess.blockDimension = 1; % PROBLEM WITH PROCESSING BY BLOCKS: DIMENSIONS CHANGE + sProcess.blockDimension = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % CUT STIMULATION ARTIFACT + if isAll || isData + sProcess = sModel; + sProcess.Name = 'cutstim'; + sProcess.Comment = ' Cut stimulation artifact'; + sProcess.FileTag = '| cutstim'; + sProcess.Description = ['Remove the values in the "baseline" time window.' 10 ... + 'Replace them with a linear interpolation.']; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 1; + sProcess.DefaultOverwrite = 1; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + % OPPOSITE VALUES + sProcess = sModel; + sProcess.Name = 'opposite'; + sProcess.Comment = ' Opposite values: -A'; + sProcess.FileTag = '| opposite'; + sProcess.Description = 'Save opposite values for A files.'; + sProcess.Category = 'Filter'; + sProcess.DefaultOverwrite = 1; + sProcess.isSourceAbsolute = 0; + sProcess.blockDimension = 1; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + + % === AVERAGING === + if isAll || (nbSamplesA >= 2) + sProcess = sModel; + sProcess.Comment = '==== AVERAGING ============='; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % GRAND-AVERAGE A (MEAN/CONDITION) + sProcess = sModel; + sProcess.Name = 'GAVE'; + sProcess.Comment = ' Average by condition (Grand-average)'; + sProcess.FileTag = ''; + sProcess.Description = ['Grand averages for each condition' 10 ... + 'One output file per condition.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + % AVERAGE BY SUBJECT + sProcess = sModel; + sProcess.Name = 'SubjAvg'; + sProcess.Comment = ' Average by subject'; + sProcess.FileTag = ''; + sProcess.Description = ['Average all the recordings for each subject.' 10 ... + 'One output file per subject.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + % AVERAGE A + sProcess = sModel; + sProcess.Name = 'meanA'; + sProcess.Comment = ' Average everything'; + sProcess.FileTag = '<#A#>'; + sProcess.Description = ['Average of all files.' 10 'Only one output file.']; + sProcess.Category = 'Average'; + sProcesses(end + 1) = sProcess; + end + + % === DATA EXTRACTION === + sProcess = sModel; + sProcess.Comment = '==== EXTRACT DATA ==========='; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % MEAN FOR A TIME WINDOW + sProcess = sModel; + sProcess.Name = 'timemean'; + sProcess.Comment = ' Average over a time window'; + sProcess.FileTag = '| timemean#TIME#'; + sProcess.Description = ['Average for each file over the selected time window.' 10 ... + 'Use absolute values for sources.']; + sProcess.Category = 'Extract'; + sProcesses(end + 1) = sProcess; + % VARIANCE FOR A TIME WINDOW + sProcess = sModel; + sProcess.Name = 'timevar'; + sProcess.Comment = ' Variance over a time window'; + sProcess.FileTag = '| timevar#TIME#'; + sProcess.Description = 'Variance for each file over the selected time window.'; + sProcess.Category = 'Extract'; + sProcesses(end + 1) = sProcess; + % EXTRACT DATA FROM SAMPLES + sProcess = sModel; + sProcess.Name = 'extract'; + sProcess.Comment = ' Extract data block (cluster,time)'; + sProcess.FileTag = '| extract#TIME#'; + sProcess.Description = 'Get a block of data from each file.'; + sProcess.Category = 'Extract'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + + % === NEUROMAG RECORDINGS === + if isAll || isData + sProcess = sModel; + sProcess.Comment = '==== NEUROMAG RECORDINGS ====='; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % GRADIOMETERS NORM + sProcess = sModel; + sProcess.Name = 'gradnorm'; + sProcess.Comment = ' Norm of gradiometers couples'; + sProcess.FileTag = '| gradnorm'; + sProcess.Description = 'Compute the norm for each gradiometer couple.'; + sProcess.Category = 'Filter'; + sProcess.UseBaseline = 0; + sProcess.isAvgRef = 0; + sProcesses(end + 1) = sProcess; + end + + % === SPECTRAL ANALYSIS === + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== SPECTRAL ANALYSIS ========'; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + % Frequency-Band SAMPLE SPECTRAL DECOMPOSITION + sProcess = sModel; + sProcess.Name = 'spectDecomp'; + sProcess.Comment = ' Spectral decomposition and statistics'; + sProcess.FileTag = ''; + sProcess.Description = ['Computes power in multiple, standard frequency bands.' 10 ... + 'Yields average, standard deviation and t-statistics across samples.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Spectral'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + + % Power spectrum analysis + sProcess = sModel; + sProcess.Name = 'powerSpectrum'; + sProcess.Comment = ' Fourier magnitude'; + sProcess.FileTag = ''; + sProcess.Description = ['Transforms each time series in file into spectral domain (modulus of Fourier transform).' 10 ... + 'Time vector is replaced by corresponding frequency bin used in Fourier tranform.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Spectral'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + end + + % === RECURRENCE MAPS=== + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== RECURRENCE MAPS ========'; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + sProcess = sModel; + sProcess.Name = 'recMaps'; + sProcess.Comment = ' Recurrence maps of activations'; + sProcess.FileTag = ''; + sProcess.Description = ['Computes recurrence maps across samples.' 10 ... + 'Source maps above 75% activation are thresholded and binarized before being summed across samples.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'Recurrence'; + sProcess.isSourceAbsolute = 1; + sProcesses(end + 1) = sProcess; + end + + % === SCOUTS functional Connectivity === + if isAll || ~isData + sProcess = sModel; + sProcess.Comment = '==== Scouts f-Connectivity ========'; + sProcess.Description = 'Please select a process...'; + sProcesses(end + 1) = sProcess; + sProcess = sModel; + sProcess.Name = 'fScoutConnect'; + sProcess.Comment = ' Evaluate functional connectivity between cortical scouts'; + sProcess.FileTag = ''; + sProcess.Description = ['Evaluate functional connectivity between cortical scouts.' 10 ... + 'Under development: use with caution.' 10 ... + 'WARNING: Only applies to KERNEL sources files.']; + sProcess.Category = 'fConnectivity'; + sProcess.isSourceAbsolute = 0; + sProcesses(end + 1) = sProcess; + end + end + + % ===== "A/B" PROCESSES ===== + if isAll || (NbSamplesSets == 2) + % Differences : same number of samples in each set + if isAll || (nbSamplesA == nbSamplesB) + % DIFFERENCE: A - B + sProcess = sModel; + sProcess.Name = 'diffAB'; + sProcess.Comment = ' A - B'; + sProcess.FileTag = '#A#-#B#'; + sProcess.Description = ['Difference of each couple of samples (A-B).' 10 10 ... + 'Each pair must share the same anatomy.' 10 ... + 'Result is stored in a new condition.']; + sProcess.Category = 'Filter2'; + sProcesses(end + 1) = sProcess; + % AVERAGE: Average(A,B) + sProcess = sModel; + sProcess.Name = 'meanAB'; + sProcess.Comment = ' Average(A,B)'; + sProcess.FileTag = 'Average(#A#,#B#)'; + sProcess.Description = ['Average of each couple of samples (A,B).' 10 10 ... + 'Each pair must share the same anatomy.' 10 ... + 'Result is stored in a new condition.']; + sProcess.Category = 'Filter2'; + sProcesses(end + 1) = sProcess; + end + end + + + % ===== SIMPLE T-TESTS ===== + % NEW: t-test equal variance + sTest = sModel; + sTest.Name = 'ttest'; + sTest.Comment = ' t-test (equal variances)'; + sTest.FileTag = 'ttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for equal variances.' 10 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % NEW: t-test unequal variance + sTest = sModel; + sTest.Name = 'uttest'; + sTest.Comment = ' t-test (unequal variances)'; + sTest.FileTag = 'uttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for unequal variances.' 10 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % Paired t-test and old versions need the same number of samples in both sets + if isAll || (nbSamplesA == nbSamplesB) + % NEW: paired t-test + sTest = sModel; + sTest.Name = 'pttest'; + sTest.Comment = ' t-test (paired)'; + sTest.FileTag = 'pttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for paired samples.' 10 10 ... + 'Use for testing conditions across different subjects.' 10 ... + 'New version: use much less memory.']; + sTest.Category = 'TTest'; + sTest.isPaired = 1; + sSimpleTests(end + 1) = sTest; + % OLD: t-test equal variances + sTest = sModel; + sTest.Name = 'old_ttest'; + sTest.Comment = ' OLD t-test (equal variances)'; + sTest.FileTag = 'old_ttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for equal variances.' 10 10 ... + 'Old version: might be faster and more precise.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % OLD: t-test unequal variance + sTest = sModel; + sTest.Name = 'old_uttest'; + sTest.Comment = ' OLD t-test (unequal variances)'; + sTest.FileTag = 'old_uttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for unequal variances.' 10 10 ... + 'Old version: might be faster and more precise.']; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + % OLD: paired t-test + sTest = sModel; + sTest.Name = 'old_pttest'; + sTest.Comment = ' OLD t-test (paired)'; + sTest.FileTag = 'old_pttest: #A# vs. #B#'; + sTest.Description = ['Student''s t-test for paired samples.' 10 10 ... + 'Use for testing conditions across different subjects.' 10 ... + 'Old version: might be faster and more precise.']; + sTest.isPaired = 1; + sTest.Category = 'TTest'; + sSimpleTests(end + 1) = sTest; + end + + + % ===== PERMUTATION TESTS ===== + % PERM: t-test (independent) + sTest = sModel; + sTest.Name = 'ttest'; + sTest.Comment = ' t-test (independent)'; + sTest.FileTag = 'ttest: #A# vs. #B#'; + sTest.Description = 'Student''s t-test for independent samples.'; + sTest.Category = 'PermTest'; + sPermTests(end + 1) = sTest; + % PERM: t-test (paired) + sTest = sModel; + sTest.Name = 'pairedttest'; + sTest.Comment = ' t-test (paired)'; + sTest.FileTag = 'pairedttest: #A# vs. #B#'; + sTest.Description = 'Student''s t-test for paired samples.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Sign of the differences + sTest = sModel; + sTest.Name = 'signtest'; + sTest.Comment = ' signtest (paired)'; + sTest.FileTag = 'signtest: #A# vs. #B#'; + sTest.Description = 'Sign of the differences.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Wilcoxon + sTest = sModel; + sTest.Name = 'wilcoxon'; + sTest.Comment = ' wilcoxon (paired)'; + sTest.FileTag = 'wilcoxon: #A# vs. #B#'; + sTest.Description = 'Signed ranks.'; + sTest.Category = 'PermTest'; + sTest.isPaired = 1; + sPermTests(end + 1) = sTest; + % PERM: Difference of the means + sTest = sModel; + sTest.Name = 'difftest'; + sTest.Comment = ' Difference of the means'; + sTest.FileTag = 'difftest: #A# vs. #B#'; + sTest.Description = 'Difference of the means.'; + sTest.Category = 'PermTest'; + sPermTests(end + 1) = sTest; + + % ===== ANOVA ===== + % + sTest = sModel; + sTest.Name = 'RM-Anova'; + sTest.Comment = 'Anova (under dev.)'; + sTest.FileTag = 'Anova'; + sTest.Description = 'Repeated measures parametric Analysis of Variance'; + sTest.Category = 'Anova'; + sAnova(end + 1) = sTest; + +end + + + +%% ===== FORMAT CONDITIONS STRING ===== +function str = FormatConditionsString(Samples, Default) + % If no samples + if isempty(Samples) + str = ''; + return + end + % Get the best way to display the sets names + uniqueCond = unique({Samples.Condition}); + uniqueSubj = unique({Samples.SubjectName}); + isUniqueCond = (length(uniqueCond) == 1); + isUniqueSubj = (length(uniqueSubj) == 1); + % Switch + if isUniqueCond && isUniqueSubj + str = fullfile(Samples.SubjectName, Samples.Condition); + elseif isUniqueCond + str = Samples.Condition; + elseif isUniqueSubj + str = Samples.SubjectName; + else + str = Default; + end +end + + +%% ===== FORMAT COMMENT ===== +function Comment = FormatComment(sProcess, Conditions, TimeRange) + % ===== BUILD COMMENT STRINGS ===== + sA = Conditions.SamplesA; + sB = Conditions.SamplesB; + CommentA = ''; + CommentB = ''; + % Extract some more information + isSampleBySample = ismember(sProcess.Category, {'Filter2', 'Filter', 'Extract'}); + + % === SAMPLE BY SAMPLE: A/B === + if isSampleBySample && (length(sA) == 1) && (length(sB) == 1) + if strcmpi(sA.SubjectFile, sB.SubjectFile) && strcmpi(sA.Condition, sB.Condition) + CommentA = sA.Comment; + CommentB = sB.Comment; + elseif io_compareFileNames(sA.SubjectFile, sB.SubjectFile) + CommentA = sA.Condition; + CommentB = sB.Condition; + elseif strcmpi(sA.Condition, sB.Condition) + CommentA = fullfile(sA.SubjectName, sA.Condition); + CommentB = fullfile(sB.SubjectName, sB.Condition); + else + CommentA = fullfile(sA.SubjectName, sA.Condition); + CommentB = fullfile(sB.SubjectName, sB.Condition); + end + % === AVERAGE === + elseif ~isSampleBySample + CommentA = FormatConditionsString(sA, 'A'); + CommentB = FormatConditionsString(sB, 'B'); + end + + % Build string for time interval + if (max(abs(TimeRange)) > 2) + strTime = sprintf('(%1.2fs,%1.2fs)', TimeRange); + else + strTime = sprintf('(%dms,%dms)', round(TimeRange * 1000)); + end + % Apply process naming + if ~isempty(CommentA) || isempty(sB) + Comment = sProcess.FileTag; + Comment = strrep(Comment, '#A#', CommentA); + Comment = strrep(Comment, '#B#', CommentB); + Comment = strrep(Comment, '#TIME#', strTime); + else + Comment = ''; + end +end + + +%% ===== GET CLUSTERS ===== +% OUTPUT: +% - sClusters : -1, if no channel file available for at least one sample +% -2, if no clusters available +% Else, return an array of Cluster structures +function [sClusters, iClusters] = GetClusters(Cond) + % Get unique list of studies + iStudies = unique([Cond.SamplesA.iStudy, Cond.SamplesB.iStudy]); + % Process all studies + for i = 1:length(iStudies) + % Get study structure + iStudy = iStudies(i); + %sStudy = bst_getContext('Study', iStudy); + sChannel = bst_getContext('ChannelForStudy', iStudy); + % Check that a ChannelFile is defined for this study + if isempty(sChannel) + sClusters = -1; + iClusters = []; + return + end + end + % Get the scouts available for this surface + [sClusters, iClusters] = panel_clusters('GetClusters'); + % If no scout avaialable: error + if isempty(sClusters) + sClusters = -2; + iClusters = []; + return; + end +end + + +%% ===== GET SCOUTS ===== +% OUTPUT: +% - sScouts : -1, if all samples do not refer to the same cortical surface +% -2, if no scout avaialable +% Else, return an array of scout structures +function [sScouts, iScouts] = GetScouts(Cond) + iScouts = []; + % Get studies and results indices + iStudies = [Cond.SamplesA.iStudy, Cond.SamplesB.iStudy]; + iResults = [Cond.SamplesA.iItem, Cond.SamplesB.iItem]; + SurfaceFile = []; + % Process all studies + for i = 1:length(iStudies) + iStudy = iStudies(i); + sStudy = bst_getContext('Study', iStudy); + % Get result file + ResultsMat = in_results_bst(sStudy.Result(iResults(i)).FileName, 0, 'SurfaceFile'); + % If it is first results: store the surface file + if isempty(SurfaceFile) + SurfaceFile = ResultsMat.SurfaceFile; + % If surface file is not the same than previous files: error + elseif ~io_compareFileNames(ResultsMat.SurfaceFile, SurfaceFile) + sScouts = -1; + return + end + end + % Get the scouts available for this surface + [sScouts, iScouts] = panel_scouts('GetScoutsWithSurface', SurfaceFile); + % If no scout avaialable: error + if isempty(sScouts) + sScouts = -2; + return; + end +end + + +%% ================================================================================================ +% ===== HELPERS ================================================================================== +% ================================================================================================ +%% ===== GET FILE TIME VECTOR ===== +function TimeVector = GetFileTimeVector(iStudy, iItem, isData) + TimeVector = []; + % Get protocols directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get study + sStudy = bst_getContext('Study', iStudy); + % Load time range from this file + if (isData) + % Build filename + filename = fullfile(ProtocolInfo.STUDIES, sStudy.Data(iItem).FileName); + % Load time vector + DataMat = load(filename, 'Time'); + if ~isempty(DataMat) && isfield(DataMat, 'Time') && ~isempty(DataMat.Time) + TimeVector = DataMat.Time; + end + else + % Build filename + refFilename = fullfile(ProtocolInfo.STUDIES, sStudy.Result(iItem).FileName); + % Resvole link + refFilename = resolveResultsLink(refFilename); + % Is results file is a kernel-only file + isKernel = ~isempty(strfind(refFilename, 'KERNEL')); + % KERNEL + if isKernel + % No time information available in file => Use DataMat results + DataFile = strrep(sStudy.Result(iItem).DataFile, ProtocolInfo.STUDIES, ''); + DataFileFull = fullfile(ProtocolInfo.STUDIES, DataFile); + DataMat = load(DataFileFull, 'Time'); + if ~isempty(DataMat) && isfield(DataMat, 'Time') && ~isempty(DataMat.Time) + TimeVector = DataMat.Time; + end + % FULL RESULTS FILE + else + % Load time vector + ResultMat = in_results_bst(refFilename, 0, 'ImageGridTime'); + if ~isempty(ResultMat) && isfield(ResultMat, 'ImageGridTime') + TimeVector = ResultMat.ImageGridTime; + end + end + end +end + + diff --git a/brainstorm3/toolbox/gui/panel_surface.m b/brainstorm3/toolbox/gui/panel_surface.m new file mode 100644 index 0000000..582dceb --- /dev/null +++ b/brainstorm3/toolbox/gui/panel_surface.m @@ -0,0 +1,1840 @@ +function varargout = panel_surface(varargin) +% PANEL_SURFACE: Panel to load and plot surfaces. +% +% USAGE: bstPanel = panel_surface('CreatePanel') +% panel_surface('UpdatePanel') +% panel_surface('CurrentFigureChanged_Callback') +% nbSurfaces = panel_surface('CreateSurfaceList', % % iSurface = panel_surface('AddSurface', hFig, surfaceFile) +% panel_surface('UpdateSurfaceProperties') +% iSurface = panel_surface('AddSurface', hFig, surfaceFile) +% panel_surface('RemoveSurface', hFig, iSurface) +% panel_surface('SetSurfaceTransparency', hFig, iSurf, alpha) +% panel_surface('SetSurfaceColor', hFig, iSurf, newColor) +% panel_surface('ApplyDefaultDisplay') +% [isOk] = panel_surface('SetSurfaceData', hFig, iTess, dataType, dataFile, isStat, isZscore) + +% [isOk] = panel_surface('UpdateSurfaceData', hFig, iSurfaces) +% [iCortex,TessInfo,hFig] = panel_surface('GetSurfaceCortex') +% iCortex = panel_surface('GetSurfaceCortex', hFig) +% panel_surface('UpdateOverlayCube', hFig, iTess) + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% No parameters +if (nargin == 0) +% Else : execute appropriate local function +elseif ischar(varargin{1}) + if (nargout) + [varargout{1:nargout}] = bst_safeCall(str2func(varargin{1}), varargin{2:end}); + else + bst_safeCall(str2func(varargin{1}), varargin{2:end}); + end +end +end + + +%% ===== CREATE PANEL ===== +function bstPanelNew = CreatePanel() %#ok + panelName = 'Surface'; + % Java initializations + import java.awt.*; + import javax.swing.*; + import org.brainstorm.icon.IconLoader; + + % Constants + LABEL_WIDTH = 30; + BUTTON_WIDTH = 40; + SLIDER_WIDTH = 20; + DEFAULT_HEIGHT = 22; + TB_HEIGHT = 28; + jFontText = java.awt.Font('Dialog', java.awt.Font.PLAIN, 10); + % Create panel + jPanelNew = JPanel(BorderLayout()); + jPanelNew.setBorder([]); + + % ==================================================================== + % ==== TOOLBAR : SURFACES LIST ======================================= + % Create Toolbar + jToolbarSurfaces = JToolBar('Edit scouts'); + jToolbarSurfaces.setBorderPainted(0); + jToolbarSurfaces.setFloatable(0); + jToolbarSurfaces.setRollover(1); + jToolbarSurfaces.setPreferredSize(Dimension(100, TB_HEIGHT)); + % Add title "Surfaces" + jLabelSurfacesTitle = JLabel(' Surfaces:'); + jLabelSurfacesTitle.setFont(jFontText); + jToolbarSurfaces.add(jLabelSurfacesTitle); + % Separation panel + jToolbarSurfaces.add(JPanel()); + % Add separator + jToolbarSurfaces.addSeparator(Dimension(10, TB_HEIGHT)); + % Create "Add" button + jButtonAddSurface = JButton(IconLoader.ICON_SURFACE_ADD); + jButtonAddSurface.setMaximumSize(Dimension(26, 26)); + jButtonAddSurface.setPreferredSize(Dimension(26, 26)); + jButtonAddSurface.setToolTipText('Add a surface'); + jButtonAddSurface.setFocusPainted(0); + set(jButtonAddSurface, 'ActionPerformedCallback', @ButtonAddSurfaceCallback); + jToolbarSurfaces.add(jButtonAddSurface); + % Create "Remove" button + jButtonRemoveSurface = JButton(IconLoader.ICON_SURFACE_REMOVE); + jButtonRemoveSurface.setMaximumSize(Dimension(26, 26)); + jButtonRemoveSurface.setPreferredSize(Dimension(26, 26)); + jButtonRemoveSurface.setToolTipText('Remove surface from figure'); + jButtonRemoveSurface.setFocusPainted(0); + set(jButtonRemoveSurface, 'ActionPerformedCallback', @ButtonRemoveSurfaceCallback); + jToolbarSurfaces.add(jButtonRemoveSurface); + jPanelNew.add(jToolbarSurfaces, BorderLayout.NORTH); + + % ==================================================================== + % ==== OPTIONS PANEL ================================================== + % Create OPTIONS scrollpane + jPanelOptions = getRiverPanel([3,5]); + % ===== Create panel : surface configuration ===== + jPanelSurfaceOptions = getRiverPanel([1,1], [1,1,1,1], 'Surface options'); + % Alpha title + jLabelTranspTitle = JLabel('Transp.:'); + jLabelTranspTitle.setFont(jFontText); + jPanelSurfaceOptions.add('br', jLabelTranspTitle); + % Alpha slider + jSliderSurfAlpha = JSlider(0, 100, 0); + jSliderSurfAlpha.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderSurfAlpha, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'SurfAlpha'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'SurfAlpha')); + jPanelSurfaceOptions.add('tab hfill', jSliderSurfAlpha); + % Alpha label + jLabelSurfAlpha = JLabel(' ', JLabel.RIGHT); + jLabelSurfAlpha.setFont(jFontText); + jLabelSurfAlpha.setPreferredSize(Dimension(LABEL_WIDTH, DEFAULT_HEIGHT)); + jLabelSurfAlpha.setToolTipText('Set surface transparency'); + jPanelSurfaceOptions.add(jLabelSurfAlpha); + % Color button + jButtonSurfColor = JButton('Color'); + jButtonSurfColor.setFont(jFontText); + jButtonSurfColor.setPreferredSize(Dimension(BUTTON_WIDTH, DEFAULT_HEIGHT)); + jButtonSurfColor.setMargin(Insets(0,0,0,0)); + jButtonSurfColor.setToolTipText('Set surface color'); + jButtonSurfColor.setFocusPainted(0); + set(jButtonSurfColor, 'ActionPerformedCallback', @ButtonSurfColorCallback); + jPanelSurfaceOptions.add(jButtonSurfColor); + + % Curvature title and slider + jLabelCurvTitle = JLabel('Curvature:'); + jLabelCurvTitle.setFont(jFontText); + jPanelSurfaceOptions.add('br', jLabelCurvTitle); + % Curvature : [-0.20, 0.20] with step=0.01 => Integer:[-20,20] + jSliderSurfCurvature = JSlider(-20, 20, 0); + jSliderSurfCurvature.setPreferredSize(Dimension(SLIDER_WIDTH,DEFAULT_HEIGHT)); + set(jSliderSurfCurvature, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'SurfCurvature'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'SurfCurvature')); + jPanelSurfaceOptions.add('tab hfill', jSliderSurfCurvature); + % Curvature label + jLabelSurfCurvature = JLabel(' ', JLabel.RIGHT); + jLabelSurfCurvature.setFont(jFontText); + jLabelSurfCurvature.setPreferredSize(Dimension(LABEL_WIDTH,DEFAULT_HEIGHT)); + jPanelSurfaceOptions.add(jLabelSurfCurvature); + % Curvature 'View' button + jButtonSurfCurvature = JToggleButton('Show'); + jButtonSurfCurvature.setFont(jFontText); + jButtonSurfCurvature.setPreferredSize(Dimension(BUTTON_WIDTH,DEFAULT_HEIGHT)); + jButtonSurfCurvature.setMargin(Insets(0,0,0,0)); + jButtonSurfCurvature.setToolTipText('Show/hide surface curvature'); + jButtonSurfCurvature.setFocusPainted(0); + set(jButtonSurfCurvature, 'ActionPerformedCallback', @ButtonShowCurvatureCallback); + jPanelSurfaceOptions.add(jButtonSurfCurvature); + + % Smooth title + jLabelSmoothTitle = JLabel('Smooth:'); + jLabelSmoothTitle.setFont(jFontText); + jPanelSurfaceOptions.add('br', jLabelSmoothTitle); + % Smooth slider + jSliderSurfSmoothValue = JSlider(0, 100, 0); + jSliderSurfSmoothValue.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + jSliderSurfSmoothValue.setToolTipText('Smooth surface'); + set(jSliderSurfSmoothValue, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'SurfSmoothValue'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'SurfSmoothValue')); + jPanelSurfaceOptions.add('tab hfill', jSliderSurfSmoothValue); + % Smooth ALPHA label + jLabelSurfSmoothValue = JLabel(' ', JLabel.RIGHT); + jLabelSurfSmoothValue.setFont(jFontText); + jLabelSurfSmoothValue.setPreferredSize(Dimension(LABEL_WIDTH, DEFAULT_HEIGHT)); + jPanelSurfaceOptions.add(jLabelSurfSmoothValue); + + % Edge button + jButtonSurfEdge = JToggleButton('Edge'); + jButtonSurfEdge.setFont(jFontText); + jButtonSurfEdge.setPreferredSize(Dimension(BUTTON_WIDTH,DEFAULT_HEIGHT)); + jButtonSurfEdge.setMargin(Insets(0,0,0,0)); + jButtonSurfEdge.setToolTipText('Show/hide surface triangles'); + jButtonSurfEdge.setFocusPainted(0); + set(jButtonSurfEdge, 'ActionPerformedCallback', @ButtonShowEdgesCallback); + jPanelSurfaceOptions.add(jButtonSurfEdge); + jPanelOptions.add('br hfill', jPanelSurfaceOptions); + + % ===== Create panel : data description ===== + jPanelDataOptions = getRiverPanel([1,1], [1,8,1,10], 'Data options'); + % ====================== + % Threshold label + jLabelIntThreshTitle = JLabel('Int. Thresh.:'); + jLabelIntThreshTitle.setFont(jFontText); + jPanelDataOptions.add(jLabelIntThreshTitle); + % Threshold slider + jSliderDataIntThresh = JSlider(0, 100, 50); + jSliderDataIntThresh.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderDataIntThresh, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'DataIntThreshold'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'DataIntThreshold')); + jPanelDataOptions.add('tab hfill', jSliderDataIntThresh); + % Threshold label + jLabelDataIntThresh = JLabel(' ', JLabel.RIGHT); + jLabelDataIntThresh.setFont(jFontText); + jLabelDataIntThresh.setPreferredSize(Dimension(LABEL_WIDTH, DEFAULT_HEIGHT)); + jPanelDataOptions.add(jLabelDataIntThresh); + + % ====================== + % Cluster size (extent) threshold + jLabelExtThreshTitle = JLabel('Extent Thr.:'); + jLabelExtThreshTitle.setFont(jFontText); + jPanelDataOptions.add('br', jLabelExtThreshTitle); + % Threshold slider + jSliderDataExtThresh = JSlider(0, 100, 50); + jSliderDataExtThresh.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderDataExtThresh, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'DataExtThreshold'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'DataExtThreshold')); + jPanelDataOptions.add('tab hfill', jSliderDataExtThresh); + % Threshold label + jLabelDataExtThresh = JLabel(' ', JLabel.RIGHT); + jLabelDataExtThresh.setFont(jFontText); + jLabelDataExtThresh.setPreferredSize(Dimension(LABEL_WIDTH, DEFAULT_HEIGHT)); + jPanelDataOptions.add(jLabelDataExtThresh); + + % ====================== + % Alpha title and slider + jLabelAlphaTitle = JLabel('Transp.:'); + jLabelAlphaTitle.setFont(jFontText); + jPanelDataOptions.add('br', jLabelAlphaTitle); + jSliderDataAlpha = JSlider(0, 100, 0); + jSliderDataAlpha.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderDataAlpha, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'DataAlpha'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'DataAlpha')); + jPanelDataOptions.add('tab hfill', jSliderDataAlpha); + % Data alpha label + jLabelDataAlpha = JLabel(' ', JLabel.RIGHT); + jLabelDataAlpha.setFont(jFontText); + jLabelDataAlpha.setPreferredSize(Dimension(LABEL_WIDTH, DEFAULT_HEIGHT)); + jPanelDataOptions.add(jLabelDataAlpha); + + jPanelOptions.add('br hfill', jPanelDataOptions); + + % ===== Create panel : surface resect ===== + jPanelSurfaceResect = getRiverPanel([0,4], [1,8,8,0], 'Resect [X,Y,Z]'); + % === RESECT SLIDERS === + % Sub panel + panelResect = JPanel(); + panelResect.setLayout(BoxLayout(panelResect, BoxLayout.LINE_AXIS)); + % Resect X : Slider + jSliderResectX = JSlider(-100, 100, 0); + jSliderResectX.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderResectX, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'ResectX'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'ResectX')); + panelResect.add('hfill', jSliderResectX); + % Resect Y : Title and Slider + jSliderResectY = JSlider(-100, 100, 0); + jSliderResectY.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderResectY, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'ResectY'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'ResectY')); + panelResect.add('hfill', jSliderResectY); + % Resect Z : Title and Slider + jSliderResectZ = JSlider(-100, 100, 0); + jSliderResectZ.setPreferredSize(Dimension(SLIDER_WIDTH, DEFAULT_HEIGHT)); + set(jSliderResectZ, 'MouseReleasedCallback', @(h,ev)SliderCallback(h, ev, 'ResectZ'), ... + 'KeyPressedCallback', @(h,ev)SliderCallback(h, ev, 'ResectZ')); + panelResect.add('hfill', jSliderResectZ); + jPanelSurfaceResect.add('hfill', panelResect); + + % === HEMISPHERES SELECTION === + % Title + jPanelSurfaceResect.add('br', JLabel(' ')); + % Left Hemisphere + jToggleResectLeft = JToggleButton('Left'); + jToggleResectLeft.setFont(jFontText); + jToggleResectLeft.setMargin(Insets(0,0,0,0)); + jToggleResectLeft.setPreferredSize(Dimension(50, 20)); + jToggleResectLeft.setFocusPainted(0); + set(jToggleResectLeft, 'MouseReleasedCallback', @ButtonResectLeftToggle_Callback); + jPanelSurfaceResect.add(jToggleResectLeft); + + % Right Hemisphere + jToggleResectRight = JToggleButton('Right'); + jToggleResectRight.setFont(jFontText); + jToggleResectRight.setMargin(Insets(0,0,0,0)); + jToggleResectRight.setPreferredSize(Dimension(50, 20)); + jToggleResectRight.setFocusPainted(0); + set(jToggleResectRight, 'MouseReleasedCallback', @ButtonResectRightToggle_Callback); + jPanelSurfaceResect.add(jToggleResectRight); + + % Separator + jPanelSurfaceResect.add('hfill', JLabel(' ')); + + % Reset button + jButtonResectReset = JButton('Reset'); + jButtonResectReset.setFont(jFontText); + jButtonResectReset.setMargin(Insets(0,0,0,0)); + jButtonResectReset.setPreferredSize(Dimension(50, 20)); + jButtonResectReset.setFocusPainted(0); + set(jButtonResectReset, 'ActionPerformedCallback', @ButtonResectResetCallback); + jPanelSurfaceResect.add(jButtonResectReset); + % Separator from the border + jPanelSurfaceResect.add(JLabel(' ')); + + jPanelOptions.add('br hfill', jPanelSurfaceResect); + + % NbVertices Title + jLabelNbVertTitle = JLabel(' Vertices : '); + jLabelNbVertTitle.setFont(jFontText); + jPanelOptions.add('br', jLabelNbVertTitle); + % NbVertices + jLabelNbVertices = JLabel('0'); + jLabelNbVertices.setFont(jFontText); + jPanelOptions.add(jLabelNbVertices); + % NbFaces Title + jLabelNbFacesTitle = JLabel(' Faces : '); + jLabelNbFacesTitle.setFont(jFontText); + jPanelOptions.add(jLabelNbFacesTitle); + % NbFaces + jLabelNbFaces = JLabel('0'); + jLabelNbFaces.setFont(jFontText); + jPanelOptions.add(jLabelNbFaces); + + jScrollPaneOptions = JScrollPane(jPanelOptions); + jScrollPaneOptions.setBorder([]); + jPanelNew.add(jScrollPaneOptions, BorderLayout.CENTER); + + % Create the BstPanel object that is returned by the function + % => constructor BstPanel(jHandle, panelName, sControls) + bstPanelNew = BstPanel(panelName, ... + jPanelNew, ... + struct('jToolbarSurfaces', jToolbarSurfaces, ... + 'jPanelOptions', jPanelOptions, ... + 'jPanelSurfaceOptions', jPanelSurfaceOptions, ... + 'jPanelSurfaceResect', jPanelSurfaceResect, ... + 'jPanelDataOptions', jPanelDataOptions, ... + 'jLabelNbVertices', jLabelNbVertices, ... + 'jLabelNbFaces', jLabelNbFaces, ... + 'jSliderSurfAlpha', jSliderSurfAlpha, ... + 'jLabelSurfAlpha', jLabelSurfAlpha, ... + 'jButtonSurfColor', jButtonSurfColor, ... + 'jLabelSurfSmoothValue', jLabelSurfSmoothValue, ... + 'jSliderSurfSmoothValue', jSliderSurfSmoothValue, ... + 'jSliderSurfCurvature', jSliderSurfCurvature, ... + 'jLabelSurfCurvature', jLabelSurfCurvature, ... + 'jButtonSurfCurvature', jButtonSurfCurvature, ... + 'jButtonSurfEdge', jButtonSurfEdge, ... + 'jSliderResectX', jSliderResectX, ... + 'jSliderResectY', jSliderResectY, ... + 'jSliderResectZ', jSliderResectZ, ... + 'jToggleResectLeft', jToggleResectLeft, ... + 'jToggleResectRight', jToggleResectRight, ... + 'jSliderDataAlpha', jSliderDataAlpha, ... + 'jLabelDataAlpha', jLabelDataAlpha, ... + 'jSliderDataExtThresh', jSliderDataExtThresh, ... + 'jLabelDataExtThresh', jLabelDataExtThresh, ... + 'jSliderDataIntThresh', jSliderDataIntThresh, ... + 'jLabelDataIntThresh', jLabelDataIntThresh)); + + + + %% ===== RESET RESECT CALLBACK ===== + function ButtonResectResetCallback(varargin) + import java.awt.event.MouseEvent; + % Reset initial resect sliders positions + jSliderResectX.setValue(0); + jSliderResectY.setValue(0); + jSliderResectZ.setValue(0); + SliderCallback([], MouseEvent(jSliderResectX, 0, 0, 0, 0, 0, 1, 0), 'ResectX'); + SliderCallback([], MouseEvent(jSliderResectY, 0, 0, 0, 0, 0, 1, 0), 'ResectY'); + SliderCallback([], MouseEvent(jSliderResectZ, 0, 0, 0, 0, 0, 1, 0), 'ResectZ'); + end + + %% ===== RESECT LEFT TOGGLE CALLBACK ===== + function ButtonResectLeftToggle_Callback(varargin) + if jToggleResectLeft.isSelected() + jToggleResectRight.setSelected(0); + SelectHemispheres('left'); + else + SelectHemispheres('none'); + end + end + + %% ===== RESECT RIGHT TOGGLE CALLBACK ===== + function ButtonResectRightToggle_Callback(varargin) + if jToggleResectRight.isSelected() + jToggleResectLeft.setSelected(0); + SelectHemispheres('right'); + else + SelectHemispheres('none'); + end + end +end + + +%% ================================================================================= +% === CONTROLS CALLBACKS ========================================================= +% ================================================================================= +%% ===== SLIDERS CALLBACKS ===== +function SliderCallback(hObject, event, target) + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Surface'); + % Get slider pointer + jSlider = event.getSource(); + % If slider is not enabled : do nothing + if ~jSlider.isEnabled() + return + end + + % Get handle to current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get current surface index (in the current figure) + iSurface = getappdata(hFig, 'iSurface'); + % If surface data is not accessible + if isempty(hFig) || isempty(iSurface) + return; + end + % Get figure AppData (figure's surfaces configuration) + TessInfo = getappdata(hFig, 'Surface'); + if (iSurface > length(TessInfo)) + return; + end + % Is selected surface a MRI/slices surface + isAnatomy = strcmpi(TessInfo(iSurface).Name, 'Anatomy'); + + % Get slider value and update surface value + switch (target) + case 'SurfAlpha' + % Update value in Surface array + TessInfo(iSurface).SurfAlpha = jSlider.getValue() / 100; + % Display value in the label associated with the slider + ctrl.jLabelSurfAlpha.setText(sprintf('%d%%', round(TessInfo(iSurface).SurfAlpha * 100))); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % For MRI: redraw all slices + if isAnatomy + figure_callback(hFig, 'UpdateMriDisplay', hFig, [], TessInfo, iSurface); + % Else: Update color display on the surface + else + figure_callback(hFig, 'UpdateSurfaceAlpha', hFig, iSurface); + end + + case 'SurfSmoothValue' + TessInfo(iSurface).SurfSmoothValue = jSlider.getValue() / 100; + ctrl.jLabelSurfSmoothValue.setText(sprintf('%d%%', round(TessInfo(iSurface).SurfSmoothValue * 100))); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % For MRI display : Smooth slider changes threshold + if isAnatomy + figure_callback(hFig, 'UpdateMriDisplay', hFig, [], TessInfo, iSurface); + % Else: Update color display on the surface + else + % Smooth surface + figure_callback(hFig, 'UpdateSurfaceAlpha', hFig, iSurface); + % Update scouts displayed on this surfce + panel_scouts('UpdateScoutsVertices', TessInfo(iSurface).SurfaceFile); + % Set the new value as the default value + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + DefaultSurfaceDisplay.SurfSmoothValue = TessInfo(iSurface).SurfSmoothValue; + bst_setContext('DefaultSurfaceDisplay', DefaultSurfaceDisplay); + end + + case 'SurfCurvature' + % Update value in Surface array + % Correspondance : [-80,80] <=> [-0.80, 0.80] + TessInfo(iSurface).SurfCurvatureThreshold = jSlider.getValue() / 100; + ctrl.jLabelSurfCurvature.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).SurfCurvatureThreshold))); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % Update surface display (ONLY if Curvature is currently displayed) + if TessInfo(iSurface).SurfShowCurvature + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurface); + end + + case 'DataAlpha' + % Update value in Surface array + TessInfo(iSurface).DataAlpha = jSlider.getValue() / 100; + ctrl.jLabelDataAlpha.setText(sprintf('%d%%', round(TessInfo(iSurface).DataAlpha * 100))); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % Update color display on the surface + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurface); + + case 'DataIntThreshold' + % Update value in Surface array + TessInfo(iSurface).DataIntThreshold = jSlider.getValue() / 100; + ctrl.jLabelDataIntThresh.setText(sprintf('%d%%', round(TessInfo(iSurface).DataIntThreshold * 100))); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % Update color display on the surface + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurface); + % Set the new value as the default value (NOT FOR MRI) + if ~isAnatomy + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + DefaultSurfaceDisplay.DataIntThreshold = TessInfo(iSurface).DataIntThreshold; + bst_setContext('DefaultSurfaceDisplay', DefaultSurfaceDisplay); + end + + case 'DataExtThreshold' + % Threshold based on cluster size + % I use a very gross exponential scale + % Update value in Surface array + %TessInfo(iSurface).DataExtThreshold = round(exp(jSlider.getValue()/15))-1; + TessInfo(iSurface).DataExtThreshold = round(jSlider.getValue())-1; + ctrl.jLabelDataExtThresh.setText(sprintf('%d', TessInfo(iSurface).DataExtThreshold)); + % Update current surface + setappdata(hFig, 'Surface', TessInfo); + % Update color display on the surface + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurface); + % Set the new value as the default value (NOT FOR MRI) + if ~isAnatomy + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + DefaultSurfaceDisplay.DataExtThreshold = TessInfo(iSurface).DataExtThreshold; + bst_setContext('DefaultSurfaceDisplay', DefaultSurfaceDisplay); + end + + case {'ResectX', 'ResectY', 'ResectZ'} + % Get target axis + dim = find(strcmpi(target, {'ResectX', 'ResectY', 'ResectZ'})); + % JSliderResect values : [-100,100] + if isAnatomy + % Get MRI size + sMri = bst_dataSetsManager('GetMri', TessInfo(iSurface).SurfaceFile); + cubeSize = size(sMri.Cube); + % Change slice position + newPos = round((jSlider.getValue()+100) / 200 * cubeSize(dim)); + newPos = saturate(newPos, [1, cubeSize(dim)]); + TessInfo(iSurface).CutsPosition(dim) = newPos; + % Update MRI display + figure_callback(hFig, 'UpdateMriDisplay', hFig, dim, TessInfo, iSurface); + else + ResectSurface(hFig, iSurface, dim, jSlider.getValue() / 100); + end + + otherwise + error('Unknow slider'); + end +end + + + +%% ===== BUTTON SURFACE COLOR CALLBACK ===== +function ButtonSurfColorCallback(hObject, event) + % Get handle to current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get figure AppData (figure's surfaces configuration) + TessInfo = getappdata(hFig, 'Surface'); + % Get current surface index (in the current figure) + iSurface = getappdata(hFig, 'iSurface'); + % Ignore MRI slices + if strcmpi(TessInfo(iSurface).Name, 'Anatomy') + return + end + % Ask user to select a color + newColor2 = uisetcolor(TessInfo(iSurface).AnatomyColor(2,:), 'Select surface color'); + if (length(newColor2) ~= 3) + return + end + % Change surface color + SetSurfaceColor(hFig, iSurface, newColor2); +end + + + +%% ===== BUTTON SURFACE "SHOW CURVATURE" CALLBACK ===== +function ButtonShowCurvatureCallback(hObject, event) + % Get handle to current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get current surface index (in the current figure) + iSurface = getappdata(hFig, 'iSurface'); + % Get handle to "View" button + jButtonSurfCurvature = event.getSource(); + % Show/hide curvature in figure display + SetShowCurvature(hFig, iSurface, jButtonSurfCurvature.isSelected()); + % Set the new value as the default value + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + DefaultSurfaceDisplay.SurfShowCurvature = jButtonSurfCurvature.isSelected(); + bst_setContext('DefaultSurfaceDisplay', DefaultSurfaceDisplay); +end + +%% ===== SET SHOW CURVATURE ===== +% Usage : SetShowCurvature(hFig, iSurfaces, status) +% Parameters : +% - hFig : handle to a 3DViz figure +% - iSurfaces : can be a single indice or an array of indices +% - status : 1=display, 0=hide +function SetShowCurvature(hFig, iSurfaces, status) + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + gui_makeuswait('start') + % Process all surfaces + for iSurf = iSurfaces + % Shet status : show/hide + TessInfo(iSurf).SurfShowCurvature = status; + end + % Update figure's AppData (surfaces configuration) + setappdata(hFig, 'Surface', TessInfo); + % Update surface display + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurf); + gui_makeuswait('stop'); +end + + +%% ===== SHOW SURFACE EDGES ===== +function ButtonShowEdgesCallback(varargin) + % Get handle to current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get current surface (in the current figure) + TessInfo = getappdata(hFig, 'Surface'); + iSurf = getappdata(hFig, 'iSurface'); + % Set edges display on/off + TessInfo(iSurf).SurfShowEdges = ~TessInfo(iSurf).SurfShowEdges; + setappdata(hFig, 'Surface', TessInfo); + % Update display + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurf); +end + + +%% ===== HEMISPHERE SELECTION RADIO CALLBACKS ===== +function SelectHemispheres(name) + % Get handle to current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get surface properties + TessInfo = getappdata(hFig, 'Surface'); + iSurf = getappdata(hFig, 'iSurface'); + % Ignore MRI + if strcmpi(TessInfo(iSurf).Name, 'Anatomy') + return; + end + % Update surface Resect field + TessInfo(iSurf).Resect = name; + setappdata(hFig, 'Surface', TessInfo); + + % Reset all the resect sliders + ctrl = bst_getContext('PanelControls', 'Surface'); + ctrl.jSliderResectX.setValue(0); + ctrl.jSliderResectY.setValue(0); + ctrl.jSliderResectZ.setValue(0); + + % Display progress bar + bst_progressBar('start', 'Select hemisphere', 'Selecting hemisphere...'); + % Update surface display + figure_callback(hFig, 'UpdateSurfaceAlpha', hFig, iSurf); + % Display progress bar + bst_progressBar('stop'); +end + + +%% ===== RESECT SURFACE ===== +function ResectSurface(hFig, iSurf, resectDim, resectValue) + % Get surfaces description + TessInfo = getappdata(hFig, 'Surface'); + % If previously using "Select hemispheres" + if ischar(TessInfo(iSurf).Resect) + % Reset "Resect" field + TessInfo(iSurf).Resect = [0 0 0]; + end + % Update value in Surface array + TessInfo(iSurf).Resect(resectDim) = resectValue; + % Update surface + setappdata(hFig, 'Surface', TessInfo); + % Hide trimmed part of the surface + figure_callback(hFig, 'UpdateSurfaceAlpha', hFig, iSurf); + + % Deselect both Left and Right buttons + ctrl = bst_getContext('PanelControls', 'Surface'); + ctrl.jToggleResectLeft.setSelected(0); + ctrl.jToggleResectRight.setSelected(0); +end + + +%% ===== ADD SURFACE CALLBACK ===== +function ButtonAddSurfaceCallback(varargin) + % Get target figure handle + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get Current subject + SubjectFile = getappdata(hFig, 'SubjectFile'); + if isempty(SubjectFile) + return + end + sSubject = bst_getContext('Subject', SubjectFile); + if isempty(sSubject) + return + end + + % List of available surfaces types + typesList = {}; + if ~isempty(sSubject.iScalp) + typesList{end+1} = 'Scalp'; + end + if ~isempty(sSubject.iOuterSkull) + typesList{end+1} = 'OuterSkull'; + end + if ~isempty(sSubject.iInnerSkull) + typesList{end+1} = 'InnerSkull'; + end + if ~isempty(sSubject.iCortex) + typesList{end+1} = 'Cortex'; + end + if ~isempty(sSubject.iAnatomy) + typesList{end+1} = 'Anatomy'; + end + if isempty(typesList) + return + end + % Ask user which kind of surface he wants to add to the figure 3DViz + surfaceType = java_dialog('question', 'What kind of surface would you like to display ?', 'Add surface', [], typesList, typesList{1}); + + % Switch between surfaces types + switch (surfaceType) + case 'Anatomy' + SurfaceFile = sSubject.Anatomy(sSubject.iAnatomy(1)).FileName; + case 'Cortex' + SurfaceFile = sSubject.Surface(sSubject.iCortex(1)).FileName; + case 'Scalp' + SurfaceFile = sSubject.Surface(sSubject.iScalp(1)).FileName; + case 'InnerSkull' + SurfaceFile = sSubject.Surface(sSubject.iInnerSkull(1)).FileName; + case 'OuterSkull' + SurfaceFile = sSubject.Surface(sSubject.iSurfaceFile(1)).FileName; + otherwise + return; + end + % Add surface to the figure + AddSurface(hFig, SurfaceFile); + % 3D MRI: Update Colormap + if strcmpi(surfaceType, 'Anatomy') + % Get figure + [hFig,iFig,iDS] = gui_figuresManager('GetFigure', hFig); + % Update colormap + gui_figure3DViz('ColormapChangedCallback', iDS, iFig); + end +end + + +%% ===== REMOVE SURFACE CALLBACK ===== +function ButtonRemoveSurfaceCallback(varargin) + % Get target figure handle + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get current surface index + iSurface = getappdata(hFig, 'iSurface'); + if isempty(iSurface) + return + end + % Remove surface + RemoveSurface(hFig, iSurface); + % Update "Surfaces" panel + UpdatePanel(); +end + + +%% ===== SURFACE BUTTON CLICKED CALLBACK ===== +function ButtonSurfaceClickedCallback(hObject, event, varargin) + % Get current 3DViz figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get index of the surface associated to this button + iSurface = str2num(event.getSource.getName()); + % Store current surface index + setappdata(hFig, 'iSurface', iSurface); + % Update scouts surface + panel_scouts('UpdateCurrentSurface'); + % Update surface properties + UpdateSurfaceProperties(); +end + + + +%% ================================================================================= +% === EXTERNAL CALLBACKS ========================================================= +% ================================================================================= +%% ===== UPDATE PANEL ===== +function UpdatePanel(varargin) + % Get JComboBox pointer + panelSurfacesCtrl = bst_getContext('PanelControls', 'Surface'); + if isempty(panelSurfacesCtrl) + return + end + % If no current 3D figure defined + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + % Remove surface buttons + CreateSurfaceList(panelSurfacesCtrl.jToolbarSurfaces, 0); + % Disable all panel controls + gui_setEnabledControls([panelSurfacesCtrl.jToolbarSurfaces, panelSurfacesCtrl.jPanelOptions], 0); + else + % Enable Surfaces selection panel + gui_setEnabledControls(panelSurfacesCtrl.jToolbarSurfaces, 1); + % Update surfaces list + nbSurfaces = CreateSurfaceList(panelSurfacesCtrl.jToolbarSurfaces, hFig); + % If no surface is available + if (nbSurfaces <= 0) + % Disable "Display" and "Options" panel + gui_setEnabledControls(panelSurfacesCtrl.jPanelOptions, 0); + % Else : one or more surfaces are available + else + % Enable "Display" and "Options" panel + gui_setEnabledControls(panelSurfacesCtrl.jPanelOptions, 1); + % Update surface properties + UpdateSurfaceProperties(); + end + end +end + + +%% ===== DISPATCH FIGURE CALLBACKS ===== +function figure_callback(hFig, CallbackName, varargin) + % Get figure type + FigureId = getappdata(hFig, 'FigureId'); + % Different figure types + switch (FigureId.Type) + case 'MriViewer' + gui_figureMriViewer(CallbackName, varargin{:}); + case '3DViz' + gui_figure3DViz(CallbackName, varargin{:}); + end +end + + +%% ===== CURRENT FIGURE CHANGED ===== +function CurrentFigureChanged_Callback() %#ok + UpdatePanel(); +end + + +%% ===== CREATE SURFACES LIST ===== +function nbSurfaces = CreateSurfaceList(jToolbarSurfaces, hFig) + % Java initializations + import java.awt.*; + import javax.swing.*; + import org.brainstorm.icon.IconLoader; + + nbSurfaces = 0; + % Remove all toolbar surface buttons + for iComp = 1:jToolbarSurfaces.getComponentCount()-5 + jToolbarSurfaces.remove(1); + end + % If no figure is specified : return + if isempty(hFig) || ~ishandle(hFig) || (hFig == 0) + return; + end + % Create a button group for Surfaces and "Add" button + jButtonGroup = ButtonGroup(); + + % If a figure is defined + if ishandle(hFig) + % Get selected surface index + iSurface = getappdata(hFig, 'iSurface'); + % Loop on all the available surfaces for this figure + TessInfo = getappdata(hFig, 'Surface'); + for iSurf = 1:length(TessInfo) + % Select only one button + isSelected = (iSurf == iSurface); + % Get button icon (depends on surface name) + switch lower(TessInfo(iSurf).Name) + case 'cortex' + iconButton = IconLoader.ICON_SURFACE_CORTEX; + case 'scalp' + iconButton = IconLoader.ICON_SURFACE_SCALP; + case 'innerskull' + iconButton = IconLoader.ICON_SURFACE_INNERSKULL; + case 'outerskull' + iconButton = IconLoader.ICON_SURFACE_OUTERSKULL; + case 'other' + iconButton = IconLoader.ICON_SURFACE; + case 'anatomy' + iconButton = IconLoader.ICON_ANATOMY; + end + % Create surface button + jButtonSurf = JToggleButton(iconButton, isSelected); + jButtonSurf.setMaximumSize(Dimension(24,24)); + jButtonSurf.setPreferredSize(Dimension(24,24)); + % Store the surface index as the button Name + jButtonSurf.setName(sprintf('%d', iSurf)); + % Attach a click callback + set(jButtonSurf, 'ActionPerformedCallback', @ButtonSurfaceClickedCallback); + % Add button to button group + jButtonGroup.add(jButtonSurf); + % Add button to toolbar, at the end of the surfaces list + iButton = jToolbarSurfaces.getComponentCount() - 4; + jToolbarSurfaces.add(jButtonSurf, iButton); + end + % Return number of surfaces added + nbSurfaces = length(TessInfo); + else + % No surface available for current figure + nbSurfaces = 0; + end + + % Update graphical composition of panel + jToolbarSurfaces.updateUI(); +end + + +%% ===== UPDATE SURFACE PROPERTIES ===== +function UpdateSurfaceProperties() +% disp('=== panel_surface > UpdateSurfaceProperties ==='); + import org.brainstorm.list.BstListItem; + % Get current figure handle + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + if isempty(hFig) + return + end + % Get panel controls + panelControls = bst_getContext('PanelControls', 'Surface'); + if isempty(panelControls) + return + end + % Get selected surface properties + TessInfo = getappdata(hFig, 'Surface'); + if isempty(TessInfo) + return; + end + % Get selected surface index + iSurface = getappdata(hFig, 'iSurface'); + % If surface is sliced MRI + isAnatomy = strcmpi(TessInfo(iSurface).Name, 'Anatomy'); + + % ==== Surface properties ==== + % Number of vertices + panelControls.jLabelNbVertices.setText(sprintf('%d', TessInfo(iSurface).nVertices)); + % Number of faces + panelControls.jLabelNbFaces.setText(sprintf('%d', TessInfo(iSurface).nFaces)); + % Surface alpha + panelControls.jSliderSurfAlpha.setValue(100 * TessInfo(iSurface).SurfAlpha); + panelControls.jLabelSurfAlpha.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).SurfAlpha))); + % Surface color + surfColor = TessInfo(iSurface).AnatomyColor(2, :); + panelControls.jButtonSurfColor.setBackground(java.awt.Color(surfColor(1),surfColor(2),surfColor(3))); + % Surface smoothing ALPHA + panelControls.jSliderSurfSmoothValue.setValue(100 * TessInfo(iSurface).SurfSmoothValue); + panelControls.jLabelSurfSmoothValue.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).SurfSmoothValue))); + % Correspondance : [-0.80, 0.80] <=> [-80,80] + panelControls.jSliderSurfCurvature.setValue(round(100 * TessInfo(iSurface).SurfCurvatureThreshold)); + panelControls.jLabelSurfCurvature.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).SurfCurvatureThreshold))); + % Show surface curvature button + panelControls.jButtonSurfCurvature.setSelected(TessInfo(iSurface).SurfShowCurvature); + % Show surface edges button + panelControls.jButtonSurfEdge.setSelected(TessInfo(iSurface).SurfShowEdges); + + % ==== Resect properties ==== + % Ignore for MRI slices + if isAnatomy + sMri = bst_dataSetsManager('GetMri', TessInfo(iSurface).SurfaceFile); + ResectXYZ = double(TessInfo(iSurface).CutsPosition) ./ size(sMri.Cube) * 200 - 100; + radioSelected = 'none'; + elseif ischar(TessInfo(iSurface).Resect) + ResectXYZ = [0,0,0]; + radioSelected = TessInfo(iSurface).Resect; + else + ResectXYZ = 100 * TessInfo(iSurface).Resect; + radioSelected = 'none'; + end + % X, Y, Z + panelControls.jSliderResectX.setValue(ResectXYZ(1)); + panelControls.jSliderResectY.setValue(ResectXYZ(2)); + panelControls.jSliderResectZ.setValue(ResectXYZ(3)); + + % Select one radio button + switch (radioSelected) + case 'left' + panelControls.jToggleResectLeft.setSelected(1); + panelControls.jToggleResectRight.setSelected(0); + case 'right' + panelControls.jToggleResectRight.setSelected(1); + panelControls.jToggleResectLeft.setSelected(0); + case 'none' + panelControls.jToggleResectLeft.setSelected(0); + panelControls.jToggleResectRight.setSelected(0); + end + + % ==== Data properties ==== + % Data alpha + panelControls.jSliderDataAlpha.setValue(100 * TessInfo(iSurface).DataAlpha); + panelControls.jLabelDataAlpha.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).DataAlpha))); + % Data intensity threshold + panelControls.jSliderDataIntThresh.setValue(100 * TessInfo(iSurface).DataIntThreshold); + panelControls.jLabelDataIntThresh.setText(sprintf('%d%%', round(100 * TessInfo(iSurface).DataIntThreshold))); + % Cluster extent threshold + panelControls.jSliderDataExtThresh.setValue(TessInfo(iSurface).DataExtThreshold); + panelControls.jLabelDataExtThresh.setText(sprintf('%d', TessInfo(iSurface).DataExtThreshold)); + +end + + +%% ===== ADD A SURFACE ===== +% Add a surface to a given 3DViz figure +% USAGE : iTess = panel_surface('AddSurface', hFig, surfaceFile) +% OUTPUT: Indice of the surface in the figure's surface array +function iTess = AddSurface(hFig, surfaceFile) + % ===== CHECK EXISTENCE ===== + % Check whether filename is an absolute or relative path + if exist(surfaceFile, 'file') + ProtocolInfo = bst_getContext('ProtocolInfo'); + surfaceFile = strrep(surfaceFile, ProtocolInfo.SUBJECTS, ''); + end + % Get figure appdata (surfaces configuration) + TessInfo = getappdata(hFig, 'Surface'); + % Check that this surface is not already displayed in 3DViz figure + iTess = find(io_compareFileNames({TessInfo.SurfaceFile}, surfaceFile)); + if ~isempty(iTess) + warning('Brainstorm:SurfaceAlreadyDisplayed', 'This surface is already displayed. Ignoring...'); + return + end + % Get figure type + FigureId = getappdata(hFig, 'FigureId'); + % Progress bar + isNewProgressBar = ~bst_progressBar('isVisible'); + bst_progressBar('start', 'Add surface', 'Updating display...'); + + % ===== BUILD STRUCTURE ===== + % Add a new surface at the end of the figure's surfaces list + iTess = length(TessInfo) + 1; + TessInfo(iTess) = db_getDataTemplate('TessInfo'); + % Set the surface properties + TessInfo(iTess).SurfaceFile = surfaceFile; + TessInfo(iTess).DataSource.Type = ''; + TessInfo(iTess).DataSource.FileName = ''; + + % ===== PLOT OBJECT ===== + % Get file type (tessalation or MRI) + [fileFormat, fileType] = io_getFileType(surfaceFile); + % === TESSELATION === + if ismember('tess', fileType) + % === LOAD SURFACE === + % Load surface file + sSurface = bst_dataSetsManager('LoadSurface', surfaceFile); + % Get some properties + TessInfo(iTess).Name = sSurface.Name; + TessInfo(iTess).nVertices = size(sSurface.Vertices, 1); + TessInfo(iTess).nFaces = size(sSurface.Faces, 1); + + % === PLOT SURFACE === + switch (FigureId.Type) + case 'MriViewer' + % Nothing to do: surface will be displayed as an overlay slice in gui_figureMriViewer.m + case {'3DViz', 'Topography'} + % Create and display surface patch + [hFig, TessInfo(iTess).hPatch] = gui_figure3DViz('PlotSurface', hFig, ... + sSurface.Faces, ... + sSurface.Vertices, ... + TessInfo(iTess).AnatomyColor(2,:), ... + TessInfo(iTess).SurfAlpha); + end + % Update figure's surfaces list and current surface pointer + setappdata(hFig, 'Surface', TessInfo); + setappdata(hFig, 'iSurface', iTess); + % Show curvature if needed + if TessInfo(iTess).SurfShowCurvature + SetShowCurvature(hFig, iTess, 1); + end + + % === MRI === + elseif ismember('subjectimage', fileType) + % === LOAD MRI === + sMri = bst_dataSetsManager('LoadMri', surfaceFile); + TessInfo(iTess).Name = 'Anatomy'; + % Initial position of the cuts : middle in each direction + TessInfo(iTess).CutsPosition = round(size(sMri.Cube) / 2); + TessInfo(iTess).SurfSmoothValue = .3; + % Update figure's surfaces list and current surface pointer + setappdata(hFig, 'Surface', TessInfo); + setappdata(hFig, 'iSurface', iTess); + + % === PLOT MRI === + switch (FigureId.Type) + case 'MriViewer' + % Configure MRIViewer + gui_figureMriViewer('SetupMri', hFig); + case '3DViz' + % Camera basic orientation: TOP + gui_figure3DViz('SetStandardView', hFig, 'top'); + end + % Plot MRI + PlotMri(hFig); + end + % Automatically set transparencies (to view different layers at the same time) + SetAutoTransparency(hFig); + drawnow; + % Close progress bar + if isNewProgressBar + bst_progressBar('stop'); + end + % Update panel + UpdatePanel(); +end + + + +%% ===== SET DATA SOURCE FOR A SURFACE ===== +%Associate a data/results matrix to a surface. +% Usage : SetSurfaceData(hFig, iTess, dataType, dataFile, isStat, isZscore) +% Parameters : +% - hFig : handle to a 3DViz figure +% - iTess : indice of the surface to update (in hFig appdata) +% - dataType : type of data to overlay on the surface {'Source', 'Data', ...} +% - dataFile : filename of the data to display over the surface +% - isStat : 1, if results is a statistical result; 0, else +% - isZscore : 1, if results is a result of z-score normalization; 0, else +function isOk = SetSurfaceData(hFig, iTess, dataType, dataFile, isStat, isZscore) %#ok + % Get figure index in DataSet figures list + [tmp__, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + if isempty(iDS) + error('No DataSet acessible for this 3D figure'); + end + % Get surfaces list for this figure + TessInfo = getappdata(hFig, 'Surface'); + + % === GET DATA THRESHOLD === + % Cortex + if strcmpi(TessInfo(iTess).Name, 'Cortex') + % Get defaults for surface display + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + % Data threshold + try + dataIntThreshold = DefaultSurfaceDisplay.DataIntThreshold; + catch + DefaultSurfaceDisplay + dataIntThreshold = 1; + end + try + dataExtThreshold = DefaultSurfaceDisplay.DataExtThreshold; + catch + DefaultSurfaceDisplay + dataExtThreshold = 0; + end + % Anatomy or Statistics : 0% + elseif strcmpi(TessInfo(iTess).Name, 'Anatomy') || isStat + dataIntThreshold = 0; + dataExtThreshold = 0; + % Else: normal data on scalp + else + dataIntThreshold = 0.5; + dataExtThreshold = 0; + end + + % === PREPARE SURFACE === + TessInfo(iTess).DataSource.Type = dataType; + TessInfo(iTess).DataSource.FileName = dataFile; + TessInfo(iTess).DataSource.isStat = isStat; + TessInfo(iTess).DataSource.isZscore = isZscore; + TessInfo(iTess).DataIntThreshold = dataIntThreshold; + TessInfo(iTess).DataExtThreshold = dataExtThreshold; + % Type of data displayed on the surface: sources/recordings/nothing + switch (dataType) + case 'Data' + setappdata(hFig, 'DataFile', dataFile); + case 'Source' + setappdata(hFig, 'ResultsFile', dataFile); + case 'Surface' + % Nothing to do... + otherwise + TessInfo(iTess).Data = []; + TessInfo(iTess).DataWmat = []; + end + % Update figure appdata + setappdata(hFig, 'Surface', TessInfo); + % Plot surface + isOk = UpdateSurfaceData(hFig, iTess); + % Update panel + UpdatePanel(); +end + + + +%% ===== UPDATE SURFACE DATA ===== +% Update the 'Data' field for given surfaces : +% - Load data/results matrix (F, ImageGridAmp, ...) if it is not loaded yet +% - Store global minimum/maximum of data +% - Interpolate data matrix over the target surface (interp_mail) if number of vertices does not match +% - And update color display (ColormapChangedCallback) +% +% Usage: UpdateSurfaceData(hFig, iSurfaces) +% UpdateSurfaceData(hFig) +function isOk = UpdateSurfaceData(hFig, iSurfaces) +% disp('=== panel_surface > UpdateSurfaceData ==='); + global GlobalData; + isOk = 1; + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + % If the aim is to update all the surfaces + if (nargin < 2) || isempty(iSurfaces) + iSurfaces = 1:length(TessInfo); + end + + % Get figure index (in DataSet structure) + [tmp__, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + % Find the DataSet indice that corresponds to the current figure + if isempty(iDS) + error('No DataSet acessible for this 3D figure'); + end + + % For each surface + for iTess = iSurfaces + % If surface patch object doesn't exist => error + if isempty(TessInfo(iTess).hPatch) + error('Patch is not displayed'); + end + + % ===== GET SURFACE DATA ===== + % Switch between different data types to display on the surface + switch (TessInfo(iTess).DataSource.Type) + case 'Data' + % Get TimeVector and current time indice + [TimeVector, CurrentTimeIndex] = bst_dataSetsManager('GetTimeVector', iDS); + % If 'F' matrix is not loaded for this file + if isempty(GlobalData.DataSet(iDS).Measures.F) + % Load recording matrix + bst_dataSetsManager('LoadRecordingsMatrix', iDS); + end + + % If surface is displayed : update it + if ~isempty(TessInfo(iTess).hPatch) && ishandle(TessInfo(iTess).hPatch) + % Get vertices of surface + Vertices = get(TessInfo(iTess).hPatch, 'Vertices'); + % Warn user if tessellation is huge + if size(Vertices,1) > 20000 + if ~java_dialog('confirm', {sprintf('Tessellation has %d vertices; computation time for rendering might be excessive.',size(Vertices,1)),'Do you still want to proceed ?'},'Long computation expected') + % Stop computation + isOk = 0; + return + end + end + + % Get selected channels indices and location + [SelectedChannels, PChanLocs] = gui_figure3DViz('GetSelectedChannels', iDS, iFig); +% % Get Selected channels +% SelectedChannels = good_channel(GlobalData.DataSet(iDS).Channel, ... +% GlobalData.DataSet(iDS).Measures.ChannelFlag, ... +% GlobalData.DataSet(iDS).Figure(iFig).Id.Modality); + + % Interpolate data on scalp surface (only if Matrix is not computed yet, or channels changed) + % => TRICK : it is difficult to test if the sensors locations or the surface vertices changed + % => Just the the number of channels and vertices (should be ok...) + if isempty(TessInfo(iTess).DataWmat) || ... + (size(TessInfo(iTess).DataWmat,2) ~= length(SelectedChannels)) || ... + (size(TessInfo(iTess).DataWmat,1) ~= length(Vertices)) + interType = [GlobalData.DataSet(iDS).Figure(iFig).Id.Modality, 'ToScalp']; + TessInfo(iTess).DataWmat = interp_mail(Vertices, PChanLocs, interType); + end + % Set data for current time frame + TessInfo(iTess).Data = single(TessInfo(iTess).DataWmat * ... + double(GlobalData.DataSet(iDS).Measures.F(SelectedChannels, CurrentTimeIndex))); + % Store minimum and maximum of displayed data + TessInfo(iTess).DataMinMax = [min(min(TessInfo(iTess).Data)), ... + max(max(TessInfo(iTess).Data))]; + end + % Update "Static" status for this figure + setappdata(hFig, 'isStatic', GlobalData.DataSet(iDS).Measures.isStatic); + + case 'Source' + % === LOAD RESULTS VALUES === + % Get results index + iResult = bst_dataSetsManager('GetResultInDataSet', iDS, TessInfo(iTess).DataSource.FileName); + % If Results file is not found in GlobalData structure + if isempty(iResult) + % Load Results file + [iDS, iResult] = bst_dataSetsManager('LoadResultsFile', ... + TessInfo(iTess).DataSource.FileName, ... + GlobalData.DataSet(iDS).DataFile, ... + '', ... + GlobalData.DataSet(iDS).StudyFile, ... + GlobalData.DataSet(iDS).SubjectFile); + if isempty(iResult) + return + end + end + % If 'ImageGridAmp' matrix is not loaded for this file + if isempty(GlobalData.DataSet(iDS).Results(iResult).ImageGridAmp) && ... + isempty(GlobalData.DataSet(iDS).Results(iResult).ImagingKernel) + % Load recording matrix + bst_dataSetsManager('LoadResultsMatrix', iDS, iResult); + end + + % === GET CURRENT VALUES === + % Get results values + TessInfo(iTess).Data = bst_dataSetsManager('GetResultsValues', iDS, iResult, [], 'CurrentTimeIndex'); + % If min/max values for this file were not computed yet + if isempty(TessInfo(iTess).DataMinMax) + TessInfo(iTess).DataMinMax = bst_dataSetsManager('GetResultsMaximum', iDS, iResult); + end + % Reset Overlay cube + TessInfo(iTess).OverlayCube = []; + + % Check the consistency between the number of results points (number of sources) + % and the number of vertices of the target surface patch + % IGNORE TEST FOR MRI + if (length(TessInfo(iTess).Data) ~= TessInfo(iTess).nVertices) && ~strcmpi(TessInfo(iTess).Name, 'Anatomy') + bst_error(sprintf(['Number of sources (%d) is smaller than number of vertices (%d).\n\n' ... + 'Please compute the sources again.'], size(TessInfo(iTess).Data, 1), TessInfo(iTess).nVertices), 'Data mismatch', 0); + isOk = 0; + return; + end + % Update "Static" status for this figure + setappdata(hFig, 'isStatic', GlobalData.DataSet(iDS).Results(iResult).isStatic); + + case 'Surface' + % Get loaded surface + SurfaceFile = TessInfo(iTess).DataSource.FileName; + sSurf = bst_dataSetsManager('LoadSurface', SurfaceFile); + % Build uniform data vector + TessInfo(iTess).Data = ones(length(sSurf.Vertices),1); + TessInfo(iTess).DataMinMax = [1 1]; + setappdata(hFig, 'isStatic', 1); + + otherwise + % Nothing to do + end + % Error if all data values are null + if (max(abs(TessInfo(iTess).DataMinMax)) == 0) +% bst_error('All values are null. Please check your input file.', 'Surface error'); + warning('All values are null. Please check your input file.'); + end + end + % Update surface definition + setappdata(hFig, 'Surface', TessInfo); + % Update colormap + UpdateSurfaceColormap(hFig, iSurfaces); +end + + + +%% ===== UPDATE SURFACE COLORMAP ===== +function UpdateSurfaceColormap(hFig, iSurfaces) +% disp('=== panel_surface > UpdateSurfaceColormap ==='); + global GlobalData; + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + if isempty(TessInfo) + return + end + % If the aim is to update all the surfaces + if (nargin < 2) || isempty(iSurfaces) + iSurfaces = 1:length(TessInfo); + end + + % Get default colormap to use for this figure + [listTypes, defaultColormapType] = gui_figuresManager('GetDisplayedDataTypes', hFig); + % Get figure axes + hAxes = [findobj(hFig, 'Tag', 'Axes3D'), findobj(hFig, 'Tag', 'axc'), findobj(hFig, 'Tag', 'axa'), findobj(hFig, 'Tag', 'axs')]; + hasData = 0; + hasSource = 0; + + % Get figure index (in DataSet structure) + [tmp__, iFig, iDS] = gui_figuresManager('GetFigure', hFig); + % Find the DataSet indice that corresponds to the current figure + if isempty(iDS) + error('No DataSet acessible for this 3D figure'); + end + + % For each surface + for iTess = iSurfaces + % ===== COLORMAPPING ===== + % Get recordings and source colormap + if isempty(TessInfo(iTess).DataSource.Type) || strcmpi(TessInfo(iTess).DataSource.Type, 'Surface') + sColormap = bst_colormaps('GetColormap', 'Anatomy'); + elseif TessInfo(iTess).DataSource.isStat || TessInfo(iTess).DataSource.isZscore + sColormap = bst_colormaps('GetColormap', 'Stat'); + else + sColormap = bst_colormaps('GetColormap', TessInfo(iTess).DataSource.Type); + end + % === Colormap : Normalized or Absolute ? + % Normalized : Color bounds (CLim) are set to a local extrema (at this time frame) + if sColormap.isNormalized + absMaxVal = max(abs(TessInfo(iTess).Data(:))); + % Fixed : Color bounds are fixed, defined statically by the user (sColormap.MaxValue) + elseif ~isempty(sColormap.MaxValue) + absMaxVal = sColormap.MaxValue; + % Absolute : Color bounds (CLim) are set to the global extrema (over all the time frames) + else + absMaxVal = max(abs(TessInfo(iTess).DataMinMax)); + end + + % === Data values : Absolute | Normal ? === + if sColormap.isAbsoluteValues + % Display absolute values of data + TessInfo(iTess).Data = abs(TessInfo(iTess).Data); + TessInfo(iTess).DataLimitValue = [0, absMaxVal]; + else + % Display normal data (positive and negative values) + TessInfo(iTess).DataLimitValue = [-absMaxVal, absMaxVal]; + end + % If current colormap is the default colormap for this figure (for colorbar) + if (strcmpi(defaultColormapType, 'Stat') && (TessInfo(iTess).DataSource.isStat || TessInfo(iTess).DataSource.isZscore)) || ... + strcmpi(defaultColormapType, TessInfo(iTess).DataSource.Type) + if all(~isnan(TessInfo(iTess).DataLimitValue)) && (TessInfo(iTess).DataLimitValue(1) < TessInfo(iTess).DataLimitValue(2)) + set(hAxes, 'CLim', TessInfo(iTess).DataLimitValue); + else + %warning('Brainstorm:AxesError', 'Error using set: Bad value for axes property: CLim: Values must be increasing and non-NaN.'); + set(hAxes, 'CLim', [0 1e-30]); + end + end + + % ===== DISPLAY ON MRI ===== + if strcmpi(TessInfo(iTess).Name, 'Anatomy') && ~isempty(TessInfo(iTess).DataSource.Type) && ... + (isempty(TessInfo(iTess).OverlayCube) )...|| ~strcmpi(TessInfo(iTess).DataSource.Type, 'Surface')) + % Progress bar + isProgressBar = bst_progressBar('isVisible'); + bst_progressBar('start', 'Display MRI', 'Updating values...'); + % ===== Update surface display ===== + % Update figure's appdata (surface list) + setappdata(hFig, 'Surface', TessInfo); + % Update OverlayCube + UpdateOverlayCube(hFig, iTess); + % Hide progress bar + if ~isProgressBar + bst_progressBar('stop'); + end + % Put focus back on previous figure + curFig = gui_figuresManager('GetCurrentFigure', '3D'); + if ~isempty(curFig) + figure(curFig); + end + else + % Update figure's appdata (surface list) + setappdata(hFig, 'Surface', TessInfo); + % Update surface color + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iTess); + end + + % ===== Colorbar ticks and labels ===== + if strcmpi(TessInfo(iTess).DataSource.Type, 'Data') + hasData = 1; + elseif strcmpi(TessInfo(iTess).DataSource.Type, 'Source') + hasSource = 1; + end + end + + % ===== Colorbar ticks and labels ===== + % Set figure colormap + set(hFig, 'Colormap', sColormap.CMap); + % Create/Delete colorbar + bst_colormaps('SetColorbarVisible', hFig, sColormap.DisplayColorbar); + % Display only one colorbar (preferentially the results colorbar) + if GlobalData.DataSet(iDS).isStat % || GlobalData.DataSet(iDS).isZscore (NOT FOR THE COLORMAP, ONLY FOR THE UNITS) + bst_colormaps('ConfigureColorbar', hFig, 'stat'); + elseif hasSource + bst_colormaps('ConfigureColorbar', hFig, 'Results'); + elseif hasData + bst_colormaps('ConfigureColorbar', hFig, GlobalData.DataSet(iDS).Figure(iFig).Id.Modality); + end +end + + +%% ===== GET SURFACE: ANATOMY ===== +function [sMri,TessInfo,iTess,iMri] = GetSurfaceMri(hFig) + % Get list of surfaces for the figure + TessInfo = getappdata(hFig, 'Surface'); + % Find "Anatomy" + iTess = find(strcmpi({TessInfo.Name}, 'Anatomy')); + if isempty(iTess) + sMri = []; + return + elseif (length(iTess) > 1) + iTess = iTess(1); + end + % Get Mri filename + MriFile = TessInfo(iTess).SurfaceFile; + % Get loaded MRI + [sMri,iMri] = bst_dataSetsManager('GetMri', MriFile); +end + + +%% ===== GET SURFACE: CORTEX ===== +% Usage: [iCortex, TessInfo, hFig] = GetSurfaceCortex() +% [iCortex, TessInfo] = GetSurfaceCortex(hFig) +function [iCortex, TessInfo, hFig] = GetSurfaceCortex(hFig) + % If target figure is not defined: use the current 3D figure + if ((nargin < 1) || isempty(hFig)) + % Get current 3d figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + % No current 3D figure: error + if isempty(hFig) + iCortex = []; + TessInfo = []; + return + end + end + % Get surfaces list + TessInfo = getappdata(hFig, 'Surface'); + % Find 'Cortex' surfaces + iCortex = find(strcmpi({TessInfo.Name}, 'Cortex')); + % No cortex + if isempty(iCortex) + iCortex = []; + return; + % More than one + elseif (length(iCortex) > 1) + % Try to get the one that is selected in "surfaces" panel + iSurf = getappdata(hFig, 'iSurface'); + % Selected surface does not help + if isempty(iSurf) || ~ismember(iSurf, iCortex) + % Use first cortex surface available + iCortex = iCortex(1); + return + % Use selected surface + else + iCortex = iSurf; + end + end +end + + +%% ===== GET CORTEX OR ANATOMY SURFACE ===== +% Usage: [iSurf, TessInfo, hFig] = GetSurfaceCortexOrAnatomy() +% [iSurf, TessInfo] = GetSurfaceCortexOrAnatomy(hFig) +function [iSurf, TessInfo, hFig] = GetSurfaceCortexOrAnatomy(hFig) %#ok + % If target figure is not defined: use the current 3D figure + if ((nargin < 1) || isempty(hFig)) + % Get current 3d figure + hFig = gui_figuresManager('GetCurrentFigure', '3D'); + % No current 3D figure: error + if isempty(hFig) + iSurf = []; + TessInfo = []; + return + end + end + % Get surfaces + iCortex = GetSurfaceCortex(hFig); + [sMri, TessInfo, iAnatomy] = GetSurfaceMri(hFig); + % Get target surface + if ~isempty(iCortex) + iSurf = iCortex; + elseif ~isempty(iAnatomy) + iSurf = iAnatomy; + else + iSurf = []; + end +end + + +%% ===== REMOVE A SURFACE ===== +function RemoveSurface(hFig, iSurface) + % Get figure appdata (surfaces configuration) + TessInfo = getappdata(hFig, 'Surface'); + if (iSurface < 0) || (iSurface > length(TessInfo)) + return; + end + % Remove associated patch + iRemPatch = ishandle(TessInfo(iSurface).hPatch); + delete(TessInfo(iSurface).hPatch(iRemPatch)); + + % Remove surface from the figure's surfaces list + TessInfo(iSurface) = []; + % Update figure's surfaces list + setappdata(hFig, 'Surface', TessInfo); + % Set another figure as current figure + if isempty(TessInfo) + setappdata(hFig, 'iSurface', []); + elseif (iSurface <= length(TessInfo)) + setappdata(hFig, 'iSurface', iSurface); + else + setappdata(hFig, 'iSurface', iSurface - 1); + end + +% % Get figure description +% [hFig, iFig, iDS] = gui_figuresManager('GetFigure', hFig); +% % Update colormaps +% figure_callback(hFig, 'ColormapChangedCallback', iDS, iFig); +end + + + +%% ===== PLOT MRI ===== +% Usage: hs = panel_surface('PlotMri', hFig, posXYZ) : Set the position of cuts and plot MRI +% hs = panel_surface('PlotMri', hFig) : Plot MRI for current positions +function hs = PlotMri(hFig, posXYZ) + global GlobalData; + % Get MRI + [sMri,TessInfo,iTess,iMri] = GetSurfaceMri(hFig); + % Set positions or use default + if (nargin < 2) || isempty(posXYZ) + posXYZ = TessInfo(iTess).CutsPosition; + iDimPlot = ~isnan(posXYZ); + else + iDimPlot = ~isnan(posXYZ); + TessInfo(iTess).CutsPosition(iDimPlot) = posXYZ(iDimPlot); + end + % Get initial threshold value + threshold = TessInfo(iTess).SurfSmoothValue * 2 * double(sMri.Histogram.bgLevel); + % Get colormaps + switch (TessInfo(iTess).DataSource.Type) + case 'Source' + if TessInfo(iTess).DataSource.isStat || TessInfo(iTess).DataSource.isZscore + sColormapData = bst_colormaps('GetColormap', 'Stat'); + else + sColormapData = bst_colormaps('GetColormap', 'Source'); + end + case 'Surface' + sColormapData = bst_colormaps('GetColormap', 'Overlay'); + otherwise + sColormapData = bst_colormaps('GetColormap', 'Source'); + end + sColormapMri = bst_colormaps('GetColormap', 'Anatomy'); + % Define OPTIONS structure + OPTIONS.sMri = sMri; + OPTIONS.iMri = iMri; + OPTIONS.cutsCoords = posXYZ; % [x,y,z] location of the cuts in the volume + OPTIONS.MriThreshold = threshold; % MRI threshold (if value + for i = 1:length(hFig) + [sMri, TessInfo, iTess] = GetSurfaceMri(hFig(i)); + if ~isempty(iTess) && ~isempty(TessInfo(iTess).Data) + UpdateOverlayCube(hFig(i), iTess); + end + end +end + + +%% ===== UPDATE OVERLAY MASK ===== +% Usage: UpdateOverlayCube(hFig, iTess) +function UpdateOverlayCube(hFig, iTess) +% disp('=== panel_surface > UpdateOverlayCube ==='); + % Get MRI + TessInfo = getappdata(hFig, 'Surface'); + sMri = bst_dataSetsManager('GetMri', TessInfo(iTess).SurfaceFile); + if isempty(sMri) || isempty(sMri.Cube) || isempty(TessInfo(iTess).Data) + return + end + % Process depend on overlay data file + switch (TessInfo(iTess).DataSource.Type) + case 'Data' + % Get scalp surface + error('Not supported yet'); + case 'Source' + % Get cortex surface + sSubject = bst_getContext('MriFile', sMri.FileName); + SurfaceFile = sSubject.Surface(sSubject.iCortex).FileName; + case 'Surface' + % Get surface specified in DataSource.FileName + SurfaceFile = TessInfo(iTess).DataSource.FileName; + end + % Get transformation MRI<->Surface + [sSurf, iSurf] = bst_dataSetsManager('LoadSurface', SurfaceFile); + tess2mri_interp = bst_dataSetsManager('GetTess2MriInterp', iSurf); + % If no interpolation tess<->mri accessible : exit + if isempty(tess2mri_interp) + return + end + % === GET SCOUTS === + % Get "Scouts" panel controls + ctrl = bst_getContext('PanelControls', 'Scout'); + % View mode : VIEW SELECTED SCOUTS + if ctrl.jRadioScoutViewSelected.isSelected() + % Get selected scouts + [sSelScouts, iSelScouts] = panel_scouts('GetSelectedScouts'); + % View mode : VIEW ALL SCOUTS + elseif ctrl.jRadioScoutViewAll.isSelected() + % Get all available scouts + [sSelScouts, iSelScouts] = panel_scouts('GetScouts'); + end + % Display only scouts that are related to this figure + FigureId = getappdata(hFig, 'FigureId'); + switch (FigureId.Type) + case 'MriViewer' + % Take all the scouts + case '3DViz' + [sScoutsFig, iScoutsFig] = panel_scouts('GetScoutsWithFigure', hFig); + iSelScouts = intersect(iSelScouts, iScoutsFig); + sSelScouts = panel_scouts('GetScouts', iSelScouts); + end + % Progress bar + isProgressBar = bst_progressBar('isVisible'); + bst_progressBar('start', 'Display MRI', 'Updating values...'); + + % === UPDATE MASK === + mriSize = size(sMri.Cube); + % If no selected scouts + if isempty(sSelScouts) || ~ctrl.jCheckLimitMriSources.isSelected() + % Build interpolated cube + TessInfo(iTess).OverlayCube = tess_projectDataInMri(... + tess2mri_interp, ... + mriSize, ... + TessInfo(iTess).Data); + else + % Get all the vertices concerned by the interpolation + iVertices = [sSelScouts.Vertices]; + % Build interpolated cube + TessInfo(iTess).OverlayCube = tess_projectDataInMri(... + tess2mri_interp(:,iVertices), ... + mriSize, ... + TessInfo(iTess).Data(iVertices)); + end + % Reset MIP functional fields + TessInfo(iTess).MipFunctional = cell(3,1); + % === UPDATE DISPLAY === + % Get surface description + setappdata(hFig, 'Surface', TessInfo); + % Redraw surface vertices color + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iTess); + % Hide progress bar + if ~isProgressBar + bst_progressBar('stop'); + end +end + + +%% ===== SET SURFACE TRANSPARENCY ===== +function SetSurfaceTransparency(hFig, iSurf, alpha) + % Update surface transparency + TessInfo = getappdata(hFig, 'Surface'); + TessInfo(iSurf).SurfAlpha = alpha; + setappdata(hFig, 'Surface', TessInfo); + % Update panel controls + UpdateSurfaceProperties(); + % Update surface display + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurf); + figure_callback(hFig, 'UpdateSurfaceAlpha', hFig, iSurf); +end + + + +%% ===== SET THRESHOLD ===== +function SetDataThreshold(hFig, iSurf, value) + % Update surface transparency + TessInfo = getappdata(hFig, 'Surface'); + TessInfo(iSurf).DataIntThreshold = value; + setappdata(hFig, 'Surface', TessInfo); + % Update panel controls + UpdateSurfaceProperties(); + % Update color display on the surface + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurf); +end +%% ===== SET AUTO TRANSPARENCY ===== +function SetAutoTransparency(hFig) + % Get surfaces definitions + TessInfo = getappdata(hFig, 'Surface'); + % Look for different surfaces types + iCortex = find(ismember({TessInfo.Name}, {'Cortex', 'Anatomy'})); + iOther = find(ismember({TessInfo.Name}, {'Scalp', 'InnerSkull', 'OuterSkull'})); + % Set other surfaces transparency if cortex at the same time + if ~isempty(iCortex) && ~isempty(iOther) + for i = 1:length(iOther) + SetSurfaceTransparency(hFig, iOther(i), 0.7); + end + end +end + + +%% ===== SET SURFACE COLOR ===== +function SetSurfaceColor(hFig, iSurf, newColor2) + % Compute the color used to display curvature (newColor1) + newColor1 = .6 .* newColor2; + + % Get description of surfaces + TessInfo = getappdata(hFig, 'Surface'); + % Update surface description (figure's appdata) + TessInfo(iSurf).AnatomyColor(1,:) = newColor1; + TessInfo(iSurf).AnatomyColor(2,:) = newColor2; + % Update Surface appdata structure + setappdata(hFig, 'Surface', TessInfo); + + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Surface'); + % Change button color + ctrl.jButtonSurfColor.setBackground(java.awt.Color(newColor2(1), newColor2(2), newColor2(3))); + % Update panel controls + UpdateSurfaceProperties(); + + % Update color display on the surface + figure_callback(hFig, 'UpdateSurfaceColor', hFig, iSurf); +end + +%% ===== APPLY DEFAULT DISPLAY TO SURFACE ===== +function ApplyDefaultDisplay() %#ok + % Get panel controls + ctrl = bst_getContext('PanelControls', 'Surface'); + % Get defaults for surface display + DefaultSurfaceDisplay = bst_getContext('DefaultSurfaceDisplay'); + % Surface smooth + if (ctrl.jSliderSurfSmoothValue.getValue() ~= DefaultSurfaceDisplay.SurfSmoothValue * 100) + ctrl.jSliderSurfSmoothValue.setValue(DefaultSurfaceDisplay.SurfSmoothValue * 100); + event = java.awt.event.MouseEvent(ctrl.jSliderSurfSmoothValue, 0, 0, 0, 0, 0, 1, 0, 0); + SliderCallback([], event, 'SurfSmoothValue'); + end + % Surface edges + if DefaultSurfaceDisplay.SurfShowCurvature && ~ctrl.jButtonSurfCurvature.isSelected() + ctrl.jButtonSurfCurvature.doClick(); + end +end + diff --git a/brainstorm3/toolbox/io/import_data.m b/brainstorm3/toolbox/io/import_data.m new file mode 100644 index 0000000..819ff61 --- /dev/null +++ b/brainstorm3/toolbox/io/import_data.m @@ -0,0 +1,545 @@ +function import_data(varargin) +% IMPORT_DATA: Imports a list of datafiles in a Study of Brainstorm database +% +% USAGE: import_data(iStudyInit, DataFiles, FileFormat) +% import_data(iStudyInit, DataFiles, FileFormat, DataCfg) +% import_data(iStudyInit) +% import_data( [], iSubjectInit) : imports data in the target subject (after having created a default condition) +% import_data() : Rely on data filenames to create automatically subjects/conditions +% +% INPUT: +% - iStudyInit: Indices of the studies where to import the Data +% If 0, a study is created automatically before importation (iSubject must be specified) +% - DataFiles : Cell array of full filenames of the data files to import (format is autodetected) +% => if not specified : file to import is asked to the user +% - iSubjectInit: The subject indice must be specified if and only if iStudyInit is not defined (0) +% => in this case, a default study is created for the target subject +% +% NOTE : Some data filenames can be interpreted as subjects/conditions/run : +% - cell__obs.erp : subject #j, condition #i, conditionName + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2008 +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Creation +% ------------------------------------------------------------------------------ + +% ===== Parse inputs ===== +DataFiles = {}; +FileFormat = ''; +iSubjectInit = 0; +% Check command line +if (nargin==0) + iStudyInit = 0; +elseif (nargin==1) && isnumeric(varargin{1}) && (varargin{1} > 0) + iStudyInit = varargin{1}; +elseif (nargin>=2) && isnumeric(varargin{1}) + iStudyInit = varargin{1}; + if ischar(varargin{2}) + DataFiles = {varargin{2}}; + elseif iscell(varargin{2}) + DataFiles = varargin{2}; + elseif isnumeric(varargin{2}) + iSubjectInit = varargin{2}; + end + if nargin>=3 + FileFormat = varargin{3}; + end + if nargin>=4 + sSubject = varargin{4}; + end +else + error('Usage: import_data(iStudyInit, [,DataFiles || iSubjectInit])'); +end +% Get Protocol information +ProtocolInfo = bst_getContext('ProtocolInfo'); +% Get current byte order +ByteOrder = bst_getContext('ByteOrder'); + + +%% ===== SELECT DATA FILE ===== +% If MRI file to load was not defined : open a dialog box to select it +if isempty(DataFiles) + % Get default import directory and formats + LastUsedDirs = bst_getContext('LastUsedDirs'); + DefaultFormats = bst_getContext('DefaultFormats'); + % Get MRI file + [DataFiles, FileFormat, FileFilter] = java_fileSelector( 'open', ... + 'Import EEG/MEG recordings...', ... % Window title + LastUsedDirs.ImportData, ... % Last used directory + 'multiple', 'files_and_dirs', ... % Selection mode + {{'.meg4','.res4'}, 'MEG/EEG: CTF (*.ds;*.meg4;*.res4)', 'CTF' ; ... + {'.fif'}, 'MEG/EEG: Neuromag FIFF (*.fif)', 'FIF'; ... + {'_data'}, 'MEG/EEG: Brainstorm MAT (*data*.mat)', 'BST-MAT'; ... + {'.lena'}, 'MEG/EEG: LENA (*.lena)', 'LENA-BIN'; ... + {'.raw'}, 'EEG: EGI Netstation epoch-marked RAW (*.raw)', 'EEG-EGI-RAW'; ... + {'.set'}, 'EEG: EEGLab (*.set)', 'EEG-EEGLAB'; ... + {'.sef','.ep','.eph'}, 'EEG: Cartool (*.sef;*.ep;*.eph)', 'EEG-CARTOOL'; ... + {'.erp','.hdr'}, 'EEG: ERPCenter (*.hdr;*.erp)', 'EEG-ERPCENTER'; ... + {'.eeg'}, 'EEG: BrainAmp (*.eeg)', 'EEG-BRAINAMP'; ... + {'.cnt','.avg','.eeg','.dat'}, 'EEG: Neuroscan (*.cnt;*.eeg;*.avg;*.dat)', 'EEG-NEUROSCAN'; ... + {'.mat'} 'EEG: Matlab matrix (*.mat)', 'EEG-MAT'; + {'*'}, 'EEG: ASCII text (*.*)', 'EEG-ASCII' ... + }, DefaultFormats.DataIn); + % If no file was selected: exit + if isempty(DataFiles) + return + end + % Save default import directory + LastUsedDirs.ImportData = fileparts(DataFiles{1}); + bst_setContext('LastUsedDirs', LastUsedDirs); + % Save default import format + DefaultFormats.DataIn = FileFormat; + bst_setContext('DefaultFormats', DefaultFormats); + % Process the selected directories : + % 1) If they are .ds/ directory with .meg4 and .res4 files : keep them as "files to open" + % 2) Else : add all the data files they contains (subdirectories included) + DataFiles = ExpandDataFilesList(FileFilter, DataFiles); + if isempty(DataFiles) + bst_error(['No data ' FileFormat ' file in the selected directories.'], 'Import EEG/MEG recordings...', 0); + return + end +end + +%% ===== CHECK DATA FORMAT ===== +if isempty(FileFormat) + error('Unknown FileFormat'); +end + + +%% ===== IMPORT SELECTED DATA ===== +% Reset data selection in study +nbCall = 0; +iNewAutoSubject = []; +isReinitStudy = 0; +iAllStudies = []; +iAllSubjects = []; +% Process all the selected data files +for iFile = 1:length(DataFiles) + nbCall = nbCall + 1; + DataFile = DataFiles{iFile}; + [DataFile_path, DataFile_base] = fileparts(DataFile); + % Check file location (a file cannot be directly inside the brainstorm directories) + itmp = strfind(DataFile_path, ProtocolInfo.STUDIES); + if ~isempty(itmp) && (itmp(1) == 1) + error(['You are not supposed to put your original files in the Brainstorm data directory.' 10 ... + 'This directory is part of the Brainstorm database and its content can be altered only' 10 ... + 'by the Brainstorm GUI.' 10 10 ... + 'Please create a new folder somewhere else, move all you original recordings files in it, ' 10 ... + 'and then try again to import them.']); + end + + % List or directories where to copy the channel file + iStudies = []; + iStudyCopyChannel = []; + % If needed: reinitialize target study + if isReinitStudy + iStudyInit = 0; + end + + % ===== CONVERT DATA FILE ===== + bst_progressBar('start', 'Import MEG/EEG recordings', ['Loading file "' DataFile '"...']); + bst_message_window(sprintf('Loading MEG/EEG "%s"...', DataFile)); + % Load file(s) + [ImportedDataMat, ChannelMat, loadedFiles] = in_data(DataFile, FileFormat, ByteOrder, nbCall); + if isempty(ImportedDataMat) + continue + end + % Detect auxiliary EEG channels + if ~isempty(ChannelMat) + ChannelMat = channel_detectType(ChannelMat); + end + + % ===== CREATE STUDY (IIF SUBJECT IS DEFINED) ===== + bst_progressBar('start', 'Import MEG/EEG recordings', 'Preparing output studies...'); + % Check if subject/condition is in filenames + [SubjectName, ConditionName] = ParseDataFilename(ImportedDataMat(1).FileName,loadedFiles); + % If subj/cond are defined in filenames => default (ignore node that was clicked) + if ~isempty(SubjectName) + iSubjectInit = NaN; + end + if ~isempty(ConditionName) + iStudyInit = NaN; + end + + % If study is already known + if (iStudyInit ~= 0) + iStudies = iStudyInit; + % If a study needs to be created AND subject is already defined + elseif (iStudyInit == 0) && (iSubjectInit ~= 0) + % Get the target subject + sSubject = bst_getContext('Subject', iSubjectInit, 1); + % Try to get default study + [sStudies, iStudies] = bst_getContext('StudyWithCondition', fullfile(fileparts(sSubject.FileName), DataFile_base)); + % If does not exist yet: Create the default study + if isempty(iStudies) + iStudies = db_addCondition(fileparts(sSubject.FileName), DataFile_base); + if isempty(iStudies) + error('Default study could not be created : "%s".', DataFile_base); + end + isReinitStudy = 1; + end + iStudyInit = iStudies; + % If need to create Subject + Condition + Study : do it file per file + else + iSubjectInit = NaN; + iStudyInit = NaN; + iStudies = []; + end + + % ===== STORE IMPORTED FILES IN DB ===== + bst_progressBar('start', 'Import MEG/EEG recordings', 'Saving imported files in database...', 0, length(ImportedDataMat)); + % Store imported data files in Brainstorm database + for iImported = 1:length(ImportedDataMat) + bst_progressBar('inc', 1); + % ===== CREATE STUDY (IF SUBJECT NOT DEFINED) ===== + % Need to get a study for each imported file + if isnan(iSubjectInit) || isnan(iStudyInit) + % === PARSE FILENAME === + % Try to get subject name and condition name out of the filename + [SubjectName, ConditionName] = ParseDataFilename(ImportedDataMat(iImported).FileName,loadedFiles); + sSubject = []; + % === SUBJECT NAME === + if isempty(SubjectName) + % If subject is defined by the input node: use this subject's name + if (iSubjectInit ~= 0) && ~isnan(iSubjectInit) + [sSubject, iSubject] = bst_getContext('Subject', iSubjectInit); + end + else + % Find the subject in DataBase + [sSubject, iSubject] = bst_getContext('SubjectWithName', SubjectName); + % If subject is not found in DB: create it + if isempty(sSubject) + [sSubject, iSubject] = db_addSubject(SubjectName); + % If subject cannot be created: error: stop everything + if isempty(sSubject) + bst_error(['Could not create subject "' SubjectName '"'], 'Import MEG/EEG recordings'); + return; + end + end + end + % If a subject creation is needed + if isempty(sSubject) + SubjectName = 'NewSubject'; + % If auto subject was not created yet + if isempty(iNewAutoSubject) + % Try to get a subject with this name in database + [sSubject, iSubject] = bst_getContext('Subject', SubjectName); + % If no subject with automatic name exist in database, create it + if isempty(sSubject) + [sSubject, iSubject] = db_addSubject(SubjectName); + iNewAutoSubject = iSubject; + end + % If auto subject was created for the previous imported file + else + [sSubject, iSubject] = bst_getContext('Subject', iNewAutoSubject); + end + end + % === CONDITION NAME === + if isempty(ConditionName) + % If a condition is defined by the input node + if (iStudyInit ~= 0) && ~isnan(iStudyInit) + sStudyInit = bst_getContext('Study', iStudyInit); + ConditionName = sStudyInit.Condition{1}; + else + ConditionName = 'Default'; + end + end + % Get real subject directory (not the default subject directory, which is the default) + sSubjectRaw = bst_getContext('Subject', iSubject, 1); + ConditionPath = fileparts(sSubjectRaw.FileName); + % Find study (subject/condition) in database + [sNewStudy, iNewStudy] = bst_getContext('StudyWithCondition', fullfile(ConditionPath, ConditionName)); + % If study does not exist : create it + if isempty(iNewStudy) + iNewStudy = db_addCondition(ConditionPath, ConditionName, 'NoRefresh'); + if isempty(iNewStudy) + warning(['Cannot create condition : "' fullfile(ConditionPath, ConditionName) '"']); + continue; + end + end + iStudies = [iStudies, iNewStudy]; + else + iSubject = iSubjectInit; + sSubject = bst_getContext('Subject', iSubject); + iStudies = iStudyInit; + end + % ===== CHANNEL FILE TARGET ===== + % If subject uses default channel + if (sSubject.UseDefaultChannel) + % Add the DEFAULT study directory to the list + [sDefaultStudy, iDefaultStudy] = bst_getContext('DefaultStudy', iSubject); + iStudyCopyChannel(iImported) = iDefaultStudy; + else + % Else add study directory in the list + iStudyCopyChannel(iImported) = iStudies(end); + end + + % ===== MOVE IMPORTED FILES IN STUDY DIRECTORY ===== + % Current study + sStudy = bst_getContext('Study', iStudies(end)); + % Get study subdirectory + studySubDir = fileparts(sStudy.FileName); + % Get the directory in which the file was stored by the in_data() function + [importedPath, importedBase, importedExt] = fileparts(ImportedDataMat(iImported).FileName); + % Remove ___COND and ___SUBJ tags + importedBase = removeStudyTags(importedBase); + % Build final filename + finalImportedFile = fullfile(ProtocolInfo.STUDIES, studySubDir, [importedBase, importedExt]); + finalImportedFile = io_makeUniqueFilename(finalImportedFile); + % If data file is not in study subdirectory : need to move it + if ~io_compareFileNames(importedPath, fileparts(finalImportedFile)) + bst_message_window(sprintf('Moving file : "%s" => "%s"...', ImportedDataMat(iImported).FileName, finalImportedFile)); + movefile(ImportedDataMat(iImported).FileName, finalImportedFile, 'f'); + ImportedDataMat(iImported).FileName = strrep(finalImportedFile, ProtocolInfo.STUDIES, ''); + end + + % ===== STORE DATA FILE IN DATABASE ====== + % New data indice in study + nbData = length(sStudy.Data) + 1; + % Add data to subject + sStudy.Data(nbData) = ImportedDataMat(iImported); + % Store current study + bst_setContext('Study', iStudies(end), sStudy); + % Record all subjects + iAllSubjects = [iAllSubjects, iSubject]; + end + clear iStudy sStudy studySubDir + + % Remove NaN and duplicated values in studies list + iStudies = unique(iStudies(~isnan(iStudies))); + iStudyCopyChannel = unique(iStudyCopyChannel(~isnan(iStudyCopyChannel))); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%% SECTION A REFAIRE COMPLETEMENT %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%% FONCTION "SET CHANNEL" SEPAREE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % If a channel file was imported + if ~isempty(ChannelMat) + for i=1:length(iStudyCopyChannel) + iStudy = iStudyCopyChannel(i); + sStudy = bst_getContext('Study', iStudy); + studySubDir = fileparts(sStudy.FileName); + + % ===== SAVE CHANNEL FILE ===== + % Delete all the other channel files in the study directory + channelFiles = dir(fullfile(ProtocolInfo.STUDIES, studySubDir, '*channel*.mat')); + if ~isempty(channelFiles) + io_deleteFile({fullfile(ProtocolInfo.STUDIES, studySubDir, channelFiles.name)}, 1); + end + % Add comment field if it does not exist + if ~isfield(ChannelMat, 'Comment') + %ChannelMat.Comment = DataFile_base; + ChannelMat.Comment = [FileFormat ' channels']; + end + % Base channel filename + ChannelFile_base = DataFile_base; + + % VECTORVIEW 306: 204 Gradiometers + 102 Magnetometers + if (nnz(strcmpi({ChannelMat.Channel.Type}, 'MEG GRAD')) == 204) && ... + (nnz(strcmpi({ChannelMat.Channel.Type}, 'MEG MAG')) == 102) + % Add a tag in the filename + ChannelFile_base = [ChannelFile_base, '_vectorview306']; + % CTF: 29 references + elseif (nnz(strcmpi({ChannelMat.Channel.Type}, 'MEG REF')) > 26) + % Check if accuracy is 1 (MEG channel = axial gradio = 8 points) + iMeg = find(strcmpi({ChannelMat.Channel.Type}, 'MEG')); + if (size(ChannelMat.Channel(iMeg(1)).Loc, 2) == 8) + ChannelFile_base = [ChannelFile_base, '_ctf_acc1']; + end + end + + % Produce a default channel filename + BstChannelFile = fullfile(ProtocolInfo.STUDIES, studySubDir, ['channel_' ChannelFile_base '.mat']); + % Save new ChannelFile in Brainstorm format + save(BstChannelFile, '-struct', 'ChannelMat'); + bst_message_window(sprintf(' => Channels list saved in "%s".', strrep(BstChannelFile, ProtocolInfo.STUDIES, ''))) + + % ===== STORE NEW CHANNEL IN DATABASE ====== + % New channel structure + newChannel = db_getDataTemplate('Channel'); + newChannel(1).FileName = strrep(BstChannelFile, ProtocolInfo.STUDIES, ''); + newChannel(1).nbChannels = length(ChannelMat.Channel); + newChannel(1).Comment = sprintf('%s (%d)', ChannelMat.Comment, length(ChannelMat.Channel)); + newChannel(1).Modalities = getChannelModalities( ChannelMat.Channel ); + % Save displayable types list + newChannel(1).DisplayableSensorTypes = getChannelModalities( ChannelMat.Channel, 5 ); + + % Add channel to study + sStudy.Channel = newChannel; + % Store studies database + bst_setContext('Study', iStudy, sStudy); + end + end + iAllStudies = [iAllStudies, iStudies, iStudyCopyChannel]; +end +bst_progressBar('stop'); + +% === UPDATE DISPLAY === +% Update links +if ~isempty(iAllSubjects) + iAllSubjects = unique(iAllSubjects); + for i = 1:length(iAllSubjects) + db_updateLinkResults('Subject', iAllSubjects(i)); + end +end +% Update tree +if ~isempty(iAllStudies) + iAllStudies = unique(iAllStudies); + tree_updateNode('Study', iAllStudies); + if (length(iAllStudies) == 1) + tree_selectStudyNode(iAllStudies(1)); + end +end +% Edit new subject (if a new subject was created automatically) +if ~isempty(iNewAutoSubject) + db_editSubject(iNewAutoSubject); +end +% Save database +bst_saveDatabase(); + +return +end + + + + +%% ================================================================================ +% ===== HELPER FUNCTIONS ========================================================= +% ================================================================================ +% Expands a list of paths : +% 1) If it is a file => keep it unchanged +% 2) If they are .ds/ directory with .meg4/.res4 files, +% or ERPCenter directories with .hdr/.erp files, +% => keep them as "files to open" +% 3) Else : add all the data files they contains (subdirectories included) +function ExpFiles = ExpandDataFilesList(FileFilter, Files) + ExpFiles = {}; + for i = 1:length(Files) + % DIRECTORIES + if isdir(Files{i}) + isFormatCTF = strcmpi(FileFilter.getFormatName(), 'CTF'); + isFormatERP = strcmpi(FileFilter.getFormatName(), 'EEG-ERPCenter'); + isDirFile = 0; + % If CTF/ERP format + if isFormatCTF || isFormatERP + if isFormatCTF + % Check if there are .meg4 or .res4 files in directory + dirFiles = [dir(fullfile(Files{i}, '*.meg4')); + dir(fullfile(Files{i}, '*.res4'))]; + else + % Check if there are .hdr file in directory + dirFiles = dir(fullfile(Files{i}, '*.hdr')); + end + j = 1; + while (~isDirFile && (j <= length(dirFiles))) + if FileFilter.accept(java.io.File(fullfile(Files{i}, dirFiles(j).name))) + isDirFile = 1; + ExpFiles = cat(2, ExpFiles, Files{i}); + else + j = j + 1; + end + end + end + + % If directory is not a CTF/ERP dir to be opened + if ~isDirFile + % Get all files in this directory + dirFiles = dir(fullfile(Files{i}, '*')); + % Build a new files list + dirFullFiles = {}; + for j = 1:length(dirFiles) + % Process all the files that do not start with a '.' + if (dirFiles(j).name(1) ~= '.') + dirFullFiles{end + 1} = fullfile(Files{i}, dirFiles(j).name); + end + end + % And call function recursively + ExpFiles = cat(2, ExpFiles, ExpandDataFilesList(FileFilter, dirFullFiles)); + end + + % SINGLE FILE + else + % Test if is accepted by FileFilter + if FileFilter.accept(java.io.File(Files{i})) + % If single file is CTF : get the parent + if strcmpi(FileFilter.getFormatName(), 'CTF') + ExpFiles{end+1} = fileparts(Files{i}); + else + ExpFiles{end+1} = Files{i}; + end + end + end + end +end + + +% Parse filename to detect subject/condition/run +function [SubjectName, ConditionName] = ParseDataFilename(filename,loadedFiles) + SubjectName = ''; + ConditionName = ''; + % Get only short filename without extension + [fPath, fName, fExt] = fileparts(filename); + + % IMPORTED FILENAMES : '....___SUBJsubjectname___CONDcondname___...' + % Get subject tag + iTag_subj = strfind(fName, '___SUBJ'); + if ~isempty(iTag_subj) + iStartSubj = iTag_subj + 7; + % Find closing tag + iCloseSubj = strfind(fName(iStartSubj:end), '___'); + % Find closing tag + if ~isempty(iCloseSubj) + SubjectName = fName(iStartSubj:iStartSubj + iCloseSubj - 2); + end + elseif nargin>1 + % Uses path of the loaded files to define subject name + [p,n]=fileparts(loadedFiles{1}); + [p,SubjectName]=fileparts(p); + end + + % Get condition tag + iTag_cond = strfind(fName, '___COND'); + if ~isempty(iTag_cond) + iStartCond = iTag_cond + 7; + % Find closing tag + iCloseCond = strfind(fName(iStartCond:end), '___'); + % Find closing tag + if ~isempty(iCloseCond) + ConditionName = fName(iStartCond:iStartCond + iCloseCond - 2); + end + end +end + +% Remove study tags (___COND and ___SUBJ) +function fname = removeStudyTags(fname) + iTags = findstr(fname, '___'); + if iTags >= 2 + iStart = iTags(1); + if (iTags(end) + 2 == length(fname)) + iStop = iTags(end) + 2; + else + % Leave at least one '_' as a separator + iStop = iTags(end) + 1; + end + fname(iStart:iStop) = []; + end +end + diff --git a/brainstorm3/toolbox/misc/mri_drawCuts.m b/brainstorm3/toolbox/misc/mri_drawCuts.m new file mode 100644 index 0000000..1b6a7fc --- /dev/null +++ b/brainstorm3/toolbox/misc/mri_drawCuts.m @@ -0,0 +1,230 @@ +function [hCuts, OutputOptions] = mri_drawCuts(hFig, OPTIONS) +% MRI_DRAWMRICUTS: Plot a MRI volume in a 3D visualization figure (three orthogonal cuts). +% +% USAGE: hCuts = mri_drawCuts(hFig, OPTIONS) +% INPUT: (structure OPTIONS) +% - sMri : Brainstorm MRI structure +% - iMri : Indice of MRI structure in GlobalData.Mri array +% - cutsCoords : [x,y,z] location of the cuts in the volume +% (value that is set to NaN => cut is not displayed) +% - MriThreshold : Intensity threshold above which a voxel is displayed in the MRI slice. +% - MriAlpha : Transparency of MRI slices +% - MriColormap : Colormap to use to display the slices +% (optional) +% - OverlayCube : 3d-volume (same size than MRI) with specific data values +% - OverlayIntThreshold : Intensity threshold above which a voxel is overlayed in the MRI slices. +% - OverlayExtThreshold : Extent threshold, minimal size of clusters overlayed in the MRI slices. +% - OverlayAlpha : Overlayed voxels transparency +% - OverlayColormap : Colormap to use to display the overlayed data +% - OverlayBounds : [minValue, maxValue]: amplitude of the OverlayColormap +% - isMipAnatomy : 1=compute maximum intensity projection in the MRI volume +% - isMipAnatomy : 1=compute maximum intensity projection in the OVerlay volume +% +% OUTPUT: +% - hCuts : [3x1 double] Graphic handles to the images that were created +% - OutputOptions : structure with some output information +% |- MipAnatomy : {3x1 cell} +% |- MipFunctional : {3x1 cell} + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2006 (University of Geneva) +% ----------------------------- Script History --------------------------------- +% FT 24-Jun-2008 Adaptation for brainstorm3 +% ------------------------------------------------------------------------------ + + +%% ===== INITIALIZATION ===== +mriSize = size(OPTIONS.sMri.Cube); +isOverlay = ~isempty(OPTIONS.OverlayCube); +% Output variable +hCuts = [-1 -1 -1]; +OutputOptions.MipAnatomy = cell(3,1); +OutputOptions.MipFunctional = cell(3,1); +% Colormap bounds +if isempty(OPTIONS.sMri.Histogram.intensityMax) + MriColormapBounds = []; +else + MriColormapBounds = [0 double(OPTIONS.sMri.Histogram.intensityMax)]; +end +% Get the type of figure +FigureId = getappdata(hFig, 'FigureId'); +% Get in which axes we are supposed to display the MRI +switch (FigureId.Type) + case '3DViz' + hTarget = findobj(hFig, 'tag', 'Axes3D'); + case 'MriViewer' + % Get figure handles + Handles = gui_figuresManager('GetFigureHandles', hFig); + hTarget = [Handles.imgs_mri, Handles.imgc_mri, Handles.imga_mri]; +end + + + +%% ===== DISPLAY SLICES ===== +for iCoord = 1:3 + % Ignore the slice if indice is NaN + if isnan(OPTIONS.cutsCoords(iCoord)) + continue + end + + % === GET MRI SLICE === + % If maximum intensity power required + if OPTIONS.isMipAnatomy + % If the maximum is not yet computed: compute it + if isempty(OPTIONS.MipAnatomy{iCoord}) + sliceMri = double(mri_getSlice(OPTIONS.sMri.Cube, OPTIONS.cutsCoords(iCoord), iCoord, OPTIONS.isMipAnatomy)'); + OutputOptions.MipAnatomy{iCoord} = sliceMri; + % Else: use the previously computed maximum + else + sliceMri = OPTIONS.MipAnatomy{iCoord}; + end + % Else: just extract a slice from the volume + else + sliceMri = double(mri_getSlice(OPTIONS.sMri.Cube, OPTIONS.cutsCoords(iCoord), iCoord, OPTIONS.isMipAnatomy)'); + end + + % === GET OVERLAY SLICE === + % Get Overlay slice + if isOverlay + % If maximum intensity power required + if OPTIONS.isMipFunctional + % If the maximum is not yet computed: compute it + if isempty(OPTIONS.MipFunctional{iCoord}) + sliceOverlay = double(mri_getSlice(OPTIONS.OverlayCube, OPTIONS.cutsCoords(iCoord), iCoord, OPTIONS.isMipFunctional)'); + OutputOptions.MipFunctional{iCoord} = sliceOverlay; + % Else: use the previously computed maximum + else + sliceOverlay = OPTIONS.MipFunctional{iCoord}; + end + % Else: just extract a slice from the volume + else + sliceOverlay = double(mri_getSlice(OPTIONS.OverlayCube, OPTIONS.cutsCoords(iCoord), iCoord, OPTIONS.isMipFunctional)'); + end + else + sliceOverlay = []; + end + + % === APPLY COLORMAP === + % Alpha value depends on if MIP is used + if OPTIONS.isMipFunctional && ~OPTIONS.isMipAnatomy + alphaValue = .3; + else + alphaValue = 0; + end + % Compute alpha map + sliceSize = size(sliceMri); + AlphaMap = ones(sliceSize) * (1 - OPTIONS.MriAlpha); + AlphaMap(sliceMri < OPTIONS.MriThreshold) = alphaValue; + % Apply colormap to slice + cmapSlice = applyColormap(sliceMri, OPTIONS.MriColormap, MriColormapBounds); + + % === Display overlay slice === + if isOverlay + % Get max value for slice + %MaxValue = max(abs(sliceOverlay(:))); + % Apply colormap to overlay slice + %cmapOverlaySlice = applyColormap(sliceOverlay, OverlayColormap, MaxValue * [0 1]); + cmapOverlaySlice = applyColormap(sliceOverlay, OPTIONS.OverlayColormap, OPTIONS.OverlayBounds); + % Build overlay mask + overlayMask = ones(sliceSize) * (1 - OPTIONS.OverlayAlpha); + overlayMask(abs(sliceOverlay) <= OPTIONS.OverlayIntThreshold .* OPTIONS.OverlayBounds(2)) = 0; + %knd: to do: + % overlayMask(abs(sliceOverlay) <= OPTIONS.OverlayExtThreshold .* OPTIONS.OverlayBounds(2)) = 0; + + % Draw overlay slice over MRI slice + cmapSlice(:,:,1) = cmapSlice(:,:,1) .* (1 - overlayMask) + cmapOverlaySlice(:,:,1) .* overlayMask; + cmapSlice(:,:,2) = cmapSlice(:,:,2) .* (1 - overlayMask) + cmapOverlaySlice(:,:,2) .* overlayMask; + cmapSlice(:,:,3) = cmapSlice(:,:,3) .* (1 - overlayMask) + cmapOverlaySlice(:,:,3) .* overlayMask; + end + + % Display function depends on figure type + switch (FigureId.Type) + case '3DViz' + hCut = plotSlice3DViz(hTarget, cmapSlice, OPTIONS.cutsCoords(iCoord), iCoord); + if ~isempty(hCut) + hCuts(iCoord) = hCut; + end + case 'MriViewer' + hCut = plotSliceMriViewer(hTarget(iCoord), cmapSlice); + end +end + + +%% ================================================================================================ +% ===== INTERNAL FUNCTIONS ======================================================================= +% ================================================================================================ +%% ===== PLOT SLICES IN 3D ====== + function hCut = plotSlice3DViz(hAxes, cmapSlice, sliceLocation, dimension) + % Get locations of the slice + nbPts = 50; + baseVect = linspace(0,1,nbPts); + switch(dimension) + case 1 + X = ones(nbPts) .* sliceLocation .* OPTIONS.sMri.Voxsize(1); + Y = meshgrid(baseVect) .* mriSize(2) .* OPTIONS.sMri.Voxsize(2); + Z = meshgrid(baseVect)' .* mriSize(3) .* OPTIONS.sMri.Voxsize(3); + case 2 + X = meshgrid(baseVect) .* mriSize(1) .* OPTIONS.sMri.Voxsize(1); + Y = ones(nbPts) .* sliceLocation .* OPTIONS.sMri.Voxsize(2); + Z = meshgrid(baseVect)' .* mriSize(3) .* OPTIONS.sMri.Voxsize(3); + case 3 + X = meshgrid(baseVect) .* mriSize(1) .* OPTIONS.sMri.Voxsize(1); + Y = meshgrid(baseVect)' .* mriSize(2) .* OPTIONS.sMri.Voxsize(2); + Z = ones(nbPts) .* sliceLocation .* OPTIONS.sMri.Voxsize(3); + end + + % === Switch coordinates from MRI-CS to SCS === + % Apply Rotation/Translation + XYZ = [reshape(X, 1, []); + reshape(Y, 1, []); + reshape(Z, 1, [])]; + XYZ = mri2scs(OPTIONS.sMri, XYZ); + % Convert to milimeters + XYZ = XYZ ./ 1000; + + % === PLOT SURFACE === + tag = sprintf('MriCut%d', dimension); + % Delete previous cut + delete(findobj(hFig, 'Tag', tag)); + % Plot new surface + hCut = surface('XData', reshape(XYZ(1,:),nbPts,nbPts), ... + 'YData', reshape(XYZ(2,:),nbPts,nbPts), ... + 'ZData', reshape(XYZ(3,:),nbPts,nbPts), ... + 'CData', cmapSlice, ... + 'FaceColor', 'texturemap', ... + 'FaceAlpha', 'texturemap', ... + 'AlphaData', AlphaMap, ... + 'AlphaDataMapping', 'none', ... + 'EdgeColor', 'none', ... + 'AmbientStrength', .5, ... + 'DiffuseStrength', .5, ... + 'SpecularStrength', .6, ... + 'Tag', tag, ... + 'Parent', hAxes); + end + + +%% ===== PLOT SLICES IN MRIVIEWER ====== + function hCut = plotSliceMriViewer(hImg, cmapSlice) + % Get locations of the slice + set(hImg, 'CData', cmapSlice); + hCut = hImg; + end +end diff --git a/brainstorm3/toolbox/stat/bst_batch.m b/brainstorm3/toolbox/stat/bst_batch.m new file mode 100644 index 0000000..9996589 --- /dev/null +++ b/brainstorm3/toolbox/stat/bst_batch.m @@ -0,0 +1,1258 @@ +function bst_batch(OPTIONS) +% BST_BATCH: Apply a process defined with panel_statRun, to a list a file. +% +% USAGE: bst_batch('CreatePanel', OPTIONS) +% +% INPUTS: (OPTIONS structure) +% - Conditions : Structure describing the files to process (from panel_stat and panel_process) +% - sProcess : Process to apply (defined in panel_statRun/GetProcessesList) +% - isData : 1 if files to process are recordings, 0 if they are cortical sources +% - Comment : Default comment for output files +% - isAbsoluteValues : For sources, apply "abs" before applying the process +% - nbPermutation : Number of permutations to perform +% - isOverwriteFiles : For filters, if 1 the input files will be replaced +% - OutputType : {'database', 'file', 'matlab'} +% - isCluster : If 1, use the clusters/scouts (only for data extraction functions) +% - isClusterAverage : If 1, merge the input clusters/scouts +% - sClusters : Clusters/scouts to apply (if isCluster = 1) +% - ClustersOptions : Structure that describes the way to compute the clusters/scouts values +% - Time : Time bounds to compute values +% - Baseline : Baseline bounds +% - iTime : Indices of the time samples to process +% - iBaseline : Indices of the baseline + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2009 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: Francois Tadel, 2009 +% ----------------------------- Script History --------------------------------- +% FT 17-Jul-2009 Creation +% ------------------------------------------------------------------------------ + +% Get samples lists +SamplesA = OPTIONS.Conditions.SamplesA; +SamplesB = OPTIONS.Conditions.SamplesB; + +% ===== APPLY PROCESS ===== +sProcess = OPTIONS.sProcess; +% Switch according to category +switch (sProcess.Category) + case 'Filter' + iStudyToRedraw = BatchFilter(SamplesA, OPTIONS); + isNewConditions = 0; + case 'Extract' + iStudyToRedraw = BatchExtract(SamplesA, OPTIONS); + isNewConditions = 0; + case 'Filter2' + iStudyToRedraw = BatchFilter2(SamplesA, SamplesB, OPTIONS); + isNewConditions = 0; + case 'Average' + % === Grand-average (by condition) === + % Call several time the average function (once per condition) + if strcmpi(sProcess.Name, 'GAVE') + % Initial values + iStudyToRedraw = []; + isNewConditions = 0; + % Process each condition independently + uniqueConditions = unique({SamplesA.Condition}); + for i = 1:length(uniqueConditions) + % Process the average of condition #i + iSampCond = find(strcmpi(uniqueConditions{i}, {SamplesA.Condition})); + [tmpStudyToRedraw, tmpNewConditions] = BatchAverage(SamplesA(iSampCond), OPTIONS); + % Save the results + iStudyToRedraw = [iStudyToRedraw tmpStudyToRedraw]; + isNewConditions = isNewConditions || tmpNewConditions; + end + + % === Average by subject === + % Call several time the average function (once per condition) + elseif strcmpi(sProcess.Name, 'SubjAvg') + % Initial values + iStudyToRedraw = []; + isNewConditions = 0; + % Process each subject independently + uniqueSubjects = unique({SamplesA.SubjectFile}); + for i = 1:length(uniqueSubjects) + % Process the average of subject #i + iSampSubj = find(strcmpi(uniqueSubjects{i}, {SamplesA.SubjectFile})); + [tmpStudyToRedraw, tmpNewConditions] = BatchAverage(SamplesA(iSampSubj), OPTIONS); + % Save the results + iStudyToRedraw = [iStudyToRedraw tmpStudyToRedraw]; + isNewConditions = isNewConditions || tmpNewConditions; + end + + % Else, just call function once to average everything + else + [iStudyToRedraw, isNewConditions] = BatchAverage(SamplesA, OPTIONS); + end + + case {'Spectral'} + [iStudyToRedraw, isNewConditions] = BatchSpectralDecomposition(SamplesA, OPTIONS); + + case {'Recurrence'} + [iStudyToRedraw, isNewConditions] = BatchRecurrenceMaps(SamplesA, OPTIONS); + + case {'TTest', 'PermTest'} + iStudyToRedraw = BatchStat(SamplesA, SamplesB, OPTIONS); + isNewConditions = 0; + + case {'Anova'} + iStudyToRedraw = BatchStat(SamplesA,[],OPTIONS); + isNewConditions = 0; +end + +% ===== UPDATE INTERFACE ===== +% OUTPUT TYPE: DATABASE ONLY +if strcmpi(OPTIONS.OutputType, 'database') && ~isempty(iStudyToRedraw) + iStudyToRedraw = unique(iStudyToRedraw); + % Unload all datasets + bst_dataSetsManager('UnloadAll', 'Forced'); + % Update results links in target study + db_updateLinkResults('Study', iStudyToRedraw); + % Update tree model + if isNewConditions + tree_updateModel(); + else + tree_updateNode('Study', iStudyToRedraw); + end + % Select target study as current node + tree_selectStudyNode( iStudyToRedraw(1) ); + % Save database + bst_saveDatabase(); +end + +% Hide waitbar +bst_progressBar('stop'); + + +end + + + +%% ====================================================================================== +% ===== BATCH FUNCTIONS ================================================================ +% ====================================================================================== + +%% ===== BATCH: FILTERS ===== +function iStudyToRedraw = BatchFilter(SamplesA, OPTIONS) + % === SOME VERIFICATIONS === + % OUTPUT: DATABASE ONLY + if ~strcmpi(OPTIONS.OutputType, 'database') + error('Filtering results can only be stored in database.'); + end + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + % Prepare OPTIONS structure for process_apply function + filterOPTIONS = struct('fcnFilter', str2func(['process_' sProcess.Name]), ... + 'FileA', '', ... + 'iTime', OPTIONS.iTime, ... + 'iBaseline', OPTIONS.iBaseline, ... + 'FileTag', sProcess.Name, ... + 'Comment', OPTIONS.Comment, ... + 'isAbsoluteValues', OPTIONS.isAbsoluteValues, ... + 'blockDimension', sProcess.blockDimension, ... + 'isAvgRef', sProcess.isAvgRef); + + % === FILES LOOP === + bst_progressBar('start', ['Apply process: ' sProcess.Name], 'Initialization...', 0, nbSamplesA); + % Process all the files + for i = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(i).FileName]); + bst_progressBar('inc', 1); + % Output study: same as input file + iTargetStudy = SamplesA(i).iStudy; + sTargetStudy = bst_getContext('Study', iTargetStudy); + % Ignore computation for files that are already processed + if ~isempty(strfind(SamplesA(i).FileName, ['_' sProcess.Name])) + res = java_dialog('confirm', ['The following file has already been processed with this filter: ' 10 SamplesA(i).FileName '.' 10 10 'Apply this process again ?'], 'Processes'); + if ~res + continue + end + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === COMPUTE FILTER === + % Complete filter configuration + filterOPTIONS.FileA = SamplesA(i).FullFileName; + % Apply process + [sNewFile, filterOPTIONS] = process_apply(filterOPTIONS); + % If process cancelled + if isempty(sNewFile) + return + end + + % === UPDATE STUDY === + % Overwrite initial file + if OPTIONS.isOverwriteFiles + % Delete the intial file + io_deleteFile(SamplesA(i).FullFileName, 1); + end + % Add new file to database + if OPTIONS.isData + if OPTIONS.isOverwriteFiles + iItem = SamplesA(i).iItem; + else + iItem = length(sTargetStudy.Data) + 1; + end + % Add new descriptor it to study + sTargetStudy.Data(iItem) = sNewFile; + else + if OPTIONS.isOverwriteFiles + iResult = SamplesA(i).iItem; + else + iResult = length(sTargetStudy.Result) + 1; + end + % Add new descriptor it to study + sTargetStudy.Result(iResult) = sNewFile; + end + bst_setContext('Study', iTargetStudy, sTargetStudy); + end +end + + +%% ===== BATCH: EXTRACT ===== +function iStudyToRedraw = BatchExtract(SamplesA, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + isOneOutputMat = ~strcmpi(OPTIONS.OutputType, 'database'); + initTimeVector = []; + ProtocolInfo = bst_getContext('ProtocolInfo'); + + % === FILES LOOP === + bst_progressBar('start', 'Data extraction', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Output study: same as input file + iTargetStudy = SamplesA(iSample).iStudy; + sTargetStudy = bst_getContext('Study', iTargetStudy); + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILE === + if sProcess.isAvgRef + [matValues, matName, ChannelFlag, TimeVector] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, []); + else + [matValues, matName, ChannelFlag, TimeVector] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, [], 'NoAvgRef'); + end + + % === TIME === + % Check time vectors + if (iSample == 1) + initTimeVector = TimeVector; + elseif (length(initTimeVector) ~= length(TimeVector)) || ~all(abs(initTimeVector - TimeVector) < 1e-6) + filedesc = fullfile(fileparts(SamplesA(iSample).FileName), SamplesA(iSample).Comment); + bst_error(['Time definition should be the same for all the files.' 10 10 'Ignoring file: "' filedesc '"'], 'bst_batch', 0); + return + end + % Keep only required time indices + matValues = matValues(:, OPTIONS.iTime); + TimeVector = TimeVector(OPTIONS.iTime); + + % === PROCESSES === + % Absolute values + if OPTIONS.isAbsoluteValues + matValues = abs(matValues); + end + % Process to apply to this block of data + switch (sProcess. Name) + case 'timemean' + % Compute the average of all the time samples on the defined time window + matValues = mean(matValues, 2); + isTimeMean = 1; + case 'timevar' + % Compute the variance of all the time samples on the defined time window + matValues = var(matValues, 0, 2); + isTimeMean = 1; + case 'extract' + % Nothing to do + isTimeMean = 0; + end + % TimeMean: Keep only the time window from which was computed the result + if isTimeMean + OPTIONS.iTime = OPTIONS.iTime([1,end]); + TimeVector = TimeVector([1, end]); + end + + % === APPLY CLUSTER === + if OPTIONS.isCluster + % Process each cluster + nbClusters = length(OPTIONS.Clusters); + tmpMatValues = zeros(nbClusters, size(matValues, 2)); + DescCluster = cell(nbClusters, 1); + for i = 1:nbClusters + sCluster = OPTIONS.Clusters(i); + % === GET ROWS INDICES === + if OPTIONS.isData + % Get channel file + [sStudy, iStudy] = bst_getContext('DataFile', SamplesA(iSample).FileName); + sChannel = bst_getContext('ChannelForStudy', iStudy); + % Load channel file + ChannelFile = fullfile(ProtocolInfo.STUDIES, sChannel.FileName); + ChannelMat = load(ChannelFile, 'Channel'); + % CLUSTERS: Get cluster channels + iRows = panel_clusters('GetChannelsInCluster', sCluster, ChannelMat.Channel, ChannelFlag); + if isempty(iRows) + return; + end + else + % SCOUTS: Get the indices of the sources of this scout + iRows = sCluster.Vertices; + end + + % === COMPUTE CLUSTER VALUES === + % Scouts: absolute or relative values + isDifference = strcmpi(sProcess.Name, 'diffAB'); + % If computing a difference : FORCE RELATIVE VALUES + if ~OPTIONS.ClustersOptions.isAbsolute || isDifference + tmp = matValues(iRows, :); + else + tmp = abs(matValues(iRows, :)); + end + % Scouts computation operation : mean or max + switch (OPTIONS.ClustersOptions.function) + case 'Max' + tmpMatValues(i,:) = max(tmp, [], 1); + case 'Power' + tmpMatValues(i,:) = sum(tmp .^ 2, 1); + case 'Mean' + tmpMatValues(i,:) = mean(tmp, 1); + otherwise + bst_error(['Cannot extract automatically all values.' 10 ... + 'Please change scout options: "Scouts" panel > View > Time series options'], ... + 'bst_batch', 0); + return; + end + % Save the name of the scout + DescCluster{i} = sCluster.Label; + end + % Return results matrix averaged by scout + matValues = tmpMatValues; + else + DescCluster = {}; + end + + % ===== OUTPUT STRUCTURE ==== + % Create new output structure + if ~isOneOutputMat || (iSample == 1) + newFileMat = CreateDefaultStruct(sProcess, SamplesA(iSample).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, isOneOutputMat, 1); + % Append comment + newFileMat.Comment = [newFileMat.Comment, ' ', OPTIONS.Comment]; + end + % If new file to be saved at each loop: copy matValues + if ~isOneOutputMat + if isTimeMean + newFileMat.(matName) = repmat(matValues, [1, 2]); + else + newFileMat.(matName) = matValues; + end + else + % Get new matrix + prevMat = newFileMat.(matName); + % Check the orientation in which the new data should be appended: + % - Time mean : dimension 2 (time) + % - Channels mean : dimension 1 (channels) + if isTimeMean + % Check the number of electrodes + if ~isempty(prevMat) && (size(prevMat,1) ~= size(matValues,1)) + error(['The data files in samples set A do not have the same number of channels.' 10 ... + 'It is impossible to store their averages in the same matrix.']); + end + % Concatenate the results matrices & add description fields + newFileMat.(matName) = cat(2, prevMat, matValues); + newFileMat.DescFileName = cat(2, newFileMat.DescFileName, repmat({SamplesA(iSample).FileName}, [1, size(matValues,2)])); + newFileMat.DescCluster = cat(2, newFileMat.DescCluster, DescCluster); + else + if ~isempty(prevMat) && (size(prevMat,2) ~= size(matValues,2)) + error(['The files in samples set A do not have the same number of time samples.' 10 ... + 'It is impossible to store their averages in the same matrix.']); + end + % Concatenate the results matrices & add description fields + newFileMat.(matName) = cat(1, prevMat, matValues); + newFileMat.DescFileName = cat(1, newFileMat.DescFileName, repmat({SamplesA(iSample).FileName}, [size(matValues,1), 1])); + newFileMat.DescCluster = cat(1, newFileMat.DescCluster, DescCluster); + end + % Add bad channels from current ChannelFlag + newFileMat.ChannelFlag(ChannelFlag == -1) = -1; + end + + % ===== SAVE FILE ===== + if ~isOneOutputMat + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(iSample).FileName); + end + end + + % === EXPORT DATA === + if isOneOutputMat + % Display waitbar + bst_progressBar('start', 'Processes', 'Saving results...'); + % Save file + switch(OPTIONS.OutputType) + case 'file' + % Save in a user defined file + if OPTIONS.isData || OPTIONS.isCluster + export_data(newFileMat); + else + export_result(newFileMat); + end + case 'matlab' + % Export to Matlab workspace + export_matlab(newFileMat); + end + end +end + + +%% ===== BATCH: AVERAGE ===== +function [iStudyToRedraw, isNewConditions] = BatchAverage(SamplesA, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA,repmat(SamplesA, 0),OPTIONS); + % Update this study + iStudyToRedraw = iTargetStudy; + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + + % === PROCESS AVERAGE === + bst_progressBar('start', ['Apply process: ' sProcess.Name], 'Initialization...', 0, length(SamplesA)); + % If absolute values + if OPTIONS.isAbsoluteValues + strAbsolute = 'AbsoluteValues'; + else + strAbsolute = []; + end + Stat = bst_statFiles('mean', {SamplesA.FullFileName}, OPTIONS.iTime, 'PercentProgressBar', strAbsolute); + + % === SAVE RESULTS === + % Get default file structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, Stat.Time, OPTIONS.iTime, Stat.ChannelFlag, 0, 0); + % Add averaged values in it + newFileMat.(Stat.MatName) = Stat.mean; + % Comment + if isempty(OPTIONS.Comment) && isempty(Comment) + % Use default commet: "ProcessName: date" + c = clock; + strTime = sprintf('%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + newFileMat.Comment = [sProcess.Name ': ' strTime]; + elseif isempty(OPTIONS.Comment) + newFileMat.Comment = Comment; + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save and register file + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); +end + + +%% ===== BATCH: FILTER2 ===== +function [iStudyToRedraw, isNewConditions] = BatchFilter2(SamplesA, SamplesB, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),SamplesB(iSample),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + if sProcess.isAvgRef + % Sample A + [matValuesA, matNameA, ChannelFlagA, TimeVectorA] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, []); + % Sample B + [matValuesB, matNameB, ChannelFlagB, TimeVectorB] = bst_readMatrixInFile(SamplesB(iSample).FullFileName, []); + else + % Sample A + [matValuesA, matNameA, ChannelFlagA, TimeVectorA] = bst_readMatrixInFile(SamplesA(iSample).FullFileName, [], 'NoAvgRef'); + % Sample B + [matValuesB, matNameB, ChannelFlagB, TimeVectorB] = bst_readMatrixInFile(SamplesB(iSample).FullFileName, [], 'NoAvgRef'); + end + + % === TIME === + % Check time vectors + if (length(TimeVectorA) ~= length(TimeVectorB)) || ~all(abs(TimeVectorA - TimeVectorB) < 1e-6) + bst_error('Each couple of files (A,B) must have the same time definition.', 'bst_batch', 0); + return + elseif (length(ChannelFlagA) ~= length(ChannelFlagB)) + bst_error('Each couple of files (A,B) must have the same number of channels.', 'bst_batch', 0); + return + end + % Keep only required time indices + matValuesA = matValuesA(:, OPTIONS.iTime); + matValuesB = matValuesB(:, OPTIONS.iTime); + TimeVector = TimeVectorA(OPTIONS.iTime); + % Combine bad channels + ChannelFlag = ones(size(ChannelFlagA)); + ChannelFlag((ChannelFlagA == -1) | (ChannelFlagB == -1)) = -1; + + % === PROCESSES === + % Absolute values + if OPTIONS.isAbsoluteValues + matValuesA = abs(matValuesA); + matValuesB = abs(matValuesB); + end + % Apply process + switch (sProcess.Name) + case 'diffAB' + matValues = matValuesA - matValuesB; + case 'meanAB' + matValues = (matValuesA + matValuesB) / 2; + end + + % ===== SAVE FILE ==== + % Create default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(iSample).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 1); + % Add averaged values in it + newFileMat.(matNameA) = matValues; + % Comment + if isempty(OPTIONS.Comment) + if ~isempty(Comment) + newFileMat.Comment = Comment; + else + % Build comments based on the samples couple + localCond = struct('SamplesA',SamplesA(iSample), 'SamplesB',SamplesB(iSample)); + newFileMat.Comment = panel_statRun('FormatComment', sProcess, localCond, OPTIONS.Time); + end + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save file + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(iSample).FileName); + end +end + + +%% ===== BATCH: STAT ===== +function iStudyToRedraw = BatchStat(SamplesA, SamplesB, OPTIONS) + % Get process + sProcess = OPTIONS.sProcess; + testType = sProcess.Name; + isPermTest = strcmpi(sProcess.Category, 'PermTest'); + % For old Karim t-test + isOldSimpleTest = ~isempty(strfind(sProcess.Name, 'old')); + if isOldSimpleTest + testType = strrep(testType, 'old_', ''); + end + isAnova = strcmpi(sProcess.Category, 'Anova'); + + + % Display progress bar + bst_progressBar('start', 'Statistical test', 'Initialization...', 0, length(SamplesA)); + % Get output study + if isAnova + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess, SamplesA, SamplesA([]), OPTIONS); + else + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess, SamplesA, SamplesB, OPTIONS); + end + iStudyToRedraw = iTargetStudy; + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + + % === Load all the samples === + % Needed only for permutation t-test, and OLD KARIM T-TEST + if isPermTest || isOldSimpleTest + % Samples set A + [X1, ChannelFlagA, TimeVector] = buildDataArray({SamplesA.FullFileName}, OPTIONS.iTime); + % Samples set B + [X2, ChannelFlagB] = buildDataArray({SamplesB.FullFileName}, OPTIONS.iTime); + % If is absolute values + if OPTIONS.isAbsoluteValues + X1 = abs(X1); + X2 = abs(X2); + end + % Combine channel flag + ChannelFlag = ChannelFlagA; + ChannelFlag(ChannelFlagB == -1) = -1; + end + + if isAnova + %knd: to do + warning('manually changed anova factors!') + [pmap,Fmap,fx,ChannelFlag, TimeVector] = knd_rmanova_files(SamplesA,OPTIONS); + + % === SIMPLE TESTS (OLD) === + elseif ~isPermTest && isOldSimpleTest + % Remove the "old" tag + testType = strrep(testType, 'old_', ''); + % Set permutation dimension + dim_p = 1; + % Display waitbar + bst_progressBar('start', 'Processes', 'Computing t-test...'); + % Compute test + [pmap,tmap] = knd_ttest(X1, X2, dim_p, testType); + + % === SIMPLE TESTS === + elseif ~isPermTest + % Compute test + if OPTIONS.isAbsoluteValues + [pmap,tmap,ChannelFlag, TimeVector] = knd_ttest_files({SamplesA.FullFileName}, {SamplesB.FullFileName}, testType, OPTIONS.iTime, OPTIONS.iTime, 'AbsoluteValues'); + else + [pmap,tmap,ChannelFlag, TimeVector] = knd_ttest_files({SamplesA.FullFileName}, {SamplesB.FullFileName}, testType, OPTIONS.iTime, OPTIONS.iTime); + end + + % === PERMUTATIONS TESTS === + elseif isPermTest + tic + % Set permutation dimension + if sProcess.isPaired + dim_p = 1; + else + dim_p = -1; + end + + % Compute test + [pmap,tmap] = permtest(X1, X2, {testType}, dim_p, [], OPTIONS.nbPermutation); + % Display computation time + timeLength = toc(); + bst_message_window(sprintf('\nTook: %3.2f secs', timeLength)); + + + end + + % === BUILD NEW FILES === + % Display waitbar + bst_progressBar('start', 'Processes', 'Saving results...'); + + if isAnova + Factors.N = 3; + NS = numel(unique({SamplesA.SubjectName})) + [u,i,j] = unique([SamplesA.iItem]) + if numel(u)>1 + SelectedItem = listdlg('ListString', [strvcat({SamplesA(i).Condition}) repmat(' : ',length(u),1) strvcat({SamplesA(i).Comment})],'SelectionMode','single'); + if isempty(SelectedItem) + return + end + SamplesA = SamplesA(j == SelectedItem); + end + f = {SamplesA.Condition}; + f=reshape(f(1+[0:3]*NS),[2 2]) + fa=sprintf('%s+',f{1,:}); + fb=sprintf('%s+',f{2,:}); + Factors.Names{1}=sprintf('%s vs. %s',fa(1:end-1),fb(1:end-1)); + fa=sprintf('%s+',f{:,1}); + fb=sprintf('%s+',f{:,2}); + Factors.Names{2}=sprintf('%s vs. %s',fa(1:end-1),fb(1:end-1)); + + %Factors.Names = { 'FB' 'Conf' 'Subj'}; + Factors.NLevels = [2 2 NS] + Factors.Levels = { {'C' 'I'} {'H' 'L'} [] }; + Factors.X = []; + %must loop on maps + for i_fx=1:size(pmap,1) + % Get default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 0); + % Comment + newFileMat.Comment = OPTIONS.Comment ; + if numel(fx{i_fx}) == 1 + newFileMat.Comment = [newFileMat.Comment ' - Main effect of ']; + else + newFileMat.Comment = [newFileMat.Comment ' - Interaction of ']; + end + newFileMat.Comment = [newFileMat.Comment sprintf('%s * ',Factors.Names{fx{i_fx}})]; + newFileMat.Comment(end-2:end)=[]; + % Save P and F maps + sz=[size(pmap) 1]; + newFileMat.pmap = single(reshape(pmap(i_fx,:),sz(2:end))); + newFileMat.tmap = single(reshape(Fmap(i_fx,:),sz(2:end))); + % Save new file and register in database + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + end + else + % Get default structure + newFileMat = CreateDefaultStruct(sProcess, SamplesA(1).FullFileName, OPTIONS.isData, TimeVector, OPTIONS.iTime, ChannelFlag, 0, 0); + % Comment + if isempty(OPTIONS.Comment) + newFileMat.Comment = Comment; + else + newFileMat.Comment = OPTIONS.Comment; + end + % Save P and T maps + newFileMat.pmap = single(pmap); + newFileMat.tmap = single(tmap); + % Save new file and register in database + SaveNewFile(newFileMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + end +end + + +%% ===== BATCH: SPECTRAL ANALYSIS ====== +function [iStudyToRedraw, isNewConditions] = BatchSpectralDecomposition(SamplesA, OPTIONS) + % Frequency bands of interest + freqBands = ... + [1 3.9;... + 4,7.9;... + 8,12.9;... + 13,34.9;... + 35,54.9;... + 65,85;... + 200,250]; + NamesFreqBands = {... + 'delta_1_4Hz',... + 'theta_4_8Hz',... + 'alpha_8_13Hz',... + 'beta_13_35Hz',... + 'gamma_35_55Hz',... + 'gamma_65_85Hz',... + 'gamma_200_250Hz'}; + + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),repmat(SamplesA, 0),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + % Resolve link + [FileName, DataFile] = resolveResultsLink(SamplesA(iSample).FullFileName); + % Load results file + kernelMat = load(FileName); +% dataMat = load(DataFile,'F', 'Time'); + dataMat = in_data_bst( DataFile, [], 'Time', 'F'); + + %iMEG = good_channel(kernelMat.Channel,kernelMat.ChannelFlag, 'MEG'); %CBB: need to expand to EEG as well + iMEG = kernelMat.OPTIONS.GoodChannel; + dataMat.F = dataMat.F(iMEG, :); + + if iSample == 1 + F_RMS = zeros(size(kernelMat.ImagingKernel,1),length(NamesFreqBands),nbSamplesA); + end + sRate = abs(1/(dataMat.Time(2)-dataMat.Time(1))); + nTime = size(dataMat.F,2); + NFFT = 2^nextpow2(nTime); % Next power of 2 from length of y + freqVec = sRate/2*linspace(0,1,NFFT/2); + + fftF = fft(dataMat.F,NFFT,2)/nTime; + %powfftF = 2*abs(fftF(:,1:end/2)); + clear dataMat; + for ifreq = 1:length(NamesFreqBands) + VecInd = findclosest(freqBands(ifreq,:),freqVec); + %F = bandpassFilter_all(dataMat.F,sRate,freqBands(ifreq,1),freqBands(ifreq,2)); + F_RMS(:,ifreq,iSample) = sum(2*abs(kernelMat.ImagingKernel * fftF(:, VecInd(1):VecInd(2))),2)... + /length(VecInd(1):VecInd(2)); + % ImageGridAmp = sqrt(sum(ImageGridAmp.^2,2)/size(ImageGridAmp,2)); % compute root mean square power in current frequency band + end + end + + clear dataMat fftF + % Compute statistics + %F_RMS(F_RMS<.05*max(F_RMS(:)))=0; + aveStat = mean(F_RMS,3); + stdStat = std(F_RMS,0,3); + clear F_RMS + for ifreq = 1:length(NamesFreqBands) + current_aveStat = aveStat(:,ifreq); + tmp_current_aveStat = current_aveStat; + tmp_current_aveStat(tmp_current_aveStat<.5*max(tmp_current_aveStat))=0; + current_stdStat = stdStat(:,ifreq); + tStat = (tmp_current_aveStat./current_stdStat)*sqrt(nbSamplesA-1); + %tStat(isnan(tStat))=0; + + % === SAVE RESULTS === + kernelMat.ImageGridAmp = repmat(current_aveStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('GAVE: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + kernelMat.ImageGridAmp = repmat(current_stdStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('STD: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + + kernelMat.ImageGridAmp = repmat(tStat,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('T: %s',NamesFreqBands{ifreq}); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + end + +end + +%% ===== BATCH: RECURRENCE MAPS ====== +function [iStudyToRedraw, isNewConditions] = BatchRecurrenceMaps(SamplesA, OPTIONS) + % Frequency bands of interest + ampThresh = .75; %Binarization Threshold + timeWindow = 30; % time window within which binarization is processed + bandPass1 = 1; + bandPass2 = 250; + + % Get process + sProcess = OPTIONS.sProcess; + nbSamplesA = length(SamplesA); + iStudyToRedraw = []; + + % === FILES LOOP === + bst_progressBar('start', 'Comparisons', 'Initialization...', 0, nbSamplesA); + % Process all the files + for iSample = 1:nbSamplesA + % Progress bar + bst_progressBar('text', ['File: ' SamplesA(iSample).FileName]); + bst_progressBar('inc', 1); + % Get output study + [sTargetStudy, iTargetStudy isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA(iSample),repmat(SamplesA, 0),OPTIONS); + % If no valid output study can be found + if isempty(iTargetStudy) + return; + end + % Update this study + iStudyToRedraw(end + 1) = iTargetStudy; + + % === READ FILES === + % Resolve link + [FileName, DataFile] = resolveResultsLink(SamplesA(iSample).FullFileName); + % Load results file + kernelMat = load(FileName); +% dataMat = load(DataFile,'F', 'Time'); + dataMat = in_data_bst( DataFile, [], 'Time', 'F'); + iMEG = good_channel(kernelMat.Channel,kernelMat.ChannelFlag, 'MEG'); %CBB: need to expand to EEG as well + dataMat.F = dataMat.F(iMEG, :); + + sRate = abs(1/(dataMat.Time(2)-dataMat.Time(1))); + nTime = size(dataMat.F,2); + + VecInd = findclosest([-timeWindow,timeWindow]/1000,dataMat.Time); + timeVec = VecInd(1):VecInd(2); + dataMat.F = bandpassFilter_all(dataMat.F,sRate, bandPass1,bandPass2); + ImageGridAmp = abs(kernelMat.ImagingKernel * dataMat.F(:, VecInd(1):VecInd(2))); + + % Thresholding + if iSample == 1; + iMask = zeros(size(ImageGridAmp,1),1); + iTimeMask = zeros(size(ImageGridAmp,1),nbSamplesA); + end + %tmp = zeros(size(ImageGridAmp)); + %tmp(find(ImageGridAmp>ampThresh*max(ImageGridAmp(:)))) = 1; + + % time-relative max + % maxx = max(ImageGridAmp); + % maxx = repmat(maxx,size(ImageGridAmp,1),1); + % time-absolute max + maxx = max(ImageGridAmp(:)); + maxx = maxx*ones(size(ImageGridAmp)); + + iMaxtmp = ImageGridAmp > (ampThresh * maxx); + iTimeMask(:,iSample) = min(... + iMaxtmp .* repmat(dataMat.Time(timeVec),size(ImageGridAmp,1),1), ... + [],2); + iMaxtmp = sum(iMaxtmp,2); + + iMask(find(iMaxtmp)) = iMask(find(iMaxtmp)) + 1; + %[I,J] = find(ImageGridAmp>ampThresh*max(ImageGridAmp(:))); + %iMask(I) = iMask(I) + 1; + %iTimeMask(I,iSample) = dataMat.Time(timeVec(J)); + end + clear dataMat + iMask = 100*iMask/nbSamplesA; + iTimeMask = 1000*mean(iTimeMask,2).*(iMask>0); + + % === SAVE RESULTS === + kernelMat.ImageGridAmp = repmat(iMask,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('Recurrence Map'); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + kernelMat.ImageGridAmp = repmat(iTimeMask,1,2); + kernelMat.ImagingKernel = []; + kernelMat.ImageGridTime = [1,2]; + kernelMat.Comment = sprintf('Recurrence Map (latencies)'); + % Save and register file + SaveNewFile(kernelMat, sProcess, OPTIONS.isData, iTargetStudy, sTargetStudy, SamplesA(1).FileName); + + +end + +%% ====================================================================================== +% ===== HELPERS ======================================================================== +% ====================================================================================== +%% ===== CREATE DEFAULT OUTPUT STRUCTURE ===== +function sFileMat = CreateDefaultStruct(sProcess, FileName, isData, TimeVector, iTime, ChannelFlag, isOneOutputMat, isSampleBySample) +% Default structures for stat +isStat = ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); +if isStat + sStat = struct(... + 'Type', '', ... + 'Comment', '', ... + 'Time', TimeVector, ... + 'ChannelFlag', ChannelFlag, ... + 'pmap', [], ... + 'tmap', [], ... + 'pThreshold', 0.05); + end + + % If recordings + if isData + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'data'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + % Data + else + sFileMat.Time = TimeVector; + sFileMat.F = []; + end + % Else: sources + else + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Resolve link, if it is a link + [FileName, DataFile] = resolveResultsLink(FileName); + % Load file + sFileMat = load(FileName); + % Stat + if isStat + sStat.Type = 'results'; + sStat.Comment = sFileMat.Comment; + sFileMat = sStat; + else + % Time + sFileMat.Time = iTime; + sFileMat.ImageGridTime = TimeVector; + % Reset some fields + sFileMat.OPTIONS.Data = []; + sFileMat.Fsynth = []; + sFileMat.ImagingKernel = []; + sFileMat.ImageGridAmp = []; + if ~isSampleBySample + sFileMat.DataFile = []; + elseif ~isempty(DataFile) + sFileMat.DataFile = strrep(DataFile, ProtocolInfo.STUDIES, ''); + end + end + % Remove "Kernel" indications in the Comment field + sFileMat.Comment = strrep(sFileMat.Comment, '(Kernel)', ''); + sFileMat.Comment = strrep(sFileMat.Comment, 'Kernel', ''); + end + % Bad channels list + sFileMat.ChannelFlag = ChannelFlag; + + % Add some fields for exported results + if isOneOutputMat + sFileMat.DescFileName = {}; + sFileMat.DescCluster = {}; + sFileMat.DescProcessType= sProcess.Name; + end +end + + +%% ===== SAVE NEW FILE ===== +function sTargetStudy = SaveNewFile(newFileMat, sProcess, isData, iTargetStudy, sTargetStudy, InputFile) + % Get protocol directories + ProtocolInfo = bst_getContext('ProtocolInfo'); + % Get default output file + OutputDir = fullfile(ProtocolInfo.STUDIES, fileparts(sTargetStudy.FileName)); + FullFileName = GetDefaultFileName(sProcess, isData, OutputDir, InputFile); + % Save in database + save(FullFileName, '-struct', 'newFileMat'); + % Register in database + isStat = ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}); + FileName = strrep(FullFileName, ProtocolInfo.STUDIES, ''); + sTargetStudy = RegisterNewFile(newFileMat, FileName, isData, isStat, iTargetStudy); +end + + +%% ===== GET DEFAULT FILE NAME ===== +function OutputFile = GetDefaultFileName(sProcess, isData, OutputDir, InputFile) + % Get date and time for filename + c = clock; + strTime = sprintf('_%02.0f%02.0f%02.0f_%02.0f%02.0f', c(1)-2000, c(2:5)); + + % Output file tag + if ismember(sProcess.Category, {'TTest', 'PermTest', 'Anova'}) + if isData + fileTag = 'pdata'; + else + fileTag = 'presults'; + end + else + if isData + fileTag = 'data'; + else + fileTag = 'results'; + end + end + + % Other tags present in input file + if ~isempty(strfind(InputFile, '_zscore')) + strInputTags = '_zscore'; + else + strInputTags = ''; + end + + % Default filename + defFileName = [fileTag '_' sProcess.Name strTime strInputTags '.mat']; + % File in the target study + OutputFile = fullfile(OutputDir, defFileName); + % Make filename unique + OutputFile = io_makeUniqueFilename(OutputFile); +end + + +%% ===== REGISTER NEW FILE ===== +function sStudy = RegisterNewFile(FileMat, FileName, isData, isStat, iStudy) + % Get study + sStudy = bst_getContext('Study', iStudy); + % Stat + if isStat + % Create new stat file descriptor + sNewStat = db_getDataTemplate('Stat'); + sNewStat.FileName = FileName; + sNewStat.Comment = FileMat.Comment; + sNewStat.Type = FileMat.Type; + sNewStat.pThreshold = FileMat.pThreshold; + % Add it to study + sStudy.Stat(end+1) = sNewStat; + % Data + elseif isData + % Create new data descriptor + sNewData = db_getDataTemplate('Data'); + sNewData.FileName = FileName; + sNewData.Comment = FileMat.Comment; + % Add it to study + sStudy.Data(end+1) = sNewData; + % Results + else + % Create new results descriptor + sNewResult = db_getDataTemplate('Results'); + sNewResult.FileName = FileName; + sNewResult.Comment = FileMat.Comment; + sNewResult.DataFile = FileMat.DataFile; + % Add it to study + sStudy.Result(end+1) = sNewResult; + end + % Update database + bst_setContext('Study', iStudy, sStudy); +end + + +% ===== GET OUTPUT STUDY ===== +function [sOutputStudy, iOutputStudy, isNewConditions, Comment] = GetOutputStudy(sProcess,SamplesA,SamplesB,OPTIONS) + % Get some properties of the filter + isMixedSubjectsAB = isempty(SamplesB) || ~isequal({SamplesA.SubjectFile}, {SamplesB.SubjectFile}); + isSampleBySample = ismember(sProcess.Category, {'Filter2', 'Filter', 'Extract'}); + isConditionByCondition = strcmpi(sProcess.Name, 'GAVE'); + isNewConditions = 0; + % Get the list of involved studies + uniqueStudiesInd = unique([SamplesA.iStudy, SamplesB.iStudy]); +% Comment = OPTIONS.Comment; + Comment = ''; + + % ===== CHECK SUBJECT UNICITY ===== + % Get full subjects list without repetitions + uniqueSubjectFiles = unique(cat(2, {SamplesA.SubjectFile}, {SamplesB.SubjectFile})); + % For stat on sources: all the results files must be computed on the same surface. + % => else, the number of sources might be different between different files + % => user should realign surfaces before going on + if (length(uniqueSubjectFiles) > 1) + isUniqueSubject = 0; + if ~isSampleBySample && ~OPTIONS.isData + % If there is more than one subjects involved: need to check that all + % the subjects use the default anatomy + for i = 1:length(uniqueSubjectFiles) + sSubject = bst_getContext('Subject', uniqueSubjectFiles{i}); + if ~sSubject.UseDefaultAnat + gui_hidePanel('panel_statRun'); + sOutputStudy = []; + iOutputStudy = []; + bst_error(['The sources files you selected use different anatomies.' 10 ... + 'In order to perform any computation on sources, all the files' 10 ... + 'should use the same anatomy.' 10 10 ... + 'You have to project all your results on a template anatomy.' 10 ... + 'Popup menu: "Project sources on default anatomy".'], 'Processes', 0); + return; + end + end + end + else + isUniqueSubject = 1; + end + + % ===== GET OUTPUT STUDY ===== + % SUBJECT AVERAGE + if strcmpi(sProcess.Name, 'SubjAvg') + % Get subject + [sSubject, iSubject] = bst_getContext('Subject', SamplesA(1).SubjectFile); + % Get "intra" study for this subject + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisIntraStudy', iSubject); + % Comment + Comment = ['SubjectAvg(' SamplesA(1).SubjectName ')']; + % UNIQUE STUDY (OR OVERWRITE) + elseif (length(uniqueStudiesInd) == 1) || OPTIONS.isOverwriteFiles + % Get this unique study + [sOutputStudy, iOutputStudy] = bst_getContext('Study', uniqueStudiesInd(1)); + % MULTIPLE STUDIES : SAMPLE BY SAMPLE + elseif isSampleBySample && ~isMixedSubjectsAB + % Target study is a new condition (name = test comment) + % Get subject path + newCondPath = fileparts(SamplesA(1).SubjectFile); + % Get new condition name + localCond = struct('SamplesA',SamplesA,'SamplesB',SamplesB); + newCondName = panel_statRun('FormatComment', sProcess, localCond, OPTIONS.Time); + newCondName = io_standardizeFileName(newCondName); + % Comment + Comment = sProcess.FileTag; + Comment = strrep(Comment, '#A#', localCond.SamplesA(1).Comment); + Comment = strrep(Comment, '#B#', localCond.SamplesB(1).Comment); + % Try to get an existing condition with this path + [sOutputStudy, iOutputStudy] = bst_getContext('StudyWithCondition', fullfile(newCondPath,newCondName)); + % If does not exist: Create a new condition + if isempty(sOutputStudy) + iOutputStudy = db_addCondition(newCondPath, newCondName, 'NoRefresh'); + sOutputStudy = bst_getContext('Study', iOutputStudy); + isNewConditions = 1; + end + % MULTIPLE STUDIES : CONDITION BY CONDITION + elseif isConditionByCondition + Comment = ['GAVE(' SamplesA(1).Condition ')']; + % Grand average: stored in 'analysis-inter' node + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisInterStudy'); + % MULTIPLE STUDIES : GLOBAL + else + % UNIQUE SUBJECT : 'analysis-intra' + if isUniqueSubject + % Subject file is the same for all the studies => find common subject + [sSubject, iSubject] = bst_getContext('Subject', SamplesA(1).SubjectFile); + % Get 'analysis-intra' node of this subject + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisIntraStudy', iSubject); + % MULTIPLE SUBJECTS : 'analysis-inter' + else + % Get 'analysis-inter' node in current protocol + [sOutputStudy, iOutputStudy] = bst_getContext('AnalysisInterStudy'); + end + end + % Error ? + if isempty(sOutputStudy) + error('Cannot find an analysis study to store the results.'); + end + + % ===== COMBINE CHANNEL FILES ===== + % If source and target studies are not the same + if ~isequal(uniqueStudiesInd, iOutputStudy) + % Destination study for new channel file + [tmp__, iChanStudyDest] = bst_getContext('ChannelForStudy', iOutputStudy); + % Source channel files studies + [tmp__, iChanStudySrc] = bst_getContext('ChannelForStudy', uniqueStudiesInd); + % If target study has no channel file: create a new one by combination of the others + isNewChannelFile = db_combineChannelFiles(unique(iChanStudySrc), iChanStudyDest, [], ~OPTIONS.isData); + % Reload target study if it changed (new channel file) + if isNewChannelFile + sOutputStudy = bst_getContext('Study', iOutputStudy); + tree_updateModel(); + end + end +end + + +%% ===== BUILD DATA ARRAY ===== +function [X, ChannelFlag, Time] = buildDataArray(sampleFiles, iTime) + % Read out the data from multiple files and store in larger array X + % Parameters: + % - sampleFiles : cell array of data file names + % - Time : time values of the samples to extract + % - isData : a flag; 0 means read from Results file, 1 from surface data file + + % Open progress bar + isNewProgressBar = ~bst_progressBar('isvisible'); + if isNewProgressBar + bst_progressBar('start', 'Loading samples...', 'Processes', 0, length(sampleFiles)); + end + ChannelFlag = []; + + % Process all the samples files + for k = 1:length(sampleFiles) + % Progress bar + bst_progressBar('inc', 1); + bst_progressBar('text', ['File: ' sampleFiles{k}]); + % Read matrix + [matValues, matName, tmpChannelFlag, TimeVector] = bst_readMatrixInFile(sampleFiles{k}, iTime); + % Get time for the specified indices + % Bug: Time = TimeVector(iTime); + Time = TimeVector; + % Add bad channels to list of bad channels + if isempty(ChannelFlag) + ChannelFlag = tmpChannelFlag; + else + ChannelFlag(tmpChannelFlag == -1) = -1; + end + % Initialize large array + if (k == 1) + X = zeros(length(sampleFiles), size(matValues,1), size(matValues,2)); + end + + % Store read values in full data array + try + X(k,:,:) = matValues; + catch + error('Please first check that all the files in your samples have the same of channels/sources. Consider registering the MEG/EEG data to the same sensor cap'); + end + end + + if isNewProgressBar + bst_progressBar('stop'); + end +end diff --git a/brainstorm3/tvalue_paired.mexglx b/brainstorm3/tvalue_paired.mexglx new file mode 100755 index 0000000000000000000000000000000000000000..fab8b6d24a04523ff322b45fa02014ea40df97f9 GIT binary patch literal 7442 zcmb_h4{%&X8Q;5HA<)o27@)LO9!^G!=uKJzwEU5@={2?{CAPU1EpS|NuernIF5JDV zX{VtH*I>^_urm}vr#czYF{2%)4xOPYXhI6141*n}LV~>-omQ@<)~E=y7US=?e=gTj z)N%Z7zWesK`|Y>i?%QwQzTItsx)mOeM;Iy*C4y-0MM6|TcFk5LRl*X}!~*eAF;|uw zeaem*il-6G60%(8eGK_z7~BemNm=fN*oitjQAU;(bh!_(;kXm=q1^C%EZ^+E(~@l2JLc;!jFJS#@-zY z3QE@Brty6Ai)gxjj?#RHMYeTp;eng zYwVU-%CVC*t>IM4PKh?VV?{dN?8FjrrUS`jeX6Cg!x3#AD^tr8>84g2$y(c4EpuuT zZSAdg2UXXHlktKs6zZW+leEK*t*X_Bon)*dbaQ2;GSHBe7S^_hlPPU;RkJRx54W}^ znrXl!U~pwpmZly^!W+9|ot;e4%hp&^TZccDkO{kx3Ognb(ti_6Q%2tEn8;(4X!jT;7NTJGc;;kj z{yMmj-^age(AdEtG5IuCtI4O>2h!wIT)Co5o*0`1J;f19C3rhd{aalh^r-L z)#zQsl@i}Zd>^qTaW!$2c$UP=iQ9>V#55i4AfEW=^4ws#>!ss!0JaY}m%E+iZmo|w7s;G7D(ur0oZ<@4ybsHP{%lVN z8bz(lurJ$rlJ=I#>QA72Nub|B{lmI`73;(P#Wc_I?E~rAZt$e?;9;3T{cl}J{|&bH zVnO>Q!r>(^Qor<+>f~YM4KJ@K<+!?VZFz-n*jItT5cz{Ba)V`AZ=u6);o)TidkO~M zka+KKV1N}kR_TZvD9;R(W_z}>i|kn`J-;2cFjSwO%K5ysZpyz6OT&SE^a9o>#^<_^ zOB-^i+hj}obW89`^?#kr-tWo*9ULoRQ{R<&UFejLy;5Z?_@*q_p6TotGatPb9`~02 zoh@a92i(A(Y~XNj`TGjL8nbfVk>jHSBL|NT<%CYXaP;8O!OWm1 z^L!~?c{Tl;+>zXyqc7)r=<(4rTK;47;L+!G`t*p~fLU;K@JM=x8+gSHcA@P|;F!k^ z9Pk7VyTO+{!9(zkGje9nJ2St22`r7CIxz==&)O;f1znQk`Sl3K^F$y1+~D?X@Yzh~ zfN<_*QST;<_E%ZZxi9-%E9%NxZfF1CTP5TE99ru-QigW6AMs7(=1*WOJ*Srh`_soW zFM2XPtWdfn-9K|X`|tJ=%fTFfVQMbjd4}_HmyAO>-F_i6o^)#^8k1Jg>=`$(tG9f@^|+nS_WFji(v6(gRob0!c-WPB zM?`K8{T%dR;N9n>vB2&n&VJuE3}xQq2J`I8X`*l)+a zv*jXZc5YE%nVrTwWr?Db>bE8K(`{ax`gC;Nr57vx7J7r@819zT{Sp^&UM+zoJ zicO?{*?oY^-iCWa_Y7ej%yZw}Jy?b}q}$DP|DGYYOfQqg>-oC1`R6c--9x{}JGD16 z2F>1vvu^d-%zKm0%A!8bSK2OqXY4_>{4x0SMZ76iCmhR;C(0Qz)s{{#2)x-Fi%PSp*!ByF2U8{{6%N`<)z zO{v0YcoR%VZRXn6l!?|@94ZT9e%o&)no@RhQ<$6F)OB)UFO*XH{X3 zzsOotS-H6K=E^E-!5TYaeJ<>%{LfTXVa}YRy~w}l|B~|`TlJ?lw>jY^;ZHe9C8H)4 z4X2{QAK4s-ijq!J_*>#>|0eyRR189qbIL+cP1>!jt`hC7j_}9gG5k9=zW)69XpEsK z5eYkC;kToqjY-5;C>lXcgM`1?NhDKfU5WdfQOF9?b}}K|3b)0Y(RKnh@#mKfDWgp( zRBcYQagq7&XT?0I;&ID)%6U!h(-=a|cT6{NEtqqgbCUC&+yLergphii_goK{M?J;| znQ>vrBo`vX%xTVN@~4o;dL&BnXTc^G7#HNl$TMvKN~*^{V}*4XFXU>Z&)2&fd6$5x z$M_>N{)kC{G7fD>qsMq9cOj2@jCG?IN1A;?D9Ck!YXxK65cNngu+iHE9r7$Q7$~D2 znUBus@vKaqm(jQ;jxlKq*ywRxB6Hm|WZLaQ2K8kBxQKzd-Wf7_JCI@YiqFT+*ZW41 zo;5=V@?Ay=(%9?MdK`awRtG(~0S6`-y&oXWcB$8eb)@S<^nP5Vw*z`Rpl58LsE~fT zNRQv`k9>&U0Q5MlY*(HaLXVCRlW3d%9t0cz_`Saqhi-f)7@{8eRj|?Hy1yHGbw)|+ zQ16W*J+7U3=v`=Ba?oQw{h5H?1oT+nkV*d@8En@O^}c5Sq$%V3#`KNFyD*W)nb2hP zC`~M|s1z^RJ~YO;brYEFat<;!itY8!#k--XqOk|H4-nTFk~$GqYl*_j0M`tKRSR4j z6jlkY0SY6CK#X-#iF~3erWMAy2Z*stD$yg&7*&|PP_d{mBU{Cs!d&rGY$>dtJmUyd zB6kHC6V4rpRe~|0Fdhbo^Pg0rPaHYV73NdHTrObl2GE}Z=B_}WWkZ(eT@&XasYISe zt9^#Taz`ZJ$qK8Li1SBb?w+QoL|iTB2iF*q7c0E-NMRq&eEHms{~q|yHQM;^fi~A- z!uk-ZJTY@hSNBj(66R-T`cJXk3ofUH)J>4NQdqI|0!54Qg`V7cFr^=FGG zARRs49x+pVAGp|`p8)UGkB$8s1~$b0F&+&O9|Pd{bIN$ID?16vwUy*W31Y#>T(n8XJ2P8rN$5cY%w~_`O&QiqH6G=(WMvo2&61y8b6MHfQ|R8k;lzyU)`X z%{U@2I_4M6`0{en8#nr!ao%6kc;}i>-O9C%^7McCIcQZ)QBfojYH3Y0g8ZBleo?k{ z?x{PD{_PIEZ$&@M4whFJF%hb*yK~vny3m~~R;&#)h8mYHs|)aMBa%vlqTzT1Hx!`| zHk0bw1L@dJi*NF`*iNXuIpjps@h|(EJ4DEiNAM@No)=PSg39tQu3lQdvPOjDPFP-h z$Xg3}{c--?$^|Y{cx%9Wlfo^@)Ex?MF{-Q0l>)Cs{@tAijTB#$;BIB=0tCsaD;r+T bm}``CuWvr&F6P`jp(&Sm%K^(pw>tj(nv-1) + error(['In AIMS mesh format, vertices indices start at 0 in' ... + ' the ''Faces'' array']) + end + if (min(faces(:)) == 1 && max(faces(:)) == nv) + warning(['In AIMS mesh format, vertices indices start at 0 in' ... + ' the ''Faces'' array']) + end + + if nargin < 4 + nn=0; + % normals=normalsvertices(vertices, faces); + % nn=size(normals, 1); + else + nn=size(normals, 1); + end + + % By default, we are working in the AIMS referential, which is indirect. + if nargin<5 + indirect_referential = 1; + end + + if indirect_referential + faces=fliplr(faces); + end + + [ext,ext]=fileparts(filemesh); + + fid = fopen(filemesh ,'w') ; + + fprintf(fid, 'ascii\n'); + fprintf(fid, 'VOID\n'); + fprintf(fid, '%d\n',size(vertices,2)); + fprintf(fid, '%d\n',nt); + + for t=1:nt + % Instant in time (an integer !) + fprintf(fid, '%d\n',t-1); + + % VERTICES + fprintf(fid, '%d\n',nv); + for i = 1:nv + fprintf(fid, '(%1.4g,%1.4g,%1.4g)\n',vertices(i,1:3,t)); + end + + % NORMALS + fprintf(fid, '%d\n',nn); + for i = 1:nn + fprintf(fid, '(%1.4g,%1.4g,%1.4g)\n',normals(i,1:3,t)); + end + + % The following line HAS TO be here !!! + % There is no texture + fprintf(fid, '0\n\n'); + + % FACES + fprintf(fid, '%d\n',nf); + for i = 1:nf + fprintf(fid, '(%d,%d,%d)\n',faces(i,1:3,t)); + end + end + fclose(fid); + diff --git a/brodmann/MNITemplate_brodmann.m b/brodmann/MNITemplate_brodmann.m new file mode 100644 index 0000000..b36dd82 --- /dev/null +++ b/brodmann/MNITemplate_brodmann.m @@ -0,0 +1,195 @@ +mypath + +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'mtoolbox/spm2')) +addpath(fullfile(HOMEDIR, 'matlab/')) +addpath(fullfile(HOMEDIR, 'matlab/ctf2tal/')) +addpath(fullfile(HOMEDIR, 'matlab/stormvisa')) +addpath(fullfile(HOMEDIR, 'matlab/brodmann')) +try + addpath(fullfile(USBDIR, 'matlab/')) + addpath(fullfile(USBDIR, 'matlab/ctf2tal/')) + addpath(fullfile(USBDIR, 'matlab/stormvisa')) + addpath(fullfile(USBDIR, 'matlab/brodmann')) +end + +load(fullfile(HOMEDIR, 'mtoolbox/brainstorm/MNITemplate/MNI_braincereb_small_tess_CTF')) +fv.vertices=Vertices{end}'; +try + fv.vertconn=VertConn{end}; +catch +end +clear Vertices; +fv.faces=Faces{end}; +clear Faces; +clear VertConn +clear tess2mri_interp +% try +% load(fullfile(USBDIR, 'data/subjects/montreal_subject/TalairachMRIscs.mat'), 'TAL') +% S(1)=load(fullfile(HOMEDIR, 'data/subjects/montreal_subject/montreal_subjectimage.mat'), 'SCS') +% S(2).SCS=S(1).SCS(1); +% S(3)=load(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Phantom/montreal_subject/montreal_subjectimage_info.mat'), 'SCS') +% S(4).SCS=S(3).SCS(1); +% +% catch +% end + +S=load(fullfile(HOMEDIR, 'mtoolbox/brainstorm/MNITemplate/MNI_subjectimage'), 'talCS', 'SCS') + + +if not(exist('xyz2')) + DECIMATION=1000 + y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + %y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','brodmann.img')) + v=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + ref=v(v>0); + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + % in MRI + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(v), find(v>0)); + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); + + fv2.vertices=fv.vertices; + + % I dunno why but brodmann from MRIcro is not centered?!? + % xyz2=xyz2-repmat([-3 10 -10], [size(xyz2,1) 1]); + fv2.vertices=fv2.vertices+repmat([0 10 -8],size(fv2.vertices,1),1); +end +plot3d([xyz2]/1000) + +% fv2.vertices=scs2mri(S(2),fv.vertices'*1000)'-repmat([92 128 74],[10001,1]); +fv2.faces=fv.faces; + +% fv2.vertices=scs2mri(S(end),fv.vertices'*1000); +% [ignore,fv2.vertices]=mri2scs(TAL,fv2.vertices); + +% Apply Talairach nomalization to vertex locations +%1)Load Talairach fiducials and bounding box from MRI file +% 2) Apply global Talairach transform +[fv2.vertices] = scs2tal(S.talCS.scsCubeFiducial/1000, S.talCS.cortexTess,fv.vertices', S.talCS.Type); + +fv2.vertices=fv2.vertices'*1000; +v2=fv2.vertices; + +figure(1) +clf +view_cortex(fv2.faces,v2,'FaceColor','none', 'EdgeColor', 'k' , 'FaceAlpha', .5) +hold on +view_cortex(fv2.faces,mni2tal(v2), 'FaceColor','none', 'EdgeColor', 'g') +legend({'orig','tal', 'mni2tal'},0) + +view(90,0) +rotate3d +drawnow + + +return + +disp('Lecture des fichiers Analyze') +apc=[0 0 0; 0 -23 0; 0 0 50]; +verttal = ctf2tal(v2, [], 'ACPCIH_ctf', [apc], 'brainvert', v2); +view_cortex(fv2.faces,verttal, 'FaceColor','none', 'EdgeColor', 'r') + +% Same story for new (target)tessellation +load(newTess,'Faces','Vertices') +newFaces = Faces{iGrid}; +newVertices = Vertices{iGrid}; + +MRI = load(newMRI,'talCS'); +[newVertices] = scs2tal(MRI.talCS.scsCubeFiducial/1000, MRI.talCS.cortexTess,newVertices, MRI.talCS.Type); + +return + + + + +% r=labelize(v2, xyz2, ref2, 'TimeBar', 'on'); + +return +labelviewer(struct('vertices', v2, 'faces', fv.faces), r, xyz2, ref2, labels) + + +r=ref2(closest(v2,xyz2)); + +if 0 + load(fullfile(HOMEDIR, 'matlab/ctf2tal/TTareas.mat')); + xyz=xyz(1:10:end,:); + ref=ref(1:10:end); + ref=double(ref); + xyz=ctf2tal(xyz, [], 'brainvert', xyz, 'CA', [0 0 0], 'CP', [0 -23 0], 'IH' ,[0 0 50]); + r=labelize(verttal, xyz2, ref, 'TimeBar', 'on'); + talairach.vertices=verttal; + talairach.faces=fv.faces; +end + +return + +save(fullfile(SCOUTDIR,date,[date '_brodmann.mat']), 'r','talairach', 'xyz', 'ref', 'labels' ) + +disp('Sauvegarde dans un fichier CorticalScout') + +scoutfile=dir(fullfile(RESDIR,date, [date '*CorticalScout_2.mat'])); +scouts=load(fullfile(RESDIR,date, scoutfile.name)); + +BA=strmatch('Brodmann', labels); + +SIDES=['R', 'L']; +for side=0:1 +for i=1:length(BA) + vba=find(r==BA(i) & left==side); + scouts.CorticalScouts.CorticalMarkersLabels{i+42*side}=[labels{BA(i)} '-' SIDES(side+1)]; + if not(isempty(vba)) + scouts.CorticalScouts.CorticalSpots(i+42*side)=vba(1); + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = v_ctf(vba(1),:); +else + scouts.CorticalScouts.CorticalSpots(i+42*side)=NaN; + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = NaN; +end + scouts.CorticalScouts.CorticalProbePatches{i+42*side}=vba; + scouts.CorticalScouts.CorticalProbeDepth(i+42*side)=0; + scouts.CorticalScouts.CorticalProbePatchesXYZ{i+42*side}=v_ctf(scouts.CorticalScouts.CorticalProbePatches{i},:)'; +end +end +bascoutfile=strrep(scoutfile.name, '_2.mat', '_BA.mat') + CorticalScouts=scouts.CorticalScouts; + ResultFile=scouts.ResultFile; + ActiveTess=scouts.ActiveTess; + save(fullfile(SCOUTDIR,date,bascoutfile), 'ResultFile','ActiveTess','CorticalScouts') + +return + + + +cmap=hsv(69); +hf=figure; +p=patch('vertices', fv.vertices, 'faces',fv.faces, ... + 'CData', r, 'CDataMapping', 'direct', ... + 'EdgeColor', 'none', 'FaceColor', 'flat'); +colormap(cmap) +h=colorbar; +axis image +light('position' , [-1 1 0]) +light('position' , [ 0 0 1]) +light('position' , [ 1 -1 -1]) +light('position' , [ 1 1 0]) +l=findobj(hf, 'type', 'light'); +set(l, 'color', .8*ones(1,3)) +set(h, 'YDir', 'reverse'); +set(h, 'position', [0.8314 0.1100 0.02 0.8150]) +view(3) +rotate3d +lighting gouraud + +return diff --git a/brodmann/MNI_brodmann.m b/brodmann/MNI_brodmann.m new file mode 100644 index 0000000..9c35a30 --- /dev/null +++ b/brodmann/MNI_brodmann.m @@ -0,0 +1,80 @@ +mypath +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'mtoolbox/spm2')) +addpath((MATLABDIR)) +addpath(fullfile(MATLABDIR, 'ctf2tal')) +addpath(fullfile(MATLABDIR, 'stormvisa')) +addpath(fullfile(MATLABDIR, 'brodmann')) + + +try + load(fullfile(USBDIR, 'data/subjects/montreal_subject/TalairachMRIscs.mat'), 'TAL') + S(1)=load(fullfile(HOMEDIR, 'data/subjects/montreal_subject/montreal_subjectimage.mat'), 'SCS') + S(2).SCS=S(1).SCS(1); + S(3)=load(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Phantom/montreal_subject/montreal_subjectimage_info.mat'), 'SCS') + S(4).SCS=S(3).SCS(1); +catch +end + + +if not(exist('xyz2')) + DECIMATION=1000 +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','brodmann.img')) + vol=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + ref=vol(vol>0); + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + % in MRI + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); + + % I dunno why but brodmann from MRIcro is not centered?!? + % xyz2=xyz2-repmat([-3 10 -10], [size(xyz2,1) 1]); + v2=fv2.vertices+repmat([0 10 -8],10001,1); + +end + +% +% tessfile='d:\ndiaye\data\subjects\MNI\MNI_LhemiMNI_Rhemi_10000V_tess.mat' +% fv=tess2patch(tessfile); +% % in mm: +% fv.vertices=fv.vertices*1000; +% % Re-center +% % Z-flip: +% fv.vertices(:,3)=-fv.vertices(:,3); +% % Y (antero-post) flip +% fv.vertices(:,2)=-fv.vertices(:,2); +% fv.vertices=fv.vertices+repmat(y.mat(1:3,4)', [size(fv.vertices,1),1]); +% delete(findTessellationHandles);view_cortex(fv);pause + +s=load('MNI_subjectimage.mat', 'talCS', 'SCS') +tessfile='MNI_braincereb_small_tess_CTF.mat' +fv=tess2patch(tessfile); +v=scs2tal(s.talCS.scsCubeFiducial/1000, s.talCS.cortexTess, fv.vertices', 'mnicereb'); +view_cortex(fv.faces, v*1000) + +return + +fv2.faces=fv.faces; +% fv2.vertconn=fv.vertconn; +fv2.vertices=scs2mri(S(end),fv.vertices'*1000); +[ignore,fv2.vertices]=mri2scs(TAL,fv2.vertices); +fv2.vertices=fv2.vertices'; +v2=fv2.vertices; + +disp('Lecture des fichiers Analyze') +apc=[0 0 0; 0 -23 0; 0 0 50]; +verttal = ctf2tal(v2, [], 'ACPCIH_ctf', [apc], 'brainvert', v2); diff --git a/brodmann/MNI_brodmann_karimovitch.m b/brodmann/MNI_brodmann_karimovitch.m new file mode 100644 index 0000000..a3cb29a --- /dev/null +++ b/brodmann/MNI_brodmann_karimovitch.m @@ -0,0 +1,170 @@ +% Transpose, Flip, etc so that Left is on Left +% and all the rest is okay +% TessFile='D:\ndiaye\data\subjects\MNI_4_Yann\MNI_brain_NoCollosum_12000V_tess.mat'; +% fv=tess2patch(TessFile); +% v=(fv.vertices*diag([1 -1 -1])+repmat([-90e-3 217e-3-126e-3 181e-3-72e-3], size(fv.vertices,1),1))*diag([-1 1 1])*1000; +% view_cortex(fv.faces, v) +% image_spm(y,vol); view(2); hold on +% h=findTessellationHandles +% set(h, 'visible', 'off') + + +clear +spm_defaults + +switch(1) + case 1 + TessFile='D:\ndiaye\data\subjects\MNI_4_Yann\MNI_brain_NoCollosum_12000V_tess_corrected.mat'; + fv=tess2patch(TessFile); + % Note that the right hemi at the occipital pole viewed from above goes towards the left + case 2 + % TessFile='D:\ndiaye\data\subjects\MNI_4_Yann\MNI_brain_tess.mat'; + + fv=tess2patch(TessFile); + % In MNI coordinates: + fv.vertices=(fv.vertices*diag([1 -1 -1])+repmat([-90e-3 217e-3-126e-3 181e-3-72e-3], size(fv.vertices,1),1))*diag([-1 1 1])*1000; + case 3 + TessFile=uigetpathfile + fv=tess2patch(TessFile); + % In MNI coordinates: + fv.vertices=(fv.vertices*diag([1 -1 -1])+repmat([-90e-3 217e-3-126e-3 181e-3-72e-3], size(fv.vertices,1),1))*diag([-1 1 1])*1000; +end + +AtlasMRI='d:/ndiaye/data/subjects/colin27/brodmann.img'; +%AtlasMRI='d:/ndiaye/data/subjects/colin27/aal.img'; +ColinMRI='d:/ndiaye/data/subjects/colin27/colin.img'; + +% Note: the right occipital pole of the single subject MNI (colin27) goes a +% little on the left side +if not(exist('xyz')) +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol(AtlasMRI) + vol=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + + ref=vol(vol>0); + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); + % MRI to MNI coord. + xyz=[xyz ones(size(xyz,1),1)]; + xyz=xyz*y.mat'; + xyz=xyz(:,1:3); + + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + + % Import + yc=spm_vol(ColinMRI); + if spm_flip_analyze_images + yc.mat(1,:)=-yc.mat(1,:); + end + volc=spm_read_vols(yc); + +end + +if 0 + if not(exist('xyz2')) + DECIMATION=1; + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + end +end + + +figure(1); +clf +z=40; dz=2; +k=fv.vertices(:,3)z-dz; +p=plot3d(fv.vertices(k,:) ,'.'); +view(2);hold on; +% set(hp, 'FaceAlpha', 'interp');set(hp, 'FaceVertexAlphaData', k+(1-k)*0); +n=100; +colormap([ subarray(colorcube(n), randperm(n)) ; gray(100)]); +colorbar +hc=img_slice(yc,volc./max(volc(:))*100+n+1, [NaN NaN z]); +set(hc, 'CDataMapping', 'direct', 'FaceAlpha', 1) +hi=img_slice(y,[], [NaN NaN z]); +set(hi, 'CDataMapping', 'direct', 'AlphaData', logical(get(hi, 'CData'))*.51) + +return + +if 0 + % Make AAL for all vertices + fv.r=ref(nearest(fv.vertices, xyz)); +elseif BRODMANN + % Brodmann only for cerebral matter + r=zeros(size(fv.vertices,1), 1) + k=load(TessFile, 'Lhemi', 'Rhemi', 'Cerebellum') + r([ k.Rhemi ; k.Lhemi])=ref(nearest(fv.vertices([ k.Rhemi ; k.Lhemi]), xyz)); +end + + + +return + +% ========================================================================= +% ========================================================================= +% ========================================================================= + +mypath +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'mtoolbox/spm2')) +addpath((MATLABDIR)) +addpath(fullfile(MATLABDIR, 'ctf2tal')) +addpath(fullfile(MATLABDIR, 'stormvisa')) +addpath(fullfile(MATLABDIR, 'brodmann')) + +AtlasMRI='d:/ndiaye/data/subjects/colin27/brodmann.img'; +AtlasMRI='d:/ndiaye/data/subjects/colin27/aal.img'; + +MNISubjectImage=fullfile(USBDIR,'/mtoolbox/brainstorm/MNItemplate','MNI_subjectimage.mat') +tessfile=fullfile(USBDIR,'/mtoolbox/brainstorm/MNItemplate','MNI_braincereb_small_tess_CTF.mat') + +% Note: the right occipital pole of the single subject MNI (colin27) goes a +% little on the left side +if not(exist('xyz')) +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol(AtlasMRI) + vol=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + ref=vol(vol>0); + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + % in MRI + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); +end +if not(exist('xyz2')) + DECIMATION=1; + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); +end + +return + +s=load(MNISubjectImage, 'talCS', 'SCS') +fv=tess2patch(tessfile); + +v=scs2tal(s.talCS.scsCubeFiducial/1000, s.talCS.cortexTess, fv.vertices', 'mnicereb'); + +return + +view_cortex(fv.faces, v*1000) +r=ref2(closest(v'*1000, xyz2)); % labelize(v'*1000, xyz2,ref2, 'Timebar', 'on') +labelviewer(fv, r, xyz2, ref2, labels) + diff --git a/brodmann/MNI_karimovitch.m b/brodmann/MNI_karimovitch.m new file mode 100644 index 0000000..8208687 --- /dev/null +++ b/brodmann/MNI_karimovitch.m @@ -0,0 +1,42 @@ + +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'mtoolbox/spm2')) +addpath((MATLABDIR)) +addpath(fullfile(MATLABDIR, 'ctf2tal')) +addpath(fullfile(MATLABDIR, 'stormvisa')) +addpath(fullfile(MATLABDIR, 'brodmann')) + +if not(exist('xyz2')) + DECIMATION=1000 +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol('brodmann.img') + vol=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + ref=vol(vol>0); + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + % in MRI + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); +end + + +s=load('MNI_subjectimage.mat', 'talCS', 'SCS') +tessfile='MNI_braincereb_small_tess_CTF.mat' +fv=tess2patch(tessfile); +v=scs2tal(s.talCS.scsCubeFiducial/1000, s.talCS.cortexTess, fv.vertices', 'mnicereb'); +view_cortex(fv.faces, v*1000) +r=labelize(v'*1000, xyz2,ref2, 'Timebar', 'on') +labelviewer(fv, r, xyz2, ref2, labels) + diff --git a/brodmann/TTareas2TTgyri.m b/brodmann/TTareas2TTgyri.m new file mode 100644 index 0000000..cd12985 --- /dev/null +++ b/brodmann/TTareas2TTgyri.m @@ -0,0 +1,4 @@ +function []=f(tta,ttg) +% index of ttareas into ttgyri +[tf,loc]=ismember(tta,ttg,'rows'); 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z<)@;=d{3T-?Q^l!Ug9zcWj;)e>;l!2nh9$N)3<*zaGWoIE8#Vst?btIzz;Hgk{n-W-Q61 z1?wTzs-WM7BDDFwO!92-Z;Pa6V-`hnfju1)w!^<^I%aF=FCH_^8+aGzM>Wh?w&~cN z`IwZLq>Y+ku4gNP38`$)$Mmep!LyS@uQ}+G8Ot89pUK!Y84ECF1zKnzt`-{3A=eW$ zrb-oe>zSaN6cpP7>VX9=inh5%Et;k9R96o6%k@K_8=a2~as^O4G* zKGib#Vg3<6a&kut`58n`liyL(~{-8T+xbh++hMPRf{QIP55-oRH}k+*D%{ z)2~}pqW*y?WF)Bn3}3K&51$^(2Dr|@2FUL|rG%&}p83}S6jiS0X`Yl_`nqRh#*AQu$&IT=hHY@3s9U_a$D zI7}YqWc+*YfiOJ!4~|D^Dh-K=U+~ECNnY5UDi3-n5H4^M_p>j zUFv@*>ugTO%mm5I$rMqu7*TDRlPM2`qeR9OEFzydCzHA^m&~z7D>l%r>LMgqb2Ohu zk|-+--!)lMvgTyu0))); + nlu=length(lu); + colors=hsv(nlu); + hp{i+1}=zeros(nlu,3); + areas{i+1}=zeros(nlu,1); + axes(ax(1).h) + + if any(l==0) + colors=hsv(nlu+1); + hp{i+1}=zeros(nlu+1,3); + hp{i+1}(nlu+1)=plot3d(atlas1.xyz(v(l==0),:), '.', 'Marker', '.', 'MarkerSize', 1, 'Color', colors(nlu+1,:)); + areas{i+1}=zeros(nlu,1); + areas{i+1}(nlu+1)=nl2+1; + end + for j=1:nlu + hp{i+1}(j)=plot3d(atlas1.xyz(v(atlas2.ref(l(l>0))==lu(j)),:), '.', 'Marker', '.', 'MarkerSize', 1, 'Color', colors(j,:)); + areas{i+1}(j)=lu(j); + end + + hp{i+1}(:,2)=copyobj(hp{i+1}(:,1),ax(2).h); + hp{i+1}(:,3)=copyobj(hp{i+1}(:,1),ax(3).h); + end + + % timebar(hbar,(i)/(nl)) + fprintf(sprintf('\b\b\b\b\b%02d/%02d', i,nl)) +end +disp('... done') +if 0 + v=find(not(ismember(ref,0:nl))); + if ~isempty(v) + hp(end+1,3)=plot3d(xyz(v,:), '.', 'Marker', '.', 'MarkerSize', 1); + else + hp(end+1,3)=plot3d([0 0 0], '.', 'Marker', '.', 'MarkerSize', 1); + set(hp(end,3), 'Visible', 'Off'); + end +end +% close(hbar); + +for j=1:3 + axes(ax(j).h) + axis image +end + +u.labels2=[ atlas2.labels(:) ; {'Not in Atlas2'}]; +u.areas=areas; + +u.hp=hp; +set(gcf, 'UserData', u); + +callback=[ 'u=get(gcbf, ''UserData'');' ... + 'set(cat(1,u.hp{:}), ''MarkerSize'', 1, ''Color'', ''k'');' ... + 'u.iref=get(gcbo,''value'');'... + 'set([u.hp{u.iref}(:)], ''MarkerSize'', 5);' ... + 'u.colors=hsv(size(u.hp{u.iref},1));'... + 'for i=1:size(u.hp{u.iref},1);'... + 'set(u.hp{u.iref}(i,:), ''Color'', u.colors(i,:));'... + 'end;'... + 'u.hleg=legend(u.hp{u.iref}(:,3), strrep(u.labels2(u.areas{u.iref}), ''_'', ''\_''),0);'... + 'set(u.hleg, ''Position'', get(u.hleg, ''Position'').*[0 0 1 1] + [ .4 .45 0 0]);'... + 'clear u;']; + +hui=uicontrol('Style', 'listbox', 'Tag', 'Labels', ... + 'String', [ {'Not Labeled'} ; atlas1.labels ; {'Missing labels'}], ... + 'callback', callback); +set(hui, 'units', 'normalized') +set(hui, 'Max', 2, 'Min', 0) +set(hui, 'position', get(ax(4).h, 'Position')); + +axes(ax(4).h) +set(ax(4).h, 'Units', 'centimeters') +ht=title(sprintf('%d labeled regions', nl)); +set(ht, 'Units', 'centimeters') +p=get(ht, 'Extent')+get(ax(4).h, 'Position').*[ 1 1 0 0] +htui=uicontrol('Style', 'text', 'Units', 'centimeters', 'position', p, 'String', get(ht, 'String')); +set(htui, 'units', 'normalized') +delete(ax(4).h) diff --git a/brodmann/atlasviewer.m b/brodmann/atlasviewer.m new file mode 100644 index 0000000..7c14460 --- /dev/null +++ b/brodmann/atlasviewer.m @@ -0,0 +1,97 @@ +function [h] = atlasviewer(xyz, ref, labels) +% ATLASVIEWER - Display labelled regions in 3 plans for a brain atlas +% [] = atlasviewer(AtlasXYZ, AtlasREF, AtlasLabels) +% +% - TemplateXYZ: [Na x 3] Atlas Coordinates of the Na vertices +% - TemplateREF: [Na x 1] Atlas Label ID +% - Labels: Cell of strings +% + + +figure +clf + +ax(1).h=subplot(2,2,1); +ax(1).name='coronal'; +view(0,0); % Left on left +hold on + + +ax(2).h=subplot(2,2,2); +ax(2).name='sagittal'; +view(-90,0); % anterior on left +hold on + +ax(3).h=subplot(2,2,3); +ax(3).name='axial'; +view(0,90); % anterior on top +hold on + + +ax(4).h=subplot(2,2,4); + +set([ax(:).h], 'units', 'normalized'); + +nl=length(labels); +hbar = timebar('Labeling clusters','Progress') + +v=find(ref==0); +axes(ax(3).h) +if ~isempty(v) + hp(1,3)=plot3d(xyz(v,:), '.', 'Marker', '.', 'MarkerSize', 1); +else + hp(1,3)=plot3d([0 0 0], '.', 'Marker', '.', 'MarkerSize', 1); + set(hp(1,3), 'Visible', 'Off'); +end +for i=2:nl+1 + v=find(ref==i-1); + if ~isempty(v) + axes(ax(3).h) + hp(i,3)=plot3d(xyz(v,:), '.', 'Marker', '.', 'MarkerSize', 1); + end + timebar(hbar,(i)/(nl)) +end +v=find(not(ismember(ref,0:nl))); +axes(ax(3).h) +if ~isempty(v) + hp(end+1,3)=plot3d(xyz(v,:), '.', 'Marker', '.', 'MarkerSize', 1); +else + hp(end+1,3)=plot3d([0 0 0], '.', 'Marker', '.', 'MarkerSize', 1); + set(hp(end,3), 'Visible', 'Off'); +end +close(hbar); +hp(hp(:,3)>0,1)=copyobj(hp(hp(:,3)>0,3),ax(1).h); +hp(hp(:,3)>0,2)=copyobj(hp(hp(:,3)>0,3),ax(2).h); +for j=1:3 + axes(ax(j).h) + axis image +end + +u.hp=hp; +set(gcf, 'UserData', u); + +callback=[ 'u=get(gcbf, ''UserData'');'... + 'set([u.hp(u.hp>0)], ''MarkerSize'', 1, ''Color'', ''b'');' ... + 'set([u.hp(get(gcbo,''value''),:)],''MarkerSize'',5, ''Color'', ''r''); ' ... + 'clear u;']; + +hui=uicontrol('Style', 'listbox', 'Tag', 'Labels', ... + 'String', [ {'Not Labeled'} ; labels ; {'Missing labels'}], ... + 'callback', callback); +set(hui, 'units', 'normalized') +set(hui, 'Max', 2, 'Min', 0) +set(hui, 'position', get(ax(4).h, 'Position')); + +axes(ax(4).h) +set(ax(4).h, 'Units', 'centimeters') +ht=title(sprintf('%d labeled regions', nl)); +set(ht, 'Units', 'centimeters') +p=get(ht, 'Extent')+get(ax(4).h, 'Position').*[ 1 1 0 0] +htui=uicontrol('Style', 'text', 'Units', 'centimeters', 'position', p, 'String', get(ht, 'String')); +set(htui, 'units', 'normalized') +delete(ax(4).h) + + + + + diff --git a/brodmann/ba_color.m b/brodmann/ba_color.m new file mode 100644 index 0000000..e7ced9e --- /dev/null +++ b/brodmann/ba_color.m @@ -0,0 +1,102 @@ +if 0 + a=readAPCmm('../../brainvisa/div/div11/anatomy/div11.APC') + [m,m2]=readMRItoCTF([ '../../brainvisa/div/div11/tri/'... + 'div11_MD_CTF.txt']) + [fv.vertices, fv.faces]=readmeshes({'../../brainvisa/div/div11/tri/div11_Lhemi.mesh' '../../brainvisa/div/div11/tri/div11_Rhemi.mesh'}); + fv.faces=fv.faces+1; + fv=reducepatch(fv,50000); + faces=fv.faces; + v_ctf=[fv.vertices ones(size(fv.vertices,1),1)]*m2; + apc=[a ones(3,1)]*m2; + vertices = ctf2tal(v_ctf, [], 'ACPCIH_ctf', apc, 'brainvert', v_ctf); + save ../../data/s11cortex_tal.mat faces vertices + + load ../../data/talairach/TTareas.mat + cmap= hsv(66); %[repmat(.6, 3,3) ; hsv(47-3) ; repmat(.6,69-47,3)]; + kcmap=0.3; + +xyz=xyz(1:10:end,:); +ref=ref(1:10:end); +ref=double(ref); + +% Bizarrely, this vertices are not exactly shaped to the talairach +% box... We deform them slightly +xyz=ctf2tal(xyz, [], 'brainvert', xyz, 'CA', [0 0 0], 'CP', [0 -23 0], 'IH' ,[0 0 50]); + +r=zeros(length(vertices),1)*NaN; +k=r; + +end + +figure +p=patch('vertices', vertices, 'faces',faces, ... + 'CData', r, 'CDataMapping', 'direct', ... + 'EdgeColor', 'none', 'FaceColor', 'flat'); +axis image +set(p, 'SpecularExponent', 2) +set(p, 'SpecularStrength', .3) + + +light('position' , [-1 1 0]) +light('position' , [ 0 0 1]) +light('position' , [ 1 -1 -1]) +light('position' , [ 1 1 0]) +l=findobj(gcf, 'type', 'light'); +set(l, 'color', .8*ones(1,3)) + +lighting gouraud +colormap(cmap) +h=colorbar +set(h, 'YDir', 'reverse'); +set(h, 'position', [0.8314 0.1100 0.02 0.8150]) +view(3) +rotate3d + +if all(isnan(r)) %not(exist('k')) & not(exist('r')) + r=labelize(vertices, xyz, ref, 'TimeBar', 'on'); + +% $$$ h=timebar('Labelling vertices...', 'TTGyri'); +% $$$ for i=1:length(vertices) +% $$$ d=sqrt(sum(power(xyz-repmat(vertices(i,:),size(xyz,1),1),2),2)); +% $$$ +% $$$ % local "smoothing" +% $$$ % r(i)=imax(hist(ref(d<5e-3), .5:length(labels))); +% $$$ +% $$$ k(i)=imax(-d); +% $$$ r(i)=ref(k(i)); +% $$$ timebar(h, i/length(vertices),1); +% $$$ %set(p, 'FaceVertexCData',r); drawnow; +% $$$ end +% $$$ close(h) +end + + +% jj=hsv;jj=jj(randperm(64),:);colormap(jj) + +hold on +for i=1:length(labels) + pp(i)=plot3d(xyz(ref==i,:),'w.', 'markerSize', 2); +end +set(pp, 'visible', 'off'); + +if not(exist('cmap')) + cmap=hsv(69); +end + + +hui=findobj(gcf,'Tag', 'Labels') +if isempty(hui) + callback=['set(pp, ''visible'', ''off'');' ... + 'i=get(hui,''value'');set(pp(i),''visible'',''on''); ' ... + 'c=cmap*kcmap; c(i,:)=cmap(i,:); colormap([c]);' ... + 'roi=find(r==i);']; + hui=uicontrol('Style', 'listbox', 'Tag', 'Labels', ... + 'callback', callback); + eval(callback); + set(hui, 'units', 'normalized') + set(hui, 'Max', 2, 'Min', 0) + set(hui, 'position', [0.8414 0.1100 .15 .8150]) + set(hui, 'String', labels) +end +rotate3d + diff --git a/brodmann/brodmann.m b/brodmann/brodmann.m new file mode 100644 index 0000000..6e7944f --- /dev/null +++ b/brodmann/brodmann.m @@ -0,0 +1,122 @@ +mypath + +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'matlab/')) +addpath(fullfile(HOMEDIR, 'matlab/ctf2tal/')) +addpath(fullfile(HOMEDIR, 'matlab/stormvisa')) +addpath(fullfile(HOMEDIR, 'matlab/brodmann')) + +IRMDIR='/pclxserver2/home/datalinks/DAV/brainvisa/div' +TESSDIR='/pclxserver2/home/datalinks/DAV/brainvisa/div' +SCOUTDIR=fullfile(HOMEDIR, 'tmp') + +sujet='div07' +segdir='tri' +date=sujet +RESDIR=SCOUTDIR; + + +IRMdim=readdim(fullfile(IRMDIR,sujet,'anatomy', [sujet '.dim'])); +a=readAPCmm(fullfile(IRMDIR,sujet,'anatomy', [sujet '.APC']), IRMdim.voxelsize(1:3)) +tessfile=dir(fullfile(TESSDIR,sujet, segdir, [sujet '*_tess.mat'])); +tess=load(fullfile(TESSDIR,sujet, segdir, tessfile.name)); +fv.vertices=tess.Vertices{end}'; +fv.faces=tess.Faces{end}; +v1=readtri(fullfile(TESSDIR,sujet, segdir, [sujet '_Lhemi.tri'])); +v2=readtri(fullfile(TESSDIR,sujet, segdir, [sujet '_Lhemi-CTF.tri'])); +v2=v2/1000; + +if not(exist('left')) +% look for Left sided vertices +left=zeros(size(fv.vertices,1),1); +nverts=size(fv.vertices,1); +h=timebar('Finding side of scouts', 'Left or Right?') +for i=1:nverts +timebar(h, i/nverts) +d=sum((repmat(fv.vertices(i,:), size(v2,1),1)-v2).^2,2); + x=find(d==0); +if not(isempty(x)) + left(i)=1; +end +end +close(h) +end + +disp('Calcul des régions de Brodmann dans Talairach') + +m2=[v1 ones(size(v1,1),1)]\v2; + +%id est: +% v_ctf=[fv.vertices ones(size(fv.vertices,1),1)]*m2; + +v_ctf=fv.vertices; +apc=[a*1000 ones(3,1)]*m2; +verttal = ctf2tal(v_ctf, [], 'ACPCIH_ctf', apc, 'brainvert', v_ctf); +load(fullfile(HOMEDIR, 'matlab/ctf2tal/TTareas.mat')); +xyz=xyz(1:10:end,:); +ref=ref(1:10:end); +ref=double(ref); +xyz=ctf2tal(xyz, [], 'brainvert', xyz, 'CA', [0 0 0], 'CP', [0 -23 0], 'IH' ,[0 0 50]); +r=labelize(verttal, xyz, ref, 'TimeBar', 'on'); + +talairach.vertices=verttal; +talairch.faces=fv.faces; + +save(fullfile(SCOUTDIR,date,[date '_brodmann.mat']), 'r','talairach', 'xyz', 'ref', 'labels' ) + +disp('Sauvegarde dans un fichier CorticalScout') + +scoutfile=dir(fullfile(RESDIR,date, [date '*CorticalScout_2.mat'])); +scouts=load(fullfile(RESDIR,date, scoutfile.name)); + +BA=strmatch('Brodmann', labels); + +SIDES=['R', 'L']; +for side=0:1 +for i=1:length(BA) + vba=find(r==BA(i) & left==side); + scouts.CorticalScouts.CorticalMarkersLabels{i+42*side}=[labels{BA(i)} '-' SIDES(side+1)]; + if not(isempty(vba)) + scouts.CorticalScouts.CorticalSpots(i+42*side)=vba(1); + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = v_ctf(vba(1),:); +else + scouts.CorticalScouts.CorticalSpots(i+42*side)=NaN; + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = NaN; +end + scouts.CorticalScouts.CorticalProbePatches{i+42*side}=vba; + scouts.CorticalScouts.CorticalProbeDepth(i+42*side)=0; + scouts.CorticalScouts.CorticalProbePatchesXYZ{i+42*side}=v_ctf(scouts.CorticalScouts.CorticalProbePatches{i},:)'; +end +end +bascoutfile=strrep(scoutfile.name, '_2.mat', '_BA.mat') + CorticalScouts=scouts.CorticalScouts; + ResultFile=scouts.ResultFile; + ActiveTess=scouts.ActiveTess; + save(fullfile(SCOUTDIR,date,bascoutfile), 'ResultFile','ActiveTess','CorticalScouts') + + labelviewer(struct('vertices', verttal, 'faces', fv.faces), r, xyz, ref, labels) +return + + + +cmap=hsv(69); +hf=figure; +p=patch('vertices', fv.vertices, 'faces',fv.faces, ... + 'CData', r, 'CDataMapping', 'direct', ... + 'EdgeColor', 'none', 'FaceColor', 'flat'); +colormap(cmap) +h=colorbar; +axis image +light('position' , [-1 1 0]) +light('position' , [ 0 0 1]) +light('position' , [ 1 -1 -1]) +light('position' , [ 1 1 0]) +l=findobj(hf, 'type', 'light'); +set(l, 'color', .8*ones(1,3)) +set(h, 'YDir', 'reverse'); +set(h, 'position', [0.8314 0.1100 0.02 0.8150]) +view(3) +rotate3d +lighting gouraud + +return diff --git a/brodmann/correct_flip_tess.m b/brodmann/correct_flip_tess.m new file mode 100644 index 0000000..58c0c77 --- /dev/null +++ b/brodmann/correct_flip_tess.m @@ -0,0 +1,47 @@ +% Transpose, Flip, etc so that Left is on Left +% and all the rest is okay +% TessFile='D:\ndiaye\data\subjects\MNI_4_Yann\MNI_brain_NoCollosum_12000V_tess.mat'; +% fv=tess2patch(TessFile); +% v=(fv.vertices*diag([1 -1 -1])+repmat([-90e-3 217e-3-126e-3 181e-3-72e-3], size(fv.vertices,1),1))*diag([-1 1 1])*1000; +% view_cortex(fv.faces, v) +% image_spm(y,vol); view(2); hold on +% h=findTessellationHandles +% set(h, 'visible', 'off') + +TessFile='D:\ndiaye\data\subjects\MNI_4_Yann\MNI_brain_NoCollosum_12000V_tess_corrected.mat'; +fv=tess2patch(TessFile); + + +AtlasMRI='d:/ndiaye/data/subjects/colin27/brodmann.img'; +AtlasMRI='d:/ndiaye/data/subjects/colin27/aal.img'; + +% Note: the right occipital pole of the single subject MNI (colin27) goes a +% little on the left side +if not(exist('xyz')) +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol(AtlasMRI) + vol=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + + ref=vol(vol>0); + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); + + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + +end +if not(exist('xyz2')) + DECIMATION=1; + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); +end diff --git a/brodmann/img2voxels.m b/brodmann/img2voxels.m new file mode 100644 index 0000000..7e05b71 --- /dev/null +++ b/brodmann/img2voxels.m @@ -0,0 +1,17 @@ +function [xyz,ref]=img2voxels(y,thd) +if ischar(y) + y=spm_vol(y); +end +if nargin<2 + thd=0; +end +vol=spm_read_vols(y); +% Undo L-R flipping +if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); +end +ref=vol(vol>0); +[xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(vol), find(vol>0)); +xyz=[xyz ones(size(xyz,1),1)]*y.mat'; +xyz=xyz(:,1:3); diff --git a/brodmann/labelbrainstorm.m b/brodmann/labelbrainstorm.m new file mode 100644 index 0000000..467f7b2 --- /dev/null +++ b/brodmann/labelbrainstorm.m @@ -0,0 +1,191 @@ +function [r]=labelbrainstorm(varargin) +% labelbrainstorm - display (and compute) labels on a brainstorm cortical surface +% +% [] = labelviewer([inputs]) +% +% Inputs should be given according to the following way: +% 'Option', OptionValue +% - BrainstormSubject='FileName': optional Brainstorm Subject file +% - BrainstormTess='FileName': a brainstorm tess file +% - PialSurface: vertices used for the Talairach Bounding Box +% (usually the Rhemi and Lhemi surfaces) +% +% - Atlas='FileName': an atlas file, e.g. TTareas.mat or TTgyri.mat (or any one you can design) +% Ouputs: +% - [none] : GUI version +% - or: [r, labels, xyz, ref]: +% r: label for each vertex +% +% Examples of use: +% > labelbrainstorm +% > [r]=labelbrainstorm('BrainstormSubject','d:/subjects/darwin/darw_brainstormsubject.mat') +% +% Version 1.0 - K. N'Diaye + +% What we need +% 1. The vertices of interest +% 2. The pial surface (R+L hemispheres) +% 3. AC, PC, IH in the same referential +% 4. The atlas + +options=struct(varargin{:}); +% if not(isfield(options, 'BrainstormTess')) & not(isfield(options, 'BrainstormSubjectImage')) +% uigetfile +% end +if isfield(options, 'BrainstormSubject') + bsj=load(options.BrainstormSubject); + if not(isempty(bsj.Tesselation)) + options.Tesselation=bsj.Tesselation; + end +end + +if isfield(options, 'PialSurface') + options.MRI2CTF=[diag([1 1 1]) zeros(3,1)]; +end +data_path=[]; + +if isfield(options, 'BrainstormTess') + tess=load(options.BrainstormTess); + if length(tess.Vertices)>1 + [s,v] = listdlg('PromptString','Choose a cortical surface:',... + 'SelectionMode','single',... + 'ListString',tess.Comment); + if not(v),return,end + options.Tesselation.vertices=tess.Vertices{s}'; + options.Tesselation.faces=tess.Faces{s}; + else + options.Tesselation.vertices=tess.Vertices{1}'; + options.Tesselation.faces=tess.Faces{1}; + end + clear tess +end + + +if not(isfield(options, 'Tesselation')) & not(isfield(options, 'BrainstormTess')) + import_tess=1; + tessfiles={}; + while import_tess + [f,p,fidx]=uigetfile({'*tess.mat', '(*tess.mat) Brainstorm Tess File'; '*.mat' 'Matlab file'; '*.mesh' 'AIMS mesh file'} , 'pick a tesselation/mesh file', data_path); + if isempty(f) | f==0, return, end + data_path=p; + tessfiles=[tessfiles {fullfile(p,f)}]; + if fidx<=2 + options.BrainstormTess=tessfiles{end}; + import_tess=0; + else + if not(isfield(options, 'Tesselation')) + options.Tesselation.faces=[]; + options.Tesselation.vertices=[]; + end + [fv.vertices,fv.faces]=readmesh(tessfiles{end}); + fv.faces=fv.faces+1+size(options.Tesselation.vertices,1); + options.Tesselation.faces=[options.Tesselation.faces ; fv.faces]; + options.Tesselation.vertices=[options.Tesselation.vertices ; fv.vertices]; + button = questdlg(['Add another file?' sprintf('%s\n', tessfiles{:})],'Importing tesselations','Yes','No','Cancel','Yes'); + if strmatch('No', button) + import_tess=0; + elseif strmatch('Cancel', button) + return; + end + end + end +end + +if not(isfield(options, 'Tesselation')) + error(sprintf('%s: No tesselation!', mfilename)); + return +end + +if not(isfield(options, 'PialSurface')) + [f,p,fidx]=uigetfile({'*tess.mat', '(*tess.mat) Brainstorm Tess File'; '*.mat' 'Matlab file'; '*.mesh' 'AIMS mesh file'} , 'pick a tesselation/mesh file for external cortical surface',data_path); + if isempty(f) | f==0, return, end + data_path=p; + if fidx<=2 + tess=load(options.BrainstormTess); + if length(tess.Vertices)>1 + [s,v] = listdlg('PromptString','Choose a cortical surface:',... + 'SelectionMode','single',... + 'ListString',tess.Comment); + if not(v),return,end + options.PialSurface=tess.Vertices{s}'; + else + options.PialSurface=tess.Vertices{1}'; + end + clear tess + else + [options.PialSurface]=readmesh(fullfile(p,f)); + end +end + +if not(isfield(options, 'APC')) + if not(isfield(options, 'VoxelSize')) + prompt={'Voxel size (in mm) : '}; + dlgTitle=['MR Slices']; + lineNo=[1]; + DefAns={'0.9375 0.9375 1.3'}; + options.VoxelSize=inputdlg(prompt,dlgTitle,lineNo, DefAns); + options.VoxelSize=str2num(char(options.VoxelSize{1})); + if isempty(options.VoxelSize) + return + end + end + [f,p]=uigetfile({'*.APC', 'Brainvisa APC file'} ,'Pick an APC file',data_path); + if f==0, return, end + data_path=p; + options.APCfile=fullfile(p,f); +end + +if not(isfield(options, 'APC')) + options.APCmm=readAPCmm(options.APCfile, options.VoxelSize); +end + +if not(isfield(options, 'APC')) + if not(isfield(options, 'MRItoCTF')) + button = questdlg('MRI to CTF registration file?','MRI to CTF registration','MegDraw','Compute it!','Cancel','MegDraw'); + if strmatch('MegDraw', button) + [f,p]=uigetfile({'*.txt', 'megDraw MRI to CTF'} ,'Pick a megDraw MRI to CTF file',data_path); + if f==0,return,end + data_path=p; + [ignore, options.MRItoCTF] =readMRItoCTF(fullfile(p,f)); + elseif strmatch('Compute it!', button, 'exact') + [f1,p1]=uigetfile({'*.mesh', 'original mesh file'} ,'Pick a mesh file',data_path); + if f1==0,return,end + data_path=p; + [f2,p2]=uigetfile({'*CTF.mesh', 'CTF registered mesh file'} ,'Pick a CTF mesh file',data_path); + if f2==0,return,end + data_path=p; + v1=readmesh(fullfile(p1,f1)); + v2=readmesh(fullfile(p2,f2)); + options.MRItoCTF=[v1 repmat(1,size(v1,1),1)]\v2; + else + return + end + + + + + end +end +if isfield(options, 'APCmm') + options.APC=[options.APCmm ones(3,1)]*options.MRItoCTF; +end +% options.PialSurface=[options.PialSurface ones(size(options.PialSurface,1),1)]*options.MRItoCTF; +end + + + + +fv.vertices = ctf2tal(options.Tesselation.vertices, [], 'ACPCIH_ctf', options.APC, 'brainvert', options.PialSurface); +fv.vertices = fv.vertices * 1000; +fv.faces=options.Tesselation.faces; +load TTdemo +%error('pb w/ CTF MRI ???') +fv=reducepatch(fv,500); +r=labelize(fv.vertices, xyz, ref,'TimeBar', 'on'); + +labelviewer(fv, r, xyz, ref, labels) + + +return + +function [vertices, faces]=imoprt_tess(curr_datadir) diff --git a/brodmann/labelize.m b/brodmann/labelize.m new file mode 100644 index 0000000..06184a3 --- /dev/null +++ b/brodmann/labelize.m @@ -0,0 +1,52 @@ +function [r]=labelize(vertices, t_xyz, t_ref,varargin) +% labelize - labelize vertrices according to a reference template +% +% [r]=labelize(vertices, t_xyz, t_ref,['TimeBar']) +% +% Each item of the vertices will be labeled with the t_ref value +% of the closest vertex in the t_xyz template (geometrical distance). +% +% Input: +% vertices: [Nvx3] coordinates of Nv vertices for which labels are computed +% t_xyz: [Ntx3] matrix, positions of the Nt template vertices +% t_ref: [Ntx1] vector, labels of the template vertices +% +% Output: +% r: [Nvx1] vector of the labels +% +% Options: +% TimeBar 1 or 'on' to show a progress bar +if nargin>3 +options=struct(varargin{:}); +end +if isfield(options, 'TimeBar') + if strmatch('on', lower(options.TimeBar)) + options.TimeBar=1; + else + options.TimeBar=0; + end +else + options.TimeBar=0; +end + +r=zeros(length(vertices),1)*NaN; +if options.TimeBar + h=timebar('Progres...','Labeling vertices'); +end + +for i=1:length(vertices) + d=sqrt(sum(power(t_xyz-repmat(vertices(i,:),size(t_xyz,1),1),2),2)); + + % local "smoothing" + % r(i)=imax(hist(ref(d<5e-3), .5:length(labels))); + + r(i)=t_ref(imax(-d)); + if options.TimeBar + timebar(h, i/length(vertices),1); + end + %set(p, 'FaceVertexCData',r); drawnow; +end +if options.TimeBar + close(h) +end + diff --git a/brodmann/labelviewer.m b/brodmann/labelviewer.m new file mode 100644 index 0000000..f393e6c --- /dev/null +++ b/brodmann/labelviewer.m @@ -0,0 +1,80 @@ +function [patchhandle, template] = labelviewer(fv, r, xyz, ref, labels, varargin) +% LABELVIEWER - Display labels on a cortex +% [] = labelviewer(Brain, CData, TemplateXYZ, TemplateREF, Labels, [ColorMap]) +% +% - Brain: a .vertices and .faces structure +% - CData: already computed labels on the brain mesh +% - TemplateXYZ: [Na x 3] Atlas Coordinates of the Na vertices +% - TemplateREF: [Na x 1] Atlas Label ID +% - Labels: Cell of strings +% - ColorMap=[Nlabels x 3] colormap (default: hsv) +% +% Ouputs: +% - [none] : GUI version + + +if nargin > 5 + cmap=varargin{1}; +else + cmap=hsv(length(labels)); +end + +kcmap=.4; +r=double(r); +hf=figure; +axes +set(gca, 'color', 'k'); +p=patch('vertices', fv.vertices, 'faces',fv.faces, ... + 'CData', r, 'CDataMapping', 'direct', ... + 'EdgeColor', 'none', 'FaceColor', 'flat'); +lighting gouraud +colormap(cmap) +h=colorbar; +axis image +light('position' , [-1 1 0]) +light('position' , [ 0 0 1]) +light('position' , [ 1 -1 -1]) +light('position' , [ 1 1 0]) +l=findobj(hf, 'type', 'light'); +set(l, 'color', .8*ones(1,3)) +set(h, 'YDir', 'reverse'); +set(h, 'position', [0.8314 0.1100 0.02 0.8150]) +view(3) +rotate3d + +hold on +if not(isempty(xyz)) & not(isempty(ref)) + for i=1:length(labels) + if any(ref==i) + pp(i)=plot3d(xyz(ref==i,:),'o', 'markerSize', 2, 'color', 1-cmap(i,:)); + else + pp(i)=plot3d([0 0 0],'Marker', 'none', 'markerSize', 2, 'color', 1-cmap(i,:)); + end + end + set(pp, 'visible', 'off'); +else + pp=[]; +end +u.pp=pp; +u.r=r; +u.cmap=cmap; +u.kcmap=kcmap; +u.ref=ref; +u.roi=[]; +set(hf, 'UserData', u); +callback=[ 'u=get(gcbf, ''UserData'');'... + 'set(u.pp, ''visible'', ''off'');' ... + 'i=get(gcbo,''value'');set(u.pp(i),''visible'',''on''); ' ... + 'c=u.cmap*u.kcmap; c(i,:)=u.cmap(i,:); colormap([c]);' ... + 'u.roi=find(ismember(u.r,i));' ... + 'set(gcbf, ''UserData'', u);']; +hui=uicontrol('Style', 'listbox', 'Tag', 'Labels', ... + 'String', labels , ... + 'callback', callback); +set(hui, 'units', 'normalized') +set(hui, 'Max', 2, 'Min', 0) +set(hui, 'position', [0.8414 0.1100 .15 .8150]) + +eval(strrep(strrep(callback, 'gcbf', 'hf'), 'gcbo', 'hui')); +rotate3d + diff --git a/brodmann/makeTTbasta.m b/brodmann/makeTTbasta.m new file mode 100644 index 0000000..fa8b41e --- /dev/null +++ b/brodmann/makeTTbasta.m @@ -0,0 +1,53 @@ +function [TTbasta]=makeTTbasta(ref,labels,xyz) +% Merge Brodmann regions into bigger ones + + +% Remove midline points +keep=find(xyz(:,1)~=0); +% Decimate +% keep=keep(1:10:end); +xyz=xyz(keep,:); +ref=ref(keep); + + +hbar=timebar('...', 'Merging BA clusters'); +ba=strmatch('Brodmann', labels); +baref=double(ref); +baref=0.*baref; +for i=1:length(ba) + timebar(hbar,i/length(ba)); + baref(find(ref==ba(i)))=str2num(labels{ba(i)}(15:end)); +end + +[a,labels2]=textread('mergeBA.txt','%s%s', 'delimiter', '|'); +ref2=0.*(baref); +for i=1:length(a) + timebar(hbar,i/length(a)); + ref2(find(ismember(baref, str2num(a{i}))))=i; +end +ref2=int16(ref2); +close(hbar) + +% add limbic structures to hippocampal region +limbix={'Hippocampus', 'Amygdala'}; +hipp=strmatch('hippocampal region', labels2); +for i=1:2 + ref2(find(ref==strmatch(limbix{i}, labels)))=hipp; +end +labels2{hipp}=[ labels2{hipp} ' + hippocampus + amygdala']; + +% Separate Left/Right hemisphere +nl=length(labels2); +ref3=zeros(size(ref2)); +for i=1:nl + l2{2*i-1}=['Left ' labels2{i}]; + l2{2*i}=['Right ' labels2{i}]; + ref3(find(ref2==i & xyz(:,1)<0))=2*i-1; + ref3(find(ref2==i & xyz(:,1)>0))=2*i; +end + +TTbasta.ref=int8(ref3); +TTbasta.xyz=int8(xyz); +TTbasta.labels=l2'; + +% Thalamic nuclei: 2 51 52 54 56 57 59 61 66 67 68 69 diff --git a/brodmann/make_aal_colormap.m b/brodmann/make_aal_colormap.m new file mode 100644 index 0000000..5ec1991 --- /dev/null +++ b/brodmann/make_aal_colormap.m @@ -0,0 +1,148 @@ +aal.labels={ + 'Precentral_L' + 'Precentral_R' + 'Frontal_Sup_L' + 'Frontal_Sup_R' + 'Frontal_Sup_Orb_L' + 'Frontal_Sup_Orb_R' + 'Frontal_Mid_L' + 'Frontal_Mid_R' + 'Frontal_Mid_Orb_L' + 'Frontal_Mid_Orb_R' + 'Frontal_Inf_Oper_L' + 'Frontal_Inf_Oper_R' + 'Frontal_Inf_Tri_L' + 'Frontal_Inf_Tri_R' + 'Frontal_Inf_Orb_L' + 'Frontal_Inf_Orb_R' + 'Rolandic_Oper_L' + 'Rolandic_Oper_R' + 'Supp_Motor_Area_L' + 'Supp_Motor_Area_R' + 'Olfactory_L' + 'Olfactory_R' + 'Frontal_Sup_Medial_L' + 'Frontal_Sup_Medial_R' + 'Frontal_Mid_Orb_L' + 'Frontal_Mid_Orb_R' + 'Rectus_L' + 'Rectus_R' + 'Insula_L' + 'Insula_R' + 'Cingulum_Ant_L' + 'Cingulum_Ant_R' + 'Cingulum_Mid_L' + 'Cingulum_Mid_R' + 'Cingulum_Post_L' + 'Cingulum_Post_R' + 'Hippocampus_L' + 'Hippocampus_R' + 'ParaHippocampal_L' + 'ParaHippocampal_R' + 'Amygdala_L' + 'Amygdala_R' + 'Calcarine_L' + 'Calcarine_R' + 'Cuneus_L' + 'Cuneus_R' + 'Lingual_L' + 'Lingual_R' + 'Occipital_Sup_L' + 'Occipital_Sup_R' + 'Occipital_Mid_L' + 'Occipital_Mid_R' + 'Occipital_Inf_L' + 'Occipital_Inf_R' + 'Fusiform_L' + 'Fusiform_R' + 'Postcentral_L' + 'Postcentral_R' + 'Parietal_Sup_L' + 'Parietal_Sup_R' + 'Parietal_Inf_L' + 'Parietal_Inf_R' + 'SupraMarginal_L' + 'SupraMarginal_R' + 'Angular_L' + 'Angular_R' + 'Precuneus_L' + 'Precuneus_R' + 'Paracentral_Lobule_L' + 'Paracentral_Lobule_R' + 'Caudate_L' + 'Caudate_R' + 'Putamen_L' + 'Putamen_R' + 'Pallidum_L' + 'Pallidum_R' + 'Thalamus_L' + 'Thalamus_R' + 'Heschl_L' + 'Heschl_R' + 'Temporal_Sup_L' + 'Temporal_Sup_R' + 'Temporal_Pole_Sup_L' + 'Temporal_Pole_Sup_R' + 'Temporal_Mid_L' + 'Temporal_Mid_R' + 'Temporal_Pole_Mid_L' + 'Temporal_Pole_Mid_R' + 'Temporal_Inf_L' + 'Temporal_Inf_R' + 'Cerebelum_Crus1_L' + 'Cerebelum_Crus1_R' + 'Cerebelum_Crus2_L' + 'Cerebelum_Crus2_R' + 'Cerebelum_3_L' + 'Cerebelum_3_R' + 'Cerebelum_4_5_L' + 'Cerebelum_4_5_R' + 'Cerebelum_6_L' + 'Cerebelum_6_R' + 'Cerebelum_7b_L' + 'Cerebelum_7b_R' + 'Cerebelum_8_L' + 'Cerebelum_8_R' + 'Cerebelum_9_L' + 'Cerebelum_9_R' + 'Cerebelum_10_L' + 'Cerebelum_10_R' + 'Vermis_1_2' + 'Vermis_3' + 'Vermis_4_5' + 'Vermis_6' + 'Vermis_7' + 'Vermis_8' + 'Vermis_9' + 'Vermis_10' + }; +l=aal.labels(1:2:end); + + + +if 1 + colors=subarray(colorcube(64),1:54); +else + +colors=zeros(54,3); +% FRONTAL: +% 'Frontal_Sup_L' +% 'Frontal_Sup_Orb_L' +% 'Frontal_Mid_L' +% 'Frontal_Mid_Orb_L' +% 'Frontal_Inf_Oper_L' +% 'Frontal_Inf_Tri_L' +% 'Frontal_Inf_Orb_L' +% 'Frontal_Sup_Medial_L' +% 'Frontal_Mid_Orb_L' + +i=strmatch('Frontal', l); +c=huemap([1 0 0],length(i)) +colors(i)=c; +end + +% Symmetrical colors +colors=reshape([ colors colors ]', 3,2*size(colors,1))'; +%Add gray colors for vermis: +colors=[colors; bone(8)]; + diff --git a/brodmann/mergeBA.m b/brodmann/mergeBA.m new file mode 100644 index 0000000..f5b40c5 --- /dev/null +++ b/brodmann/mergeBA.m @@ -0,0 +1,32 @@ +function [ref2,labels2]=mergeBA(ref,labels) +% Merge Brodmann regions into bigger ones + +hbar=timebar('...', 'Merging BA clusters'); +ba=strmatch('Brodmann', labels); +baref=double(ref); +baref=0.*baref; +for i=1:length(ba) + timebar(hbar,i/length(ba)); + baref(find(ref==ba(i)))=str2num(labels{ba(i)}(15:end)); +end + +[a,labels2]=textread('mergeBA.txt','%s%s', 'delimiter', '|') +ref2=0.*(baref); +for i=1:length(a) + timebar(hbar,i/length(a)); + ref2(find(ismember(baref, str2num(a{i}))))=i; +end +ref2=int16(ref2); +close(hbar) + +% add limbic structures to hippocampal region +limbix={'Hippocampus', 'Amygdala', 'Dentate'} +hipp=strmatch('hippocampal region', labels2); +for i=1:3 + ref2(find(ref==strmatch(limbix{i}, labels)))=hipp; +end + + + + +% Thalamic nuclei: 2 51 52 54 56 57 59 61 66 67 68 69 diff --git a/brodmann/mergeBA.txt b/brodmann/mergeBA.txt new file mode 100644 index 0000000..ae14e25 --- /dev/null +++ b/brodmann/mergeBA.txt @@ -0,0 +1,24 @@ +1 2 3 5 43 | intermediate postcentral area 1 + caudal postcentral area 2 + rostral postcentral area 3 + preparietal area 5 + subcentral area 43 +4 | precentral gigantopyramidal area 4 +6 | agranular frontal area 6 +7 | superior parietal area 7 +8 | intermediate frontal area 8 +9 | granular frontal area 9 +10 | frontopolar area 10 +11 12 25 47 | prefrontal area 11 + rostral area 12 + subgenual area 25 + orbital area 47 +13 | insular area 13 +17 | striate area 17 +18 | parastriate area 18 +19 | peristriate area 19; +20 | inferior temporal area 20 +21 | middle temporal area 21 +22 | superior temporal area 22 +23 31 26 29 30 | posterior cingulate & retrosplenial : ventral posterior cingulate area 23 + dorsal posterior cingulate area 31 + ectosplenial area 26 + granular retrolimbic area 29 + agranular retrolimbic area 30 +24 32 33 | anterior cingulate : ventral anterior cingulate area 24 + dorsal anterior cingulate area 32 + pregenual area 33 +27 28 34 35 36 | hippocampal region : presubiculum 27 + entorhinal area 28 + dorsal entorhinal area 34 + perirhinal area 35 + ectorhinal area 36 +37 | occipitotemporal area 37 +38 | temporopolar area 38 +39 | angular area 39 +40 | supramarginal area 40 +41 42 | anterior transverse temporal area 41 + posterior transverse temporal area 42 +44 45 46 | opercular area 44 + triangular area 45 + middle frontal area 46 diff --git a/brodmann/merge_cluster.m b/brodmann/merge_cluster.m new file mode 100644 index 0000000..1e4a8e0 --- /dev/null +++ b/brodmann/merge_cluster.m @@ -0,0 +1,15 @@ +function [pcl2, vc]=merge_cluster(pcl, parcelle) +% merge parcels (pcl) computed from Anael's geod_cluster +% [pcl2, vc]=merge_cluster(pcl, parcelle) +% +% pcl2: merged parcelles +% vc: vector of the parcel number for each source +% pcl: product of geod_cluster +% parcelle: list of {list of seeds} + +for i=1:length(parcelle) + seeds=[parcelle{i}]; + seeds(seeds>2027)=[]; + pcl2{i}= [pcl{seeds}]; + vc([pcl2{i}])=i; +end \ No newline at end of file diff --git a/brodmann/montreal_brodmann.m b/brodmann/montreal_brodmann.m new file mode 100644 index 0000000..dc33b61 --- /dev/null +++ b/brodmann/montreal_brodmann.m @@ -0,0 +1,162 @@ +mypath + +addpath(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Toolbox')) +addpath(fullfile(HOMEDIR, 'mtoolbox/spm2')) +addpath(fullfile(MATLABDIR)) +addpath(fullfile(MATLABDIR, 'ctf2tal')) +addpath(fullfile(MATLABDIR, 'stormvisa')) +addpath(fullfile(MATLABDIR, 'brodmann')) + + +load(fullfile(HOMEDIR, 'data/subjects/montreal_subject/montreal_4layer_tess')) +fv.vertices=Vertices{4}'; +fv.vertconn=VertConn{4}; +clear Vertices; +fv.faces=Faces{4}; +clear Faces; +clear VertConn +clear tess2mri_interp +try + load(fullfile(USBDIR, 'data/subjects/montreal_subject/TalairachMRIscs.mat'), 'TAL') + S(1)=load(fullfile(HOMEDIR, 'data/subjects/montreal_subject/montreal_subjectimage.mat'), 'SCS') + S(2).SCS=S(1).SCS(1); + S(3)=load(fullfile(HOMEDIR, 'mtoolbox/brainstorm/Phantom/montreal_subject/montreal_subjectimage_info.mat'), 'SCS') + S(4).SCS=S(3).SCS(1); + +catch +end +% fv2.vertices=scs2mri(S(2),fv.vertices'*1000)'-repmat([92 128 74],[10001,1]); +fv2.faces=fv.faces; +fv2.vertconn=fv.vertconn; + +fv2.vertices=scs2mri(S(end),fv.vertices'*1000); +[ignore,fv2.vertices]=mri2scs(TAL,fv2.vertices); +fv2.vertices=fv2.vertices'; +v2=fv2.vertices; + +disp('Lecture des fichiers Analyze') +apc=[0 0 0; 0 -23 0; 0 0 50]; +verttal = ctf2tal(v2, [], 'ACPCIH_ctf', [apc], 'brainvert', v2); + +figure(1) +clf +view_cortex(fv2.faces,v2/1000,'FaceColor','none', 'EdgeColor', 'k' , 'FaceAlpha', .5) +hold on +view_cortex(fv2.faces,verttal, 'FaceColor','none', 'EdgeColor', 'r') +view_cortex(fv2.faces,mni2tal(v2)/1000, 'FaceColor','none', 'EdgeColor', 'g') +legend({'orig','tal', 'mni2tal'},0) + +view(90,0) +rotate3d +drawnow + + + +if not(exist('xyz2')) + DECIMATION=1000 +% y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','aal.img')) + y=spm_vol(fullfile(HOMEDIR, 'data', 'subjects', 'colin27','brodmann.img')) + v=spm_read_vols(y); + % Undo L-R flipping + if spm_flip_analyze_images + y.mat(1:5:11)=y.private.hdr.dime.pixdim(2:4); + y.mat(1,4)=-y.mat(1,4); + end + ref=v(v>0); + try + [ign,labels,ign]=textread(strrep(y.fname,'img', 'txt'), '%f%s%f'); + catch + labels=cellstr(num2str([1:max(ref)]')); + end + % in MRI + [xyz(:,1),xyz(:,2),xyz(:,3)]=ind2sub(size(v), find(v>0)); + xyz2=xyz(1:DECIMATION:end,:); + ref2=ref(1:DECIMATION:end); + % in MNI + xyz2=[xyz2 ones(size(xyz2,1),1)]*y.mat'; + xyz2=xyz2(:,1:3); + + % I dunno why but brodmann from MRIcro is not centered?!? + % xyz2=xyz2-repmat([-3 10 -10], [size(xyz2,1) 1]); + v2=fv2.vertices+repmat([0 10 -8],10001,1); +end +plot3d([xyz2]/1000) + +% r=labelize(v2, xyz2, ref2, 'TimeBar', 'on'); + +return +labelviewer(struct('vertices', v2, 'faces', fv.faces), r, xyz2, ref2, labels) + + +r=ref2(closest(v2,xyz2)); + +if 0 + load(fullfile(HOMEDIR, 'matlab/ctf2tal/TTareas.mat')); + xyz=xyz(1:10:end,:); + ref=ref(1:10:end); + ref=double(ref); + xyz=ctf2tal(xyz, [], 'brainvert', xyz, 'CA', [0 0 0], 'CP', [0 -23 0], 'IH' ,[0 0 50]); + r=labelize(verttal, xyz2, ref, 'TimeBar', 'on'); + talairach.vertices=verttal; + talairach.faces=fv.faces; +end + +return + +save(fullfile(SCOUTDIR,date,[date '_brodmann.mat']), 'r','talairach', 'xyz', 'ref', 'labels' ) + +disp('Sauvegarde dans un fichier CorticalScout') + +scoutfile=dir(fullfile(RESDIR,date, [date '*CorticalScout_2.mat'])); +scouts=load(fullfile(RESDIR,date, scoutfile.name)); + +BA=strmatch('Brodmann', labels); + +SIDES=['R', 'L']; +for side=0:1 +for i=1:length(BA) + vba=find(r==BA(i) & left==side); + scouts.CorticalScouts.CorticalMarkersLabels{i+42*side}=[labels{BA(i)} '-' SIDES(side+1)]; + if not(isempty(vba)) + scouts.CorticalScouts.CorticalSpots(i+42*side)=vba(1); + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = v_ctf(vba(1),:); +else + scouts.CorticalScouts.CorticalSpots(i+42*side)=NaN; + scouts.CorticalScouts.CorticalMarkers(i+42*side,:) = NaN; +end + scouts.CorticalScouts.CorticalProbePatches{i+42*side}=vba; + scouts.CorticalScouts.CorticalProbeDepth(i+42*side)=0; + scouts.CorticalScouts.CorticalProbePatchesXYZ{i+42*side}=v_ctf(scouts.CorticalScouts.CorticalProbePatches{i},:)'; +end +end +bascoutfile=strrep(scoutfile.name, '_2.mat', '_BA.mat') + CorticalScouts=scouts.CorticalScouts; + ResultFile=scouts.ResultFile; + ActiveTess=scouts.ActiveTess; + save(fullfile(SCOUTDIR,date,bascoutfile), 'ResultFile','ActiveTess','CorticalScouts') + +return + + + +cmap=hsv(69); +hf=figure; +p=patch('vertices', fv.vertices, 'faces',fv.faces, ... + 'CData', r, 'CDataMapping', 'direct', ... + 'EdgeColor', 'none', 'FaceColor', 'flat'); +colormap(cmap) +h=colorbar; +axis image +light('position' , [-1 1 0]) +light('position' , [ 0 0 1]) +light('position' , [ 1 -1 -1]) +light('position' , [ 1 1 0]) +l=findobj(hf, 'type', 'light'); +set(l, 'color', .8*ones(1,3)) +set(h, 'YDir', 'reverse'); +set(h, 'position', [0.8314 0.1100 0.02 0.8150]) +view(3) +rotate3d +lighting gouraud + +return diff --git a/bugs/emptiness.m b/bugs/emptiness.m new file mode 100644 index 0000000..ef943aa --- /dev/null +++ b/bugs/emptiness.m @@ -0,0 +1,163 @@ +disp('************************************************') +disp('* *') +disp('* BUGS in Matlab *') +disp('* *') +disp('************************************************') + +disp(['Version: ' version]) + +disp('------------------------------------------------') +disp('Matrix product is ill defined for "empty" arrays') +A=ones(2,0) +B=ones(0,3) +disp('A*B=') +A*B +disp('------------------------------------------------') + + + +disp('------------------------------------------------') +disp('Matrix product is ill defined for "empty" arrays') +A=ones(2,2) +disp('A(:,[])*A(:,[])'' =') +A(:,[])*A(:,[])' +disp('size(A(:,[]))') +size(A(:,[])) +disp('------------------------------------------------') + + +disp('------------------------------------------------') +disp(' Inconsistent logics due to If short circuit') +disp(' if 1 | [] ; ''T'' , else ''F'',end ') +if 1 | [] ; disp('T') , else disp('F'), end +disp(' if [] | 1 ; ''T'' , else ''F'', end ') +if [] | 1 ; disp('T') , else disp('F'), end + +disp('------------------------------------------------') +disp(' Inconsistent logics due to scalar expansion') +disp(' 1 == [] ') +1 == [] +disp(' [] == 1 ') +[] == 1 +disp(' [ 1 & [] ] ') +[ 1 & [] ] +disp(' [ [] & 1 ] ') +[ [] & 1 ] +disp(' [ 1 | [] ] ') +[ 1 | [] ] +disp(' [ [] | 1 ] ') +[ [] | 1 ] +% disp(' [ 1 || [] ] ') +% [ 1 || [] ] +% disp(' [ [] || 1 ] ') +% [ [] || 1 ] + + + +disp('------------------------------------------------') +disp(' Fields of empty arrays of structs') +a=dir +b=a([]); +disp('b=setfield(a([]),''test'', [])') +try +b=setfield(b,'test', []) +catch ME + disp('Error:') + disp(ME.message) +end + + + +% $$$ Groupes de discussion : comp.soft-sys.matlab +% $$$ De : Scott French - Rechercher les messages de cet auteur +% $$$ Date : 2000/09/13 +% $$$ Objet : Re: if (1 | []) : inconsistencies? +% $$$ +% $$$ Eric, +% $$$ +% $$$ There are a couple of issues interacting here. First, there's scalar +% $$$ expansion. In an expression of the form +% $$$ +% $$$ Scalar OPERATOR Matrix +% $$$ +% $$$ Scalar is replaced by a matrix with the same dimensions as Matrix, and +% $$$ whose every element is Scalar. Then the operator's operation is +% $$$ performed. Applying this to the expression +% $$$ +% $$$ 1 | [] +% $$$ +% $$$ You get the value 1 replaced by a matrix with the same dimensions as +% $$$ [], in other word, an empty matrix. So 1 | [] evaluates to [] | [], +% $$$ which is []. +% $$$ +% $$$ Second, IF treats the empty matrix conditional as false. It probably +% $$$ should be treated as true, since technically every element of the +% $$$ empty matrix (what few of them there are) is nonzero. It was +% $$$ implemented with empty treated as false a long time ago, and when we +% $$$ tried to change it a few years ago we found that we broke such a large +% $$$ amount of code (just among the M-code in MATLAB and our toolboxes) +% $$$ that we decided it would cause more problems for our customers if we +% $$$ fixed it than if we left it alone. +% $$$ +% $$$ Thirdly, in MATLAB 5.0, we added short circuited conditionals for IF +% $$$ and WHILE if the left hand side of the conditional is a +% $$$ scalar. Unfortunately, at the time, we didn't realize that empty +% $$$ matrices and scalar expansion violate a requirement for short +% $$$ circuiting. That is, in order to short circuit, +% $$$ +% $$$ 1 | X == 1 +% $$$ +% $$$ has to be true for all values of X. If X is the empty matrix, though, +% $$$ then the requirement fails. Its worth pointing out that even if IF +% $$$ treated [] as true, we would still have a problem because to short +% $$$ circuit logical AND, you need +% $$$ +% $$$ 0 & X == 0 +% $$$ +% $$$ to be true for all X, and if [] is treated as true, then this fails +% $$$ for X equal to [] as well. +% $$$ +% $$$ Since short circuited conditionals have been part of MATLAB since +% $$$ version 5.0, we have the same issue as before, that is, maintaining +% $$$ backward compatibility versus improving/fixing the MATLAB language. +% $$$ +% $$$ So now at least you know what is going on. You are the first person +% $$$ that I know of to state the issue as succinctly as you have, and as a +% $$$ result a bunch of us here are now in deep meditative trances trying to +% $$$ decide what the right thing to do is. In the meantime, if having [] be +% $$$ treated as false is a problem for you, you can pass conditional +% $$$ expressions that could potentially be empty through the ALL function +% $$$ first. If the short circuiting is a problem, you could call the +% $$$ functional form of OR, like this +% $$$ +% $$$ if (or(1,[])), disp('T'), else disp('F'), end % F +% $$$ +% $$$ I hope these suggestions are helpful. +% $$$ +% $$$ Sincerely, +% $$$ Scott French +% $$$ Software Engineer +% $$$ +% $$$ - Masquer le texte des messages pr?c?dents - +% $$$ - Afficher le texte des messages pr?c?dents - +% $$$ Eric Durant writes: +% $$$ > After reading 2-12 ff. and 2-398 ff. in the Matlab Function Reference, +% $$$ > Volume 1, Version 5, I expect all of the following to give the same +% $$$ > result ('T'), but they don't. Is this a bug or documentation error, or +% $$$ > have I missed something? +% $$$ +% $$$ > expr=(1|[]); if expr , disp('T'), else disp('F'), end % F +% $$$ > expr=([]|1); if expr , disp('T'), else disp('F'), end % F +% $$$ > if(1|[]), disp('T'), else disp('F'), end % T +% $$$ > if([]|1), disp('T'), else disp('F'), end % F +% $$$ > if(all(1|[])), disp('T'), else disp('F'), end % T +% $$$ > if(all([]|1)), disp('T'), else disp('F'), end % T + +% $$$ > I've tested this with R11.1 on PCWIN and SOL2. +% $$$ +% $$$ > -- Eric Durant +% $$$ > http://edurant.com/ +% $$$ +% $$$ -- +% $$$ Scott French E-mail - s...@mathworks.com +% $$$ The MathWorks, Inc. WWW - http://www.mathwor \ No newline at end of file diff --git a/cartool/J_segmentation.m b/cartool/J_segmentation.m new file mode 100644 index 0000000..39da59c --- /dev/null +++ b/cartool/J_segmentation.m @@ -0,0 +1,297 @@ +function [GFP,DE,indm,indM,DEm]=J_segmentation(flowc,graphe,Time,tstim,tend,GFP) + +if nargin<3 + Time=flowc.t; + [m,tstim]=min(abs(Time)); + + DE=sqrt(flowc.de); + nF=size(flowc.F,1); + GFP=sqrt(sum((flowc.F-repmat(mean(flowc.F),nF,1)).^2,1)); + % DE modifié par la moyenne des champs de vitesse + + nV=size(flowc.V,1); + for tt=1:size(flowc.V,3) + V=flowc.V(:,:,tt); + + mV=mean(V); + DEm(tt)=sqrt(sum((V(:,1)-mV(1)).^2) + sum((V(:,2)-mV(2)).^2) + sum((V(:,3)-mV(3)).^2)); + end + +else + DEm=sqrt(flowc); +end + + + +%%%%%%%%%%%%%%%%% +% Vizualisation % +%%%%%%%%%%%%%%%%% + +[mval,indm]=lmin(DEm,3); +[Mval,indM]=lmax(DEm,3); + +if graphe + figure + plot(Time,DEm,'Color',[0 0 0]) + hold on + if nargin==6 + figure(2) + plot(Time,GFP,'Color',[0 0 0]) + hold on + end +end + +goodm=find(indm>tstim & indmtstim & indM tstim + +% OUTPUTS +if nargin<3 + + +else + GFP=stable_state; + DE=trans_state; + DEm=0; +end +%%%%%%%%%%%%%%%% +% Subfunctions % +%%%%%%%%%%%%%%%% + +function [tm,tM]=intermediate_values(curve,ind,thres) +% Find the nearest indices before and after ind such that curve==thres +tm=ind; +tM=ind; + +if curve(ind)1 + tm=tm-1; + end + + while curve(tM)thres & tm>1 + tm=tm-1; + end + + while curve(tM)>thres & tM x(i-1) + if x(i) > x(i+1) % definite max + lmval =[lmval x(i)]; + indd = [ indd i]; + elseif x(i)==x(i+1)&x(i)==x(i+2) % 'long' flat spot + %lmval =[lmval x(i)]; %1 comment these two lines for strict case + %indd = [ indd i]; %2 when only definite max included + i = i + 2; % skip 2 points + elseif x(i)==x(i+1) % 'short' flat spot + %lmval =[lmval x(i)]; %1 comment these two lines for strict case + %indd = [ indd i]; %2 when only definite max included + i = i + 1; % skip one point + end + end + i = i + 1; +end +if filt>0 & ~isempty(indd), + if (indd(1)<= 3)|(indd(length(indd))+2>length(xx)), + rng=1; %check if index too close to the edge + else rng=2; + end + for ii=1:length(indd), % Find the real maximum value + [val(ii) iind(ii)] = max(xx(indd(ii) -rng:indd(ii) +rng)); + iind(ii)=indd(ii) + iind(ii) -rng-1; + end + indd=iind; lmval=val; +else +end + + + + +function [lmval,indd]=lmin(xx,filt) +%LMIN function [lmval,indd]=lmin(x,filt) +% Find local minima in vector X, where LMVAL is the output +% vector with minima values, INDD is the corresponding indeces +% FILT is the number of passes of the small running average filter +% in order to get rid of small peaks. Default value FILT =0 (no +% filtering). FILT in the range from 1 to 3 is usially sufficient to +% remove most of a small peaks +% Examples: +% xx=0:0.01:35; y=sin(xx) + cos(xx ./3); +% plot(xx,y); grid; hold on; +% [a b]=lmin(y,2) +% plot(xx(a),y(a),'r+') +% see also LMAX, MAX, MIN + +% +%**************************************************| +% Serge Koptenko, Guigne International Ltd., | +% phone (709)895-3819, fax (709)895-3822 | +%--------------06/03/97----------------------------| + +x=xx; +len_x = length(x); +fltr=[1 1 1]/3; +if nargin <2, filt=0; +else + x1=x(1); x2=x(len_x); + + for jj=1:filt, + c=conv(fltr,x); + x=c(2:len_x+1); + x(1)=x1; + x(len_x)=x2; + end +end + +lmval=[]; +indd=[]; +i=2; % start at second data point in time series + +while i < len_x-1, + if x(i) < x(i-1) + if x(i) < x(i+1) % definite min + lmval =[lmval x(i)]; + indd = [ indd i]; + + elseif x(i)==x(i+1)&x(i)==x(i+2) % 'long' flat spot + %lmval =[lmval x(i)]; %1 comment these two lines for strict case + %indd = [ indd i]; %2 when only definite min included + i = i + 2; % skip 2 points + + elseif x(i)==x(i+1) % 'short' flat spot + %lmval =[lmval x(i)]; %1 comment these two lines for strict case + %indd = [ indd i]; %2 when only definite min included + i = i + 1; % skip one point + end + end + i = i + 1; +end + +if filt>0 & ~isempty(indd), + if (indd(1)<= 3)|(indd(length(indd))+2>length(xx)), + rng=1; %check if index too close to the edge + else rng=2; + end + + for ii=1:length(indd), + [val(ii) iind(ii)] = min(xx(indd(ii) -rng:indd(ii) +rng)); + iind(ii)=indd(ii) + iind(ii) -rng-1; + end + indd=iind; lmval=val; +else +end \ No newline at end of file diff --git a/cartool/converts.m b/cartool/converts.m new file mode 100644 index 0000000..613cc98 --- /dev/null +++ b/cartool/converts.m @@ -0,0 +1,16 @@ +cd('D:\ndiayek\data\rings') +x=load('random02-Tr18_data_trial_1'); +c=load('random02-Tr18_channel.mat'); +[y,ic]=getMEGChannels(c.Channel); +f=x.F(i,:); + +fid = fopen('random02-Tr18_data_trial_1.ep','wt'); +for t=1:2125 + for i=1:151 + fprintf(fid,'%g ',f(i,t)); + end + fprintf(fid,'\n'); +end + +fclose(fid); + \ No newline at end of file diff --git a/cartool/ctf2cartool.m b/cartool/ctf2cartool.m new file mode 100644 index 0000000..61ba76e --- /dev/null +++ b/cartool/ctf2cartool.m @@ -0,0 +1,40 @@ +function [] = ctf2cartool(ctf) +%CTF2CARTOOL - Converts CTF M/EEG data to .ep text file and .xyz channel file +% [] = ctf2cartool(input) +% +% Example +% >> ctf=ctf_read_meg4('folder.ds',[],'meg'); +% >> ctf2cartool(ctf) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-01-30 Creation +% +% ----------------------------- Script History --------------------------------- + +fid = fopen([ctf.folder(1:end-3) '.ep'],'wt'); +for t=1:size(ctf.data,1); + for i=1:size(ctf.data,2); + fprintf(fid,'%g ',ctf.data(t,i)); + end + fprintf(fid,'\n'); +end +fclose(fid); + +nsens=length(ctf.sensor.label); + +fid = fopen([ctf.folder(1:end-3) '_channels.xyz'],'wt'); +fprintf(fid,'%d 1', nsens); +for i=1:nsens + fprintf(fid,'%g %g %g ',ctf.sensor.location(:,i)); + fprintf(fid,'%s\n',ctf.sensor.label{i}); +end +fclose(fid); \ No newline at end of file diff --git a/cartool/event2mrkfile.m b/cartool/event2mrkfile.m new file mode 100644 index 0000000..b2030a2 --- /dev/null +++ b/cartool/event2mrkfile.m @@ -0,0 +1,29 @@ +function [] = event2mrkfile(mrkfile,event,srate,pnts) +%EVENT2MRKFILE - Writes EEGLAB events to .MRK marker (Cartool) +% [] = event2mrkfile(event,srate) +% +% Example +% >> event2mrkfile +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-04-04 Creation +% +% ----------------------------- Script History --------------------------------- + +fid=fopen(mrkfile, 'wt'); +fprintf(fid,'TL02\n') +for i=1:length(event) + fprintf(fid,'\t%d\t\t', round(event(i).latency)); + fprintf(fid,'%d\t\t', round(event(i).latency+event(i).duration)); + fprintf(fid,'"%02d"\n', event(i).type); +end +fclose(fid) \ No newline at end of file diff --git a/cartool/pierre/computeavgref.m b/cartool/pierre/computeavgref.m new file mode 100644 index 0000000..1cd031c --- /dev/null +++ b/cartool/pierre/computeavgref.m @@ -0,0 +1,23 @@ +function avgref=computeavgref(thedata) +% computeavgref: computes the average reference of a data set +% +% inputs: data as a 2-D numeric array where dimension 1 contains the +% timeframes, dimension 2 contains the channels +% +% outputs: average reference as a 1-D numeric array that contains the +% average reference at each timeframe +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% define number of channels and time frames +numtimeframes=size(thedata,1); +numchannels=size(thedata,2); + +% compute average reference +avgref=zeros(numtimeframes,1); +for i=1:numtimeframes + avgref(i)=sum(thedata(i,:))/numchannels; +end \ No newline at end of file diff --git a/cartool/pierre/computedataagainstref.m b/cartool/pierre/computedataagainstref.m new file mode 100644 index 0000000..fc9c382 --- /dev/null +++ b/cartool/pierre/computedataagainstref.m @@ -0,0 +1,34 @@ +function thedata=computedataagainstref(thedata,ref) +% computedataagainstref: changes the reference of a data set +% +% inputs: data as a 2-D numeric array where dimension 1 contains the +% timeframes, dimension 2 contains the channels; ref as either a number +% (1-D numeric array) or the 'avgref' string for average reference +% +% outputs: data as a 2-D numeric array where dimension 1 contains the +% timeframes, dimension 2 contains the channels +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% define number of channels and time frames +numtimeframes=size(thedata,1); +numchannels=size(thedata,2); + +% compute data against selected reference +if ischar(ref)==1&strcmp(ref,'avgref')==1 + avgref=computeavgref(thedata); + for i=1:numtimeframes + thedata(i,:)=thedata(i,:)-avgref(i); + end +elseif ischar(ref)==1&strcmp(ref,'avgref')==0 + error('Unknown code for reference'); +elseif isnumeric(ref)==1&ref>=1&ref<=numchannels + for i=1:numtimeframes + thedata(i,:)=thedata(i,:)-thedata(i,ref); + end +elseif isnumeric(ref)==1&(ref<1|ref>numchannels); + error('Reference specified does not exist'); +end \ No newline at end of file diff --git a/cartool/pierre/computedissandsc.m b/cartool/pierre/computedissandsc.m new file mode 100644 index 0000000..9ff17d2 --- /dev/null +++ b/cartool/pierre/computedissandsc.m @@ -0,0 +1,33 @@ +function [diss,sc]=computedissandsc(thedata1,thedata2) +% computediss: computes dissimilarity and spatial correlation between 2 +% data sets +% +% inputs: data as 2-D numeric arrays where dimension 1 contains the +% timeframes, dimension 2 contains the channels +% +% outputs: diss and sc as 1-D numeric arrays that contain the +% dissimilarity and spatial correlation at each timeframe +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% verify equal number of channels and time frames +if size(thedata1,1)~=size(thedata2,1) + error('Number of timeframes is different'); +elseif size(thedata1,2)~=size(thedata2,2) + error('Number of channels is different'); +end + +% compute dissimilarity +diss=zeros(size(thedata1,1),1); +for i=1:size(thedata1,1) + diss(i)=sqrt(sum((thedata1(i,:)-thedata2(i,:)).^2)/size(thedata1,2)); +end + +% compute spatial correlation +sc=zeros(size(diss,1),1); +for i=1:size(diss,1) + sc(i)=(2-diss(i)^2)/2; +end diff --git a/cartool/pierre/computegfp.m b/cartool/pierre/computegfp.m new file mode 100644 index 0000000..e149384 --- /dev/null +++ b/cartool/pierre/computegfp.m @@ -0,0 +1,24 @@ +function gfp=computegfp(thedata) +% computegfp: calculates the global field power of a data set +% +% inputs: data as a 2-D numeric array where dimension 1 contains the +% timeframes, dimension 2 contains the channels +% +% outputs: global field power as a 1-D numeric array that contains the +% global field power at each timeframe +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% define number of channels and time frames +numtimeframes=size(thedata,1); +numchannels=size(thedata,2); + +% compute global field power +gfp=zeros(numtimeframes,1); +avgref=computeavgref(thedata); +for i=1:numtimeframes + gfp(i)=sqrt(sum((thedata(i,:)-avgref(i)).^2)/numchannels); +end \ No newline at end of file diff --git a/cartool/pierre/openels.m b/cartool/pierre/openels.m new file mode 100644 index 0000000..ac5ff74 --- /dev/null +++ b/cartool/pierre/openels.m @@ -0,0 +1,38 @@ +% opens a Cartool electrode coordinates file (.els) +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% check whether filename exists +if exist('filename')==0 + error('filename is not defined') +end + +% open filename for reading in text mode +fid=fopen(openfilename,'rt'); + +% read file +els=textscan(fid,'%s','delimiter','/n'); +els=els{1}; +magicnumber=els{1}; +totalnumelectrodes=str2num(els{2}); +numclusters=str2num(els{3}); +pointer=4; + +for i=1:numclusters + clusters(i).name=els{pointer}; + clusters(i).numelectrodes=str2num(els{pointer+1}); + clusters(i).dimension=str2num(els{pointer+2}); + pointer=pointer+3; + for j=1:clusters(i).numelectrodes + clusters(i).electrodes(j).name=sscanf(els{pointer},'%*f %*f %*f %s',1); + clusters(i).electrodes(j).x=sscanf(els{pointer},'%f',1); + clusters(i).electrodes(j).y=sscanf(els{pointer},'%*f %f',1); + clusters(i).electrodes(j).z=sscanf(els{pointer},'%*f %*f %f',1); + pointer=pointer+1; + end +end + +fclose(fid); \ No newline at end of file diff --git a/cartool/pierre/openeph.m b/cartool/pierre/openeph.m new file mode 100644 index 0000000..84258a5 --- /dev/null +++ b/cartool/pierre/openeph.m @@ -0,0 +1,59 @@ +function [numchannels,numtimeframes,samplingrate,thedata]=openeph(openfilename) +% openeph: opens a Cartool evoked potential data file (.ep(h)) +% +% inputs: full path and name of the file to open +% +% outputs: number of channels, number of timeframes (and sampling rate for +% .eph files) as 1-D numeric arrays; data as a 2-D numeric array where +% dimension 1 contains the timeframes, dimension 2 contains the channels +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% open filename for reading in text mode +fid=fopen(openfilename,'rt'); + +% for .eph files +if strcmp(openfilename(end-3:end),'.eph')==1 + + % read header + eph=textscan(fid,'%s','delimiter','/n'); + eph=eph{1}; + numchannels=sscanf(eph{1},'%f',1); + numtimeframes=sscanf(eph{1},'%*f %f',1); + samplingrate=sscanf(eph{1},'%*f %*f %f',1); + + % prepare for reading data + formatstring='%f'; + if numchannels>1 + for i=1:numchannels-1 + formatstring=[formatstring ' %f']; + end + end + + % read data + thedata=zeros(numtimeframes,numchannels); + for i=1:numtimeframes + thedata(i,:)=sscanf(eph{i+1},formatstring); + end + +% for .ep files +elseif strcmp(openfilename(end-2:end),'.ep')==1 + thedata=''; + while ~feof(fid) + thedataline=fgetl(fid); + thedata=strvcat(thedata,thedataline); + end + thedata=str2num(thedata); + numtimeframes=size(thedata,1); + numchannels=size(thedata,2); + samplingrate=0; + +else + error('incorrect file type'); +end + +% close file +fclose(fid); \ No newline at end of file diff --git a/cartool/pierre/openfreq.m b/cartool/pierre/openfreq.m new file mode 100644 index 0000000..d35c2ca --- /dev/null +++ b/cartool/pierre/openfreq.m @@ -0,0 +1,53 @@ +function [numchannels,numfrequencies,numblocks,samplingrate,channels,frequencies,thedata]=openfreq(openfilename) +% openfreq: opens a Cartool frequency data file (.freq) +% +% inputs: full path and name of the file to open +% +% outputs: number of channels, number of frequencies, number of blocks and +% sampling rate as 1-D numeric arrays; frequencies as 1-D numeric array +% containing the frequencies; data as a 2-D numeric array where dimension 1 +% contains the frequencies, dimension 2 contains the channels, dimension 3 +% contains the blocks (=timeframes) +% +% ATTENTION: this function is unable to read FFT Complex files yet! +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% open file for reading +fid=fopen(openfilename,'r'); + +% read fixed part of header +version=strcat(fread(fid,4,'int8=>char')'); +type=strcat(fread(fid,32,'int8=>char')'); +numchannels=fread(fid,1,'int32'); +numfrequencies=fread(fid,1,'int32'); +numblocks=fread(fid,1,'int32'); +samplingrate=fread(fid,1,'double'); +blockfrequency=fread(fid,1,'double'); +year=fread(fid,1,'int16'); +month=fread(fid,1,'int16'); +day=fread(fid,1,'int16'); +hour=fread(fid,1,'int16'); +minute=fread(fid,1,'int16'); +second=fread(fid,1,'int16'); +millisecond=fread(fid,1,'int16'); + +% read variable part of header +channels=strcat(fread(fid,[8,numchannels],'int8=>char')'); +frequencies=strcat(fread(fid,numfrequencies*16,'int8=>char')'); + +% read data +thedata=zeros(numfrequencies,numchannels,numblocks); +if strcmp(type,'FFT Norm')|strcmp(type,'FFT Norm2')|strcmp(type,'FFT Approximation')==1 + for i=1:numblocks + thedata(:,:,i)=fread(fid,[numfrequencies,numchannels],'float32'); + end +elseif strcmp(type,'FFT Complex')==1 + error('Sorry, I do not know how to read FFT Complex files yet! :)'); +end + +% close file +fclose(fid); \ No newline at end of file diff --git a/cartool/pierre/opensef.m b/cartool/pierre/opensef.m new file mode 100644 index 0000000..5626b15 --- /dev/null +++ b/cartool/pierre/opensef.m @@ -0,0 +1,39 @@ +function [numchannels,numtimeframes,samplingrate,thedata]=opensef(openfilename) +% opensef: opens a Cartool simple EEG data file (.sef) +% +% inputs: full path and name of the file to open +% +% outputs: number of channels, number of timeframes and sampling rate as +% 1-D numeric arrays; data as a 2-D numeric array where dimension 1 +% contains the timeframes, dimension 2 contains the channels +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% open filename for reading +fid=fopen(openfilename,'r'); + +% read fixed part of header +version=strcat(fread(fid,4,'int8=>char')'); +numchannels=fread(fid,1,'int32'); +numauxchannels=fread(fid,1,'int32'); +numtimeframes=fread(fid,1,'int32'); +samplingrate=fread(fid,1,'float32'); +year=fread(fid,1,'int16'); +month=fread(fid,1,'int16'); +day=fread(fid,1,'int16'); +hour=fread(fid,1,'int16'); +minute=fread(fid,1,'int16'); +second=fread(fid,1,'int16'); +millisecond=fread(fid,1,'int16'); + +% read variable part of header +channels=strcat(fread(fid,[8,numchannels],'int8=>char')'); + +% read data +thedata=fread(fid,[numchannels,numtimeframes],'float32')'; + +% close file +fclose(fid); \ No newline at end of file diff --git a/cartool/pierre/saveeph.m b/cartool/pierre/saveeph.m new file mode 100644 index 0000000..f13573e --- /dev/null +++ b/cartool/pierre/saveeph.m @@ -0,0 +1,36 @@ +function saveeph(savefilename,thedata,varargin) +% saveeph: saves data as a Cartool evoked potential data file (.ep(h/sd/se)) +% +% inputs: full path and name of the file to save, data as a 2-D numeric +% array where dimension 1 contains the timeframes, dimension 2 contains the +% channels, (optional) samplingrate as 1-D numeric array passed as +% 3rd argument +% +% outputs: .ep(h/sd/se) file +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +if strcmp(savefilename(end-3:end),'.eph')==1 + numtimeframes=size(thedata,1); + numchannels=size(thedata,2); + samplingrate=varargin{1}; + theheader=[numchannels numtimeframes samplingrate]; + dlmwrite(savefilename,theheader,'\t'); + dlmwrite(savefilename,thedata,'delimiter','\t','-append'); +elseif strcmp(savefilename(end-2:end),'.ep')==1 + dlmwrite(savefilename,thedata,'delimiter','\t','-append'); +elseif strcmp(savefilename(end-4:end),'.epsd')==1|strcmp(savefilename(end-4:end),'.epse')==1 + if nargin==2 + dlmwrite(savefilename,thedata,'delimiter','\t','-append'); + elseif nargin==3 + numtimeframes=size(thedata,1); + numchannels=size(thedata,2); + samplingrate=varargin{1}; + theheader=[numchannels numtimeframes samplingrate]; + dlmwrite(savefilename,theheader,'\t'); + dlmwrite(savefilename,thedata,'delimiter','\t','-append'); + end +end \ No newline at end of file diff --git a/cartool/pierre/savesef.m b/cartool/pierre/savesef.m new file mode 100644 index 0000000..75c83d0 --- /dev/null +++ b/cartool/pierre/savesef.m @@ -0,0 +1,61 @@ +function savesef(savefilename,thedata,samplingrate) +% savesef: saves data as a Cartool simple EEG data file (.sef) +% +% inputs: full path and name of the file to save, data as a 2-D numeric +% array where dimension 1 contains the timeframes, dimension 2 contains the +% channels, samplingrate as 1-D numeric array +% +% outputs: .sef file +% +% Cartool: http://brainmapping.unige.ch/Cartool.htm +% +% author of this script: pierre.megevand@medecine.unige.ch + + +% define fixed part of header +version='SE01'; +numchannels=size(thedata,2); +numauxchannels=0; +numtimeframes=size(thedata,1); +year=0; +month=0; +day=0; +hour=0; +minute=0; +second=0; +millisecond=0; + +% open savefilename for writing +fid=fopen(savefilename,'w'); + +%write fixed part of header +fwrite(fid,version,'int8'); +fwrite(fid,numchannels,'int32'); +fwrite(fid,numauxchannels,'int32'); +fwrite(fid,numtimeframes,'int32'); +fwrite(fid,samplingrate,'float32'); +fwrite(fid,year,'int16'); +fwrite(fid,month,'int16'); +fwrite(fid,day,'int16'); +fwrite(fid,hour,'int16'); +fwrite(fid,minute,'int16'); +fwrite(fid,second,'int16'); +fwrite(fid,millisecond,'int16'); + +% define and write variable part of header +for i=1:numchannels + fwrite(fid,101,'int8'); + currentchannel=uint8(num2str(i)); + for j=1:size(currentchannel,2) + fwrite(fid,currentchannel(j),'int8'); + end + for k=j+2:8 + fwrite(fid,0,'int8'); + end +end + +% write data +count=fwrite(fid,thedata','float32'); + +% close file +fclose(fid); \ No newline at end of file diff --git a/cartool/read_eeg.m b/cartool/read_eeg.m new file mode 100644 index 0000000..de07ae9 --- /dev/null +++ b/cartool/read_eeg.m @@ -0,0 +1,47 @@ +%struct TSefHeader{ +% int Version; // magic number filled with the wide char 'SE01' +% int NumElectrodes; // total number of electrodes +% int NumAuxElectrodes; // out of which are auxiliaries +% int NumTimeFrames; // time length +% float SamplingFrequency; // frequency in Hertz +% short Year; // Date of the recording +% short Month; // (set to 00-00-0000 if unknown) +% short Day; +% short Hour; // Time of the recording +% short Minute; // (set to 00:00:00:0000 if unknown) +% short Second; +% short Millisecond; +% }; +% +% Variable part of the header: +% The names of the channels, as a matrix of NumElectrodes x 8 chars. +%typedef char TSefChannelName[8]; // 1 electrode name +% +% To allow an easy calculation of the data origin, be aware that names are +% always stored on 8 bytes, even if the string length is smaller than that. +% In this case, the remaining part is padded with bytes set to 0, f.ex. two +% consecutive names: +% +% binary values 70 112 122 00 00 00 00 00 65 70 55 00 00 00 00 00 ... +% string equivalence F P z \0 A F 7 \0 +% +% Data part: +% Starting at file position: +% sizeof ( TSefHeader ) + 8 * NumElectrodes +% data are stored as a float (Little Endian convention - PC) matrix written row by row: +% float data [ NumTimeFrames ][ NumElectrodes ]; + +frewind(fid) + +eeg.Version = fread(fid,1,'int') +eeg.NumElectrodes = fread(fid,1,'int') +eeg.NumAuxElectrodes = fread(fid,1,'int') +eeg.NumTimeFrames = fread(fid,1,'int'); +eeg.SamplingFrequency = fread(fid,1,'float'); +eeg.Year=fread(fid,1,'short'); +eeg.Month = fread(fid,1,'short'); +eeg.Day = fread(fid,1,'short'); +eeg.Hour = fread(fid,1,'short'); +eeg.Minute = fread(fid,1,'short'); +eeg.Second = fread(fid,1,'short'); +eeg.Millisecond = fread(fid,1,'short'); diff --git a/cartool/read_eph.m b/cartool/read_eph.m new file mode 100644 index 0000000..9082de9 --- /dev/null +++ b/cartool/read_eph.m @@ -0,0 +1,7 @@ +function [eeg] =read_eph(ephfile) +% read_eph() - Reads EPH file (Cartool) + +eeg.Filename = ephfile; +[eeg.NumElectrodes eeg.NumTimeFrames eeg.SamplingFrequency]=textread(ephfile,'%d %d %d',1); +eeg.data=textread(ephfile,'%f',eeg.NumElectrodes*eeg.NumTimeFrames , 'headerlines',1); +eeg.data=reshape(eeg.data,[eeg.NumElectrodes eeg.NumTimeFrames]); diff --git a/cartool/read_is.m b/cartool/read_is.m new file mode 100644 index 0000000..27765a1 --- /dev/null +++ b/cartool/read_is.m @@ -0,0 +1,28 @@ +function [K]=read_is(seffile) +%read_is() - reads IS inverse solution file (Cartool) +% [K]=read_is(isfile) +% K is the transposed inverse matrix [M electrodes]-by-[N sources] +% or possibly, if vectorial, [M electrodes]-by-[N sources]-by-3 + +fid=fopen(seffile, 'rb'); +tag=char(fread(fid,4,'char')'); +switch (tag) + case 'IS01' + datatype='float32'; + case 'IS02' + datatype='double'; + otherwise + error('Unknown tag: %s', tag) +end +ne=fread(fid,1,'int32'); +ns=fread(fid,1,'int32'); +scalar=double(fread(fid,1,'char')); +K=fread(fid,ne*ns*(3 - 2*scalar),datatype); +K=reshape(K,[ne ns (3 - 2*scalar) ]); + +% We keep the transposed inverse matrix. +% if scalar +% K=transpose(K); +% else +% K=permute(K, [2 3 1]); +% end diff --git a/cartool/read_mrk.m b/cartool/read_mrk.m new file mode 100644 index 0000000..f44a75f --- /dev/null +++ b/cartool/read_mrk.m @@ -0,0 +1,33 @@ +function [mrk]=read_mrk(mrkfile) +%read_mrk - reads .MRK marker file (Cartool) + +ascii=1; + +if ascii + mrk.Filename = mrkfile; + mrk.Name=textread(mrkfile, '%s', 1); + [mrk.Position mrk.To mrk.Type]=textread(mrkfile, '%d %d %s', 'headerlines',1); + +else + fid=fopen('Waridel\Alan_UG.EEG.MRK', 'r') + % struct mrkheader { + % char magic[4]; // always 'TL01' + % } mrkheader; // size 4 + magic=char(fread(fid,4,'char')'); + + % And the format for a single marker is: + % struct onemrk { + % long Position; // from this TF + % long To; // to this TF + % ushort Code; // trigger code + % ushort Type; // should always be 0x2 for a marker + % ushort Dummy; // not used, for the user + % char Name[6]; // name of the tag + % } onemrk; // size 20 + mrk.Position=fread(fid,1,'uint32'); + mrk.To=fread(fid,1,'uint32'); + mrk.Type=fread(fid,1,'uint16'); + mrk.Dummy=fread(fid,1,'uint16'); + mrk.Name=char(fread(fid,6,'char')); + fclose(fid) +end \ No newline at end of file diff --git a/cartool/read_ris.m b/cartool/read_ris.m new file mode 100644 index 0000000..64c8f6f --- /dev/null +++ b/cartool/read_ris.m @@ -0,0 +1,28 @@ +function [R,SF]=read_ris(risfile) +%read_ris() - reads RIS result of inverse solution file (Cartool) +% [R,SF]=read_ris(risfile) +% R is the values +% FS ssampling frequency +fid=fopen(risfile, 'rb'); +tag=char(fread(fid,4,'char')'); +switch (tag) + case 'RI01' + otherwise + warning('Unknown tag in file header: %s', tag) +end + +ns=fread(fid,1,'int32'); +nt=fread(fid,1,'int32'); +SF=fread(fid,1,'float32'); +isinversescalar=double(fread(fid,1,'char')); +K=fread(fid,ns*(3 - 2*isinversescalar)*nt,datatype); +K=reshape(K,[ns*(3 - 2*isinversescalar) nt]); +K=transpose(K); +K=reshape(K,[nt ns (3 - 2*isinversescalar) ]); + +% We keep the transposed inverse matrix. +% if scalar +% K=transpose(K); +% else +% K=permute(K, [2 3 1]); +% end diff --git a/cartool/read_sef.m b/cartool/read_sef.m new file mode 100644 index 0000000..7c0ca1c --- /dev/null +++ b/cartool/read_sef.m @@ -0,0 +1,55 @@ +function [eeg]=read_sef(seffile) +%read_sef() - reads SEF file (Cartool) +% [eeg]=read_sef(seffile) +fid=fopen(seffile, 'rb'); + +%struct TSefHeader{ +% int Version; // magic number filled with the wide char 'SE01' +% int NumElectrodes; // total number of electrodes +% int NumAuxElectrodes; // out of which are auxiliaries +% int NumTimeFrames; // time length +% float SamplingFrequency; // frequency in Hertz +% short Year; // Date of the recording +% short Month; // (set to 00-00-0000 if unknown) +% short Day; +% short Hour; // Time of the recording +% short Minute; // (set to 00:00:00:0000 if unknown) +% short Second; +% short Millisecond; +% }; +% +% Variable part of the header: +% The names of the channels, as a matrix of NumElectrodes x 8 chars. +%typedef char TSefChannelName[8]; // 1 electrode name +% +% To allow an easy calculation of the data origin, be aware that names are +% always stored on 8 bytes, even if the string length is smaller than that. +% In this case, the remaining part is padded with bytes set to 0, f.ex. two +% consecutive names: +% +% binary values 70 112 122 00 00 00 00 00 65 70 55 00 00 00 00 00 ... +% string equivalence F P z \0 A F 7 \0 +% +% Data part: +% Starting at file position: +% sizeof ( TSefHeader ) + 8 * NumElectrodes +% data are stored as a float (Little Endian convention - PC) matrix written row by row: +% float data [ NumTimeFrames ][ NumElectrodes ]; + +frewind(fid) + +eeg.Version = char(fread(fid,4,'uint8')'); % fread(fid,1,'int'); +eeg.NumElectrodes = fread(fid,1,'int'); +eeg.NumAuxElectrodes = fread(fid,1,'int'); +eeg.NumTimeFrames = fread(fid,1,'int'); +eeg.SamplingFrequency = fread(fid,1,'float'); +eeg.Year = fread(fid,1,'short'); +eeg.Month = fread(fid,1,'short'); +eeg.Day = fread(fid,1,'short'); +eeg.Hour = fread(fid,1,'short'); +eeg.Minute = fread(fid,1,'short'); +eeg.Second = fread(fid,1,'short'); +eeg.Millisecond = fread(fid,1,'short'); +eeg.TSefChannelName = reshape(char(fread(fid,8*eeg.NumElectrodes,'char')),8,eeg.NumElectrodes)' ; + +eeg.data = reshape(fread(fid,eeg.NumElectrodes*eeg.NumTimeFrames,'float'),eeg.NumElectrodes,eeg.NumTimeFrames); diff --git a/cartool/read_spi.m b/cartool/read_spi.m new file mode 100644 index 0000000..8fd77d4 --- /dev/null +++ b/cartool/read_spi.m @@ -0,0 +1,4 @@ +function [XYZ]=read_spi(spifile) +%read_ris() - reads SPI Solution Points Irregularly spaced file (Cartool) +% [XYZ]=read_spi(spifile) +[XYZ(:,1) XYZ(:,2) XYZ(:,3)]=textread(spifile,'%f %f %f'); \ No newline at end of file diff --git a/cartool/read_xyz.m b/cartool/read_xyz.m new file mode 100644 index 0000000..0645f1c --- /dev/null +++ b/cartool/read_xyz.m @@ -0,0 +1,6 @@ +function [XYZ,labels,R]=read_xyz(xyzfile) +%read_xyz() - reads XYZ electrode coordinates file (Cartool) +% [XYZ,labels,R]=read_xyz(xyzfile) +[ne,R]=textread(xyzfile,'%d %f',1); + +[XYZ(:,1) XYZ(:,2) XYZ(:,3), labels]=textread(xyzfile,'%f %f %f %s', ne, 'headerlines',1); \ No newline at end of file diff --git a/cartool/write_sef.m b/cartool/write_sef.m new file mode 100644 index 0000000..86dba3d --- /dev/null +++ b/cartool/write_sef.m @@ -0,0 +1,78 @@ +function [] = write_sef(seffile,eeg,varargin) +%write_sef - Writes a Simple EEG Format file (Cartool) +% [] = write_sef(EEG) +% +% Example +% >> write_sef +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-04-04 Creation +% +% ----------------------------- Script History --------------------------------- + +if isfield(eeg,'chanlocs') + % EEGLAB format + EEG=eeg; + eeg=[]; + eeg.data=EEG.data; + [eeg.NumElectrodes, eeg.NumTimeFrames] = size(EEG.data) + eeg.TSefChannelName = strvcat({EEG.chanlocs.labels}); + eeg.TSefChannelName =[eeg.TSefChannelName repmat(' ', size(eeg.TSefChannelName,1), max(0,8-size(eeg.TSefChannelName,2)))]; + eeg.TSefChannelName(eeg.TSefChannelName==32)=0; + if eeg.NumElectrodes ~= EEG.nbchan | eeg.NumElectrodes ~= numel(eeg.TSefChannelName)/8 + error('check electrode number, size of data and chanlocs') + end + eeg.NumAuxElectrodes = eeg.NumElectrodes-64; + eeg.SamplingFrequency = EEG.srate; + +elseif isnumeric(eeg) + data=eeg; + eeg=[]; + eeg.data=data; + eeg.NumElectrodes = size(eeg.data,1); + eeg.NumAuxElectrodes = 0; + eeg.TSefChannelName = sprintf('e%03d\0\0\0\0',1:eeg.NumAuxElectrodes); + + clear data; +else + error('Wrong type of input: Should be raw data OR EEGLAB structure.') +end + +fid=fopen(seffile, 'wb'); +eeg.Year = 0; +eeg.Month = 0; +eeg.Day = 0; +eeg.Hour = 0; +eeg.Minute = 0; +eeg.Second = 0; +eeg.Millisecond = 0; + +eeg.Version = 'SE01'; + +fwrite(fid,eeg.Version, 'uchar'); +fwrite(fid,eeg.NumElectrodes,'int32'); +fwrite(fid,eeg.NumAuxElectrodes,'int32'); +fwrite(fid,eeg.NumTimeFrames,'int32'); +fwrite(fid,eeg.SamplingFrequency,'float32'); + +fwrite(fid,eeg.Year,'int16'); +fwrite(fid,eeg.Month,'int16'); +fwrite(fid,eeg.Day,'int16'); +fwrite(fid,eeg.Hour,'int16'); +fwrite(fid,eeg.Minute,'int16'); +fwrite(fid,eeg.Second,'int16'); +fwrite(fid,eeg.Millisecond,'int16'); + +fwrite(fid,eeg.TSefChannelName(:,:)','uchar'); +fwrite(fid,eeg.data,'float32') + +fclose(fid) diff --git a/catstructs.m b/catstructs.m new file mode 100644 index 0000000..60c2eef --- /dev/null +++ b/catstructs.m @@ -0,0 +1,118 @@ +function [z]=catstructs(dim,x,y,keepfields) +% catstructs - Concatenate structures independently of field order/presence +% +% [Z]=catstructs(dim, X,Y) will concatenate structures X and Y into Z along +% dimension dim which MUST be 1 (ie. vertical concatenation) +% +% [Z]=catstructs(dim,X,Y,keepfields) +% keepfields: 1/0(default), keep non-matching fields. Missing values +% will be set to [] +if ~isequal(dim,1) + error('Concatenated dimension MUST be 1 (until further development!)') +end +if ~isvector(x) | ~isvector(y) + error('Structures MSUT be unidimensional') +end +if nargin<4 + keepfields=0; +end + +z=x(:); +y=y(:); + +fy=fieldnames(y); +if ~keepfields + f=fieldnames(z); + z=rmfield(z,f(~ismember(f,fy))); + y=rmfield(y,fy(~ismember(fy,f))); + fy=fy(ismember(fy,f)); +end +% if isempty(z) +% z=y; +% end +for j=1:length(y) + for i=1:length(fy) + if i==1 + z(end+1).(fy{i})= y(j).(fy{i}); + else + z(end).(fy{i})= y(j).(fy{i}); + end + end +end + + + +return + +% the following bugs when any argument is a struct array + + + +function A = catstruct(varargin) +% CATSTRUCT - concatenate structures +% +% X = CATSTRUCT(S1,S2,S3,...) concates the structures S1, S2, ... into one +% structure X. +% +% A.name = 'Me' ; +% B.income = 99999 ; +% X = CATSTRUCT(A,B) -> +% X.name = 'Me' ; +% X.income = 99999 ; +% +% CATSTRUCT(S1,S2,'sorted') will sort the fieldnames alphabetically. +% +% If a fieldname occurs more than once in the argument list, only the last +% occurence is used, and the fields are alphabetically sorted. +% +% To sort the fieldnames of a structure A use: +% A = CATSTRUCT(A,'sorted') ; +% +% See also CAT, STRUCT, FIELDNAMES, STRUCT2CELL + +% 2005 Jos van der Geest + +N = nargin ; + +error(nargchk(1,Inf,N)) ; + +if ~isstruct(varargin{end}), + if isequal(varargin{end},'sorted'), + sorted = 1 ; + N = N-1 ; + if N < 1, + A = [] ; + return + end + else + error('Last argument should be a structure, or the string "sorted".') ; + end +else + sorted = 0 ; +end + +for ii=1:N, + X = varargin{ii} ; + if ~isstruct(X), + error(['Argument #' num2str(ii) ' is not a structure.']) ; + end + FN{ii} = fieldnames(X) ; + VAL{ii} = struct2cell(X) ; +end + +FN = cat(1,FN{:}) +VAL = cat(1,VAL{:}) ; +[UFN,ind] = unique(FN) ; + +if length(UFN) ~= length(FN), + warning('Duplicate fieldnames found. Last value is used.') ; + sorted = 1 ; +end + +if sorted, + VAL = VAL(ind) ; + FN = FN(ind) +end + +VF = reshape([FN VAL].',1,[]) ; +A = struct(VF{:}) ; diff --git a/ccaxis.m b/ccaxis.m new file mode 100644 index 0000000..b09f5b2 --- /dev/null +++ b/ccaxis.m @@ -0,0 +1,46 @@ +function [varargout] = ccaxis(clim) +%CCAXIS - Contour compatible CAXIS +% [] = ccaxis(clim) +% Works ALSO when there are contours in the plot +% Example +% >> ccaxis([0 1]) +% +% See also: caxis + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-27 Creation +% +% ----------------------------- Script History --------------------------------- + +caxis(clim) +ha=gca; +ch=get(gca, 'Children'); +peers=findobj(get(gcf, 'Children'),'type','axes'); +hcont=findobj(ch, 'type', 'hggroup'); +if ~isempty(hcont) + cb=findobj(peers, 'tag', 'Colorbar'); + for i=length(cb):-1:1 + hcb=handle(cb); + if ~isequal(double(hcb.axes),ha) + cb(i)=[]; + end + end + if isempty(cb) + cb=colorbar; + end + for i=1:length(cb) + child=get(cb,'children'); + set(cb, 'YLim', clim); + set(child, 'ydata', clim); + end + axes(ha) + delete(cb(~ismember(cb,peers))) +end +varargout={hcont}; \ No newline at end of file diff --git a/cdf.m b/cdf.m new file mode 100644 index 0000000..d00f2fc --- /dev/null +++ b/cdf.m @@ -0,0 +1,77 @@ +function p = cdf(name,x,a1,a2,a3) +%CDF Computes a chosen cumulative distribution function. +% P = CDF(NAME,X,A1) returns the named cumulative distribution +% function, which uses parameter A, at the the values in X. +% P = CDF(NAME,X,A1,A2) returns the named cumulative distribution +% function, which uses parameters a and b, at the the values in X. +% Similarly for P = CDF(NAME,X,A1,A2,A3). +% +% The name can be: 'beta' or 'Beta', 'bino' or 'Binomial', +% 'chi2' or 'Chisquare','exp' or 'Exponential', 'f' or 'F', +% 'gam' or 'Gamma','geo' or 'Geometric','hyge' or 'Hypergeometric', +% 'logn' or 'Lognormal','nbin' or 'Negative Binomial', +% 'ncf' or 'Noncentral F','nct' or 'Noncentral t', +% 'ncx2' or 'Noncentral Chi-square' +% 'norm' or 'Normal','poiss' or 'Poisson','rayl' or 'Rayleigh', +% 't' or 'T','unif' or 'Uniform','unid' or 'Discrete Uniform', +% 'weib' or 'Weibull'. +% +% CDF calls many specialized routines that do the calculations. + +if nargin<2, error('Not enough input arguments'); end + +if ~isstr(name), error('First argument must be distribution name'); end + +if nargin<5, + a3=0; +end +if nargin<4, + a2=0; +end +if nargin<3, + a1=0; +end + +if strcmp(name,'beta') | strcmp(name,'Beta'), + p = betacdf(x,a1,a2); +elseif strcmp(name,'bino') | strcmp(name,'Binomial'), + p = binocdf(x,a1,a2); +elseif strcmp(name,'chi2') | strcmp(name,'Chisquare'), + p = chi2cdf(x,a1); +elseif strcmp(name,'exp') | strcmp(name,'Exponential'), + p = expcdf(x,a1); +elseif strcmp(name,'f') | strcmp(name,'F'), + p = fcdf(x,a1,a2); +elseif strcmp(name,'gam') | strcmp(name,'Gamma'), + p = gamcdf(x,a1,a2); +elseif strcmp(name,'geo') | strcmp(name,'Geometric'), + p = geocdf(x,a1); +elseif strcmp(name,'hyge') | strcmp(name,'Hypergeometric'), + p = hygecdf(x,a1,a2,a3); +elseif strcmp(name,'logn') | strcmp(name,'Lognormal'), + p = logncdf(x,a1,a2); +elseif strcmp(name,'nbin') | strcmp(name,'Negative Binomial'), + p = nbincdf(x,a1,a2); +elseif strcmp(name,'ncf') | strcmp(name,'Noncentral F'), + p = ncfcdf(x,a1,a2,a3); +elseif strcmp(name,'nct') | strcmp(name,'Noncentral T'), + p = nctcdf(x,a1,a2); +elseif strcmp(name,'ncx2') | strcmp(name,'Noncentral Chi-square'), + p = ncx2cdf(x,a1,a2); +elseif strcmp(name,'norm') | strcmp(name,'Normal'), + p = normcdf(x,a1,a2); +elseif strcmp(name,'poiss') | strcmp(name,'Poisson'), + p = poisscdf(x,a1); +elseif strcmp(name,'rayl') | strcmp(name,'Rayleigh'), + p = raylcdf(x,a1); +elseif strcmp(name,'t') | strcmp(name,'T'), + p = tcdf(x,a1); +elseif strcmp(name,'unid') | strcmp(name,'Discrete Uniform'), + p = unidcdf(x,a1); +elseif strcmp(name,'unif') | strcmp(name,'Uniform'), + p = unifcdf(x,a1,a2); +elseif strcmp(name,'weib') | strcmp(name,'Weibull'), + p = weibcdf(x,a1,a2); +else + error('Sorry, the statistics toolbox does not support this distribution.'); +end diff --git a/cell2str.m b/cell2str.m new file mode 100644 index 0000000..bea3e80 --- /dev/null +++ b/cell2str.m @@ -0,0 +1,68 @@ +function t = cell2str(c,sep,s) +%CELL2STR - Convert a cell array into text (i.e. string array) +% [S] = cell2str(C) +% +% Example +% >> celldisp2 +% +% See also: celldisp + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-01 Creation +% +% ----------------------------- Script History --------------------------------- + +%error(nargchk(1,2,nargin,'struct')); +if ~iscell(c), + error('MATLAB:celldisp:notCellArray', 'Must be a cell array.'); +end +if nargin<2, sep = {'-' '|' }; end +if nargin<3, s = inputname(1); end +if isempty(s), s = 'ans'; end + +for i=1:numel(c), + if iscell(c{i}) && ~isempty(c{i}), + t=sprintf( '%s\n%s\n%s',s,repmat(sep{1}, [1 size(s,2)]), cell2str(c{i},sep,[s subs(i,size(c))])); + else + t=sprintf('%s%s =\n',s,subs(i,size(c))); + + if ~isempty(c{i}), + t=sprintf('%s%s',t,); + else + if iscell(c{i}) + disp(' {}') + elseif ischar(c{i}) + disp(' ''''') + elseif isnumeric(c{i}) + disp(' []') + else + [m,n] = size(c{i}); + disp(sprintf('%0.f-by-%0.f %s',m,n,class(c{i}))) + end + end + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = subs(i,siz) +%SUBS Display subscripts + +if length(siz)==2 && any(any(siz==1)) + v = cell(1,1); +else + v = cell(size(siz)); +end +[v{1:end}] = ind2sub(siz,i); + +s = ['{' int2str(v{1})]; +for i=2:length(v), + s = [s ',' int2str(v{i})]; +end +s = [s '}']; \ No newline at end of file diff --git a/cellcat.m b/cellcat.m new file mode 100644 index 0000000..a497d11 --- /dev/null +++ b/cellcat.m @@ -0,0 +1,19 @@ +function X = cellcat(C) +%CELLCAT - Concatenate cell array content +% [X] = cellcat(C) is equivalent to X=[C{:}] +% +% See also: cell2mat() + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-04-08 Creation +% +% ----------------------------- Script History --------------------------------- + +X = [C{:}]; \ No newline at end of file diff --git a/cellfun2.m b/cellfun2.m new file mode 100644 index 0000000..a035608 --- /dev/null +++ b/cellfun2.m @@ -0,0 +1,31 @@ +function [varargout] = cellfun2(varargin) +% cellfun2() - Cap funtion for cellfun which accepts any function call +% +% D = CELLFUN2(FUN, C) applies function FUN to the cells of C +% +% D = CELLFUN2(FUN, C, P,...) applies function FUN to the cells of C using +% parameters P in the call of FUN +% +%See also: cellfun + +try + if nargout == 0 + builtin('cellfun', varargin{:}); + else + [varargout{1:nargout}] = builtin('cellfun', varargin{:}); + end +catch + if nargout > 1 + error('cellfun2 cannot handle more than one output') + end + if iscell(varargin{1}) || ~iscell(varargin{2}) + error('cellfun2 input format is: cellfun2(function, cell array, ...)') + end + fname = varargin{1}; + x = varargin{2}; + y = cell(size(x)); + for i=1:numel(x) + y{i} = feval(fname, x{i},varargin{3:end}); + end + varargout{1} = y; +end diff --git a/circle3.m b/circle3.m new file mode 100644 index 0000000..2e2f8bb --- /dev/null +++ b/circle3.m @@ -0,0 +1,19 @@ +function [h]=circle3(X,R, varargin) +% CIRCLE3: draw an circle in 3D +% h = circle3(x,y,z,r) or circle3(xyz,r) +if prod(size(R))=prod(size(X))/3 + X(:,2)=varargin{1}; + X(:,3)=varargin{2}; + varargin=varargin{3:end}; +end + +h = circle(X,Y,R) +rotate( + + +function circle(C,r,npts); +if nargin<3 + npts = 50; +end +theta=0:2*pi/(npts-1):2*pi; +plot(C(1)+r*cos(theta),C(2)+r*sin(theta),'w'); \ No newline at end of file diff --git a/circpermarray.m b/circpermarray.m new file mode 100644 index 0000000..8ec0041 --- /dev/null +++ b/circpermarray.m @@ -0,0 +1,29 @@ +function [y]=circpermarray(x,pv,dim) +% circpermarray - circularly permute values in an array +% +% [y]=circpermarray(x,pv,dim) +% +% pv: length of the permutation. +% dim: dimension on which permutation is done. +% +% NB: The direction of permutation is top-down (dim==1) and +% left-right (dim==2). Of course! + +if nargin<3 + [dim]=min(find(size(x)>1)); + if isempty(dim) + dim=1; + end +end +sx=size(x); +pd=[dim, 1:dim-1 dim+1:ndims(x)]; +%permute dimensions +x=permute(x,pd); +pv=mod(pv, sx(dim)); +x=x([end-pv+1:end 1:end-pv],:); +x=reshape(x,sx(pd)); +y=ipermute(x,pd); + +return + + \ No newline at end of file diff --git a/clickableLegend.m b/clickableLegend.m new file mode 100644 index 0000000..5cf6a0b --- /dev/null +++ b/clickableLegend.m @@ -0,0 +1,56 @@ +function varargout = clickableLegend(varargin) +% clickableLegend is a wrapper around the LEGEND function that provides the +% added functionality to turn on and off (hide or show) a graphics object +% (line or patch) by clicking on its text label in the legend. Its usage is +% the same as the LEGEND function. For +% further information please see the LEGEND documentation. +% +% Notes: +% 1. If you save the figure and re-load it, the toggling functionality +% is not automatically re-enabled. To restore it, simply call clickableLegend +% with no arguments. +% +% 2. To prevent the axis from automatically scaling every time a line is +% turned on and off, issue the command: axis manual +% +% Example 1: +% z = peaks(100); +% plot(z(:,26:5:50)) +% grid on; +% axis manual; +% clickableLegend({'Line1','Line2','Line3','Line4','Line5'}, 'Location', 'NorthWest'); + +% Example 2: +% plot(1:10,1:10,'x', 1:10,10:-1:1,'r-', 1:10,rand(1,10)*5,'b:'); +% clickableLegend('Line1','Line2','Line3'); +% hgsave(gcf, 'testfig.fig'); +% hgload testfig.fig +% clickableLegend + + +% Create legend as if it was called directly +[varargout{1:nargout(@legend)}] = legend(varargin{:}); + +% Extract what is needed for the rest of the function and fix varargout +[leghan, objhan, plothan] = varargout{1:4}; %#ok +varargout = varargout(1:nargout); + +% At this point, we can quit and behavior would be equivalent to calling +% just legend. + +% Set the callbacks +for i = 1:length(plothan) + set(objhan(i), 'HitTest', 'on', 'ButtonDownFcn',... + @(varargin)togglevisibility(objhan(i),plothan(i)),... + 'UserData', true); +end + + +function togglevisibility(hObject, obj) +if get(hObject, 'UserData') % It is on, turn it off + set(hObject, 'Color', (get(hObject, 'Color') + 1)/1.5, 'UserData', false); + set(obj,'HitTest','off','Visible','off','handlevisibility','off'); +else + set(hObject, 'Color', get(hObject, 'Color')*1.5 - 1, 'UserData', true); + set(obj, 'HitTest','on','visible','on','handlevisibility','on'); +end diff --git a/closest.m b/closest.m new file mode 100644 index 0000000..55ee905 --- /dev/null +++ b/closest.m @@ -0,0 +1,15 @@ +function [I,D] = closest(A,B) % deprecated +% DEPRECATED. See: nearest + +% closest - Closest points between two sets +% (N-dimension euclidian distance) +% +% [I,D] = closest(A,B) +% +% INPUTS: +% A - MxD matrix (M=number of points, D=number of dimensions) +% B - NxD matrix (N=number of points, D=number of dimensions) +% OUTPUTS: +% I - Mx1 vector of indices of B's closest to each A's +% D - Mx1 vector of euclidian distances +error \ No newline at end of file diff --git a/cluster_threshold.m b/cluster_threshold.m new file mode 100644 index 0000000..44b00d7 --- /dev/null +++ b/cluster_threshold.m @@ -0,0 +1,68 @@ +function [Y,clusters] = cluster_threshold(X,thd,vc,dim,verbose) +%CLUSTER_THRESHOLD - Keep only data which are clustered +% [Y] = cluster_threshold(X,thd,vc/adj,dim,verbose) +% Finds clusters along dimension dim in matrix X whose mass/area is +% bigger than (or equal to) thd: +% for each cluster clu{i}=[ ... ], sum(X([clu{i}])) >= thd; +% Adjacency/connectivity must be specified in vc +% * use vc=1 for continous data (e.g. time samples) +% * use a conectivity matrix or cell array of neighbors otherwise +% By default [dim] is the first non singleton dimension of X +% Outputs Y (of the same size as X) such that Y=X where the clusters +% match the criterion, Y=0 elsewhere. +% +% See also: CLUSTERING + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-18 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<4 + [dim,dim]=min(find(size(X)>1)); + if isempty(dim) + dim=1; + end +end +if nargin<5 + verbose=1; +end + +sX=size(X); +ndX=ndims(X); +Y=permute(X, [dim setdiff(1:ndX,dim)]); +if iscell(vc) + warning(sprintf('%s\n%s', '''vc'' is provided as a vertices_connectivity cell list.' , ... + 'It will be converted to an adjacency matrix for faster computation.')); + vc=vertconn2adjacency(vc); + fprintf('Adjacency matrix now computed\n'); +end + +if verbose + htime=timebar('Finding clusters'); +end +niter=(prod(sX)/sX(dim)); +for i=1:niter + [clu,sclu]=clustering(Y(:,i),vc); + y=Y(:,i); + Y(:,i)=0; + Y([clu{sclu>=thd}],i)=y([clu{sclu>=thd}],1); + if verbose + try,timebar(htime,i/niter);end + end + if nargout>1 + clusters{i} = clu(sclu>=thd); + end + +end +if verbose + try;close(htime);end +end +Y=ipermute(Y, [dim setdiff(1:ndX,dim)]); \ No newline at end of file diff --git a/clustering.m b/clustering.m new file mode 100644 index 0000000..447b25b --- /dev/null +++ b/clustering.m @@ -0,0 +1,117 @@ +function [clu,sz,mc,v2c] = clustering(X,vc,VERBOSE) +%CLUSTERING - find clusters of data (continuous or on a mesh) +% [clu,sz,mc] = clustering(X,vc, verbose) +% Find clusters of non-zeros values in data vector X according to the +% connectivity defined by 'vc' +% +%INPUTS: +% X: N-by-1 array of zeros and non-zeros data +% vc: Connectivity pattern, can be: +% [1] -> continuous data (e.g. time samples) +% vertice_connectivity (cell list) +% adjacency matrix +% +%OUPTUTS: +% clu: clusters found ss a cell list of indices in X, ordered in +% decreasing size +% sz: size of each cluster +% mc: mass of each cluster, mc(i)=sum(X(clu{i})) +% vtx2clu: N-by-1 array indicating the cluster to which belongs the +% vertex +% +%EXAMPLE +% >> [clu,sz]=clustering(ImageGridAmp(:,1),vertconn); + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-05 Creation +% KND 2007-04-16 Bug correction: unidimensional +% ----------------------------- Script History --------------------------------- + +if numel(X)>max(size(X)) + error('X should be a vector, not a matrix') +end +if nargin<3 + VERBOSE=0; +end + +X=X(:); +n=size(X,1); + +if isequal(vc,1) | isempty(vc) + % The '~~' avoids warnings MATLAB:conversionToLogical + p=logical(~~X); + dip=diff(cumsum(p),2); + dp1=find(dip==1)+2; + dp2=find(dip==-1)+2; + if isequal(p(1),1) + % check for siding values + dp1=[1; dp1]; + if isequal(p(2),0) + dp2=[2; dp2]; + end + elseif isequal(p(2),1) + dp1=[2; dp1]; + end + if isequal(p(end),1) + dp2=[dp2; n]; + end + clu=cell(1,length(dp1)); + sz=dp2-dp1; + mc=zeros(1,length(dp1)); + for i=1:length(dp1) + clu{i}=dp1(i):(dp2(i)-1); + if nargout>2 + mc(i)=sum(X(dp1(i):(dp2(i)-1))); + end + end + +else + if size(vc,1) ~= n + error('Connectivity and number of values in X don''t match') + end + + if iscell(vc) + A=vertconn2adjacency(vc,VERBOSE); + else + A=vc; + end + X=double(X); + % NaN values + X(isnan(X))=0; + + A=A|speye(size(A)); + % Remove OFF vertices from their neighbours + A(~X,:)=0; + A(:,~X)=0; + + % Compute clusters using matlab's dmperm + [p,ignore,r,s] = dmperm(A); + + sz=diff(r).*(diff(r)&diff(s)); + idx=find(sz); + [ign,idx2]=sort(-sz(idx)); + sz=sz(idx(idx2)); + clu=cell(1,length(idx2)); + if nargout>2 + mc=zeros(1,length(idx2)); + end + if nargout > 3 + v2c=zeros(n,1); + end + for i=1:length(idx2) + clu{i}=p(r(idx(idx2(i))):(r(idx(idx2(i))+1)-1)); + if nargout>2 + mc(i)=sum(X(clu{i})); + end + if nargout > 3 + v2c(p(r(idx(idx2(i))):(r(idx(idx2(i))+1)-1)))=i; + end + end +end diff --git a/clusters2faces.m b/clusters2faces.m new file mode 100644 index 0000000..dac3d8b --- /dev/null +++ b/clusters2faces.m @@ -0,0 +1,29 @@ +function [fclusters]=clusters2faces(vclusters, faces,verbose) +% clusters2faces - find faces encompassed in each cluster +% +% [fclusters]=clusters2faces(vclusters, faces,verbose) +% Retrieve faces fully included in each cluster + +% KND : 2005-07-01 : Initial release. Some vectorization should be possible +if nargin<3 + verbose=0; +end + +nclu=length(vclusters); +if verbose + h=waitbar(0,'Clusters of faces '); +end +for i=1:nclu + fclusters{i}=[]; + for j=1:size(faces,1) + if length(intersect(faces(j,:),vclusters{i}))==3 + fclusters{i}=[fclusters{i} j]; + end + end + if verbose + waitbar(i/nclu,h); + end +end +if verbose + close(h) +end \ No newline at end of file diff --git a/clusters2patches.m b/clusters2patches.m new file mode 100644 index 0000000..db5b922 --- /dev/null +++ b/clusters2patches.m @@ -0,0 +1,54 @@ +function [fv,vclusters]=clusters2patches(vclusters, faces, vertices,verbose) +% clusters2patches - computes patches of clusters +% +% [p,clusters]=clusters2patches(clusters, faces, vertices,verbose) +% +% INPUTS: +% clusters: cell list of vertex indices +% faces: from a FV structure, see PATCH +% vertices: idem. +% verbose: optional, default=1 +% +% OUPUTS: +% p: Nx1 array of FV structures +% clusters: newly assignated vertices in each clusters. +% Indeed, as some faces may lie on the border of two (or even +% three) clusters, the new patches may overlap. Therefore some +% faces and vertices are duplicated between patches and we keep +% track of these "extended" clusters in this output + +% KND : 2005-07-01 : Initial release. Some vectorization should be possible +if nargin<3 + verbose=0; +end + +nclu=length(vclusters); +if verbose + h=waitbar(0,'Clusters of patches'); +end +for i=1:nclu + fv(i).faces=[]; + for j=1:size(faces,1) + if length(intersect(faces(j,:),vclusters{i}))>1 + fv(i).faces=[fv(i).faces; 0 0 0]; + for k=1:3 + if ~ismember(faces(j,k),vclusters{i}) + vclusters{i}=[vclusters{i} faces(j,k)]; + end + fv(i).faces(end,k)=find(faces(j,k)==vclusters{i}); + end + end + end + fv(i).vertices=vertices(vclusters{i},:); + if verbose + waitbar(i/nclu,h); + end +end + +% Post process faces to remove duplicated faces +% f=unique(cat(1,fv(:).faces), 'rows'); +% [f,f]=setdiff(cat(1,fv(:).faces),f, 'rows'); + +if verbose + close(h) +end \ No newline at end of file diff --git a/cnrs_section27.m b/cnrs_section27.m new file mode 100644 index 0000000..91454b8 --- /dev/null +++ b/cnrs_section27.m @@ -0,0 +1,101 @@ +% Candidats 2009 +% ALAHYANE Nadia Admis à concourir +% AMIEZ Celine Admis à concourir +% ANTRI Myriam Admis à concourir +% BARAKAT Youssef Admis à concourir +% BARIK Jacques Admis à concourir +% BARRIERE Grégory Admis à concourir +% BEGUE Anne Admis à concourir +% BENCHENANE Karim Admis à concourir +% BENTURQUIA Nadia Admis à concourir +% BERANECK Mathieu Admis à concourir +% BIDET-ILDEI Christel Admis à concourir +% BLANGERO Annabelle Admis à concourir +% BOISTEL Renaud Admis à concourir +% BOMPAS Aline Admis à concourir +% BOUDIN Florian Admis à concourir +% BOULENGER Veronique Admis à concourir +% BRUEL JUNGERMAN Elodie Admis à concourir +% COENEN Olivier Admis à concourir +% COLLINS Thérèse Admis à concourir +% COPPOLA Vincent Admis à concourir +% COQUART Jérémy Admis à concourir +% DANGLOT Lydia Admis à concourir +% DE CHEVIGNY Antoine Admis à concourir +% DE MARGERIE Emmanuel Admis à concourir +% DELLEN Babette Admis à concourir +% DOLY Stephane Admis à concourir +% DUFOUR Valerie Admis à concourir +% DULIN David Admis à concourir +% DUPIERRIX Eve Admis à concourir +% DURAND Jean Baptiste Admis à concourir +% EGO-STENGEL Valérie Admis à concourir +% ELEORE Lyndell Admis à concourir +% FAURE Alexis Admis à concourir +% FERNANDEZ Julian Admis à concourir +% GENTY Emilie Admis à concourir +% GOMEZ Doris Admis à concourir +% GOUREVITCH Boris Admis à concourir +% GUILLEM Karine Admis à concourir +% HADJ-BOUZIANE Fadila Admis à concourir +% HANSARD Miles Edward Admis à concourir +% HERVE Pierre Yves Admis à concourir +% HICHEUR Halim Admis à concourir +% HOK Vincent Admis à concourir +% HOSY Eric Admis à concourir +% HUSKY Mathilde Admis à concourir +% HUYS Raoul Admis à concourir +% ISEL Frédéric Admis à concourir +% IZARD Véronique Admis à concourir +% KILAVIK Bjørg Elisabeth Admis à concourir +% LEBLOIS Arthur Admis à concourir +% LECOURTIER Lucas Admis à concourir +% LOPEZ Christophe Admis à concourir +% MADDEN Carol Admis à concourir +% MAIRESSE Jérome Admis à concourir +% MARQUES PEREIRA Patricia Admis à concourir +% MENDOZA Jorge Admis à concourir +% MICHELENA Pablo Admis à concourir +% MICHELET Thomas Admis à concourir +% MONTAGNINI Anna Admis à concourir +% MORICE Elise Admis à concourir +% MUNIER Claire Alice Admis à concourir +% NAVAILLES Sylvia Admis à concourir +% NAVARRO Jordan Admis à concourir +% PARRON Carole Admis à concourir +% PASCAL Frédéric Admis à concourir +% PASTORINI Chiara Admis à concourir +% PATINO VILCHIS Jose Luis Admis à concourir +% PIETROPAOLO Susanna Admis à concourir +% PLAILLY Jane Admis à concourir +% POIRIER Karine Admis à concourir +% REGUIGNE-KHAMASSI Mehdi Admis à concourir +% RIBOT Jérôme Admis à concourir +% ROUSTIT Christelle Admis à concourir +% SAGASPE Patricia Admis à concourir +% SARLEGNA Fabrice Admis à concourir +% SCHIRLIN Olivier Admis à concourir +% SELIMBEGOVIC Leila Admis à concourir +% SERGENT Claire Admis à concourir +% SMADJA Carole Admis à concourir +% SNOEREN Natalie Admis à concourir +% TAGLIABUE Michele Admis à concourir +% TRONEL Sophie Admis à concourir +% UPAL Roy Admis à concourir +% WARDAK Claire Admis à concourir +% WIRTH Sylvia Admis à concourir +% YALCIN CHRISTMANN Ipek Admis à concourir +clear +clc +filename=mfilename('fullpath'); +nc = 86; +[a ,nom(:,1),nom(:,2)]=textread(filename ,'%s%s%s%*[^\n]',nc, 'headerlines',1); +query = 'http://www.ncbi.nlm.nih.gov/pubmed/search?term=("2000"[Publication%20Date]%20:%20"3000"[Publication%20Date])%20AND%20("%s%%20%s"[au])'; +for i=1:nc +% nom={'Baillet', 'S'} + q =sprintf(query, nom{i,1},nom{i,2}(1)) + t=urlread(q); + pmid=findstr('pmid',t); + findstr('title',t(pmid(1)+[5:400])) + return +end \ No newline at end of file diff --git a/cogent/Textquestions.m b/cogent/Textquestions.m new file mode 100644 index 0000000..cd12d6f --- /dev/null +++ b/cogent/Textquestions.m @@ -0,0 +1,135 @@ +function [tx]=Textquestions(questions3,examples,keys) +if nargin ==0 + warning('no subject name - will use default name') + sname = 'test'; + listnum=1; +end +if nargin<1 || isempty(questions3) + questions3={'Est-ce que cette musique vous evoque des sensations corporelles ?' ... + 'Est-ce que cette musique vous evoque des images ?'}; + examples={'(par exemple des frissons ou besoin d''un mouvement)' '(par exemple des couleurs ou paysages)'}; +end +if nargin<2 + keys=[]; +end + +tx=[]; + +if length(dbstack)==1 + + global cogent + config_keyboard; + config_display(1, 2, [0 0 0], [1 1 1], 'Arial', 25, 4 ) + % config_log(['C:\Documents and Settings\SCHWARTZ\My Documents\MATLAB\Wiebke\myresults\' sname '.log']); + % config_results(['C:\Documents and Settings\SCHWARTZ\My Documents\MATLAB\Wiebke\myresults\' sname '.res']); + % datafilename= ['C:\Documents and Settings\SCHWARTZ\My Documents\MATLAB\Wiebke\mylists\datafile_' num2str(listnum) '.dat']; + % config_data(datafilename); + % config_sound; + + start_cogent + + fontName = 'Helvetica'; fontSize = 20; % font parameters (optional) + cgalign('c','c'); + keys=[]; + keys=getkeymap; + +end + +% thechar=char(fieldnames(themap)); +% thechar= {'A','B','C','D','E','F','G','H','I','J',... +% 'K','L','M','N','O','P','Q','R','S','T',... +% 'U','V','W','X','Y','Z','K0','K1','K2','K3',... +% 'K4','K5','K6','K7','K8','K9','F1','F2','F3','F4',... +% 'F5','F6','F7','F8','F9','F10','F11','F12','F13','F14',... +% 'F15','Escape','Minus','Equals','BackSpace','Tab','LBracket','RBracket','Return','LControl',... +% 'SemiColon','Apostrophe','Grave','LShift','BackSlash','Comma','Period','Slash','RShift','LAlt',... +% 'Space','CapsLock','NumLock','Scroll','Pad0','Pad1','Pad2','Pad3','Pad4','Pad5',... +% 'Pad6','Pad7','Pad8','Pad9','PadSubtrack','PadAdd','PadDivide','PadMultiply','PadPeriod','PadEnter',... +% 'RControl','RAlt','Pause','Home','Up','PageUp','Left','Right','End','Down',... +% 'PageDown','Insert','Delete'} +thechar= {'A','B','C','D','E','F','G','H','I','J',... + 'K','L','M','N','O','P','Q','R','S','T',... + 'U','V','W','X','Z','Y','0','1','2','3',... + '4','5','6','7','8','9','F1','F2','F3','F4',... + 'F5','F6','F7','F8','F9','F10','F11','F12','F13','F14',... + 'F15','Escape','-','=','BackSpace','Space','è','','Return','LControl',... + 'é','à','Grave','LShift','$',',','.','-','RShift','LAlt',... + 'Space','CapsLock','NumLock','Scroll','Pad0','1','2','3','4','5',... + '6','7','8','9','-','+','/','*','.','Return',... + 'RControl','RAlt','Pause','Home','Up','PageUp','Left','Right','End','Down',... + 'PageDown','Insert','Delete'}; +thechar=char( thechar'); +thenum=cell2mat(struct2cell(keys)); +clearkeys +NQ=length(questions3); + +for k = 1:NQ + theword={''}; + cgflip(0,0,0) + cgflip(0,0,0) + cgtext(questions3{k},0,200) + cgtext(examples{k},0,150) + cgflip + wait(2000); + cgflip(0,0,0) + cgflip(0,0,0) + + while 1 + theline=length(theword); + if length(theword{theline})>50 + lastblank= findstr(theword{theline},' '); + lastblank= lastblank(end); + theword{theline+1}=theword{theline}(lastblank+1:end); + theword{theline} = theword{theline}(1:lastblank) ; + theline=length(theword); + end + + [ keyout, time, n ] = waitkeydown( Inf ); + keyout= keyout(1); + if keys.Return == keyout + break + else + cgflip(0,0,0) + cgflip(0,0,0) + theletter = deblank(thechar(find(thenum==keyout),:)); + if strcmp(theletter,'Space') + theword{theline}=[theword{theline} ' ']; + elseif strcmp(theletter,'BackSpace') + if length(theword{theline})>0 + theword{theline}=[theword{theline}(1:end-1)]; + end + else + theword{theline}=[theword{theline} deblank(thechar(find(thenum==keyout),:))]; + end + posx= 0; + posy= 50; + theresp = ''; + for i=1:theline + theresp = [theresp theword{i}]; + cgtext(questions3{k},0,200) + cgtext(examples{k},0,150) + cgtext(theword{i},posx,posy) + posy=posy-50; + end + + cgflip + end + + tx{k}=theresp; + + end + if length(theword{1})==1 + tx{k}=['NO']; + end + cgflip(0,0,0) + cgflip(0,0,0) + wait(1000) +end + +if length(dbstack)==1 + stop_cogent; +end + +tx + +return \ No newline at end of file diff --git a/cogent/discrethopper.m b/cogent/discrethopper.m new file mode 100644 index 0000000..a1464db --- /dev/null +++ b/cogent/discrethopper.m @@ -0,0 +1,146 @@ +function [resp,rt]=discrethopper(trial,questions,map,buf) +resp=[]; % the answer +rt=[]; % the reactiontime between each key press +if nargin<1 + trial=''; +else + trial=sprintf('%02d/%02d',trial); % output of the current number of trial in realation to the total number of trials +end +if nargin<2 || isempty(questions) % in the case of testing the script alone without arguments + questions={'Enchantement (heureux, emerveillé)' 'Triomphe (energique, heroïque)' 'Nostalgie (sentimental, rêveur)'... + 'Transcendence (inspiré, spirituel)' 'Sérénité (calme, apaisé)' 'Tendresse (affectueux, doux)'... + 'Joie (euphorique, dansant)' 'Tristesse (deprimé, solonnel)' 'Agitation (tendu, neurveux)'}; +end +if nargin<3 + map=[]; +end +if nargin<4 + buf=1; +end + +scale=[]; + +Reckx = [-180 -140 -100 -60 -20 20 60 100 140 180]; +nbr = length(Reckx); % number of rects + +rectw=20; % width +recth=20; % hight +rectb=1; % thickness of rectangle +rectwi=rectw-rectb*2; %inside part width +recthi=recth-rectb*2; %inside part hight +vspace=51; % space between the lines + +fgcolor=[1 1 1]; +bgcolor=[0 0 0]; +fontSize=16; % textsize + +if length(dbstack)==1 % in case of calling the script without input variables + config_display(1,1,bgcolor,fgcolor,'Arial',20); + config_keyboard; + + start_cogent; + if ~isempty(scale) + cgScale(scale); + end + % the keyboardsetting + keys = getkeymap; +end + + +NQ=length(questions); +keyadjust=0; +polpos=5; % the default start position (5=in the middle) + + +for i=1:NQ % loop for the questions + + trial_start = time; % the onset time of the trial + hopper=polpos; + + while 1 + readkeys; + clearpict( buf ); + keyadjust; + + if keyadjust==29 + hopper = hopper + 1; + if hopper > 10 + hopper = hopper - 1; + end + end + if keyadjust==28 + hopper = hopper - 1; + if hopper < 1 + hopper = hopper + 1; + end + end + + for j=1:NQ + y=(5-j)*vspace; + if j0); +fullscreen = 1; +fullscreen = 0; + +clc; +t=textread(textfile,'%s', 'delimiter', '\n','whitespace',''); +scale=[]; +rectx=0; +recty=0; +rectw=400; +recth=rectw/40; +rectb=1; +rectwi=rectw-rectb*2; %inside part +recthi=recth-rectb*2; %inside part +vspace=5; + +fgcolor=[1 1 1]; +bgcolor=[0 0 0]; +fontSize=rectw/20; +linewidth=40; +textheight=20; + +if length(dbstack)==1 + config_display(fullscreen,1,bgcolor,fgcolor,'Arial',20,25); + if fullscreen==0 + config_keyboard( 100, 5, 'nonexclusive') + else + config_keyboard; + end + config_log; + config_results; + start_cogent; + cogprocess( 'getpriority' ) + cogstd('spriority','NORMAL') + cogprocess( 'getpriority' ) + keymap=getkeymap; +end +logstring( textfile); +addresults(textfile) +addresults(datestr(now,0)) +addresults('Subject', subject) +clearpict( 0 ); + +%% Instructions + +clearpict( 1 ); % Clear display buffer 1 +s=find(cellfun('isempty',t)); +i=1; +j=2; +while not(isempty(t{i}) & isempty(t{i+1}) ) + nlines=s(min(find(s>i)))-i; + for j=1:nlines + preparestring(t{i+j-1},1,0,(nlines/2-j)*textheight); + drawpict(1); + end + waitkeydown(5000+nlines*2000); + clearpict( 1 ); % Clear display buffer 1 + i=i+nlines; +end + +%% Response options + +i=i+2; +j=0; +while not(isempty(t{i})) + j =j+1; + if isempty(t{i+1}) + respoption(j).txt = t{i}; + respoption(j).key = getfield(keymap, sprintf('K%d',j)); + else + respoption(j).txt = [t{i+1} ' -> ' t{i}]; + if ismember( t{i+1} , '1234567890') + respoption(j).key = getfield(keymap,['K' t{i+1}]); + else + respoption(j).key = getfield(keymap,t{i+1}); + end + end + preparestring(respoption(j).txt,2,0,-50-textheight*j); + respoption(j).buf=2+j; + preparestring(respoption(j).txt,respoption(j).buf,0,-50-textheight*j); + respoption(j) + i=i+2; +end +preparestring('En cas d''erreur, appuyer sur la flèche gauche pour revenir en arrière',2,0,-50-textheight*(j+2)); + + +%% Questions + + +iq=1; +iline(iq)=i+1+iq; +if iline > length(t) + stop_cogent; + error; + return +elseif isempty(t{iline}) + stop_cogent; + return +end +clearpict( 0 ); +drawpict(0); + + +while (iline(iq))<=length(t) + nlines=1; + ok=(iline(iq)+nlines)<=length(t); + if ok, ok=ok & ~isempty(t{iline(iq)+nlines}); end + while ok + nlines=nlines+1; + ok=iline(iq)+nlines<=length(t); + if ok, ok=ok & ~isempty(t{iline(iq)+nlines}); end + end + cgsetsprite(0); + cgdrawsprite(2,0,0); + for j=1:nlines + preparestring(t{iline(iq)+j-1},0,0,(nlines-j)*textheight); + end + t0=drawpict(0); + wait(300); + clearkeys; + [k,rt] = waitkeydown(inf,[keymap.Delete keymap.Left keymap.Escape respoption.key] );%getkeydown; + rt=rt-t0+300; + if isempty(k) + elseif k(1)==keymap.Delete | k(1)==keymap.Left + iq=iq-1; + if iq<1, iq=1; end + clearpict( 0 ); + drawpict(0); + wait(100) + elseif k(1)==keymap.Escape + iline(iq)=inf; + else + r = find(k(1)==[respoption.key]); + r = r(1); + clearpict( 0 ); + cgsetsprite(0); + cgdrawsprite(respoption(r).buf,0,0); + for j=1:nlines + preparestring(t{iline(iq)+j-1},0,0,(nlines-j)*textheight); + end + drawpict(0); + wait(500) + addresults(iq, r, rt) + iq=iq+1; + iline(iq)=iline(iq-1)+nlines+1; + end + +end + +wait(100); +clearkeys; +stop_cogent; + +return + +loadpict( face, 1 ); % Copy face into buffer +clearkeys; % Clear all keyboard events +drawpict( 1 ); % Copy display buffer 1 to screen +wait( 1000 ); % Wait for 1000ms +drawpict( 2 ); % Clear screen +wait( 1000 ); % Wait for 1000ms +readkeys; \ No newline at end of file diff --git a/cogent/semislider.m b/cogent/semislider.m new file mode 100644 index 0000000..10fa7f8 --- /dev/null +++ b/cogent/semislider.m @@ -0,0 +1,166 @@ +function [resp,rt]=discretslider(trial,questions,map,buf) +resp=[]; % the answer +rt=[]; % the reactiontime between each key press +if nargin<1 + trial=''; +else + trial=sprintf('%02d/%02d',trial); +end +if nargin<2 || isempty(questions) + questions={'Enchantement (heureux, emerveillé)' 'Triomphe (energique, heroïque)' 'Nostalgie (sentimental, rêveur)'... + 'Transcendence (inspiré, spirituel)' 'Sérénité (calme, apaisé)' 'Tendresse (affectueux, doux)'... + 'Joie (euphorique, dansant)' 'Tristesse (deprimé, solonnel)' 'Agitation (tendu, neurveux)'}; +end +if nargin<3 + map=[]; +end +if nargin<4 + buf=1; +end + +scale=[]; +rectxa=-190; % x-axis +rectya=100; % y-axis 1st square +rectxb=-60; % x-axis 2nd square +rectxc=60; % x-axis 3rd square +rectxd=190; % x-axis 4th square + +rectw=20; % width +recth=20; % hight +rectb=1; % thickness of rectangle +rectwi=rectw-rectb*2; %inside part width +recthi=recth-rectb*2; %inside part hight +vspace=50; + +fgcolor=[1 1 1]; +bgcolor=[0 0 0]; +fontSize=20; % textsize + +if length(dbstack)==1 + config_display(1,1,bgcolor,fgcolor,'Arial',20); + config_keyboard; + start_cogent; + if ~isempty(scale) + cgScale(scale); + end + % the keyboardsetting + keys = getkeymap; +end + +NQ=length(questions); + +for i=1:NQ + mx=0; + trial_start = time; + keyout=[]; + while 1 + clearpict( buf ); + for j=1:NQ + y=(5-j)*vspace; + if j> coolhot +% +% See also: activmap, grayhot, greyish + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-22 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin < 1, n=size(get(gcf,'colormap'),1); end +n = ceil(n/2); +c=[flipud(fliplr(hot(n))); hot(n)]; \ No newline at end of file diff --git a/colon2.m b/colon2.m new file mode 100644 index 0000000..186e782 --- /dev/null +++ b/colon2.m @@ -0,0 +1,44 @@ +function [varargout] = colon2(varargin) +%: Colon2. (Adapted fomr COLON for 2-element input by KND) +% +% COLON2([J K]) is equivalent to COLON(J,K) +% +% See also: COLON + +% J:K is the same as [J, J+1, ..., K]. +% J:K is empty if J > K. +% J:D:K is the same as [J, J+D, ..., J+m*D] where m = fix((K-J)/D). +% J:D:K is empty if D == 0, if D > 0 and J > K, or if D < 0 and J < K. +% +% COLON(J,K) is the same as J:K and COLON(J,D,K) is the same as J:D:K. +% +% The colon notation can be used to pick out selected rows, columns +% and elements of vectors, matrices, and arrays. A(:) is all the +% elements of A, regarded as a single column. On the left side of an +% assignment statement, A(:) fills A, preserving its shape from before. +% A(:,J) is the J-th column of A. A(J:K) is [A(J),A(J+1),...,A(K)]. +% A(:,J:K) is [A(:,J),A(:,J+1),...,A(:,K)] and so on. +% +% The colon notation can be used with a cell array to produce a comma- +% separated list. C{:} is the same as C{1},C{2},...,C{end}. The comma +% separated list syntax is valid inside () for function calls, [] for +% concatenation and function return arguments, and inside {} to produce +% a cell array. Expressions such as S(:).name produce the comma separated +% list S(1).name,S(2).name,...,S(end).name for the structure S. +% +% For the use of the colon in the FOR statement, See FOR. +% For the use of the colon in a comma separated list, See VARARGIN. + +if nargout == 0 + if nargin==1 && length(varargin{1})==2 + builtin('colon',varargin{1}(1),varargin{1}(2)); + else + builtin('colon', varargin{:}); + end +else + if nargin==1 && length(varargin{1})==2 + [varargout{1:nargout}] = builtin('colon', varargin{1}(1),varargin{1}(2)); + else + [varargout{1:nargout}] = builtin('colon', varargin{:}); + end +end \ No newline at end of file diff --git a/colorbar_slider.m b/colorbar_slider.m new file mode 100644 index 0000000..cf433ac --- /dev/null +++ b/colorbar_slider.m @@ -0,0 +1,97 @@ +function varargout = colorbar_slider(action,varargin) +%COLORBAR_SLIDER - Add a GUI slider next to the colorbar +% [h] = colorbar_slider([ha]) +% [h] = colorbar_slider('init',ha) +% Adds a slider on the side of the specified colorbar +% (default: current colorbar, added if none) +% +% Example +% >> colorbar_slider +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-03 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + ha=colorbar; + varargin={ha}; + action='init'; +elseif nargin==1 || isnumeric(action) + ha=action; + action='init'; + if ishandle(ha) + if ~strmatch('Colorbar', get(ha, 'tag')) + ha=colorbar(ha); + end + varargin=[{ha} varargin ]; + end +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [h]=action_init(ha,varargin) +pos=get(ha, 'Position'); +h=findobj(get(ha,'parent'), 'tag', mfilename); + +if ~isempty(h) + if all(all(getappdata(h, 'CurrentColormap')==colormap)) + colormap(ha,getappdata(h, 'BaseColormap') ) + delete(h) + end +end + +h=uicontrol('style', 'slider', 'units', get(ha,'units'),'tag', mfilename); +% Check orientation of colorbar +if isempty(get(ha, 'Xtick')) + % vertical colorbar + if strmatch('right',get(ha, 'YAxisLocation')) + set(h, 'Position',pos*[1 0 -0.5 0;0 1 0 0; 0 0 .5 0; 0 0 0 1]') + else + set(h, 'Position',pos*[1 0 +1.5 0;0 1 0 0; 0 0 .5 0; 0 0 0 1]') + end + set(h, 'Min',min(get(ha, 'YLim')), 'max',max(get(ha, 'YLim')),'value',min(get(ha, 'YLim'))) +else + % horizontal colorbar + if strmatch('top',get(ha, 'XAxisLocation')) + set(h, 'Position',pos*[1 0 0 0;0 1 0 -0.5; 0 0 1 0; 0 0 0 .5]') + else + set(h, 'Position',pos*[1 0 0 0;0 1 0 +1.5; 0 0 1 0; 0 0 0 .5]') + end + set(h, 'Min',min(get(ha, 'XLim')), 'max',max(get(ha, 'XLim')),'value',min(get(ha, 'XLim'))) +end +% set(h, 'SliderStep', (get(h,'Max')-get(h,'Min')).*[1/100 1/10]); +set(h, 'UserData', ha); +setappdata(h, 'Colorbar', ha); +setappdata(h, 'Figure', get(ha,'Parent')); +setappdata(h, 'BaseColormap', colormap); +setappdata(h, 'BaseColor', [.6 .6 .6]); +setappdata(h, 'CurrentColormap', colormap); +set(h, 'Callback', sprintf('%s(''slide'', gcbo);', mfilename)); +return + + +function [h]=action_slide(h,varargin) +x=get(h, 'Value'); +h=action_value(h,x); + +function [h]=action_value(h,x) +cmap=getappdata(h, 'BaseColormap'); +n=round((x-get(h,'Min'))/(get(h,'Max')-get(h,'Min'))*size(cmap,1)); +cmap(1:n,:)=repmat(getappdata(h,'BaseColor'), n,1); +colormap(getappdata(h,'Colorbar'),cmap); +setappdata(h, 'CurrentColormap', colormap); \ No newline at end of file diff --git a/colormap_threshold.m b/colormap_threshold.m new file mode 100644 index 0000000..e797369 --- /dev/null +++ b/colormap_threshold.m @@ -0,0 +1,85 @@ +function c = colormap_threshold(x,cmap,beta) +%COLORMAP_THRESHOLD - Cut colormap at a given threshold +% +% [cmap] = colormap_threshold(x) +% Replace colormap in current axes (gca) with a thresholded one at +% the value x (or [-x x] if both positive and negatice values are +% used in the current graphics +% +% [cmap] = colormap_threshold(x,rgb) if RGB has only one line, the new +% colormap will be based on the colormap of the current axes +% +% [cmap] = colormap_threshold(x,handle) uses the colormap of the +% specified axes. If empty, uses the current axes. +% +% [cmap] = colormap_threshold(x,cmap,beta) +% beta specifies where the colormap should be cut and replace by the +% given RGB color (col). In percent (if beta<1) or actual number of colors (if >=1). +% Default: beta=0 (the whole previous colormap will be +% used to display values beyond the threshold x) +% +% [cmap] = colormap_threshold(x,beta,cmap,clim,col) + +% +% Example +% To cut p-value map displayed in log10 at a p<0.05 threshold +% >> colormap_threshold(-log10(0.05)) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-18 Creation +% +% ----------------------------- Script History --------------------------------- +h=gca; +beta=0; +if nargin>1 + h=varargin{1}; +end +if nargin>2 + beta=varargin{2}; +end +if nargin>3 + col=varargin{3}; + if length(col)==3 + cmap=colormap(h); + clim=get(h, 'CLim'); + else + beta=varargin{1}; + cmap=varargin{2}; + clim=varargin{3}; + col=[]; + if nargin>4 + col=varargin{4}; + end + + end +else + cmap=colormap(h); + clim=get(h, 'CLim'); + col=[]; +end + +if prod(clim)>=0 + % all values have same sign + d=clim(2)-clim(1); + + if (clim(2)>0) + % All positive + + elseif clim(1)<0 + % All negative + else + % All zeros! + error('Wrong CLim') + end +else + +end diff --git a/colorname2rgb.m b/colorname2rgb.m new file mode 100644 index 0000000..04e0b5d --- /dev/null +++ b/colorname2rgb.m @@ -0,0 +1,64 @@ +function y = colorname2rgb(x) +%COLORNAME2RGB - Converts colornames to +% [] = colorname(x) +% +% Example +% >> colorname('r') +% [ 1 0 0 ] +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-10-02 Creation +% +% ----------------------------- Script History --------------------------------- +if isnumeric(x) + y=x; + return; +end +if iscell(x) + y=cell(size(x)); + for i=1:numel(x) + y{i}=colorname2rgb(x{i}); + end + return +end +if ischar(x) + if size(x,1) >1 + y=NaN*zeros(size(x,1),3); + for i=1:size(x,1) + y(i,:)=colorname2rgb(x(i,:)); + end + else + switch lower(x) + case { 'k' 'black'} + y=[0 0 0]; + case { 'w' 'white'} + y=[1 1 1]; + case { 'r' 'red'} + y=[1 0 0]; + case { 'g' 'green'} + y=[0 1 0]; + case { 'b' 'blue'} + y=[0 0 1]; + case { 'y' 'yellow'} + y=[1 1 0]; + case { 'c' 'cyan'} + y=[0 1 1]; + case { 'm' 'magenta'} + y=[1 0 1]; + + otherwise + y=str2num(x) + end + end +end +if isempty(y) + y=NaN; +end diff --git a/columnlegend.m b/columnlegend.m new file mode 100755 index 0000000..f8a5907 --- /dev/null +++ b/columnlegend.m @@ -0,0 +1,132 @@ +function [legend_h,object_h,plot_h,text_strings] = columnlegend(numcolumns, str, varargin) +% +% columnlegend creates a legend with a specified number of columns. +% +% columnlegend(numcolumns, str, varargin) +% numcolumns - number of columns in the legend +% str - cell array of strings for the legend +% +% columnlegend(..., 'Location', loc) +% loc - location variable for legend, default is 'NorthEast' +% possible values: 'NorthWest', 'NorthEast', 'SouthEast', 'SouthWest' +% +% columnlegend(..., 'boxon') +% columnlegend(..., 'boxoff') +% set legend bounding box on/off +% +% example: +% legend_str = []; +% for i=1:10, +% x = 1:i:(10*i); +% plot(x); hold on; +% legend_str = [legend_str; {num2str(i)}]; +% end +% columnlegend(3, legend_str, 'Location', 'NorthWest'); +% +% +% Author: Simon Henin +% +% 4/09/2013 - Fixed bug with 3 entries / 3 columns +% 4/09/2013 - Added bounding box option as per @Durga Lal Shrestha (fileexchage) + + + +location = 'NorthEast'; +boxon = false; +for i=1:length(varargin), + switch lower(varargin{i}) + case 'location' + location = varargin{i+1}; + i=i+2; + case 'boxon' + boxon = true; + case 'boxoff' + boxon = false; + end +end + +%create the legend +[legend_h,object_h,plot_h,text_strings] = legend(str); + +%some variables +numlines = length(str); +numpercolumn = ceil(numlines/numcolumns); + +%get old width, new width and scale factor +pos = get(legend_h, 'position'); +width = numcolumns*pos(3); +rescale = pos(3)/width; + +%get some old values so we can scale everything later +xdata = get(object_h(numlines+1), 'xdata'); +ydata1 = get(object_h(numlines+1), 'ydata'); +ydata2 = get(object_h(numlines+3), 'ydata'); + +%we'll use these later to align things appropriately +sheight = ydata1(1)-ydata2(1); % height between data lines +height = ydata1(1); % height of the box. Used to top margin offset +line_width = (xdata(2)-xdata(1))*rescale; % rescaled linewidth to match original +spacer = xdata(1)*rescale; % rescaled spacer used for margins + + +%put the legend on the upper left corner to make initial adjustments easier +loci = get(gca, 'position'); +set(legend_h, 'position', [loci(1) pos(2) width pos(4)]); + + +col = -1; +for i=1:numlines, + if (mod(i,numpercolumn)==1 || (numpercolumn == 1)), + col = col+1; + end + + if i==1 + linenum = i+numlines; + else + linenum = linenum+2; + end + labelnum = i; + + position = mod(i,numpercolumn); + if position == 0, + position = numpercolumn; + end + + %realign the labels + set(object_h(linenum), 'ydata', [(height-(position-1)*sheight) (height-(position-1)*sheight)]); + set(object_h(linenum), 'xdata', [col/numcolumns+spacer col/numcolumns+spacer+line_width]); + + set(object_h(linenum+1), 'ydata', [height-(position-1)*sheight height-(position-1)*sheight]); + set(object_h(linenum+1), 'xdata', [col/numcolumns+spacer*3.5 col/numcolumns+spacer*3.5]); + + set(object_h(labelnum), 'position', [col/numcolumns+spacer*2+line_width height-(position-1)*sheight]); + + +end + +%unfortunately, it is not possible to force the box to be smaller than the +%original height, therefore, turn it off and set background color to none +%so that it no longer appears +set(legend_h, 'Color', 'None', 'Box', 'off'); + +%let's put it where you want it +pos = get(legend_h, 'position'); +fig_pos = get(gca, 'position'); +switch lower(location), + case {'northeast'} + set(legend_h, 'position', [pos(1)+fig_pos(3)-pos(3) pos(2) pos(3) pos(4)]); + case {'southeast'} + set(legend_h, 'position', [pos(1)+fig_pos(3)-pos(3) fig_pos(2)-pos(4)/2+pos(4)/4 pos(3) pos(4)]); + case {'southwest'} + set(legend_h, 'position', [fig_pos(1) fig_pos(2)-pos(4)/2+pos(4)/4 pos(3) pos(4)]); +end + +% display box around legend +if boxon, + pos = get(legend_h, 'position'); + orgHeight = pos(4); + pos(4) = orgHeight/numlines*numpercolumn; + pos(2)=pos(2) + orgHeight-pos(4) - pos(4)*0.05; + pos(1) = pos(1)+pos(1)*0.05; + annotation('rectangle',pos) +end \ No newline at end of file diff --git a/compute_forward.m b/compute_forward.m new file mode 100644 index 0000000..dc25a43 --- /dev/null +++ b/compute_forward.m @@ -0,0 +1,2660 @@ +function [varargout] = bst_headmodeler(varargin); +%BST_HEADMODELER - Solution to the MEG/EEG forward problem +% function [varargout] = bst_headmodeler(varargin); +% Authorized syntax: +% [G, OPTIONS] = bst_headmodeler(StudyFile, OPTIONS); +% [G, OPTIONS] = bst_headmodeler(OPTIONS); +% [OPTIONS] = bst_headmodeler; +% +% --------------------------------- INPUTS ------------------------------------- +% INPUTS +% +% [OPTIONS] = bst_headmodeler; Returns the default values for the OPTIONS +% parameter structure +% +% StudyFile: the name of a BrainStorm study file. We suppose the +% corresponding BrainStorm channel file is available in the same folder +% with the conventional file name (e.g., for a study file calles +% meg_brainstormstudy.mat, BST_HEADMODELER expects to find the +% corresponding channel file under the name meg_channel.mat). If the +% channel file were not sitting in the same folder as the study file, +% OPTIONS.ChannelFile enforces computation of the forward model with the +% channel information contained in OPTIONS.ChannelFile. +% +% If no further input arguments are specified, forward modeling is +% completed with the default parameters specified below +% +% OPTIONS a structure where optional parameters may be specified using the +% following fields Note: if no options are specified, BST_HEADMODELER will +% proceed to the computation of the foward problem on a 3D grid of source +% locations that cover the entire head volume See +% OPTIONS.VolumeSourceGridSpacing for default settings +% +% Important notice: there is no need to define all the following fields +% when using the OPTIONS argument. The undefined field(s) will be assigned +% default values. +% +% * +% * Fields Related to forward approach +% * +% +% .Method: is either a character string or a cell array of two strings that +% specifies the kind of approach to be applied to the compuation +% of the foward model In case Method is a cell array, it should +% contain 2 strings, one to specifiy the method to be used for MEG +% and the other for . If only a single string is specified, the +% foward computation will be completed on the set of corresponding +% CHANndx only (i.e. MEG or MEG) Available forward modeling +% methods and corresponding authorized strings for Method: +% - MEG +% 'meg_sphere' (DEFAULT) : Spherical head model designed +% following the Sarvas analytical formulation (i.e. +% considering the true orientation +% of the magnetic field sensors) (see OPTIONS.HeadCenter) +% 'meg_os' : MEG overlapping sphere forward model +% 'meg_bem' : Apply BEM computation (see OPTIONS.BEM for details) +% - +% 'eeg_sphere' : Single-sphere forward modeling (see +% OPTIONS.HeadCenter, OPTIONS.Radii, OPTIONS.Conductivity) +% 'eeg_3sphere' : EEG forward modeling with a set of 3 +% concentric spheres (Scalp, Skull, Brain/CSF) (see +% OPTIONS.HeadCenter, OPTIONS.Radii, OPTIONS.Conductivity) +% 'eeg_3sphereBerg' (DEFAULT) : Same as eeg_3sphere with +% correction for possible dipoles outside the sphere +% 'eeg_os' : EEG overlapping sphere head model (see +% OPTIONS.HeadCenter, OPTIONS.Radii, OPTIONS.Conductivity) +% 'eeg_bem' : Apply BEM computation (see OPIONS.BEM for details) +% +% Default is {'meg_sphere','eeg_3sphereBerg'}; +% +% .HeadModelName : a character string that specifies the name of the +% headmodel represented by this file, e.g "Spherical", +% "Overlapping Spheres", "Constant Collocation BEM", etc. +% Default is "Default", meaning it will include the the +% name(s) of the method(s) used in the MEG and/or EEG +% forward models +% +% * +% * Fields Related to function's I/O +% * +% +% .HeadModelFile : Specifies the name of the head model file where to store +% the forward model. If set to 'default', the default +% nomenclature for BrainStorm's head model file name is +% used and BST_HEADMODELER creates a file in StudyFile's +% folder. +% Default is empty. +% .ImageGridFile : Specifies the name of the file where to store the full +% cortical gain matrix file If set to 'default', the +% default nomenclature for BrainStorm's head model file +% name is used and BST_HEADMODELER creates a file in +% StudyFile's folder. +% Default is empty. +% .ImageGridBlockSize : Number of sources for which to compute the forward +% model at a time in a block computation routines +% (saves memory space). This option is relevant only +% when some forward modeling on cortical surface is +% requested (i.e. when .Cortex is specified) +% Default is 2000 +% .FileNamePrefix : A string that specifies the prefix for all file names +% (Channel, HeadModel, Gain Matrices) when .HeadModelFile +% is set to 'default' and .ChannelFile is empty. +% Default is 'bst_' +% .Verbose : Toggles verbose mode on/off; +% Default is 1 (on) +% +% * +% * Fields Related to Head Geometry * +% * +% +% .Scalp : A structure specifying the Scalp surface envelope to serve +% for parameter adjustment of best-fitting sphere, with +% following fields: +% .FileName : A string specifying the name of the BrainStorm +% tessellation file containing the Scalp +% tessellation (default is 1); +% .iGrid : An integer for the index of the Scalp surface in +% the Faces, Vertices and Comments cell arrays in +% the tessellation file +% Default is empty (Best-fitting sphere is +% computed from the sensor array). +% .HeadCenter: a 3-element vector specifying the coordinates, in the +% sensors coordinate system, of the center of the spheres that +% might be used in the head model. +% Default is estimated from the center of the best-fitting +% sphere to the sensor locations +% .Radii : a 3-element vector containing the radii of the single or 3 +% concentric spheres, when needed; +% Order must be the following : [Rcsf, Routerskull, Rscalp]; +% Default is estimated from the best-fitting sphere to the +% sensor locations and OPTIONS.Radii is set to: Rscalp [.88 +% .93 1]. Rscalp is estimated from the radius of the +% best-fitting sphere; +% .Conductivity : a 3-element vector containing the values for the +% conductivity of the tissues in the following order: +% [Ccsf, Cskull, Cscalp]; +% Default is set to [.33 .0042 .33]; +% .EEGRef : the NAME (not index of the channel file) of the electrode +% that acts as the reference channel for the EEG. If data is +% referenced to instantaneous average (i.e. so called +% average-reference recording) value is 'AVERAGE REF'; +% IMPORTANT NOTICE: When user calls bst_headmodeler with the +% .ChannelLoc option and .ChannelType = 'EEG'and wants the EEG +% reference to be e.g. channel 26, then .EEGRef should be set +% to 'EEG 26' +% Default is 'AVERAGE REF'. +% +% .OS_ComputeParam : if 1, force computation of all sphere parameters when +% choosing a method based on either the MEG or EEG +% overlapping-sphere technique, if 0 and when +% .HeadModelFile is specified, sphere parameters are +% loaded from the pre-computed HeadModel file. +% Default is 1. +% +% .BEM : Structure that specifies the necessary BEM parameters +% .Interpolative : Flag indicating whether exact or +% interpolative approach is used to compute +% the forward solution using BEM. +% if set to 1, exact computation is run on a +% set of points distributed wihtin the inner +% head volume and any subsequent request for +% a forward gain vector (e.g. during a +% volumic source scan using RAP-MUSIC) is +% computed using an interpolation of the +% forward gain vectors of the closest volumic +% grid points. This allows faster computation +% of the BEM solution during source search. +% if set to 0, exact computation is required +% at every source location. +% We recommend to set it to 0 (default) when +% sources have fixed location, e.g. +% constrained on the cortical surface. +% .EnvelopeNames : a cell array of strutures that specifies +% the ORDERED tessellated surfaces to be +% included in the BEM computation. +% .EnvelopeNames{k}.TessFile : A string for +% the name of the tessellation file +% containing the kth surface +% .EnvelopeNames{k}.TessName : A string for +% the name of the surface within the +% tessellation file This string should match +% one of the Comment strings in the +% tessellation file. The chosen surfaces must +% be ordered starting by the the innermost +% surface (e.g. brain or inner skull +% surface) and finishing with the outermost +% layer (e.g. the scalp) +% .Basis : set to either 'constant' or 'linear' (default) +% .Test : set to either 'Galerkin' or 'Collocation' (default) +% .ISA : Isolated-skull approach set to 0 or 1 (default is 1) +% .NVertMax : Maximum number of vertices per envelope, +% therefore leading to decimation of orginal +% surfaces if necessary +% (default is 1000) +% .ForceXferComputation: if set to 1, force recomputation of +% existing transfer matrices in current +% study folder (replace existing +% files); +% Default is 1 +% +% * +% * Fields Related to Sensor Information * +% * +% +% .ChannelFile : Specifies the name of the file containing the channel +% information (needs to be a BrainStorm channel file). If +% file does not exists and sensor information is provided in +% .ChannelLoc, a BrainStorm Channl file with name +% .ChannelFile is created +% Default is left blank as this information is extracted +% from the channel file associated to the chosen BrainStorm +% studyfile. +% .Channel : A full BrainStorm channel structure if no channel file is +% specified; +% Default is empty +% .ChannelType : A string specifying the type of channel in ChannelLoc. Can +% be either 'MEG' or 'EEG'. Note that the same channel type +% is assumed for every channel. +% Default is empty +% .ChannelLoc : Specifies the location of the channels where to compute +% the forward model Can be either a 3xNsens (for EEG or +% MEG-magnetometer) or 6xNsens matrix (for the +% MEG-gradiometer case). (for magnetometer or gradiometer +% MEG - channel weights are set to -1 and 1 for each +% magnetometer in the gradiometer respectively) Note that +% in the MEG-gradiometer case, the 3 first (res. last) rows +% of .ChannelLoc stand for each of the magnetometers of the +% gradiometer set. In the case of a mixture of MEG magneto +% and MEG gradio-meters, .ChannelLoc needs to be a 6xNsens +% matrix where the last 3 rows are filled with NaN for +% MEG-magnetometers If ones wants to handle both EEG and MEG +% sensors, please create a full ChannelFile and use the +% .ChannelFile option. +% Default is empty (Information extracted from the ChannelFile). +% .ChannelOrient : Specifies the orientation of the channels where to +% compute the EEG or MEG forward model Can be either a +% 3xNsens (for EEG and magnetometer MEG) or 6xNsens (for +% gradiometer MEG) matrix or a cell array of such matrices +% (one cell per type of method selected) +% Default is empty (Information extracted from the +% ChannelFile or assume radial orientation when +% .ChannelLoc is filled). +% +% * +% * Fields Related to Source Models * +% * +% .SourceModel : A vector indicating the type of source models to be +% computed; The following code is enfoced: +% -1 : Compute the forward fields of Current Dipole sources +% (available for all forward approaches) +% 1 : 1st-order Current Multipole Sources +% (available for sphere-based MEG approaches only) +% User can set OPTIONS.SourceModel to e.g., [-1 1] to +% compute forward models from both source models. +% Default is -1 +% +% +% * +% * Fields Related to Source Localization * +% * +% .Cortex : A structure specifying the Cortex surface +% envelope to serve as an image support with +% following fields. +% .FileName : A string specifying the name of +% the BrainStorm tessellation file +% containing the Cortex +% tessellation; +% .iGrid : An integer for the index of the +% Cortex surface in the Faces, +% Vertices and Comments cell arrays +% in the tessellation file (default +% is 1) +% Default is empty. +% .GridLoc : A 3xNsources matrix that contains the +% locations of the sources at which the forward +% model will be computed +% Default is empty (Information taken from +% OPTIONS.Cortex or OPTIONS.VolumeSourceGrid); +% .GridOrient : a 3xNsources matrix that forces the source +% orientation at every vertex of the .ImageGrid +% cortical surface; +% Defaults is empty; this information being +% extracted from the corresponding tessellated +% surface. +% .ApplyGridOrient : if set to 1, force computation of the forward +% fields by considering the local orientation of +% the cortical surface; +% If set to 0, a set of 3 orthogonal dipoles are +% considered at each vertex location on the +% tessellated surface. +% Default is 1. +% .VolumeSourceGrid : if set to 1, a 3D source grid is designed to +% fit inside the head volume and will serve as a +% source space for scannig techniques such as +% RAP-MUSIC; +% if set to 0, this grid will be computed at the +% first call of e.g. RAP-MUSIC); +% Default is 1 +% .VolumeSourceGridSpacing : Spacing in centimeters between two consecutive +% sources in the 3D source grid described above; +% Default is 2 cm. +% .VolumeSourceGridLoc : a 3xN matrix specifying the locations of the +% grid points that will be used to design the +% volumic search grid (see .VolumicSourceGrid) +% Default is empty (locations are estimated +% automatically to cover the estimated inner +% head volume) +% .SourceLoc : a 3xNsources matrix that contains the +% locations of the sources at which the forward +% model will be computed +% Default is empty (Information taken from +% OPTIONS.ImageGrid or +% OPTIONS.VolumeSourceGrid); +% .SourceOrient : a 3xNsources matrix that contains the +% orientations of the sources at which the +% forward model will be computed +% Default is empty. +% +% +% --------------------------------- OUTPUTS ------------------------------------ +% OUTPUT +% G if the number of sources (Nsources) if less than +% .ImageGridBlockSize then G is a gain matrix of dimension +% Nsensors x Nsources: Each column of G is the forward field +% created by a dipolar source of unit amplitude. Otherwise, G is +% the name of the binary file containing the gain matrix. This +% file can be read using the READ_GAIN function. +% OPTIONS Returns the OPTIONS structure with updated fields following the +% call to BST_HEADMODELER. Can be useful to obtain a full +% BrainStorm Channel structure when only the .ChannelLoc and +% possibly .ChannelOrient fields were provided. + +% ---------------------- 27-Jun-2005 10:43:31 ----------------------- +% ------ Automatically Generated Comments Block Using AUTO_COMMENTS_PRE7 ------- +% +% CATEGORY: Forward Modeling +% +% Alphabetical list of external functions (non-Matlab): +% toolbox\bem_gain.m +% toolbox\bem_xfer.m +% toolbox\berg.m +% toolbox\bst_message_window.m +% toolbox\colnorm.m +% toolbox\get_channel.m +% toolbox\get_user_directory.m +% toolbox\good_channel.m +% toolbox\gridmaker.m +% toolbox\inorcol.m +% toolbox\norlig.m +% toolbox\overlapping_sphere.m +% toolbox\rownorm.m +% toolbox\save_fieldnames.m +% toolbox\source_grids.m +% toolbox\view_surface.m +% +% Subfunctions in this file, in order of occurrence in file: +% BEMGaingridFname = bem_GainGrid(DataType,OPTIONS,BEMChanNdx) +% g = gterm_constant(r,rq) +% +% At Check-in: $Author: Mosher $ $Revision: 66 $ $Date: 6/27/05 8:59a $ +% +% This software is part of BrainStorm Toolbox Version 27-June-2005 +% +% Principal Investigators and Developers: +% ** Richard M. Leahy, PhD, Signal & Image Processing Institute, +% University of Southern California, Los Angeles, CA +% ** John C. Mosher, PhD, Biophysics Group, +% Los Alamos National Laboratory, Los Alamos, NM +% ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory, +% CNRS, Hopital de la Salpetriere, Paris, France +% +% See BrainStorm website at http://neuroimage.usc.edu for further information. +% +% Copyright (c) 2005 BrainStorm by the University of Southern California +% This software distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html . +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% ------------------------ 27-Jun-2005 10:43:31 ----------------------- + + + +% /---Script Author--------------------------------------\ +% | | +% | *** Sylvain Baillet Ph.D. | +% | Cognitive Neuroscience & Brain Imaging Laboratory | +% | CNRS UPR640 - LENA | +% | Hopital de la Salpetriere, Paris, France | +% | sylvain.baillet@chups.jussieu.fr | +% | | +% \------------------------------------------------------/ +% +% Date of creation: March 2002 + + +% ----------------------------- Script History --------------------------------- +% +% SB 07-Aug-2002 Fixed GridLoc saving issues - now GridLoc +% is a cell array of length one which indicates +% the name of the tessellation file that was +% used as an imaging support. +% SB 03-Sep-2002 Fixed minor bugs when function is called from command line +% Now bst_headmodeler can be called even when Brainstorm is not running +% SB 05-Sep-2002 BEM can now be called from command line as well. +% Updated script header +% SB 06-Sep-2002 Updated EEG BEM : added option for arbitrary reference of the +% potentials (takes now OPTIONS.EEGRef into account). +% SB 18-Nov-2002 Updated EEG reference management. +% SB 21-Nov-2002 Minor fixes for command line calls. +% SB 21-Nov-2002bis Fixed bug from the get(*,'VertexNormals') command that +% sometimes returns [0 0 0] at some vertex +% SB 23-Dec-2002 Correct HeadModelFile name is passed to OPTIONS output argument +% JCM 27-May-2004 Cleaning comments +% Found Matlab bug and temp solution. +% Matlab 6.5.0 bug, Technical Solution Number: 1-19NOK +% http://www.mathworks.com/support/solutions/data/1-19NOK.html?solution=1-19NOK +% Must REWIND first before fseek. +% Apparently fixed in 6.5.1 +% Example: +% status = fseek(fdest,0,'bof'); +% status = fseek(fdest,offset,'bof'); +% SB 08-Mar-05 Fixed bug in BEM computation +% ----------------------------- Script History --------------------------------- + +% Default options settings-------------------------------------------------------------------------------------------------- +DefaultMethod = {'meg_sphere','eeg_3sphereBerg'}; + +ReducePatchScalpNVerts = 500; % Number of vertices the scalp tessellation will be reduced to in OS computations +BEM_defaults = struct(... + 'Basis','linear',... + 'Test','galerkin',... + 'Interpolative',0,... + 'ISA',1,... + 'NVertMax',1000,... + 'ForceXferComputation', 1, ... + 'checksurf',0); + +Def_OPTIONS = struct(... + 'ApplyGridOrient',1,... + 'BEM', BEM_defaults,... + 'Channel', [],... + 'ChannelFile', '',... + 'ChannelLoc', '',... + 'ChannelOrient', '',... + 'ChannelType', '',... + 'Conductivity', [.33 .0042 .33],... + 'Cortex',[],... + 'EEGRef','',... + 'HeadCenter',[],... + 'HeadModelFile', '',... + 'HeadModelName','Default',... + 'ImageGridBlockSize', 2000,... + 'ImageGridFile', '',... + 'GridOrient',[],... + 'Method', {DefaultMethod},... + 'OS_ComputeParam', 1,... + 'PrefixFileName','bst_',... + 'Radii', [],... + 'Scalp',[],... + 'SourceLoc',[],... + 'SourceModel', [-1],... + 'SourceOrient',[],... + 'StudyFile','',... + 'TessellationFile','',... + 'VolumeSourceGrid',1,... + 'VolumeSourceGridSpacing', 2,... + 'VolumeSourceGridLoc', [],... + 'Verbose', 1 ... + ); + +SourceOrderString = {'Current Dipole',... + 'Unvalid Order (was Magnetic Dipole Moment)',... + 'Current Multipole Expansion',... + 'Current Dipole Pairs',... + 'Unvalid Order (was Magnetic Dipole Moment PAIRS)',... + 'Current Multipole Expansion Pairs'}; + +if nargin == 0 + if nargout > 1 + varargout{1} = Def_OPTIONS; + varargout{2} = Def_OPTIONS; + else + varargout{1} = Def_OPTIONS; + end + return +elseif nargin == 1 + if ischar(varargin{1}) % User enters only the studyfile name + StudyFile = varargin{1}; + OPTIONS = Def_OPTIONS; + elseif isstruct(varargin{1}) % User enters only the OPTION field + OPTIONS = varargin{1}; + else + errordlg('Uncorrect input parameter type, please check the help file'), varargout = cell(nargout,1); + return, + end +elseif nargin == 2 % No options were specified, apply default + StudyFile = varargin{1}; + OPTIONS = varargin{2}; +else + errordlg('Wrong number of arguments when calling head modeler') + varargout = cell(nargout,1); + return +end + +% Check field names of passed OPTIONS and fill missing ones with default values +DefFieldNames = fieldnames(Def_OPTIONS); +for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) | strcmp(DefFieldNames{k},'BEM') + if ~isfield(OPTIONS,DefFieldNames{k}) + + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + + elseif strcmp(DefFieldNames{k},'BEM') + + BEM_DefFieldNames = fieldnames(BEM_defaults); + for kk = 1:length(BEM_DefFieldNames) + if ~isfield(OPTIONS.BEM,BEM_DefFieldNames{kk}) + OPTIONS.BEM = setfield(OPTIONS.BEM,BEM_DefFieldNames{kk},getfield(BEM_defaults,BEM_DefFieldNames{kk})); + end + end + end + end +end + +if isempty(OPTIONS.Conductivity) + OPTIONS.Conductivity = Def_OPTIONS.Conductivity; +end + +clear Def_OPTIONS + + +if isempty(OPTIONS.HeadModelFile) & ~isempty(OPTIONS.ImageGridFile) + % Force creation of a headmodel file + OPTIONS.HeadModelFile = 'default'; +end + +OPTIONS.HeadModelFileOld = OPTIONS.HeadModelFile; + +% What type of forward model (MEG and/or EEG) ? +DataType.MEG = strmatch('meg',OPTIONS.Method); % Rank of the respective forward method in cell array Method (ie could be Method = {'meg_bem','eeg_sphere'} or vice-versa) +DataType.EEG = strmatch('eeg',OPTIONS.Method); + +if ~iscell(OPTIONS.Method) + OPTIONS.Method = {OPTIONS.Method}; +end + +MegMethod = []; +if ~isempty(DataType.MEG) + MegMethod = OPTIONS.Method{DataType.MEG}; % String indicating the forward method selected for MEG (res. EEG) +end +EegMethod = []; +if ~isempty(DataType.EEG) + EegMethod = OPTIONS.Method{DataType.EEG}; +end + + +% Check inputs integrity + +%Source models +if ~isempty(find(OPTIONS.SourceModel == 0)) | ~isempty(find(abs(OPTIONS.SourceModel) > 1)) % unValid source models + if ~isempty(DataType.MEG) + errordlg('Valid source model orders for MEG are: -1 (Current Dipole) and 1 (fist-order Current Multipole Expansion)') + end + if ~isempty(DataType.EEG) + errordlg('Valid source model order for EEG is: -1 (Current Dipole) ') + end + varargout = cell(nargout,1); + return +end + +% Source locations +if isempty(OPTIONS.SourceLoc) & ~OPTIONS.VolumeSourceGrid & isempty(OPTIONS.Cortex) % No source locations were specified + errordlg('No source locations are specified. Please fill either one of the following fields of OPTIONS: .SourceLoc / .VolumeSourceGrid / .Cortex') + varargout = cell(nargout,1); + return +end + + +%-------------------------------------------------------------------------------------------------------------------------------------------- +% +% HEAD MODELING BEGINS +% +%-------------------------------------------------------------------------------------------------------------------------------------------- + +if OPTIONS.Verbose, + + clockk = fix(clock); + time0 = clock; + + bst_message_window({... + ' ',... + '__________________________________________',... + sprintf(... + 'Head modeling begins (%s - %dH %dmin %ds)',date,clockk(4:6))... + }) + +end + +User = get_user_directory; +if isempty(User) % Function is called from command line: BrainStorm is not running + % Use default folders + User.SUBJECTS = pwd; + User.STUDIES = pwd; +end +try +cd(User.STUDIES) +catch +end + +% Get all Subject and Study information------------------------------------------------------------------------------------------------------ +if exist('StudyFile','var') + if OPTIONS.Verbose, bst_message_window('Loading Study and Subject Information...'), end + try + load(StudyFile) % Load study information + [StudyPath,tmp,ext] = fileparts(StudyFile); clear tmp + catch + errordlg(['Could not find ',StudyFile,' in current Matlab path']) + varargout = cell(nargout,1); + return + end + + if isempty(OPTIONS.StudyFile) + OPTIONS.StudyFile = StudyFile; + end + + SubjectFile = BrainStormSubject; clear BrainStormSubject + + OPTIONS.rooot = findstr(StudyFile,'brainstormstudy.mat'); + if isempty(OPTIONS.rooot) + errordlg('Study file name should be of the form ''*brainstormstudy.mat''') + varargout = cell(nargout,1); + return + end + OPTIONS.rooot = strrep(StudyFile,'brainstormstudy.mat',''); + + Study = load(StudyFile); + %User = get_user_directory; + try + cd(User.SUBJECTS) + Subject = load(Study.BrainStormSubject); + catch + errordlg(sprintf('Please make sure the subject''s information in %s is available on this plateform',Study.BrainStormSubject)); return + end + + if isempty(OPTIONS.TessellationFile) % No Tessellation file was passed to the headmodeler + if isfield(Subject,'Tesselation') + OPTIONS.TessellationFile = Subject.Tesselation; % Take default (OBSOLETE as for BsT MMII because we now consider all tessellation files in Subject's folder) + else + OPTIONS.TessellationFile = ''; + %[OPTIONS.TessellationFile,DataPopup, Leader] = find_brainstorm_files('tess',fullfile(Users.SUBJECTS,OPTIONS.subjectpath)); + end + end +end + +% Get Channel Information ------------------------------------------------------------------------------------------------------------------ +if ~isempty(OPTIONS.Channel) + Channel = OPTIONS.Channel; +else + if isempty(OPTIONS.ChannelFile) & isempty(OPTIONS.ChannelLoc) % Load Channel file in current folder + + [Channel, ChannelFile] = get_channel(fullfile(User.STUDIES,OPTIONS.StudyFile)); + OPTIONS.ChannelFile = fullfile(fileparts(fullfile(User.STUDIES,OPTIONS.StudyFile)),ChannelFile); + + if isempty(ChannelFile) + errordlg(sprintf('Channel file %s is missing. Please have it available it the current study folder.',OPTIONS.ChannelFile), 'Missing Channel File') + return + end + + elseif isempty(OPTIONS.ChannelLoc) & exist(OPTIONS.ChannelFile,'file') % If no specific channel locations are given and channel file exists, load the proper channel file + + OPTIONS.rooot = strrep(lower(OPTIONS.ChannelFile),'channel.mat',''); + try + load(OPTIONS.ChannelFile) + catch + cd(User.STUDIES) + load(OPTIONS.ChannelFile) + end + + else % Create a dummy Channel structure with Channel Locations (res. Orientations) specified in OPTIONS.ChannelLoc (res .ChannelOrient) + + if OPTIONS.Verbose, bst_message_window('Creating the channel structure from information in the OPTIONS fields. . .'), end + + % Get Channel Locations + nchan = size(OPTIONS.ChannelLoc,2); % Number of channels + Channel = struct('Loc',[],'Orient',[],'Comment','','Weight',[],'Type','','Name',''); + Channel(1:nchan) = deal(Channel); + + ChanType = upper(OPTIONS.ChannelType); + if isempty(ChanType) + errordlg('Please specify a channel type (i.e. MEG or EEG) in the ChannelType field of OPTIONS'), + bst_message_window('Please specify a channel type (i.e. MEG or EEG) in the ChannelType field of OPTIONS'), + varargout = cell(nargout,1); + return + end + [Channel(:).Type] = deal(ChanType); + if size(OPTIONS.ChannelLoc,1) == 6 % MEG Gradiometers or mixture gradio/magneto meters + OPTIONS.ChannelLoc = reshape(OPTIONS.ChannelLoc,3,nchan*2); + iGradFlag = 1; % Flag - gradiometer-type sensor set + else + iGradFlag = 0; % Flag - EEG or magnetometer-type sensor set + end + ichan = 1; + for k = 1:nchan + if iGradFlag + Channel(k).Loc = OPTIONS.ChannelLoc(:,ichan:ichan+1); + ichan = ichan+2; + else + if strcmp(ChanType,'MEG') + Channel(k).Loc = OPTIONS.ChannelLoc(:,ichan); + elseif strcmp(ChanType,'EEG') % Artificially add a dummy column full of zeros to each Channel(k).Loc + Channel(k).Loc = [OPTIONS.ChannelLoc(:,ichan) [0 0 0]'];; + end + ichan = ichan+1; + end + Channel(k).Name = sprintf('%s %d',ChanType,k); + Channel(k).Comment = int2str(k); + end + clear ichan k + + % Get Channel Orientations + if isempty(OPTIONS.ChannelOrient) & strcmp(ChanType,'MEG') % No channel orientation were specified: use radial sensors + if OPTIONS.Verbose, bst_message_window('Assign radial orientation to all Channels. . .'), end + if isempty(OPTIONS.HeadCenter) + if iGradFlag + Vertices = OPTIONS.ChannelLoc(:,1:2:end)'; + else + Vertices = OPTIONS.ChannelLoc'; + end + + nscalp = size(Vertices,1); + if nscalp > 500 % 500 points is more than enough to compute scalp's best fitting sphere + Vertices = Vertices(unique(round(linspace(1,nscalp,500))),:); + nscalp = size(Vertices,1); + end + nmes = size(Vertices,1); + + % Run parameters fit -------------------------------------------------------------------------------------------------------------- + mass = mean(Vertices); % center of mass of the scalp vertex locations + R0 = mean(norlig(Vertices - ones(nscalp,1)*mass)); % Average distance between the center of mass and the scalp points + vec0 = [mass,R0]; + + [minn,brp] = fminsearch('dist_sph',vec0,[],Vertices); + OPTIONS.HeadCenter = minn(1:end-1); + if isempty(OPTIONS.Radii) + OPTIONS.Radii = minn(end); + OPTIONS.Radii = minn(end)*[1/1.14 1/1.08 1]; + end + + if OPTIONS.Verbose, bst_message_window({... + sprintf('Center of the Sphere : %3.1f %3.1f %3.1f (cm)',100*OPTIONS.HeadCenter),... + sprintf('Radius : %3.1f (cm)',100*OPTIONS.Radii(3)),... + '-> DONE',' '}) + end + + clear minn brp mass R0 Vertices vec0 + end + + tmp = [Channel.Loc] - repmat(OPTIONS.HeadCenter',1,nchan*(1+(iGradFlag==1))); + OPTIONS.ChannelOrient = tmp*inorcol(tmp); % Radial orientation for every channel + clear tmp + elseif ~isempty(OPTIONS.ChannelOrient) & strcmp(ChanType,'MEG') & iGradFlag + OPTIONS.ChannelOrient = reshape(OPTIONS.ChannelOrient,3,nchan*2); + end + + if strcmp(ChanType,'MEG') + for k=1:nchan + Channel(k).Orient = OPTIONS.ChannelOrient(:,((1+(iGradFlag==1))*k-1):(1+(iGradFlag==1))*k); + end + end + + clear k + + % Define Weights + if iGradFlag + [Channel(:).Weight] = deal([1 -1]); + else + [Channel(:).Weight] = deal([1]); + end + + if strcmp(ChanType,'MEG') % Force no reference channels + Channel(1).irefsens = []; + end + + % New Channel stbemructure completed: save as a new channel file + if ~isempty(OPTIONS.ChannelFile) + %OPTIONS.ChannelFile = [OPTIONS.rooot,'channel.mat']; + save(OPTIONS.ChannelFile,'Channel') + if OPTIONS.Verbose, bst_message_window({... + sprintf('Channel file created in : %s',OPTIONS.ChannelFile),... + '-> DONE',' '}), end + end + + end + + %load(OPTIONS.ChannelFile) + OPTIONS.Channel = Channel; +end + +% Find MEG and EEG channel indices +MEGndx = good_channel(Channel,[],'MEG'); +EEGndx = good_channel(Channel,[],'EEG'); +EEGREFndx = good_channel(Channel,[],'EEG REF'); + +MEG = ~isempty(MEGndx) & ~isempty(DataType.MEG); % == 1 if MEG is requested and is available +EEG = ~isempty(EEGndx) & ~isempty(DataType.EEG); + +if ~EEG & ~MEG + errordlg('Please check that data (MEG or EEG) and channel types are compatible.') + return +end + +% Test whether CME models are requested for EEG +if ~isempty(find(OPTIONS.SourceModel == 1)) & EEG + if MEG + if OPTIONS.Verbose + bst_message_window('wrap',... + {'',... + 'CME model not available for EEG - Skipping. . .',... + 'Keeping it for MEG forward modeling only',... + ''... + }) + end + else % EEG only is requested + errordlg(... + {'CME model not available for EEG - Skipping. . .',... + 'Keeping it for MEG forward modeling only'... + }) + return + end + +end + +% Detect EEG reference - if none is specified in the .Comment or Type fields, +% and if none was passed through OPTIONS.EEGRef +% -> Apply average-referencing of the potentials by default. + +if EEG + if isempty(OPTIONS.EEGRef) + + % EEG Reference Channel + EEGREFndx = good_channel(Channel,[],'EEG REF'); + if isempty(EEGREFndx) % Average EEG reference anyway + [Channel(EEGndx).Comment] = deal('AVERAGE REF'); + end + + else % EEG Reference is specified + + switch(OPTIONS.EEGRef) + case 'AVERAGE REF' + [Channel(:).Comment] = deal('AVERAGE REF'); + + otherwise + + EEGREFndx = strmatch(OPTIONS.EEGRef,char(Channel(:).Name)); + if isempty(EEGREFndx) + errordlg(sprintf(... + 'No channel named ''%s'' was found amongst available EEG channels. Cannot use it as a reference for EEG.',OPTIONS.EEGRef... + )) + return + end + + end + + end + + % if isempty(EEGREFndx) & ~MEG % No reference electrode was defined for the EEG stop if no MEG to compute... + % errordlg('Please make sure you have defined a reference for the EEG') + % return + % elseif isempty(EEGREFndx) & MEG % Skip EEG forward modeling and proceed to MEG + % EEG = 0; + % if OPTIONS.Verbose + % bst_message_window({... + % 'No reference was defined for the EEG',... + % 'Skipping EEG modeling and completing MEG only...',... + % }) + % end + % end + +end + +if OPTIONS.Verbose, + if EEG & MEG + if ~isempty(EEGREFndx) + bst_message_window({'Channel count for current computation:',[int2str(length(MEGndx)), ' MEG Channels'],... + sprintf('%d EEG Channels with Reference: %s',length(EEGndx),Channel(EEGREFndx).Name),' '}) + else + bst_message_window({'Channel count for current computation:',[int2str(length(MEGndx)), ' MEG Channels'],... + sprintf('%d EEG Channels with Average Reference',length(EEGndx)),' '}) + end + + elseif MEG + bst_message_window({'Channel count for current computation:',[int2str(length(MEGndx)), ' MEG Channels'],... + ' '}) + elseif EEG + if ~isempty(EEGREFndx) + bst_message_window({'Channel count for current computation:',... + sprintf('%d EEG Channels with Reference: %s',length(EEGndx),Channel(EEGREFndx).Name),' '}) + else + bst_message_window({'Channel count for current computation:',... + sprintf('%d EEG Channels with Average Reference',length(EEGndx)),' '}) + end + + end +end + +if MEG & isempty(MEGndx) % User wants to compute MEG but no MEG data is available + errordlg('Sorry - No MEG data is available'), return +end + +if EEG & isempty(EEGndx) % User wants to compute EEG but no EEG data is available + errordlg('Sorry - No EEG data is available'), return +end + + +% Computation of parameters of the best-fitting sphere -------------------------------------------------------------------------------------------------------------- +if length(findstr('bem',[OPTIONS.Method{:}])) ~= length(OPTIONS.Method)% Only if sphere-based head model is requested in any modality (MEG or EEG) + + % Best-fitting sphere parameters -------------------------------------------------------------------------------------------------------------- + if isempty(OPTIONS.HeadCenter) | isempty(OPTIONS.Radii) + + if OPTIONS.Verbose, bst_message_window('Estimating Center of the Head. . .'), end + + if isempty(OPTIONS.Scalp) % Best-fitting sphere is derived from the sensor array + % ans = questdlg('No scalp surface was selected - Do you want to use a spherical approximation of the head derived from the sensor locations instead ?',... + % '','Yes','No','Yes'); + if EEG & length(EEGndx) > 9 % If EEG is available but a reasonable number of electrodes, use it to compute the sphere parameters + ndx = [EEGndx]; % Compute Sphere parameters from EEG sensors only + else + ndx = [MEGndx]; + end + + Vertices = zeros(length(ndx),3); + for k=1:length(ndx) + Vertices(k,:) = Channel(ndx(k)).Loc(:,1)'; + end + + else % Best-fitting sphere is computed from the set of vertices of the scalp surface enveloppe + + try + load(fullfile(User.SUBJECTS,OPTIONS.Scalp.FileName),'Vertices') + catch + load(OPTIONS.Scalp.FileName,'Vertices') + end + + if ~isfield(OPTIONS.Scalp,'iGrid') % Apply Default + OPTIONS.Scalp.iGrid = 1; + end + + try + Vertices = Vertices{OPTIONS.Scalp.iGrid}'; + catch + errordlg(sprintf(... + 'Tessellation file %s does not contain %d enveloppes',... + OPTIONS.Scalp.FileName,OPTIONS.Scalp.iGrid)) + end + end + + nscalp = size(Vertices,1); + nmes = size(Vertices,1); + + % Run parameters fit -------------------------------------------------------------------------------------------------------------- + mass = mean(Vertices); % center of mass of the scalp vertex locations + R0 = mean(norlig(Vertices - ones(nscalp,1)*mass)); % Average distance between the center of mass and the scalp points + vec0 = [mass,R0]; + + [SphereParams,brp] = fminsearch('dist_sph',vec0,[],Vertices); + + + if OPTIONS.Verbose + bst_message_window({... + sprintf('Center of the Sphere : %3.1f %3.1f %3.1f (cm)',100*SphereParams(1:end-1)'),... + sprintf('Radius : %3.1f (cm)',100*SphereParams(end)),... + '-> DONE',' '}) + + end + + end % no head center and sphere radii were specified by user + + % Assign default values for sphere parameters + % if none were specified before + if isempty(OPTIONS.Radii) + OPTIONS.Radii = SphereParams(end)*[1/1.14 1/1.08 1]; + end + + if isempty(OPTIONS.HeadCenter) + OPTIONS.HeadCenter = SphereParams(1:end-1)'; + end + + if isempty(OPTIONS.Conductivity) + OPTIONS.Conductivity = [.33 .0042 .33]; + end + +end % Use BEM Approach, so proceed to the selection of the envelopes + +% --------------------------------------------------------------------------------------------------------- +%Create HeadModel Param structure +Param(1:length(Channel)) = deal(struct('Center',[],'Radii',[],'Conductivity',[],'Berg',[])); + +if ~isempty(findstr('os',[OPTIONS.Method{:}])) % Overlapping-Sphere EEG or MEG is requested: load the scalp's tessellation + + if isempty(OPTIONS.Scalp) + errordlg('Please specify a subject tessellation file for Scalp enveloppe in OPTIONS.Scalp when using Overlapping-Sphere forward approach'); + return + end + + % load(fullfile(User.SUBJECTS,BrainStorm.SubjectTess),'Faces'); + load(fullfile(User.SUBJECTS,OPTIONS.Scalp.FileName),'Faces','Vertices'); + + Faces = Faces{OPTIONS.Scalp.iGrid}; + Vertices = Vertices{OPTIONS.Scalp.iGrid}'; + + if size(Vertices,1) > ReducePatchScalpNVerts % Reducepatch the scalp tessellation for fastest OS computation + nfv = reducepatch(Faces,Vertices,2*ReducePatchScalpNVerts); + if OPTIONS.Verbose, bst_message_window({... + sprintf('Decimated scalp tessellation from %d to %d vertices.',size(Vertices,1),size(nfv.vertices,1)),... + ' '}); + end + clear Faces Vertices + SubjectFV.vertices = nfv.vertices'; + SubjectFV.faces = nfv.faces; + clear nfv + else + SubjectFV.vertices = Vertices; % Available from the computation of the head center above + clear Vertices + SubjectFV.faces = Faces; clear Faces + end + + if length(findstr('os',[OPTIONS.Method{:}])) == 2 % OS approach requested fro both MEG and EEG + ndx = [MEGndx,EEGndx]; + + else + if MEG + if strcmpi('meg_os',OPTIONS.Method{DataType.MEG}) % OS for MEG only + ndx = MEGndx; + end + end + + if EEG + if strcmpi('eeg_os',OPTIONS.Method{DataType.EEG}) % OS for EEG only + ndx = [EEGndx, EEGREFndx]; + end + end + end + if OPTIONS.Verbose + bst_message_window({... + ' ', 'Computing Overlapping-sphere model. . .'}) + end + + if isempty(OPTIONS.HeadModelFile) | OPTIONS.OS_ComputeParam + + Sphere = overlapping_sphere(Channel(ndx),SubjectFV,OPTIONS.Verbose,OPTIONS.Verbose); % Compute all spheres parameters + if OPTIONS.Verbose + bst_message_window({... + 'Computing Overlapping-sphere model -> DONE',' '}) + end + [Param(ndx).Center] = deal(Sphere.Center); + [Param(ndx).Radii] = deal(Sphere.Radius); + [Param(ndx).Conductivity] = deal(OPTIONS.Conductivity); + + elseif exist(OPTIONS.HeadModelFile,'file') + + load(OPTIONS.HeadModelFile,'Param') % or use precomputed + if OPTIONS.Verbose + bst_message_window({... + sprintf('Sphere parameters loaded from : %s -> DONE',OPTIONS.HeadModelFile),' '}) + end + + else + + errordlg(sprintf('Headmodel file %s does not exist in Matlab''s search path',OPTIONS.HeadModelFile)) + return + + end + +end + +% Saving HeadModel's Param structure in the headmodel file +if strcmp(lower(OPTIONS.HeadModelFile),'default') + if ~isfield(OPTIONS,'rooot') + OPTIONS.rooot = OPTIONS.PrefixFileName; + end + OPTIONS.HeadModelFile = [OPTIONS.rooot,'headmodel.mat']; + ifile = 0; + while exist(OPTIONS.HeadModelFile,'file') % Do not overwrite headmodel files + ifile = ifile + 1; + OPTIONS.HeadModelFile = [OPTIONS.rooot,'headmodel_',int2str(ifile),'.mat']; + end + +elseif ~isfield(OPTIONS,'rooot') & ~isempty(OPTIONS.HeadModelFile) + OPTIONS.rooot = strrep(OPTIONS.HeadModelFile,'headmodel.mat',''); +end +if ~isfield(OPTIONS,'rooot') % Last Chance + OPTIONS.rooot = 'bst_'; +end + +if ~isempty(findstr('sphere',[OPTIONS.Method{:}])) % Single or nested-sphere approaches + + [Param([MEGndx, EEGndx, EEGREFndx]).Center] = deal(OPTIONS.HeadCenter); + [Param([MEGndx, EEGndx, EEGREFndx]).Radii] = deal(OPTIONS.Radii); + [Param([MEGndx, EEGndx, EEGREFndx]).Conductivity] = deal(OPTIONS.Conductivity); + + if EEG & strcmpi('eeg_3sphereberg',lower(OPTIONS.Method{DataType.EEG})) % BERG APPROACH + + if ~isempty(OPTIONS.HeadModelFile) & exist(OPTIONS.HeadModelFile,'file') + if OPTIONS.Verbose, bst_message_window('Checking for previous EEG "BERG" parameters'), end + ParamOld = load(OPTIONS.HeadModelFile,'Param'); + iFlag = 0; % Flag + if isfield(ParamOld.Param,'Berg') & ~isempty(ParamOld.Param(1).Radii) + % Check if these older parameters were computed with the same as current radii and conductivity values + if ParamOld.Param(1).Radii ~= Param(1).Radii; + iFlag = 1; + end + if ParamOld.Param(1).Conductivity ~= Param(1).Conductivity; + iFlag = 1; + end + else + iFlag = 1; + end + else + iFlag = 1; + end + + if iFlag == 1 + if OPTIONS.Verbose , bst_message_window('Computing EEG "BERG" Parameters. . .'), end + [mu_berg_tmp,lam_berg_tmp] = berg(OPTIONS.Radii,OPTIONS.Conductivity); + Param(EEGndx(1)).Berg.mu = mu_berg_tmp; clear mu_berg_tmp + Param(EEGndx(1)).Berg.lam = lam_berg_tmp; clear lam_berg_tmp + if OPTIONS.Verbose, bst_message_window({'Computing EEG "BERG" Parameters -> DONE',' '}), end + else + if OPTIONS.Verbose , bst_message_window('Using Previous EEG "BERG" Parameters'), end + Param(EEGndx(1)).Berg.mu = ParamOld.Param(1).Berg.mu; + Param(EEGndx(1)).Berg.lam = ParamOld.Param(1).Berg.lam; clear ParamOld + end + [Param.Berg]= deal(Param(EEGndx(1)).Berg); + + end + +end + +if ~isempty(findstr('bem',[OPTIONS.Method{:}])) % BEM approaches - Compute transfer matrices + + if OPTIONS.BEM.Interpolative==0 & OPTIONS.VolumeSourceGrid %& isempty(OPTIONS.Cortex) % User wants volumic grid : force Interpolative approach + OPTIONS.BEM.Interpolative = 1; % CBB (SB, 07-May-2004)| Should work also for volumic grid + hwarn = warndlg('Volumic Source Grid BEM is only available for interpolative BEM. BEM computation will be now forced to interpolative. If you want a non-interpolative BEM on a cortical image grid, first uncheck the Volumic Grid box from headmodeler gui.','Limitation from current BrainStorm version'); + drawnow + waitfor(hwarn) + end + + if MEG + if ~isempty(findstr('bem',OPTIONS.Method{DataType.MEG})) % BEM is requested for MEG + BEMChanNdx{DataType.MEG} = MEGndx; + end + end + + if EEG + if ~isempty(findstr('bem',OPTIONS.Method{DataType.EEG})) % BEM is requested for EEG + BEMChanNdx{DataType.EEG} = sort([EEGndx,EEGREFndx]); % EEGREFndx = [] is average ref + end + end + + OPTIONS.Param = Param; + + if OPTIONS.BEM.Interpolative % Computation of gain matrix over 3D interpolative grid + if OPTIONS.BEM.ForceXferComputation + BEMGaingridFileName = bem_GainGrid(DataType, OPTIONS, BEMChanNdx); % Computation of the BEM gain matrix on the 3D interpolative grid for MEG and/or EEG data + else + try + BEMGaingridFileName = OPTIONS.BEM.GaingridFileName; + catch + cd(User.STUDIES) + BEMGaingridFileName = bem_GainGrid(DataType, OPTIONS, BEMChanNdx); % Computation of the BEM gain matrix on the 3D interpolative grid for MEG and/or EEG data + end + end + + if MEG & EEG + [Param(MEGndx).bem_gaingrid_mfname] = deal(BEMGaingridFileName.MEG); + [Param([EEGndx]).bem_gaingrid_mfname] = deal(BEMGaingridFileName.EEG); + else + [Param(:).bem_gaingrid_mfname] = deal(BEMGaingridFileName); + end + + else % BEM gain matrix computation over cortical surface + + + BEMGaingridFileName = bem_GainGrid(DataType, OPTIONS, BEMChanNdx); + + [Param(:).bem_gaingrid_mfname] = deal(''); + + end + + + OPTIONS = rmfield(OPTIONS,'Param'); + + ndx = sort([BEMChanNdx{:}]); + + + [Param(ndx).Center] = deal([]); + test=0; % this test is nowhere defined ? + + if OPTIONS.VolumeSourceGrid + % Now define the outer scalp envelope for the source volume gridding if requested + + if OPTIONS.BEM.ForceXferComputation | ~test + global nfv + SubjectFV.vertices = nfv(end).vertices'; + SubjectFV.faces = nfv(end).faces; clear Faces + else + load(fullfile(User.SUBJECTS,fileparts(OPTIONS.Subject),OPTIONS.BEM.EnvelopeNames{end}.TessFile)) + + idScalp = find(strcmpi(OPTIONS.BEM.EnvelopeNames{end}.TessName,Comment)); clear Comment + if isempty(idScalp) + errodlg(sprintf(... + 'Scalp tessellation %s was not found in %s.',OPTIONS.BEM.EnvelopeNames{end}.TessName, OPTIONS.BEM.EnvelopeNames{end}.TessFile),... + 'Error during BEM computation') + return + end + + SubjectFV.vertices = Vertices{idScalp}'; clear Vertices + SubjectFV.faces = Faces{idScalp}; clear Faces + end + + end + +end % if BEM + +if EEG + + switch(lower(OPTIONS.Method{DataType.EEG})) + case 'eeg_sphere' + [Param(EEGndx).EEGType] = deal('EEG_SINGLE'); + case 'eeg_3sphere' + [Param(EEGndx).EEGType] = deal('EEG_3SHELL'); + case 'eeg_3sphereberg' + [Param(EEGndx).EEGType] = deal('EEG_BERG'); + case 'eeg_os' + [Param(EEGndx).EEGType] = deal('EEG_OS'); + case 'eeg_bem' + [Param(EEGndx).EEGType] = deal('BEM'); + if EEG & ~MEG + [Param(EEGndx).bem_gaingrid_mfname] = deal(BEMGaingridFileName); + end + end + +else + + tmp = []; + [Param.Conductivity] = deal(tmp); + [Param.Berg] = deal(tmp); + [Param.EEGType] = deal(tmp); + +end + + +%_________________________________________________________________________________________________________________________________________________________________________ +% +% The following part is an adaptation of the former HEADMODEL_MAKE script +% +% ________________________________________________________________________________________________________________________________________________________________________ + + +% Allocate function names depending on the selected forward approaches specified in the Method argument +Function = cell(1,length(Channel)); %allocate function names + +if MEG + if ~isempty(findstr('bem',OPTIONS.Method{DataType.MEG})) % MEG BEM + Function(MEGndx) = deal({'meg_bem'}); + if isfield(Channel(MEGndx(1)),'irefsens') + Function(Channel(MEGndx(1)).irefsens) = deal({'meg_bem'}); + end + + else + Function(MEGndx) = deal({'os_meg'}); + if isfield(Channel(MEGndx(1)),'irefsens') + Function(Channel(MEGndx(1)).irefsens) = deal({'os_meg'}); + end + if isfield(OPTIONS,'BEM') + OPTIONS = rmfield(OPTIONS,'BEM'); + end + + end +end + + +if EEG + if ~isempty(findstr('bem',OPTIONS.Method{DataType.EEG})) % MEG BEM + Function(EEGndx) = deal({'eeg_bem'}); + else + Function(EEGndx) = deal({'eeg_sph'}); + if isfield(OPTIONS,'BEM') + OPTIONS = rmfield(OPTIONS,'BEM'); + end + end + +end +% -------------------------------------------------------------------------------------------------------- + +DIMS = [3 12]; % number of columns for each parametric source model: Current Dipole / Current Multipole +HeadModel.Param = Param; +HeadModel.Function = Function; + +if OPTIONS.VolumeSourceGrid % if SearchGain matrices are requested + + SearchGain = cell(1,6); % One cell for each source order + pairs of sync. sources - keep 2 'phantom' cells for former Magnetic Dipole model + + %------------------------------ Computing SearchGridLoc and SearchGain------------------------------------------- + + if ~isempty(findstr(MegMethod,'bem')) | (EEG & ~MEG) + if OPTIONS.Verbose, bst_message_window(... + {'Forward modeling not available for EEG''s Current Mulipole models or the BEM approach','Computing forward fields for Current Dipole models. . .'... + ,' '}), end + %return + OPTIONS.SourceModel = [-1]; % Force current dipole source model when MEG BEM or any EEG is requested + end + + if OPTIONS.Verbose, bst_message_window(... + 'Computing the Gain Matrices from the Volumic Search Grid. . .'), end + + % Prepare call to source_grids + + GUI.VALIDORDER = OPTIONS.SourceModel; + GUI.SPACING = 10*OPTIONS.VolumeSourceGridSpacing; % Pass it to source_grids in millimeters + GUI.VERBOSE = OPTIONS.Verbose; + GUI.MEG = MEG; + GUI.EEG = EEG; + + if ~exist('SubjectFV','var') + % Create a spherical tessellation of the INNER SKULL surface boundary for source gridding + + [x,y,z] = sphere(30); + %Scale to Radius BrainStorm.R + [TH,PHI,R] = cart2sph(x,y,z); + if OPTIONS.Radii(1) == 0 + error('The sphere radius you have specified is ZERO - please change it to a non null positive value') + end + R = OPTIONS.Radii(1) * ones(size(R)); + [x,y,z] = sph2cart(TH,PHI,R); + + % Tessellate both hemispheres + Im = find(z>=0); + tri = delaunay(x(Im),y(Im)); + + %Gather everything into the same patch + SubjectFV.vertices = [x(Im),y(Im),z(Im);... + x(Im),y(Im),-z(Im)]; + + % Translate about the head center + SubjectFV.vertices = SubjectFV.vertices + repmat(OPTIONS.HeadCenter',size(SubjectFV.vertices,1),1); + + SubjectFV.faces = [tri;tri(:,[3 2 1])+max(tri(:))]; + + clear x y z R TH PHI Im tri + + end + + HeadModel = source_grids(HeadModel,Channel,SubjectFV,GUI); + clear SubjectFV + + if OPTIONS.Verbose, bst_message_window({... + '-> DONE',... + 'Now saving HeadModel file. . .'... + }) + end + + % Now save VolumeSourceGrid headmodel(s) + SaveHeadModel.Param = HeadModel.Param; + SaveHeadModel.Function = HeadModel.Function; + + if strcmpi(OPTIONS.HeadModelName,'Default') % Specify default HeadModelName + if MEG & EEG + SaveHeadModel.HeadModelName = sprintf('%s | %s', OPTIONS.Method{DataType.MEG},OPTIONS.Method{DataType.EEG}); + elseif MEG + SaveHeadModel.HeadModelName = sprintf('%s', OPTIONS.Method{DataType.MEG}); + elseif EEG + SaveHeadModel.HeadModelName = sprintf('%s', OPTIONS.Method{DataType.EEG}); + end + else + SaveHeadModel.HeadModelName = OPTIONS.HeadModelName; + end + + if ~isempty(OPTIONS.HeadModelFile), + [HeadModelFilePath,HeadModelFile,ext] = fileparts(OPTIONS.HeadModelFile); + end + + try + cd(User.STUDIES) + catch + end + + for k = 1:length(GUI.VALIDORDER) % One file per source order + + % Specify Source Model Name and Other Fields + if GUI.VALIDORDER(k) == -1 + SourceOrderString = 'CD'; % Current Dipole + elseif GUI.VALIDORDER(k) == 0 + SourceOrderString = 'MD'; % Magnetic Dipole + elseif GUI.VALIDORDER(k) == 1 + SourceOrderString = 'CME'; % Current Multipole + end + + [SaveHeadModel.Param.Order] = deal(GUI.VALIDORDER(k)); + SaveHeadModel.SourceOrder = GUI.VALIDORDER(k); % Alternative to previous line + SaveHeadModel.HeadModelType = 'SearchGrid'; + if MEG + SaveHeadModel.MEGMethod = OPTIONS.Method{DataType.MEG}; + end + if EEG + SaveHeadModel.EEGMethod = OPTIONS.Method{DataType.EEG}; + end + + SaveHeadModel.GridName = {sprintf('%s Volumic Grid : %3.1f cm spacing',SourceOrderString, OPTIONS.VolumeSourceGridSpacing)}; + SaveHeadModel.GridLoc = HeadModel.GridLoc(GUI.VALIDORDER(k)+2); + SaveHeadModel.Gain = {single(HeadModel.Gain{GUI.VALIDORDER(k)+2})}; % Convert to single precision gain matrix as in BST MMII convention + + % now collect together and save + if ~isempty(OPTIONS.HeadModelFile), % User has provided a headmodel file name + SaveHeadModelFile = fullfile(HeadModelFilePath,[HeadModelFile,... + sprintf('VolGrid_%s',SourceOrderString),... + ext]); + ifile = 0; + while exist(SaveHeadModelFile,'file') % Do not overwrite headmodel files + ifile = ifile + 1; + SaveHeadModelFile = fullfile(HeadModelFilePath,[HeadModelFile,... + sprintf('VolGrid_%s',SourceOrderString),... + '_',int2str(ifile),ext]); + end + + + if OPTIONS.Verbose, bst_message_window({... + sprintf('Writing HeadModel file:'),... + sprintf('%s', SaveHeadModelFile)... + }) + end + + if strcmp(lower(OPTIONS.HeadModelFileOld),'default') + OPTIONS.HeadModelFile = SaveHeadModelFile; + end + + save_fieldnames(SaveHeadModel, SaveHeadModelFile); + + if OPTIONS.Verbose, bst_message_window(... + {'-> DONE',' '}), end + end + + end + + OPTIONS.HeadModelName = SaveHeadModel.HeadModelName; + + if OPTIONS.Verbose, bst_message_window(... + {'Grid gain matrices are saved','RAP-MUSIC & Least-Squares Fits Approaches are now available',' '}) + end + +end + + +%% ------------------------------------------------------------------------- +% +% Now proceed to forward modeling of cortical grids or at some other specific source locations +% +%% ------------------------------------------------------------------------- + + +if ~isempty(OPTIONS.Cortex), % subject has cortical vertices as source supports + % First make room in memory + HeadModel.SearchGain = []; + clear SearchGridLoc SearchGain G + + if OPTIONS.Verbose, bst_message_window({... + 'Computing the Image Gain Matrices (this may take a while). . .'}) + end + + % Find the cortical grid where to compute the forward model in the tessellation file + try + ImageGrid = load(fullfile(User.SUBJECTS,OPTIONS.Cortex.FileName),'Comment','Vertices'); + catch + ImageGrid = load(OPTIONS.Cortex.FileName,'Comment','Vertices'); + end + + if ~isfield(OPTIONS.Cortex,'iGrid') + OPTIONS.Cortex.iGrid = 1; + end + + if OPTIONS.Cortex.iGrid > length(ImageGrid.Comment) % Corresponding cortical surface not found + errordlg(sprintf('Cortical Tessellation file "%s" does not contain %d surfaces',... + OPTIONS.Cortex.FileName,OPTIONS.Cortex.iGrid)) + return + end + + GridLoc = ImageGrid.Vertices{OPTIONS.Cortex.iGrid}; % keep only the desired cell + ImageGrid = rmfield(ImageGrid,'Vertices'); + +elseif ~isempty(OPTIONS.SourceLoc) % Specific source locations are provided + if size(OPTIONS.SourceLoc,1) ~= 3 + OPTIONS.SourceLoc = OPTIONS.SourceLoc'; + end + GridLoc = OPTIONS.SourceLoc; + +else + rmfield(OPTIONS,'rooot'); + if nargout == 1 + varargout{1} = OPTIONS; + else + varargout{1} = HeadModel; + varargout{2} = OPTIONS; + end + return % No ImageGrid requested + +end + +if ~isempty(OPTIONS.Cortex) + GridName{OPTIONS.Cortex.iGrid} = ImageGrid.Comment{OPTIONS.Cortex.iGrid}; + OPTIONS.Cortex.Name = ImageGrid.Comment{OPTIONS.Cortex.iGrid}; +end + +%for i = 1 % CHEAT - Dipoles only here +for Order = OPTIONS.SourceModel % Compute gain matrices for each requested source models (-1 0 1) + + i = 1; % Index to cell in headmodel cell arrays (MMII convention) + + switch(Order) + case -1 + SourceOrderString = 'CD'; % Current Dipole + Dims = DIMS(1);% number of columns per source + case 0 + errordlg(sprintf('Unauthorized Source Model Order %d.',iSrcModel),'Wrong HeadModel parameter assignment') + return + %SourceOrderString = 'MD'; % Magnetic Dipole - OBSOLETE + case 1 + SourceOrderString = 'CME'; % Current Multipole + Dims = DIMS(2);% number of columns per source + otherwise + errordlg(sprintf('Unauthorized Source Model Order %d.',iSrcModel),'Wrong HeadModel parameter assignment') + return + end + + if OPTIONS.Verbose, + bst_message_window(... + 'wrap',... + sprintf('Computing Gain Matrix for the %s Model',SourceOrderString)) + h = waitbar(0,sprintf('Computing Gain Matrix for the %s Model',SourceOrderString)); + pos = get(h,'position'); + end + + if ~isempty(OPTIONS.Cortex) & OPTIONS.ApplyGridOrient % Use cortical grid + try + load(OPTIONS.Cortex.FileName,'Faces'); + catch + Users = get_user_directory; + load(fullfile(Users.SUBJECTS,OPTIONS.Cortex.FileName),'Faces'); + end + + Faces = Faces{OPTIONS.Cortex.iGrid}; + + ptch = patch('Vertices',GridLoc','Faces',Faces,'Visible','off'); + set(get(ptch,'Parent'),'Visible','off') + clear Faces + GridOrient{i} = get(ptch,'VertexNormals')'; % == {1} as of MMII conventions. Most data in HeadModel files are single-cell cell arrays. + % Cell array structure kept for backward compatibility with BsT2000. + delete(ptch); + + end + + if OPTIONS.ApplyGridOrient % Take cortex normals into account + if isempty(OPTIONS.GridOrient) & isempty(OPTIONS.SourceOrient) % Consider the cortical patch's normals + if isempty(OPTIONS.Cortex) % Specific source locations in .SourceLoc but nohing in. SourceOrient + OPTIONS.ApplyGridOrient = 0; % No source orientation specified: Force computation of full gain matrix + else + [nrm,GridOrient{i}] = colnorm(GridOrient{i}); + % Now because some orientations may be ill-set to [0 0 0] with the get(*,'VertexNormals' command) + % set these orientation to arbitrary [1 1 1]: + izero = find(nrm == 0);clear nrm + if ~isempty(izero) + GridOrient{i}(:,izero) = repmat([1 1 1]'/norm([1 1 1]),1,length(izero)); + end + clear izero + + end + + elseif ~isempty(OPTIONS.GridOrient) % Apply user-defined cortical source orientations + + if size(OPTIONS.GridOrient,2) == size(GridLoc,2) % Check size integrity + GridOrient{i} = OPTIONS.GridOrient; + [nrm,GridOrient{i}] = colnorm(GridOrient{i}); + clear nrm + else + errordlg(sprintf('The source orientations you have provided are for %0.f sources. Considered cortical surface has %0.f sources. Computation aborted',... + size(OPTIONS.GridOrient,2),size(GridOrient{i},2))); + return + end + + elseif ~isempty(OPTIONS.SourceOrient) % Apply user-defined specific source orientations + + if size(OPTIONS.SourceOrient,2) == size(GridLoc,2) % Check size integrity + GridOrient{i} = OPTIONS.SourceOrient; + [nrm,GridOrient{i}] = colnorm(GridOrient{i}); + clear nrm + else + errordlg(sprintf('The source orientations you have provided are for %0.f sources. Computation aborted',... + size(OPTIONS.SourceOrient,2))); + return + end + + end + end + + nv = size(GridLoc,2); % number of grid points + + if ~isempty(OPTIONS.ImageGridFile) % Save cortical gain matrix in a binary file + + [PATH,NAME,EXT,VER] = fileparts(OPTIONS.HeadModelFile); + + if strcmp(lower(OPTIONS.ImageGridFile),'default') + if exist('GridName','var') % Cortical support was specified + destname = [NAME,'_Gain_',strrep(ImageGrid.Comment{OPTIONS.Cortex.iGrid},' ',''),'_',SourceOrderString,'.bin']; % New naming (March, 19 - 2002) + k = 1; + try + while exist(destname,'file') % Don't write over existing .bin gain matrix file + destname = [NAME,'_Gain_',strrep(ImageGrid.Comment{OPTIONS.Cortex.iGrid},' ',''),'_',SourceOrderString,'_',int2str(k),'.bin']; % New naming (March, 19 - 2002) + k = k+1; + end + catch + while exist(destname,'file') % Don't write over existing .bin gain matrix file + destname = [NAME,'_Gain_',strrep(ImageGrid.Comment{OPTIONS.Cortex.iGrid},' ',''),'_',SourceOrderString,'_',int2str(k),'.bin']; % New naming (March, 19 - 2002) + k = k+1; + end + end + + clear k + + else % Specific location was provided in .SourceLoc + destname = [NAME,'_Gain_SpecLoc_',SourceOrderString,'.bin']; % Specific location was provided in .SourceLoc + k = 1; + while exist(destname,'file') % Don't write over existing .bin gain matrix file + destname = [NAME,'_Gain_SpecLoc_',SourceOrderString,'_',int2str(k),'.bin']; + k = k+1; + end + clear k + end + OPTIONS.ImageGridFile = destname; + else + [PATH,destname,ext,ver] = fileparts(OPTIONS.ImageGridFile); + destname = [destname, ext]; + end + + % Check whether this name exists - if yes, don't overwrite + try + cd(fullfile(User.STUDIES,PATH)) + catch + cd(PATH) + end + + hdml = 1; + while exist(destname,'file') + if hdml == 1 + destname = strrep(destname,'.bin',['_',int2str(hdml),'.bin']); + else + destname = strrep(destname,[int2str(hdml-1),'.bin'],[int2str(hdml),'.bin']); + end + + hdml = hdml+1; + end + clear hdml + + fdest = fopen(destname,'w','ieee-be'); + if fdest < 0 + errordlg('Error creating the file for the cortical image forward model; Please check for disk space availability') + return + end + frewind(fdest); + + fwrite(fdest,length([OPTIONS.Channel]),'uint32'); + + % % BEM and non-interpolative, store gain matrix already computed + % if isfield(OPTIONS,'BEM') % BEM computation + % if ~OPTIONS.BEM.Interpolative + % global GBEM_grid + % end + % end + + if fdest < 0 , errordlg('Please Check Write Permissions', ['Cannot create ',destname]), return, end + else % If no ImageGridFile was specified + %OPTIONS.ImageGridBlockSize = nv; % Force a one-time computation of all source forward fields + end + + src_ind = 0; + jj = 0; % Number of OPTIONS.ImageGridBlockSize + + + for j = 1:(OPTIONS.ImageGridBlockSize):nv, + jj = jj+1; + if 1%OPTIONS.ApplyGridOrient + ndx = [0:OPTIONS.ImageGridBlockSize-1]+j; + else + ndx = [0:3*OPTIONS.ImageGridBlockSize-1]+j; + end + + if 1%OPTIONS.ApplyGridOrient + if(ndx(end) > nv), % last OPTIONS.ImageGridOPTIONS.ImageGridBlockSizeSize too long + ndx = [ndx(1):nv]; + end + else + if(ndx(end) > 3*nv), + ndx = [ndx(1):3*nv]; + end + end + + % Compute MEG + if MEG & ~isempty(MEGndx) + Gmeg = NaN*zeros(length(MEGndx),Dims*length(ndx)); + if ~isempty(Function{MEGndx(1)}) + + if MEG & EEG + clear('gain_bem_interp2'); % Free persistent variables to avoid confusion + end + + if isfield(OPTIONS,'BEM') % BEM computation + if ~OPTIONS.BEM.Interpolative % ~interpolative : retrieve stored gain matrix + global GBEM_grid + tmpndx = [3*(ndx(1)-1)+1:min([3*nv,3*ndx(end)])];%[0:3*OPTIONS.ImageGridBlockSize-1]+j; + Gmeg = GBEM_grid(MEGndx,tmpndx); + end + else + Gmeg = feval(Function{MEGndx(1)},GridLoc(:,ndx),Channel,Param,Order,OPTIONS.Verbose); + end + + end + else + Gmeg = []; + end + + if EEG & ~isempty(EEGndx) & i==1 % % Order -1 only for now in EEG + + Geeg = NaN*zeros(length(EEGndx),Dims*length(ndx)); + if ~isempty(Function{EEGndx(1)}) + if MEG & EEG + clear('gain_bem_interp2'); % Free persistent variables to avoid confusion + end + + if isfield(OPTIONS,'BEM') % BEM computation + if ~OPTIONS.BEM.Interpolative % ~interpolative : retrieve stored gain matrix + global GBEM_grid + %Geeg = GBEM_grid(EEGndx,[j:min([3*nv,j+3*OPTIONS.ImageGridBlockSize-1])]); + tmpndx = [3*(ndx(1)-1)+1:min([3*nv,3*ndx(end)])];%[0:3*OPTIONS.ImageGridBlockSize-1]+j; + %min(tmpndx ), max(tmpndx) + Geeg = GBEM_grid(EEGndx,tmpndx); + end + else + Geeg = feval(Function{EEGndx(1)},GridLoc(:,ndx),Channel,Param,Order,OPTIONS.Verbose); + end + + end + else + Geeg = []; + end + + if OPTIONS.ApplyGridOrient + G = NaN*zeros(length(OPTIONS.Channel),length(ndx)); + else + G = NaN*zeros(length(OPTIONS.Channel),Dims*length(ndx)); + end + + if OPTIONS.Verbose, bst_message_window(... + ['Computing Cortical Gain Vectors. . . Block # ',int2str(jj),... + ' of ',int2str(length(1:OPTIONS.ImageGridBlockSize:nv))]) + + hh = waitbar(0,['Computing Cortical Gain Vectors. . . Block # ',int2str(jj),... + ' of ',int2str(length(1:OPTIONS.ImageGridBlockSize:nv))]); + set(hh,'Position',[pos(1), pos(2)+pos(4),pos(3),pos(4)]) + drawnow + end + + src = 0; + % Options on cortical source orientation + if OPTIONS.ApplyGridOrient % Apply source orientation + + for k = 1:Dims:Dims*length(ndx)-2 + src = src+1; + src_ind = src_ind+1; + if ~isempty(Gmeg) + G(MEGndx,src) = Gmeg(:,k:k+2) * GridOrient{1}(:,src_ind); + end + + if ~isempty(Geeg)&(i==1)% % Order -1 only + G(EEGndx,src) = Geeg(:,k:k+2) * GridOrient{1}(:,src_ind); + end + if OPTIONS.Verbose, + if ~rem(src,5000) + waitbar(src/length(1:Dims:Dims*length(ndx)-2),hh) + end + end + + end + + else % Do not apply cortical orientation. Keep full gain matrix at each cortical location + + if MEG + G(MEGndx,:) = Gmeg; + end + if EEG + G(EEGndx,:) = Geeg; + end + + end + + if OPTIONS.Verbose, + if ~rem(src_ind,1000) + waitbar(src_ind/nv,h) + end + + delete(hh) + end + + + if ~isempty(OPTIONS.ImageGridFile) + % 4 bytes per element, find starting point + if OPTIONS.ApplyGridOrient % Apply source orientation + offset = 4 + (ndx(1)-1)*length(Channel)*4; + else + offset = 4 + 3*(ndx(1)-1)*length(Channel)*4; + end + + % Matlab 6.5.0 bug, Technical Solution Number: 1-19NOK + % http://www.mathworks.com/support/solutions/data/1-19NOK.html?solution=1-19NOK + % must REWIND first before fseek. + % Apparently fixed in 6.5.1 + % JCM 27-May-2004 + status = fseek(fdest,0,'bof'); + status = fseek(fdest,offset,'bof'); + if(status == -1), + errordlg('Error writing Image Gain Matrix file'); return + end + + fwrite(fdest,G,'float32'); + elseif nargout>1 + if ~exist('GG', 'var') + if OPTIONS.ApplyGridOrient + GG = NaN*zeros(length(OPTIONS.Channel),nv); + else + GG = NaN*zeros(length(OPTIONS.Channel),Dims*nv); + end + end + if MEG + GG(MEGndx,ndx) = G(MEGndx,:); + end + if EEG + GG(EEGndx,ndx) = G(EEGndx,:); + end + + end + + clear Gmeg Geeg + + end + if exist('destname','var') & ~isempty(OPTIONS.Cortex) + Gain{OPTIONS.Cortex.iGrid}{i} = destname; + OPTIONS.ImageGridFile = destname; + end + + if OPTIONS.Verbose + close(h) + end + + if ~isempty(OPTIONS.ImageGridFile) + fclose(fdest); + if OPTIONS.Verbose, bst_message_window({... + sprintf('Computing Gain Matrix for the %s Model -> DONE',SourceOrderString),... + sprintf('Saved in:'),... + sprintf('%s',destname)... + }), + end + end + + + % Now save ImageGrid headmodel(s)----------------------------------------------------------------------------------- + OPTIONS.HeadModelFile = OPTIONS.HeadModelFileOld; % Use original HeadModelFile entry + if strcmp(lower(OPTIONS.HeadModelFile),'default') + if ~isfield(OPTIONS,'rooot') + OPTIONS.rooot = OPTIONS.PrefixFileName; + end + OPTIONS.HeadModelFile = [OPTIONS.rooot,'headmodel.mat']; + ifile = 0; + while exist(OPTIONS.HeadModelFile,'file') % Do not overwrite headmodel files + ifile = ifile + 1; + OPTIONS.HeadModelFile = [OPTIONS.rooot,'headmodel_',int2str(ifile),'.mat']; + end + + elseif ~isfield(OPTIONS,'rooot') & ~isempty(OPTIONS.HeadModelFile) + OPTIONS.rooot = strrep(OPTIONS.HeadModelFile,'headmodel.mat',''); + end + + SaveHeadModel.Param = HeadModel.Param; + SaveHeadModel.Function = HeadModel.Function; + + if MEG + SaveHeadModel.MEGMethod = OPTIONS.Method{DataType.MEG}; + end + if EEG + SaveHeadModel.EEGMethod = OPTIONS.Method{DataType.EEG}; + end + + if strcmpi(OPTIONS.HeadModelName,'Default') % Specify default HeadModelName + if MEG & EEG + SaveHeadModel.HeadModelName = sprintf('%s | %s', OPTIONS.Method{DataType.MEG},OPTIONS.Method{DataType.EEG}); + elseif MEG + SaveHeadModel.HeadModelName = sprintf('%s', OPTIONS.Method{DataType.MEG}); + elseif EEG + SaveHeadModel.HeadModelName = sprintf('%s', OPTIONS.Method{DataType.EEG}); + end + else + SaveHeadModel.HeadModelName = OPTIONS.HeadModelName; + end + + if ~isempty(OPTIONS.HeadModelFile), % and is not empty + [HeadModelFilePath,HeadModelFile,ext] = fileparts(OPTIONS.HeadModelFile); + end + + % Assign proper GridName + switch(Order) + case -1 + SourceOrderString = 'CD'; % Current Dipole + case 0 + SourceOrderString = 'MD'; % Magnetic Dipole + case 1 + SourceOrderString = 'CME'; % Current Multipole + end + + [SaveHeadModel.Param.Order] = deal(Order); + SaveHeadModel.SourceOrder = Order; % Alternative to previous line + SaveHeadModel.HeadModelType = 'ImageGrid'; + + + if ~isempty(OPTIONS.Cortex) + SaveHeadModel.GridName = {sprintf('%s Surface Grid : %s',SourceOrderString, OPTIONS.Cortex.Name)}; + if ~isempty(OPTIONS.ImageGridFile) + SaveHeadModel.Gain = {OPTIONS.ImageGridFile}; % Store Image Grid File name in the headmodel.mat file + end + + SaveHeadModel.GainCovar{1} = cell(1); % May compute it later within headmodel_make + SaveHeadModel.GainCovarName =''; + SaveHeadModel.GridLoc{1} = OPTIONS.Cortex.FileName; + if 1%OPTIONS.Cortex.iGrid > 1 % Meaning that cortical support is not the fisrt surface in tessellation file (default in MMII) + % Add yet another field to headmodel file to specify this information. + SaveHeadModel.iGrid = OPTIONS.Cortex.iGrid; + end + else + SaveHeadModel.GainCovar = []; + SaveHeadModel.GainCovarName = []; + SaveHeadModel.GridName = []; + SaveHeadModel.GridLoc = {OPTIONS.SourceLoc}; + SaveHeadModel.Gain = {OPTIONS.ImageGridFile}; + end + if ~OPTIONS.ApplyGridOrient + SaveHeadModel.GridOrient = []; + else + SaveHeadModel.GridOrient = {OPTIONS.SourceOrient}; + end + + + % now collect together and save + if ~isempty(OPTIONS.HeadModelFile) & exist('destname','var') + % HeadModel file name + SaveHeadModelFile = fullfile(HeadModelFilePath,[HeadModelFile,... + sprintf('SurfGrid_%s',SourceOrderString),... + ext]); + ifile = 0; + while exist(SaveHeadModelFile,'file') % Do not overwrite headmodel files + ifile = ifile + 1; + SaveHeadModelFile = fullfile(HeadModelFilePath,[HeadModelFile,... + sprintf('SurfGrid_%s',SourceOrderString),... + '_',int2str(ifile),ext]); + end + if OPTIONS.Verbose, bst_message_window({... + sprintf('Writing Cortical Image Support HeadModel file:'),... + sprintf('%s', SaveHeadModelFile)... + }) + end + + if strcmp(lower(OPTIONS.HeadModelFileOld),'default') + OPTIONS.HeadModelFile = SaveHeadModelFile; + end + + try + save_fieldnames(SaveHeadModel, SaveHeadModelFile); + catch + cd(User.STUDIES) + save_fieldnames(SaveHeadModel, SaveHeadModelFile); + end + + + if OPTIONS.Verbose, bst_message_window(... + {'-> DONE',' '}), end + end + + % Save completed ----------------------------------------------------------------------------------- + +end % Cortical gain matrix for each source model + + +%% ------------------------------------------------------------------------- +if isfield(OPTIONS,'rooot') + OPTIONS = rmfield(OPTIONS,'rooot'); +end + +if nargout == 0 + clear G SearchGain +elseif nargout == 1 + varargout{1} = OPTIONS; +else + if OPTIONS.ImageGridBlockSize < nv & ~isempty(OPTIONS.HeadModelFile) + varargout{1} = OPTIONS.HeadModelFile; + else + varargout{1} = GG; + end + + varargout{2} = OPTIONS; +end + +fclose('all'); + +if OPTIONS.Verbose, bst_message_window(... + {'The head model has been properly designed and written to disk'}) +end + +if OPTIONS.Verbose, bst_message_window({... + sprintf(... + 'Head modeling ends (%s - %dH %dmin %ds (took %3.2f seconds))',date,clockk(4:6), etime(clock,time0)),... + '__________________________________________'... + }) +end + +%------------------------------------------------------------------------------------------------------------------------------ +% +% SUB-FUNCTIONS +% +%------------------------------------------------------------------------------------------------------------------------------ + +function BEMGaingridFname = bem_GainGrid(DataType,OPTIONS,BEMChanNdx) + +% Computation of the BEM gain matrix on the 3D interpolative grid for MEG and/or EEG data +% DataType : a structure with fields MEG and EEG. DataType.MEG (res. DataType.EEG) is set to 1 if MEG (res. EEG) data is available +% OPTIONS : the OPTIONS structure, input argument from bst_headmodeler +% BEMChanNdx : a cell array of channel indices such that : BEMChanNdx{DataType.EEG} = EEGndx (res. MEG). +% +% BEMGaingridFname: a structure with fields: +% .EEG : string with the name of the file containing the gain matrix of the 3D BEM interpolative grid in EEG +% .MEG : same as .EEG respectively to MEG BEM model. + + +% Detect the requested BEM computations: MEG and/or EEG___________________________________ + +User = get_user_directory; +if isempty(User) + User.STUDIES = pwd; + User.SUBJECTS = pwd; +end + +MEG = ~isempty(BEMChanNdx(DataType.MEG)); % == 1 if MEG is requested +EEG = ~isempty(BEMChanNdx(DataType.EEG)); % == 1 if EEG is requested +if MEG + MEGndx = BEMChanNdx{DataType.MEG}; +end +if EEG + %EEGndx = BEMChanNdx{DataType.EEG}; + EEGndx = OPTIONS.EEGndx; % EEG sensors (not including EEG reference channel, if any) + EEGREFndx = good_channel(OPTIONS.Channel,[],'EEG REF'); +end + +if MEG & EEG + [Param(:).mode] = deal(3); +elseif ~MEG & EEG + [Param(:).mode] = deal(1); +elseif MEG & ~EEG + [Param(:).mode] = deal(2); +else + errordlg('Please check that the method requested for forward modeling has an authorized name'); + return +end + +% BEM parameters ________________________________________________________________________ +% Determine what basis functions to use +constant = ~isempty(strmatch('constant',lower(OPTIONS.BEM.Basis))); +if constant == 0 + [Param(:).basis_opt] = deal(1); +else + [Param(:).basis_opt] = deal(0); +end + +% Determine what Test to operate +collocation = ~isempty(strmatch('collocation',lower(OPTIONS.BEM.Test))); +if collocation == 0 + [Param(:).test_opt] = deal(1); +else + [Param(:).test_opt] = deal(0); +end + +% Insulated-skull approach +isa = OPTIONS.BEM.ISA; +if isa == 1 + [Param(:).ISA] = deal(1); +else + [Param(:).ISA] = deal(0); +end + +Param.Ntess_max = OPTIONS.BEM.NVertMax; +Param.Conductivity = deal(OPTIONS.Conductivity); + +%_________________________________________________________________________________________ + +% Load surface envelopes information______________________________________________________ + +% Find the indices of the enveloppes selected for BEM computation +if ~isfield(OPTIONS.BEM,'EnvelopeNames') + errordlg('Please specify the ordered set of head-tissue envelopes by filling the OPTIONS.BEM.EnvelopeNames field') + return +end +if isempty(OPTIONS.BEM.EnvelopeNames) + errordlg('Please specify the ordered set of head-tissue envelopes by filling the OPTIONS.BEM.EnvelopeNames field') + return +end +for k = 1:length(OPTIONS.BEM.EnvelopeNames) + + try + load(fullfile(User.SUBJECTS,OPTIONS.subjectpath,OPTIONS.BEM.EnvelopeNames{k}.TessFile),'Comment'); + catch % Maybe user is using command line call to function with absolute-referenced files OPTIONS.*.TessFile + try + OPTIONS.BEM.EnvelopeNames{k}.TessFile = [OPTIONS.BEM.EnvelopeNames{k}.TessFile,'.mat']; + load(fullfile(User.SUBJECTS,OPTIONS.subjectpath,OPTIONS.BEM.EnvelopeNames{k}.TessFile),'Comment'); + catch + cd(User.SUBJECTS) + load(OPTIONS.BEM.EnvelopeNames{k}.TessFile,'Comment'); + end + end + + Comment = strrep(Comment,' ',''); + % find surface in current tessellation file + OPTIONS.BEM.EnvelopeNames{k}.SurfId = find(strcmpi(OPTIONS.BEM.EnvelopeNames{k}.TessName,Comment)); + IDs(k) = OPTIONS.BEM.EnvelopeNames{k}.SurfId; + if isempty(OPTIONS.BEM.EnvelopeNames{k}.SurfId) + errordlg(... + sprintf('Surface %s was not found in file %s',... + OPTIONS.BEM.EnvelopeNames{k}.TessName, OPTIONS.BEM.EnvelopeNames{k}.TessFile)) + return + end + + % Load vertex locations + try + tmp = load(fullfile(User.SUBJECTS,OPTIONS.subjectpath,OPTIONS.BEM.EnvelopeNames{k}.TessFile),'Vertices'); + catch % Maybe user is using command line call to function with absolute-referenced files OPTIONS.*.TessFile + tmp = load(OPTIONS.BEM.EnvelopeNames{k}.TessFile,'Vertices'); + end + Vertices{k} = tmp.Vertices{OPTIONS.BEM.EnvelopeNames{k}.SurfId}'; + + % Load faces + try + tmp = load(fullfile(User.SUBJECTS,OPTIONS.subjectpath,OPTIONS.BEM.EnvelopeNames{k}.TessFile),'Faces'); + catch% Maybe user is using command line call to function with absolute-referenced files OPTIONS.*.TessFile + tmp = load(OPTIONS.BEM.EnvelopeNames{k}.TessFile,'Faces'); + end + + Faces(k) = tmp.Faces(OPTIONS.BEM.EnvelopeNames{k}.SurfId); +end +clear Comment tmp + +cd(User.STUDIES) + + +%_________________________________________________________________________________________ + + +% Channel Parameters______________________________________________________________________ +if MEG + R_meg1 = zeros(length(MEGndx),3); + O_meg1 = R_meg1; + R_meg2 = R_meg1; + O_meg2 = O_meg1; + flaggrad = zeros(length(MEGndx),1);% if = 1 - Flag to indicate there are some gradiometers here + + i = 0; + for k = MEGndx + i = i+1; + R_meg1(i,:) = OPTIONS.Channel(k).Loc(:,1)'; + O_meg1(i,:) = OPTIONS.Channel(k).Orient(:,1)'; + + if size(OPTIONS.Channel(k).Loc,2) == 2 + if sum(OPTIONS.Channel(k).Loc(:,1)-OPTIONS.Channel(k).Loc(:,2))~=0 % Gradiometer + R_meg2(i,:) = OPTIONS.Channel(k).Loc(:,2)'; + O_meg2(i,:) = OPTIONS.Channel(k).Orient(:,2)'; + flaggrad(k-min(MEGndx)+1) = 1; + end + end + + end + O_meg1 = (O_meg1' * inorcol(O_meg1'))'; + if exist('O_meg2','var') + O_meg2 = (O_meg2' * inorcol(O_meg2'))'; + end + + % Handle MEG reference channels if necessary + % if isfield(OPTIONS.Channel(MEGndx(1)),'irefsens') + % irefsens = OPTIONS.Channel(MEGndx(1)).irefsens; + % else + % irefsens = []; + % end + irefsens = good_channel(OPTIONS.Channel,[],'MEG REF'); + + if ~isempty(irefsens) + flaggrad_REF = zeros(length(irefsens),1);% if = 1 - Flag to indicate there are some gradiometers here + R_meg_REF = zeros(length(irefsens),3); + O_meg_REF = R_meg_REF; + R_meg_REF = R_meg_REF; + O_meg_REF = R_meg_REF; + + if ~isempty(irefsens) & ~isempty(OPTIONS.Channel(MEGndx(1)).Comment) % Reference Channels are present + if OPTIONS.Verbose, bst_message_window('Reference Channels have been detected.'), end + end + i = 0; + for k = irefsens + i = i+1; + R_meg_REF(i,:) = OPTIONS.Channel(k).Loc(:,1)'; + O_meg_REF(i,:) = OPTIONS.Channel(k).Orient(:,1)'; + + if size(OPTIONS.Channel(k).Loc,2) == 2 + if sum(OPTIONS.Channel(k).Loc(:,1)-OPTIONS.Channel(k).Loc(:,2))~=0 % Reference Gradiometer + R_meg_REF2(i,:) = OPTIONS.Channel(k).Loc(:,2)'; + O_meg_REF2(i,:) = OPTIONS.Channel(k).Orient(:,2)'; + flaggrad_REF(k-min(irefsens)+1) = 1; + end + end + + end + + else + R_meg_REF = []; + O_meg_REF = R_meg_REF; + R_meg_REF = R_meg_REF; + O_meg_REF = R_meg_REF; + end + + MEGndx_orig = MEGndx; +else + R_meg1 = zeros(length(EEGndx),3); % Use dummy channel locations + O_meg1 = R_meg1; + R_meg2 = R_meg1; + O_meg2 = O_meg1; +end + +if EEG + R_eeg = zeros(length([EEGREFndx,EEGndx]),3); + i = 0; + for k = [EEGREFndx,EEGndx] + i = i+1; + R_eeg(i,:) = OPTIONS.Channel(k).Loc(:,1)'; + end + if ~MEG + flaggrad = []; + irefsens = []; + end + +else + R_eeg = NaN * zeros(size(R_meg1)); % Dummy coordinates +end + +%_________________________________________________________________________________________ + + +%Compute Transfer Matrices__________________________________________________________________ + +BrainStorm.iscalp = IDs(end); % Index of the outermost surface (scalp, supposedly) + +eeg_answ = ''; +meg_answ = ''; + +% Check whether some transfer-matrix files already exist for current study + +fn_eeg = sprintf('%s_eegxfer_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); +fn_meg = sprintf('%s_megxfer_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); +if MEG + test = exist(fn_meg,'file'); +elseif EEG + test = exist(fn_eeg,'file'); +else MEG& EEG + test = exist(fn_eeg,'file') & exist(fn_meg,'file'); +end + +if (OPTIONS.BEM.ForceXferComputation | ~test) | OPTIONS.BEM.Interpolative + + % Force (re)computation of transfer matrices, even if files exist in current study folder + + % if OPTIONS.Verbose, bst_message_window('Computing the BEM Transfer Matrix (this may take a while)....'), end + + global nfv + nfv = bem_xfer(R_eeg,R_meg1,O_meg1,Vertices,Faces,Param(1).Conductivity,Param(1).mode, ... + Param(1).basis_opt,Param(1).test_opt,Param(1).ISA,fn_eeg,fn_meg,Param.Ntess_max,OPTIONS.Verbose,OPTIONS.BEM.checksurf); + + if ~isempty(find(flaggrad)) + if OPTIONS.Verbose, bst_message_window({'Gradiometers detected',... + 'Computing corresponding Gain Matrix. . .'}), end + + %fn_meg_2 = fullfile(pwd,[OPTIONS.rooot,'_megxfer_2.mat']); + fn_meg_2 = sprintf('%s_megxfer2_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + bem_xfer(R_eeg,R_meg2,O_meg2,Vertices,Faces,Param(1).Conductivity,Param(1).mode, ... + Param(1).basis_opt,Param(1).test_opt,Param(1).ISA,fn_eeg,fn_meg_2,Param.Ntess_max,0,OPTIONS.BEM.checksurf); % Verbose = 0 + if OPTIONS.Verbose, bst_message_window('Gradiometer Channel Gain Matrix is Completed.'), end + end + + if ~isempty(irefsens) % Do the same for reference channels + %fn_meg_REF = fullfile(pwd,[OPTIONS.rooot,'_megxfer_REF.mat']); + fn_meg_REF = sprintf('%s_megREFxfer_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + bem_xfer(R_eeg,R_meg_REF,O_meg_REF,Vertices,Faces,Param(1).Conductivity,Param(1).mode, ... + Param(1).basis_opt,Param(1).test_opt,Param(1).ISA,fn_eeg,fn_meg_REF,Param.Ntess_max,0,OPTIONS.BEM.checksurf);% Verbose = 0 + + if ~isempty(find(flaggrad_REF)) + + if OPTIONS.Verbose, bst_message_window({'MEG Reference Channels detected',... + 'Computing corresponding Gain Matrix. . .'}), end + + %fn_meg_REF2 = fullfile(pwd,[OPTIONS.rooot,'_megxfer_REF2.mat']); + fn_meg_REF2 = sprintf('%s_megREFxfer2_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + + bem_xfer(R_eeg,R_meg_REF2,O_meg_REF2,Vertices,Faces,Param(1).Conductivity,Param(1).mode, ... + Param(1).basis_opt,Param(1).test_opt,Param(1).ISA,fn_eeg,fn_meg_REF2,Param.Ntess_max,0,OPTIONS.BEM.checksurf);% Verbose = 0 + if OPTIONS.Verbose, bst_message_window('MEG Reference Channel Gain Matrix is Completed.'), end + end + end +end + +% Computation of TRANSFER MATRIX Completed ___________________________________________________ + + +%%%% THIS PART SPECIFIES PARAMETERS USED TO GENERATE THE 3-D GRID %%%%%%%%%% + + +if OPTIONS.BEM.Interpolative%1%~exist(BEMGridFileName,'file') + + if OPTIONS.Verbose, bst_message_window('Computing BEM Interpolative Grid. . .'), end + + BEMGridFileName = [OPTIONS.rooot,'grid.mat']; + + % update tessellated envelope with surfaces possibly modified by + % BEM_XFER (downsampling, alignment, embedding etc.) + Vertices = {nfv(:).vertices}; + Faces = {nfv(:).faces}; + gridmaker(Vertices,Faces,BEMGridFileName,OPTIONS.Verbose); + + if OPTIONS.Verbose, + bst_message_window('Computing BEM Interpolative Grid -> DONE'), + + % Visualization of surfaces + grid points + for k = 1:length(Vertices) + [hf,hs(k),hl] = view_surface('Head envelopes & a subset of BEM interpolative grid points',Faces{k},Vertices{k}); + view(90,0) + delete(hl) + end + camlight + rotate3d on + + set(hs(1),'FaceAlpha',.3,'edgealpha',.3,'edgecolor','none','facecolor','r') + set(hs(2),'FaceAlpha',.2,'edgealpha',.2,'edgecolor','none','facecolor','g') + set(hs(3),'FaceAlpha',.1,'edgealpha',.1,'edgecolor','none','facecolor','b') + + hold on + + load(BEMGridFileName) + hgrid = scatter3(Rq_bemgrid(1:10:end,1),Rq_bemgrid(1:10:end,2),Rq_bemgrid(1:10:end,3),'.','filled'); + + end + +else + + global GBEM_grid + + % Grid points are the locations of the distributed sources + if isempty(OPTIONS.Cortex) % CBB (SB, 07-May-2004)| Should work also for volumic grid + errordlg('Please select a cortical grid for computation of BEM vector fields') + return + end + + try + load(OPTIONS.Cortex.FileName); % Load tessellation supporting the source locations and orientations + catch + Users = get_user_directory; + load(fullfile(Users.SUBJECTS,OPTIONS.Cortex.FileName)); % Load tessellation supporting the source locations and orientations + end + + BEMGridFileName.Loc = Vertices{OPTIONS.Cortex.iGrid}; clear Vertices + + if OPTIONS.ApplyGridOrient % Take cortex normals into account + ptch = patch('Vertices',BEMGridFileName.Loc','Faces',Faces{OPTIONS.Cortex.iGrid},'Visible','off'); + set(get(ptch,'Parent'),'Visible','off') + clear Faces + BEMGridFileName.Orient = get(ptch,'VertexNormals')'; + delete(ptch); + [nrm,BEMGridFileName.Orient] = colnorm(BEMGridFileName.Orient); + % Now because some orientations may be ill-set to [0 0 0] with the get(*,'VertexNormals' command) + % set these orientation to arbitrary [1 1 1]: + izero = find(nrm == 0);clear nrm + if ~isempty(izero) + BEMGridFileName.Orient(:,izero) = repmat([1 1 1]'/norm([1 1 1]),1,length(izero)); + end + clear izero + else + BEMGridFileName.Orient = []; + end + + %if OPTIONS.Verbose, bst_message_window(sprintf('Loading BEM interpolative grid points from %s', BEMGridFileName)), end + +end + + + +% This part computes the gain matrices defined on precomputed grid------------------------------------------------------------ + +% Assign file names where to store the gain matrices +if MEG & ~EEG + bem_xfer_mfname = {fn_meg}; + %BEMGaingridFname = [OPTIONS.rooot,'_meggain_grid.mat']; + BEMGaingridFname = sprintf('%s_MEGGainGrid_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + test = exist(BEMGaingridFname,'file'); +elseif EEG & ~ MEG + bem_xfer_mfname = {fn_eeg}; + %BEMGaingridFname = [OPTIONS.rooot,'_eeggain_grid.mat']; + BEMGaingridFname = sprintf('%s_EEGGainGrid_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + test = exist(BEMGaingridFname,'file'); +elseif EEG & MEG + bem_xfer_mfname = {fn_meg,fn_eeg}; + % BEMGaingridFname.MEG = [OPTIONS.rooot,'_meggain_grid.mat']; + % BEMGaingridFname.EEG = [OPTIONS.rooot,'_eeggain_grid.mat']; + BEMGaingridFname.MEG = sprintf('%s_MEGGainGrid_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + BEMGaingridFname.EEG = sprintf('%s_EEGGainGrid_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + test = exist(BEMGaingridFname.MEG,'file') & exist(BEMGaingridFname.EEG,'file'); +end + +if 1%OPTIONS.BEM.ForceXferComputation | ~test% Recompute gain matrices when transfer matrices have been recomputed just before + + if OPTIONS.Verbose + if OPTIONS.BEM.Interpolative + bst_message_window('Computing the BEM gain matrix for interpolative grid. . .'), + else + bst_message_window('Computing the BEM gain matrix for source grid. . .'), + end + end + + t0 = clock; + + if OPTIONS.Verbose, + if MEG & EEG + bst_message_window('for MEG and EEG channels. . .') + elseif EEG + bst_message_window('for EEG channels. . .') + elseif MEG + bst_message_window('for MEG channels. . .') + end + end + + + if length(bem_xfer_mfname) == 1 % xor(MEG,EEG) + bem_gain(BEMGridFileName,bem_xfer_mfname{1},Param(1).ISA,BEMGaingridFname, OPTIONS.Verbose); + else + % MEG gaingrid matrix + bem_gain(BEMGridFileName,bem_xfer_mfname{1},Param(1).ISA,BEMGaingridFname.MEG, OPTIONS.Verbose); + % EEG gaingrid matrix + bem_gain(BEMGridFileName,bem_xfer_mfname{2},Param(1).ISA,BEMGaingridFname.EEG, OPTIONS.Verbose); + end + + if OPTIONS.Verbose, bst_message_window('-> DONE'), end + + if ~isempty(find(flaggrad)) % Compute forward model on the second set of magnetometers from the gradiometers array + + bem_xfer_mfname = sprintf('%s_megxfer2_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + bem_gaingrid_mfname_2 = sprintf('%s_MEGGainGrid2_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + + if OPTIONS.Verbose, bst_message_window('MEG - completing gradiometers. . .'), end + + bem_gain(BEMGridFileName,bem_xfer_mfname,Param(1).ISA,bem_gaingrid_mfname_2,OPTIONS.Verbose); + + if OPTIONS.Verbose, bst_message_window('-> DONE'), end + + if MEG & EEG + G1 = load(BEMGaingridFname.MEG); + else + G1 = load(BEMGaingridFname); + end + G2 = load(bem_gaingrid_mfname_2); + % Apply respective weights within the gradiodmeters + meg_chans = [OPTIONS.Channel(MEGndx(find(flaggrad))).Weight]; + w1 = meg_chans(1:2:end); + w2 = meg_chans(2:2:end); + + G1.GBEM_grid(find(flaggrad),:) = w1'*ones(1,size(G1.GBEM_grid,2)).*G1.GBEM_grid(find(flaggrad),:)... + + w2' * ones(1,size(G1.GBEM_grid,2)).*G2.GBEM_grid(find(flaggrad),:); + clear G2 + + % is there special reference channel considerations? + if ~isempty(irefsens) + + % Forward model on all reference sensors + bem_xfer_mfname_REF = sprintf('%s_megREFxfer_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + bem_gaingrid_mfname_REF = sprintf('%s_MEGGainGrid_REF_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + + if OPTIONS.Verbose, bst_message_window('MEG reference channels. . .'), end + bem_gain(BEMGridFileName,bem_xfer_mfname_REF,Param(1).ISA,bem_gaingrid_mfname_REF,OPTIONS.Verbose); + if OPTIONS.Verbose, bst_message_window('-> DONE'), end + + if ~isempty(find(flaggrad_REF)) % Gradiometers are present in reference channels + + bem_xfer_mfname_REF2 = sprintf('%s_megREFxfer2_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + bem_gaingrid_mfname_REF2 = sprintf('%s_MEGGainGrid2_REF_%s_%s.mat',OPTIONS.rooot, OPTIONS.BEM.Basis,OPTIONS.BEM.Test); + + if OPTIONS.Verbose, bst_message_window('MEG reference channels / completing gradiometers. . .'), end + + bem_gain(BEMGridFileName,bem_xfer_mfname_REF2,Param(1).ISA,bem_gaingrid_mfname_REF2,OPTIONS.Verbose); + + if OPTIONS.Verbose, bst_message_window('-> DONE'), end + + GR = load(bem_gaingrid_mfname_REF); + GR2 = load(bem_gaingrid_mfname_REF2); + + meg_chans = [OPTIONS.Channel(irefsens(find(flaggrad_REF))).Weight]; + w1 = meg_chans(1:2:end); + w2 = meg_chans(2:2:end); + + GR.GBEM_grid(find(flaggrad_REF),:) = w1'*ones(1,size(GR.GBEM_grid,2)).*GR.GBEM_grid(find(flaggrad_REF),:)... + + w2' * ones(1,size(GR.GBEM_grid,2)).*GR2.GBEM_grid(find(flaggrad_REF),:); + + %GR.GBEM_grid(find(flaggrad_REF),:) = GR.GBEM_grid(find(flaggrad_REF),:) - GR2.GBEM_grid(find(flaggrad_REF),:); + clear GR2; + end + + % Apply nth-order gradient correction on good channels only + %Weight by the current nth-order correction coefficients + %G1.GBEM_grid = G1.GBEM_grid - Channel(MEGndx(1)).Gcoef(find(ChannelFlag(irefsens)>0),:)*GR.GBEM_grid; + + G1.GBEM_grid = G1.GBEM_grid - OPTIONS.Channel(MEGndx(1)).Comment*GR.GBEM_grid; + + end + + GBEM_grid = 1e-7*G1.GBEM_grid; + + if MEG & EEG + save(BEMGaingridFname.MEG,'GBEM_grid','-append'); + else + save(BEMGaingridFname,'GBEM_grid','-append'); + end + + end + + % Detect EEG reference - if none is specified in the .Comment or Type fields, + % and if none was passed through OPTIONS.EEGRef + % -> Apply average-referencing of the potentials by default. + + if EEG + % EEG Reference Channel + EEGREFndx = good_channel(OPTIONS.Channel,[],'EEG REF'); + + if MEG & EEG + load(BEMGaingridFname.EEG,'GBEM_grid') + else + load(BEMGaingridFname,'GBEM_grid') + end + + + if isempty(EEGREFndx)% AVERAGE REF + GBEM_grid = GBEM_grid - repmat(mean(GBEM_grid),size(GBEM_grid,1),1); + else + % GBEM_grid = GBEM_grid(setdiff(EEGndx,EEGREFndx)-EEGndx(1)+1,:) - repmat(GBEM_grid(EEGREFndx-EEGndx(1)+1,:),size(GBEM_grid(setdiff(EEGndx,EEGREFndx)-EEGndx(1)+1,:),1),1); + GBEM_grid = GBEM_grid(2:end,:) - repmat(GBEM_grid(1,:),length(EEGndx),1); % SB : EEG REF is stored as first sensor in GBEM_grid; see line 2226 + end + + if MEG + save(BEMGaingridFname.EEG,'GBEM_grid','-append') + else + save(BEMGaingridFname,'GBEM_grid','-append') + end + + end + + + if MEG & EEG + meg = load(BEMGaingridFname.MEG,'GBEM_grid'); + eeg = load(BEMGaingridFname.EEG,'GBEM_grid'); + GBEM_grid = zeros(length(OPTIONS.Channel),size(GBEM_grid,2)); + GBEM_grid(MEGndx,:)= meg.GBEM_grid; clear meg + GBEM_grid(EEGndx,:)= eeg.GBEM_grid; clear eeg + + elseif MEG + + meg = load(BEMGaingridFname,'GBEM_grid'); + GBEM_grid = zeros(length(OPTIONS.Channel),size(GBEM_grid,2)); + GBEM_grid(MEGndx,:)= meg.GBEM_grid; clear meg + + elseif EEG + + eeg = load(BEMGaingridFname,'GBEM_grid'); + GBEM_grid = zeros(length(OPTIONS.Channel),size(GBEM_grid,2)); + EEGndx = OPTIONS.EEGndx; + GBEM_grid(EEGndx,:)= eeg.GBEM_grid; clear eeg + + %clear GBEM_grid + % % Now save the combined MEG/EEG gaingrid matrix in a single file + % MEGEEG_BEMGaingridFname = strrep(BEMGaingridFname.EEG,'eeg','meg_eeg'); + % Gmeg = load(BEMGaingridFname.MEG,'GBEM_grid'); + % GBEM_grid = NaN * zeros(length(OPTIONS.Channel),size(Gmeg.GBEM_grid,2)); + % GBEM_grid(MEGndx,:) = Gmeg.GBEM_grid; clear Gmeg + % eeg = load(BEMGaingridFname.EEG); + % + % save_fieldnames(eeg,MEGEEG_BEMGaingridFname); + % + % GBEM_grid(setdiff(EEGndx,EEGREFndx),:) = eeg.GBEM_grid; clear eeg + % + % save(MEGEEG_BEMGaingridFname,'GBEM_grid','-append') + % + % BEMGaingridFname = MEGEEG_BEMGaingridFname; + else + save(BEMGaingridFname,'GBEM_grid','-append') + end + + telap_meg_interp = etime(clock,t0); + + if OPTIONS.Verbose, bst_message_window(sprintf('Completed in %3.1f seconds', telap_meg_interp),... + 'Computing the Gain Matrix for the Interpolative Grid Points -> DONE'), end +else + % if MEG & EEG + % if OPTIONS.Verbose, bst_message_window(sprintf('Loading 3D grid gain matrix from %s', BEMGaingridFname.EEG)),end + % else + % if OPTIONS.Verbose, bst_message_window(sprintf('Loading 3D grid gain matrix from %s', BEMGaingridFname)),end + % end +end + + + +function g = gterm_constant(r,rq) +%gterm_constant +% function g = gterm_constant(r,rq) + +% -------- 20-Nov-2002 14:06:02 ------------------------------ +% ---- Automatically Generated Comments Block using auto_comments ----------- +% +% Alphabetical list of external functions (non-Matlab): +% toolbox\rownorm.m +% ---------- 20-Nov-2002 14:06:02 ------------------------------ + + +if size(rq,1) == 1 % Just one dipole + r_rq= [r(:,1)-rq(1),r(:,2)-rq(2),r(:,3)-rq(3)]; + n = rownorm(r_rq).^3; + g = r_rq./[n,n,n]; +else + g = zeros(size(r,1),3*size(rq,1)); + isrc = 1; + for k = 1:size(rq,1) + r_rq= [r(:,1)-rq(k,1),r(:,2)-rq(k,2),r(:,3)-rq(k,3)]; + n = rownorm(r_rq).^3; + g(:,3*(isrc-1)+1: 3*isrc) = r_rq./[n,n,n]; + isrc = isrc + 1; + end + +end diff --git a/compute_inverse.m b/compute_inverse.m new file mode 100644 index 0000000..b293ef1 --- /dev/null +++ b/compute_inverse.m @@ -0,0 +1,862 @@ +function Results = minnorm(OPTIONS); +%MINNORM - Mininum norm solution as called from command line or BST_SOURCEIMAGING.M +% function Results = minnorm(OPTIONS); +% ------------------------------------------------------------------------------------------------- +% NOTICE: +% This function is not optimized for stand-alone command calls. +% Please use the generic BST_SOURCEIMAGING function to access Min.Norm. source map computations. +% ------------------------------------------------------------------------------------------------- +% +% +% INPUTS +% OPTIONS - a structure of parameters +% OUTPUTS +% Results - a regular BrainStorm Results structure (see documentation for details) +% +% Details of the OPTIONS structure +% +% Data Information: +% .DataFile : A string actual data file requested for localization. If isempty, look for data array(s) in .Data +% .Data : Array of nChannel x nTime array(s) of data. +% .SegmentIndices: Vector of all time samples (in sample values) +% of the latencies specifying the time window for analysis. +% .Trial : A scalar specifying the trial from which to extract the data segment +% (not empty only when data in .DataFile is stored in native format) +% .ChannelFlag: a vector of flags (1 for good, -1 for bad) of channels in the data file to process +% .DataTypes : A scalar or a vector of codes to specidy which is the type of data to use: +% 1 is MEG, 2 is EEG, 3 is Fusion +% (Default is all data type available) +% .FusionType : Code for the type of fusion to apply between MEG and EEG data +% 1 is linear, 2 is non-linear +% (Defaut is 1) +% .Data : Specify some data to be passed independently of any data file +% .F : Cell array of nChannel x nTime array(s) of data. +% If not empty: uses this array as input for inverse process. +% .ChannelFile : Channel file corresponding to data in .F +% .Time : Vector specifying the time instants of data samples in .Data.F +% (Default for .Data is empty) +% +% Source Support Information: +% .GridLoc : a string or a 3xN matrix +% - if a string : specifies the name of the BrainStorm tessellation file where cortical support is stored +% - if a matrix : contains the coordinates of the cortical locations where to compute the cortical current density +% .iGrid : when .GridLoc is a file name, specify which imaging grid to use (Default is 1). +% +% Forward Field Information : +% .HeadModelFile: Cell array of strings for filename of the BrainStorm headmodel file(s) to use for imaging. If is empty, look for.GainFile field. +% There are only 2 options at this point: +% - .HeadModelFile is of length 1, a single headmodel file is used for all data sets passed to the bst_sourceimaging. +% - .HeadModelFile is of length the number of data sets passed to bst_sourceimaging (i.e. the length of .DataFile). +% .GainFile : Cell array of filenames of image gain matrix (.bin) for the selected cortical support. If is empty, look for .Gain field. +% Remarks about the length of .HeadModelFile hold for .GainFile too. +% .Gain : Cell array containing the gain matrix of the cortical support (either a single cell or a cell array the length the number of data sets passed to function) +% Remarks about the length of .HeadModelFile hold for .GainFile too. +% (Default is empty). +% +% Processing Parameters : +% .Method : A string that specifies the imaging method +% 'Minimum-Norm Imaging': MN estimate of current density using MN priors on source amplitudes (Default) +% 'Recursive Min. Norm.': Recursive MN estimate based on adaptation of FOCUSS (NOT AVAILABLE) +% 'SPTF' : Scanning technique constrained on cortical surface (see Denis Schwartz) (UNDER DEVELOPMENT) +% 'ST-MAP' : Non-linear imaging technique based on sparse-focal image models (NOT AVAILABLE) +% 'RAP-MUSIC' : link to Mosher's GUI (UNDER DEVELOPMENT) +% (Default is 'Minimum-Norm Imaging') +% .Tikhonov : Hyperparameter used in Tykhonov regularization +% (Default is 10) +% .FFNormalization : Apply forward field normalization of the gain matrix +% (Default is 1) +% .Rank : Specify a rank for signal subspace following SVD of the spatio-temporal data matrix +% (Default is full rank) +% .ComputeKernel : If 1, compute MN kernel to be applied subsequently to data instead of full ImageGridAmp array +% (Default is 0: compute full ImageGridAmp array) +% +% Output Information: +% .ResultFile : optional string for filename where to write results +% if 'default', filename as used in GUI environment is used +% (Default is '' (no Result file created)) +% .Verbose : Turn ON/OFF verbose mode +% (Default is 1 (ON)) +% .GUIHandles : A vector of GUI handles to the SOURCEIMAGING GUI +% when operating in graphic mode: passed automatically to bst_sourceimaging by the source imaging switchyard +% in command line mode: leave this field empty (default). +% .NNormalization : Apply noise normalization +% (Default is 0) + +% ---------------------- 27-Jun-2005 10:45:06 ----------------------- +% ------ Automatically Generated Comments Block Using AUTO_COMMENTS_PRE7 ------- +% +% CATEGORY: Inverse Modeling +% +% Alphabetical list of external functions (non-Matlab): +% toolbox\bst_message_window.m +% toolbox\colnorm.m +% toolbox\good_channel.m +% toolbox\inorcol.m +% toolbox\meg4read.m +% toolbox\norcol.m +% toolbox\read_gain.m +% toolbox\regcheck.m +% toolbox\regsubspace.m +% +% Subfunctions in this file, in order of occurrence in file: +% varargout = gainmat_covar(varargin) +% +% At Check-in: $Author: Mosher $ $Revision: 38 $ $Date: 6/27/05 9:00a $ +% +% This software is part of BrainStorm Toolbox Version 27-June-2005 +% +% Principal Investigators and Developers: +% ** Richard M. Leahy, PhD, Signal & Image Processing Institute, +% University of Southern California, Los Angeles, CA +% ** John C. Mosher, PhD, Biophysics Group, +% Los Alamos National Laboratory, Los Alamos, NM +% ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory, +% CNRS, Hopital de la Salpetriere, Paris, France +% +% See BrainStorm website at http://neuroimage.usc.edu for further information. +% +% Copyright (c) 2005 BrainStorm by the University of Southern California +% This software distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html . +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% ------------------------ 27-Jun-2005 10:45:06 ----------------------- + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% /---Script Author--------------------------------------\ +% | *** John C. Mosher, Ph.D. | +% | Biophysics Group | +% | | +% | *** Sylvain Baillet, Ph.D. | +% | Cognitive Neuroscience & Brain Imaging Laboratory | +% | CNRS UPR640 - LENA | +% | Hopital de la Salpetriere, Paris, France | +% | sylvain.baillet@chups.jussieu.fr | +% \------------------------------------------------------/ +% +% Date of creation: October 2002 (adapted from MINNORM_GUI.M, now obsolete and moved to ARCHIVE) +% +% Script History ----------------------------------------------------------------------------------- +% SB 23-Dec-2002 Added .ComputeKernel option +% Added .Data option +% SB 19-Oct-2003 Added .TimeSeries field to Results structure (as per BrainStorm general convention) +% EK 02-Oct-2004 Changed .Tikhonov to be defined as the percentage of the +% maximum sigular value. +% EK 04-Oct-2004 Added noise normalization for both BST and Kernel +% format +% SB 02-May-2005 Added deprecated code +% SB 13-May-2005 More efficient computation of noise normalization +% SB 16-May-2005 Warning off when trying to load Projector from data file +% SB 19-May-2005 Added DP bug fix when number of sources > 10,000 (default block +% size) +% SB 22-May-2005 Fixed bug for AAt EEG computation when length(sources) = +% block size + 1 +% SB 23-May-2005 Fixed bug: ChannelFlag are now properly read from file +%--------------------------------------------------------------------------------------------------- + +% General hard-wired parameter values:-------------------------------------------------------------- +DataType = {'MEG','EEG','Fusion'}; % String labels corresponding to OPTIONS.DataTypes flags +OPTIONS.BLOCK = 10000; % process by blocks +OPTIONS.ExpoiG = .4; % Exponential weighting for column normalization +%--------------------------------------------------------------------------------------------------- + +% Load Headmodel information ----------------------------------------------------------------------- + +% From file, if passed to function +if ~isempty(OPTIONS.HeadModelFile) + HeadModel = load(OPTIONS.HeadModelFile,'Function','Param',... + 'GridLoc','Gain'); % Load Basics + + if ~isempty(OPTIONS.GridLoc) + HeadModel.GridLoc = {OPTIONS.GridLoc}; + end + if ~isempty(OPTIONS.Gain) + HeadModel.Gain = OPTIONS.Gain; + end + + HeadModelFileWhos = whos('-file',OPTIONS.HeadModelFile); + % if OPTIONS.DataTypes == 3 + % % If Fusion, force gain column normalization + % OPTIONS.FFNormalization = 1 ; + % end + + if OPTIONS.FFNormalization == 1 % Forward-field normalization requested + if OPTIONS.DataType == 3 % Fusion: load specific items + if ~isempty(find(strcmp(cellstr(char(HeadModelFileWhos(:).name)),'GainCovar_ColNormFus'))) + tmp = load(OPTIONS.HeadModelFile,'GainCovar_ColNormFus'); + AAt = tmp.GainCovar_ColNormFus{1}; % Generic name for gain covariance entry (see below) + else + AAt = []; + end + if ~isempty(find(strcmp(cellstr(char(HeadModelFileWhos(:).name)),'Gain_RowNorm'))) + tmp = load(OPTIONS.HeadModelFile,'Gain_RowNorm'); + Gain_RowNorm = tmp.Gain_RowNorm; + else + Gain_RowNorm = cell(size(HeadModel.Gain)); + end + + else + if ~isempty(find(strcmp(cellstr(char(HeadModelFileWhos(:).name)),'GainCovar_ColNorm'))) + tmp = load(OPTIONS.HeadModelFile,'GainCovar_ColNorm'); + AAt = tmp.GainCovar_ColNorm{1}; % Generic name for gain covariance entry (see below) + else + AAt = []; + end + end + + else % FF is set to 0 + if ~isempty(find(strcmp(cellstr(char(HeadModelFileWhos(:).name)),'GainCovar'))) + tmp = load(OPTIONS.HeadModelFile,'GainCovar'); + AAt = tmp.GainCovar{1}; % Generic name for gain covariance entry (see below) + if iscell(AAt) + AAt = AAt{1}; + end + else + AAt = []; + end + end + + clear tmp + + % Gain matrix full filename + gainfile = fullfile(fileparts(OPTIONS.HeadModelFile),HeadModel.Gain{1}); + +end + +% Load Data Information ----------------------------------------------------------------------- + +if(~isempty(findstr('_results',deblank(lower(OPTIONS.DataFile))))), + % CHEAT + % The DataName has the string '_results' in it + % We are trying to treat independent topographies as min norm data. Eventually this + % capability will be moved to a new routine. + % name has the string '_results' in it + Results = load(OPTIONS.DataFile); + % now synthesize a Data structure from this + [ignorm,Anrm] = colnorm(Results.IndepTopo); + + Data = struct('F',Anrm,'ChannelFlag',Results.ChannelFlag,... + 'Time',[1:size(Results.IndepTopo,2)],... % time is now simply an indexer + 'NoiseCov',Results.NoiseCov,'SourceCov',Results.SourceCov,'Projector',Results.Projector,... + 'Comment',sprintf('Synthesized Data Set from Results: %s',Results.Comment)); +else + if isempty(OPTIONS.Data) + % assume it is a standard data file + DataArray = 0; % Correponsing flag + warning off + Data = load(OPTIONS.DataFile,'F','ChannelFlag','Time','Projector','Comment'); + warning on + else + DataArray = 1; + Data = OPTIONS.Data; + Data.Projector = []; + Data.Comment = ''; + Data.ChannelFlag = ones(size(Data.F,1),1); + end + +end + +% Data & Channel information ------------------------------------------------------------------ +if isfield(OPTIONS,'ChannelFile') + Channel = load(OPTIONS.ChannelFile); + OPTIONS.Channel = Channel.Channel; clear Channel +end + +% now alter the data according to the bad channels +OPTIONS.GoodChannel = good_channel(OPTIONS.Channel,Data.ChannelFlag,DataType{OPTIONS.DataType}); %good channels for selected modality +OPTIONS.EEGChannel = good_channel(OPTIONS.Channel,[],'EEG'); +OPTIONS.MEGChannel = good_channel(OPTIONS.Channel,[],'MEG'); + +if ischar(Data.F) % Data is in native file format + VERBOSE = 1; + Data.F = meg4read(Data.F,OPTIONS.Trial,OPTIONS.SegmentIndices,OPTIONS.Verbose); + Data.FBaseline = meg4read(Data.F,OPTIONS.Trial,OPTIONS.NoiseSegmentIndices,OPTIONS.Verbose); +else + % Trim the data to the requested segments + if OPTIONS.NNormalization + Data.FBaseline = Data.F(:,OPTIONS.NoiseSegmentIndices); + end + Data.F = Data.F(:,OPTIONS.SegmentIndices); + + +end + + +try + Data.F = Data.F(OPTIONS.GoodChannel,:); % good channels only + if OPTIONS.NNormalization + Data.FBaseline = Data.FBaseline(OPTIONS.GoodChannel,:); % good channels for noise segment too + end + +catch + errordlg(sprintf('Data array has %d rows while there are %d %s channels. Possible problem is wrong type assignement of reference vs. measurement channels in channel file %s',... + size(Data.F,1),length(OPTIONS.GoodChannel), DataType{OPTIONS.DataType}, OPTIONS.ChannelFile ),'Inconsistent channel and data array sizes') + return +end + + +Time = Data.Time(OPTIONS.SegmentIndices); + + +% Is there any projector for the data ? +if ~isfield(Data,'Projector') + Data.Projector = []; +end +if(~isempty(Data.Projector)), + Data.Projector = Data.Projector(OPTIONS.GoodChannel,:); +end + +% Get HeadModel parmaters for GoodChannels +if 0 % Deprecated code (thanks to Nicolas Lefebvre) | SB - 02-May-2005 + HeadModel.Param = HeadModel.Param(OPTIONS.GoodChannel); +end + + + +% ------------------------ If not available : Create & Save Gain Matrix Covariance ------------------------------------- + +if isempty(AAt) % Need to compute the proper gain covariance matrix (depending on DataType and and Forward Fiels normalization option) + % NOTE : This is a one-time computation + % Result will be saved to HeadModelFile + if OPTIONS.Verbose + bst_message_window('Starting one-time (long) computation . . .') + if ~isempty(OPTIONS.GUIHandles) + OPTIONS.hwaitbar = waitbar(0,'Creating Column-Normalized Gain Matrix Covariance...'); + else + bst_message_window('Creating Column-Normalized Gain Matrix Covariance...'); + end + end + + % Compute gain matrix covariance + [AAt, Gain_RowNorm] = gainmat_covar(gainfile, OPTIONS); + + if OPTIONS.Verbose & ~isempty(OPTIONS.GUIHandles) + close(OPTIONS.hwaitbar); + bst_message_window('Saving the gain covar back into your head model'); + end + + % Now save back to headmodel file + + switch OPTIONS.FFNormalization + case 0 + GainCovar{1} = AAt; + save(OPTIONS.HeadModelFile,'GainCovar','-append'); + case 1 + if OPTIONS.DataType == 3 + GainCovar_ColNormFus{1} = AAt; + Gain_RowNorm = {Gain_RowNorm}; % Save it as a cell like other Gain* entries in headmodel file + save(OPTIONS.HeadModelFile,'GainCovar_ColNormFus','Gain_RowNorm','-append'); + else + GainCovar_ColNorm{1} = AAt; + save(OPTIONS.HeadModelFile,'GainCovar_ColNorm','-append'); + end + end + +end % gain covariance matrix is created and available + + +% Keep only the rows and columns of AAt corresponding to GoodChannel +AAt = AAt(OPTIONS.GoodChannel,OPTIONS.GoodChannel); +if exist('Gain_RowNorm','var') + if iscell(Gain_RowNorm) + Gain_RowNorm = Gain_RowNorm{1}; + end + if ~isempty(Gain_RowNorm) + Gain_RowNorm = Gain_RowNorm(OPTIONS.GoodChannel,OPTIONS.GoodChannel); + else + clear Gain_RowNorm + end +end + +% if OPTIONS.DataType == 3 % Fusion: Apply gain matrix row-norm weighting. +% Data.F = Gain_RowNorm*Data.F; +% end + +% Update MEG and EEG channel indices by removing bad channels. +OPTIONS.EEGChannel = intersect(OPTIONS.GoodChannel,OPTIONS.EEGChannel); +OPTIONS.MEGChannel = intersect(OPTIONS.GoodChannel,OPTIONS.MEGChannel); + +if OPTIONS.DataType == 2 & ... + length(OPTIONS.GoodChannel) < length(OPTIONS.EEGChannel) % EEG data with bad channels + + % Adjust average reference contribution from covariance matrix + if isempty(find(mean(Data.F >eps))) + % Average Reference (don't use the channel.comment field that may not have been altered following manipulations in the data viewer tool) + % Load gain matrix + G = read_gain(gainfile,[]); + if strcmp(OPTIONS.Col_norm,'y'); + G = G*inorcol(G); + end + + Gm = mean(G,1)'; + + I = ones(length(OPTIONS.GoodChannel),1); + AAt = AAt - G*Gm*I' - I*Gm'*G' + Gm'*Gm*ones(size(AAt)) ; + clear G + % Reopen the Gain file that was closed during call to read_gain + fid = fopen(... + fullfile(fileparts(OPTIONS.HeadModelFile),HeadModel.Gain{1}),... + 'r','ieee-be'); % HeadModel.Gain{1} - CHEAT Dipoles only + else + % Do nothing + end +end + +OPTIONS = regcheck(OPTIONS); % returns OPTIONS.REG set to the appropriate field + +% Did the user provide an existing control? +if(isfield(Data,'Projector')), + %Decompose it: + if(isempty(Data.Projector)), + A = []; + Ua = []; + else + A = Data.Projector; % initialize + Ua = orth(A); + end +else % user did not give a projector + A = []; + Ua = []; +end + +if isempty(OPTIONS.Rank) + OPTIONS.Rank = min(size(Data.F)); +end + +if(OPTIONS.Rank < min(size(Data.F))), % reduced rank + + % User has asked for an rank RANK subspace search. + % Form the signal subspace + + if(size(Data.F,1) >= size(Data.F,2)), % skinny matrix + [Uf,Sf,Vf] = svd(Data.F,0); % economy + else % wide matrix + [Vf,Sf,Uf] = svd(Data.F',0); + end + + % form the reduced rank data + Data.F = Uf(:,1:OPTIONS.Rank)*(Sf(1:OPTIONS.Rank,1:OPTIONS.Rank)*Vf(:,1:OPTIONS.Rank)'); + + % project away if needed + if(~isempty(Ua)), + Data.F = Data.F - Ua*(Ua'*Data.F); + end + + clear Ua Sa Va Uf Sf Vf +end + + +% -------------------------------------------------------------------------------------- + +% Begin minimum norm estimate -------------------------------------------------------------------------------------- + +% -------------------------------------------------------------------------------------- + +% recall the y = Ax, let x = A'c -> y = AA'c, solve for c, the 'coefs' of x. +% c = pinv(AA')*y, and we will regularize the inverse of AA' based on user selection +% Then form x = A'c. + +[U,S,V] = svd(AAt); +U = regsubspace(OPTIONS,U,sqrt(S)); % condition based on svd of gain matrix +reg_rank = size(U,2); % reduced rank based on regularization +S = diag(S); +switch deblank(lower(OPTIONS.REG)) + case 'tikhonov' + Lambda = sqrt(S(1))*OPTIONS.Tikhonov/100 ; % sing values already squared --ESEN Tikhonov percentage + Si = 1../(S(1:reg_rank)+Lambda^2); % filtered inverse + otherwise + % do nothing, truncation only + Si = 1../S(1:reg_rank); +end + +% the min norm coefs +coefs = V(:,1:reg_rank)*... + ((spdiags(Si,0,reg_rank,reg_rank)*U(:,1:reg_rank)') ); % * Data.F removed to allow optional computation of MN imaging kernel alone + +clear U S V + +% Contribution of MN estimate to data (Fsynth) +% let rAAt = regularized(AAt), as found by the above +% So Data.F = AAt *c, c = inv(rAAt), so Fsynth = AAt*c, let's calculate and stick into results +Fsynth = AAt * coefs * Data.F; %Estimated Data + +clear AAt + +% Calculate source amplitudes explicitly --------------------------------------------------------------- +% How many sources ? +tmp = read_gain(gainfile,OPTIONS.GoodChannel(1),[]); +nsrc = length(tmp); clear tmp % Number of sources + +if OPTIONS.ComputeKernel == 0 + + ImageGridAmp = single(zeros(nsrc,size(Data.F,2))); % one column per time slice / 07-Oct-2002 : SB - now stored as 'singles' (space saver) + ImagingKernel = []; + + if OPTIONS.Verbose + if ~isempty(OPTIONS.GUIHandles) & nsrc > OPTIONS.BLOCK + hwaitbar = waitbar(0,'Inverse transformation running. . .'); + else + bst_message_window('Inverse transformation running. . .'); + end + + bst_message_window({... + sprintf('Image support: %.0f grid points . . .',nsrc)... + }) + + end + + % Iterative block computation of source amplitudes + + for i = 1:OPTIONS.BLOCK:nsrc + + if ~isempty(OPTIONS.GUIHandles) + if nsrc > OPTIONS.BLOCK + waitbar(i/nsrc,hwaitbar); + end + end + + % Indices of next sources for which amplitude needs to be estimated + ndx = [0:(OPTIONS.BLOCK-1)]+i; + if(ndx(end) > nsrc), % last block too long + ndx = [ndx(1):nsrc]; + end + + % Load and possibly normalize forward fields (Kernel) for running block of sources + if OPTIONS.FFNormalization == 1 + clear Kernel + if OPTIONS.DataType == 1 + Chans = OPTIONS.MEGChannel; + elseif OPTIONS.DataType == 2 + Chans = OPTIONS.EEGChannel; + elseif OPTIONS.DataType == 3 + Chans = OPTIONS.GoodChannel; + end + + Kernel = read_gain(gainfile,Chans,ndx); % Chunk of gain matrix for this block of sources + if OPTIONS.DataType == 3 + Kernel = Gain_RowNorm * Kernel; + end + + OPTIONS.iG = sqrt(norcol(Kernel)'); % NORCOL computes the column norms to the SQUARE + OPTIONS.iG(OPTIONS.iG == 0) = min(OPTIONS.iG(OPTIONS.iG ~= 0)); + iKernel = spdiags((1./OPTIONS.iG).^OPTIONS.ExpoiG, 0, length(OPTIONS.iG), length(OPTIONS.iG)) ; + Kernel = (Kernel*iKernel)*iKernel; + + elseif OPTIONS.FFNormalization == 0 + + Kernel = read_gain(gainfile,OPTIONS.GoodChannel,ndx); % Chunk of gain matrix for this block of sources + + end + + % next chunk of source amplitudes + if i == 1 + if OPTIONS.NNormalization + coefsBaseline = coefs*Data.FBaseline; + end + coefs = coefs * Data.F; + + end + % ESEN - Add Noise normalization in BST Mode + if isempty(find(Kernel==NaN)) & isreal(Kernel) % Check Kernel integrity + if OPTIONS.NNormalization + % Compute source baseline stats + tmp = (Kernel'*coefsBaseline); + mean_Baseline= mean(tmp,2); + std_Baseline = std(tmp,0,2); + + % Plain source ampltiudes outside baseline + ImageGridAmp(ndx, :) = (Kernel'*coefs); + + % Proceed to Z-score normalization + iStd = spdiags(1./std_Baseline, 0, length(std_Baseline), length(std_Baseline)) ; % variance normalization + ImageGridAmp(ndx, :) = single(full(iStd * (double(ImageGridAmp(ndx, :)) - double(repmat(mean_Baseline, 1, size(ImageGridAmp, 2)))))); + + + clear tmp mean_Baseline std_Baseline + else + ImageGridAmp(ndx,:) = single(Kernel'*coefs); % 07-Oct-2002 SB : now stores under 'single' format (space saver) + end + else + ImageGridAmp(ndx,:) = NaN; + if OPTIONS.Verbose + bst_message_window('wrap',{... + 'XXXX Imaging Kernel is deficient, filling source amplitudes with NaNs.'}) + end + end + + clear Kernel + + end + + if nsrc > OPTIONS.BLOCK & ~isempty(OPTIONS.GUIHandles) + close(hwaitbar); + end + +else % Compute imaging Kernel only + + ImageGridAmp = []; + + if OPTIONS.Verbose + bst_message_window({... + 'Computing Minimum-Norm Imaging Kernel. . .',... + sprintf('Image support: %.0f grid points . . .',nsrc)... + }) + end + + % Load and possibly normalize forward fields (Kernel) + if OPTIONS.FFNormalization == 1 + clear Kernel + if OPTIONS.DataType == 1 + Chans = OPTIONS.MEGChannel; + elseif OPTIONS.DataType == 2 + Chans = OPTIONS.EEGChannel; + elseif OPTIONS.DataType == 3 + Chans = OPTIONS.GoodChannel; + end + + Kernel = read_gain(gainfile,Chans,1:nsrc); % Chunk of gain matrix for this block of sources + + if OPTIONS.DataType == 3 + Kernel = Gain_RowNorm * Kernel; + end + + OPTIONS.iG = sqrt(norcol(Kernel)'); % NORCOL computes the column norms to the SQUARE + OPTIONS.iG(OPTIONS.iG == 0) = min(OPTIONS.iG(OPTIONS.iG ~= 0)); + iKernel = spdiags((1./OPTIONS.iG).^OPTIONS.ExpoiG, 0, length(OPTIONS.iG), length(OPTIONS.iG)) ; + Kernel = (Kernel*iKernel)*iKernel; + + elseif OPTIONS.FFNormalization == 0 + + Kernel = read_gain(gainfile,OPTIONS.GoodChannel,1:nsrc); % Chunk of gain matrix for this block of sources + + end + + + % ESEN - Add Noise normalization to Kernel only format too + + if OPTIONS.NNormalization + tmp = (Kernel'*coefs*Data.FBaseline); + mean_Baseline= mean(tmp,2); + std_Baseline = std(tmp,0,2); + tmp = (Kernel'*coefs); + +% ImagingKernel = (tmp - repmat(mean_Baseline, 1, size(tmp, 2))) ./ repmat(std_Baseline, 1, size(tmp, 2)); + ImagingKernel = tmp ./ repmat(std_Baseline, 1, size(tmp, 2)); + ImagingKernel = single(ImagingKernel); + clear tmp mean_Baseline std_Baseline + else + ImagingKernel = single(Kernel'*coefs); + end + + clear Kernel + +end + + + +if OPTIONS.Verbose + bst_message_window({... + 'Inverse Transformation -> DONE.'... + }) +end + +% +% MN estimate - DONE -------------------------------------------------------------------------------------------------------------------------- + + +% Save Results in Result file ----------------------------------------------------------------------------------------------------------------- +% +% Fields from Results structure +Channel = OPTIONS.Channel; +ChannelFlag = Data.ChannelFlag; +Comment = sprintf('MIN NORM, rank %.0f',OPTIONS.Rank); +DataFile = OPTIONS.DataFile; +Date = datestr(datenum(now),0); +Time = [OPTIONS.SegmentIndices]; +ImageGridTime = Data.Time(Time); +ImageGridAmp = ImageGridAmp; % monster matrix when ImagingKernel is not computed +Function = mfilename; % name of this calling routine +HeadModelFile = OPTIONS.HeadModelFile; +ModelGain = HeadModel.Gain{1}; +Projector = Data.Projector; +SourceLoc = HeadModel.GridLoc{1}; +SourceOrder = -1; + +NoiseCov = []; +SourceCov = []; +PatchNdx = []; +PatchAmp = []; + + +% Reduced Results structure for call from bst_sourceimaging. +Results = struct('Comment',Comment,'Function',mfilename,... + 'OPTIONS',OPTIONS,'Date','','Time',Time,'HeadModelFile',HeadModelFile,... + 'Channel',Channel,'ChannelFlag',Data.ChannelFlag,'DataFile',OPTIONS.DataFile,... + 'NoiseCov',NoiseCov,'SourceCov',SourceCov,... + 'Projector',Projector,'SourceLoc',SourceLoc,'SourceOrder',SourceOrder,... + 'SourceOrientation',[],'TimeSeries',[],'ImagingKernel',ImagingKernel,'ModelGain',ModelGain,... + 'PatchNdx',PatchNdx,'PatchAmp',PatchAmp, ... + 'ImageGridAmp',ImageGridAmp,'ImageGridTime',ImageGridTime,'Fsynth',Fsynth); + +return + +% ----------------------------------------------------------------------------------------------------- +% +% +% SubFunctions +% +% +% ----------------------------------------------------------------------------------------------------- + +function varargout = gainmat_covar(varargin) + +% GAINMAT_COVAR Computation of gain matrix covariance +% function [GainCovar] = gainmat_covar(gainfile,OPTIONS) +% Computation of gain matrix covariance +% +% INPUTS +% +% gainfile : a string - filename of the binary gain matrix file (imaging grid) +% OPTIONS : a structure specifying the options for the computation +% .Verbose : turn on/off verbose mode (1/0) +% .DataType: scalar specifying the type of data +% 1 is MEG +% 2 is EEG +% 3 is MEG/EEG fusion +% .FFNormalization : flag specifying whether forward field normalization is requested +% 0 off +% 1 on +% .GoodChannel : Indices of good channels for current DataType +% .MEGChannel : Indices of all MEG channels +% .EEGChannel : Indcies of all EEG channels +% +% OUTPUTS +% GainCovar : a structure with the proper gain covar matrix outputs +% +% /---Script Author--------------------------------------\ +% | *** John C. Mosher, Ph.D. | +% | Biophysics Group | +% | | +% | *** Sylvain Baillet, Ph.D. | +% | Cognitive Neuroscience & Brain Imaging Laboratory | +% | CNRS UPR640 - LENA | +% | Hopital de la Salpetriere, Paris, France | +% | sylvain.baillet@chups.jussieu.fr | +% \------------------------------------------------------/ +% +% Date of creation: October 2002 +% Script History ----------------------------------------------------------------------------------- +%--------------------------------------------------------------------------------------------------- + +% Map entries +gainfile = varargin{1}; +OPTIONS = varargin{2}; + +% Read number of sources and total number of channels +tmp = read_gain(gainfile,OPTIONS.GoodChannel(1),[]); +nsrc = length(tmp); clear tmp % Number of sources +tmp = read_gain(gainfile,[],1); +nchan = length(tmp); clear tmp % Number of channels + +% if OPTIONS.Verbose +% bst_message_window(sprintf('Image support: %.0f grid points . . .',nsrc)); +% end + +AAt = zeros(nchan); % Initialize GainCovar matrix +Gain_RowNorm = []; % Initialize matrix containing norms of gain matrix rows (useless and therefore empty if DataType ~= 3) + +for i = 1:OPTIONS.BLOCK:nsrc, + +% if OPTIONS.Verbose & ~isempty(OPTIONS.GUIHandles) +% waitbar(i/nsrc,OPTIONS.hwaitbar); +% end + + ndx = [0:(OPTIONS.BLOCK-1)]+i; + if(ndx(end) > nsrc), % last block too long + ndx = [ndx(1):nsrc]; + end + + % Normalize EEG and MEG forward fields separately + % Fusion Case + if OPTIONS.DataType == 3 % Compute gain matrix row norm on first block only + if i == 1 + Gain_RowNorm = zeros(length(OPTIONS.Channel)); + if ~isempty(OPTIONS.GUIHandles) + hkk = waitbar(0,'Processing Lead-Field Normalization...'); + end + + tmp = inorcol((read_gain(gainfile,OPTIONS.GoodChannel,1:nsrc))'); + Gain_RowNorm(OPTIONS.GoodChannel,OPTIONS.GoodChannel) = diag(diag([tmp])); + if 0 + for kk = OPTIONS.GoodChannel + Gain_RowNorm(kk,kk) = 1/norm(read_gain(gainfile,kk,1:nsrc)); + if ~isempty(OPTIONS.GUIHandles) + waitbar((kk-OPTIONS.GoodChannel(1)+1)/length(OPTIONS.GoodChannel)) + end + end + end + + if ~isempty(OPTIONS.GUIHandles) + close(hkk) + end + end + + temp = Gain_RowNorm([OPTIONS.GoodChannel],[OPTIONS.GoodChannel])*read_gain(gainfile,[OPTIONS.GoodChannel],ndx); + OPTIONS.iG = sqrt(norcol(temp)'); % NORCOL computes the column norms to the SQUARE + OPTIONS.iG(OPTIONS.iG == 0)= min(OPTIONS.iG(OPTIONS.iG ~= 0)); + OPTIONS.iG = spdiags((1./OPTIONS.iG).^OPTIONS.ExpoiG, 0, length(OPTIONS.iG), length(OPTIONS.iG)) ; + AAt(OPTIONS.GoodChannel,OPTIONS.GoodChannel) = AAt(OPTIONS.GoodChannel,OPTIONS.GoodChannel) + temp*(OPTIONS.iG*OPTIONS.iG)*temp'; % next chunk of correlations + + else % MEG | EEG + temp = read_gain(gainfile,[OPTIONS.MEGChannel],ndx); + if ~isempty(OPTIONS.MEGChannel) & ~isempty(temp) + temp(find(isnan(temp))) = 0; + if OPTIONS.FFNormalization % Forward field normalization is requested + OPTIONS.iG = sqrt(norcol(temp)'); % NORCOL computes the column norms to the SQUARE + OPTIONS.iG(OPTIONS.iG == 0)= min(OPTIONS.iG(OPTIONS.iG ~= 0)); + OPTIONS.iG = spdiags((1./OPTIONS.iG).^OPTIONS.ExpoiG, 0, length(OPTIONS.iG), length(OPTIONS.iG)) ; + AAt(OPTIONS.MEGChannel,OPTIONS.MEGChannel) = AAt(OPTIONS.MEGChannel,OPTIONS.MEGChannel) + temp*(OPTIONS.iG*OPTIONS.iG)*temp'; % next chunk of correlations + else % no FF normalization + AAt(OPTIONS.MEGChannel,OPTIONS.MEGChannel) = AAt(OPTIONS.MEGChannel,OPTIONS.MEGChannel) + temp*temp'; % next chunk of correlations + end + end + + clear temp OPTIONS.iG + + temp = read_gain(gainfile,OPTIONS.EEGChannel,ndx); + if ~isempty(OPTIONS.EEGChannel) & ~isempty(temp) + temp(find(isnan(temp))) = 0; + if OPTIONS.FFNormalization + OPTIONS.iG = sqrt(norcol(temp)'); % NORCOL computes the column norms to the SQUARE + if (min(OPTIONS.iG(:)) == max(OPTIONS.iG(:))) & length(OPTIONS.iG) > 1 % as it happens when EEG channels stand for ECoG or EMG + OPTIONS.iG = eps; + end + + OPTIONS.iG(OPTIONS.iG == 0) = min(OPTIONS.iG(OPTIONS.iG ~= 0)); + + OPTIONS.iG = spdiags((1./OPTIONS.iG).^OPTIONS.ExpoiG, 0, length(OPTIONS.iG), length(OPTIONS.iG)) ; + AAt(OPTIONS.EEGChannel,OPTIONS.EEGChannel) = AAt(OPTIONS.EEGChannel,OPTIONS.EEGChannel) + temp*(OPTIONS.iG*OPTIONS.iG)*temp'; % next chunk of correlations + else + AAt(OPTIONS.EEGChannel,OPTIONS.EEGChannel) = AAt(OPTIONS.EEGChannel,OPTIONS.EEGChannel) + temp*temp'; % next chunk of correlations + end + end + + clear temp OPTIONS.iG + + end % datatype + +end % for each block of sources + +varargout{1} = AAt; +varargout{2} = Gain_RowNorm; + + + +% ----------------------------------------------------------------------------------------------------------------------- diff --git a/concatenatepatch.m b/concatenatepatch.m new file mode 100644 index 0000000..d93988f --- /dev/null +++ b/concatenatepatch.m @@ -0,0 +1,35 @@ +function NFV = concatenatepatch(FV1,varargin) +%CONCATENATEPATCH - Concatenate FV patch structures +% [NFV] = concatenatepatch(FV1,FV2,FV3,...) +% will concatenate FV's .vertices fields and re-index .faces ones +% Additional field will be concatenated also (if possible) +% See also: patch + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-11 Creation +% +% ----------------------------- Script History --------------------------------- + +NFV=FV1; +fn=fieldnames(NFV); +nfn=length(fn); +for i=2:nargin + nv=size(NFV.vertices,1); + NFV.vertices=[NFV.vertices; getfield(varargin{i-1}, 'vertices')]; + NFV.faces=[NFV.faces; getfield(varargin{i-1}, 'faces')+nv]; + for j=1:nfn + try + NFV=setfield(NFV, fn{j}, [ getfield(NFV, fn{j}) ; getfield(varargin{i-1}, fn{j}) ]); + catch + warning(sprintf('Can''t concatenate field: %s', fn{j})); + end + end + +end \ No newline at end of file diff --git a/continuity.m b/continuity.m new file mode 100644 index 0000000..75df912 --- /dev/null +++ b/continuity.m @@ -0,0 +1,41 @@ +function [y]=continuity(x,l,dim,lm) +%continuity - Assess minimal continuity in data +% [y]=continuity(x,w,dim,wm) +% x: ND-array of logical values (0/1) +% w: length of consecutive values explored +% dim: dimension of x which is explored. Default: 1 +% wm: minimal true values in that window. Default: wm=w +% +% NB: This function is especially useful for assessing a minimal number of +% consecutive samples below a given significance threshold. +% E.g: p is a Nc-channels x Nt-samples array of p values +% To assess a minimal length of 10 consecutive samples: +% continuity(p,10,2) + +% KND, 29-Aug-2005 + +if nargin<3 + dim=1; +end +if nargin<4 + lm=l; +end + +sx=size(x); +x=logical(x); +x=nd2array(x,dim); + +y=logical(zeros(size(x))); + +mx=sx(dim); +for i=1:sx(dim) + t=[-l+1:0]; + if i=lm; + t=t+1; + end +end +y=nd2array(y,-dim,sx); diff --git a/corrcoef2.m b/corrcoef2.m new file mode 100644 index 0000000..a379fe7 --- /dev/null +++ b/corrcoef2.m @@ -0,0 +1,147 @@ +function [r,p,t,z,p_yy,z_yy,r_yy]=corrcoef2(X,Y,sp) +%CORRCOEF2 - Iterative cap function for CORRCOEF +% [r,p,t,z]=corrcoef2(X,Y) computes the Pearson's correlation +% coefficients between the columns of X (a M-by-N matrix) and columns of +% Y (a M-by-P one) leading to a N-by-P matrix. +% r and p have the same size as the rest of Y. +% T-value t is computed as: t = r.*sqrt((n-2)./(1-r.^2)); +% Z-score z is : z = log(abs((r+1)./(r-1)))/2 +% [ref: http://faculty.chass.ncsu.edu/garson/PA765/correl.htm#faq] +% +% [r,p,t,z,p_yy,z_yy,r_yy]=corrcoef2(X,Y) also reports significant +% difference between correlations coefficients derived from Y columns. +% This requires that X is a M-by-1 vector. +% Ref: Comparing correlated correlation coefficients, Meng, 1992 +% +% [...] = corrcoef2(X,Y,sp) draws scatterplots (if sp==true) +%See also: corrcoef + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-02-04 Creation +% +% ----------------------------- Script History +% --------------------------------- + +sX=size(X); +sY=size(Y); +Y=Y(:,:); +if isvector(X) + X=X(:); + sX=size(X); + if numel(X)~=sY(1) + error('KND:corrcoef2:XYmismatch', 'The length of X and the number of lines in Y must match.'); + end +else + if ~isequal(sX(3:end),sY(3:end)) + error('KND:corrcoef2:XYmismatch', 'The remaining dimensions of X and Y must match.'); + end + X=X(:,:); +end +r=NaN*zeros([sX(2) sY(2:end)]); +p=r; +for ix=1:sX(2) + for iy=1:sY(2) + [r2,p2]=corrcoef(X(:,ix),Y(:,iy)); + r(ix,iy)=r2(2); + p(ix,iy)=p2(2); + end +end + +if nargout>2 + n=sX(1); + t = r.*sqrt((n-2)./(1-r.^2)); + if nargout>3 + z = log(abs((r+1)./(r-1)))/2; + end +end + +if nargout > 4 + if sX(2) > 1 + error('KND:corrcoef2:Xvectorfor', 'X must be a vector of observations for comparing regressors in Y.'); + end + nY=prod(sY(2:end)); + + % pairs of Y's + yy = nchoosek(1:nY,2); + % indices of the yy + idx = find(tril(ones(nY),-1)); + % cross-correlations in Y + r_yy = corrcoef(Y); + r_yy = r_yy(idx); + + r2 = sum(r(yy).^2')'/2; + f = (1-r_yy)./2./(1-r2); + f(f>1)=1; + h = 1 + r2./(1-r2).*(1-f); + + z_yy=diag(Inf*ones(nY,1)); + + z_yy(idx) = diff(z(yy)')'.*sqrt((n-3)./2./(1-r_yy)./h); + z_yy = z_yy + -z_yy'; + + %z_yy(z_yy<0)=-Inf; + p_yy = 0.5 * erfc(z_yy ./ sqrt(2)); + +end +if nargin<3 + return +end +% Scatterplots +nx=size(X,2); +ny=size(Y,2); +for i=1:nx + for j=1:ny + subplot(nx,ny,(j-1)*nx+i) + plot(Y(:,j),X(:,i),'x') + axis square + end +end + + +return + +%% avoid using corrcoef + +% ToDO: Implement directly corrcoef code down here. + +t = isnan(x); +% Compute correlation for each pair +r = eye(m,class(x)); +n = diag(sum(t,1)); +jk = 1:2; +for j = 2:m + jk(1) = j; + for k=1:j-1 + jk(2) = k; + tjk = ~any(t(:,jk),2); + njk = sum(tjk); + if njk<=1 + rjk = NaN; + else + rjk = correl(x(tjk,jk)); + rjk = rjk(1,2); + end + r(j,k) = rjk; + n(j,k) = njk; + end +end +r = r + tril(r,-1)'; +n = n + tril(n,-1)'; + +% ------------------------------------------------ +function [r,n] = correl(x) +%CORREL Compute correlation matrix without error checking. + +[n,m] = size(x); +c = cov(x); +d = sqrt(diag(c)); % sqrt first to avoid under/overflow +dd = d*d'; dd(1:m+1:end) = diag(c); % remove roundoff on diag +r = c ./ dd; + diff --git a/cov2.m b/cov2.m new file mode 100644 index 0000000..cf2c288 --- /dev/null +++ b/cov2.m @@ -0,0 +1,28 @@ +function V = cov2(X,varargin) +%COV2 - Multidimensional Covariance +% [V] = cov2(X) +% Computes the M-by-M-by-[...] covariance matrix of data X, which are +% given as N-by-M-by-[...] matrix , N observations and M variables. +% Example +% >> V=cov2(X(:,:,:)) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-14 Creation +% +% ----------------------------- Script History --------------------------------- + +sX=[size(X) 1]; +X=reshape(X,sX(1),sX(2),prod(sX(3:end))); +V=zeros(sX(2), sX(2), prod(sX(3:end))); +for i=1:size(X,3); + V(:,:,i)=cov(X(:,:,i),varargin{:}); +end \ No newline at end of file diff --git a/curvature_cortex.m b/curvature_cortex.m new file mode 100644 index 0000000..af75c2f --- /dev/null +++ b/curvature_cortex.m @@ -0,0 +1,134 @@ +function [curvature_sigmoid,curvature]=curvature_cortex(arg1,arg2,arg3,arg4) +%CURVATURE_CORTEX - calculates cortex curvature +% function [curvature_sigmoid,curvature]=curvature_cortex(arg1,arg2,arg3,arg4) +% +% function [curvature_sigmoid,curvature]=curvature_cortex(FV,VertConn,sigmoid_const,show_sigmoid) +% FV is the Faces/Vertices structure used to calculate curvature +% VertConn is the vertices connectivity of FV +% sigmoid_const is the sigmoid coefficient (small values give smooth transition of convex to concave areas +% and vice versa). Use close to zero for linear transition. +% show_sigmoid chooses whether to show the sigmoid (1) or not (0) +% +% curvature returned is the surface curvature +% curvature_sigmoid returned is the curvature weighted by a sigmoid +% +% function [curvature_sigmoid]=curvature_cortex(curvature,sigmoid_const,show_sigmoid) +% Used to change the transition of positive and negative curvatures +% +% Remarks: Curvature_cortex uses an approximation of mean curvature. It calculates the mean angle between +% the surface normal of a vertex and the edges formed by the vertex and the neighbouring ones. +% +% See also VERTICES_CONNECTIVITY + +% ---------------------- 26-May-2004 11:29:55 ----------------------- +% --------- Automatically Generated Comments Block Using AUTO_COMMENTS --------- +% +% CATEGORY: Visualization +% +% Alphabetical list of external functions (non-Matlab): +% toolbox\colnorm.m +% +% At Check-in: $Author: Mosher $ $Revision: 8 $ $Date: 5/26/04 9:59a $ +% +% This software is part of BrainStorm Toolbox Version 2.0 (Alpha) 24-May-2004 +% +% Principal Investigators and Developers: +% ** Richard M. Leahy, PhD, Signal & Image Processing Institute, +% University of Southern California, Los Angeles, CA +% ** John C. Mosher, PhD, Biophysics Group, +% Los Alamos National Laboratory, Los Alamos, NM +% ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory, +% CNRS, Hopital de la Salpetriere, Paris, France +% +% See BrainStorm website at http://neuroimage.usc.edu for further information. +% +% Copyright (c) 2004 BrainStorm by the University of Southern California +% This software distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html . +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% ------------------------ 26-May-2004 11:29:55 ----------------------- + +% Author: Dimitrios Pantazis, Ph.D. + +% ----------------------------- Script History --------------------------------- +% DP 05-May-2002 Creation +% JCM 19-May-2004 Commenting +% ----------------------------- Script History --------------------------------- + + +%choose whether to display bars +if(~exist('VERBOSE','var')), + VERBOSE = 1; % default non-silent running of waitbars +end + +narg = nargin; +if narg==4 + %assign inputs + FV=arg1; + VertConn=arg2; + sigmoid_const=arg3; + show_sigmoid=arg4; + + %ititialization + nVertices=size(FV.vertices,1); + + %calculate normals and curvature of FV + hf=figure('Visible','off'); + hp=patch('faces',FV.faces, 'vertices', FV.vertices); + normals=get(hp,'VertexNormals'); + close(hf); + %Make the normals unit norm + [nrm,normalsnrm]=colnorm(normals'); + + if(VERBOSE) + hwait = waitbar(0,sprintf('Calculating curvature...')); + drawnow %flush the display + step=round(nVertices/10); + end + %compute average angle on each vertex + curvature=zeros(nVertices,1); + curvature_sigmoid=zeros(nVertices,1); + for i=1:nVertices %for all vertices + if(VERBOSE) + if(~rem(i,step)) % ten updates + waitbar(i/nVertices,hwait,sprintf('Calculating curvature...')); + drawnow %flush the display + end + end + nNeighbours=length(VertConn{i}); %number of neighbours + edgevector=FV.vertices(VertConn{i},:)-repmat(FV.vertices(i,:),nNeighbours,1); %vectors joining vertex with neighbours + [nrm,edgevector]=colnorm(edgevector'); + curvature(i)=mean(acos(normalsnrm(:,i)'*edgevector))-pi/2; + curvature_sigmoid(i)= 1./(1+exp(-curvature(i).*sigmoid_const))-0.5; + end + close(hwait); +end + +if narg==3 + %assign inputs + curvature=arg1; + sigmoid_const=arg2; + show_sigmoid=arg3; + + curvature_sigmoid=zeros(length(curvature),1); + for i=1:length(curvature) + curvature_sigmoid(i)= 1./(1+exp(-curvature(i).*sigmoid_const))-0.5; + end +end + +if(exist('show_sigmoid')) + if(show_sigmoid) + x=-pi/2:0.01:pi/2; + y=1./(1+exp(-x*sigmoid_const))-0.5; + figure; + plot(x,y) + grid on; + title('Transition between negative and positive curvature'); + end +end diff --git a/data/COLORS.mat b/data/COLORS.mat new file mode 100644 index 0000000000000000000000000000000000000000..1e330cd8a2cda6024270782846a32e39ec646248 GIT binary patch literal 488 zcmeZu4DoSvQZUssQ1EpO(M`+DN!3vZ$Vn_o%P-2cQV4Jk_w>_Ia4t$sEJ;mK$j`G< z2u>_fa4bz%Ffvv!G`BJ_wK6nNFfuSORv;NLFnap(F)%PBFfuT(0cj2(1~S2b6-dJP zAT~%Gq{i9b$3G~TfdQn?04fGj#{$G4fUFOs2WB1%0~13wkWY@jA~N+QLG^h6X_)^& lGzcKOlNrc|xswyfmH=X7Ft}_#YbFT1w1@G@aepq*JOHV>D)|5a literal 0 HcmV?d00001 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you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-06 Creation +% +% ----------------------------- Script History --------------------------------- +[HOMEDIR,USBDIR]=mypath; +if isnan(USBDIR) + MATLABDIR=fullfile(HOMEDIR, 'matlab'); +else + MATLABDIR=fullfile(USBDIR, 'matlab'); +end + +% Brainstorm tools +addpath(fullfile(HOMEDIR, 'mtoolbox', 'brainstorm','Toolbox')); +addpath(genpath(fullfile(HOMEDIR, 'mtoolbox', 'brainstorm', 'PublicToolbox'))); + +% SPM2 Tools +addpath(fullfile(HOMEDIR, 'mtoolbox','spm2')); + +% EEGLAB +addpath(fullfile(HOMEDIR, 'mtoolbox', 'eeglab4.5b')); +addpath(fullfile(HOMEDIR, 'mtoolbox', 'eeglab4.5b', 'functions')); +% Native mat2cell & cell2mat are better: +addpath(fullfile(matlabroot, 'toolbox', 'matlab', 'datatypes')) + +% CTF/MRI plugin for EEGLAB +addpath(fullfile(HOMEDIR, 'mtoolbox', 'ctf')); + +addpath(MATLABDIR) +addpath(fullfile(MATLABDIR, 'behavioral')) +addpath(fullfile(MATLABDIR, 'ctf')) +addpath(fullfile(MATLABDIR, 'ctfimport')) +addpath(fullfile(MATLABDIR, 'brainstorm2', 'Developer')) +addpath(fullfile(MATLABDIR, 'stormvisa')) + +addpath(fullfile(HOMEDIR, 'data', 'studies', 'repromn' ,'matlab')) +if not(isnan(USBDIR)) + addpath(fullfile(USBDIR, 'data', 'studies', 'repromn' ,'matlab')) +end + +cd(fullfile(HOMEDIR, 'data', 'studies', 'repromn')) + +if (isnan(USBDIR)) + clear USBDIR +end diff --git a/data/test2.wrl b/data/test2.wrl new file mode 100644 index 0000000..9f59835 --- /dev/null +++ b/data/test2.wrl @@ -0,0 +1,30 @@ +#VRML V2.0 utf8 +WorldInfo {title "Matlab-VRML"} +NavigationInfo { + headlight FALSE + type "EXAMINE" +} +Shape { + geometry IndexedFaceSet { + appearance Appearance { + material Material { + ambientIntensity 0.4 + diffuseColor 0.2 0.7 0.2 + shininess 1.0 + specularColor 0.3 0.3 0.3 + } + } + coord Coordinate{ + point [ + 0 0 0 + 1 1 0 + -1 0 0 + 1 1 1 + -1 1 1 + -1 -1 1 ]} + color Color { color [1 0 0, 0 1 0, 0 0 1]} + colorIndex [0 1 2 -1 0 0 1] + colorPerVertex TRUE + coordIndex [0 1 2 -1, 3 4 5] +} +} diff --git a/dec2basen.m b/dec2basen.m new file mode 100644 index 0000000..aefd621 --- /dev/null +++ b/dec2basen.m @@ -0,0 +1,33 @@ +function s = dec2basen(d,b) +%DEC2BASEN Convert decimal integer to base B *number*. +% DEC2BASEN(D,B) returns the representation of D as a string in +% base B. D must be a non-negative integer array smaller than 2^52 +% and B must be an integer > 1. +% +% Examples +% dec2basen(23,3) returns [2 1 2] +% +% See also DEC2BASE + +% Original by Douglas M. Schwarz, Eastman Kodak Company, 1996. +% Modified (actually cut through !) by Karim N'Diaye, 2005 + +d = d(:); +if any(d ~= floor(d)) || any(d < 0) || any(d > 1/eps) + error('KND:dec2basen:FirstArg', 'D must be an array of integers, 0 <= D <= 2^52.'); +end +if numel(b)~=1 || b ~= floor(b) || b < 2 + error('KND:dec2basen:SecondArg', 'B must be an integer > 1'); +end +d = double(d); +b = double(b); +n = max(1,round(log2(max(d)+1)/log2(b))); +while any(b.^n <= d) + n = n + 1; +end +s(:,n) = rem(d,b); +while n > 1 & any(d) + n = n - 1; + d = floor(d/b); + s(:,n) = rem(d,b); +end diff --git a/decours.m b/decours.m new file mode 100644 index 0000000..c5d646b --- /dev/null +++ b/decours.m @@ -0,0 +1,256 @@ +function [capt]=decours(chnames, data, imod, allcond, PlotLat, Filtering, Ncond) +% decours(chnames, data[, imod,allcond,PlotLat, Filtre]) +% Affiche les décours du signal sur une liste de capteurs +% en fonction de la durée de stimulation +% data est au format data.G, data.Channel +% ex. decours({'mrt14'} , data) +% Si chnames est une 'cell' sur plusieurs lignes, 'decours' affiche les MOYENNES +% des capteurs sur chaque ligne +% +% > allcond = 1 pour avoir les plots sur la meme figure +% > imod = 1 pour l'auditif seul, 2 pour visuel, 3:les deux [bugge !], 0:demande +% > PlotLat = 1 pour qu'il place un ppoint sur la latence sur max +% > Filtre = 1 : slidingwindows, 2: lpass, 0:none + +COLORS={[0 0 0], [ .2 .7 .2], [0 0 1], [1 0 1] , [1 0 0]}; +COL2={[1 0 0], [0 1 0], [0 0 1]}; +global CONDS +CONDS={'TC', 'C','S','L','TL'} ; +CONDS={'C', 'IC','S','IL','L'} ; +MODAL={'Auditory' 'Visual'}; + +if nargin < 2 + return +end +if nargin < 4 + % Graphs on the same figure + allcond=1; +end + +if nargin < 5 + PlotLat=0; +end +if nargin < 6 + Filtering=0; +end + +if nargin < 7 + Ncond=5; +end +disp(fprintf('%d conditions', Ncond)); + +if isfield(data,'Time') + Time=data.Time; +else + global Time +end + +if ~iscell(chnames) & ischar(chnames) + chnames=cellstr(chnames); + if size(chnames,1)>1 + chnames=chnames'; + end +end + +if isfield(data,'G') & iscell(data.G) + if nargin<3 + ButtonName=questdlg('Which modality?', 'Question', 'Auditory','Visual', 'Both', 'cancel'); + switch ButtonName, + case 'Auditory', + F=data.G{1}; + imod=1; + case 'Visual', + F=data.G{2}; + imod=2; + case 'Both', + imod=3; + otherwise + return + end % switch + else + F=data.G{imod}; + end +elseif isfield(data,'F') + F=data.F; + data.G=F; +end + +if isfield(data,'F') + data=rmfield(data,'F'); +end + +if ischar(chnames) + chnames=cellstr(chnames); +end +if isnumeric(chnames) + chnames={data.Channel(chnames).Name}; +end +if size(chnames,1)>1 + % Dans le cas où l'on veut avoir des groupes d'électrodes on les + % indique en colonnes + + num=1:size(chnames,1); + for j=num + id=whichChannel(chnames(j,:), data.Channel, 'exact'); + disp(sprintf('Averaging %d electrodes', length(id))) + + if ~allcond & chnames{j,1}(1)=='M' + rev=1-2*(chnames{j,:}(2)=='L') + % reverse signal for meg ! + switch ndims(F) + case 3 + data.F(j,:,:)=rev*mean(F(id,:,:),1); + case 2 + data.F(j,:)=rev*mean(F(id,:),1); + end + else + switch ndims(F) + case 3 + data.F(j,:,:)=mean(F(id,:,:),1); + case 2 + data.F(j,:)=mean(F(id,:),1); + end + end + + chnames2{j}=sprintf('Group.%d',j); + end + + chnames2{1}='Right electrodes'; + chnames2{2}='Left electrodes'; + if size(chnames,2)>1 + chnames=chnames2; + end +else + num=1:length(chnames); + for j=num + id=whichChannel(chnames(j), data.Channel, 'exact'); + + disp(sprintf('Averaging %d electrodes', length(id))) + switch ndims(F) + case 3 + data.F(j,:,:)=mean(F(id,:,:),1); + case 2 + data.F(j,:)=mean(F(id,:),1); + end + end + +end + +if Filtering + disp('Filtering data') + switch Filtering + case 1, + disp('Sliding windows') + data.F=slidingwindows(data.F); + case 2, + disp('Low Pass') + data.F=lpass(data.F); + case 3 + filter=20; + disp(sprintf('Low Pass %fHz', filter)); + data.F=lpass(data.F, filter); + otherwise + filter=Filtering; + disp(sprintf('Low Pass %fHz', filter)); + data.F=lpass(data.F, filter); + end +end + + +if ~allcond + for j=1:size(data.F,3) + f(j)=figure(j); + clf + hold on + end +else + for j=num + f(j)=figure; + clf + hold on + end +end + +set(f,'Color', [1 1 1]) + +for j=num + p=[]; + if allcond + % Une figure par channel, plusieurs cond sur la meme + figure(f(j)); + set(f(j), 'Name', chnames{j}); + ax(j)=gca; + set(gca, 'Fontsize', 15) + if Ncond==3 + p=plot3cond(squeeze(data.F(j,:,:))); + else + p=plot5cond(squeeze(data.F(j,:,:))); + end + if PlotLat + addPlotLat(data.F(j,:,:)); + end + + hold off + if ~isfield(data, 'Title') + titletxt{j}=[MODAL{imod} ' - ' chnames{j}]; + else + titletxt{j}=[data.Title chnames{c}]; + + end + legtxt=CONDS; + + else + % Same figure for different channels, one figure by condition + for d=1:size(data.F,3) + figure(f(d)); + set(f(d), 'Name', ['Condition: ' CONDS{d}]); + F=data.F(j,:,d); %ipermute(lpass(permute(data.F(j,:,d),[1 3 2]),4),[1 3 2]); + p=[p plot(Time, F)]; + ax(d)=gca; + if ~isfield(data, 'Title') + titletxt{d}=[MODAL{imod} ' - ' CONDS{d}]; + else + titletxt{d}=[data.Title CONDS{d}] + end + + end + legtxt=chnames; + set(p,'Color', COL2{j}) + set(p,'LineWidth', 2) + + end +end +if size(data.F,2)==938 + set(ax, 'XLim', [-0.1 1.4]) +end +for a=1:length(ax) + if max(abs(get(ax(a), 'YLim')))<1e-10 + axes(ax(a)) + ylabel('Magnetic Field (T)') + elseif max(abs(get(ax(1), 'YLim')))<1e-4 + axes(ax(a)) + ylabel('Electric Potential (V)') + set(ax(a),'YDir', 'reverse') + end + + settitle(ax(a), titletxt{a}); + h=legend(legtxt); + set(h,'Position', [0.83 0.70 0.1643 0.2869]) +end + + + +function []=settitle(h,t) +global CONDS +axes(h) +ttl=title([t],'FontSize', 14); +posttl=get(ttl, 'Position'); +set(ttl, 'Position', [0.7 posttl(2) posttl(3)]) +xlabel('Time') +xlim=[-0.1 1.4]; +set(gca, 'xlim', xlim) +set(gca, 'xgrid', 'on') +set(gca, 'Box', 'on') +hold on +plot(xlim, xlim*0,':','Color', [.5 .5 .5]) +hold off \ No newline at end of file diff --git a/deg2rad.m b/deg2rad.m new file mode 100644 index 0000000..1c0a6ad --- /dev/null +++ b/deg2rad.m @@ -0,0 +1,10 @@ +% ----------------------------------------------------- +% deg2rad.m +% This M-function converts degree to radian +% Programmed by Tomonari Furukawa for MTRN9224 +% March 11, 2004 +% +% ----------------------------------------------------- +function rad = deg2rad(deg) + +rad = deg / 180 * pi; diff --git a/depfuntoolbox.m b/depfuntoolbox.m new file mode 100644 index 0000000..f41997f --- /dev/null +++ b/depfuntoolbox.m @@ -0,0 +1,62 @@ +function Files = depfuntoolbox(input) +%DEPFUNTOOLBOX Locate dependent functions of an M/P-file by toolbox +% +% Files = depfuntoolbox(filename) +% Files = depfuntoolbox(traceList) +% +% This function uses the depfun function to determine the dependent +% functions of any m or p file, and then separates the files based on the +% Matlab toolbox to which they belong. +% +% Input variables: +% +% filename: string with m or p filename +% +% traceList: cell array output of depfun function +% +% Output variables: +% +% Files: 1 x 1 structure. Each field is the name of a toolbox +% directory (for example, matlab = base Matlab, stats = +% Statistics Toolbox, map = Mapping Toolbox, etc) and holds a +% cell array of dependent function names associated with that +% toolbox. Dependent functions that are not part of a Matlab +% toolbox are listed under the fieldname 'other'. + +% Copyright 2006 Kelly Kearney + +%---------------------------- +% Check input, run depfun if +% necessary +%---------------------------- + +if ischar(input) + allFiles = depfun(input, '-quiet'); +elseif iscell(input) + allFiles = input; +else + error('Input must be a filename or cell array output of depfun'); +end + +%---------------------------- +% Separate by toolbox +%---------------------------- + +matlabToolbox = fullfile(matlabroot, 'toolbox'); +nchar = length(matlabToolbox); + +isNotMatlabProper = cellfun(@isempty, strfind(allFiles, matlabToolbox)); + +matlabFiles = allFiles(~isNotMatlabProper); +matlabFiles2 = cellfun(@(a) a(nchar+2:end), matlabFiles, 'UniformOutput', false); + +toolboxName = cellfun(@(a,b) a(1:b(1)-1), matlabFiles2, strfind(matlabFiles2, filesep), 'UniformOutput', false); +uniqueToolbox = unique(toolboxName); +filesInToolbox = cellfun(@(a) matlabFiles(strcmp(a, toolboxName)), uniqueToolbox, 'UniformOutput', false); + +Files = cell2struct(filesInToolbox, uniqueToolbox, 1); +if any(isNotMatlabProper) + Files.other = allFiles(isNotMatlabProper); +end + + diff --git a/detrend2.m b/detrend2.m new file mode 100644 index 0000000..d718f4c --- /dev/null +++ b/detrend2.m @@ -0,0 +1,65 @@ +function [X]=detrend2(X,o,i,d) +% detrend2 - polynomial detrending +% Y = detrend2(X,o,i,d) removes trends in data +% +% X: input data array +% o: order of the fitted polynom (default 1, i.e. linear detrending) +% i: indices of the control points (default: [], i.e. all points) +% d: dimension to work on (default: 1) + +% See also: detrend + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-21 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin < 2 + o = 1; +end +if nargin < 3 + i = []; +end +if nargin < 2 + d = 1; +end +nd = ndims(X); +if d>nd + error(sprintf('X has only %d dimensions', nd)); +end +sx = size(X); + +if o==0 + r = ones(1,nd); + r(d) = sx(d); + + S.type='()'; + S.subs = repmat({':'},1,nd); + S.subs{d} = i; + X = X - repmat(mean(subsref(X,S),d),r); + return +end + +error + + +% polynomial adjustment +%--------------------------------------------------------------------------- +G = []; +for i = 0:p + d = [1:m].^i; + G = [G d(:)]; +end +y = x - G*(pinv(G)*x); + + +% detrend - remove linear trend +% addpath('/pclxserver2/home/ndiaye/mtoolbox/spm2') +% F=spm_detrend(F',1)'; diff --git a/dgrouping.m b/dgrouping.m new file mode 100644 index 0000000..b0d218d --- /dev/null +++ b/dgrouping.m @@ -0,0 +1,67 @@ +function [I,nl,F] = dgrouping(G,S) +% dgrouping() - Get indices of data elements using grouping variable in multidimension (myanova) +% +% [I,NL,F] = dgrouping(G) +% +% G is a grouping variable with as many colunms (N) as there are +% factors in the design and as many unique elements per column as +% they are levels in the corresponding factor. +% G must represent BALANCED data across levels in each factor. +% I are the indices of the data in a N-dimensional array (one +% dimension per factor) +% NL : number of levels in each factor (size of reshaped data) +% F are the factors +% +% See also: myanova + +if prod(G)==max(size(G)),G=G(:);end +% number of factors +nf=size(G,2); +% total number of elements (inc. replications) +ne=size(G,1); +% output indices +I=zeros(ne,1); +% number of cells in the design +nc=1; + +% if length(unique(G, 'rows'))','name') +% Lists all MEX-files in the c:\matlab6p5\toolbox directory in the cell +% array of strings Names (including path). +% Note the regexp syntax of the filter string. +% Bytes is a structure with fields "total" and "dir". total is the +% total size of the directory, dir is a recursive substructure with +% the same fields as bytes for the subdirectories. +% +% [Files,Bytes,Names] = DIRR('c:\toto'... +% ,'name','bytes','>50000','isdir','0') +% Lists all files larger than 50000 bytes NOT recursively. +% +% [Files,Bytes,Dates] = DIRR('c:\matlab6p5\work','date','2005') +% Lists all dates of files from year 2005. (With path in front of +% date in the cell array of strings Dates) +% +% +% +% v1.02 +% Maximilien Chaumon +% maximilien.chaumon@chups.jussieu.fr +% 2006 06 16 + + +verbose = 0; +% set to 1 to get folders list in command window + +if nargin == 0 + chemin = cd; +end +if nargout == 0 + dum = varargin; + varargin{1} = 'name'; + varargin = [varargin(1) dum]; +end + +fields = {'name' 'date' 'bytes' 'isdir'}; + +if regexp(chemin,'[\*\?]') % if chemin contains any ? or * + filt = regexprep(chemin,'.*[\\/](.*\>)','$1');% get filter + filt = regexprep(filt,'\.','\.');% in regexp format + filt = regexprep(filt,'\*','.*'); + filt = regexprep(filt,'\?','.'); + filt = regexprep(filt,'(.*)','\\<$1'); + chemin = regexprep(chemin,'(.*)[\\/].*\>','$1');% and chemin +end + +if not(isempty(varargin)) % if additional fields were provided after chemin + for i = 1:length(fields) + if strcmp(varargin{1},fields{i})% if first varargin matches a fieldname, + % assume no filter was provided, + + if not(exist('filt','var'))% or it was in chemin and was set just before + filt = '.*';% set it to wildcard + break + + end + end + end + if not(exist('filt','var'))% else + filt = varargin{1};% first varargin is the filter + varargin(1) = []; + end +else% if no additional fields were provided and filter was not in chemin + if not(exist('filt','var')) + filt = '.*'; + end +end +% determine which varargin are fieldnames +whicharefields = zeros(1,length(varargin)); +for i = 1:length(varargin) + for j = 1:length(fields) + if strcmp(varargin{i},fields{j}) + whicharefields(i) = 1; + break + end + end +end +% set f2out and f2outfilt +f2out = {}; f2outfilt = {}; +idx = 0; +if not(isempty(varargin)) + for i = 1:length(varargin) + if whicharefields(i) + idx = idx + 1; + f2out{idx} = varargin{i}; + f2outfilt{idx} = ''; + else % if nargin{i} is not a fieldname, assume it's a filter + f2outfilt{idx} = varargin{i}; + end + end +end + +%%%%%%%%%%%%%%%%%%%% START +if verbose + disp(chemin); +end + +list = dir(chemin); +if isempty(list) + disp([chemin ' not found']); + if nargout == 0 + clear list + else + for i = 1:nargout - 2 + varargout{i} = []; + end + sumbytes = 0; + end + return +end +% remove . and .. +i_file = 1; +while i_file <= length(list) + if strcmp(list(i_file).name,'.')|strcmp(list(i_file).name,'..') + list(i_file) = []; + else + i_file = i_file + 1; + end +end + +% set sumbytes +sumbytes = struct('total',0,'dir',{}); +sumbytes(1).total = 0; +i_dir = 0; +% and all output fields +for i = 1:size(f2out,2) + f2out{2,i} = {}; +end +filenames = {}; +todel = 0; +r = 1; +for i_out = 1:size(f2out,2) + if strcmp(f2out{1,i_out},'isdir') + if strcmp(f2outfilt{i_out},'0') % check if no recursion is wanted + r = 0; + end + end +end + +% for each item in list +for i_file = 1:length(list) + for i_out = 1:size(f2out,2) % for every output field + if not(isempty(f2outfilt{i_out}))% if there is a filter + if strcmp(f2out{1,i_out},'bytes') % if field is 'bytes' + line = [num2str(list(i_file).(f2out{1,i_out})) f2outfilt{i_out} ';']; % compare with filter numerically + if eval(line)% if passes the filter + continue % continue to next field + else + todel(end+1) = i_file; % else set to be deleted + end + elseif not(strcmp(f2out{1,i_out},'isdir'))% if field is 'name' or 'date' + if regexpi(list(i_file).(f2out{1,i_out}),f2outfilt{i_out}) % apply filter + continue % continue to next field + else + todel(end+1) = i_file; % else set to be deleted + end + end + end + end + % once checked for every field's filter + if todel(end) == i_file % if one didn't pass, + if not(list(i_file).isdir) % and it's not a directory + continue % skip this file and continue + end + else + if regexpi(list(i_file).name,filt) % else, check for general filter on filename + sumbytes(1).total = sumbytes(1).total + list(i_file).bytes; % sum bytes of that level + for i_out = 1:size(f2out,2)% and assign all output fields with the values of that file + f2out{2,i_out}{end+1} = [chemin filesep num2str(list(i_file).(f2out{1,i_out}))]; + end + else + todel(end+1) = i_file; % else the file will be removed from the list structure + end + end + if list(i_file).isdir % if it's a directory + if not(r) + continue + end + i_dir = i_dir + 1; + cheminext = strcat(chemin,filesep,list(i_file).name); + % get it's content by recursion + % write the line to enter eval + line = '[list(i_file).isdir,sumbytes.dir(i_dir)'; + for i_out = 1:size(f2out,2)% with all the requested fields as temporary variables + line = [line ',f2outtemp{' num2str(i_out) '}']; + end + line = [line '] = dirr(cheminext,filt']; + for i_out = 1:size(f2out,2) + line = [line ',f2out{1,' num2str(i_out) '}']; + if f2outfilt{i_out} + line = [line ',f2outfilt{' num2str(i_out) '}']; + end + end + line = [line ');']; + eval(line); + + for i_out = 1:size(f2out,2) + f2out{2,i_out} = [f2out{2,i_out} f2outtemp{i_out}]; % catenate temporary variables with f2out + end + % sum bytes + sumbytes(1).total = sumbytes(1).total + sumbytes(1).dir(i_dir).total; % that level + the next one + list(i_file).bytes = sumbytes(1).dir(i_dir).total; % and set list(i_file).bytes to that value + if list(i_file).bytes & todel(end) == i_file + todel(end) = []; + end + end + + +end +todel(1) = []; +list(todel) = []; + + +for i_out = 1:size(f2out,2) + varargout{i_out} = f2out{2,i_out}; +end +if nargout == 0 + clear list + disp(char(f2out{2,1})); +end diff --git a/drag.m b/drag.m new file mode 100644 index 0000000..87af713 --- /dev/null +++ b/drag.m @@ -0,0 +1,289 @@ +function drag(varargin) +%DRAG Move around on a 2-D or 3-D plot. +% DRAG with no arguments toggles the plot dragging state. +% DRAG ON turns plot dragging on for the current figure. +% DRAG XON, YON, or ZON turns plot dragging on for the x, y, or z axis only. +% DRAG OFF turns plot dragging off in the current figure. +% DRAG RESET resets the restore point to the current axis settings. +% +% When plot dragging is on, you can click and drag the axes around while +% maintaining the current level of zoom. If DRAG RESET has not been +% called the restore point is the original non-explored plot. If DRAG +% RESET has been called the restore point is the retore point that existed +% when it was called. Double clicking retores the axes to the current +% restore point - the point at which plot dragging was first turned on for +% this figure (or to the state to which the restore point was set by DRAG +% RESET). +% +% In a figure with multiple subplots, pressing and holding the left mouse +% button drags around the currently active subplot, while pressing and +% holding the right mouse button drags around all subplots simultaneously. +% Double clicking with the left mouse button restores the currently active +% plot to its restore point, while double clicking with the right mouse +% button restores all subplots to their defined restore point. +% +% DRAG(FIG,OPTION) applies the drag command to the figure specified by +% FIG. OPTION can be any of the above arguments. +% +% Example: +% x = 0:0.1:5; y = exp(x); +% figure; subplot(211); plot(x,y,'r.'); subplot(212); plot(y,x,'g.'); +% drag xon; +% +% Ryan M. Eustice 08-15-2003 +% Woods Hole Oceanographic Institution, MS 7 +% Woods Hole, MA 02543 +% 508.289.3269 ryan@whoi.edu + +% History +% DATE WHO WHAT +%---------- ------------------ ------------------------------ +%2003-07-23 Ryan Eustice Created & written. +%2003-08-15 Boyko Stoimenov Modified the private function +% dragreset to correctly count the +% number of axes. Also, switched +% short-circuit && to & for matlab +% backwards compatability. +%2004-01-29 Ryan Eustice Fixed bug in private function +% dragreset to properly count +% number of axes and not count +% legend or colorbar objects. + +% Note: drag uses the figure buttondown and buttonmotion functions + +% +% PARSE ARGS - set fig and drag command +% +fignum = get(0,'CurrentFigure'); +if isempty(fignum) + return; % no figure +end + +switch nargin +case 0 % no arg in + switch get(fignum,'Tag') + case 'dragon' % toggle state + dragoff(fignum); + otherwise % turn on + figstate.motion = 'all'; + set(fignum,'UserData',figstate); + dragon(fignum); + end % switch get(fignum,'Tag') +case 1 % one arg in + switch lower(varargin{1}) + case 'on' + figstate.motion = 'all'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'off' + dragoff(fignum); + case 'reset' + dragreset(fignum); + case 'xon' + figstate.motion = 'xon'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'yon' + figstate.motion = 'yon'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'zon' + figstate.motion = 'zon'; + set(fignum,'UserData',figstate); + dragon(fignum); + otherwise + error(sprintf('Unrecognized argument ''%s''',varargin{1})); + end % switch varargin{1} +case 2 % two args in + fignum = varargin{1}; + switch lower(varargin{2}) + case 'on' + figstate.motion = 'all'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'off' + dragoff(fignum); + case 'reset' + dragreset(fignum); + case 'xon' + figstate.motion = 'xon'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'yon' + figstate.motion = 'yon'; + set(fignum,'UserData',figstate); + dragon(fignum); + case 'zon' + figstate.motion = 'zon'; + set(fignum,'UserData',figstate); + dragon(fignum); + otherwise + error(sprintf('Unrecognized argument ''%s''',varargin{1})); + end % switch varargin{2} +otherwise % too many args + error(nargchk(0,2,nargin)); +end % switch nargin + +%==================================================================== +% drag: private +%==================================================================== +function dragon(fignum) +figstate = get(fignum,'UserData'); +dragreset(fignum); +set(fignum,'Interruptible','on'); +set(fignum,'DoubleBuffer','on'); +set(fignum,'Tag','dragon'); +set(fignum,'WindowButtonDownFcn',@startexploring); +set(fignum,'WindowButtonUpFcn',@stopexploring); + + +function dragoff(fignum) +set(fignum,'DoubleBuffer','off'); +set(fignum,'Tag',''); +set(fignum,'WindowButtonDownFcn',''); +set(fignum,'WindowButtonUpFcn',''); + + +function dragreset(fignum) +figstate = get(fignum,'UserData'); +kids = get(fignum,'Children'); +cc = 1; +for ii=1:length(kids) + % check for regular axes handles by keying off the Tag field which should be + % empty. note that objects like legend and colorbar fill in the Tag field. + if strcmp(get(kids(ii),'Type'),'axes') & strcmp(get(kids(ii),'Tag'),'') + figstate.axishandle(cc) = kids(ii); + figstate.origlimits(cc,:) = axis(kids(ii)); + cc = cc+1; + end +end +figstate.numaxes = length(figstate.axishandle); +set(fignum,'UserData',figstate); + +%==================================================================== +% callbacks +%==================================================================== +function startexploring(obj,eventdata) +fignum = gcbf; +figstate = get(fignum,'UserData'); +switch get(fignum,'SelectionType') +case 'normal' %mouse left single-click + figstate.whichaxes = 'current'; % only drag current axis + axishandle = gca; + initaxis(axishandle); +case 'open' %mouse left or right double-click + axishandle = gca; + for ii=1:figstate.numaxes + if strcmp(figstate.whichaxes,'current') & figstate.axishandle(ii) == axishandle + % restore currently active axis limits to orig state + axis(axishandle,figstate.origlimits(ii,:)); + break; + elseif strcmp(figstate.whichaxes,'all') + % restore other subplot axis limits to orig state + axis(figstate.axishandle(ii),figstate.origlimits(ii,:)); + end + end +case 'alt' %mouse right single-click + figstate.whichaxes = 'all'; % drag all axes simultaneously + for ii=1:figstate.numaxes + axishandle = figstate.axishandle(ii); + initaxis(axishandle); + end +otherwise + error('Mouse SelectionType unknown'); +end +set(fignum,'WindowButtonMotionFcn',@setnewview); +set(fignum,'Pointer','Fleur'); +set(fignum,'UserData',figstate); % store figure state + + +function setnewview(obj,eventdata) +persistent cc; +fignum = gcbf; +figstate = get(fignum,'UserData'); +switch figstate.whichaxes +case 'current' + axishandle = gca; + updateaxes(axishandle,figstate.motion); +case 'all' + for ii=1:figstate.numaxes + axishandle = figstate.axishandle(ii); + updateaxes(axishandle,figstate.motion); + end +otherwise + %do nothing +end % switch figstate.whichaxes +cc = cc+1; +if mod(cc,2) + drawnow; % force screen update every other motion cycle (lowers cpu usage) +end + + +function stopexploring(obj,eventdata) +fignum = gcbf; +set(fignum,'WindowButtonMotionFcn',''); +set(fignum,'Pointer','arrow'); + +%==================================================================== +% callbacks: private +%==================================================================== +function pos = getcurrentposition(axishandle) +pos = get(axishandle,'CurrentPoint'); +pos = mean(pos); +pos = round(pos*1000)/1000; + + +function initaxis(axishandle) +state.currentaxislimits = axis(axishandle); +state.startpoint = getcurrentposition(axishandle); +set(axishandle,'UserData',state); % store axis state + + +function updateaxes(axishandle,motion) +state = get(axishandle,'UserData'); +state.endpoint = getcurrentposition(axishandle); +motionvector = state.startpoint - state.endpoint; + +if length(state.currentaxislimits) == 4 % 2D plot + switch motion + case 'all' + state.currentaxislimits = ... + [state.currentaxislimits(1:2) + motionvector(1), ... + state.currentaxislimits(3:4) + motionvector(2)]; + case 'xon' + state.currentaxislimits = ... + [state.currentaxislimits(1:2) + motionvector(1), ... + state.currentaxislimits(3:4)]; + case 'yon' + state.currentaxislimits = ... + [state.currentaxislimits(1:2), ... + state.currentaxislimits(3:4) + motionvector(2)]; + otherwise %do nothing + end % switch motion +elseif length(state.currentaxislimits) == 6 % 3D plot + switch motion + case 'all' + state.currentaxislimits = ... + [state.currentaxislimits(1:2) + motionvector(1), ... + state.currentaxislimits(3:4) + motionvector(2), ... + state.currentaxislimits(5:6) + motionvector(3)]; + case 'xon' + state.currentaxislimits = ... + [state.currentaxislimits(1:2) + motionvector(1), ... + state.currentaxislimits(3:4), ... + state.currentaxislimits(5:6)]; + case 'yon' + state.currentaxislimits = ... + [state.currentaxislimits(1:2), ... + state.currentaxislimits(3:4) + motionvector(2), ... + state.currentaxislimits(5:6)]; + case 'zon' + state.currentaxislimits = ... + [state.currentaxislimits(1:2), ... + state.currentaxislimits(3:4), ... + state.currentaxislimits(5:6) + motionvector(3)]; + otherwise %do nothing + end % switch motion +end +axis(axishandle,state.currentaxislimits); +set(axishandle,'UserData',state); diff --git a/dumpmemmex.dll b/dumpmemmex.dll new file mode 100644 index 0000000000000000000000000000000000000000..c230c630e2af2b5801a548185c2a6268613c5934 GIT binary patch literal 36864 zcmeIb4O~>!`Y*nR+29riXH-Zm)G@Iv&4w9JhT&xp2JrkFKca^~3H^Q)Mj*_0B#QzjyQ1F(N ztS%-revMx5+Cq=(PD~9NBYJ>ii%V4e&yvvk%Pp41?QK*t0?NZUxNE!Gg-$*7U5gx z;6?be`+Rr zw%q)|u$B4uh+pM3Z&Mz5>XXPJjYX0)5r&H$wVMz<2sxekqPcmGCXCXx`bVJD#t=%k zLythK|1`Wugp$wCjs<v-S!?Ym#*CVA=wd{ZfJKjxLX^~f{!{kJ2EFbQ$B`( z1_6nYWx3AH(V(-4#692>c?6q=(*Qm@$DS#jN88tR6EbSnzuMHof=k+OALYq)%9h7{*84-Ahnh|9L(Ro!0RnZrQSH!THv)D!G|U_KFQw#T%^goc5ZNLd!D#md*rofm z5JRscmz|Ny$DaaQs?Ay?l+t$TjKY$KM8)9qNNS*y_;wn#`>-MSEQtryk4kMARUgpM z)G#Ww_7Ha|zgbL)pc_J!RHpV2tBF0#G7V`eD^f2vF!0zr8%RR1^NNFIoL6kD+UogE zY)f;-7}%>ZI!=|=Fxr|_d!k;)bt}|9rOr-}Py3u>PeW=-G)7hob7(TuvoxmI-xt;OPk#3Wj&E78N=^CF##B@mP zsym~7wkgAOh>y8TyS+)BuE~(T!Klm4^~8uaCL`lh3IkWl4*|VAo!FHvW@%i>D!a+e zCm@5{bVwnfKBhjLAvK{?{$L1FP&P-mPx+2V?ba50)l1A28X z~o)AN(@OY^Brq-o70qZ`EW=bM*xD4>hhX%#Ht8Qoy^`$)Pp8lO1udcWP7%{CtJF#G^H+oWpkqrO#|)XCm$=;k=c(S zv)B>Tu$U%MSeJFu-@O%XE~QFIEj7vn24E)&fLC%{is2mFD=%5C%6Ic#Ir6 z&8xB^;9-{1P?_jmAwoQv6zV5*62!R1554;RRx$V(LfNhd`Yc@)W5ob3SNsLq5=~Gl zzsoNUBP@jwmhME6xw*x90thF7@d}{s%sm`w1V&KUkVEw-d1bSrAT8j$GI)?~3+?$X zAKIssA`@3JF_B};L%$l3rOv(MAj)JzC08h!M>(w=O#pJ}45UJ35zUopI%A%&r<&4b ziFd^Syg8+DFJkDa@llAn)@h0uChMBtPO?LXs^Cp{k=R z^W|tlb?*Lnf|= z38tm1@@8idP4T1TmQ?@1MuNk)F#aUX^MxxVf=n!FV7ds+GzTllcaasEA*If(t$mAx z4X$E(4~4F8>2ih7#CYv8N0TzDm+U_XVqSj!6s{~f*cjehzA(a7uN2=@8RlGt;u*Qc z>K`a-c{fwjq!fOhZ>7DIs^0Mghzd;;rtQtCqMGlO*;x(gRCkk#o!Q;Qa6#ZQ1ze(Q zOcYzi51M-Y`OhbbP(fh9MYoAT0t5W|GBB%Rd1Wlcqo9ToR%` zBm;>l9VyN2K@Sk)35A$RtT`)3nva~KlxuS)#oZ%Sa*mJm6w~Oc?7Y_L2$SW$UwNLgSOuInmaO3EoB5+ofWxpT#aLn=O~XAtSBt z28RRq*hRSLhwa%p(l{j-_7ov$Li7=kUYWn64c zCH#>R_8e6rwDUG9l@Lg^dXg20zmnXbvubyL(#;Pg;@=QfKQR@h=-H7dWu)`!NbX4O z2~M5nVNeF`ERreS5k@&L5`V%~?rY_xjzncv&EJmZ2*DI8Q+dr98I64pQo2m&(PbDv*bAQ_yJ0L^O!7x! zm*oFY7jsl(s=W0YY!k^WS%It zu%oQjB6Apb#q0ery+w?tK<;>NW~MbW)1IA~DWpV1$sdc7#lsr2q>s?q$dG}KWT#|i zX4x^lL;y?vm~0FX(Mh+3k#Vvjf-Jan*c8)*y=G4)Q5p*^*TBUf$8228B(aqZw8n&S z*T}1TdaG5GvZOK;162;5X;Zf+C@UvhI)~whX%)(7AtBh}@iV!JZo$UFyX70p$CJ$w zS_y2>a_9=6d3R$!+P&O4uzQ(Y+y^m8;FfBneuE{MZ{n8;l*munvD9?F06B|USjX;3 z!|K4IV}qctla&2L)x~V_V$;`Z%kN2&wk{l~1BGd8CD4FWf_(*QYd;2{<|-*wTYC|2 zSKSJ%SQG_e#}wx?A8=!R@MEj7!;y-x)6C8Ff^zJxzmqIdO)yq3xqNTj`a8TScBu>? zXcL7bFIh^}>fYibppYXKP9&1kx$0J-yA|(JsOmt~3&^ocV+SL}uPUj20LZ%+qE22M zyVQk!YOzkQ@?|QnRq(c8#^n#rSn0XVWn)}QhEmE775X{0gSiNlUiQu;m{3-sIr0^a zl#%_1)75=4*C)k72x1pj?LEh)z+RsUGd3ckwY4H!78P(*RWc0I8AHv|=(~AdFHy zS?UvV3b7CnbH)8Nr*u*-FsC0r*>0C-OG~h1fQDPNF&t^&FcdoofGs{S|2>V};y2(= zY2FMB8&Gy_luPxwyrYkDtyH0y=6uiw&u!k#vW>|vRSD_6SWjR;P5)uJc=Y5Kbvkx( zGIno_6hdST!x%RzheQ{Vs9@{M1#Q%l;FhX$C+n~#v09p{HBf`o+gx!EncT3Q+WH1X zB`%DhvrE;}+m?$4AxZ@)%;)}@uk5)nKwo*~m6eLMgKSADE;xxu>55lMK7$9}NsLWi zK~*#N@JHpR#P?cleHflp&lSOT8L6lj@6b@<;gera|D@+1;s~*A%28Ae04d0(5k`=e z(|cIWoNSk2A%R`utXO@y)bAd#r-1?LiiXk5Ewy_zrqg zyHXvmkqU4yqkS_iP&|$C=AO<_i#km@*7iYUd zSa0g?s6uI$NmbL7tl3HijWfN+sl?YJE^Y`xPgKt?Rdp-@t_=OLA;jtE*+MYXm!x^X z$<4)faZ>K|#Ts#o?&Q~EI@5FdmP154QO=-?LEL3twsOH@I(kj7@Bl50_5|{>p7RGp zh*V@<+{I!OiH#_6(nAV+n&x7L8v!+=KDRXBeYobm@F z6itL4^>gIMh9EyNfP7@&AtnOGQ|fvl0#%?yne^(Mo+i=F3Ul@nptdt|Fd?ksa2g~{#_))dp?Cm{R&Y`3+ z#8--H6~+-wwX(U$8)%t}iE1FSvbo-u3XzIgIvAZbFgi2hd`*sPv#KS)PSq01vDYAPdwbz5!%!q6x0TUAWS4*1i?Zp=<1GQ z7SyQ^iJvriCIy{#X~qa7e@!d7-YUN5`3z$r=z}65jZwzKKu7fX;?f8W>4Vsk%r&_i z(4slw75*w+aaYf2{&O|UOg~;fV(vWds@SF+R}fF9ZW0gkU#Ocp{Mdj?uOMpxaOML? z=@59+%>%`t{d351gP5*^HBoF5kE>fO{p%S^ulAvhXt17E()GCz&;mvN3R7{%rJZub z6MJT05^jB)BtmaiX!v%ux=oI#J2oBTHp11032IEb~)i<1hBxg=%lU<&fTj`E&{ z+YYxCt`@Eej)hwTC#F1dUPyWLJbVeh1iur0C;Tq>nDHOE4F59xUiiK6``}~C?LxIF zb(gw#KoT;k@G-cva9xBpCf${XnzxbK4h?&2?t_5GA4vnE7{GP0k$tWzbDvNC5jW%? zeErhSK9p;piBjaA(~vTSAZQJ=#}#jTOegKJ>@KA}2=caKgzMpU!8N3+ryQ@Jt6l`c zi;3iR4`5&>R-rR{xjrCg-usnj1-iOXE~5wJuG)rKvImT8Ex)*N|gx9aS-c zcZYZ+@2M2u83LV(c|J2+Ow!@l`~i))ypKQ7m(z4XD;^ae>?=7$V<)vhsP1!ZRi%J4 zA@8z~-X&_r!f1=S!43SF8wZ>5l~v3#%|CKxEVv9x93ScXf3F66K1E5rALHRs9i zUAQ9O^YP@WT`Bz|x#=i%ve^^CH?{kcf$hWCyXzow04abVZK6Su5v#`1f)b<=WYl@R z!X^gHh}W8AdND62u2+{Pu7sV9{~UaEYU`c@iRoE=fG8Z|0Daza%VDs&-d{kS538Z% zuYmx`Zn?VNPrPdRfW05babgB-$r!@@+aTmT`K`j+iOEZEa6ek%-j_VU{fWujf5d$T zt&n8Id9*O!8>Yp1j4+?UB8so>q_~mhYK^v5Kq+E+mrHYH0F#7)CV;|xTFAh3PFv

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The values in X +% are normalized via X/SUM(X) to determine the area of each slice of pie. +% If SUM(X) <= 1.0, the values in X directly specify the area of the pie +% slices. Only a partial pie will be drawn if SUM(X) < 1. +% +% E2PIE(X,EXPLODE) is used to specify slices that should be pulled out from +% the pie. The vector EXPLODE must be the same size as X. The slices +% where EXPLODE is non-zero will be pulled out. +% +% E2PIE(...,LABELS) is used to label each pie slice with cell array LABELS. +% LABELS must be the same size as X and can only contain strings. +% +% E2PIE(AX,...) plots into AX instead of GCA. +% +% H = E2PIE(...) returns a vector containing patch and text handles. +% +% E2PIE is different from the MATLAB version in that labels have +% line segments indicating which slice they belong to, and are +% spaced more rationally. +% +% Example +% e2pie([2 4 3 5],{'North','South','East','West'}) +% +% See also PIE. + +% Clay M. Thompson 3-3-94 +% Updated Eric M. Ludlam 2005 +% Copyright 1984-2006 The MathWorks, Inc. + +% Parse possible Axes input +[cax,args,nargs] = axescheck(varargin{:}); + +if nargs==0, error('Not enough input arguments.'); end %#ok + +x = args{1}(:); % Make sure it is a vector +args = args(2:end); + +if nargs>3, error('Too many input arguments.'); end %#ok + +nonpositive = (x <= 0); +if any(nonpositive) + warning('MATLAB:pie:NonPositiveData',... + 'Ignoring non-positive data in pie chart.'); + x(nonpositive) = []; +end +xsum = sum(x); +if xsum > 1+sqrt(eps), x = x/xsum; end + +% Look for labels +if nargs>1 && iscell(args{end}) + txtlabels = args{end}; + if any(nonpositive) + txtlabels(nonpositive) = []; + end + args(end) = []; +else + for i=1:length(x) + if x(i)<.01, + txtlabels{i} = '< 1%'; %#ok + else + txtlabels{i} = sprintf('%d%%',round(x(i)*100)); %#ok + end + end +end + +% Look for explode +if isempty(args), + explode = zeros(size(x)); +else + explode = args{1}; + if any(nonpositive) + explode(nonpositive) = []; + end +end + +explode = explode(:); % Make sure it is a vector + +if ~isempty(txtlabels) && length(x)~=length(txtlabels), + error('Cell array of strings must be the same length as X.'); %#ok +end + +if length(x) ~= length(explode), + error('X and EXPLODE must be the same length.'); %#ok +end + +cax = newplot(cax); +next = lower(get(cax,'NextPlot')); +hold_state = ishold(cax); + +theta0 = pi/2; +maxpts = 100; +inside = 0; + +h = []; +ytextmidlast = nan; +xtextlast = nan; +for i=1:length(x) + n = max(1,ceil(maxpts*x(i))); + r = [0;ones(n+1,1);0]; + theta = theta0 + [0;x(i)*(0:n)'/n;0]*2*pi; + txttheta = theta0 + x(i)*pi; + + if inside, + [xtext,ytext] = pol2cart(txttheta,.5); + else + [xtext,ytext] = pol2cart(txttheta,1.05); + end + + [xx,yy] = pol2cart(theta,r); + if explode(i), + [xexplode,yexplode] = pol2cart(theta0 + x(i)*pi,.1); + xtext = xtext + xexplode; + ytext = ytext + yexplode; + xx = xx + xexplode; + yy = yy + yexplode; + end + theta0 = max(theta); + h(i) = patch('XData',xx,'YData',yy,'CData',i*ones(size(xx)), ... + 'FaceColor','Flat','parent',cax); + + %% ERIC HACK + if ~isempty(txtlabels) + if ytext > .7 + ytextmid = ytext+.1; + elseif ytext < -.7 + ytextmid = ytext-.1; + else + ytextmid = ytext; + end + + if xtext > 0 + % We are slices on the right side of the chart + ha = 'left'; + xtextend = xtext+.2; + xtextmid = xtext+.1; + + if ~isnan(ytextmidlast) && xtextlast > 0 + if ytextmidlast >= ytextmid-.05 + ytextmid = ytextmidlast + .05; + end + else + %% First label. Use a flat line if > .7 + if ytext > -.7 + ytextmid = ytext; + end + end + + else + ha = 'right'; + xtextend = xtext-.2; + xtextmid = xtext-.1; + + if ~isnan(ytextmidlast) && xtextlast > 0 && ytextmidlast >= ytextmid+.05 + ytextmid = ytextmidlast - .05; + end + end + + if ~isempty(txtlabels{i}) + + xdata = [ xtext xtextmid xtextend ]; + ydata = [ ytext ytextmid ytextmid ]; + line(xdata, ydata, [ 0 0 0 ], 'color','k',... + 'clipping','off'); + + t(i) = text(xtextend,ytextmid,txtlabels{i},... + 'parent',cax,... + 'horizontalalign',ha); %#ok + ytextmidlast = ytextmid; + xtextlast = xtext; + end + end + %% END ERIC HACK +end + +if ~hold_state, + view(cax,2); set(cax,'NextPlot',next); + axis(cax,'equal','off',[-1.2 1.2 -1.2 1.2]) +end + +if nargout>0, hh = h; end +if nargout>1, th = t; end diff --git a/edist.c b/edist.c new file mode 100644 index 0000000..fecafb5 --- /dev/null +++ b/edist.c @@ -0,0 +1,68 @@ +/*-------------------------------------------------------------- +// file: edist.c - compute euclidian distance matrix +// D = edist(A,B) +// INPUTS: +// A - mxd matrix (m=number of points, d=number of dimensions) +// B - kxd matrix (k=number of points, d=number of dimensions) +// OUTPUTS: +// D - mxk matrix of euclidian distances +//--------------------------------------------------------------*/ +#include +#include "mex.h" + +/*-------------------------------------------------------------- +// function: mexFunction - Entry point from Matlab environment +// INPUTS: +// nlhs - number of left hand side arguments (outputs) +// plhs[] - pointer to table where created matrix pointers are +// to be placed +// nrhs - number of right hand side arguments (inputs) +// prhs[] - pointer to table of input matrices +//--------------------------------------------------------------*/ +void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray +*prhs[] ) +{ + int M,N,K; /* Sizes */ + int m,n,k; /* Loop variables */ + double *pA, *pB, *pD; + + if (nrhs < 2) + mexErrMsgTxt("Not enough input arguments."); + if (nrhs > 2) + mexErrMsgTxt("Too many input arguments."); + if (!mxIsDouble(prhs[0]) || !mxIsDouble(prhs[1])) + mexErrMsgTxt("Arguments must be type double."); + if (mxGetN(prhs[0]) != mxGetN(prhs[1])) + mexErrMsgTxt("matrix dimensions (number of columns) must agree."); + if (mxIsComplex(prhs[0]) || mxIsComplex(prhs[1])) + mexWarnMsgTxt("Complex parts ignored."); + + /* edist(MxK,NxK) => MxN */ + M = mxGetM(prhs[0]); /* Number of rows in output */ + N = mxGetM(prhs[1]); /* Number of columns in output */ + K = mxGetN(prhs[0]); /* Number of dimensions */ + + plhs[0] = mxCreateDoubleMatrix(M,N,mxREAL); + + pA = mxGetPr(prhs[0]); + pB = mxGetPr(prhs[1]); + pD = mxGetPr(plhs[0]); + + /* Now the distance computation */ + pA = mxGetPr(prhs[0]); + pB = mxGetPr(prhs[1]); + for (m=0; m<4Cpz<*-B#2{qp*^;p(M?YCJ zt#{2RbWk7OGP7*T&h!VyZIX6o2ioo?ENM3e+%?;pU59!)-o!NSjyHX-+|-j*2T#_M z*YDgXfs8|TlI`s5G`chA-uuoy_ug~Ad(J&qmYy94PqSr=F&#)z7`ud$QZ>&%Ih#lG 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index 0000000..e69de29 diff --git a/eeglab/icadefs.m b/eeglab/icadefs.m new file mode 100644 index 0000000..f7f1ba3 --- /dev/null +++ b/eeglab/icadefs.m @@ -0,0 +1,97 @@ +% icadefs() - function to read in a set of EEGLAB system-wide (i.e. lab-wide) +% or working directory-wide constants and preferences. Change the +% way these are defined in the master icadefs.m file (usually +% in dir eeglab/functions/sigprocfunc) or make a custom copy of +% the icadefs.m file in a project directory. Then, calling functions +% that call icadefs from an EEGLAB session in that working directory +% will read the local copy, which may set preferences different from +% the system-wide copy. +% +% Author: Arnaud Delorme, Scott Makeig, SCCN/INC/UCSD, La Jolla, 05-20-97 + +% Copyright (C) 05-20-97 Scott Makeig, SCCN/INC/UCSD, scott@sccn.ucsd.edu +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% ---------------------------------------------------------------------- +% ------ EEGLAB DEFINITION - YOU MAY CHANGE THE TEXT BELOW ------------- +% ---------------------------------------------------------------------- + +% INSERT location of ica executable for binica.m below +ICABINARY = '~/bin/ica_linux'; + +YDIR = 1; % positive potential up = 1; negative up = -1 + % for most ERP plots + +HZDIR = 'up'; % ascending freqs = 'up'; descending = 'down' + % (e.g., timef/newtimef frequency direction) + +% the eeg_options.m file also countains additional options + +% ---------------------------------------------------------------------- +% ------------------------ END OF DEFINITIONS -------------------------- +% ---------------------------------------------------------------------- + +TUTORIAL_URL = 'http://sccn.ucsd.edu/wiki/EEGLAB'; % online version +DEFAULT_SRATE = 256.0175; % default local sampling rate (rarely used) +DEFAULT_TIMLIM = [-1000 2000]; % default local epoch limits (ms) + +% Set EEGLAB figure and GUI colors +% -------------------------------- +lowscreendepth = 0; +if ~exist('OCTAVE_VERSION') + if get(0, 'screendepth') <=8 % if mono or 8-bit color + lowscreendepth = 1; + end; +end; +if lowscreendepth + fprintf('icadefs(): Setting display parameters for mono or 8-bit color\n'); + BACKCOLOR = [1 1 1]; % Background figure color + BACKEEGLABCOLOR = [1 1 1]; % EEGLAB main window background + GUIBUTTONCOLOR = [1 1 1]; % Buttons colors in figures + GUIPOPBUTTONCOLOR = [1 1 1]; % Buttons colors in GUI windows + GUIBACKCOLOR = [1 1 1]; % GUI background color + GUITEXTCOLOR = [0 0 0]; % GUI foreground color for text + PLUGINMENUCOLOR = [.5 0 .5]; % plugin menu color + +else % if full color screen + BACKCOLOR = [.93 .96 1]; % EEGLAB Background figure color + BACKEEGLABCOLOR = [.66 .76 1]; % EEGLAB main window background + GUIBUTTONCOLOR = BACKEEGLABCOLOR;% Buttons colors in figures + GUIPOPBUTTONCOLOR = BACKCOLOR; % Buttons colors in GUI windows + GUIBACKCOLOR = BACKEEGLABCOLOR;% EEGLAB GUI background color <--------- + GUITEXTCOLOR = [0 0 0.4]; % GUI foreground color for text + PLUGINMENUCOLOR = [.5 0 .5]; % plugin menu color +end; + + +% THE FOLLOWING PARAMETERS WILL BE DEPRECATED IN LATER VERSIONS +% ------------------------------------------------------------- + +SHRINKWARNING = 1; % Warn user about the shrink factor in topoplot() (1/0) + +MAXENVPLOTCHANS = 264; % maximum number of channels to plot in envproj.m +MAXPLOTDATACHANS = 264; % maximum number of channels to plot in dataplot.m +MAXPLOTDATAEPOCHS = 264; % maximum number of epochs to plot in dataplot.m +MAXEEGPLOTCHANS = 264; % maximum number of channels to plot in eegplot.m +MAXTOPOPLOTCHANS = 264; % maximum number of channels to plot in topoplot.m + +DEFAULT_ELOC = 'chan.locs'; % default electrode location file for topoplot.m +DEFAULT_EPOCH = 10; % default epoch width to plot in eegplot(s) (in sec) + +SC = ['binica.sc']; % Master .sc script file for binica.m + % MATLAB will use first such file found + % in its path of script directories. + % Copy to pwd to alter ICA defaults diff --git a/eeglab/plugins/LENA/eegplugin_lena.m b/eeglab/plugins/LENA/eegplugin_lena.m new file mode 100644 index 0000000..2ee3e95 --- /dev/null +++ b/eeglab/plugins/LENA/eegplugin_lena.m @@ -0,0 +1,33 @@ +function eegplugin_lena( fig, try_strings, catch_strings); +% Plugs in the LENA format importation +% K. N'Diaye, 2009/04/05 +if ~exist('pop_readlena', 'file') + addpath(fileparts(mfilename('fullpath'))); +end +if ~exist('fastReadLENAHeadBin', 'file') + addpath(fullfile(fileparts(mfilename('fullpath')),'ReadWriteLena')) + addpath(fullfile(fileparts(mfilename('fullpath')),'ReadWriteLena', 'Input')) + addpath(fullfile(fileparts(mfilename('fullpath')),'ReadWriteLena', 'Output')) + addpath(fullfile(fileparts(mfilename('fullpath')),'ReadWriteLena', '@xmltree')) +end; + +% e_try = 'try, if exist(''h'') == 1, clear h; disp(''EEGLAB note: variable h cleared''); end;'; +% e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +% nocheck = e_try; +% e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +% storenewcall = '[ALLEEG EEG CURRENTSET LASTCOM] = pop_newset(ALLEEG, EEG, CURRENTSET); h(LASTCOM);'; +% e_newnonempty = [e_catch 'eeg_h(EEG,LASTCOM); ... +% if ~isempty(LASTCOM) & ~isempty(EEGTMP), ... +% EEG = EEGTMP;' storenewcall 'disp(''Done.''); 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zaBq41@{zyz-q~wmbh*9${zQt;7cgMkSqrX93630lQivm$QOfZT2#kPCsJOYLUe#7fNd>AFytjZ1$QQZ%5%3FuXFs=o|*pe9F3 ziSw0|EDps(PE8WhtE^ZoHQ){b7>%xBM$7YnwkABn3bx7pM`q8wr)tvLrOI1*#2bCKjlnlz2@_ysM#~#Hf$mDfxhM zUL4Jk0x}jyV8_{F5e!wdtL(yI74pgQK|ySKP}KlGHRuUM39m) zRP^yqLJ^91YUr_QYAGj)g(T_@Q(^@GX%8d yqOyFtPFY%NtUkcWA`HC%Xr>|Q(zU3ekmiRX{`i%w^s9Hut`>A%)n}q${r>@K5=OxQ literal 0 HcmV?d00001 diff --git a/eeglab/plugins/LENA/pop_readLENA.m b/eeglab/plugins/LENA/pop_readLENA.m new file mode 100644 index 0000000..9778e64 --- /dev/null +++ b/eeglab/plugins/LENA/pop_readLENA.m @@ -0,0 +1,175 @@ +% pop_readLENA() - load LENA Data files (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_readLENA; % a window pops up +% >> EEG = pop_readLENA( lenafile ); +% +% Inputs: +% datafile - A LENA header file +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), readLENA() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2009, Karim N'Diaye (karim.ndiaye@upmc.fr) +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +function [EEG, command] = pop_readLENA(datafile) + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + cd('\data\confinum\RAWDATA\EEG5330'); + catch + try + cd('ndiayek\data\confinum\RAWDATA\EEG5330'); + catch + cd('d:\ndiayek\data\confinum\RAWDATA\EEG5330'); + end + end + [filename, filepath] = uigetfile('*.lena', 'Choose a datafile in a DS folder -- pop_readLENA()'); + drawnow; + if filename == 0 return; end; + datafile = fullfile(filepath,filename); +end; + +% load data +% --------- +EEG = eeg_emptyset; + [header data] = read_lena(datafile); +%[header data] = fastReadLENAHeadBin(datafile); + +EEG.setname = 'LENA data'; +[EEG.filepath,filename ,ext] = fileparts(datafile); +EEG.filename = [filename ext]; +EEG.data_filename = a%data_filename; +EEG.pnts = header.timeSamples; +EEG.nbchan = length(header.sensors.name); +if isempty(strmatch('datablock_dim', header.dimensions_names)) + EEG.trials = 1; +else + error ('Don''t know how to deal with multi trial data!') +end +EEG.srate = header.sampleRate; +EEG.xmin = header.preTrigger/header.sampleRate; +EEG.xmax = (header.timeSamples-1-header.preTrigger)/header.sampleRate; +EEG.data = data; +EEG.times = EEG.xmin:1./EEG.srate:EEG.xmax; + +try; + EEG.comments = header.history; +end +EEG.ref = ['nose']; + + + +%% Channel info +for chan = 1:EEG.nbchan + EEG.chanlocs(chan).labels = header.sensors.name{chan}; + fn=fieldnames(header.sensorSamples); + i=strmatch('list_sensors',fn, 'exact'); + if ~isempty(i) +% for i_fn=setdiff(1:numel(fn), i) +% EEG.chanlocs(chan) = setfield(fn{i_fn}, +% getfield(header.sensorSamples, fn{i_fn}) +% labels = header.sensors.name{chan}; +% end + end + +end + +% if isempty([chanlocs.scale]) +% chanlocs = rmfield(chanlocs, 'scale'); +% end + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_readLENA(''%s'');', datafile); + +% This +ptxfile = [ data_filename(1:end-5) '.ptx']; +if ~exist(ptxfile) + return +end + + +return +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/eeglab/plugins/LENA/readLENA.m b/eeglab/plugins/LENA/readLENA.m new file mode 100644 index 0000000..aa968b2 --- /dev/null +++ b/eeglab/plugins/LENA/readLENA.m @@ -0,0 +1,143 @@ +% read_lena() - read LENA header & data +% +% Usage: +% >> [header data lena_tree] = read_lena(lenafile) +% +% Required Input: +% lenafile = LENA header file +% Available options: +% device -> 'ALL' (default)|'MEG'|'EEG'|'EEG+MEG'|'DC' +% trials -> Trials to import as list of indices (default: [] = 'all') +% timewindow -> Default: [] = 'all' +% +% Outputs: +% header = header info (from reading the xml heder file) +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READLENA, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [header data lena_tree] = readLENA(lenafile,varargin) + +if nargin < 1 + help(mfilename); + return; +end; +binary_extensions = {'.bin' '.data'}; + + +lena_tree = xmltree(lenafile); +header = convert(lena_tree); + +if nargout<2 + return +end + +if nargin==2 + data_filename = varargin{1}; + if isfield(header, 'data_filename') + warning('Overloading binary data filname from header (%s) to: %s', header.data_filename, data_filename); + end + header.data_filename = data_filename; +end + + +if ~isfield(header, 'data_filename') + header.data_filename =''; + for i=1:length(binary_extensions) + data_filename = [lenafile(1:end-5) binary_extensions{i} ]; + if exist(data_filename, 'file') + header.data_filename = data_filename; + warning('Assumed binary data file not specified in header... Found possible match: %s', data_filename); + break; + end + end +end +if isempty(header.data_filename) + error('No datafile') +end + +fprintf('Importing data from binary file...\n') + +if strcmp(header.data_format,'LittleEndian') + data_fid = fopen(header.data_filename,'r','l'); +elseif strcmp(header.data_format,'BigEndian') + data_fid = fopen(header.data_filename,'r','b'); +else + warning('No data_format provided'); + data_fid = fopen(header.data_filename,'r'); +end + +% Read the offset because this info is not provided in header! +header.data_offset = getData_offset(lena_tree); +fseek(data_fid,data_offset); + +% Get data type : +switch(data_type) + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +% Get the data size : +header.data_size = getData_size(lena_tree); +data = fread(fid,length(time_dim),data_type); +% first sensor 1, from sample 1 to last (537264) + + +% +% fprintf('Importing channel location information') +% Channel=getfield(load([studyname '_channel']), 'Channel'); +% chanlocs=LENAchannels2chanlocs( Channel ); +% +% i=1; +% %datafilename=sprintf('%s%d.mat', database , i); +% f=dir(sprintf('%s*.mat', database)); +% f=strvcat({f.name}); +% f=f(:,length(database)+1:end); +% trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +% trials=sort(trials); +% +% h = waitbar(0,'Importing Datafiles. Please wait...'); +% for i=1:length(trials) +% waitbar(i/length(trials),h) +% datafilename=sprintf('%s%d.mat', database , trials(i)); +% fprintf('Importing %s\n', datafilename) +% Data(i)=load(datafilename); +% %channelflag=channelflags & Data(i).ChannelFlag; +% channelflag=channelflags; +% Data(i).F=Data(i).F(find(channelflag),:); +% end +%close(h) + +return diff --git a/eeglab/plugins/bstorm/WS_FTP.LOG b/eeglab/plugins/bstorm/WS_FTP.LOG new file mode 100644 index 0000000..3066cf0 --- /dev/null +++ b/eeglab/plugins/bstorm/WS_FTP.LOG @@ -0,0 +1,3 @@ +2004.01.07 17:05 A d:\ndiaye\matlab\eeglab4.301\plugins\bstorm\pop_readbstorm.m --> pclxserver2.meg.chups.jussieu.fr /meglx13/users/ndiaye/analyse/matlab/eeglab4.301/plugins/bstorm pop_readbstorm.m +2004.01.07 17:05 A d:\ndiaye\matlab\eeglab4.301\plugins\bstorm\readbstorm.m --> pclxserver2.meg.chups.jussieu.fr /meglx13/users/ndiaye/analyse/matlab/eeglab4.301/plugins/bstorm readbstorm.m +2004.01.07 17:05 A d:\ndiaye\matlab\eeglab4.301\plugins\bstorm\readbstorm.m~ --> pclxserver2.meg.chups.jussieu.fr /meglx13/users/ndiaye/analyse/matlab/eeglab4.301/plugins/bstorm readbstorm.m~ diff --git a/eeglab/plugins/bstorm/bstchannel2chanlocs.m b/eeglab/plugins/bstorm/bstchannel2chanlocs.m new file mode 100644 index 0000000..38079ce --- /dev/null +++ b/eeglab/plugins/bstorm/bstchannel2chanlocs.m @@ -0,0 +1,12 @@ +function [ chanlocs ] = bstchannel2chanlocs( Channel ) +%bstchannel2chanlocs - Converts BrainStorm Channel struct to EEGLAB chanlocs structure +% [ chanlocs ] = bstchannels2chanlocs( Channel ) +% +%NB: All Channel shoud be of the same type, of course... +for i=1:length(Channel) + eloc(i).X=Channel(i).Loc(1); + eloc(i).Y=Channel(i).Loc(2); + eloc(i).Z=Channel(i).Loc(3); + eloc(i).labels=Channel(i).Name; +end +chanlocs=convertlocs(eloc, 'cart2all') \ No newline at end of file diff --git a/eeglab/plugins/bstorm/bstormchannels2chanlocs.m b/eeglab/plugins/bstorm/bstormchannels2chanlocs.m new file mode 100644 index 0000000..f3ada0a --- /dev/null +++ b/eeglab/plugins/bstorm/bstormchannels2chanlocs.m @@ -0,0 +1,7 @@ +function [ ] = bstormchannels2chanlocs( Channel ) +%bstormchannels2chanlocs - Deprecated: use bstchannel2chanlocs + +%bstormchannels2chanlocs - Converts BrainStorm channels to EEGLAB chanlocs structure +% [ ] = bstormchannels2chanlocs( Channel ) +% +warning('Deprecated use: bstchannel2chanlocs') diff --git a/eeglab/plugins/bstorm/bstormchannels2chanlocs_gui.m b/eeglab/plugins/bstorm/bstormchannels2chanlocs_gui.m new file mode 100644 index 0000000..a275544 --- /dev/null +++ b/eeglab/plugins/bstorm/bstormchannels2chanlocs_gui.m @@ -0,0 +1,47 @@ +function [ chanlocs ] = bstormchannels2chanlocs( Channel , device ) +%bstormchannels2chanlocs - Converts BrainStorm channels to EEGLAB chanlocs structure +% [ chanlocs ] = bstormchannels2chanlocs( Channel , device ) +% +%INPUTS: +% Channel : a BrainStorm Channel structure +%Importing Electrodes to EEGLAB format + +error('NOT IMPLEMENTED YET') +return + +channelflags=zeros(length(Channel),1); +ChannelTypes = unique({Channel.Type}); +if nargin <2 + if length(ChannelTypes)>1 + DEVICES = ChannelTypes; + [s,v] = listdlg('PromptString','Select a device:',... + 'SelectionMode','multiple',... + 'ListString',DEVICES); + device={}; + if all(v) + for strread(DEVICES(s), '%s', 'delimiter', ',') + end + else + + end + else % There is only one type of channels + device=ChannelTypes; + end +if not(iscell(device)) + device={device}; +end +for i=1:length(device) + channelflags=channelflags + strcmp(device{i},{Channel.Type}'); +end +%channelflags(strmatch('EEG', {Channel.Type}))=1; +%channelflags(strmatch('MEG', {Channel.Type}))=1; + +Channel=Channel(find(channelflags)); + +for i=1:length(Channel) + eloc(i).X=Channel(i).Loc(1); + eloc(i).Y=Channel(i).Loc(2); + eloc(i).Z=Channel(i).Loc(3); + eloc(i).labels=Channel(i).Name; +end +chanlocs=convertlocs(eloc, 'cart2all') \ No newline at end of file diff --git a/eeglab/plugins/bstorm/eegplugin_bstorm.m b/eeglab/plugins/bstorm/eegplugin_bstorm.m new file mode 100644 index 0000000..f3a75f1 --- /dev/null +++ b/eeglab/plugins/bstorm/eegplugin_bstorm.m @@ -0,0 +1,28 @@ +function eegplugin_bstorm( fig, try_strings, catch_strings); +% Plugs in the BStorm importation +% K. N'Diaye, 2005/02/07 +if ~exist('pop_readbstorm') + try + p = which('eeglab'); + p=fileparts(p); + p=fileparts(p); + p=fileparts(p); + p=fullfile(p, 'matlab', 'eeglab', 'plugins', 'bstorm') + addpath(p) + catch + end + p = which('eegplugin_bstorm'); + p = p(1:findstr(p,'eegplugin_bstorm.m')-1); + addpath([ p 'bstorm' ] ); +end; + +e_try = 'try, if exist(''h'') == 1, clear h; disp(''EEGLAB note: variable h cleared''); end;'; +e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +nocheck = e_try; +e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +storenewcall = '[ALLEEG EEG CURRENTSET LASTCOM] = pop_newset(ALLEEG, EEG, CURRENTSET); h(LASTCOM);'; +e_newnonempty = [e_catch 'h(LASTCOM, EEG); if ~isempty(LASTCOM) & ~isempty(EEGTMP), EEG = EEGTMP;' storenewcall 'disp(''Done.''); end; clear EEGTMP; eeglab(''redraw'');']; + +filemenu = findobj(fig, 'label', 'File'); +neuromenu = findobj(filemenu, 'tag', 'import data'); +uimenu(neuromenu, 'Tag', 'bstormCmd', 'Label', 'From BrainStorm DS folder', 'CallBack', [ nocheck '[EEGTMP LASTCOM]= pop_readbstorm;' e_newnonempty ], 'Separator', 'on'); diff --git a/eeglab/plugins/bstorm/pop_readbstorm.m b/eeglab/plugins/bstorm/pop_readbstorm.m new file mode 100644 index 0000000..81cfb53 --- /dev/null +++ b/eeglab/plugins/bstorm/pop_readbstorm.m @@ -0,0 +1,147 @@ +% pop_readbstorm() - load BrainStorm Data files (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_readbstorm; % a window pops up +% >> EEG = pop_readbstorm( dsfolder ); +% +% Inputs: +% datafile - A datafile within a DS folder containing BrainStorm datafiles +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), readbstorm() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: pop_readbstorm.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 +% + +function [EEG, command] = pop_readbstorm(datafile); + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + %cd('..\..\data\studies\div\T01\div-d1-f.ds'); + catch + end + [filename, filepath] = uigetfile('*_data_*.mat', 'Choose a datafile in a DS folder -- pop_readbstorm()'); + drawnow; + if filename == 0 return; end; + datafile = [filepath filename]; +end; + +% load data +% --------- +EEG = eeg_emptyset; +[study EEG.chanlocs data dsfolder] = readbstorm(datafile); + +EEG.filename = study.Name +EEG.filepath = dsfolder; +EEG.setname = 'BrainStorm data'; +EEG.nbchan = length(channel); +EEG.srate = 1/mean(diff(data(1).Time)); +EEG.trials = length(data); +EEG.pnts = length(data(1).Time); +EEG.times = data(1).Time; +EEG.xmin = EEG.times(1); % huh?? +EEG.xmax = EEG.times(end); % huh?? +%Caution! CELL2MAT is overloaded in EEGLAB environment +fprintf('Importing data...(may take a while)') +EEG.data=zeros([size(data(1).F,1) size(data(1).F,2) EEG.trials]); +for i=1:EEG.trials + EEG.data(:,:,i)=data(i).F; +end +EEG.comments = study.Session; +EEG.ref = ['common']; + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_readbstorm(''%s'');', dsfolder); + +return; + + + +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/eeglab/plugins/bstorm/readbstorm.m b/eeglab/plugins/bstorm/readbstorm.m new file mode 100644 index 0000000..a961523 --- /dev/null +++ b/eeglab/plugins/bstorm/readbstorm.m @@ -0,0 +1,85 @@ +% readbstorm() - read BrainStorm datafiles +% +% Usage: +% >> [study channel data dsfolder] = readbstorm(datafile,device) +% +% Required Input: +% datafile = Data file within a DS folder +% (all data_*_[1..N] will be imported) +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% study = study info +% channel = sensor positions +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READBSTORM, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [Study,chanlocs,Data,dsfolder] = readbstorm(datafile,device) + +if nargin < 1 + help(mfilename); + return; +end; + +[dsfolder, filename]=fileparts(datafile) +studyname=strtok(filename,'_') +p=findstr(filename, '_') +database=filename(1:p(3)) +prev_dir=cd; +cd(dsfolder) +Study=load([studyname '_brainstormstudy']); + +fprintf('Importing channel location information') +Channel=getfield(load([studyname '_channel']), 'Channel'); +chanlocs=bstormchannels2chanlocs( Channel ); + +i=1; +%datafilename=sprintf('%s%d.mat', database , i); +f=dir(sprintf('%s*.mat', database)); +f=strvcat({f.name}); +f=f(:,length(database)+1:end); +trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +trials=sort(trials); + +h = waitbar(0,'Importing Datafiles. Please wait...'); +for i=1:length(trials) + waitbar(i/length(trials),h) + datafilename=sprintf('%s%d.mat', database , trials(i)); + fprintf('Importing %s\n', datafilename) + Data(i)=load(datafilename); + %channelflag=channelflags & Data(i).ChannelFlag; + channelflag=channelflags; + Data(i).F=Data(i).F(find(channelflag),:); +end +close(h) + +return diff --git a/eeglab/plugins/bstorm/v1/pop_readbstorm.m b/eeglab/plugins/bstorm/v1/pop_readbstorm.m new file mode 100644 index 0000000..3d752e1 --- /dev/null +++ b/eeglab/plugins/bstorm/v1/pop_readbstorm.m @@ -0,0 +1,156 @@ +% pop_readbstorm() - load BrainStorm Data files (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_readbstorm; % a window pops up +% >> EEG = pop_readbstorm( dsfolder ); +% +% Inputs: +% datafile - A datafile within a DS folder containing BrainStorm datafiles +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), readbstorm() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: pop_readbstorm.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 +% + +function [EEG, command] = pop_readbstorm(datafile); + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + cd('D:\ndiaye\data\studies\'); + catch + end + [filename, filepath] = uigetfile('*_data_*.mat', 'Choose a datafile in a DS folder -- pop_readbstorm()'); + drawnow; + if filename == 0 return; end; + datafile = [filepath filename]; +end; + +% load data +% --------- +EEG = eeg_emptyset; +[study channel data dsfolder] = readbstorm(datafile); + +EEG.filename = study.Name +EEG.filepath = dsfolder; +EEG.setname = 'BrainStorm data'; +EEG.nbchan = length(channel); +EEG.srate = 1/mean(diff(data(1).Time)); +EEG.trials = length(data); +EEG.pnts = length(data(1).Time); +EEG.times = data(1).Time; +EEG.xmin = EEG.times(1); % huh?? +EEG.xmax = EEG.times(end); % huh?? +%Caution! CELL2MAT is overloaded in EEGLAB environment +fprintf('Importing data...(may take a while)') +EEG.data=zeros([size(data(1).F,1) size(data(1).F,2) EEG.trials]); +for i=1:EEG.trials + EEG.data(:,:,i)=data(i).F; +end +EEG.comments = study.Session; +EEG.ref = ['common']; + +fprintf('Importing channel location information') +for i=1:length(channel) + eloc(i).X=channel(i).Loc(1); + eloc(i).Y=channel(i).Loc(2); + eloc(i).Z=channel(i).Loc(3); + eloc(i).labels=channel(i).Name; +end +EEG.chanlocs=convertlocs(eloc, 'cart2all') + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_readbstorm(''%s'');', dsfolder); + +return; + + + +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/eeglab/plugins/bstorm/v1/readbstorm.m b/eeglab/plugins/bstorm/v1/readbstorm.m new file mode 100644 index 0000000..2f45468 --- /dev/null +++ b/eeglab/plugins/bstorm/v1/readbstorm.m @@ -0,0 +1,106 @@ +% readbstorm() - read BrainStorm datafiles +% +% Usage: +% >> [study channel data dsfolder] = readbstorm(datafile,device) +% +% Required Input: +% datafile = Data file within a DS folder +% (all data_*_[1..N] will be imported) +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% study = study info +% channel = sensor positions +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READBSTORM, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [Study,Channel,Data,dsfolder] = readbstorm(datafile,device) + +if nargin < 1 + help(mfilename); + return; +end; + +[dsfolder, filename]=fileparts(datafile) +studyname=strtok(filename,'_') +p=findstr(filename, '_') +database=filename(1:p(3)) +prev_dir=cd; +cd(dsfolder) +Study=load([studyname '_brainstormstudy']); +Channel=getfield(load([studyname '_channel']), 'Channel'); + +%Importing Electrodes to EEGLAB format +channelflags=zeros(length(Channel),1); +if nargin <2 + DEVICES={'EEG', 'MEG', 'EEG+MEG', 'ALL'}; + [s,v] = listdlg('PromptString','Select a device:',... + 'SelectionMode','single',... + 'ListString',{'EEG', 'MEG', 'EEG+MEG'}); + if all(v) + switch(s) + case 1 + device={'EEG'} + case 2, device={'MEG'} + case 3, device = {'EEG', 'MEG'} + end + end +end +for i=1:length(device) + channelflags=channelflags + strcmp(device{i},{Channel.Type}'); +end +%channelflags(strmatch('EEG', {Channel.Type}))=1; +%channelflags(strmatch('MEG', {Channel.Type}))=1; + +Channel=Channel(find(channelflags)); + +i=1; +%datafilename=sprintf('%s%d.mat', database , i); +f=dir(sprintf('%s*.mat', database)); +f=strvcat({f.name}); +f=f(:,length(database)+1:end); +trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +trials=sort(trials); + +h = waitbar(0,'Importing Datafiles. Please wait...'); +for i=1:length(trials) + waitbar(i/length(trials),h) + datafilename=sprintf('%s%d.mat', database , trials(i)); + fprintf('Importing %s\n', datafilename) + Data(i)=load(datafilename); + %channelflag=channelflags & Data(i).ChannelFlag; + channelflag=channelflags; + Data(i).F=Data(i).F(find(channelflag),:); +end +close(h) + +return diff --git a/eeglab/plugins/bstorm1.01/bstormchannels2chanlocs.m b/eeglab/plugins/bstorm1.01/bstormchannels2chanlocs.m new file mode 100644 index 0000000..a9b1d35 --- /dev/null +++ b/eeglab/plugins/bstorm1.01/bstormchannels2chanlocs.m @@ -0,0 +1,67 @@ +% bstormchannels2chanlocs() - Converts brainstorm channels to EEGLAB chanlocs structure +% +% Usage: +% >> [chanlocs channelflags] = bstormchannels2chanlocs( Channel , device) +% +% Required Input: +% Channel = Brainstorm Channel structure +% (e.g. read from a study_channel.mat file) +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% channelocs = N sensor positions +% channelflags = [Nx1] array of boolean, true if channel was imported +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2005 +% +% See also: +% POP_READBSTORM, EEGLAB + +% $Log: bstormchannels2chanlocs.m,v $ +% Revision 1.01 2005/02/01 00:07:38 knd +% pop_chanedit compatible (no sph_phi/theta_besa fields) + + +function [ chanlocs, channelflags ] = bstormchannels2chanlocs( Channel , device) +channelflags=zeros(length(Channel),1); +if nargin <2 + DEVICES={'EEG', 'MEG', 'EEG+MEG', 'ALL'}; + [s,v] = listdlg('PromptString','Select a device:',... + 'SelectionMode','single',... + 'ListString',{'EEG', 'MEG', 'EEG+MEG'}); + if all(v) + switch(s) + case 1 + device={'EEG'} + case 2, device={'MEG'} + case 3, device = {'EEG', 'MEG'} + end + end +end +if not(iscell(device)) + device={device}; +end +for i=1:length(device) + channelflags=channelflags + strcmp(device{i},{Channel.Type}'); +end +%channelflags(strmatch('EEG', {Channel.Type}))=1; +%channelflags(strmatch('MEG', {Channel.Type}))=1; + +Channel=Channel(find(channelflags)); + +for i=1:length(Channel) + eloc(i).X=Channel(i).Loc(1); + eloc(i).Y=Channel(i).Loc(2); + eloc(i).Z=Channel(i).Loc(3); + eloc(i).labels=Channel(i).Name; +end +% This ouptuts fields sph_theta_besa which are not compatible with +% pop_chanedit function (Revision 1.111) +% chanlocs=convertlocs(eloc, 'cart2all') +% + +chanlocs=pop_chanedit(eloc, 'convert', 'cart2topo', 'convert', 'cart2sph'); + +return diff --git a/eeglab/plugins/bstorm1.01/eegplugin_bstorm.m b/eeglab/plugins/bstorm1.01/eegplugin_bstorm.m new file mode 100644 index 0000000..2c1e4be --- /dev/null +++ b/eeglab/plugins/bstorm1.01/eegplugin_bstorm.m @@ -0,0 +1,69 @@ +% eegplugin_bstorm() - EEGLAB plugin for importing data from BrainStorm toolbox +% +% Usage: +% >> eegplugin_bstorm(fig, try_strings, catch_strings); +% +% Inputs: +% fig - [integer] EEGLAB figure +% try_strings - [struct] "try" strings for menu callbacks. +% catch_strings - [struct] "catch" strings for menu callbacks. +% +% Create a plugin: +% For more information on how to create an EEGLAB plugin see the +% help message of eegplugin_besa() or visit http://www.sccn.ucsd.edu/eeglab/contrib.html +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Feb 2005 +% +% See also: eeglab(), readbstorm() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2003 Arnaud Delorme, Salk Institute, arno@salk.edu +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +function eegplugin_bstorm( fig, try_strings, catch_strings); + +if nargin < 3 + error('eegplugin_bstorm requires 3 arguments'); +end; + +% add bstrom folder to path +% ------------------------- +if ~exist('pop_bstorm') + p = which('eegplugin_bstorm'); + p = p(1:findstr(p,'eegplugin_bstorm.m')-1); + addpath([ p ] ); +end; + +% find import data menu +% --------------------- +filemenu = findobj(fig, 'label', 'File'); +neuromenu = findobj(filemenu, 'tag', 'import data'); + +% e_try = 'try, if exist(''h'') == 1, clear h; disp(''EEGLAB note: variable h cleared''); end;'; +% e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +% nocheck = e_try; +% e_catch = 'catch, errordlg2(lasterr, ''EEGLAB error''); LASTCOM= ''''; clear EEGTMP; end;'; +% storenewcall = '[ALLEEG EEG CURRENTSET LASTCOM] = pop_newset(ALLEEG, EEG, CURRENTSET); h(LASTCOM);'; +% e_newnonempty = [e_catch 'h(LASTCOM, EEG); if ~isempty(LASTCOM) & ~isempty(EEGTMP), EEG = EEGTMP;' storenewcall 'disp(''Done.''); end; clear EEGTMP; eeglab(''redraw'');']; +% uimenu(neuromenu, 'Tag', 'bstormCmd', 'Label', 'From BrainStorm DS folder', 'CallBack', [ nocheck '[EEGTMP LASTCOM]= pop_readbstorm;' e_newnonempty ], 'Separator', 'on'); + +% menu callbacks +% -------------- +combio = [ try_strings.no_check '[EEG LASTCOM] = pop_readbstorm;' catch_strings.new_and_hist ]; +uimenu(neuromenu, 'Tag', 'bstormCmd', 'Label', 'From BrainStorm DS folder', 'CallBack', combio, 'Separator', 'on'); + +return \ No newline at end of file diff --git a/eeglab/plugins/bstorm1.01/pop_readbstorm.m b/eeglab/plugins/bstorm1.01/pop_readbstorm.m new file mode 100644 index 0000000..db450af --- /dev/null +++ b/eeglab/plugins/bstorm1.01/pop_readbstorm.m @@ -0,0 +1,161 @@ +% pop_readbstorm() - load BrainStorm Data files (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_readbstorm; % a window pops up +% >> EEG = pop_readbstorm( dsfolder ); +% +% Inputs: +% datafile - A datafile within a DS folder containing BrainStorm datafiles +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), readbstorm() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: pop_readbstorm.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 +% + +function [EEG, command] = pop_readbstorm(datafile); + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + %cd('..\..\data\studies\div\T01\div-d1-f.ds'); + catch + end + [filename, filepath] = uigetfile('*_data_*.mat', 'Choose a datafile in a DS folder -- pop_readbstorm()'); + drawnow; + if filename == 0 return; end; + datafile = [filepath filename]; +end; + +% load data +% --------- +EEG = eeg_emptyset; +[study EEG.chanlocs data dsfolder] = readbstorm(datafile); + +EEG.filename = study.Name +EEG.filepath = dsfolder; +EEG.setname = 'BrainStorm data'; +EEG.nbchan = length(EEG.chanlocs); +EEG.srate = 1/mean(diff(data(1).Time)); +EEG.trials = length(data); +EEG.pnts = length(data(1).Time); +EEG.times = data(1).Time; +EEG.xmin = EEG.times(1); % huh?? +EEG.xmax = EEG.times(end); % huh?? +%Caution! CELL2MAT is overloaded in EEGLAB environment +fprintf('Importing data...(may take a while)') +EEG.data=zeros([size(data(1).F,1) size(data(1).F,2) EEG.trials]); +for i=1:EEG.trials + EEG.data(:,:,i)=data(i).F; +end +EEG.comments = study.Session; +EEG.ref = ['common']; + + +%EEG=pop_epoch(EEG, struct('epoc',1, 'type', '', 'latency', -EEG.xmin*EEG.srate+1)) + +% EEG = eeg_checkset(EEG, 'eventconsistency'); +% EEG = eeg_checkset(EEG, 'makeur'); + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_readbstorm(''%s'');', dsfolder); + +EEG.event.type='TimeZero'; +EEG.event.latency = 0; +EEG.epoch.event=[1]; +EEG.epoch.eventlatency={EEG.event(1).latency}; +EEG.epoch.eventtype={EEG.event(1).type}; + +EEG = eeg_checkset(EEG); + +return; + + + +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/eeglab/plugins/bstorm1.01/readbstorm.m b/eeglab/plugins/bstorm1.01/readbstorm.m new file mode 100644 index 0000000..8630ed5 --- /dev/null +++ b/eeglab/plugins/bstorm1.01/readbstorm.m @@ -0,0 +1,107 @@ +% readbstorm() - read BrainStorm datafiles +% +% Usage: +% >> [study channel data dsfolder] = readbstorm(datafile,device) +% +% Required Input: +% datafile = A folder (all data_*_[1..N] will be imported) +% OR a data file within a DS folder +% (only this file will be imported) +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% study = study info +% channel = sensor positions +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Feb 2005 +% +% See also: +% POP_READBSTORM, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readbstorm.m,v $ +% Revision 1.01 2005/02/01 00:07:38 knd +% now allows single data file importation + +function [Study,chanlocs,Data,dsfolder] = readbstorm(datafile,device) + +if nargin < 1 + help(mfilename); + return; +end; + +[dsfolder, filename]=fileparts(datafile) +studyname=strtok(filename,'_') +p=findstr(filename, '_') +database=filename(1:p(3)) +prev_dir=cd; +cd(dsfolder) +Study=load([studyname '_brainstormstudy']); + +fprintf('Importing channel location information') +Channel=getfield(load([studyname '_channel']), 'Channel'); +[chanlocs,channelflags]=bstormchannels2chanlocs( Channel ); + + +if exist(datafile,'file') + datafilename{1}=datafile; +elseif exist(datafile,'dir') + f=dir(sprintf('%s*.mat', database)); + f=strvcat({f.name}); + f=f(:,length(database)+1:end); + trials=str2double(strrep(cellstr(f), '.mat', '')); + trials=sort(trials(not(isnan(trials)))); + for i=1:length(trials) + datafilename{i}=sprintf('%s%d.mat', database , trials(i)); + end +end + +i=1; +%datafilename=sprintf('%s%d.mat', database , i); + +h = waitbar(0,'Importing Datafiles. Please wait...'); +for i=1:length(datafilename) + waitbar(i/length(datafilename),h) + fprintf('Importing %s\n', datafilename{i}) + d=load(datafilename{i}); + if exist('Data') + dfields=fieldnames(d); + Data(i)=Data(i-1); + for j=1:length(dfields) + Data(i)=setfield(Data(i), dfields{j}, getfield(d, dfields{j})); + end + else + Data=d; + end + %channelflag=channelflags & Data(i).ChannelFlag; + channelflag=channelflags; + if iscell(Data(i).F) + Data(i).F{1}=Data(i).F{1}(find(channelflag),:); + else + Data(i).F=Data(i).F(find(channelflag),:); + end +end +close(h) + +return diff --git a/eeglab/plugins/bstorm1.01/v1/pop_readbstorm.m b/eeglab/plugins/bstorm1.01/v1/pop_readbstorm.m new file mode 100644 index 0000000..3d752e1 --- /dev/null +++ b/eeglab/plugins/bstorm1.01/v1/pop_readbstorm.m @@ -0,0 +1,156 @@ +% pop_readbstorm() - load BrainStorm Data files (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_readbstorm; % a window pops up +% >> EEG = pop_readbstorm( dsfolder ); +% +% Inputs: +% datafile - A datafile within a DS folder containing BrainStorm datafiles +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), readbstorm() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: pop_readbstorm.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 +% + +function [EEG, command] = pop_readbstorm(datafile); + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + cd('D:\ndiaye\data\studies\'); + catch + end + [filename, filepath] = uigetfile('*_data_*.mat', 'Choose a datafile in a DS folder -- pop_readbstorm()'); + drawnow; + if filename == 0 return; end; + datafile = [filepath filename]; +end; + +% load data +% --------- +EEG = eeg_emptyset; +[study channel data dsfolder] = readbstorm(datafile); + +EEG.filename = study.Name +EEG.filepath = dsfolder; +EEG.setname = 'BrainStorm data'; +EEG.nbchan = length(channel); +EEG.srate = 1/mean(diff(data(1).Time)); +EEG.trials = length(data); +EEG.pnts = length(data(1).Time); +EEG.times = data(1).Time; +EEG.xmin = EEG.times(1); % huh?? +EEG.xmax = EEG.times(end); % huh?? +%Caution! CELL2MAT is overloaded in EEGLAB environment +fprintf('Importing data...(may take a while)') +EEG.data=zeros([size(data(1).F,1) size(data(1).F,2) EEG.trials]); +for i=1:EEG.trials + EEG.data(:,:,i)=data(i).F; +end +EEG.comments = study.Session; +EEG.ref = ['common']; + +fprintf('Importing channel location information') +for i=1:length(channel) + eloc(i).X=channel(i).Loc(1); + eloc(i).Y=channel(i).Loc(2); + eloc(i).Z=channel(i).Loc(3); + eloc(i).labels=channel(i).Name; +end +EEG.chanlocs=convertlocs(eloc, 'cart2all') + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_readbstorm(''%s'');', dsfolder); + +return; + + + +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/eeglab/plugins/bstorm1.01/v1/readbstorm.m b/eeglab/plugins/bstorm1.01/v1/readbstorm.m new file mode 100644 index 0000000..2f45468 --- /dev/null +++ b/eeglab/plugins/bstorm1.01/v1/readbstorm.m @@ -0,0 +1,106 @@ +% readbstorm() - read BrainStorm datafiles +% +% Usage: +% >> [study channel data dsfolder] = readbstorm(datafile,device) +% +% Required Input: +% datafile = Data file within a DS folder +% (all data_*_[1..N] will be imported) +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% study = study info +% channel = sensor positions +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READBSTORM, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [Study,Channel,Data,dsfolder] = readbstorm(datafile,device) + +if nargin < 1 + help(mfilename); + return; +end; + +[dsfolder, filename]=fileparts(datafile) +studyname=strtok(filename,'_') +p=findstr(filename, '_') +database=filename(1:p(3)) +prev_dir=cd; +cd(dsfolder) +Study=load([studyname '_brainstormstudy']); +Channel=getfield(load([studyname '_channel']), 'Channel'); + +%Importing Electrodes to EEGLAB format +channelflags=zeros(length(Channel),1); +if nargin <2 + DEVICES={'EEG', 'MEG', 'EEG+MEG', 'ALL'}; + [s,v] = listdlg('PromptString','Select a device:',... + 'SelectionMode','single',... + 'ListString',{'EEG', 'MEG', 'EEG+MEG'}); + if all(v) + switch(s) + case 1 + device={'EEG'} + case 2, device={'MEG'} + case 3, device = {'EEG', 'MEG'} + end + end +end +for i=1:length(device) + channelflags=channelflags + strcmp(device{i},{Channel.Type}'); +end +%channelflags(strmatch('EEG', {Channel.Type}))=1; +%channelflags(strmatch('MEG', {Channel.Type}))=1; + +Channel=Channel(find(channelflags)); + +i=1; +%datafilename=sprintf('%s%d.mat', database , i); +f=dir(sprintf('%s*.mat', database)); +f=strvcat({f.name}); +f=f(:,length(database)+1:end); +trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +trials=sort(trials); + +h = waitbar(0,'Importing Datafiles. Please wait...'); +for i=1:length(trials) + waitbar(i/length(trials),h) + datafilename=sprintf('%s%d.mat', database , trials(i)); + fprintf('Importing %s\n', datafilename) + Data(i)=load(datafilename); + %channelflag=channelflags & Data(i).ChannelFlag; + channelflag=channelflags; + Data(i).F=Data(i).F(find(channelflag),:); +end +close(h) + +return diff --git a/eeglab/plugins/ctf/ds2brainstorm.m b/eeglab/plugins/ctf/ds2brainstorm.m new file mode 100644 index 0000000..ec1254a --- /dev/null +++ b/eeglab/plugins/ctf/ds2brainstorm.m @@ -0,0 +1,977 @@ +function [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS); +%DS2BRAINSTORM +% [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] +% ... = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS); +% Reads CTF Systems Inc. Data and Resource file formats (4.1 MEG Data Format) +% +% This ALPHA version is optimized for small data sets only (e.g. averaged-trials data) +% +% INPUTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% DS_DIRECTORY: full path to the .ds directory containing the orginal data set +% +% VERBOSE = 1 : Toggle VERBOSE mode ON +% -> Activate screen display +% -> Save channel information in channel_file.txt +% -> Save coefficient information in coef_file.txt +% +% VERBOSE = 0 : Toggle VERBOSE mode OFF +% +%---> The rest of the input parameters are optionnal (more specific to data block extraction) +% +% READRES = 1: Read the original .res4 file and writes out a file called **_res4.mat in the .ds folder, which is a shortened version of the CTF resources file +% READRES = 0: Do not read the original .res4 file assuming it has been read previously. Read the **_res4.mat instead +% Set READRES to 0 when you want to extract another block of data after you have already read one block with READRES = 1. +% +% If READRES is left blank, the whole data are read - ATTENTION when data set is large - possible 'out of memory' issues +% +% If the optional fields below are left blank, ds2brainstorm only reads the res4 file and generates a *_res4.mat file in the current .ds folder +% with all useful information regarding EEG, MEG channels etc. for subsequent data extraction. +% +% CHANNELS: the indices of the channels to be extracted as in IEEGSENS, IMEGSENS or IREFSENS +% If you don't know what are the indices of these channels, run ds2brainstorm with READRES = 1 first. +% +% TIME: the time window to be extracted in seconds within a trial; ie a subset of Time, a vector saved in **_res4.mat (see above) +% +% NO_TRIALS: a vector containing the number(s) of the trial(s) to be extracted. +% +% Example; ds2brainstorm('tipouic.ds',1,0,[10:30],[-.5 3],2) +% .. extracts in VERBOSE mode from tipouic.ds, assuming tipouic_res4.mat was already created during a previous call to ds2brainstorm with READRES = 1 +% channels 10 to 30 (could be MEG or other -> check IEEGSENS and IMEGSENS first), between -0.5sec and 3sec, in trial 2. +% +% % +% OUTPUTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% CHANNEL - MEG,EEG, REFERENCE and OTHER channel information +% CHANNEL is a cell array of structures following the BrainStorm data format. +% F - Data Matrix: One sensor per row; one time sample per column +% IMEGSENS - Indices of the MEG data rows in F +% IEEGSENS - Indices of the EEG data rows in F +% IOTHERSENS - Indices of the OTHER data rows (not including reference coils) in F +% IREFSENS - Indices of the REFERENCE data rows in F +% GRAD_ORDER_NO - Order of the gradient correction to be taken into account in the forward model only +% NO_TRIALS - Number of trials in the .ds folder. +% FILTER - An array of structures; each structure containing information related to each filter +% TIME - A vector containing the time instants at every data sample +% RUNTITLE - A character array labelling the current run. +% +% Please refer to CTF Systems Inc. Technical Note #1 for details on DataSet file formats + +%-- Sylvain Baillet, Ph.D. / Denis Swchartz, Ph.D. +% Cognitive Neuroscience & Brain Imaging Laboratory - CNRS - Paris France +% MEG Center - Hopital de la Salpetriere - Paris - France. + +%-- $RCSfile: ds2brainstorm.m,v $ -- $Revision: 7 $ -- $Date: 11/28/01 8:20a $ +%-- Signal and Image Processing Institute +%-- University of Southern Califonia +%-- Los Angeles - USA +%-> with contributions from Line Garnero, Ph.D. and Antoine Ducorps +% MEG Center +% & +% Cognitive Neuroscience & Brain Imaging Laboratory - CNRS +% La Salpetriere Hospital, Paris, France + +% 14/08/03 - KND (kari n'diaye): Updated to include Virtual Channeln, lines 486-544 +% 11/28/00 - SB: Updated to read the 3rd-roder gradient information +% 03/09/01 - SB: Data block extraction +% 15/11/01 - SB: Extraction of the ADC Input channels in iothersens, combined with the STIM channel +% 19/11/01 - SB: Save iothersens indices in the _res4.mat file +%********************************************* +% +% Check input arguments +% + +if nargin == 2 + READRES = 1; +elseif nargin==5 % No Marker file and marker range are defined + MARKER_FILE = 0; + MARKER_RANGE = []; +elseif nargin==3 + MARKER_FILE = 0; + MARKER_RANGE = []; + CHANNELS = []; + TIME = []; + NO_TRIALS = []; +elseif nargin==1 + VERBOSE=0; + READRES = 1; + MARKER_FILE = 0; + MARKER_RANGE = []; + CHANNELS = []; + TIME = []; + NO_TRIALS = []; +end + +%% Checking files +current_dir=cd; +cd(ds_directory) +[path,rootname] = fileparts(ds_directory); +meg4file = [rootname,'.meg4']; +rec4file = [rootname,'.res4']; +res4_mat = [rootname,'_res4.mat']; + +if ~exist(rec4file,'file') | ~exist(meg4file,'file') + errordlg([rec4file ' or ' meg4file ' missing']) + return +end + +if ~exist(res4_mat,'file') + % Force the reading the original .res4 file but skip the reading of the file + READRES = 2; +end + +if VERBOSE + disp(['Working in...',ds_directory ]) + drawnow +end + + +%********************************************* + +if READRES == 1 | READRES == 2 % Read the .res4 file + + %% Define constants + MAX_COILS = 8; + MAX_BALANCING = 50; + SENSOR_LABEL = 31; + MAX_AVERAGE_BINS = 8; + + %***** nfSetUp **** Data Structure + gSetUp = struct('no_samples',[],'no_channels',[],'sample_rate',[],... + 'epoch_time',[],'no_trials',[],'preTrigPts',[],'no_trials_done',[],'no_trials_display',[],... + 'save_trials',[],'primaryTrigger',[],'secondaryTrigger',[],'triggerPolarityMask',[],... + 'trigger_mode',[],'accept_reject_Flag',[],'run_time_display',[],'zero_Head_Flag',[],... + 'artifact_mode',[]); + + nfSetUp = struct('nf_run_name','','nf_run_title','','nf_instruments','','nf_collectdescriptor','',... + 'nf_subject_id','','nf_operator','','nf_sensorFileName',''); + + GenRes4 = struct('appName','','dataOrigin','','dataDescription','',... + 'no_trials_avgd',[],'data_time',[],'data_date',[],'gSetUp',gSetUp,'nfSetUp',nfSetUp,'rdlen',[]); + + %********************************************* + + + %% Reading Resources------------------------------------------------------------------------ + [rec,message] = fopen(rec4file,'rb','s'); % Big-endian byte ordering + if rec < 0 + errordlg(message) + return + end + + % Read HEADER + header = fread(rec,8,'char')'; + if VERBOSE + disp([char(header), ' file format']) + drawnow + end + + + % Read nfSetUp + GenRes4.appName = char(fread(rec,256,'char')'); + GenRes4.dataOrigin = char(fread(rec,256,'char')'); + GenRes4.dataDescription = char(fread(rec,256,'char')'); + + GenRes4.no_trials_avgd = (fread(rec,1,'int16')'); + GenRes4.data_time = char(fread(rec,255,'char')'); + GenRes4.data_date = char(fread(rec,255,'char')'); + + gSetUp.no_samples = (fread(rec,1,'int32')'); + gSetUp.no_channels = (fread(rec,1,'int16')'); + + fseek(rec,ceil(ftell(rec)/8)*8,-1); + gSetUp.sample_rate = (fread(rec,1,'double')'); + fseek(rec,ceil(ftell(rec)/8)*8,-1); + gSetUp.epoch_time = (fread(rec,1,'double')'); + gSetUp.no_trials = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.preTrigPts = (fread(rec,1,'int32')'); + gSetUp.no_trials_done = (fread(rec,1,'int16')'); + gSetUp.no_trials_display = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.save_trials = (fread(rec,1,'int32')'); + gSetUp.primaryTrigger = char(fread(rec,1,'uchar')'); + gSetUp.secondaryTrigger = char(fread(rec,MAX_AVERAGE_BINS,'uchar')'); + gSetUp.triggerPolarityMask = char(fread(rec,1,'uchar')'); + + gSetUp.trigger_mode = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.accept_reject_Flag = (fread(rec,1,'int32')'); + gSetUp.run_time_display = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.zero_Head_Flag = (fread(rec,1,'int32')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.artifact_mode = (fread(rec,1,'int32')'); + gSetUp.padding = (fread(rec,1,'int32')'); + + + nfSetUp.nf_run_name = char(fread(rec,32,'char')'); + nfSetUp.nf_run_title = char(fread(rec,256,'char')'); + + RunTitle = nfSetUp.nf_run_title ; + + nfSetUp.nf_instruments = char(fread(rec,32,'char')'); + nfSetUp.nf_collect_descriptor = char(fread(rec,32,'char')'); + nfSetUp.nf_subject_id = char(fread(rec,32,'char')'); + nfSetUp.nf_operator = char(fread(rec,32,'char')'); + % DBG: The following line generates a warning + warnstate=warning; + warning off + nfSetUp.nf_sensorFileName = char(fread(rec,60,'char')'); + warning(warnstate) + clear warnstate + + fseek(rec,ceil(ftell(rec)/4)*4,-1); + nfSetUp.rdlen = fread(rec,1,'int32')'; + + GenRes4.gSetUp = gSetUp; + GenRes4.nfSetUp = nfSetUp; + + %---------------------------------------------------------------------------------------- + + if VERBOSE + fprintf('----------------------------------- Header information ---------------------------\n') + fprintf('Collected %s starting at %s\n', GenRes4.data_date, GenRes4.data_time) + fprintf('Run Name: %s\n', nfSetUp.nf_run_name) + fprintf('Run Titl: %s\n', nfSetUp.nf_run_title) + fprintf('Col Desc: %s\n', nfSetUp.nf_collect_descriptor) + fprintf('Run Desc: %s\n', GenRes4.dataDescription) + fprintf('Operator: %s\n', nfSetUp.nf_operator) + fprintf('Subject : %s\n', nfSetUp.nf_subject_id) + fprintf('Channels: %d\n',gSetUp.no_channels) + fprintf('Samples : %d per trial\n', gSetUp.no_samples) + fprintf('Rate : %g samples/sec\n', gSetUp.sample_rate) + fprintf('Trials : %d (average of %d)\n', gSetUp.no_trials, GenRes4.no_trials_avgd) + fprintf('Duration: %g seconds/trial\n', gSetUp.epoch_time/gSetUp.no_trials) + fprintf('Pre-trig: %g samples\n', gSetUp.preTrigPts) + fprintf('Sensor file name : %s\n', nfSetUp.nf_sensorFileName) + ON_OFF = {'Off','On'}; + fprintf('Head zeroing: %s\n', ON_OFF{gSetUp.zero_Head_Flag+1}) + fprintf('----------------------------------- End Header information -----------------------\n') + end + + + %------------------------------------------------------------------------------- + + %----------------------------------READ FILTERS--------------------------------- + + fseek(rec,1844,-1); + + % Run Description + rundescript = char(fread(rec,nfSetUp.rdlen,'char')); + if VERBOSE + fprintf('\nRun Description: %s\n', rundescript ); + drawnow + end + + classType = {'CLASSERROR','BUTTERWORTH'}; + filtType = {'TYPERROR','LOWPASS','HIGHPASS','NOTCH'}; + + + % Number of filters + no_filters = fread(rec,1,'int16'); + if VERBOSE + fprintf('\n----------------------------------- Filter information ---------------------------\n') + fprintf('Number of filters: %d\n', no_filters) + drawnow + end + + % JCM fixes 10/26/00, each of these should be looped through, not read in bulk + % old + if(0) + filter.freq = fread(rec,no_filters,'double'); + filter.fClass = classType{fread(rec,no_filters,'int32')+1}; + filter.fType = filtType{fread(rec,no_filters,'int32')+1}; + filter.numParam = fread(rec,no_filters,'int16'); + + filter.params = []; + for fi = 1:no_filters + for p = 1: filter(fi).numParam + filter(fi).params= fread(rec,filter(fi).numParam,'double'); + end + end + else % new + [filter(1:no_filters)] = struct('freq',[],'fClass',[],'fType',[],'numParam',[],'params',[]); + for fi = 1:no_filters, + filter(fi).freq = fread(rec,1,'double'); + filter(fi).fClass = classType{fread(rec,1,'int32')+1}; + filter(fi).fType = filtType{fread(rec,1,'int32')+1}; + filter(fi).numParam = fread(rec,1,'int16'); + filter(fi).params= fread(rec,filter(fi).numParam,'double'); + end + end + + if VERBOSE + for fi = 1:no_filters + fprintf('Filter - %d\n',fi) + fprintf('->Frequency: \t%g\n',filter(fi).freq) + fprintf('->Class: \t%s\n',filter(fi).fClass) + fprintf('->Type: \t%s\n',filter(fi).fType) + fprintf('->Number of parameters: \t%d\n',filter(fi).numParam) + if ~isempty(filter(fi).params) + fprintf('->Parameter Value(s): \t%g\n',filter(fi).params) + end + end + + fprintf('\n------------------------------- End Filter Information ---------------------------\n') + + fprintf('\n------------------------------- Reading Channel Information.....------------------------------\n') + drawnow + end + + % Channel Names + for chan = 1:gSetUp.no_channels + channel_name{chan} = fread(rec,32,'char')'; + tmp = channel_name{chan}; + tmp(tmp>127) = 0; + tmp(tmp<0) = 0; + channel_name{chan} = char(strtok(tmp,char(0))); + end + + % Sensor Resources + CoilType = {'CIRCULAR','SQUARE','???'}; + + for chan = 1:gSetUp.no_channels + oldtell = ftell(rec); + SensorRes(chan).sensorTypeIndex = fread(rec,1,'int16'); + SensorRes(chan).originalRunNum = fread(rec,1,'int16'); + + id = fread(rec,1,'int32')+1; + + if isempty(id) + id = -1; + end + + if id > 3 | id <0 + id = 3; + end + + SensorRes(chan).coilShape = CoilType{id}; + + SensorRes(chan).properGain = fread(rec,1,'double'); + SensorRes(chan).qGain = fread(rec,1,'double'); + SensorRes(chan).ioGain= fread(rec,1,'double'); + SensorRes(chan).ioOffset = fread(rec,1,'double'); + SensorRes(chan).numCoils = fread(rec,1,'int16'); + SensorRes(chan).grad_order_no = fread(rec,1,'int16'); + + padding = fread(rec,1,'int32'); + + for coil = 1:MAX_COILS + SensorRes(chan).coilTbl(coil).position.x = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.y = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.z = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.junk = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.x = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.y = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.z = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.junk = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).numturns = fread(rec,1,'int16'); + padding = fread(rec,1,'int32'); + padding = fread(rec,1,'int16'); + SensorRes(chan).coilTbl(coil).area = fread(rec,1,'double'); + end + + for coil = 1:MAX_COILS + SensorRes(chan).HdcoilTbl(coil).position.x = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.y = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.z = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.junk = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.x = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.y = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.z = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.junk = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).numturns = fread(rec,1,'int16'); + padding = fread(rec,1,'int32'); + padding = fread(rec,1,'int16'); + SensorRes(chan).HdcoilTbl(coil).area = fread(rec,1,'double'); + end + + end + + if VERBOSE + SensorNames ={'Ref Magnetometer','Ref Gradiometer' ,'' , '' , '' ,'MEG Sensor','' , '', '','EEG Sensor','ADC Input','Stimulation input',''}; % CHEAT - added the 13th '' ofor testing purposes + % SensorNames ={'Ref Magnetometer','Ref Gradiometer' ,'' , '' , '' ,'MEG Sensor','' , '', '','EEG Sensor','ADC Input','Stimulation input'); %OLD VERSION + + [channel_file, message] = fopen('channel_file.txt','wt+'); + if channel_file < 0 + errordlg(['Aborted - You need to the permission to write in ',ds_directory]); + return + end + for chan = 1:gSetUp.no_channels + fprintf(channel_file,'%s: sensor type Index %d (%s), %d coil(s), shape %s,Gains: proper %g q %g io %g, offset %g, gradient order %d\n',... + channel_name{chan}, SensorRes(chan).sensorTypeIndex, SensorNames{SensorRes(chan).sensorTypeIndex+1}, SensorRes(chan).numCoils, SensorRes(chan).coilShape,... + SensorRes(chan).properGain , SensorRes(chan).qGain , SensorRes(chan).ioGain, SensorRes(chan).ioOffset,SensorRes(chan).grad_order_no ) ; + + if SensorRes(chan).numCoils > 0 + fprintf(channel_file,'Dw:'); + PrintCoilPos(channel_file,SensorRes(chan).coilTbl, SensorRes(chan).numCoils ); + fprintf(channel_file,'Hd:'); + PrintCoilPos(channel_file,SensorRes(chan).HdcoilTbl, SensorRes(chan).numCoils ); + end + end + + fprintf('Channel Information written to channel_file.txt\n'); + + fprintf('\n------------------------------- End Channel Information --------------------------\n') + end + + disp('-------------------Converting Channel Information.....----------------------------') + + + nchan= length(channel_name); % Number of channels + + % Explode data according to channel type + SensorNames ={'Ref Magnetometer','Ref Gradiometer' ,'' , '' , '' ,'MEG Sensor','' , '', '','EEG Sensor','ADC Input','Stimulation input'}; + imegsens = find([SensorRes.sensorTypeIndex] == 5); % Indices of MEG sensors + ieegsens = find([SensorRes.sensorTypeIndex] == 9); % Indices of EEG sensors + iothersens = [find([SensorRes.sensorTypeIndex] == 11),find([SensorRes.sensorTypeIndex] == 10)]; % Indices of OTHER sensors ('Stimulation input' and 'ADC') + irefsens = find([SensorRes.sensorTypeIndex] == 0); % Reference Channels + irefsens = [irefsens,find([SensorRes.sensorTypeIndex] == 1)]; % Reference Channels + + + ieeg = 0; imeg = 0; + iother = 0; + iother2 = 0; + eegID = []; + otherID = []; + other2ID = []; + megID = []; + + iref = 0; + refID = []; + + chaneeg = [];% Index of EEG channels + chanmeg = [];chanother = []; + SensorNames ={'Ref Magnetometer','Ref Gradiometer' ,'' , '' , '' ,'MEG Sensor','' , '', '','EEG Sensor','ADC Input','Stimulation input',''}; % Added a 13th channel type, don't know why + + [Channel(1:nchan)] = deal(struct('Loc',[],'Orient',[],'Comment',[],'Weight',[],'Type',[],'RefChannel',[],'Gcoef',[],'Name','')); + + for chan = 1:nchan + switch SensorRes(chan).sensorTypeIndex + case {0,1} %'References coils + iref = iref+1; + MAX_COILS = 2; % Take only into account the 2 first coils for every sensor + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100; % In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + tmp = [SensorRes(chan).HdcoilTbl(:).orient]; + tmpx = [tmp(1:MAX_COILS).x]; + tmpy = [tmp(1:MAX_COILS).y]; + tmpz = [tmp(1:MAX_COILS).z]; + + Channel(chan).Orient = ... + [tmpx;tmpy;tmpz]; + + + % Reorient along the outward pointing normal + loc = Channel(chan).Loc'; + ps1=sum((loc(1,:).*Channel(chan).Orient(:,1)')')'; + ps2=sum((loc(2,:).*Channel(chan).Orient(:,2)')')'; + Channel(chan).Orient(:,1) = (sign(ps1)*ones(1,3).*Channel(chan).Orient(:,1)')'; + Channel(chan).Orient(:,2) = (sign(ps2)*ones(1,3).*Channel(chan).Orient(:,2)')'; + + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + if isempty(deblank(Channel(chan).Type)) + Channel(chan).Type = 'REF'; + end + + chanmeg = [chanmeg,chan]; + refID(iref) = chan; + Channel(chan).Weight = [1 -1] ; + + case 5 % MEG (including Virtual !) + + if SensorRes(chan).coilTbl(1).area > 0% Not a virtual one... I guess ! + + imeg = imeg+1; + MAX_COILS = 2; % Take only into account the 2 first coils for every sensor + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100; % In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + tmp = [SensorRes(chan).HdcoilTbl(:).orient]; + tmpx = [tmp(1:MAX_COILS).x]; + tmpy = [tmp(1:MAX_COILS).y]; + tmpz = [tmp(1:MAX_COILS).z]; + + Channel(chan).Orient = ... + [tmpx;tmpy;tmpz]; + + % Reorient along the outward pointing normal + loc = Channel(chan).Loc'; + ps1=sum((loc(1,:).*Channel(chan).Orient(:,1)')')'; + ps2=sum((loc(2,:).*Channel(chan).Orient(:,2)')')'; + Channel(chan).Orient(:,1) = (sign(ps1)*ones(1,3).*Channel(chan).Orient(:,1)')'; + Channel(chan).Orient(:,2) = (sign(ps2)*ones(1,3).*Channel(chan).Orient(:,2)')'; + + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Type = 'MEG';%SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + + chanmeg = [chanmeg,chan]; + megID(imeg) = chan; + Channel(chan).Weight = [1 -1] ; + Channel(chan).Name = char(strtok(channel_name{chan},'-')); + else + %KND : To detect Virtual ones: + % Head Coil Position = (0,0,0) + % ie. SensorRes(chanNumber).HdcoilTbl(1).position.x=0 + % SensorRes(chanNumber).HdcoilTbl(1).position.y=0 + % SensorRes(chanNumber).HdcoilTbl(1).position.z=0 + % could also use : + % SensorRes(chan).coilTbl(coil).area = 0; + % + % disp([num2str(chan) ' is VIRTUAL']); + + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Type = 'VirtualMEG'; + Channel(chan).Weight = [] ; + Channel(chan).Name = char(strtok(channel_name{chan},'-')); + iother = iother+1; + chanother = [chanother,chan]; + otherID(iother) = chan; + %remove it from imegsens + imegsens=setdiff(imegsens, chan); + end + + case 9 % EEG + ieeg = ieeg + 1; + MAX_COILS = 2; % Take only into account the 2 first coils for every sensor + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100;% In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + Channel(chan).Orient = []; + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + + Channel(chan).Type = 'EEG';%SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + Channel(chan).Name = char(strtok(channel_name{chan},'-'));%int2str(ieeg) ; + chaneeg = [chaneeg,chan]; + eegID(ieeg) = chan; + + case 11 % STIM + iother = iother+1; + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + if isempty(deblank(Channel(chan).Type )) + Channel(chan).Type = 'STIM'; + end + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + chanother = [chanother,chan]; + otherID(iother) = chan; + + otherwise + % KND for MicroMed EEG dataHandled... + % replaced line: iother2 = iother2+1; + % by : + iother = iother+1; + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + if isempty(deblank(Channel(chan).Type )) + Channel(chan).Type = 'OTHER'; + + end + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + chanother = [chanother,chan]; + other2ID(iother) = chan; + + end + end + + + disp('----------------------Channel Information Updated---------------------------------') + + %------------------------------------------------------------------------------- + + %----------------------------------READ Coefficients--------------------------------- + + % Number of coefficient records + nrec = fread(rec,1,'int16'); + + + % ----------------------------- Read Coefficient Information + + hexadef = {'00000000','47314252','47324252','47334252','47324f49','47334f49'}; + strdef = {'NOGRAD','G1BR','G2BR','G3BR','G2OI','G3OI'}; + + CoefInfo = cell(length(channel_name),length(strdef)-1); + + %SensorCoefResRec + if VERBOSE + h = waitbar(0,'Reading Coefficient Information...'); + end + + for k = 1:nrec + SensorCoefResRec(k).sensorName = char(fread(rec,32,'char')'); + SensorCoefResRec(k).coefType = (fread(rec,1,'bit32')); + padding = fread(rec,1,'int32'); + SensorCoefResRec(k).CoefResRec.num_of_coefs = fread(rec,1,'int16'); + + SensorCoefResRec(k).CoefResRec.sensor_list = char(fread(rec,[SENSOR_LABEL,MAX_BALANCING],'uchar')'); + SensorCoefResRec(k).CoefResRec.coefs_list = fread(rec,MAX_BALANCING,'double'); + + cchannel = strmatch( deblank(SensorCoefResRec(k).sensorName),(channel_name)); + CoefType = find(hex2dec(hexadef)==(SensorCoefResRec(k).coefType)); + + if CoefType > 0 + + CoefInfo{cchannel,CoefType-1}.num_of_coefs = SensorCoefResRec(k).CoefResRec.num_of_coefs; + + for i=1:CoefInfo{cchannel,CoefType-1}.num_of_coefs + CoefInfo{cchannel,CoefType-1}.sensor_list(i) = irefsens(strmatch(strtok(SensorCoefResRec(k).CoefResRec.sensor_list(i,:),char(0)),channel_name(irefsens))); + CoefInfo{cchannel,CoefType-1}.coefs(i) = SensorCoefResRec(k).CoefResRec.coefs_list(i); + end + end + if VERBOSE + waitbar(k/nrec) + end + + end + + if VERBOSE + delete(h) + end + + + % Channel Gains + gain_chan = zeros(size(channel_name,1),1); + gain_chan(imegsens) = ([SensorRes(imegsens).properGain]'.*[SensorRes(imegsens).qGain]'); + gain_chan(irefsens) = ([SensorRes(irefsens).properGain]'.*[SensorRes(irefsens).qGain]'); + % gain_chan(ieegsens) = 1./([SensorRes(ieegsens).qGain]'*1e-6); + gain_chan(ieegsens) = 1./([SensorRes(ieegsens).qGain]'); + gain_chan(iothersens) = ([SensorRes(iothersens).qGain]'); % Don't know exactly which gain to apply here + + if VERBOSE + fprintf('\n--------------------------- Coefficient Information ------------------------------\n') + fprintf('Number of coefficient records = %d \n', nrec); + [coef_file, message] = fopen('coef_file.txt','wt+'); + if coef_file < 0 + errordlg(message) + return + end + + fprintf(coef_file,'Number of coefficient records = %d \n', nrec); + + for k = 1:nrec + coefType = dec2hex(SensorCoefResRec(k).coefType); + coefType = strdef{hex2dec(hexadef)==hex2dec(coefType)}; + + fprintf(coef_file,'Channel %s type %s, ',SensorCoefResRec(k).sensorName, coefType); + + num_of_coefs = SensorCoefResRec(k).CoefResRec.num_of_coefs; + fprintf(coef_file,'number = %d:\n', num_of_coefs); + if 0 + for j=1:num_of_coefs + fprintf(coef_file,' %s ', SensorCoefResRec(k).CoefResRec.sensor_list{j}); + fprintf(coef_file,' %g ',SensorCoefResRec(k).CoefResRec.coefs_list(j)); + end + fprintf(coef_file,'\n'); + end + end + + fprintf('Coefficient Information saved in coef_file.txt\n') + + fprintf('\n----------------------- End Coefficient Information ------------------------------\n') + + end + + grad_order_no = [SensorRes(:).grad_order_no]; + + + if length(imegsens) + % Channel(imegsens(1)).grad_order_no = grad_order_no; + % Channel(imegsens(1)).CoefInfo = CoefInfo; + % Channel(imegsens(1)).gain_chan = gain_chan; + Channel(imegsens(1)).imegsens = imegsens; + Channel(imegsens(1)).ieegsens = imegsens; + Channel(imegsens(1)).irefsens = irefsens; + Channel(imegsens(1)).RefChannel = Channel; % Store all channel information in that field: facilitates the set-up for the forward computation + + % Calculus of the matrix for nth-order gradient correction + % Coefficients for unused reference channels are weigthed by zeros in + % the correction matrix. + + Gcoef = zeros(length(imegsens),length(min(irefsens):max(irefsens))); + + for k = 1:length(imegsens) + + % Reference coils for channel k + if grad_order_no(imegsens(k)) == 0 + %Data is saved as RAW + %Save 3rd order gradient sensor-list for subsequent correction if requested later by the user + [refs] = (CoefInfo{imegsens(k),3}.sensor_list); + Gcoef(k,refs-min(irefsens)+1) = CoefInfo{imegsens(k),3}.coefs ... + .* gain_chan(refs)'/gain_chan(imegsens(k)); + else + % PB with virtual channel + [refs] = (CoefInfo{imegsens(k),grad_order_no(imegsens(k))}.sensor_list); + %KND changed a transposition before "/" + Gcoef(k,refs-min(irefsens)+1) = CoefInfo{imegsens(k),grad_order_no(imegsens(k))}.coefs ... + .* gain_chan(refs)/gain_chan(imegsens(k)); + end + + end + + Channel(imegsens(1)).Gcoef = Gcoef; + end + Time = linspace(-GenRes4.gSetUp.preTrigPts/GenRes4.gSetUp.sample_rate,GenRes4.gSetUp.epoch_time/GenRes4.gSetUp.no_trials-GenRes4.gSetUp.preTrigPts/GenRes4.gSetUp.sample_rate,GenRes4.gSetUp.no_samples); + + save_sensor_locs(Channel) + + if VERBOSE + disp(['Sensor locations can be visualized with the MRI Tool by loading the file: sensor_result.mat']) + end + drawnow + + fclose('all'); + + % Create the BrainStorm res4 file for subsequent fast access to the data file + no_channels = length(Channel); + gain_chan(ieegsens)=1./gain_chan(ieegsens); + save(res4_mat,'gSetUp','meg4file','ieegsens','irefsens', 'iothersens', 'imegsens','Time','no_channels','gain_chan','channel_name','Channel','grad_order_no','filter','RunTitle'); + + if READRES == 2 + READRES = 0; %read the res4.mat file just created and reads the data by block. + if nargin == 2 % Read the whole thing + CHANNELS = [imegsens,ieegsens]; + TIME = Time; + NO_TRIALS = 1:gSetUp.no_trials; + end + % [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS); + % + % return + end + + +else % READRES == 0 + load(res4_mat); + +end + + +%--------------------------- Readind DATA FILE ------------------------------ + +if VERBOSE + fprintf('\n--------------------------- Reading Data -----------------------------------------\n') +end + +if nargin <= 2 %| (nargin > 2 & READRES == 0) % Reads the whole block of data + + no_trials = gSetUp.no_trials; + + [meg,message] = fopen(meg4file,'rb','s'); % Big-endian byte ordering + if meg < 0 + errordlg(message) + return + end + + F = cell(gSetUp.no_trials,1); % allocate space for the data array % ASSUME SINGLE TRIAL FOR THE MOMENT - ie enough memory space + header = char(fread(meg,8,'char')'); + + nref=length(irefsens); + + for trial = 1:gSetUp.no_trials + + if VERBOSE + fprintf('Reading Trial %d/%d\n',trial,gSetUp.no_trials); + end + + F{trial} = zeros(gSetUp.no_channels,gSetUp.no_samples); + F{trial} = fread(meg,[gSetUp.no_samples gSetUp.no_channels],'int32')'; + + if VERBOSE + fprintf('-> Done %d/%d\n',trial,gSetUp.no_trials) + end + % IMPORTANT NOTICE : Applying Gradient Correction + % Data are saved in a given nth-order gradient correction + % Applying gradient correction si only needed for forward model computation + % or if it is desired to reverse to lower-order gradient correction (see importdata.m for instance). + + % Apply channel gains + % F{trial}(ieegsens,:) = diag( gain_chan(ieegsens))*F{trial}(ieegsens,:) ; %To get Microvolts + F{trial}(ieegsens,:) = diag(1./gain_chan(ieegsens))*F{trial}(ieegsens,:) ; %To get Microvolts->already inverted when saved _res4.mat + F{trial}(imegsens,:) = diag(1./gain_chan(imegsens))*F{trial}(imegsens,:) ; + F{trial}(irefsens,:) = diag(1./gain_chan(irefsens))*F{trial}(irefsens,:) ; + F{trial}(iothersens,:) = diag(1./gain_chan(iothersens))*F{trial}(iothersens,:) ; + + end + + fclose('all'); + + %------------------------------------------------------------------------------------------------------------------------------------ + +else % Reads sub-block of data + + %ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS); + if nargin <= 3 % CHANNELS not defined + CHANNELS=[1:gSetUp.no_channels]; + end + if nargin <= 4 % TIME not defined + TIME=[-gSetUp.preTrigPts*1/gSetUp.sample_rate (gSetUp.no_samples-gSetUp.preTrigPts)*1/gSetUp.sample_rate]; + end + if nargin <= 5 % NO_TRIALS not defined + no_trials = [1:gSetUp.no_trials]; + else + no_trials = [NO_TRIALS]; + end + + fclose('all'); + [meg,message] = fopen(meg4file,'rb','s'); % Big-endian byte ordering + if meg < 0 + errordlg(message) + return + end + + % no_samples = round((TIME(end)-TIME(1))*gSetUp.sample_rate) +1; % Number of time samples in a trial + + F = cell(length(no_trials),1); % allocate space for the data array % ASSUME SINGLE TRIAL FOR THE MOMENT - ie enough memory space + % Adjust time range to the closest time samples; + + if isempty(TIME) + return + end + % [m,t1] = min(abs(TIME(1)-Time)); + % [m,t2] = min(abs(TIME(end)-Time)); + % + % TIME(1) = Time(t1); + % TIME(end) = Time(t2); + % + header = char(fread(meg,8,'char')'); + + implicit.sample_rate = 1/(Time(2) - Time(1)); % i.e. the one used in the data file given the time begin_time end period. + % Time = (Time(1):1/implicit.sample_rate:Time(end)); + t_in = round((TIME(1)-Time(1))*implicit.sample_rate) +1; % Sample time offset since the beginning of the trial: beginning of the time window TIME + %t_out = round((TIME(end)-Time(1))*implicit.sample_rate)+1; % Sample time offset since the beginning of the trial: end of the time window TIME + + no_samples = round((TIME(end)-TIME(1))*implicit.sample_rate)+1; % Number of time samples to extract + t_out = t_in + no_samples - 1; + + %no_samples = t_out-t_in+1; + + + diff_trials = diff(no_trials)-1; % Number of trials between each selected trials (useful when skipping a few trials) + + ByteSizeOfTrial= no_channels*gSetUp.no_samples*4; % Byte size of a single trial of data (Int32 coding) + + samples_skip = gSetUp.no_samples-no_samples; %Number of time samples to skip per channel + + LastChannelSkip = (no_channels - max(CHANNELS))*gSetUp.no_samples*4; % Skip data from last channels + + channels = [min(CHANNELS):max(CHANNELS)]; % Block of channels to extract. + + FirstChannelSkip = (min(CHANNELS)-1)*gSetUp.no_samples*4; % Skip data from first channels + no_channels = length(channels); + + itrial = 0; + + for trial = no_trials + itrial = itrial+1; + if VERBOSE + fprintf('Reading Trial %d / %d\n',itrial,length(no_trials)); + end + + F{itrial} = zeros(no_channels,no_samples); + + if trial == no_trials(1) % Read first trial + fseek(meg,(trial-1)*ByteSizeOfTrial + FirstChannelSkip + (t_in-1)*4 ,0); + else % just shift from the size of a trial + fseek(meg,LastChannelSkip + diff_trials(itrial-1)*ByteSizeOfTrial + FirstChannelSkip ,0); + end + + F{itrial} = fread(meg,[no_samples no_channels],[num2str(no_samples),'*int32=>int32'], samples_skip*4)'; + F{itrial} = F{itrial}(CHANNELS-min(CHANNELS)+1,:); + + % IMPORTANT NOTICE : Applying Gradient Correction + % Data are saved in a given nth-order gradient correction + % Applying gradient correction is only needed for forward model computation + % or if it is desired to reverse to lower-order gradient correction (see importdata.m for instance). + + % Apply channel gains + F{itrial} = diag(1./gain_chan(CHANNELS))*double(F{itrial}); + + + if VERBOSE + fprintf('-> Done %d/%d\n',itrial,length(no_trials)) + end + + end + + fclose('all'); + + %Time = TIME(1):1/gSetUp.sample_rate:TIME(end); + +end +cd(current_dir) + + +function PrintCoilPos(channel_file, CoilRec_ext,nCoils) ; + +% Subroutine to DS2BRAINSTORM +% Formatted output of channel locations in a file (channel_file is the pointer to this file) +% as defined in theCoilRec_ext structure, according to the number of coils nCoils for every gradiometer + +for coil=1:nCoils + fprintf(channel_file,'Coil %d:', coil); + fprintf(channel_file,' pX %g,', CoilRec_ext(coil).position.x); + fprintf(channel_file,' pY %g,', CoilRec_ext(coil).position.y); + fprintf(channel_file,' pZ %g ', CoilRec_ext(coil).position.z); + fprintf(channel_file,'-'); + fprintf(channel_file,' oX %g,', CoilRec_ext(coil).orient.x); + fprintf(channel_file,' oY %g,', CoilRec_ext(coil).orient.y); + fprintf(channel_file,' oZ %g ', CoilRec_ext(coil).orient.z); + fprintf(channel_file,'-'); + fprintf(channel_file,' turns %d,', CoilRec_ext(coil).numturns); + fprintf(channel_file,' area %g', CoilRec_ext(coil).area); + + if coil < nCoils + fprintf(channel_file,' --- '); + end + + fprintf(channel_file,'\n'); +end + +return + +function save_sensor_locs(Channel) +% Save Channel location in a pseudo-result file for visualization in the MRITool + +nchan = length(Channel); +meg = good_channel(Channel,ones(nchan,1),'MEG'); +eeg = good_channel(Channel,ones(nchan,1),'EEG'); + +nchan= length([meg,eeg]); +SourceLoc = cell(1,nchan); + +i = 0; +for k = [meg,eeg] + i = i+1; + SourceLoc{i} = Channel(k).Loc(:,1); + SourceOrder(i) = -1; + Comment = 'Sensor Locations'; +end +DataFlag = 'Sensors'; +save sensor_result SourceLoc SourceOrder DataFlag Comment + +return diff --git a/eeglab/plugins/ctf/importctf.m b/eeglab/plugins/ctf/importctf.m new file mode 100644 index 0000000..dd67c48 --- /dev/null +++ b/eeglab/plugins/ctf/importctf.m @@ -0,0 +1,114 @@ +% importctf() - import CTF DataSets +% +% Usage: +% >> [data channel study] = importctf(datafile,device) +% +% Required Input: +% dasfolder = a Dataset (DS) folder +% +% Optional Input: +% device = ['MEG'|'EEG'|'EEG+MEG'|'ALL'] +% +% Outputs: +% data = cell array of data (one cell by trial) +% channel = sensor positions +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READBSTORM, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/06/29 +% First alpha version for EEGLAB release 4.301 + +function [Data,Channel] = importctf(dsfolder,device) + +if nargin < 1 + help(mfilename); + return; +end; + +[ignore, studyname]=fileparts(dsfolder); +dsfolder + +prev_dir=cd; +cd(dsfolder) +% Converrting Data to BrainStorm format + +[Data.F,Channel,Data.imegsens,Data.ieegsens,Data.iothersens,Data.irefsens,Data.grad_order_no,Data.no_trials,Data.filter,Data.Time,Data.RunTitle] = ds2brainstorm(dsfolder,1,0); +% VERBOSE,READRES,CHANNELS, TIME, NO_TRIALS, DCOffset); + + +%Importing Electrodes to EEGLAB format +channelflags=zeros(length(Channel),1); +if nargin <2 + DEVICES={'EEG', 'MEG', 'EEG+MEG', 'ALL'}; + [s,v] = listdlg('PromptString','Select a device:',... + 'SelectionMode','single',... + 'ListString',{'EEG', 'MEG', 'EEG+MEG'}); + if not(all(v)) + s=3; + end + + switch(s) + case 1 + device={'EEG'} + case 2, device={'MEG'} + case 3, device = {'EEG', 'MEG'} + end + +end +for i=1:length(device) + channelflags=channelflags + strcmp(device{i},{Channel.Type}'); +end +%channelflags(strmatch('EEG', {Channel.Type}))=1; +%channelflags(strmatch('MEG', {Channel.Type}))=1; + +Channel=Channel(find(channelflags)); +for i=1:length(Data.F) + Data.F{i}=Data.F{i}(find(channelflags),:); +end + +return + +i=1; +%datafilename=sprintf('%s%d.mat', database , i); +f=dir(sprintf('%s*.mat', database)); +f=strvcat({f.name}); +f=f(:,length(database)+1:end); +trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +trials=sort(trials); + +h = waitbar(0,'Importing Datafiles. Please wait...'); +for i=1:length(trials) + waitbar(i/length(trials),h) + datafilename=sprintf('%s%d.mat', database , trials(i)); + fprintf('Importing %s\n', datafilename) + Data(i)=load(datafilename); + %channelflag=channelflags & Data(i).ChannelFlag; + channelflag=channelflags; + Data(i).F=Data(i).F(find(channelflag),:); +end +close(h) + +return diff --git a/eeglab/plugins/ctf/pop_importctf.m b/eeglab/plugins/ctf/pop_importctf.m new file mode 100644 index 0000000..de1403d --- /dev/null +++ b/eeglab/plugins/ctf/pop_importctf.m @@ -0,0 +1,157 @@ +% pop_importctf() - imports CTF DataSet (pop out window if no arguments). +% +% Usage: +% >> EEG = pop_importctf; % a window pops up +% >> EEG = pop_importctf( dsfolder ); +% +% Inputs: +% datafile - A datafile within a DS folder containing BrainStorm datafiles +% +% Outputs: +% EEG - EEGLAB data structure +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: eeglab(), importctf() + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: pop_importctf.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 +% + +function [EEG, command] = pop_importctf(datafile); + +EEG = []; +command = ''; +if nargin < 1 + % ask user + try + cd('D:\ndiaye\data\studies\div\Savg\avgdata\div-d-avTone1.ds'); + catch + end + [filename, filepath] = uigetfile('*.hc', 'Choose a DS folder -- pop_importctf()'); + drawnow; + if filename == 0 return; end; + [dsfolder]=fileparts(fullfile(filepath, filename)) ; +end; + +% load data +% --------- +EEG = eeg_emptyset; +[data channel ] = importctf(dsfolder); + +EEG.filename = data.RunTitle +EEG.filepath = dsfolder; +EEG.setname = ['CTF data:' data.RunTitle ]; +EEG.nbchan = length(channel); +EEG.srate = 1/mean(diff(data.Time)); +EEG.trials = length(data.F); +EEG.pnts = length(data.Time); +EEG.times = data(1).Time; +EEG.xmin = EEG.times(1); % huh?? +EEG.xmax = EEG.times(end); % huh?? +%Caution! CELL2MAT is overloaded in EEGLAB environment +fprintf('Importing data...(may take a while)') +EEG.data=zeros([EEG.nbchan EEG.pnts EEG.trials]); +for i=1:EEG.trials + EEG.data(:,:,i)=data.F{i}; +end +% EEG.comments = study.Session; +EEG.comments = sprintf('Imported from CTF dataset: %s', dsfolder); +EEG.ref = ['common']; + +fprintf('Importing channel location information') +for i=1:length(channel) + eloc(i).X=channel(i).Loc(1); + eloc(i).Y=channel(i).Loc(2); + eloc(i).Z=channel(i).Loc(3); + eloc(i).labels=channel(i).Name; +end +EEG.chanlocs=convertlocs(eloc, 'cart2all') + +EEG = eeg_checkset(EEG); +command = sprintf('EEG = pop_importctf(''%s'');', dsfolder); + +return; + + + +% importing the events +% -------------------- +if ~isempty(Eventdata) + orinbchans = EEG.nbchan; + for index = size(Eventdata,1):-1:1 + EEG = pop_chanevent( EEG, orinbchans-size(Eventdata,1)+index, 'edge', 'leading', ... + 'delevent', 'off', 'typename', Head.eventcode(index,:), ... + 'nbtype', 1, 'delchan', 'on'); + end; +end; +return + +%EEG = +% +% setname: 'Continuous EEG Data epochs' +% filename: 'eeg_demo_squareepochs.set' +% filepath: '' +% pnts: 384 +% nbchan: 32 +% trials: 80 +% srate: 128 +% xmin: -1 +% xmax: 1.9922 +% data: [32x384x80 single] +% icawinv: [] +% icasphere: [] +% icaweights: [] +% icaact: [] +% event: [1x157 struct] +% epoch: [1x80 struct] +% chanlocs: [1x32 struct] +% comments: [9x769 char] +% averef: 'no' +% rt: [] +% eventdescription: {[2x29 char] [2x63 char] [2x36 char] ''} +% epochdescription: {} +% specdata: [] +% specicaact: [] +% reject: [1x1 struct] +% stats: [1x1 struct] +% splinefile: [] +% ref: 'averef' +% history: [11x108 char] +% times: [1x384 double] + +% EEG.event +% 1x157 struct array with fields: +% type: 'square' or 'rt' +% position: [1] or [2] +% latency: in ms from the beginning of the continuous recording +% epoch: the epoch in which the event falls (indexed from 1) + +% EEG.epoch +% 1x80 struct array with fields: +% event: the index of the events that fall in that one epoch +% eventlatency: the latency of each event +% eventposition: the position of each event +% eventtype: the type of each event + + diff --git a/ellipse.m b/ellipse.m new file mode 100644 index 0000000..4de6f54 --- /dev/null +++ b/ellipse.m @@ -0,0 +1,149 @@ +function h=ellipse(ra,rb,ang,x0,y0,C,Nb) +% Ellipse adds ellipses to the current plot +% +% ELLIPSE(ra,rb,ang,x0,y0) adds an ellipse with semimajor axis of ra, +% a semimajor axis of radius rb, a semimajor axis of ang, centered at +% the point x0,y0. +% +% The length of ra, rb, and ang should be the same. +% If ra is a vector of length L and x0,y0 scalars, L ellipses +% are added at point x0,y0. +% If ra is a scalar and x0,y0 vectors of length M, M ellipse are with the same +% radii are added at the points x0,y0. +% If ra, x0, y0 are vectors of the same length L=M, M ellipses are added. +% If ra is a vector of length L and x0, y0 are vectors of length +% M~=L, L*M ellipses are added, at each point x0,y0, L ellipses of radius ra. +% +% ELLIPSE(ra,rb,ang,x0,y0,C) +% adds ellipses of color C. C may be a string ('r','b',...) or the RGB value. +% If no color is specified, it makes automatic use of the colors specified by +% the axes ColorOrder property. For several circles C may be a vector. +% +% ELLIPSE(ra,rb,ang,x0,y0,C,Nb), Nb specifies the number of points +% used to draw the ellipse. The default value is 300. Nb may be used +% for each ellipse individually. +% +% h=ELLIPSE(...) returns the handles to the ellipses. +% +% as a sample of how ellipse works, the following produces a red ellipse +% tipped up at a 45 deg axis from the x axis +% ellipse(1,2,pi/8,1,1,'r') +% +% note that if ra=rb, ELLIPSE plots a circle +% + +% written by D.G. Long, Brigham Young University, based on the +% CIRCLES.m original +% written by Peter Blattner, Institute of Microtechnology, University of +% Neuchatel, Switzerland, blattner@imt.unine.ch + + +% Check the number of input arguments + +if nargin<1, + ra=[]; +end; +if nargin<2, + rb=[]; +end; +if nargin<3, + ang=[]; +end; + +%if nargin==1, +% error('Not enough arguments'); +%end; + +if nargin<5, + x0=[]; + y0=[]; +end; + +if nargin<6, + C=[]; +end + +if nargin<7, + Nb=[]; +end + +% set up the default values + +if isempty(ra),ra=1;end; +if isempty(rb),rb=1;end; +if isempty(ang),ang=0;end; +if isempty(x0),x0=0;end; +if isempty(y0),y0=0;end; +if isempty(Nb),Nb=300;end; +if isempty(C),C=get(gca,'colororder');end; + +% work on the variable sizes + +x0=x0(:); +y0=y0(:); +ra=ra(:); +rb=rb(:); +ang=ang(:); +Nb=Nb(:); + +if isstr(C),C=C(:);end; + +if length(ra)~=length(rb), + error('length(ra)~=length(rb)'); +end; +if length(x0)~=length(y0), + error('length(x0)~=length(y0)'); +end; + +% how many inscribed elllipses are plotted + +if length(ra)~=length(x0) + maxk=length(ra)*length(x0); +else + maxk=length(ra); +end; + +% drawing loop + +for k=1:maxk + + if length(x0)==1 + xpos=x0; + ypos=y0; + radm=ra(k); + radn=rb(k); + if length(ang)==1 + an=ang; + else + an=ang(k); + end; + elseif length(ra)==1 + xpos=x0(k); + ypos=y0(k); + radm=ra; + radn=rb; + an=ang; + elseif length(x0)==length(ra) + xpos=x0(k); + ypos=y0(k); + radm=ra(k); + radn=rb(k); + an=ang(k) + else + rada=ra(fix((k-1)/size(x0,1))+1); + radb=rb(fix((k-1)/size(x0,1))+1); + an=ang(fix((k-1)/size(x0,1))+1); + xpos=x0(rem(k-1,size(x0,1))+1); + ypos=y0(rem(k-1,size(y0,1))+1); + end; + + co=cos(an); + si=sin(an); + the=linspace(0,2*pi,Nb(rem(k-1,size(Nb,1))+1,:)+1); +% x=radm*cos(the)*co-si*radn*sin(the)+xpos; +% y=radm*cos(the)*si+co*radn*sin(the)+ypos; + h(k)=line(radm*cos(the)*co-si*radn*sin(the)+xpos,radm*cos(the)*si+co*radn*sin(the)+ypos); + set(h(k),'color',C(rem(k-1,size(C,1))+1,:)); + +end; + diff --git a/elproj.m b/elproj.m new file mode 100644 index 0000000..d673808 --- /dev/null +++ b/elproj.m @@ -0,0 +1,105 @@ +function [proj] = elproj(pos, method); + +% ELPROJ makes a azimuthal projection of a 3D electrode cloud +% on a plane tangent to the sphere fitted through the electrodes +% the projection is along the z-axis +% +% [proj] = elproj([x, y, z], 'method'); +% +% Method should be one of these: +% 'gnomic' +% 'stereographic' +% 'ortographic' +% 'inverse' +% 'default' +% +% Imagine a plane being placed against (tangent to) a globe. If +% a light source inside the globe projects the graticule onto +% the plane the result would be a planar, or azimuthal, map +% projection. If the imaginary light is inside the globe a Gnomonic +% projection results, if the light is antipodal a Sterographic, +% and if at infinity, an Orthographic. +% +% The default projection is an angular projection (BESA like). +% An inverse projection is the opposite of the default angular projection. + +% Copyright (C) 2000-2001, Robert Oostenveld +% +% $Log: elproj.m,v $ +% Revision 1.2 2003/03/17 10:37:28 roberto +% improved general help comments and added copyrights +% + +x = pos(:,1); +y = pos(:,2); +if size(pos, 2)==3 + z = pos(:,3); +end + +if nargin<2 + method='default'; +end + +if nargin<3 + secant=1; +end + +if strcmp(method, 'orthographic') + % this method compresses the lowest electrodes very much + % electrodes on the bottom half of the sphere are folded inwards + xp = x; + yp = y; + num = length(find(z<0)); + str = sprintf('%d electrodes may be folded inwards in orthographic projection\n', num); + if num + warning(str); + end + proj = [xp yp]; + +elseif strcmp(method, 'gnomic') + % the lightsource is in the middle of the sphere + % electrodes on the equator are projected at infinity + % electrodes below the equator are not projected at all + rad = mean(sqrt(x.^2 + y.^2 + z.^2)); + phi = cart2pol(x, y); + th = atan(sqrt(x.^2 + y.^2) ./ z); + xp = cos(phi) .* tan(th) .* rad; + yp = sin(phi) .* tan(th) .* rad; + num = length(find(th==pi/2 | z<0)); + str = sprintf('removing %d electrodes from gnomic projection\n', num); + if num + warning(str); + end + xp(find(th==pi/2 | z<0)) = NaN; + yp(find(th==pi/2 | z<0)) = NaN; + proj = [xp yp]; + +elseif strcmp(method, 'stereographic') + % the lightsource is antipodal (on the south-pole) + rad = mean(sqrt(x.^2 + y.^2 + z.^2)); + z = z + rad; + phi = cart2pol(x, y); + th = atan(sqrt(x.^2 + y.^2) ./ z); + xp = cos(phi) .* tan(th) .* rad * 2; + yp = sin(phi) .* tan(th) .* rad * 2; + num = length(find(th==pi/2 | z<0)); + str = sprintf('removing %d electrodes from stereographic projection\n', num); + if num + warning(str); + end + xp(find(th==pi/2 | z<0)) = NaN; + yp(find(th==pi/2 | z<0)) = NaN; + proj = [xp yp]; + +elseif strcmp(method, 'inverse') + % compute the inverse projection of the default angular projection + [th, r] = cart2pol(x, y); + [xi, yi, zi] = sph2cart(th, pi/2 - r, 1); + proj = [xi, yi, zi]; + +else + % use default angular projection + [az, el, r] = cart2sph(x, y, z); + [x, y] = pol2cart(az, pi/2 - el); + proj = [x, y]; +end diff --git a/entropy.m b/entropy.m new file mode 100644 index 0000000..339acfe --- /dev/null +++ b/entropy.m @@ -0,0 +1,32 @@ +function H = entropy(X,varargin) +%ENTROPY - Entropy in bits +% [H] = entropy(X,b) +% Computes Shannon's entropy (column-wise) in bits +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-10-24 Creation +% +% ----------------------------- Script History --------------------------------- +[e,n,f]=histk(X,varargin{:}); +if ~iscell(e) + e={e}; + n={n}; +end +for i=1:numel(e) + N=sum(n{i}); + % Trick: + % We replace 0 by -1 which has imaginary log + n{i}=numrep(n{i}./N,0,-1); + H(i)=-sum(nonzeros(n{i}).*log(nonzeros(n{i})))./log(2); + % Now we discard the imaginary part + H(i)=real(H(i)); +end \ No newline at end of file diff --git a/entropy2.m b/entropy2.m new file mode 100644 index 0000000..ae5e17d --- /dev/null +++ b/entropy2.m @@ -0,0 +1,68 @@ +function H = entropy(objectSet,varargin) +%ENTROPY Compute the Shannon entropy of a set of variables. +% ENTROPY(X,P) returns the (joint) entropy for the joint distribution +% corresponding to object matrix X and probability vector P. Each row of +% MxN matrix X is an N-dimensional object, and P is a length-M vector +% containing the corresponding probabilities. Thus, the probability of +% object X(i,:) is P(i). +% +% ENTROPY(X), with no probability vector specified, will assume a uniform +% distribution across the objects in X. +% +% If X contains duplicate rows, these are assumed to be occurrences of the +% same object, and the corresponding probabilities are added. (This is +% actually the only reason that object matrix X is needed -- to detect and +% merge repeated objects. Of course, the entropy itself only depends on +% the probability vector P.) Matrix X need NOT be an exhaustive list of +% all *possible* objects in the universe; objects that do not appear in X +% are simply assumed to have zero probability. +% +% The elements of probability vector P must sum to 1 +/- .00001. +% +% For further information about entropy in information theory, see +% Information entropy. Wikipedia, The Free Encyclopedia. +% +% See also: MUTUALINFO + +%% Error checking %% +if size(objectSet,1) == 1, + objectSet = objectSet'; + %warning('Object set row vector is being transposed to a column vector.') +end +if ~isempty(varargin), + probSet = varargin{1}; +else + probSet = repmat(1/size(objectSet,1),size(objectSet,1),1); +end +if ~isequal(size(objectSet,1),length(probSet)), + error('Object set must have an object for each probability.') +end +% Check probabilities sum to 1: +if abs(sum(probSet) - 1) > .00001, + error('Probablities don''t sum to 1.') +end + +%% Merge duplicate objects/probabilities %% +% We do not use objectSet in the calculations, but just need to deal with +% duplicated objects (add probabilities together). +[minimalObjSet I equivClass] = unique(objectSet,'rows'); +if ~isequal(size(minimalObjSet,1),size(objectSet,1)), + probSetReduced = zeros(size(minimalObjSet,1),1); + for i = 1:length(probSetReduced), + probSetReduced(i) = sum(probSet(equivClass==i)); + end + probSet = probSetReduced; +end + +%% Remove any zero probabilities %% +zeroProbs = find(probSet < eps); +if ~isempty(zeroProbs), + probSet(zeroProbs) = []; + %disp('Removed zero or negative probabilities.') +end + +%% Compute the entropy +H = -sum(probSet .* log2(probSet)); + + + diff --git a/epilepsie/dataplot_cb.m b/epilepsie/dataplot_cb.m new file mode 100644 index 0000000..0b079fd --- /dev/null +++ b/epilepsie/dataplot_cb.m @@ -0,0 +1,6685 @@ +function varargout = dataplot_cb(action,varargin) +%DATAPLOT_CB : Callback switchyard for the DATAPLOT Tool +% function dataplot_cb(action) +% Callback function for the DATAVIEWER tool +% +% /---Script Author--------------------------------------\ +% | | +% | *** Sylvain Baillet, Ph.D. | +% | Cognitive Neuroscience & Brain Imaging Laboratory | +% | CNRS UPR640 - LENA | +% | Hopital de la Salpetriere, Paris, France | +% | sylvain.baillet@chups.jussieu.fr | +% \------------------------------------------------------/ +% +% Date of creation: January 1999 +% Date of modification: November 2001 +%--------------------------------------------------------------------------------------------------------------------------- +% SB, 2001-09 / revamping for compliancy with DataManager + major plastic surgery +% SB, October 2001 - Added Cortical Probes, Mapping of Curvature, Colormap Scaling of Activations +% SB - DS, November 2001 - Multiple fixings; added 0ms adjustment to data maximum peak (useful for epileptic data analysis about the maximum of the spike) +% KND, Nov. 2003 : Changed lines 610-621 to allow MEG and EEG data plot... +% KND, Nov. 2003 : Changed line 290 to put F{1} in Data.F + +frontcolor = [.4 .4 .4]; +backcolor = [.8 .8 .8]; +linecolor = [.4 .4 .4]; +textcolor = linecolor; +verbose = 0;% Verbose mode for Mosher's tools: 0 - off ; 1 - on + +%---------------------------------------------------------------------------- + +DATAPLOT = openfig('dataplot.fig','reuse'); + +TASKBAR = findobj(0,'Tag','TASKBAR'); +Users = guidata(TASKBAR); + +MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); +EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); +OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); +current = find([MEG,EEG,OTHER] == 1); +modality = {'MEG','EEG','OTHER'}; + +switch action + +case 'create' + DATAPLOT = openfig('dataplot.fig','reuse'); + % Check for data loaded from DataManager, if exists + if ~isfield(Users,'CurrentData') % No data was loaded using DataManager - do nothing (old way) + set(findobj(DATAPLOT,'style','pushbutton'),'enable','off'); + set(findobj(DATAPLOT,'string','Load'),'enable','on') + set(findobj(DATAPLOT,'string','Quit'),'enable','on') + set(findobj(DATAPLOT,'Tag','SurfaceViewer'),'enable','on') + return + end + + % Look for datafiles in current study folder + cd(Users.STUDIES); + [studypath,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(studypath) + + TestFiles = dir('*data*.mat'); + i = 0; + for k = 1:length(TestFiles) + if isempty(findstr(TestFiles(k).name,'results')) + i = i+1; + DataFiles{i} = TestFiles(k).name; + end + end + if isempty(DataFiles) + DataFiles = 'No data files in current study'; + end + + hDataplot = guihandles(DATAPLOT); + set(hDataplot.DataFileList,'String',DataFiles,'Value',1,'Max',1) + + + %Visu = get(DATAPLOT,'Userdata'); + if 1%isempty(Visu) + dataplot_cb('loaddata',Users.CurrentData.StudyFile,Users.CurrentData.DataFile); + end + + %---------------------------------------------------------------------------- + + +case 'mutincomp_cmapping' % Mutually icompatible checkboxes + mapping_win = findobj(0,'Tag','mapping'); + MEG = findobj(mapping_win ,'Tag','ABSOLUTE'); + EEG = findobj(mapping_win ,'Tag','RELATIVE'); + mutincomp([MEG,EEG]) + h = findobj([MEG,EEG],'Value',1); + if length(h)>1 + set(h(2),'Value',0) + end + %---------------------------------------------------------------------------- + +case 'mutincomp_colormap' % Mutually icompatible checkboxes + mapping_win = findobj(0,'Tag','tesselation_select'); + MEG = findobj(mapping_win ,'Tag','Normalize'); + EEG = findobj(mapping_win ,'Tag','FreezeColormap'); + mutincomp([MEG,EEG]) + h = findobj([MEG,EEG],'Value',1); + if length(h)>1 + set(h(2),'Value',0) + end + + %---------------------------------------------------------------------------- +case 'mutincomp_meanmax' % Mutually icompatible checkboxes + mapping_win = findobj(0,'Tag','tesselation_select'); + MEG = findobj(mapping_win ,'Tag','MeanCorticalArea'); + EEG = findobj(mapping_win ,'Tag','MaxCorticalArea'); + OTHER = findobj(mapping_win ,'Tag','AllCorticalArea'); + + mutincomp([MEG,EEG,OTHER]) + h = findobj([MEG,EEG,OTHER],'Value',1); + if length(h)>1 + set(h(2:end),'Value',0) + end + %---------------------------------------------------------------------------- +case 'mutincomp_opaque' % Mutually icompatible checkboxes + MEG = findobj(gcbf,'Tag','Opaque'); + EEG = findobj(gcbf,'Tag','transparent'); + mutincomp([MEG,EEG]) + h = findobj([MEG,EEG],'Value',1); + if length(h)>1 + set(h(2),'Value',0) + end + dataplot_cb mesh_vals + %---------------------------------------------------------------------------- + +case 'mapping_type' % Mutually icompatible checkboxes + mapping_win = findobj(0,'Tag','mapping'); + MEG = findobj(mapping_win ,'Tag','raw'); + EEG = findobj(mapping_win ,'Tag','gradient'); + OTHER = findobj(mapping_win,'Tag','magnetic'); + mutincomp([MEG,EEG,OTHER]) + h = findobj([MEG,EEG,OTHER],'Value',1); + if length(h)>1 + set(h(2),'Value',0) + end + %---------------------------------------------------------------------------- + +case 'mapping_head_shape' % Mutually icompatible checkboxes + mapping_win = findobj(0,'Tag','mapping'); + handles = guihandles(mapping_win); + % figure(mapping_win) + mutincomp([handles.sphere,handles.fit,handles.scalp]) + h = findobj([handles.sphere,handles.fit,handles.scalp],'Value',1); + if length(h)>1 + set(h(2),'Value',0) + end + %---------------------------------------------------------------------------- + +case 'selectmodality' % Select the current signals to visualize + MEG = findobj(DATAPLOT,'Tag','MEG'); + EEG = findobj(DATAPLOT,'Tag','EEG'); + OTHER = findobj(DATAPLOT,'Tag','OTHER'); + mutincomp([MEG,EEG,OTHER]) + h = findobj([MEG,EEG,OTHER],'Value',1); + if length(h)>1 + set(h(2),'Value',0) % Just one modality at a time please ! + end + QUICKLOOK_GUI = findobj(0,'Tag','QUICKLOOK_GUI'); + if ~isempty(QUICKLOOK_GUI) + vMEG = get(MEG,'value'); + vEEG = get(EEG,'value'); + vOTHER = get(OTHER,'value'); + current = find([vMEG,vEEG,vOTHER] == 1); + set(QUICKLOOK_GUI,'Name',['QuickLook ',modality{current}]) + end + + previous = findobj(0,'Tag','channel_select'); % Update Channel Selection Window with Current Modality + if ~isempty(previous) + dataplot_cb selectchannels + end + + mapping_win = findobj(0,'Tag','mapping'); + MEG = get(MEG,'value'); + EEG = get(EEG,'value'); + OTHER = get(OTHER,'value'); + current = find([MEG,EEG,OTHER] == 1); + if ~isempty(mapping_win) + set(mapping_win,'Name',[modality{current},' Mapping']) + RAW = findobj(mapping_win ,'Tag','raw'); + GRADIENT = findobj(mapping_win ,'Tag','gradient'); + MAGNETIC = findobj(mapping_win,'Tag','magnetic'); + + if current == 1 % If MEG + set([RAW,GRADIENT,MAGNETIC],'enable','on') + set(RAW,'Value',1) + else + set([RAW,GRADIENT,MAGNETIC],'enable','off') + end + end + + Visu = get(DATAPLOT,'Userdata'); + channel_select_win = findobj(0,'Tag','channel_select'); + goodchannels = setdiff([Visu.ChannelID{current}],find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect([Visu.ChannelID{current}],find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + + removed = findobj(channel_select_win,'Tag','removed'); + available = findobj(channel_select_win,'Tag','available'); + + + set(available,'String', cellstr(num2str(goodchannels'))); + set(removed,'String', cellstr(num2str(badchannels'))); + + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + %---------------------------------------------------------------------------- +case 'LoadFromDataFileList' % Load from popup menu list in the DataViewer + hDataplot = guihandles(DATAPLOT); + iFile = get(hDataplot.DataFileList,'Value'); + FileNames = get(hDataplot.DataFileList,'String'); + + dataplot_cb('loaddata',Users.CurrentData.StudyFile,FileNames{iFile}); + % dataplot_cb quicklook + + %---------------------------------------------------------------------------- +case 'LoadPrevFile' % Load previous file in the popup menu list in the DataViewer + hDataplot = guihandles(DATAPLOT); + iFile = get(hDataplot.DataFileList,'Value'); + FileNames = get(hDataplot.DataFileList,'String'); + + iFile = iFile - 1; + if iFile < 1 + iFile = 1; + return + end + + set(hDataplot.DataFileList,'Value',iFile) + dataplot_cb('loaddata',Users.CurrentData.StudyFile,FileNames{iFile}); + +% dataplot_cb quicklook + + %---------------------------------------------------------------------------- +case 'LoadNextFile' % Load previous file in the popup menu list in the DataViewer + hDataplot = guihandles(DATAPLOT); + iFile = get(hDataplot.DataFileList,'Value'); + FileNames = get(hDataplot.DataFileList,'String'); + + iFile = iFile + 1; + if iFile > length(FileNames) + iFile = length(FileNames); + return + end + + set(hDataplot.DataFileList,'Value',iFile) + dataplot_cb('loaddata',Users.CurrentData.StudyFile,FileNames{iFile}); + + % dataplot_cb quicklook + + %---------------------------------------------------------------------------- +case 'loaddata' % Only MAT BrainStorm file format is available - User has to import original data into BrainStorm otherwise + + TIME_MIN = findobj(DATAPLOT,'Tag','time_min'); + TIME_MAX = findobj(DATAPLOT,'Tag','time_max'); + + datatype = 'mat'; + % Read Study File + + cd(Users.STUDIES); + if nargin == 1 % Load the old-way + [studyfile,studypath] = uigetfile(['*brainstormstudy.',datatype], 'Enter file name for the study file'); + if (studyfile)==0, return, end + cd(studypath) + + [datafile,datapath] = uigetfile(['*data*.',datatype], 'Enter file name for data set'); + if (datafile)==0, return, end + disp('Loading data...') + cd(datapath) + elseif nargin == 3 + studyfile = varargin{1}; + datafile = varargin{2}; + end + [path,file,ext] = fileparts(studyfile); + + load(studyfile); + if ~isempty(path) + cd(path) + end + + try + Data= load(datafile); + catch + cd(Users.STUDIES) + Data= load(datafile); + end + + %KND + if iscell(Data.F) + Data.F=Data.F{1}; + end + + + Visu.Data = Data; clear Data + + set(findobj(DATAPLOT,'style','pushbutton'),'enable','on'); + + channelfile = strrep([file,ext],'brainstormstudy','channel'); + load(channelfile) + + % - Loading Subject Information + cd(Users.SUBJECTS) + if isempty(BrainStormSubject) + % errordlg('Please make sure you have assigned a Subject file to this study') + % study_editor_cb create + % + set(findobj(DATAPLOT,'Tag', 'SurfaceViewer'),'enable','off') + else + load(BrainStormSubject) + + Visu.Tesselation = Tesselation; + if isempty(Visu.Tesselation) + set(findobj(DATAPLOT,'Tag', 'SurfaceViewer'),'enable','off') + else + set(findobj(DATAPLOT,'Tag', 'SurfaceViewer'),'enable','on') + end + end + + % Check the nature of the channels + MEG_chk = []; + EEG_chk = []; + OTHER_chk = []; + + % Channel Identification + imeg = 0; % Index of MEG channels + ieeg = 0; + iother = 0; + megID = []; + eegID = []; + otherID = []; + + for chan = 1:max(size(Channel)) + if ~isempty(Channel(chan).Type) + switch Channel(chan).Type + % case {'MEG','MEG Sensor','Ref Magnetometer','Ref Gradiometer'} + % case {'MEG','Ref Magnetometer','Ref Gradiometer'} + case {'MEG','MEG Sensor'} + MEG_chk = 1; + imeg = imeg +1; + megID(imeg) = chan; + case {'EEG','EEG Sensor'} + EEG_chk = 1; + ieeg = ieeg +1; + eegID(ieeg) = chan; + otherwise + OTHER_chk = 1; + iother = iother +1; + otherID(iother) = chan; + end + end + end + + Visu.ChannelID = {megID,eegID,otherID}; + Visu.Channel = Channel; + + % Number of time samples - for GUI display purposes + nSamples = findobj(DATAPLOT,'tag','Samples'); + set(nSamples,'String',{int2str(size(Visu.Data.F,2)),'samples'}) + + set(TIME_MIN,'String',num2str(1000*min(Visu.Data.Time),5)) + set(TIME_MAX,'String',num2str(1000*max(Visu.Data.Time),5)) + + hDATAPLOT = guihandles(DATAPLOT); + + set([hDATAPLOT.MEG,hDATAPLOT.EEG,hDATAPLOT.OTHER,hDATAPLOT.RemoveEEGAverage],'enable','on') + + if isempty(MEG_chk) + set(hDATAPLOT.MEG,'enable','off','Value',0) + end + if isempty(EEG_chk) + set(hDATAPLOT.EEG,'enable','off','Value',0) + set(hDATAPLOT.RemoveEEGAverage,'enable','off') + end + if isempty(OTHER_chk ) + set(hDATAPLOT.OTHER,'enable','off') + end + + if ~isempty(MEG_chk) + set(hDATAPLOT.MEG,'value',~isempty(MEG_chk),'enable','on') + end + if ~isempty(EEG_chk) + set(hDATAPLOT.EEG,'enable','on','Value',1) + set(hDATAPLOT.RemoveEEGAverage,'value',0) + end + + if ~isempty(OTHER_chk) + set(hDATAPLOT.OTHER,'enable','on') + end + + set(DATAPLOT,'Userdata',Visu) + + htaskbar = guihandles(TASKBAR); + set(htaskbar.CurrentData,'String',... + { ['Study: ',''],... + ['Subject: ', Users.CurrentData.SubjectName],... + ['Data File: ',datafile],... + ['Database: ',Users.CurrentData.Database]... + }); + + + FileList = get(hDATAPLOT.DataFileList,'String'); + iFile = find(strcmp(FileList,datafile)); + if ~isempty(iFile) + set(hDATAPLOT.DataFileList,'Value',iFile) + end + + disp('Loading data... -> Done') + drawnow + + %---------------------------------------------------------------------------- + +case 'RemoveEEGAverage' % When box is checked, systematically displays the EEG as averaged-reference + + Visu = get(DATAPLOT,'Userdata'); + switch get(gcbo,'Value') + case 1 % Remove Average + % Get goodchannels + goodchannels = find(Visu.Data.ChannelFlag(Visu.ChannelID{2})==1); + goodchannels = Visu.ChannelID{2}(goodchannels); + if ~isfield(Visu,'DataOrig') % First time average reference is requested + Visu.DataOrig.F = Visu.Data.F; + end + Visu.Data.F(goodchannels,:) = Visu.Data.F(goodchannels,:) - repmat(mean(Visu.Data.F(goodchannels,:)),length(goodchannels),1); + ButtonName=questdlg('Would you like to overwrite the orignal EEG segment in the current data file with the averaged-reference EEG (ie current referenced EEG will be lost) or save it under another name ?',... + '','Overwrite','Save as a new file','Don''t save; just try it','Overwrite'); + switch ButtonName + case 'Overwrite' + % Save it back to the original data set file + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + [path,file,ext] = fileparts(Users.CurrentData.DataFile); + if file == 0, return, end + + save_fieldnames(Visu.Data,file) + + Users.CurrentData.DataFile = file; + guidata(TASKBAR,Users) + + case 'Save as a new file' + + % Save it back to the original data set file + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + [path,file,ext] = fileparts(Users.CurrentData.DataFile); + if file == 0, return, end + + file = [file,'_EEGAvrRef']; + + save_fieldnames(Visu.Data,file) + + msgbox(['Data saved in ',file]); + + Users.CurrentData.DataFile = file; + guidata(TASKBAR,Users) + + case 'Don''t save; just try it' + % Do nothing + case 'Cancel' + return + end + + otherwise % Back to original reference system + Visu.Data.F = Visu.DataOrig.F; + end + + Visu.Alter = 1; + + set(DATAPLOT,'Userdata',Visu) + dataplot_cb quicklook + + %---------------------------------------------------------------------------- +case {'set_time_min','set_time_max'} + dataplot_cb quicklook + IMAGING = findobj(0,'Tag','CorticalImaging'); + + if ~isempty(IMAGING) + dhandles = guihandles(DATAPLOT); + handles = guihandles(IMAGING); + set(handles.FromTo,'String',... + sprintf('From: %s\t To: %s (ms)', get(dhandles.time_min,'String'),get(dhandles.time_max,'String')),... + 'Userdata',[str2num(get(dhandles.time_min,'String')),str2num(get(dhandles.time_max,'String'))] ); + end + + %---------------------------------------------------------------------------- + +case 'SetPeakLatency' %0ms adjustment to data maximum peak (useful for epileptic data analysis about the maximum of the spike) + % ... prior to source localization about the spike + Visu = get(DATAPLOT,'Userdata'); + hDataPlot = guihandles(DATAPLOT); + + if get(hDataPlot.SetPeakLatency,'Value') + if length(current) > 1 + errordlg('Please select either MEG, EEG or OTHER data subset') + return + end + + % Extract channels from selected data + goodchannel = intersect(find(Visu.Data.ChannelFlag==1),[Visu.ChannelID{current}]); + F = Visu.Data.F(goodchannel,:); + + % Get value for time window of analysis + winPeak = str2num(get(hDataPlot.PeakDetectionWindow,'String')); + + % Corresponding number of samples + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2)); + winPeak = ceil(winPeak/1000/srate/2); + + % Find sample corresponding to time 0ms + zeroLat = round(abs(Visu.Data.Time(1))/srate)+1; + + % Extract data on the window of analysis: + F = F(:,zeroLat-winPeak:zeroLat+winPeak); + + % Find maximum at each time sample + [mF ,mFindx] = max((F)); + % Find absolute maximum + [mmF, mFindx] = max(mF); + + % Compute new time vector + Visu.Data.TimeOrig = Visu.Data.Time; + + % New sample number for 0ms latency + zeroLat = zeroLat-winPeak+mFindx-1; + % New time vector + Time(1) = sign(Visu.Data.Time(1))*(zeroLat-1)*srate; + Time = Time(1):srate:(Time(1)+(length(Visu.Data.Time)-1)*srate); + Visu.Data.Time = Time; + set(hDataPlot.time_min,'String',num2str(Time(1)*1000,'%3.2f')); + set(hDataPlot.time_max,'String',num2str(Time(end)*1000,'%3.2f')); + else + Visu.Data.Time = Visu.Data.TimeOrig; + end + + % Save it back to the original data set file + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + [path,file,ext] = fileparts(Users.CurrentData.DataFile); + if file == 0, return, end + + save_fieldnames(Visu.Data,file) + file + + set(DATAPLOT,'Userdata',Visu) + dataplot_cb quicklook + + %---------------------------------------------------------------------------- + +case 'quicklook' + if isempty(current) + return + end + + Visu = get(DATAPLOT,'Userdata'); + + for k = 1:length(current) % For each of selected modality + previous{k} = findobj(0,'Tag',['waves_single',int2str(current(k))]); + if isempty(previous{k}) + previous{k} = open('wave_single.fig'); + set(previous{k},'color',backcolor) + set(previous{k},'Tag',['waves_single',int2str(current(k))]) + movegui(previous{k},'north'); + else + figure(previous{k}) + end + + zoom(previous{k},'on') + + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels{k} = setdiff(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1));%Discard bad channels + badchannels{k} = intersect(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1)); + else + goodchannels{k} = Visu.ChannelID{current(k)}; + badchannels{k} = []; + end + + end + + TIME_MIN = str2num(get(findobj(DATAPLOT,'Tag','time_min'),'String')); + TIME_MAX = str2num(get(findobj(DATAPLOT,'Tag','time_max'),'String')); + + if TIME_MAX > Visu.Data.Time(end) * 1000 + TIME_MAX = Visu.Data.Time(end) * 1000; + set(findobj(DATAPLOT,'Tag','time_max'),'String',num2str(TIME_MAX,5)) + end + + if TIME_MIN < Visu.Data.Time(1) * 1000 + TIME_MIN = Visu.Data.Time(1) * 1000; + set(findobj(DATAPLOT,'Tag','time_min'),'String',num2str(TIME_MIN,5)) + end + + mapping_win = findobj(0,'Tag','mapping'); + if ~isempty(mapping_win) + slider_time = findobj(mapping_win,'Tag','slider_time'); + set(slider_time,'Min',TIME_MIN,'Max',TIME_MAX) + set(slider_time,'Value',TIME_MIN) + end + + if length(Visu.Data.Time) >1 + delta_t = 1000*(Visu.Data.Time(2)-Visu.Data.Time(1)); + samples = round(([TIME_MIN:delta_t:TIME_MAX]-Visu.Data.Time(1)*1000)/delta_t)+1; + else + samples = 1; + end + % Number of time samples - for GUI display purposes + nSamples = findobj(DATAPLOT,'tag','Samples'); + set(nSamples,'String',{int2str(length(samples)),'samples'}) + + for k = 1:length(current) + figure(previous{k}) + switch current(k) + case 1 % MEG channels + try + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F(goodchannels{k},samples)); + catch + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F{1}(goodchannels{k},samples)); + end + set(plotwaves,'Tag','plotMEGwaves') + case 2 % EEG channels + try + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F(goodchannels{k},samples)); + catch + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F{1}(goodchannels{k},samples)); + end + set(plotwaves,'Tag','plotEEGwaves') + otherwise + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F(goodchannels{k},samples)); + set(plotwaves,'Tag','plotOTHERwaves') + end + + set(plotwaves,'ButtonDownFcn','dataplot_cb line_select') + set(gca,'xcolor', textcolor,'ycolor', textcolor,'fontweight','bold','Xlim',[TIME_MIN,TIME_MAX]); + grid on + set(gcf,'Userdata',plotwaves,'NumberTitle','off',... + 'Name',[modality{current(k)},' Waveforms']) + zoom(gcf,'on') + end + + %---------------------------------------------------------------------------- + +case 'line_select' % Mouse selection of a channel in the current waves_single window + Visu = get(DATAPLOT,'Userdata'); + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + + figsingle = findobj(0,'Tag',['waves_single',int2str(current)]); % Figure of overlaping plots for the current modality + layout = findobj(0,'Tag',['layout_',modality{current}]); + + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff([Visu.ChannelID{current}],find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; % Discard bad channels + badchannels = intersect([Visu.ChannelID{current}],find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + goodchannels = [Visu.ChannelID{current}]; + badchannels = []; + end + + switch gcbf + case figsingle + line_qcklk = get(figsingle,'Userdata'); + set(line_qcklk,'linewidth',1) + axes_qcklk = get(line_qcklk(1),'Parent'); + + gco = get(figsingle,'CurrentObject'); + if ~strcmp(get(gco,'Type'),'line') + return % No channel has been cliked + end + ichan = (find(line_qcklk == gco)); % Number of the line plot that has been selected + current_chan = (ichan);%-min(Visu.ChannelID{current})+1 ; % Number of the Channel that has been selected + set(line_qcklk(ichan),'linewidth',2); + case layout + gco = get(layout,'CurrentAxes'); + ichan = str2num(get(gca,'Tag')); % Number of the channel that has been selected + line_qcklk(ichan) = findobj(get(gca,'Children'),'Type','line','color',frontcolor); + axes_qcklk = get(line_qcklk(ichan),'Parent'); + otherwise + return + end + + previous = findobj(0,'Tag',['single_wave_',[modality{current}],' ',Visu.Channel(goodchannels(current_chan)).Name]); % Plot exists already ? + if ~isempty(previous) + figure(previous) + return + end + + singlefig = figure; % Creation of a new window + set(singlefig','color',backcolor,'CreateFcn','movegui south','Position',get(singlefig,'Position')/1.5,'Name','') + switch gcbf + case figsingle + set(singlefig,'Tag',['single_wave_',[modality{current}],' ',Visu.Channel(goodchannels(current_chan)).Name]) + set(singlefig,'Name',['Selected Channel: ',[modality{current}],' ',Visu.Channel(goodchannels(current_chan)).Name]) + otherwise + set(singlefig,'Tag',['single_wave_',[modality{current}],' ',Visu.Channel(goodchannels(current_chan)).Name]) + set(singlefig,'Name',['Selected Channel: ',[modality{current}],' ',Visu.Channel(goodchannels(current_chan)).Name]) + end + + ax_single = copyobj(axes_qcklk,singlefig); + set(ax_single,'Visible','on','Xcolor',textcolor,'Ycolor',textcolor,'color',[1 1 1],... + 'Fontweight','bold','Position',get(0,'DefaultAxesPosition'),'Units','Normal') + grid on + + delete(get(ax_single,'children')) + wave = copyobj(line_qcklk(ichan),ax_single); + set(wave,'Linewidth',2,'color',linecolor) + + %---------------------------------------------------------------------------- + +case 'quicklook_plots' % Single axis or Multiple axis plots for waveforms + Visu = get(DATAPLOT,'USerdata'); + % Current Modality + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + + QUICKLOOK_GUI = findobj(0,'Tag',['QUICKLOOK_GUI']); + figsingle = findobj(0,'Tag',['waves_single',int2str(current)]); % Figure of overlaping plots for the current modality + + if isempty(figsingle) + errordlg('Please load a data set first') + return + end + + % Get handles on the QUICKLOOK graphic objects + line_qcklk = get(figsingle,'Userdata');%findobj(figsingle,'Type','line'); + axes_qcklk = get(line_qcklk(1),'Parent'); + tag = get(gcbo,'TAG'); + + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff([Visu.ChannelID{current}],find(Visu.Data.ChannelFlag == -1))- min([Visu.ChannelID{current}])+1 ; % Discard bad channels + else + goodchannels = [Visu.ChannelID{current}]- min([Visu.ChannelID{current}])+1 ; + end + + switch tag + + case 'SINGLE' + switch get(gcbo,'value') + case 0 + set(findobj(DATAPLOT,'Tag','MULTIPLE'),'Value',1) + + multi = findobj(0,'Tag',['waves_multi',int2str(current)]); + if ~isempty(multi) + set(multi,'Visible','on') + return + end + + k = length(line_qcklk); % Number of channels + c = ceil(sqrt(k)); + r = ceil(sqrt(k)); + wave_fig = get(axes_qcklk,'Parent'); + + waves_multi + multi = findobj(0,'Tag','waves_multi'); + set(multi,'Tag',[get(multi,'Tag'),int2str(current)]) + switch current + case 1 + set(gcf,'Name','MEG wave forms') + case 2 + set(gcf,'Name','EEG wave forms') + otherwise + set(gcf,'Name','Miscellaneous wave forms') + end + + Mx = get(axes_qcklk,'Xlim'); + My = get(axes_qcklk,'Ylim'); + + for kk = 1:k + ax(kk) = subplot(r,c,kk); + line_qcklk(kk)= copyobj(line_qcklk(kk),ax(kk)); + set(line_qcklk(kk),'color',frontcolor) + set(ax(kk),'xcolor', frontcolor,'ycolor', frontcolor,'fontweight','bold',... + 'XTicklabel',[],'YTicklabel',[],'Xlim',Mx,'Ylim',My,'color',backcolor,'Box','on'); + xlabel(int2str(goodchannels(kk)),'color',frontcolor,'Fontsize',8) + end + + otherwise + set(findobj(DATAPLOT,'Tag','MULTIPLE'),'Value',0) + switch current + case 1 + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + case 2 + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + otherwise + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + end + + multi = findobj(0,'Tag',['waves_multi',int2str(current)]); + if ~isempty(multi) + set(multi,'Visible','off') + end + + end + case 'MULTIPLE' + switch get(gcbo,'value') + case 0 + set(findobj(DATAPLOT,'Tag','SINGLE'),'Value',1) + switch current + case 1 + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + case 2 + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + otherwise + figure(findobj(0,'Tag',['waves_single',int2str(current)])) + end + multi = findobj(0,'Tag',['waves_multi',int2str(current)]); + if ~isempty(multi) + set(multi,'Visible','off') + end + + otherwise + set(findobj(DATAPLOT,'Tag','SINGLE'),'Value',0) + + multi = findobj(0,'Tag',['waves_multi',int2str(current)]); + if ~isempty(multi) + set(multi,'Visible','on') + return + end + + k = length(line_qcklk); % Number of channels + c = ceil(sqrt(k)); + r = round(sqrt(k)); + wave_fig = get(axes_qcklk,'Parent'); + + waves_multi + multi = findobj(0,'Tag','waves_multi'); + set(multi,'Tag',[get(multi,'Tag'),int2str(current)]) + switch current + case 1 + set(gcf,'Name','MEG wave forms') + case 2 + set(gcf,'Name','EEG wave forms') + otherwise + set(gcf,'Name','Miscellaneous wave forms') + end + + Mx = get(axes_qcklk,'Xlim'); + My = get(axes_qcklk,'Ylim'); + + for kk = 1:k + ax(kk) = subplot(r,c,kk); + line_qcklk(kk)= copyobj(line_qcklk(kk),ax(kk)); + set(line_qcklk(kk),'color',frontcolor) + set(ax(kk),'xcolor', frontcolor,'ycolor', frontcolor,'fontweight','bold',... + 'XTicklabel',[],'YTicklabel',[],'Xlim',Mx,'Ylim',My,'color',backcolor,'Box','on'); + xlabel(Visu.Channel(Visu.ChannelID{current}(goodchannels(kk))).Name,'color',textcolor,'Fontsize',8) + end + end + end + %---------------------------------------------------------------------------- + +case 'Residuals' + Visu = get(DATAPLOT,'Userdata'); + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + if isempty(tesselation_select_win) + tesselation_select_win = open('tessellation_select.fig'); + end + handles = guihandles(tesselation_select_win); + + ResFiles = get(handles.ResultFiles,'String'); + ResFile = ResFiles{get(handles.ResultFiles,'Value')}; + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + ResFile = fullfile(Users.STUDIES,path,ResFile); + load(ResFile,'Fsynth','GUI','ImageGridTime'); + + if ~isempty(find(Visu.Data.ChannelFlag == -1))%~isempty(find(Visu.Data.ChannelFlag == 0)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)); % - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + goodchannels = Visu.ChannelID{current};% - min(Visu.ChannelID{current})+1; + badchannels = []; + end + + %F = Visu.Data.F(goodchannels,[GUI.Segment(1):GUI.Segment(end)]); % Try next line instead + F = Visu.Data.F(goodchannels,:); + + res = 100*norcol(F-Fsynth)./(norcol(F)); + clear Results; + mean_res = mean(res); + std_res = std(res); + min_res = min(res); + max_res = max(res); + + figres = figure; + powF = norm(norcol(F)); + [haxes, hline1,hline2] = plotyy(1000*ImageGridTime,res,1000*ImageGridTime,100*(norcol(F))/powF); + hold on + axes(haxes(1)) + set(haxes(1),'Ycolor','r') + set(hline1,'linewidth',2) + xlabel('Time (ms)'); + ylabel('Residuals (%)'); + + axes(haxes(2)) + set(haxes(2),'Ycolor','b') + xlabel('Time (ms)'); + ylabel('GFP (%)'); + grid on + set(hline1,'Color','r') + set(hline2,'Color','b') + grid on + + fprintf(... + 'Residuals\nAverage: %4.2f%%\nStd.:%4.2f%%\nMin.: %4.2f%%\nMax.: %4.2f%%\n',mean_res,std_res,min_res,max_res); + + set(figres,'Name','Residuals / GFP') + set(get(figres,'CurrentAxes'),'XGrid','on','YGrid','on') + + %---------------------------------------------------------------------------- + +case 'mesh_rendering' + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + if isempty(tesselation_select_win) + tesselation_select_win = open('tessellation_select.fig'); + end + + handles = guihandles(tesselation_select_win); + + set(handles.removed,'String','') + set(handles.available,'String','') + + Visu = get(DATAPLOT,'Userdata'); + if isempty(Visu) % Just Mesh rendering without any study + cd(Users.SUBJECTS); + [tessfile,tesspath] = uigetfile('*.mat','Please choose a tessellation file'); + load(fullfile(tesspath,tessfile)) + Visu.Tesselation = fullfile(tesspath,tessfile); + set(DATAPLOT,'Userdata',Visu) + set(handles.removed,'Userdata',[]) + set(handles.current_surface,'visible','off') % can't get rid of this object using GUIDE + set(handles.CurrentSurface,'String',tessfile) + else + try + load(Visu.Tesselation) + catch % Not in proper directory - try something else + cd(Users.SUBJECTS) + load(Visu.Tesselation) + end + set(handles.CurrentSurface,'String',Visu.Tesselation) + end + set(handles.light_props,'value',1) + + % How many meshes available ? + nmesh = max(size(Vertices)); + Vals = [ones(nmesh,1),zeros(nmesh,7)]; + set(handles.removed,'Userdata',Vals) + + set(handles.available,'String',Comment) + set(handles.available,'Max',length(Comment)) + + % Look for Results file in the current study folder + % Get the path + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + % Dir list and look for result files + cd(fullfile(Users.STUDIES,path)) + ResFiles = dir('*result*.mat'); + for k = 1:length(ResFiles) + ResFiles(k).name = strrep(ResFiles(k).name,'.mat',''); + end + set(handles.ResultFiles,'String',{ResFiles(:).name},'Value',1) + + + %dataplot_cb LoadResultFile + + %---------------------------------------------------------------------------- +case 'LoadResultFile' % Load selected Result File parameters for source visualization + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + + if isempty(tesselation_select_win) + tesselation_select_win = open('tessellation_select.fig'); + end + handles = guihandles(tesselation_select_win); + + set(tesselation_select_win,'Pointer','watch'),drawnow + + set(handles.ZScore,'Value',0) + dataplot_cb('ToggleButtonColor',handles.ZScore) + + if nargin == 1 + ResFiles = get(handles.ResultFiles,'String'); + ResFile = ResFiles{get(handles.ResultFiles,'Value')}; + else % A result file is specified + ResFile = varargin{1}; + end + + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + ResFile = fullfile(Users.STUDIES,path,ResFile); + Results = load(ResFile); + set(handles.Refresh,'Userdata',ResFile) + + if isfield(Results,'ZScore') + if (get(handles.Baseline,'Userdata')) == 0 + try + set(handles.Baseline,'String',num2str(1000*(Results.ZScore.BaselineTime),'%4.2f ')); + if isfield(Results.ZScore,'BaselineFile') + disp(['ZScore available - baseline taken from file: ',Results.ZScore.BaselineFile]) + else + disp(['ZScore available - baseline was set to: ', num2str(1000*Results.ZScore.BaselineTime,'%4,2f '),' ms']) + end + + catch + set(handles.Baseline,'String','File'); + end + + elseif (get(handles.Baseline,'Userdata')) == 1 + set(handles.Baseline,'String','File'); + if isfield(Results.ZScore,'BaselineFile') + disp(['ZScore available - baseline taken from file: ',Results.ZScore.BaselineFile]) + else + disp(['ZScore available - baseline was set to: ', num2str(1000*Results.ZScore.BaselineTime,'%4,2f '),' ms']) + end + + end + + end + + %Load Associated Data File + cd(fullfile(Users.STUDIES,path)) + ResFiletmp = strrep(ResFile,Users.STUDIES,''); + ResFiletmp = strrep(ResFiletmp,'.mat',''); + Iunder = findstr(ResFiletmp,'_'); + DataFile= [ResFiletmp(1:Iunder(end-1)-1),'.mat']; + + if exist(DataFile,'file') + dataplot_cb('loaddata',Users.CurrentData.StudyFile,[DataFile]); + end + + + set(handles.ResultFiles,'Userdata',Results); % Save in GUI for future use + nSources = length(Results.SourceLoc); + if nSources == 0 % Probably an ImageGrid file + nSources = size(Results.ImageGridAmp,1); + BeginTime = Results.ImageGridTime(1)*1000; + EndTime = Results.ImageGridTime(end)*1000; + set(handles.CorticalMap,'enable','on') % Allo20w visualization of cortical current density maps + else + BeginTime = []; + EndTime = []; + set(handles.CorticalMap,'enable','off') + end + + DATA = {'MEG','EEG','FUSION'}; + + if ~isfield(Results,'ZScore') + ResultFileParamString= sprintf('%s\nNumber of Sources: %d\nTime window: %3.1f %3.1f msec',... + Results.Comment,nSources,BeginTime,EndTime); + else + if ~isempty(Results.ZScore.BaselineFile) + [tmp,tmpfile,ext] = fileparts(Results.ZScore.BaselineFile); + ResultFileParamString= sprintf(... + '%s-%s\nNumber of Sources: %d\nTime window: %3.1f %3.1f msec\nZScore done: baseline from file:\n%s\n%4.1f to %4.1f ms',... + Results.Comment,DATA{Results.GUI.DataType},nSources,BeginTime,EndTime,tmpfile,1000*(Results.ZScore.BaselineTime)); + else + ResultFileParamString= sprintf(... + '%s-%s\nNumber of Sources: %d\nTime window: %3.1f %3.1f msec\nZScore done: baseline set to\n%4.1f to %4.1f ms',... + Results.Comment,DATA{Results.GUI.DataType},nSources,BeginTime,EndTime,1000*(Results.ZScore.BaselineTime)); + end + end + + + + set(handles.ResultFileParam,'String',ResultFileParamString) + + % Find the corresponding tessellated envelope in the list + nsrc = size(Results.ImageGridAmp,1); % Number of cortical sources + % Is there a cortical surface available qith the same number of sources ? + Visu = get(DATAPLOT,'Userdata'); + try + load(Visu.Tesselation,'Vertices','Comment') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Vertices','Comment') + end + + for k = 1:length(Vertices) + nverts(k) = size(Vertices{k},2); + end + clear Vertices + iCortex = find(nverts == nsrc); + if isempty(iCortex) + errordlg('No corresponding cortical surface was found among the available tessellated surfaces') + return + elseif length(iCortex)>1 + msgbox('Several tessellated surfaces may be corresponding to this result file. Please select the proper one manually') + return + end + + % Find the cortical surface is the list and mark it as selected + + set(handles.removed,'String',Comment{iCortex}) + set(handles.available,'String',Comment(setdiff(1:length(Comment),iCortex))) + + set(handles.CorticalMap,'Value',1); + Green = [.66 1 .43]; + Dark = [.4 .4 .4]; + set(handles.CorticalMap,'Backgroundcolor',Green,'Foregroundcolor',Dark) + + set(tesselation_select_win,'Pointer','arrow') + %---------------------------------------------------------------------------- +case 'mesh_props' % Indicate Mesh Surface Properties with Radiobuttons + Visu = get(DATAPLOT,'Userdata'); + % eval(['load ',Visu.Tesselation,' Comment']) + cd(Users.SUBJECTS) + load(Visu.Tesselation) + + nmesh = max(size(Comment)); + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(gcbo,'Value'); + IDs = get(gcbo,'String'); + mesh_names = IDs(removeID); + % current_surface = findobj(tesselation_select_win,'Tag','current_surface'); + % set(current_surface,'String',mesh_names{1}); + + OPAQUE = findobj(gcbf,'Tag','Opaque'); + TRANSPARENT = findobj(gcbf,'Tag','transparent'); + RIGHT = findobj(tesselation_select_win,'Tag','right'); + LEFT = findobj(tesselation_select_win,'Tag','left'); + FRONT = findobj(tesselation_select_win,'Tag','front'); + BACK = findobj(tesselation_select_win,'Tag','back'); + TOP = findobj(tesselation_select_win,'Tag','top'); + BOTTOM = findobj(tesselation_select_win,'Tag','bottom'); + + if length(removeID)>1 + return + end + + % Identification of the active mesh surfaces + for i = 1:length(removeID) + imesh(i) = find(strcmp(mesh_names{i},Comment)); + end + + if length(imesh)== 1 + set(findobj(gcbf,'Tag','faces'),'string',[int2str(size(Faces{imesh},1)),' Faces']) + set(findobj(gcbf,'Tag','vertices'),'string',[int2str(size(Vertices{imesh},2)), ' Vertices']) + if ~strcmp(get(gcbo,'Tag'),'removed'); return, end + end + + Vals = get(removed,'Userdata'); + if isempty(Vals) + Vals = [ones(nmesh,1),zeros(nmesh,7)]; + else + HANDLES = [OPAQUE TRANSPARENT RIGHT LEFT FRONT BACK TOP BOTTOM]; + for k = 1:length(HANDLES) + set(HANDLES(k),'Value',Vals(imesh,k)); + end + end + + %---------------------------------------------------------------------------- + +case 'camlight' % Add light in the tesselation window + previous = findobj(0,'Tag','tessellation_window'); + if isempty(previous) + return + end + figure(previous) + h = camlight('headlight'); + set(h,'color','w'); % mute the intensity of the lights + rotate3d on + %---------------------------------------------------------------------------- + +case 'remove_camlight' % Remove last camlight + previous = findobj(0,'Tag','tessellation_window'); + if isempty(previous) + return + end + figure(previous) + h = findobj(previous,'type','light'); + if isempty(h), return, end + delete(h(end)) + rotate3d on + %---------------------------------------------------------------------------- + +case 'mesh_vals' % Indicate Mesh Surface Properties with Radiobuttons + Visu = get(DATAPLOT,'Userdata'); + try + eval(['load ',Visu.Tesselation,' Comment']) + catch + cd(Users.SUBJECTS) + eval(['load ',Visu.Tesselation,' Comment']) + end + + nmesh = max(size(Comment)); + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + IDs = get(removed,'String'); + if iscell(IDs) + mesh_names = IDs(removeID); + else + mesh_names = IDs; + end + + + current_surface = findobj(tesselation_select_win,'Tag','current_surface'); + % set(current_surface,'String',mesh_names{1}); + + OPAQUE = findobj(gcbf,'Tag','Opaque'); + TRANSPARENT = findobj(gcbf,'Tag','transparent'); + RIGHT = findobj(tesselation_select_win,'Tag','right'); + LEFT = findobj(tesselation_select_win,'Tag','left'); + FRONT = findobj(tesselation_select_win,'Tag','front'); + BACK = findobj(tesselation_select_win,'Tag','back'); + TOP = findobj(tesselation_select_win,'Tag','top'); + BOTTOM = findobj(tesselation_select_win,'Tag','bottom'); + + % Identification of the active mesh surfaces + if ~iscell(mesh_names) + imesh = find(strcmp(mesh_names,Comment)); + else + for i = 1:length(removeID) + imesh(i) = find(strcmp(mesh_names{i},Comment)); + end + end + + + Vals = get(removed,'Userdata'); + if 0%isempty(Vals) + Vals = [ones(nmesh,1),zeros(nmesh,7)]; + else + HANDLES = [OPAQUE TRANSPARENT RIGHT LEFT FRONT BACK TOP BOTTOM]; + tmp = get(HANDLES,'Value'); + Vals(imesh,:) = [tmp{:}]; + end + + set(removed,'Userdata',Vals) + + %---------------------------------------------------------------------------- +case 'ConcatenateTess' % Concatenate 2 selected envelopes into 1 + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + Visu = get(DATAPLOT,'Userdata'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + + IDs = get(removed,'String'); + if isempty(IDs) + return + end + + mesh_names = IDs(removeID); + eval(['load ',Visu.Tesselation,' Comment']) + + nmesh = max(size(Comment)); + + % Identification of the active mesh surfaces + for i = 1:length(removeID) + imesh{i} = find(strcmp(mesh_names{i},Comment)); + end + + if length(imesh) >2 + errordlg('Cannot concatenate more than 2 envelopes yet') % CHEAT - need to generalize this + return + end + + load(Visu.Tesselation,'Faces','Vertices') + Vertices{end+1} = [Vertices{imesh{1}},Vertices{imesh{2}}] ; + Faces{end+1} = [Faces{imesh{1}}; Faces{imesh{2}}+size(Vertices{imesh{1}},2)]; + Comment{end+1} = [Comment{imesh{1}},Comment{imesh{2}}] ; + + save(Visu.Tesselation,'Faces','Vertices','Comment','-append') + + dataplot_cb mesh_rendering + + %---------------------------------------------------------------------------- + +case 'SwapFaces' % Swap vertex ordering for face definition as some pacthes normal may happen to be oriented inwards and therefore look dark in 3d + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + Visu = get(DATAPLOT,'Userdata'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + + IDs = get(removed,'String'); + if isempty(IDs) + return + end + + mesh_names = IDs(removeID); + eval(['load ',Visu.Tesselation,' Comment']) + + nmesh = max(size(Comment)); + + % Identification of the active mesh surfaces + for i = 1:length(removeID) + imesh{i} = find(strcmp(mesh_names{i},Comment)); + end + + if length(imesh) > 1 + errordlg('Cannot swap vertices of more than 1 envelope yet') % CHEAT - need to generalize this + return + end + + load(Visu.Tesselation,'Faces') + + Faces{imesh{1}} = Faces{imesh{1}}(:,[2 1 3]); + + save(Visu.Tesselation,'Faces','-append') + + dataplot_cb mesh_rendering + + + %---------------------------------------------------------------------------- + +case 'RenameTess' % Edit the Comment (ie label) of selected envelope + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + Visu = get(DATAPLOT,'Userdata'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + + IDs = get(removed,'String'); + if isempty(IDs) + return + end + + mesh_names = IDs(removeID); + eval(['load ',Visu.Tesselation,' Comment']) + + nmesh = max(size(Comment)); + + % Identification of the active mesh surfaces + for i = 1:length(removeID) + imesh{i} = find(strcmp(mesh_names{i},Comment)); + end + + if length(imesh) > 1 + errordlg('Cannot rename more than 1 envelope yet') % CHEAT - need to generalize this + return + end + + newComment = inputdlg('Please enter a new label for the selected envelope'); + if isempty(newComment) + return + end + + Comment{imesh{1}} = newComment{:}; + + save(Visu.Tesselation,'Comment','-append') + + dataplot_cb mesh_rendering + + + + %---------------------------------------------------------------------------- +case 'DownsizeTess' + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + Visu = get(DATAPLOT,'Userdata'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + + IDs = get(removed,'String'); + if isempty(IDs) + return + end + + mesh_names = IDs(removeID); + eval(['load ',Visu.Tesselation,' Comment']) + + nmesh = max(size(Comment)); + + % Identification of the active mesh surfaces + for i = 1:length(removeID) + imesh{i} = find(strcmp(mesh_names{i},Comment)); + end + + if length(imesh) > 1 + errordlg('Cannot swap vertices of more than 1 envelope yet') % CHEAT - need to generalize this + return + end + + load(Visu.Tesselation,'Faces','Vertices') + + handles = guihandles(tesselation_select_win); + nfv.faces = Faces{imesh{1}}; + nfv.vertices = Vertices{imesh{1}}'; + + set(tesselation_select_win,'Pointer','watch') + NFV = reducepatch(nfv, str2num(get(handles.DownsizeFactor,'String'))); + + clear nfv + Faces{end+1} = NFV.faces; + Vertices{end+1} = NFV.vertices'; + clear NFV + Comment{end+1} = [Comment{imesh{1}},'_',get(handles.DownsizeFactor,'String')]; + + save(Visu.Tesselation,'Faces','Comment','Vertices', '-append') + + dataplot_cb mesh_rendering + + set(tesselation_select_win,'Pointer','arrow') + %---------------------------------------------------------------------------- +case 'mesh_add' % Add a meshed surface to visualization + Visu = get(DATAPLOT,'Userdata'); + load(Visu.Tesselation) + nmesh = max(size(Vertices)); + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(available,'Value'); + + %Check if it's a double-click + old_available = get(available,'Userdata'); + if isempty(old_available) | old_available ~= removeID % Single Click + set(available,'Userdata',removeID) + return + else + set(available,'Userdata',[]) + end + + IDs = get(available,'String'); + if isempty(IDs), return, end + chan = 1:length(get(available,'String')); + + set(available,'String', IDs(setdiff(chan,removeID))); + if isempty(get(removed,'String')) + set(removed,'String', IDs(removeID)); + else + strtmp = (get(removed,'String')); + strtmp(end+1:end+length(IDs)) = IDs(removeID) ; + set(removed,'String', sort(unique(strtmp))); + end + set(available,'String', IDs(setdiff(chan,removeID))); + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + %---------------------------------------------------------------------------- + +case 'delete_tess' + % Update the tessellation file (SubjectTess) by deleting the selected surface tessellation + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(available,'Value'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs) + errordlg('Please select a Tessellation in the ''Active'' listbox') + return + end + + mesh_names = IDs(availableID); + Visu = get(DATAPLOT,'Userdata'); + eval(['load ',Visu.Tesselation,' Comment']) + nmesh = max(size(Comment)); + % Identification of the active mesh surfaces + for i = 1:length(availableID) + imesh{i} = find(strcmp(mesh_names{i},Comment)); + end + ButtonName=questdlg(['Are you sure you want to delete permanently ',[Comment{[imesh{:}]}],' from the subject tessellation file ?'], ... + 'Warning', ... + 'Yes','No','No'); + switch ButtonName, + case 'No', + return + end + + set(removed,'Value',1) + set(removed,'String',setdiff(get(removed,'String'),char(Comment{[imesh{:}]}))) + + load(Visu.Tesselation) + tmp = 1:length(Comment); + Comment = Comment(setdiff(tmp,[imesh{:}])); + Vertices = Vertices(setdiff(tmp,[imesh{:}])); + Faces= Faces(setdiff(tmp,[imesh{:}])); + + save(Visu.Tesselation,'Faces','Vertices','Comment','-append') + + %---------------------------------------------------------------------------- + +case 'mesh_lighting_props' % Set lighting to Flat/Gouraud/Phong + + TessWin = findobj(0,'Tag','tessellation_window'); % Handle to the 3D display + SlidesWin = findobj(0,'Tag','subplot_tess_window'); % Handle to the Slides or Movie Window + if ~isempty(SlidesWin) + TessWin = SlidesWin; + end + + if isempty(TessWin), return, end + TessSelect = findobj(0,'Tag','tesselation_select'); + light_props = findobj(TessSelect,'Tag','light_props'); % Handle to the lighting properties pull-down menu + tmp = get(light_props,'String'); + + + try + set(findobj(TessWin,'type','patch'),'edgelighting',tmp{get(light_props,'Value')},... + 'facelighting',tmp{get(light_props,'Value')}) + + catch + if ~isempty(findstr(tmp{get(light_props,'Value')},'Flat')) + set(findobj(TessWin,'type','patch'),... + 'facecolor','flat') + else + set(findobj(TessWin,'type','patch'),... + 'facecolor','interp') + end + + end + + + %---------------------------------------------------------------------------- + +case 'mesh_remove' % Remove a mesh surface from visualization + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + Faces = findobj(tesselation_select_win,'Tag','faces'); + + %Check if it's a double-click + old_removed = get(Faces,'Userdata'); + if isempty(old_removed) | old_removed ~= availableID % Single Click + set(Faces ,'Userdata',availableID) + return + else + set(Faces ,'Userdata',[]) + end + + IDs = get(removed,'String'); + if isempty(IDs), return, end + chan = [1:length(IDs)]; + + set(removed,'Max',max([1,length(setdiff(chan,availableID))])) + set(removed,'Value',1,'String',IDs(setdiff(chan,availableID))); + + if isempty(get(available,'String')) + set(available,'String', [IDs(availableID)]); + else + strtmp = (get(available,'String')); + strtmp(end+1:end+length(IDs)) = IDs(availableID) ; + set(available,'String', sort(unique(strtmp))); + end + set(available,'Value',1,'Max',length(get(available,'String'))) + + %---------------------------------------------------------------------------- + +case 'change_color' % Changes the color of the current mesh surface + Visu = get(DATAPLOT,'Userdata'); + eval(['load ',Visu.Tesselation,' Comment']) + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + removeID = get(removed,'Value'); + IDs = get(removed,'String'); + mesh_names = IDs(removeID); + + for i = 1:length(removeID) + imesh(i) = find(strcmp(mesh_names{i},Comment)); + end + previous = findobj(0,'Tag','tessellation_window'); + + if isempty(previous), return, end + + for k = imesh + h = findobj(previous,'Tag',Comment{k}); + corig = get(h,'Edgecolor'); + if ischar(corig) % Edgecolor 'none' + corig = get(h,'FaceVertexCdata'); + iok = find(isfinite(corig(:,1))); + corig = corig(iok,:); + corig = corig(1,:); + else + iok = []; + end + c = uisetcolor(corig, [Comment{k}, ' Color Change']); + if c == corig, return, end + + ctet = get(h,'vertices'); + vertexcolorh = get(h,'FaceVertexCData'); + siz = size(vertexcolorh,2); + if size(vertexcolorh ,1) == 1 + vertexcolorh = ones(size(ctet,1),1)*vertexcolorh; + end + if 0%size(ctet,1)~=length(iok) + vertexcolorh(tmp,:) = NaN * ones(length(tmp),siz); + end + + vertexcolorh(iok,:) = ones(length(iok),1)*c ; + set(h,'FaceVertexCData',vertexcolorh,'Userdata',c) + if isempty(iok) + set(h,'edgecolor',c) + end + + end + + %-------------------------------------------------------------------------------------------------------------------- + +case 'saveas' % Save the new data set as... + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + + Visu = get(DATAPLOT,'Userdata'); + + Data = Visu.Data; + + TASKBAR = findobj(0,'Tag','TASKBAR'); + Current = get_user_directory; + cd(Current.STUDIES) + [FILENAME, PATHNAME] = uiputfile('*data*mat', 'New File Name'); + if FILENAME == 0, return, end + cd(PATHNAME) + + [F,Device,ChannelFlag,Time,NoiseCov,SourceCov,Projector,Comment] = ... + deal(Data.F,Data.Device,Data.ChannelFlag,Data.Time,Data.NoiseCov,Data.SourceCov,Data.Projector,Data.Comment); + clear Data + save(FILENAME,'Device','ChannelFlag','F','Time','NoiseCov','SourceCov','Projector','Comment'); + + I = findstr(FILENAME,['_data']); + if isempty(I) + error('File name should contain ''_data'' string ') + return + end + + channelfile = FILENAME(1:I-1); + channelfile = [channelfile,'_channel']; + Channel = Visu.Channel; + save (channelfile,'Channel') + + %---------------------------------------------------------------------------- +case 'create_filter_window' + filter_wind = findobj(0,'Tag','filter_win'); + if isempty(filter_wind) + filter_win + end + filter_wind = findobj(0,'Tag','filter_win'); + set(0,'CurrentFigure',filter_wind) + + %---------------------------------------------------------------------------- +case 'data_filter' % Filter the data and update visualization + filter_win = findobj(0,'Tag','filter_win'); + lpf = findobj(filter_win,'Tag','LPF'); % Low Cut-off + hpf = findobj(filter_win,'Tag','HPF'); % High Cut-off + AVG = findobj(filter_win,'Tag','average'); % Remove average + lpf = str2num(get(lpf,'string')); + hpf = str2num(get(hpf,'string')); + AVG = get(AVG,'Value'); + + Visu = get(DATAPLOT,'Userdata'); + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + + if ~isempty(find(Visu.Data.ChannelFlag == -1))%~isempty(find(Visu.Data.ChannelFlag == 0)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)); % - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + %KND + goodchannels = [Visu.ChannelID{current}];% - min(Visu.ChannelID{current})+1; + badchannels = []; + end + + srate = abs(1/(Visu.Data.Time(2)-Visu.Data.Time(1))); + new_waves = zeros(size(Visu.Data.F));%Visu.ChannelID{current},:))); + %tmp = brainstorm_filt(Visu.Data.F(goodchannels+min(Visu.ChannelID{current})-1,:),srate,0,lpf); + tmp = brainstorm_filt(Visu.Data.F(goodchannels,:),srate,0,lpf); + new_waves(goodchannels,:) = tmp; clear tmp + % SB 11/10/00 back to space average which is the so-called reference in EEG + %JCM 10/27/00 changed the average to be the average in time, not space + if(1) + if 0%AVG == 1 % Remove average + new_waves(goodchannels,:) = new_waves(goodchannels,:) - repmat(mean(new_waves(goodchannels,:)),length(goodchannels),1); + end + else + if AVG == 1 % Remove average in time from each channel + AVG_MAX = Visu.Data.Time(end)*1000; % milliseconds + AVG_MIN = Visu.Data.Time(1)*1000; + prompt={'Enter the starting time (ms)','Enter the ending time (ms)'}; + def={sprintf('%g',AVG_MIN),sprintf('%g',AVG_MAX)}; + dlgTitle='Input the times to use for average removal'; + answer = inputdlg(prompt,dlgTitle,1,def); + if(isempty(answer)), + disp('Cancelled') + return + else + AVG_MIN = sscanf(answer{1},'%g'); + AVG_MAX = sscanf(answer{2},'%g'); + end + AVG_MIN = min(find(Visu.Data.Time >= AVG_MIN/1000)); % convert to index + AVG_MAX = max(find(Visu.Data.Time <= AVG_MAX/1000)); + if(isempty(AVG_MIN) | isempty(AVG_MAX)), % nothing + disp('Invalid time values') + return; + end + if(AVG_MAX < AVG_MIN), % bogus + disp('Inconsistent time values') + return; + end + + tmp = mean(new_waves(goodchannels,AVG_MIN:AVG_MAX)')'; % mean in time for each channel + new_waves(goodchannels,:) = new_waves(goodchannels,:) - tmp(:,ones(1,size(new_waves,2)),:); + end + end + % Visu.Data.F(goodchannels+min(Visu.ChannelID{current})-1 ,:) = new_waves(goodchannels,:); + Visu.Data.F(goodchannels,:) = new_waves(goodchannels,:); + Visu.Alter = 1; + + set(DATAPLOT,'Userdata',Visu); + dataplot_cb quicklook + + %---------------------------------------------------------------------------- +case 'show_fragment' + Visu = get(DATAPLOT,'Userdata'); + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + chan = [1:length(IDs)]; + + load(Visu.Tesselation,'Clusters','Comment') + + if ~exist('Clusters','var') % No fragmentation available for this tessellation file + return + end + + % Identification of the active mesh surfaces + for i = 1:length(IDs) + imesh(i) = find(strcmp(IDs(i),Comment)); + end + + Vals = get(removed,'Userdata'); + if isempty(Vals) + Vals = [ones(nmesh,1),zeros(nmesh,8)]; + end + + % Check for clusters for the current surface (highlighted surface name in the "selected text listbox") + FragmentMenu = findobj(gcbf,'Tag','FragmentMenu'); + nsurf = imesh(availableID); % Selected surface + + dataplot_cb mesh_props + + if ~exist('Clusters','var') % Classes were not defined beforehand + set(FragmentMenu,'String','No Fragmentation','Value',1); + return + end + + if isempty(Clusters{nsurf}) % No cluster available for surface 'nsurf' + set(FragmentMenu,'String','No Fragmentation','Value',1); + return + else + if isempty(Clusters{nsurf}.Seed)% No fragmentation availlable for this surface + set(FragmentMenu,'String','No Fragmentation'); + else + sstring = {'No Fragmentation'}; + for k = 1:length(Clusters{nsurf}.Seed) + sstring{k+1} = int2str(Clusters{nsurf}.Seed(k)); + end + set(FragmentMenu,'String',sstring,'Value',2) + end + end + + %---------------------------------------------------------------------------- + +case 'SelectCorticalSpot' + + TessWin = findobj(0,'tag','tessellation_window'); + if isempty(TessWin) + TessWin = open('tessellation_window.fig'); + set(TessWin,'CurrentAxes',findobj(TessWin,'Tag','MainAxis')); + end + + figure(TessWin) + hold on + + if nargin == 1 + ginput(1); + else + TessWin = (varargin{2}); + figure(TessWin) + hold on + end + + MainAxes = findobj(TessWin,'Tag','MainAxes'); + + scurrent = plot3(0,0,0,'o','parent',MainAxes,'Markersize',5,'Markerfacecolor','r'); + set(scurrent,'visible','off') + + vertices = get(findobj(MainAxes,'type','patch'),'vertices'); + % Search for intersection with cortical nodes which + % are considered as visible only, ie FVCData ~- NaN + vert_isnan = get(findobj(MainAxes,'type','patch'),'FaceVertexCdata'); + if size(vert_isnan,2) == 1 + vert_isnan = find(~isnan(vert_isnan)); + else + vert_isnan = sum(vert_isnan ,2); + vert_isnan = find(~isnan(vert_isnan)); + end + + vertices = vertices(vert_isnan,:); + + x = vertices(:,1)'; + y = vertices(:,2)'; + z = vertices(:,3)'; + clear vertices + + if nargin == 1 % Vertex selection from a manual probe + + % Calcul de la distance minimale du cortex a la droite C + C = get(MainAxes,'Currentpoint'); + + % Vecteur directeur du rayon d'observation + u = (C(1,:)-C(2,:))'/norm(C(1,:)-C(2,:)); + + algo = 'new'; + if algo == 'old' + %% --------- Ancien algo + + normals = get(cortex,'Userdata'); + scalaire = normals*u'; + %%clear normals + %inorm = find(scalaire > mean(scalaire)+std(scalaire)/2); + %inorm = find(scalaire >= 0); + inorm = 1:length(scalaire); + + tempo = [C(1,1)-x(inorm);C(1,2)-y(inorm);C(1,3)-z(inorm)]; + distboite = norcol(tempo); + [minn,im] = min(distboite); + %% ------------------------ + else + %% ----------- Nouvel algo + inorm= 1:length(x); + tempo1 = [C(1,1)-x(inorm);C(1,2)-y(inorm);C(1,3)-z(inorm)]; + DIR = u * ones(1,length(inorm)); + tempo = cross(tempo1,DIR); + clear DIR + distdroite = norcol(tempo); + distboite = norcol(tempo1); + distdroite = distdroite/max(distdroite); + distboite = distboite/max(distboite); + [minn,im] = min(.04*distboite+0.96*distdroite); + clear tempo tempo1 + %% ----------- + end % algo + + clear tempo + + % Affiche source courante + + else % Point location is passed as an argument + inorm= 1:length(x); + im = varargin{1}; + end + + set(scurrent,'Xdata',x(inorm(im)),'Ydata',y(inorm(im)),'Zdata',z(inorm(im))) + drawnow + + set(scurrent,'visible','on') + if isempty(im) + warndlg('Please reselect your location','Location error') + end + + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + if isempty(TessWinUserData) + TessWinUserData = struct('CorticalSpots',[],'CorticalMarkers',[],'CorticalMarkersLabels',[]); + elseif ~isfield(TessWinUserData, 'CorticalSpots') + TessWinUserData.CorticalSpots = []; + TessWinUserData.CorticalMarkers = []; + TessWinUserData.CorticalMarkersLabels = []; + end + + % TessWinUserData.CorticalSpots = [TessWinUserData.CorticalSpots,inorm(im)]; + TessWinUserData.CorticalSpots = [TessWinUserData.CorticalSpots,vert_isnan(inorm(im))]; + if size(TessWinUserData.CorticalMarkers,1) > 1 + TessWinUserData.CorticalMarkers = TessWinUserData.CorticalMarkers'; + end + + TessWinUserData.CorticalMarkers = [TessWinUserData.CorticalMarkers,scurrent]; + + htext = text(1.05*x(inorm(im)),1.05*y(inorm(im)),1.05*z(inorm(im)),int2str(length(TessWinUserData.CorticalSpots))); + set(htext,'FontWeight','normal','color','g','Fontname','helvetica','Fontsize',10,'FontUnits','Point') + + TessWinUserData.CorticalMarkersLabels = [TessWinUserData.CorticalMarkersLabels,htext]; + + set(TessWin,'Userdata',TessWinUserData); + + CorticalSpotList = cell(length(TessWinUserData.CorticalSpots),1); + for k = 1:length(TessWinUserData.CorticalSpots) + CorticalSpotList{k} = k; + end + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + if length(CorticalSpotList) == 1 + set(hTessSelect.CorticalSpotList,'String',{get(TessWinUserData.CorticalMarkersLabels,'string')}... + ,'Max',length(CorticalSpotList),'Value',1) + else + set(hTessSelect.CorticalSpotList,'String',get(TessWinUserData.CorticalMarkersLabels,'string')... + ,'Max',length(CorticalSpotList),'Value',1) + end + + rotate3d on + + + %---------------------------------------------------------------------------- +case 'DeleteCorticalSpot' + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); + + AreaLabels = get(hTessSelect.CorticalSpotList,'String'); + + % Update label information + ResidualAreas = setdiff([1:length(AreaLabels)],SelectedArea); + + set(hTessSelect.CorticalSpotList,'String',AreaLabels(ResidualAreas),'Value',1,'Max',length(AreaLabels)); + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + TessWinUserData.CorticalSpots = TessWinUserData.CorticalSpots(ResidualAreas); + delete(TessWinUserData.CorticalMarkers(SelectedArea)) + delete(TessWinUserData.CorticalMarkersLabels(SelectedArea)) + TessWinUserData.CorticalMarkers = TessWinUserData.CorticalMarkers(ResidualAreas); + TessWinUserData.CorticalMarkersLabels = TessWinUserData.CorticalMarkersLabels(ResidualAreas); + + set(TessWin,'Userdata',TessWinUserData); + + %---------------------------------------------------------------------------- + +case 'ImportScoutsFromMRI' % Create a scout file from points selected in the MR + + TessWin = findobj(0,'tag','tessellation_window'); + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + + cd(Users.STUDIES); + [filename, pathname] = uigetfile('*.txt', 'Select an MRI Point File'); + if filename == 0, return, end + CorticalScouts = struct('MarkersLabels','','CorticalSpots',[],'CorticalMarkers',[]); + + [Number,CorticalScouts.CorticalMarkersLabels,X,Y,Z,Xmri,Ymri,Zmri] = ... + textread(fullfile(pathname,filename),'%d %s %f %f %f %f %f %f',-1); + clear Number Xmri Ymri Zmri + + % What's the name of the current cortical envelope ? + ActiveTess = get(hTessSelect.removed,'String'); % Find the active Cortical surface + iCortex = get(hTessSelect.removed,'Value'); + if iscell(ActiveTess) + ActiveTess= ActiveTess{iCortex}; + end + + % What's the name of the current data set ? + ResultFiles = get(hTessSelect.ResultFiles,'String'); + ResultFile = ResultFiles{get(hTessSelect.ResultFiles,'Value')}; + + % XYZ Coordinates of the scouts + Visu = get(DATAPLOT,'Userdata'); + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment','Vertices') + % What's the current surface ? + imesh = find(strcmp(Comment,ActiveTess)); + Vertices = Vertices{imesh}; + X = X/1000; + Y = Y/1000; + Z = Z/1000; + + for k = 1:length(X) % Find closest vertex in the tessellation + [mm CorticalScouts.CorticalSpots(k)] = min(norcol(... + [Vertices(1,:)-X(k); ... + Vertices(2,:)-Y(k); ... + Vertices(3,:)- Z(k)])); + CorticalScouts.CorticalMarkers(k,:) = Vertices(:,CorticalScouts.CorticalSpots(k))'; + end + CorticalScouts.CorticalMarkers = Vertices(:,CorticalScouts.CorticalSpots)'; + clear Vertices + + CorticalScouts + + % Create Cortical Scout File + cd(Users.STUDIES); + [filename, pathname] = uiputfile(['CorticalScoutFromMRI.mat'], 'Save Cortical Scout in...'); + save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat'); + + % Visualization + dataplot_cb('LoadCorticalSpot',fullfile(pathname,filename)) + + + %---------------------------------------------------------------------------- + +case 'CorticalScoutFromThres' % Create a cortical scout file with areas above a given %-threshold + TessWin = findobj(0,'tag','tessellation_window'); + CorticalScouts = get(TessWin,'Userdata'); + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + + % Let's do it simple first + Results = get(hTessSelect.ResultFiles,'Userdata'); + M = max(abs(Results.ImageGridAmp),[],2); % Take maximum over time + MAX = max(M); + cThres = str2num(get(hTessSelect.TruncateFactor,'string'))/100; + + % Indices of the sources above threshold + CorticalScouts.CorticalSpots = find(M >= cThres*MAX); + + + % What's the name of the current cortical envelope ? + ActiveTess = get(hTessSelect.removed,'String'); % Find the active Cortical surface + iCortex = get(hTessSelect.removed,'Value'); + if iscell(ActiveTess) + ActiveTess= ActiveTess{iCortex}; + end + + % XYZ Coordinates of the scouts + Visu = get(DATAPLOT,'Userdata'); + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment','Vertices') + % What's the current surface ? + imesh = find(strcmp(Comment,ActiveTess)); + Vertices = Vertices{imesh}; + CorticalScouts.CorticalMarkers = Vertices(:,CorticalScouts.CorticalSpots)'; + clear Vertices + for k =1 : length(CorticalScouts.CorticalSpots) + CorticalScouts.CorticalMarkersLabels{k} = int2str(k); + end + + + % What's the name of the current data set ? + ResultFiles = get(hTessSelect.ResultFiles,'String'); + ResultFile = ResultFiles{get(hTessSelect.ResultFiles,'Value')}; + + cd(Users.STUDIES) + dirr = fileparts(Users.CurrentData.StudyFile); + cd(dirr); + + % Create Cortical Scout File + [filename, pathname] = uiputfile(['CorticalScoutFromThresh_',get(hTessSelect.TruncateFactor,'string'),'.mat'], 'Save Cortical Scout in...'); + save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat'); + + % Visualization + dataplot_cb('LoadCorticalSpot',fullfile(pathname,filename)) + + + %---------------------------------------------------------------------------- + +case 'LoadCorticalSpot' % Load cortical scout locations + TessWin = findobj(0,'tag','tessellation_window'); + + if nargin == 1 + + CorticalScouts = get(TessWin,'Userdata'); + if ~isempty(CorticalScouts) % some exist - remove + if isfield(CorticalScouts,'CorticalMarkers') + delete(CorticalScouts.CorticalMarkers) + delete(CorticalScouts.CorticalMarkersLabels) + clear CorticalScouts + end + end + + cd(Users.STUDIES) + dirr = fileparts(Users.CurrentData.StudyFile); + cd(dirr); + + [filename, pathname] = uigetfile('CorticalScout.mat', 'Save Cortical Scout in...'); + if filename == 0 + return + end + load(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat'); + else + load(varargin{1}, 'ResultFile','ActiveTess','CorticalScouts','-mat'); + end + + figure(TessWin), hold on + MainAxes = findobj(TessWin,'Tag','MainAxes'); + vertices = get(findobj(MainAxes,'type','patch'),'vertices'); + x = vertices(:,1)'; + y = vertices(:,2)'; + z = vertices(:,3)'; + clear vertices + + CorticalScouts.CorticalMarkers = zeros(length(CorticalScouts.CorticalSpots),1); + for k = 1:length(CorticalScouts.CorticalSpots) + scurrent = plot3(0,0,0,'o','parent',MainAxes,'Markersize',5,'Markerfacecolor','r'); + set(scurrent,'visible','off') + set(scurrent,'Xdata',x(CorticalScouts.CorticalSpots(k)),... + 'Ydata',y(CorticalScouts.CorticalSpots(k)),... + 'Zdata', z(CorticalScouts.CorticalSpots(k))) + set(scurrent,'visible','on') + CorticalScouts.CorticalMarkers(k) = scurrent; + + r_text =1.1; + + if iscell(CorticalScouts.CorticalMarkersLabels) + htext = text(r_text*x(CorticalScouts.CorticalSpots(k)),... + r_text*y(CorticalScouts.CorticalSpots(k)),... + r_text*z(CorticalScouts.CorticalSpots(k)),... + CorticalScouts.CorticalMarkersLabels{k}); + else + htext = text(r_text*x(CorticalScouts.CorticalSpots(k)),... + r_text*y(CorticalScouts.CorticalSpots(k)),... + r_text*z(CorticalScouts.CorticalSpots(k)),... + CorticalScouts.CorticalMarkersLabels); + + end + + + set(htext,'FontWeight','normal','color','g','Fontname','helvetica',... + 'Fontsize',10,'FontUnits','Point') + + Label_tmp(k) = htext; + end + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + set(hTessSelect.CorticalSpotList,'String',CorticalScouts.CorticalMarkersLabels,... + 'Value',1,'Max', length(CorticalScouts.CorticalMarkersLabels)) + + CorticalScouts.CorticalMarkersLabels = Label_tmp; clear Label_tmp; + + set(TessWin,'Userdata',CorticalScouts); + + figure(TessWin) + rotate3d on + + %---------------------------------------------------------------------------- +case 'SaveCorticalSpot' % Save cortical scout locations + % Cortical scouts need to be indexed with both the corresponding cortical surface name + % and the current data set name + + TessWin = findobj(0,'tag','tessellation_window'); + CorticalScouts = get(TessWin,'Userdata'); + + CorticalScouts.CorticalMarkersLabels = get(CorticalScouts.CorticalMarkersLabels,'String'); + CorticalScouts.CorticalMarkers = [get(CorticalScouts.CorticalMarkers,'Xdata');... + get(CorticalScouts.CorticalMarkers,'Ydata');... + get(CorticalScouts.CorticalMarkers,'Zdata')]; + if iscell( CorticalScouts.CorticalMarkers) + CorticalScouts.CorticalMarkers = [CorticalScouts.CorticalMarkers{:}]; + end + + CorticalScouts.CorticalMarkers = reshape(CorticalScouts.CorticalMarkers,length(CorticalScouts.CorticalMarkersLabels),3); + % CorticalScouts.CorticalMarkers is now Number of Scouts x 3 + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hSelect = guihandles(tesselation_select_win); + + % What's the name of the current cortical envelope ? + ActiveTess = get(hSelect.removed,'String'); % Find the active Cortical surface + iCortex = get(hSelect.removed,'Value'); + if iscell(ActiveTess) + ActiveTess= ActiveTess{iCortex}; + end + + if isfield(CorticalScouts,'CorticalProbePatches') % Process members of cortical patches to get their x,y,z's + Visu = get(DATAPLOT,'Userdata'); + try + load(Visu.Tesselation,'Comment','Vertices') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment','Vertices') + end + % What's the current surface ? + imesh = find(strcmp(Comment,ActiveTess)); + Vertices = Vertices{imesh}; + CorticalScouts.CorticalProbePatchesXYZ = cell(size(CorticalScouts.CorticalProbePatches)); + for k=1:length(CorticalScouts.CorticalProbePatches) % for each area + CorticalScouts.CorticalProbePatchesXYZ{k} = ... + Vertices(:,CorticalScouts.CorticalProbePatches{k}); + end + + end + + % What's the name of the current data set ? + ResultFiles = get(hSelect.ResultFiles,'String'); + ResultFile = ResultFiles{get(hSelect.ResultFiles,'Value')}; + + cd(Users.STUDIES) + dirr = fileparts(Users.CurrentData.StudyFile); + cd(dirr); + + [filename, pathname] = uiputfile('CorticalScout.mat', 'Save Cortical Scout in...'); + save(fullfile(pathname,filename), 'ResultFile','ActiveTess','CorticalScouts','-mat'); + + %---------------------------------------------------------------------------- +case 'RenameCorticalSpot' + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); + SelectedArea = SelectedArea(1); % only one at a time please + + AreaLabels = get(hTessSelect.CorticalSpotList,'String'); + + Title = ''; + Prompt = sprintf('Please enter a new label for %s',AreaLabels{SelectedArea}); + newLabel = inputdlg(Prompt,Title); + if isempty(newLabel), return, end + + AreaLabels{SelectedArea} = newLabel{:} ; + + set(hTessSelect.CorticalSpotList,'String',AreaLabels) + + TessWin = findobj(0,'tag','tessellation_window'); + TessWinUserData = get(TessWin,'Userdata'); + set(TessWinUserData.CorticalMarkersLabels(SelectedArea),'String',newLabel{:}) + set(TessWin,'Userdata',TessWinUserData); + + %---------------------------------------------------------------------------- +case 'ZScoreThreshold' + %Thresholded ZScore map in terms of multiples of sigmas in the baseline + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + TessWin = findobj(0,'tag','tessellation_window'); + %if isempty(TessWin), return, end + %hTessWin = guihandles(TessWin); + + %TessWinUserData = get(TessWin,'Userdata'); + + % Are we switching from ZScore to Absolute mapping or vice-versa ? + Results = get(hTSelect.ResultFiles,'Userdata'); + set(hTSelect.AbsoluteCurrent,'Value',1) + + switch get(hTSelect.ZScoreThresholdApply,'Value') + case 1 % Switch to ZScore map and threshold it + if isempty(Results), return, end % No results were loaded + + if ~isfield(Results,'ZScore') % No ZScore was defined beforehand + dataplot_cb ZScore % Compute the ZScore map + Results = get(hTSelect.ResultFiles,'Userdata'); + end + + set(hTSelect.ZScore,'Value',1); + dataplot_cb('ToggleButtonColor',hTSelect.ZScore) + + ZThres = str2num(get(hTSelect.ZScoreThreshold,'String')); + if isempty(ZThres) + set(hTSelect.ZScoreThreshold,'String',2); % Apply Default + ZThres = str2num(get(hTSelect.ZScoreThreshold,'String')); + end + + Results.ZScore.ImageGridZ.ZThres = ZThres; + + set(hTSelect.ZScoreThreshold,'Userdata',ZThres / max(Results.ImageGridAmp(:))) + + case 0 + % Don't apply thresholded map + set(hTSelect.ZScoreThreshold,'Userdata',0) + + end + + + %Results.ImageGridAmp(iZeroed) = eps ; %Thresholded Map + + % Update display + set(hTSelect.ResultFiles,'Userdata',Results); + + dataplot_cb ScaleColormap + %dataplot_cb tesselation_select_done + %---------------------------------------------------------------------------- +case 'IntegSTHistogram' % Integrate Saptio-temporal histogram overtime + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + + avResults = get(hTSelect.ResultFiles,'Userdata'); + if ~isfield(avResults,'HistoSrc'), return, end % This is not an histogram result set + + % Integrate over time + figure, imagesc(avResults.ImageGridTime, 1:size(avResults.ImageGridAmp,1),avResults.ImageGridAmp) + colorbar + avResults.ImageGridAmp = max(avResults.ImageGridAmp,[],2) *ones(1,size(avResults.ImageGridAmp,2)); + + + set(hTSelect.ResultFiles,'Userdata',avResults); + + + %---------------------------------------------------------------------------- + +case 'STHistogram' % Spatio-temporal histogram of activations (in terms of ZScore) on a series of result files + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + + % Look for Results file in the current study folder + % Get the path + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + % Dir list and look for result files + cd(fullfile(Users.STUDIES,path)) + ResFiles = dir('*result*.mat'); + for k = 1:length(ResFiles) + ResFiles(k).name = strrep(ResFiles(k).name,'.mat',''); + end + [ResSelect,ok] = listdlg('Liststring',{ResFiles.name},'Selectionmode','multiple','Name','Please select one or sevral result files',... + 'listsize',[400 400]); + + if ok == 0 + return + end + + hw = waitbar(0,['Computing the spatio-temporal histogram of activation maps through a set of ',int2str(length(ResSelect)),' result files...']); + nDataFiles = 0; + + % Get Value for Z threshold + ZThres = str2num(get(hTSelect.ZScoreThreshold,'String')); + if isempty(ZThres) + set(hTSelect.ZScoreThreshold,'String',2); % Apply Default + ZThres = str2num(get(hTSelect.ZScoreThreshold,'String')); + end + + + for k = 1:length(ResSelect) + dataplot_cb('LoadResultFile',ResFiles(ResSelect(k)).name) + ResFiles(ResSelect(k)).name + Results = get(hTSelect.ResultFiles,'Userdata'); + + if k == 1 + avResults = Results; + avResults.ImageGridAmp = 0* avResults.ImageGridAmp; % ImageGridAmp becomes a hit-count table - + % cell (i,j) will indicate how many times source i had a ZScore > ZThres at time j + + avResults.HistoSrc = cell(length(ResSelect)); + end + + if isfield(Results,'ZScore') + +% % Adapt length to the length of shortest result file +% cropMin = 0; +% cropMax = 0; +% if Results.Time(1) > avResults.Time(1) +% cropMin = Results.Time(1)-avResults.Time(1); +% avResults.ImageGridAmp = avResults.ImageGridAmp(:,cropMin+1:end); +% avResults.ImageGridTime = avResults.ImageGridTime(:,cropMin+1:end); +% avResults.Fsynth = avResults.Fsynth(:,cropMin+1:end); +% avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp(:,cropMin+1:end); +% +% end +% if Results.Time(1) < avResults.Time(1) +% cropMin = -Results.Time(1)+avResults.Time(1); +% % Results.ImageGridAmp = Results.ImageGridAmp(:,cropMin+1:end); +% Results.ZScore.ImageGridZ.Amp = Results.ZScore.ImageGridZ.Amp(:,cropMin+1:end); +% Results.Time = Results.Time(cropMin+1:end); +% end +% if Results.Time(end) > avResults.Time(end) +% cropMax = Results.Time(end)-avResults.Time(end); +% % Results.ImageGridAmp = Results.ImageGridAmp(:,1:end-cropMax); +% Results.ZScore.ImageGridZ.Amp = Results.ZScore.ImageGridZ.Amp(:,1:end-cropMax); +% Results.Time = Results.Time(1:end-cropMax); +% end +% if Results.Time(end) < avResults.Time(end) +% cropMax = -Results.Time(end)+avResults.Time(end); +% avResults.ImageGridAmp = avResults.ImageGridAmp(:,1:end-cropMax); +% avResults.ImageGridTime = avResults.ImageGridTime(:,1:end-cropMax); +% avResults.Fsynth = avResults.Fsynth(:,1:end-cropMax); +% avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp(:,1:end-cropMax); +% end +% + avResults.Time = Results.Time; + + Results.ZScore.ImageGridZ.Amp = (Results.ImageGridAmp)-repmat(Results.ZScore.ImageGridZ.mean,1,size(Results.ImageGridAmp,2)); + iStd = spdiags(1./Results.ZScore.ImageGridZ.std, 0, length(Results.ZScore.ImageGridZ.std), length(Results.ZScore.ImageGridZ.std)) ; + Results.ZScore.ImageGridZ.Amp = abs(iStd*Results.ZScore.ImageGridZ.Amp); + + avResults.HistoSrc{k} = sparse(Results.ZScore.ImageGridZ.Amp > ZThres); + % avResults.HistoSrc{k} stores the source indices and time where sources had greater ZScore that ZThres + avResults.ImageGridAmp = avResults.ImageGridAmp + avResults.HistoSrc{k} ; + + if k == 1 + prev = figure; + end + + nDataFiles = nDataFiles + 1; + k + figure(prev) + plot(avResults.ImageGridTime, sum(avResults.HistoSrc{k},1)) + + + else % No ZScore available - skip file + + disp([ResFiles(ResSelect(k)).name,' does not contain any ZScore map - skip file']) + + end + + waitbar(k/length(ResSelect)) + + end + + avResults.ImageGridAmp = 100*avResults.ImageGridAmp/nDataFiles; % Scale to 100% hits + + cd(Users.STUDIES); + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + c = clock; + ResFiletmp = strrep(ResFiles(ResSelect(end)).name,Users.STUDIES,''); + ResFiletmp = strrep(ResFiletmp,'.mat',''); + Iunder = findstr(ResFiletmp,'_'); + DataFile= [ResFiletmp(1:Iunder(end)-1)]; + + newname = ([DataFile sprintf('_HISTO_%02.0f%02.0f',c(4:5)) ext]); + i = 0; + while(exist(newname,'file')), + i = i+1; % subtract another minute + c(5) = mod(c(5) - 1,60); + newname = ([DataFile sprintf('_HISTO_%02.0f%02.0f',MethodeCode,c(4),c(5)) ext]); + end + + save_fieldnames(avResults,newname) + + delete(hw) + + msgbox(['Average activation maps saved in ', newname]) + set(hTSelect.ResultFiles,'Userdata',avResults) + + % Refresh results list + dataplot_cb mesh_rendering + ResFiles = get(hTSelect.ResultFiles,'String'); + iFile = find(strcmp(ResFiles,strrep(newname,'.mat',''))); + set(hTSelect.ResultFiles,'Value',iFile) + + + + %---------------------------------------------------------------------------- + +case 'AverageMaps' % Average activations across multiple result files + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + + % Look for Results file in the current study folder + % Get the path + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + % Dir list and look for result files + cd(fullfile(Users.STUDIES,path)) + ResFiles = dir('*result*.mat'); + for k = 1:length(ResFiles) + ResFiles(k).name = strrep(ResFiles(k).name,'.mat',''); + end + [ResSelect,ok] = listdlg('Liststring',{ResFiles.name},'Selectionmode','multiple','Name','Please select one or sevral result files',... + 'listsize',[400 400]); + + if ok == 0 + return + end + + % Now compute ZScore for each of the selected files + hw = waitbar(0,['Averaging activation maps through a set of ',int2str(length(ResSelect)),' result files...']); + for k = 1:length(ResSelect) + dataplot_cb('LoadResultFile',ResFiles(ResSelect(k)).name) + ResFiles(ResSelect(k)).name + Results = get(hTSelect.ResultFiles,'Userdata'); + + if k == 1 + avResults = Results; + avResults.ImageGridAmp = avResults.ImageGridAmp/length(ResSelect); + end + + % !!!!!!Suppose all result files were computed on the same time window - discard what's commented below + +% % Adapt length to the length of shortes result file +% cropMin = 0; +% cropMax = 0; +% if Results.Time(1) > avResults.Time(1) +% cropMin = Results.Time(1)-avResults.Time(1); +% avResults.ImageGridAmp = avResults.ImageGridAmp(:,cropMin+1:end); +% avResults.ImageGridTime = avResults.ImageGridTime(:,cropMin+1:end); +% avResults.Time = avResults.Time(:,cropMin+1:end); +% avResults.Fsynth = avResults.Fsynth(:,cropMin+1:end); +% +% if isfield(Results,'ZScore') +% avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp(:,cropMin+1:end); +% end +% end +% if Results.Time(1) < avResults.Time(1) +% cropMin = -Results.Time(1)+avResults.Time(1); +% Results.ImageGridAmp = Results.ImageGridAmp(:,cropMin+1:end); +% Results.ImageGridTime = Results.ImageGridTime(:,cropMin+1:end); +% Results.Time = Results.Time(:,cropMin+1:end); +% if isfield(Results,'ZScore') +% Results.ZScore.ImageGridZ.Amp = Results.ZScore.ImageGridZ.Amp(:,cropMin+1:end); +% end +% end +% if Results.Time(end) > avResults.Time(end) +% cropMax = Results.Time(end)-avResults.Time(end); +% Results.ImageGridAmp = Results.ImageGridAmp(:,1:end-cropMax); +% Results.ImageGridTime = Results.ImageGridTime(:,1:end-cropMax); +% Results.Time = Results.Time(:,1:end-cropMax); +% if isfield(Results,'ZScore') +% Results.ZScore.ImageGridZ.Amp = Results.ZScore.ImageGridZ.Amp(:,1:end-cropMax); +% end +% end +% if Results.Time(end) < avResults.Time(end) +% cropMax = -Results.Time(end)+avResults.Time(end); +% avResults.ImageGridAmp = avResults.ImageGridAmp(:,1:end-cropMax); +% avResults.ImageGridTime = avResults.ImageGridTime(:,1:end-cropMax); +% avResults.Fsynth = avResults.Fsynth(:,1:end-cropMax); +% avResults.Time = avResults.Time(:,1:end-cropMax); +% if isfield(Results,'ZScore') +% avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp(:,1:end-cropMax); +% end +% end + + if k == 1 + prev = figure; + if isfield(Results,'ZScore') + Results.ZScore.ImageGridZ.Amp = (Results.ImageGridAmp)-repmat(Results.ZScore.ImageGridZ.mean,1,size(Results.ImageGridAmp,2)); + iStd = spdiags(1./Results.ZScore.ImageGridZ.std, 0, length(Results.ZScore.ImageGridZ.std), length(Results.ZScore.ImageGridZ.std)) ; + Results.ZScore.ImageGridZ.Amp = abs(iStd*Results.ZScore.ImageGridZ.Amp); + end + end + + if k >1 + avResults.ImageGridAmp = avResults.ImageGridAmp + (Results.ImageGridAmp)/length(ResSelect); + if isfield(Results,'ZScore') + avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp + (Results.ZScore.ImageGridZ.Amp)/length(ResSelect); + end + end + figure(prev) + plot(Results.ImageGridTime,mean(abs(Results.ImageGridAmp),1),'b'), hold on + plot(avResults.ImageGridTime,mean(abs(avResults.ImageGridAmp),1),'r'), hold off + + waitbar(k/length(ResSelect)) + + end + + %avResults.ImageGridAmp = avResults.ImageGridAmp/length(ResSelect); +% if isfield(avResults,'ZScore') +% avResults.ZScore.ImageGridZ.Amp = avResults.ZScore.ImageGridZ.Amp/length(ResSelect); +% end + + cd(Users.STUDIES); + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + c = clock; + ResFiletmp = strrep(ResFiles(ResSelect(end)).name,Users.STUDIES,''); + ResFiletmp = strrep(ResFiletmp,'.mat',''); + Iunder = findstr(ResFiletmp,'_'); + DataFile= [ResFiletmp(1:Iunder(end-1)-1)]; + + newname = ([DataFile sprintf('_AVRresults_%02.0f%02.0f',c(4:5)) ext]); + i = 0; + while(exist(newname,'file')), + i = i+1; % subtract another minute + c(5) = mod(c(5) - 1,60); + newname = ([DataFile sprintf('_AVRresults_%02.0f%02.0f',MethodeCode,c(4),c(5)) ext]); + end + + save_fieldnames(avResults,newname) + + delete(hw) + + msgbox(['Average activation maps saved in ', newname]) + set(hTSelect.ResultFiles,'Userdata',avResults) + + % Refresh results list + dataplot_cb mesh_rendering + ResFiles = get(hTSelect.ResultFiles,'String'); + iFile = find(strcmp(ResFiles,strrep(newname,'.mat',''))); + set(hTSelect.ResultFiles,'Value',iFile) + + %---------------------------------------------------------------------------- + +case 'DefineBaseline' + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + set(hTSelect.ZScore,'Value',1) + dataplot_cb('ToggleButtonColor',hTSelect.ZScore) + + if ~strcmp(get(hTSelect.Baseline,'String'),'File') + set(hTSelect.Baseline,'Userdata',0) % FLAG: Baseline defined on current file + end + + dataplot_cb('ZScore',1) % Force ZScore computation + + %---------------------------------------------------------------------------- + +case 'LoadBaseline' % Define Baseline from a different result file + cd(Users.STUDIES) + [resfile, respath] = uigetfile('*result*.mat','Please Select a Result File Containing the Activation Baseline'); + if resfile == 0, return, end + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + set(hTSelect.LoadBaseline,'userdata',fullfile(respath, resfile)); + set(hTSelect.Baseline,'String','File'); + set(hTSelect.Baseline,'Userdata',1) % FLAG: Baseline defined on a pre-loaded file + + dataplot_cb DefineBaseline + + %---------------------------------------------------------------------------- +case 'ZScoreBatch' % Compute ZScore on a set of Result files + + % Look for Results file in the current study folder + % Get the path + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + % Dir list and look for result files + cd(fullfile(Users.STUDIES,path)) + ResFiles = dir('*result*.mat'); + for k = 1:length(ResFiles) + ResFiles(k).name = strrep(ResFiles(k).name,'.mat',''); + end + [ResSelect,ok] = listdlg('Liststring',{ResFiles.name},'Selectionmode','multiple','Name','Please select one or sevral result files',... + 'listsize',[400 400]); + + if ok == 0 + return + end + + % Now compute ZScore for each of the selected files + hw = waitbar(0,['Computing ZScore for the selected set of ',int2str(length(ResSelect)),' result files...']); + for k = 1:length(ResSelect) + dataplot_cb('LoadResultFile',ResFiles(ResSelect(k)).name) + ResFiles(ResSelect(k)).name + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + set(hTSelect.ZScore,'Value',1) + dataplot_cb('ToggleButtonColor',hTSelect.ZScore) + dataplot_cb('ZScore',1) % Force the computation of the ZScore for each of the file (ie force test to 1 in dataplot_cb ZScore) + waitbar(k/length(ResSelect)) + end + set(hTSelect.Baseline,'Userdata',0) + + delete(hw) + + %---------------------------------------------------------------------------- +case 'ZScore' % Switches from Z-Score to Absolute current density mapping + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTSelect = guihandles(tesselation_select_win); + TessWin = findobj(0,'tag','tessellation_window'); + + switch get(hTSelect.ZScore,'Value') + case 1 % Switch to ZScore map + + % Are we switching from ZScore to Absolute mapping or vice-versa ? + set(hTSelect.AbsoluteCurrent,'Value',1) + + if get(hTSelect.Baseline,'Userdata') == 1 % Baseline is defined from an existing result file, load it + Results = load(get(hTSelect.LoadBaseline,'Userdata')); + FlagBaselineFile = 1; + else % else use current loaded results + Results = get(hTSelect.ResultFiles,'Userdata'); + FlagBaselineFile = 0; + end + + if isempty(Results), return, end % No results were loaded + + test = 0; % By default, consider not computing a new ZScore - check if a previously computation is available - + % if test is set to 1 anytime below, this will conduct to a new ZScore computation either because the baseline has changed + % or the computation is conducted on a new set of data. + if nargin == 1 + varargin{1} = 0; + end + + if (~isfield(Results,'ZScore') | varargin{1} == 1) % No ZScore was defined beforehand or computation is forced + Results.ZScore.Baseline = [-Inf Inf]; % Dummy Score + test = 1; % Force ZScore computation + end + + %Get baseline time limits + if FlagBaselineFile == 1 + set(hTSelect.Baseline,'String',... + [num2str(Results.ImageGridTime(1)*1000,'%3.1f'),' ',num2str(Results.ImageGridTime(end)*1000,'%3.1f')]); + + baseline = [Results.ImageGridTime(1) Results.ImageGridTime(end)]; + else + baseline = str2num(get(hTSelect.Baseline,'String'))/1000; + end + + if length(baseline) < 2 + errordlg('Please enter 2 time values to define the baseline interval') + return + end + + if isfield(Results.ZScore,'FlagBaselineFile') % Was this ZScore computed from a stored baseline ? + if Results.ZScore.FlagBaselineFile == 0 % No - check new baseline limits + % Get exact time samples closest to these values + if round(1000*baseline(1)) < round(1000*Results.ImageGridTime(1)) | round(1000*baseline(2)) > round(1000*Results.ImageGridTime(end)) % Accuracy set to the ms + errordlg('Please set baseline time extremas within the available time window for this result file') + return + end + + [tmp, tmin] = min(abs(Results.ImageGridTime-baseline(1))); + [tmp, tmax] = min(abs(Results.ImageGridTime-baseline(2))); + + baseline_new = [tmin tmax]; + + test = (sum(baseline_new == ... + Results.ZScore.Baseline) ~= 2); % New baseline requested - recompute Z-Score + + elseif test ~= 1 % Yes - Baseline was stored in a file - do not recompute the ZScore + + [tmp, tmin] = min(abs(Results.ImageGridTime-baseline(1))); + [tmp, tmax] = min(abs(Results.ImageGridTime-baseline(2))); + + test = 0; + + elseif varargin{1} == 1 % Force computation + [tmp, tmin] = min(abs(Results.ImageGridTime-baseline(1))); + [tmp, tmax] = min(abs(Results.ImageGridTime-baseline(2))); + + test = 1; + + end + + else + [tmp, tmin] = min(abs(Results.ImageGridTime-baseline(1))); + [tmp, tmax] = min(abs(Results.ImageGridTime-baseline(2))); + + test = 1; + end + + if 1%test + + set(tesselation_select_win,'Pointer','watch') + + disp('Computing a new Z-Score map from this baseline...'), drawnow + + disp(sprintf('Baseline is %d time samples large (out of %d samples available)',... + tmax-tmin+1, length(Results.ImageGridTime))) + + % Store original results patter in memory + if 1%(~isfield(Results,'ImageGridAmpOrig') & FlagBaselineFile == 0) | varargin{1} == 1 + Results.ImageGridAmpOrig = Results.ImageGridAmp; + end + + if FlagBaselineFile == 0 % remove the zero here !!! + Results.ImageGridAmp = Results.ImageGridAmpOrig; + end + + %Results.ImageGridAmp = abs(Results.ImageGridAmp); + + + % Compute ZScores on that baseline + Results.ZScore.Baseline = [tmin tmax]; + Results.ZScore.BaselineTime = [baseline(1) baseline(2)]; + + % Average activity and its standard deviation over the baseline, for each source + Results.ZScore.ImageGridZ.mean = ... + mean((Results.ImageGridAmp(:,tmin:tmax)),2); + Results.ZScore.ImageGridZ.std = ... + std((Results.ImageGridAmp(:,tmin:tmax)),0,2); + Results.ZScore.ImageGridZ.std = ... + Results.ZScore.ImageGridZ.std + max(Results.ZScore.ImageGridZ.std)*eps; % Avoid devide-by-zero issues + + if ~isempty(get(hTSelect.CorrectionFactor,'String')) + Results.ZScore.ImageGridZ.std = str2num(get(hTSelect.CorrectionFactor,'String'))*Results.ZScore.ImageGridZ.std; + end + + % Compute Z-Scores + if FlagBaselineFile == 1 % Now load current results + ZScore = Results.ZScore; + Results = get(hTSelect.ResultFiles,'Userdata'); + Results.ZScore = ZScore; clear ZScore + if ~isfield(Results,'ImageGridAmpOrig') + Results.ImageGridAmpOrig = []; + end + if isempty(Results.ImageGridAmpOrig) + Results.ImageGridAmpOrig = Results.ImageGridAmp; % Store original current density map + end + Results.ImageGridAmp = Results.ImageGridAmpOrig; + Results.ZScore.BaselineFile = get(hTSelect.LoadBaseline,'Userdata'); + Results.ZScore.FlagBaselineFile = 1; + else + Results.ZScore.FlagBaselineFile = 0; + Results.ZScore.BaselineFile = ''; + end + + disp('Updating Result File...'), drawnow + Results.ImageGridAmp = Results.ImageGridAmpOrig; + tmp = Results.ImageGridAmpOrig; + Results.ImageGridAmpOrig = []; + save_fieldnames(Results,get(hTSelect.Refresh,'Userdata')); + %Results.ImageGridAmp = Results.ZScore.ImageGridZ.Amp; + Results.ImageGridAmpOrig = tmp; clear tmp + + Results.ImageGridAmp = (Results.ImageGridAmp)-repmat(Results.ZScore.ImageGridZ.mean,1,size(Results.ImageGridAmp,2)); + iStd = spdiags(1./Results.ZScore.ImageGridZ.std, 0, length(Results.ZScore.ImageGridZ.std), length(Results.ZScore.ImageGridZ.std)) ; + + %Results.ZScore.ImageGridZ.Amp = Results.ImageGridAmp; + + disp('Computing a new Z-Score map from this baseline...-> DONE'), drawnow + + else % Compute ZScore from saved mean and std maps + + Results.ImageGridAmpOrig = Results.ImageGridAmp; + %Results.ImageGridAmp= Results.ZScore.ImageGridZ.Amp ; + + Results.ImageGridAmp = (Results.ImageGridAmp)-repmat(Results.ZScore.ImageGridZ.mean,1,size(Results.ImageGridAmp,2)); + iStd = spdiags(1./Results.ZScore.ImageGridZ.std, 0, length(Results.ZScore.ImageGridZ.std), length(Results.ZScore.ImageGridZ.std)) ; + + end + + %Results.ImageGridAmp = rand(size(iStd*Results.ImageGridAmp)); + Results.ImageGridAmp = abs(iStd*Results.ImageGridAmp); + + set(tesselation_select_win,'Pointer','arrow') + + case 0 % Switch to absolute current density mapping + + Results = get(hTSelect.ResultFiles,'Userdata'); + + disp('Previous Z-Score map on same baseline is used'), drawnow + Results.ImageGridAmp = Results.ImageGridAmpOrig; + set(hTSelect.ZScoreThresholdApply,'Value',0) + dataplot_cb('ToggleButtonColor',hTSelect.ZScoreThresholdApply) + end + + % Update display + set(hTSelect.ResultFiles,'Userdata',Results); + + dataplot_cb tesselation_select_done + + %---------------------------------------------------------------------------- + + +case 'AnalyzeCorticalMap' % Spatio-temporal segmentation of the cortical current density maps + + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + + % Identification of the active mesh surfaces + Visu = get(DATAPLOT,'Userdata'); + + try + load(Visu.Tesselation,'Comment') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment') + end + + if ~iscell(IDs) + imesh = find(strcmp(IDs,Comment)); + end + + nsurf = imesh(availableID); % Selected surface + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + if ~isfield(TessWinUserData,'VertConn') % Vertex connectivity not available here - load or compute + nsurfaces = length(Comment); + + % ----------------- Load current surface parameters - + load(Visu.Tesselation,'Faces','Vertices') + FV.faces = Faces{nsurf}; clear Faces + FV.vertices = Vertices{nsurf}'; clear Vertices + % ----------------- Load current surface parameters - DONE + + load(Users.CurrentData.SubjectFile,'VertConn'); % Is the vertex connectivity available ? + + if isempty(VertConn) % Vertex connectivity was not defined before + VertConn = cell(nsurfaces,1); + else + if exist(VertConn,'file') + load(VertConn) + else + VertConn = cell(nsurfaces,1); + end + end + + if isempty(VertConn{nsurf}) % Compute the vertex connectivity + [pathname, filename] = fileparts(Visu.Tesselation); + VertConn{nsurf} = vertices_connectivity(FV); + clear FV + VertConnFile = [filename,'_vertconn.mat']; + + % Save this file in the current subject folder + [path,name,ext] = fileparts(Users.CurrentData.SubjectFile); + if ~isempty(path) + cd(path) + else + cd(Users.SUBJECTS) + end + + save(VertConnFile,'VertConn'); + + VertConn = VertConnFile; + save(Users.CurrentData.SubjectFile,'VertConn','-append') + else % Load VC from the file + load(Users.CurrentData.SubjectFile,'VertConn'); + end + load(VertConn); + VertConn = VertConn{nsurf}; + TessWinUserData.VertConn = VertConn; clear VertConn; + end + + + % Get Z threshold + ZThres = str2num(get(hTessSelect.ZScoreThreshold,'String')) ; + + % Vertices which maximum Z score is above ZThres + Results = get(hTessSelect.ResultFiles,'Userdata'); + ImageGridAmp = Results.ImageGridAmp; clear Results + + % Get baseline info + Results = get(hTessSelect.ResultFiles,'userdata'); + AnalyzeWin = [0 370]/1000; % in sec + [tmp, tmin] = min(abs(Results.ImageGridTime-AnalyzeWin(1))); + [tmp, tmax] = min(abs(Results.ImageGridTime-AnalyzeWin(2))); + clear Results + + %Baseline = Results.ZScore.Baseline; clear Results + %Time = Baseline(end)+1:size(ImageGridAmp,2); %setdiff([1:size(ImageGridAmp,2)],[Baseline(1):Baseline(end)]); + + Time = [tmin:tmax]; + + MaxVerts = max(ImageGridAmp(:,Time)'); + iThres = find(MaxVerts > ZThres); + % Threshold in terms of correlation + CorrThres = .9; + + Scout{1} = []; + iScout = 1; + imax = 1; + + % Sort MaxVerts + [s, iMaxVertsSort] = sort(MaxVerts); clear s + + CONNEX = 0; % if 1; enforce connexity of each clusters + + + while ~isempty(imax) + %%%% Segmentation process + if iScout == 1 % We are starting from scratch + % Initialization + % Start region growing from the vertex with maximum ZScore + imax = iMaxVertsSort(end); + else + tmp = setdiff(iMaxVertsSort,[Scout{:}]); + [mm, imax] = max(MaxVerts(tmp)); clear mm + imax = tmp(imax); + end + + % Does imax checks iThres + if isempty(find(iThres == imax)) + break + end + + + if CONNEX == 1 + % Look for his neighbors + voiz = patch_swell(imax,TessWinUserData.VertConn); + % Select those that check the Zthres condition + voiz = intersect(iThres,voiz); + + else % Just look for all the points above ZThres + voiz = setdiff(iThres,imax); + end + + % Remove those previously selected + voiz = setdiff(voiz,[Scout{:}]); + + % Compute correlation coefficients of their time series + %CorrCoeff = abs(corrcoef(ImageGridAmp([imax,voiz],Time)')); + if ~isempty(voiz) + CorrCoeff = abs(ImageGridAmp(imax,Time)/norm(ImageGridAmp(imax,Time)))... + *abs(ImageGridAmp(voiz,Time)'*inorcol(ImageGridAmp(voiz,Time)')); + else + CorrCoeff = CorrThres/10; + end + + % Apply Correlation Threshold + %icorr = find(CorrCoeff(1,2:end)>CorrThres); + icorr = find(CorrCoeff>CorrThres); + + Scout{iScout} = [imax,voiz(icorr)]; + + while ~isempty(icorr) + + if CONNEX == 1 + voiz = patch_swell(voiz(icorr),TessWinUserData.VertConn); + % Select those that check the Zthres condition + voiz = intersect(iThres,voiz); + else + voiz = setdiff(iThres,imax); + end + + % Remove those previously selected + voiz = setdiff(voiz,[Scout{:}]); + + % Compute correlation coefficients of their time series + %CorrCoeff = abs(corrcoef(ImageGridAmp([imax,voiz],Time)')); + if ~isempty(voiz) + CorrCoeff = abs(ImageGridAmp(imax,Time)/norm(ImageGridAmp(imax,Time)))... + *abs(ImageGridAmp(voiz,Time)'*inorcol(ImageGridAmp(voiz,Time)')); + + CorrCoeffBaseLine = abs(ImageGridAmp(imax,125:500)/norm(ImageGridAmp(imax,125:500)))... + *abs(ImageGridAmp(voiz,125:500)'*inorcol(ImageGridAmp(voiz,125:500)')); + else + + CorrCoeff = CorrThres/10; + end + + % Apply Correlation Threshold + %icorr = find(CorrCoeff(1,2:end)>CorrThres); + icorr = find(CorrCoeff>CorrThres); + + Scout{iScout} = [Scout{iScout},voiz(icorr)]; + + end + + if length([Scout{:}]) ~= length(unique([Scout{:}])) + keyboard + end + + length(iThres) - length([Scout{:}]) + + CorticalScouts.CorticalProbePatches(iScout) = Scout(iScout); + CorticalScouts.CorticalMarkersLabels{iScout} = int2str(iScout); + CorticalScouts.CorticalSpots(iScout) = imax; + if iScout == 1 + load(Visu.Tesselation,'Vertices') + end + CorticalScouts.CorticalMarkers(iScout,:) = Vertices{nsurf}(:,Scout{iScout}(1)); + + iScout = iScout+1; + disp('') + + + end + + newScout = 1; + + for iScout = 1:length(Scout) + if length(Scout{iScout}) == 1 % Single point scout: do we keep it ? + % Check if its neighbors with activation < ZThres have time series that correlate with his with corrcoeff > CorrThres + voiz = patch_swell(Scout{iScout},TessWinUserData.VertConn); + + if ~isempty(voiz) + CorrCoeff = abs(ImageGridAmp(imax,Time)/norm(ImageGridAmp(imax,Time)))... + *abs(ImageGridAmp(voiz,Time)'*inorcol(ImageGridAmp(voiz,Time)')); + else + CorrCoeff = CorrThres/10; + end + + icorr = find(CorrCoeff>CorrThres); + + if isempty(icorr) + disp('Remove spurious Scout') + % Scout{iScout} = []; + % iScout = iScout - 1; + else + newCorticalScouts.CorticalProbePatches(newScout) = Scout(iScout); + newCorticalScouts.CorticalMarkersLabels{newScout} = int2str(newScout); + newCorticalScouts.CorticalSpots(newScout) = Scout{iScout}(1); + if newScout == 1 + load(Visu.Tesselation,'Vertices') + end + newCorticalScouts.CorticalMarkers(newScout,:) = Vertices{nsurf}(:,Scout{iScout}(1)); + newScout = newScout + 1; + end + + else + newCorticalScouts.CorticalProbePatches(newScout) = Scout(iScout); + newCorticalScouts.CorticalMarkersLabels{newScout} = int2str(newScout); + newCorticalScouts.CorticalSpots(newScout) = Scout{iScout}(1); + if newScout == 1 + load(Visu.Tesselation,'Vertices') + end + newCorticalScouts.CorticalMarkers(newScout,:) = Vertices{nsurf}(:,Scout{iScout}(1)); + newScout = newScout + 1; + end + + clear CorticalScouts + CorticalScouts = newCorticalScouts; + + end + + + CorticalScouts.VertConn = TessWinUserData.VertConn; + CorticalScouts.CorticalProbeDepth = ones(1,length(Scout)); + + cd(Users.STUDIES) + + length(CorticalScouts.CorticalProbePatches) + + save test CorticalScouts + + %---------------------------------------------------------------------------- +case 'ShowClusters' % Show all cortical scouts/clusters at once + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + + % Identification of the active mesh surfaces + Visu = get(DATAPLOT,'Userdata'); + + try + load(Visu.Tesselation,'Comment') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment') + end + + if ~iscell(IDs) + imesh = find(strcmp(IDs,Comment)); + end + + nsurf = imesh(availableID); % Selected surface + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + if ~isfield(TessWinUserData,'VertConn') % Vertex connectivity not available here - load or compute + nsurfaces = length(Comment); + + % ----------------- Load current surface parameters - + load(Visu.Tesselation,'Faces','Vertices') + FV.faces = Faces{nsurf}; clear Faces + FV.vertices = Vertices{nsurf}'; clear Vertices + % ----------------- Load current surface parameters - DONE + + load(Users.CurrentData.SubjectFile,'VertConn'); % Is the vertex connectivity available ? + + if isempty(VertConn) % Vertex connectivity was not defined before + VertConn = cell(nsurfaces,1); + else + if exist(VertConn,'file') + load(VertConn) + else + VertConn = cell(nsurfaces,1); + end + end + + if isempty(VertConn{nsurf}) % Compute the vertex connectivity + [pathname, filename] = fileparts(Visu.Tesselation); + VertConn{nsurf} = vertices_connectivity(FV); + VertConnFile = [filename,'_vertconn.mat']; + + % Save this file in the current subject folder + [path,name,ext] = fileparts(Users.CurrentData.SubjectFile); + if ~isempty(path) + cd(path) + else + cd(Users.SUBJECTS) + end + + save(VertConnFile,'VertConn'); + + VertConn = VertConnFile; + save(Users.CurrentData.SubjectFile,'VertConn','-append') + else % Load VC from the file + load(Users.CurrentData.SubjectFile,'VertConn'); + end + load(VertConn); + VertConn = VertConn{nsurf}; + TessWinUserData.VertConn = VertConn; clear VertConn; + end + + % Now grow a patch around the selected probe and selected neighbors + + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); +% if ~isfield(TessWinUserData,'CorticalProbePatches') +% TessWinUserData.CorticalProbePatches = cell(get(hTessSelect.CorticalSpotList,'Max'),1); +% TessWinUserData.CorticalProbeDepth = zeros(get(hTessSelect.CorticalSpotList,'Max'),1); % Number of patch_swells necessary to achieve the patch growth; +% end +% if length(TessWinUserData.CorticalProbePatches) < SelectedArea % User just added a new probe +% nareas = length(TessWinUserData.CorticalProbePatches); +% TessWinUserData.CorticalProbePatches(nareas+1:SelectedArea) = cell(SelectedArea-nareas,1); +% TessWinUserData.CorticalProbeDepth(nareas+1:SelectedArea) = 0; +% end + +% if isempty(TessWinUserData.CorticalProbePatches{SelectedArea}) % No areas around patches were defined +% TessWinUserData.CorticalProbeDepth(SelectedArea) = 1; +% TessWinUserData.CorticalProbePatches{SelectedArea} = ... +% [TessWinUserData.CorticalSpots(SelectedArea),patch_swell(TessWinUserData.CorticalSpots(SelectedArea),TessWinUserData.VertConn)]; +% else +% TessWinUserData.CorticalProbeDepth(SelectedArea) = TessWinUserData.CorticalProbeDepth(SelectedArea) +1; +% TessWinUserData.CorticalProbePatches{SelectedArea} = [TessWinUserData.CorticalProbePatches{SelectedArea},... +% patch_swell([TessWinUserData.CorticalProbePatches{SelectedArea}],TessWinUserData.VertConn)]; +% end + + ActiveTess = get(hTessSelect.removed,'String'); % Find the active scalp surface + iCortex = get(hTessSelect.removed,'Value'); % Find the active scalp surface + if isempty(iCortex) + h = msgbox('Please select a cortex surface from the tessellations available.'); + return + end + if iscell(ActiveTess) + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess{iCortex}); %CHEAT - need to be improved ? + else + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess); %CHEAT - need to be improved ? + end + + FVCData = get(Cortex,'FaceVertexCData'); + MM = max(abs(FVCData)); + if size(FVCData,2) == 1 % No curvature mapping + FVCData = .1*MM*ones(size(FVCData)); + else + FVCData = repmat(MM,size(FVCData,1),1); + end + + if ~isfield(TessWinUserData,'FVCData') + TessWinUserData.FVCData = FVCData; % Keep track of the original activation vertex colordata + end + + if size(FVCData,2) == 1 % No curvature mapping + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ]) = MM; + else + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ],:) = repmat(MM,length(TessWinUserData.CorticalProbePatches{SelectedArea} ),1); + end + + set(Cortex,'FaceVertexCData',FVCData); + + set(Cortex,'FaceVertexCData',FVCData); + set(TessWin,'Userdata',TessWinUserData) + + + %---------------------------------------------------------------------------- + + %---------------------------------------------------------------------------- +case 'GrowCorticalArea' % Grow a survey cortical area around a probe to include connected vertices + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + + % Identification of the active mesh surfaces + Visu = get(DATAPLOT,'Userdata'); + + try + load(Visu.Tesselation,'Comment') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment') + end + + if ~iscell(IDs) + imesh = find(strcmp(IDs,Comment)); + end + + nsurf = imesh(availableID); % Selected surface + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + if ~isfield(TessWinUserData,'VertConn') % Vertex connectivity not available here - load or compute + nsurfaces = length(Comment); + + % ----------------- Load current surface parameters - + load(Visu.Tesselation,'Faces','Vertices') + FV.faces = Faces{nsurf}; clear Faces + FV.vertices = Vertices{nsurf}'; clear Vertices + % ----------------- Load current surface parameters - DONE + + load(Users.CurrentData.SubjectFile,'VertConn'); % Is the vertex connectivity available ? + + if isempty(VertConn) % Vertex connectivity was not defined before + VertConn = cell(nsurfaces,1); + else + if exist(VertConn,'file') + load(VertConn) + else + VertConn = cell(nsurfaces,1); + end + end + + if isempty(VertConn{nsurf}) % Compute the vertex connectivity + [pathname, filename] = fileparts(Visu.Tesselation); + VertConn{nsurf} = vertices_connectivity(FV); + VertConnFile = [filename,'_vertconn.mat']; + + % Save this file in the current subject folder + [path,name,ext] = fileparts(Users.CurrentData.SubjectFile); + if ~isempty(path) + cd(path) + else + cd(Users.SUBJECTS) + end + + save(VertConnFile,'VertConn'); + + VertConn = VertConnFile; + save(Users.CurrentData.SubjectFile,'VertConn','-append') + else % Load VC from the file + load(Users.CurrentData.SubjectFile,'VertConn'); + end + load(VertConn); + VertConn = VertConn{nsurf}; + TessWinUserData.VertConn = VertConn; clear VertConn; + end + + % Now grow a patch around the selected probe and selected neighbors + + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); + if ~isfield(TessWinUserData,'CorticalProbePatches') + TessWinUserData.CorticalProbePatches = cell(get(hTessSelect.CorticalSpotList,'Max'),1); + TessWinUserData.CorticalProbeDepth = zeros(get(hTessSelect.CorticalSpotList,'Max'),1); % Number of patch_swells necessary to achieve the patch growth; + end + if length(TessWinUserData.CorticalProbePatches) < SelectedArea % User just added a new probe + nareas = length(TessWinUserData.CorticalProbePatches); + TessWinUserData.CorticalProbePatches(nareas+1:SelectedArea) = cell(SelectedArea-nareas,1); + TessWinUserData.CorticalProbeDepth(nareas+1:SelectedArea) = 0; + end + + if isempty(TessWinUserData.CorticalProbePatches{SelectedArea}) % No areas around patches were defined + TessWinUserData.CorticalProbeDepth(SelectedArea) = 1; + TessWinUserData.CorticalProbePatches{SelectedArea} = ... + [TessWinUserData.CorticalSpots(SelectedArea),patch_swell(TessWinUserData.CorticalSpots(SelectedArea),TessWinUserData.VertConn)]; + else + TessWinUserData.CorticalProbeDepth(SelectedArea) = TessWinUserData.CorticalProbeDepth(SelectedArea) +1; + TessWinUserData.CorticalProbePatches{SelectedArea} = [TessWinUserData.CorticalProbePatches{SelectedArea},... + patch_swell([TessWinUserData.CorticalProbePatches{SelectedArea}],TessWinUserData.VertConn)]; + end + + ActiveTess = get(hTessSelect.removed,'String'); % Find the active scalp surface + iCortex = get(hTessSelect.removed,'Value'); % Find the active scalp surface + if isempty(iCortex) + h = msgbox('Please select a cortex surface from the tessellations available.'); + return + end + if iscell(ActiveTess) + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess{iCortex}); %CHEAT - need to be improved ? + else + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess); %CHEAT - need to be improved ? + end + + FVCData = get(Cortex,'FaceVertexCData'); + + if ~isfield(TessWinUserData,'FVCData') + TessWinUserData.FVCData = FVCData; % Keep track of the original activation vertex colordata + end + + if size(FVCData,2) == 1 % No curvature mapping + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ]) = max(abs(FVCData)); + else + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ],:) = repmat(max(abs(FVCData)),length(TessWinUserData.CorticalProbePatches{SelectedArea} ),1); + end + + set(Cortex,'FaceVertexCData',FVCData); + set(TessWin,'Userdata',TessWinUserData) + + + %---------------------------------------------------------------------------- +case 'ReduceCorticalArea' % See above 'GrowCorticalArea' - except we are here reducing the size of the survey cortical zone to monitor + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + available = findobj(tesselation_select_win,'Tag','available'); + removed = findobj(tesselation_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + + % Identification of the active mesh surfaces + Visu = get(DATAPLOT,'Userdata'); + + try + load(Visu.Tesselation,'Comment') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Comment') + end + + if ~iscell(IDs) + imesh = find(strcmp(IDs,Comment)); + end + + nsurf = imesh(availableID); % Selected surface + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + if ~isfield(TessWinUserData,'VertConn') % Vertex connectivity not available here - load or compute + nsurfaces = length(Comment); + + % ----------------- Load current surface parameters - + load(Visu.Tesselation,'Faces','Vertices') + FV.faces = Faces{nsurf}; clear Faces + FV.vertices = Vertices{nsurf}'; clear Vertices + % ----------------- Load current surface parameters - DONE + + load(Users.CurrentData.SubjectFile,'VertConn'); % Is the vertex connectivity available ? + + if isempty(VertConn) % Vertex connectivity was not defined before + VertConn = cell(nsurfaces,1); + else + if exist(VertConn,'file') + load(VertConn) + else + VertConn = cell(nsurfaces,1); + end + end + + if isempty(VertConn{nsurf}) % Compute the vertex connectivity + [pathname, filename] = fileparts(Visu.Tesselation); + VertConn{nsurf} = vertices_connectivity(FV); + VertConnFile = [filename,'_vertconn.mat']; + + save(VertConnFile,'VertConn'); + + VertConn = VertConnFile; + save(Users.CurrentData.SubjectFile,'VertConn','-append') + else % Load VC from the file + load(Users.CurrentData.SubjectFile,'VertConn'); + end + load(VertConn); + VertConn = VertConn{nsurf}; + TessWinUserData.VertConn = VertConn; clear VertConn; + end + + + % Now grow a patch around the selected probe and selected neighbors + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); + + tmp = []; + + for k = 1:TessWinUserData.CorticalProbeDepth(SelectedArea)-1 + if k == 1 + tmp = ... + patch_swell(TessWinUserData.CorticalSpots(SelectedArea),TessWinUserData.VertConn); + else + tmp = ... + [tmp,patch_swell(tmp,TessWinUserData.VertConn)]; + end + end + + TessWinUserData.CorticalProbeDepth(SelectedArea) = max([TessWinUserData.CorticalProbeDepth(SelectedArea)-1,0]); + + ActiveTess = get(hTessSelect.removed,'String'); % Find the active scalp surface + iCortex = get(hTessSelect.removed,'Value'); % Find the active scalp surface + + if isempty(iCortex) + h = msgbox('Please select a cortex surface from the tessellations available.'); + return + end + if iscell(ActiveTess) + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess{iCortex}); %CHEAT - need to be improved ? + else + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess); %CHEAT - need to be improved ? + end + FVCData = get(Cortex,'FaceVertexCData'); + old_members = intersect(TessWinUserData.CorticalProbePatches{SelectedArea},tmp); % Older members of the cortical survey zone (keep them) + if isempty(old_members) + old_members = TessWinUserData.CorticalSpots(SelectedArea); + end + new_members = setdiff(TessWinUserData.CorticalProbePatches{SelectedArea},tmp); % Last members of the cortical survey zone (remove them) + + if size(FVCData,2) == 1 % No curvature mapping + FVCData(new_members) = TessWinUserData.FVCData(new_members); % Reset their color to original + else + FVCData(new_members,:) = TessWinUserData.FVCData(new_members,:); % Reset their color to original + end + + TessWinUserData.CorticalProbePatches{SelectedArea} = old_members; + + if size(FVCData,2) == 1 % No curvature mapping + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ]) = max(abs(FVCData)); + else + FVCData([ TessWinUserData.CorticalProbePatches{SelectedArea} ],:) = repmat(max(abs(FVCData)),length(TessWinUserData.CorticalProbePatches{SelectedArea} ),1); + end + + set(Cortex,'FaceVertexCData', TessWinUserData.FVCData) + set(Cortex,'FaceVertexCData',FVCData); + + set(TessWin,'Userdata',TessWinUserData) + + + %---------------------------------------------------------------------------- +case 'CorticalSpotActivity' + tesselation_select_win = findobj(0,'Tag','tesselation_select'); + hTessSelect = guihandles(tesselation_select_win); + + % What kind of display is wanted here ? + MEAN = get( hTessSelect.MeanCorticalArea,'Value'); + MAX = get(hTessSelect.MaxCorticalArea,'Value'); + ALL = get(hTessSelect.AllCorticalArea,'Value'); + + SelectedArea = get(hTessSelect.CorticalSpotList,'Value'); + + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + Results = get(hTessSelect.ResultFiles,'Userdata'); + + if get(hTessSelect.ZScoreThresholdApply,'Value') % Threshold is applied on ZScore map: indicate significant Z Scores time samples + flagZScoreT = 1; + flagHisto = 0; + else + flagZScoreT = 0; + if get(hTessSelect.ZScore,'Value') + flagZScore = 1; + flagHisto = 0; + else + flagZScore = 0; + % !!! CorticalActivity is scaled to nA.m + if max(abs(Results.ImageGridAmp(:))) < 1e-5 % Probably dipole moment values - scale to nA.m + flagHisto = 0; + Results.ImageGridAmp = 1e9*Results.ImageGridAmp; + else + % This is a plot of histogram of activations + flagHisto = 1; + end + + end + + end + + + if ~isfield(TessWinUserData,'CorticalProbePatches') + if get(hTessSelect.AbsoluteCurrent,'Value') + CorticalActivity = abs(Results.ImageGridAmp(TessWinUserData.CorticalSpots(SelectedArea),:)); + else + CorticalActivity = Results.ImageGridAmp(TessWinUserData.CorticalSpots(SelectedArea),:); + end + else + for k = 1:length(SelectedArea) % For each cortical survey area + if length(TessWinUserData.CorticalProbePatches{SelectedArea(k)})>1 + if MEAN == 1% Average of the patch activity at each time instant + if get(hTessSelect.AbsoluteCurrent,'Value') + CorticalActivity(k,:) = mean(abs(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:))); + else + CorticalActivity(k,:) = sign(mean(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:)))... + .* mean((Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:))) ; + end + elseif MAX==1 % Strongest + nor = 1e9*norlig(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:)); + [m,iMax] = max(nor); + if get(hTessSelect.AbsoluteCurrent,'Value') + CorticalActivity(k,:) = max(abs(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:))); + else + CorticalActivity(k,:) = max(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:)); + end + + else % Display every source activity in the patch + % All sources need to be displayed + if get(hTessSelect.AbsoluteCurrent,'Value') + CorticalActivity{k} = abs(Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:)); + else + CorticalActivity{k} = Results.ImageGridAmp(TessWinUserData.CorticalProbePatches{SelectedArea(k)},:); + end + % Detect Maxima in amplitudes (needed for proper display in the offset plot) + maxCorticalActivity(k,:) = sign(min(CorticalActivity{k})).*max(abs(CorticalActivity{k})); + end + else + if get(hTessSelect.AbsoluteCurrent,'Value') + tmp = abs(Results.ImageGridAmp(TessWinUserData.CorticalSpots(SelectedArea(k)),:)); + else + tmp = Results.ImageGridAmp(TessWinUserData.CorticalSpots(SelectedArea(k)),:); + end + if (MEAN | MAX) + CorticalActivity(k,:) = tmp; clear tmp + else + CorticalActivity{k} = tmp; clear tmp + maxCorticalActivity(k,:) = CorticalActivity{k}; + end + end + end + end + + t = 1000*Results.ImageGridTime; + fActivation = figure; + % Display set-up + switch(find([MEAN,MAX,ALL])) + case 1 + tail = 'MEAN'; + case 2 + tail = 'MAX'; + case 3 + tail = 'ALL'; + end + + set(gcf,'Tag','source_time_series','Name',['Activation time series: ', tail],'color','w' ) + Color = get(gca,'ColorOrder'); % Default Colormapping for line plots + + if ~iscell(CorticalActivity) + S = CorticalActivity'; + + % %Sn = colnorm(S); + % %Sn = S./Sn(ones(1,size(S,1)),:); + % % each waveform is now unity in norm. Weight + % % by its total contribution to the field + % %Snw = Sn .* (ones(size(S,1),1)*(colnorm(A).*colnorm(S))); + % [outmatnw, col_offsetnw] = offset(S); + % plot(t,outmatnw,'linewidth',1), + % hold on + % plot(t,col_offsetnw,'linewidth',2) % want same color order as data + + % Get Max amplitude and apply to all axes + M = max(abs(S(:))); + for k = 1:size(CorticalActivity,1) + subplot(size(CorticalActivity,1)+1,1,k) % One-column display + plot(t,CorticalActivity(k,:),'color',Color(modulo(k,size(Color,1)),:),'Tag','AllSamples') + hold on + set(gca,'XlimMode','manual') + if get(hTessSelect.AbsoluteCurrent,'Value') + axis([t(1) t(end) 0 M+.05*M]) + else + axis([t(1) t(end) -M-.05*M M+.05*M]) + end + + + if flagZScoreT == 1 % Add markers for significant amplitudes along time + iZeroed = find(... + abs(CorticalActivity(k,:)) ... + - Results.ZScore.ImageGridZ.ZThres... + <=0); + CorticalActivity(k,iZeroed) = NaN; + hold on + if length(iZeroed) ~= length(CorticalActivity(k,:)) + plot(t,CorticalActivity(k,:),'color',Color(modulo(k,size(Color,1)),:),'linewidth',2,'Tag','SignificantSamples') + end + + end + + if 0 < t(end) & 0 > t(1) + if get(hTessSelect.AbsoluteCurrent,'Value') + line([0 0], [0 M+.05*M],'color','k','linestyle','--') + else + line([0 0] ,[-M-.05*M M+.05*M],'color','k','linestyle','--') + end + end + + % Plastic Surgery to Axes Display + set(gca,'box','off','XGrid','off','FontUnits','Points','fontsize',9,'LineWidth',2) + + Label = get(TessWinUserData.CorticalMarkersLabels(SelectedArea(k)),'String'); + + if flagZScoreT == 1 + if length(iZeroed) ~= length(CorticalActivity(k,:)) + hLeg = legend(sprintf(... + '%s',Label),... + sprintf('p<%4.2f', 1/Results.ZScore.ImageGridZ.ZThres^2)... + ,0); + else + hLeg = legend(sprintf(... + '%s (n.s.)',Label),0); + + end + + else + hLeg = legend(sprintf(... + '%s',Label)... + ); + end + + %set(hLeg,'color',Color(modulo(k,size(Color,1)),:),'fontsize',9) + %legend('boxoff') + + if flagZScoreT == 1 + line([t(1) t(end)], [Results.ZScore.ImageGridZ.ZThres Results.ZScore.ImageGridZ.ZThres],... + 'Color',Color(modulo(k,size(Color,1)),:),'linestyle','--') + if k==1 + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + xlabel('time (ms)','fontunits','point','fontsize',9) + end + + hold off + else + if k == 1 + if flagZScore == 0 + if flagHisto == 0 + ylabel(['nA\cdotm'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + else + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + end + xlabel('time (ms)','fontunits','point','fontsize',9) + end + end + + % Summary plot + subplot(size(CorticalActivity,1)+1,1,size(CorticalActivity,1)+1) + plot(t,CorticalActivity(k,:),'color',Color(modulo(k,size(Color,1)),:),'Tag','AllSamples') + hold on + set(gca,'XlimMode','manual') + set(gca,'box','off','XGrid','off','FontUnits','point','fontsize',10,'LineWidth',2) + if get(hTessSelect.AbsoluteCurrent,'Value') + axis([t(1) t(end) 0 M+.05*M]) + else + axis([t(1) t(end) -M-.05*M M+.05*M]) + end + + if 0 < t(end) & 0 > t(1) + if get(hTessSelect.AbsoluteCurrent,'Value') + line([0 0], [0 M+.05*M],'color','k','linestyle','--') + else + line([0 0] ,[-M-.05*M M+.05*M],'color','k','linestyle','--') + end + end + + if flagZScoreT == 1 + line([t(1) t(end)], [Results.ZScore.ImageGridZ.ZThres Results.ZScore.ImageGridZ.ZThres],... + 'Color',Color(modulo(k,size(Color,1)),:),'linestyle','--') + if k==1 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + xlabel('time (ms)','fontunits','point','fontsize',9) + end + else + if k == 1 + if flagZScore == 0 + if flagHisto == 0 + ylabel(['nA\cdotm'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + else + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + end + xlabel('time (ms)','fontunits','point','fontsize',9) + end + end + + + + %---------------- + + + end + + else + + % Find MAX + for k = 1:length(CorticalActivity) + M(k) = max(abs([CorticalActivity{k}(:)])); + end + M = max(M); + for k = 1:length(CorticalActivity) + subplot(length(CorticalActivity)+1,1,k) % One-column display + plot(t,CorticalActivity{k},'color',Color(modulo(k,size(Color,1)),:)) + hold on + + set(gca,'XlimMode','manual') + if get(hTessSelect.AbsoluteCurrent,'Value') + axis([t(1) t(end) 0 M+.05*M]) + else + axis([t(1) t(end) -M-.05*M M+.05*M]) + end + + + if flagZScoreT == 1 % Add markers for significant amplitudes along time + iZeroed = find(... + abs(CorticalActivity{k}) ... + - Results.ZScore.ImageGridZ.ZThres... + <=0); + CorticalActivity{k}(iZeroed) = NaN; + hold on + if length(iZeroed) ~= length(CorticalActivity{k}(:)) + plot(t,CorticalActivity{k},'color',Color(modulo(k,size(Color,1)),:),'linewidth',2,'Tag','SignificantSamples') + end + if k== 1 + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + xlabel('time (ms)','fontunits','point') + end + + else + if k==1 + if flagZScore == 0 + if flagHisto == 0 + ylabel(['nA\cdotm'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + else + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + end + xlabel('time (ms)','fontunits','point') + end + + end + + if 0 < t(end) & 0 > t(1) + if get(hTessSelect.AbsoluteCurrent,'Value') + line([0 0], [0 M+.05*M],'color','k','linestyle','--') + else + line([0 0] ,[-M-.05*M M+.05*M],'color','k','linestyle','--') + end + end + + % Plastic Surgery to Axes Display + set(gca,'box','off','XGrid','off','FontUnits','point','fontsize',10,'LineWidth',2) + Label = get(TessWinUserData.CorticalMarkersLabels(SelectedArea(k)),'String'); + % title(sprintf(... + % ' Area: %s',Label)... + % ); + if flagZScoreT == 1 + if length(iZeroed) ~= length(CorticalActivity{k}) + hLeg = legend(sprintf(... + '%s',Label),... + sprintf('p<%4.2f', 1/Results.ZScore.ImageGridZ.ZThres^2)... + ,0); + else + hLeg = legend(sprintf(... + '%s (n.s.)',Label),0); + end + + else + hLeg = legend(sprintf(... + ' Area: %s',Label)... + ,0); + end + + %set(hLeg,'color',Color(modulo(k,size(Color,1)),:),'fontunits','points','fontsize',9) + %set(findobj(get(hLeg,'children'),'type','text'),'color',Color(modulo(k,size(Color,1)),:)) + %%legend('boxoff') + + % S = maxCorticalActivity'; + % [outmatnw, col_offsetnw] = offset(S); + % off = plot(t,col_offsetnw,'linewidth',2); % want same color order as data + % hold on + % for k = 1:length(CorticalActivity) + % Src = CorticalActivity{k} + repmat(col_offsetnw(:,k)',size(CorticalActivity{k},1),1); + % plot(t,Src,'linewidth',1,'color',get(off(k),'color')), + % set(off(k),'color',[.4 .4 .4]) + + + % Summary plot + subplot(length(CorticalActivity)+1,1,length(CorticalActivity)+1) + plot(t,CorticalActivity{k},'color',Color(modulo(k,size(Color,1)),:),'Tag','AllSamples') + hold on + set(gca,'XlimMode','manual') + set(gca,'box','off','XGrid','off','FontUnits','point','fontsize',10,'LineWidth',2) + if get(hTessSelect.AbsoluteCurrent,'Value') + axis([t(1) t(end) 0 M+.05*M]) + else + axis([t(1) t(end) -M-.05*M M+.05*M]) + end + + if 0 < t(end) & 0 > t(1) + if get(hTessSelect.AbsoluteCurrent,'Value') + line([0 0], [0 M+.05*M],'color','k','linestyle','--') + else + line([0 0] ,[-M-.05*M M+.05*M],'color','k','linestyle','--') + end + end + + + if flagZScoreT == 1 + line([t(1) t(end)], [Results.ZScore.ImageGridZ.ZThres Results.ZScore.ImageGridZ.ZThres],... + 'Color',Color(modulo(k,size(Color,1)),:),'linestyle','--') + hold off + end + + if flagZScoreT == 1 + line([t(1) t(end)], [Results.ZScore.ImageGridZ.ZThres Results.ZScore.ImageGridZ.ZThres],... + 'Color',Color(modulo(k,size(Color,1)),:),'linestyle','--') + if k==1 + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + xlabel('time (ms)','fontunits','point','fontsize',9) + end + + hold off + else + if k == 1 + if flagZScore == 0 + if flagHisto == 0 + ylabel(['nA\cdotm'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + else + if flagHisto == 0 + ylabel(['Z-Score (\bf\sigma)'],'fontunits','point') + else + ylabel(['% Spikes'],'fontunits','point') + end + + end + xlabel('time (ms)','fontunits','point','fontsize',9) + end + end + + + %---------------- + + + + end + end + + hold off + + % for i = 1:size(S,2) + % Label = get(TessWinUserData.CorticalMarkersLabels(SelectedArea(i)),'String'); + % htext = text(t(end),col_offsetnw(end,i),sprintf(... + % ' Area: %s',Label)... + % ,'color','k'); + % set(htext, 'FontUnits','Normal','FontName','Helvetica') + % end + + % zoom on + % set(gca,'xgrid','on','xcolor','k','ycolor','k','box','on') + % set(gca,'yticklabel',[]) + % set(gca,'Position',[.05 .10 .75 .9]) + % drawnow + + % Draw Source Time Cursor + if 0 + figsingle = findobj(0,'Tag','source_time_series'); + src_slider_time = findobj(SRC_MAPPING,'Tag','src_slider_time'); + ctime = get(src_slider_time,'Value'); + cursor = line([ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + end + + %---------------------------------------------------------------------------- +case 'tesselation_select_done' % Launch/Refresh Mesh Surface Visulization + Visu = get(DATAPLOT,'Userdata'); + TessSelect = findobj(0,'Tag','tesselation_select'); + hSelect = guihandles(TessSelect); + + available = findobj(TessSelect,'Tag','available'); + removed = findobj(TessSelect,'Tag','removed'); + + previous = findobj(0,'tag','tessellation_window'); + tmp = findobj(0,'tag','subplot_tess_window'); + if ~isempty(tmp) + previous = tmp; % Consider the slides or movie window + end + + if isempty(previous) + previous = open('tessellation_window.fig'); + set(previous,'CurrentAxes',findobj(previous,'Tag','MainAxis'),... + 'Renderer','OpenGL',... + 'Color','w', 'Colormap',gray); + rotate3d on + set(hSelect.TruncateFactor,'String',0) + set(hSelect.ColorMAP,'Userdata',[]) + set(hSelect.ScaleColormap,'Userdata',[]) + + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs), return, end + chan = [1:length(IDs)]; + + try + load(Visu.Tesselation) + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation) + end + + % How many meshes available ? + nmesh = max(size(Vertices)); + + % Identification of the active mesh surfaces + if ischar(IDs) % only one envelope was selected + imesh = find(strcmp(IDs,Comment)); + else + for i = 1:length(IDs) + imesh(i) = find(strcmp(IDs(i),Comment)); + end + end + + Vals = get(removed,'Userdata'); + if isempty(Vals) + Vals = [ones(nmesh,1),zeros(nmesh,8)]; + end + Vals = set(removed,'Userdata'); + nsurf = imesh(availableID); % Selected surface + set(hSelect.Apply,'Userdata',{imesh,nsurf,Comment,Vertices,Faces}) + else + tmp = get(hSelect.Apply,'Userdata'); + imesh = tmp{1}; + nsurf = tmp{2}; + Comment = tmp{3}; + Vertices = tmp{4}; + Faces = tmp{5}; + end + figure(previous) + + Vals = get(removed,'Userdata'); + + FragmentMenu = findobj(gcbf,'Tag','FragmentMenu'); + nclust = get(FragmentMenu,'Value')-1; % Get label of clustering to visualize + + TAG = get(hSelect.OrthoViews,'Value'); + + if TAG == 1 + OrthoViews = 1; + else + OrthoViews = 0; + end + hpatch = []; + if OrthoViews == 0 + hpatch = findobj(findobj(previous,'Tag','MainAxes'),'Type','patch','Visible','on'); + else + if ~isempty(findobj(findobj(previous,'Tag','axsub1'),'Type','patch')) + hpatch(1) = findobj(findobj(previous,'Tag','axsub1'),'type','patch'); + hpatch(2) = findobj(findobj(previous,'Tag','axsub2'),'type','patch'); + hpatch(3) = findobj(findobj(previous,'Tag','axsub3'),'type','patch'); + hpatch(4) = findobj(findobj(previous,'Tag','axsub4'),'type','patch'); + else + if isempty(hpatch) + hpatch = []; + end + end + end + + % What kind of visualization type is needed here ? ------------------------------- + ScalpMaps = get(hSelect.ScalpMaps,'Value'); + ColorSensors = get(hSelect.ColorSensors,'Value'); + CorticalMap = get(hSelect.CorticalMap,'Value'); + + nmesh = 0; % Number of meshes to display + + for k = imesh + h = findobj(hpatch,'Tag',Comment{k}); + set(h,'Visible','on') + + if isempty(h) + h{1}= 'new_patch'; + elseif iscell(h) + if get(h{1},'Parent') ~= get(previous,'CurrentAxes') + h{1}= 'new_patch'; + end + else + hh = cell(length(h),1); + for kh = 1:length(hh) + hh{kh} = h(kh); + end + h = hh; clear hh + end + + switch h{1} + case 'new_patch' + + h = patch('vertices',Vertices{k}','Faces',Faces{k},... + 'Facecolor',[.8 .8 .8],'Edgecolor','none',... + 'Visible','off','Tag',Comment{k}); + + % Surface orientation + if ~isfield(Visu.Data,'System') + Visu.Data.System = 'ctf'; + end + + switch(Visu.Data.System) + case 'ctf' + view(-90,90) + end + + %------------------------- + + if length(imesh)>1 + nmesh = nmesh+1; + hpatch(nmesh) = h; + else + hpatch = h; + end + % Lightning properties ------------------------------------------------------- + set(h,'facelighting','none','edgelighting','none',... + 'ambientstrength',.5,... + 'DiffuseStrength',.3,... + 'specularcolorreflectance',.0,... + 'specularexponent',1,'specularstrength',.2,... + 'backfacelighting','unlit'); + + lightangle(0,0) + lightangle(0,90) + lightangle(180,0) + axis normal , axis equal, axis vis3d, axis off + + end + end + + if get(hSelect.MapCurvature,'Value') % ColorCoding of surface curvature is requested + TessWin = findobj(0,'tag','tessellation_window'); + hTessWin = guihandles(TessWin); + TessWinUserData = get(TessWin,'Userdata'); + + if ~isfield(get(hpatch, 'Userdata'),'CDepth') % No curvature mapping is available - compute it + % Try to load the depth map from the tessellation file + nsurfaces = length(Comment); + + try + load(Visu.Tesselation,'Curvature') + catch + cd(Users.SUBJECTS) + load(Visu.Tesselation,'Curvature') + end + + if ~exist('Curvature','var') + Curvature = cell(nsurfaces,1); + end + + if length(Curvature) < nsurf + tmp = cell(nsurf,1); + tmp(1:length(Curvature)) = Curvature; + Curvature = tmp; clear tmp + end + + if isempty(Curvature{nsurf}) %| ~isfield(TessWinUserData,'VertConn') % Vertex connectivity not available here - load or compute + + load(Users.CurrentData.SubjectFile,'VertConn'); % Is the vertex connectivity available ? + + if isempty(VertConn) % Vertex connectivity was not defined before + VertConn = cell(nsurfaces,1); + else + if exist(VertConn,'file') + load(VertConn) + else + VertConn = cell(nsurfaces,1); + end + end + + if length(VertConn) < nsurf + tmp = cell(nsurf,1); + tmp(1:length(VertConn)) = VertConn; + VertConn = tmp; clear tmp + end + + if isempty(VertConn{nsurf}) % Compute the vertex connectivity + + % ----------------- Load current surface parameters + load(Visu.Tesselation,'Faces','Vertices') + FV.faces = Faces{nsurf}; clear Faces + FV.vertices = Vertices{nsurf}'; clear Vertices + % ----------------- Load current surface parameters - DONE + + [pathname, filename] = fileparts(Visu.Tesselation); + VertConn{nsurf} = vertices_connectivity(FV); + VertConnFile = [filename,'_vertconn.mat']; + + % Save this file in the current subject folder + [path,name,ext] = fileparts(Users.CurrentData.SubjectFile); + if isempty(path) + cd(Users.SUBJECTS) + else + cd(path) + end + save(VertConnFile,'VertConn'); + + cd(Users.SUBJECTS) + VertConn = fullfile(path,VertConnFile); + save(Users.CurrentData.SubjectFile,'VertConn','-append') + load(VertConn) + end + VertConn = VertConn{nsurf}; + TessWinUserData.VertConn = VertConn; clear VertConn; + set(TessWin,'Userdata',TessWinUserData) + % Compute colormap for this surface + FV.vertices = get(hpatch,'Vertices'); + FV.faces = get(hpatch,'Faces'); + [vertexcolorh,map]=c_activ(FV,TessWinUserData.VertConn); clear FV + Curvature{nsurf} = vertexcolorh; + save(Visu.Tesselation,'Curvature','-append') + else + vertexcolorh = Curvature{nsurf}; + clear Curvature + end + + if strcmp(get(hpatch(1),'Visible'),'off') + set(hpatch,'FaceVertexCData',vertexcolorh) + end + % Now save it back to the Tesselation file + + else + + vertexcolorh = get(hpatch,'Userdata'); + vertexcolorh = vertexcolorh.CDepth; + + end + + cortex = get(hpatch,'Userdata'); + cortex.CDepth = vertexcolorh; + set(hpatch,'Userdata',cortex); + + else + + vertexcolorh = get(hpatch,'FaceVertexCdata'); + + end + + if ColorSensors + dataplot_cb DataOnSensors + end + + if ScalpMaps + dataplot_cb DataOnScalp + end + + if CorticalMap + dataplot_cb('CorticalMap',hpatch) + else + if get(hSelect.MapCurvature,'Value') + set(hpatch,'FaceVertexCData',vertexcolorh) + end + end + + set(hpatch,'Visible','on') + + vertexcolorh = get(hpatch,'FaceVertexCdata'); + + nmesh = 0; + for k = imesh + nmesh = nmesh + 1; + h = findobj(get(previous,'CurrentAxes'),'Tag',Comment{k},'Visible','on'); + if isempty(h) + + if k == nsurf & nclust > 0 % Some clustering has been selected - display clusters on the surface + set(h,'FacevertexCdata',Clusters{nsurf}.Cluster{nclust},'Userdata',Clusters{nsurf}.Cluster{nclust}') + colormap(rand(Clusters{nsurf}.NClusters(nclust),3)) + end + + hold on + + if Vals(k,1) == 1 + set(h,'edgecolor','none','facecolor','interp') + else + set(h,'edgecolor',[.7 .7 .7],'facecolor','none') + end + + else + + if isempty(vertexcolorh) + vertexcolorh = get(h,'FaceVertexCData'); + elseif iscell(vertexcolorh) + vertexcolorh = vertexcolorh{nmesh}; + end + + if Vals(k,1) == 1 + + if isempty(vertexcolorh) + set(h,'edgecolor','none','facecolor',[.5 .5 .5]) + else + set(h,'edgecolor','none','facecolor','interp') + end + + else + set(h,'edgecolor','interp','facecolor','none') + end + end + % Update envelope properties ------------------------------------------------------ + + ctet = get(h,'vertices'); + siz = size(vertexcolorh,2); + if size(vertexcolorh,1) == 1 + vertexcolorh = ones(size(ctet,1),1)*vertexcolorh; + end + + + if Vals(k,3) == 1 + vertexcolorh(find(ctet(:,2) < 0),:) = NaN * ones(length(find(ctet(:,2) < 0)),siz); + end + if Vals(k,4) == 1 + vertexcolorh(find(ctet(:,2) > 0),:) = NaN * ones(length(find(ctet(:,2) > 0)),siz); + end + if Vals(k,5) == 1 + vertexcolorh(find(ctet(:,1) > 0),:) = NaN * ones(length(find(ctet(:,1) > 0)),siz); + end + if Vals(k,6) == 1 + vertexcolorh(find(ctet(:,1) < 0),:) = NaN * ones(length(find(ctet(:,1) < 0)),siz); + end + if Vals(k,7) == 1 + vertexcolorh(find(ctet(:,3) > 0),:) = NaN * ones(length(find(ctet(:,3) > 0)),siz); + end + if Vals(k,8) == 1 + vertexcolorh(find(ctet(:,3) < 0),:) = NaN * ones(length(find(ctet(:,3) < 0)),siz); + end + + clear ctet + if iscell(vertexcolorh) + set(h,'FaceVertexCData',vertexcolorh{1},'Visible','on') + if length(hpatch)>1 % OrthoViews + for kk = 1:length(hpatch) + h = hpatch(kk); + set(h,'FaceVertexCData',vertexcolorh{1},'Visible','on') + end + + end + + else + if OrthoViews == 1 + set(hpatch,'FaceVertexCData',vertexcolorh,'Visible','on') + else + set(h,'FaceVertexCData',vertexcolorh,'Visible','on') + end + end + vertexcolorh = []; % Move to next surface + end + + figure(previous) + hold off + rotate3d on + if ~isempty(findobj(gcf,'Tag','MainAxes')) + if length(hpatch)>1 & length(imesh) == 1% suplots with only one surface to display (need to generalize this) + if ~strcmp(get(hpatch(4),'Visible'),'on') + set(gca,'View',get(findobj(gcf,'Tag','MainAxes'),'view')) + end + end + + end + + dataplot_cb mesh_lighting_props + + %---------------------------------------------------------------------------- +case 'listchan_create' % Selection of channel names for n-plot visualization + Visu = get(DATAPLOT,'Userdata'); + if isempty(Visu) + errordlg('Please load a data set first') + return + end + 0 + str = {'MEG','EEG','OTHER'}; + + LISTCHAN = findobj(0,'Tag','listchan'); + if isempty(LISTCHAN) + LISTCHAN = open('listchan.fig'); + end + + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)) - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)) - min(Visu.ChannelID{current})+1; + + available = findobj(LISTCHAN,'Tag','available'); + removed = findobj(LISTCHAN,'Tag','removed'); + + set(available,'String', {Visu.Channel(Visu.ChannelID{current}(goodchannels)).Name}); + + if ~isempty(badchannels) + set(removed,'String', {Visu.Channel(Visu.ChannelID{current}(badchannels)).Name}); + else + set(removed,'String', ''); + end + + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + %---------------------------------------------------------------------------- + +case 'channel_plot_remove' % Remove Channels + channel_select_win = findobj(0,'Tag','listchan'); + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + removeID = get(available,'Value'); + IDs = get(available,'String'); + chan = [1:length(IDs)]; + + set(available,'String', IDs(setdiff(chan,removeID))); + if isempty(get(removed,'String')) + set(removed,'String', [IDs(removeID)] ); + else + strtmp = ([cellstr(get(removed,'String'));IDs(removeID)]); + strtmp = sort(strtmp); + set(removed,'String', cellstr(strtmp)); + end + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + + %---------------------------------------------------------------------------- + +case 'channel_plot_restore' % Restore Channels - Make them become available again + channel_select_win = findobj(0,'Tag','listchan'); + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + chan = [1:length(IDs)]; + + set(removed,'Max',max([1,length(setdiff(chan,availableID))])) + set(removed,'Value',1,'String',IDs(setdiff(chan,availableID))); + + if isempty(get(available,'String')) + set(available,'String', [IDs(availableID)]); + else + strtmp = ([cellstr(get(available,'String'));IDs(availableID)]); + strtmp = sort(strtmp); + set(available,'String', cellstr(strtmp)); + end + set(available,'Value',1,'Max',length(get(available,'String'))) + + %---------------------------------------------------------------------------- + +case 'listchan_SelectAll' + + channel_select_win = findobj(0,'Tag','listchan'); + available = findobj(channel_select_win,'Tag','available'); + set(available,'Value',[1:get(available,'Max')]) + dataplot_cb channel_plot_remove + + %---------------------------------------------------------------------------- +case 'listchan_RemoveAll' + + channel_select_win = findobj(0,'Tag','listchan'); + available = findobj(channel_select_win,'Tag','removed'); + set(available,'Value',[1:get(available,'Max')]) + dataplot_cb channel_plot_restore + + %---------------------------------------------------------------------------- +case 'listchan_refresh' % Update the channel information / plots + + Visu = get(DATAPLOT,'Userdata'); + str = {'MEG','EEG','OTHER'}; + + channel_select_win = findobj(0,'Tag','listchan'); + removed = findobj(channel_select_win,'Tag','removed'); + available = findobj(channel_select_win,'Tag','available'); + handles = guihandles(channel_select_win); + ncol = str2num(get(handles.NumberOfColumns,'String')); % Number of columns in the layout + + if isempty(get(removed,'String')) + errordlg('Please Select Channels for the Plot first') + return + end + + [tmp,IDs] = intersect({Visu.Channel(Visu.ChannelID{current}).Name},get(removed,'String')); + + % Get time window + TIME_MIN = str2num(get(findobj(DATAPLOT,'Tag','time_min'),'String')); + TIME_MAX = str2num(get(findobj(DATAPLOT,'Tag','time_max'),'String')); + + if TIME_MAX > Visu.Data.Time(end) * 1000 + TIME_MAX = Visu.Data.Time(end) * 1000; + set(findobj(DATAPLOT,'Tag','time_max'),'String',num2str(TIME_MAX,5)) + end + + if TIME_MIN < Visu.Data.Time(1) * 1000 + TIME_MIN = Visu.Data.Time(1) * 1000; + set(findobj(DATAPLOT,'Tag','time_min'),'String',num2str(TIME_MIN,5)) + end + + delta_t = 1000*(Visu.Data.Time(2)-Visu.Data.Time(1)); + samples = round(([TIME_MIN:delta_t:TIME_MAX]-Visu.Data.Time(1)*1000)/delta_t)+1; + + M = max(max(abs(Visu.Data.F(Visu.ChannelID{current}(IDs),samples)))); + + fignplot = findobj(0,'Tag','nplot_win'); % Figure of overlaping plots for the current modality + if isempty(fignplot) + fig = figure; + delete(findobj(fig,'type','axes')) + movegui(fig,'center') + set(fig,'Tag','nplot_win') + else + figure(fignplot) + clf + end + + % Visualization + N = ceil(length(IDs)/ncol); % Maximum number of channels to visualize per column + + delta = .95/(N+1); % Space between plots (in normalized units) + hold on + for col = 1:ncol % For each column of the layout + + if col1 + axes + end + + i = 0; + + for k = IDscol + i = i+1; + plotwaves = plot([TIME_MIN:delta_t:TIME_MAX],Visu.Data.F(Visu.ChannelID{current}(k),samples)+(2*M*i)); + hold on + end + + set(gca,'units','normalized','ygrid','on','xgrid','on','Box','on',... + 'Position',[(col-1)*0.96/ncol + 0.039, 0.035, 0.80/ncol, 0.96],... + 'Yticklabel',{Visu.Channel(Visu.ChannelID{current}(IDscol)).Name},'Ytick',2*M*[1:length(IDscol)],... + 'FontName','Helvetica','FontSize',7,'FontUnits','Points','Fontweight','light',... + 'xColor',[.4 .4 .4], 'ycolor', [.05 .45 .80],'XMinorGrid','on',... + 'Xlim',[TIME_MIN,TIME_MAX],'Ylim',[0 2*M*(N+1)]) + % set(gca,'Fontunits','normal') + liine = line([0 0],get(gca,'Ylim'),'linewidth',1); + set(liine,'color','r','Tag','cursor') + end + + hold off + %--------------------------------------------------------------'-------------- +case 'selectchannels' % Selection of Good/Bad Channels + Visu = get(DATAPLOT,'Userdata'); + previous = findobj(0,'Tag','channel_select'); + + if length(current) > 1 + errordlg('Please select either MEG, EEG or OTHER data subset') + return + end + + for kur = 1:length(current) + + goodchannels = setdiff(Visu.ChannelID{current(kur)},find(Visu.Data.ChannelFlag == -1)) - min(Visu.ChannelID{current(kur)})+1; % Discard bad channels + + if ~isempty(previous) + figure(previous) + channel_select_win = previous; + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + channel_removed = get(channel_select_win,'Userdata'); + if isfield(channel_removed,str{current}) + eval(['removedIDs = channel_removed.',str{current},';']); + set(removed,'String',{Visu.ChannelID{current(kur)}(goodchannels(removedIDs)).Name}) + + set(removed,'Value',1,'Max',length(get(removed,'String'))) + chan = [1:length(Visu.ChannelID{current(kur)})]; + + set(available,'String',{Visu.Channel(Visu.ChannelID{current(kur)}(goodchannels(setdiff(chan,removedIDs)))).Name}); + set(available,'Value',1,'Max',length(get(available,'String'))) + else + set(removed,'String','') + set(available,'String', {Visu.Channel(Visu.ChannelID{current(kur)}(goodchannels)).Name}); + + set(available,'Max',length(Visu.ChannelID{current(kur)})) + set(removed,'Max',length(get(removed,'String'))) + end + else + channel_select_win = openfig('channel_select.fig'); + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)) - min(Visu.ChannelID{current(kur)})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)) - min(Visu.ChannelID{current(kur)})+1; + + removed = findobj(channel_select_win,'Tag','removed'); + available = findobj(channel_select_win,'Tag','available'); + + set(available,'String', {Visu.Channel(Visu.ChannelID{current(kur)}(goodchannels)).Name}); + + if ~isempty(badchannels) + set(removed,'String', {Visu.Channel(Visu.ChannelID{current(kur)}(badchannels)).Name}); + else + set(removed,'String', ''); + end + + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + end + end + + + set(channel_select_win,'Name',[modality{current(kur)},' Channels']) + + %---------------------------------------------------------------------------- + +case 'channel_remove' % Remove Channels + if length(current) > 1 + errordlg('Please select either MEG, EEG or OTHER data subset') + return + end + + channel_select_win = findobj(0,'Tag','channel_select'); + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + removeID = get(available,'Value'); + IDs = get(available,'String'); + if isempty(IDs) + return + end + chan = [1:length(IDs)]; + + set(available,'String', IDs(setdiff(chan,removeID))); + if isempty(get(removed,'String')) + set(removed,'String', [IDs(removeID)] ); + else + strtmp = ([cellstr(get(removed,'String'));IDs(removeID)]); + strtmp = sort(strtmp); + set(removed,'String', cellstr(strtmp)); + end + set(available,'Value',1,'Max',length(get(available,'String'))) + set(removed,'Value',1,'Max',max([1,length(get(removed,'String'))])) + + + %---------------------------------------------------------------------------- + +case 'channel_restore' % Restore Channels - Make them become available again + if length(current) > 1 + errordlg('Please select either MEG, EEG or OTHER data subset') + return + end + channel_select_win = findobj(0,'Tag','channel_select'); + available = findobj(channel_select_win,'Tag','available'); + removed = findobj(channel_select_win,'Tag','removed'); + availableID = get(removed,'Value'); + IDs = get(removed,'String'); + if isempty(IDs) + return + end + chan = [1:length(IDs)]; + + set(removed,'Max',max([1,length(setdiff(chan,availableID))])) + set(removed,'Value',1,'String',IDs(setdiff(chan,availableID))); + + if isempty(get(available,'String')) + set(available,'String', [IDs(availableID)]); + else + strtmp = ([cellstr(get(available,'String'));IDs(availableID)]); + strtmp = sort(strtmp); + set(available,'String', cellstr(strtmp)); + end + set(available,'Value',1,'Max',length(get(available,'String'))) + + + %---------------------------------------------------------------------------- +case 'GenerateAverage' % Generate Time-Locked Average of all Data Files in Current Study + + hDATAPLOT = guihandles(DATAPLOT); + + disp('Time-locked averaging of all data files from current study...') + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + + [DataDir,DataPopup,Leader] = find_brainstorm_files('data',fullfile(Users.STUDIES,path)); + ndatafiles = 0; + + for file = DataDir + + cd(fullfile(Users.STUDIES,path)) + if isempty(findstr(file{:},'results')) & isempty(findstr(file{:},'avr.mat')) + ndatafiles = ndatafiles+1 + load(file{:},'F','Time') + Users.CurrentData.DataFile = file{:}; + guidata(TASKBAR,Users) + + if get(hDATAPLOT.SetPeakLatency,'Value') % Adjust peak latency + Visu = get(DATAPLOT,'Userdata'); + Visu.Data.F = F; + Visu.Data.Time = Time; + set(DATAPLOT,'Userdata',Visu) + dataplot_cb SetPeakLatency + + %Adjust time window + Visu = get(DATAPLOT,'Userdata'); + if ndatafiles == 1 + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2)); + zeroLat = round(abs(Visu.Data.Time(1))/srate)+1; + zeroLatOld = zeroLat; + end + + end + + if ndatafiles == 1 + Fav = F; + iunder = findstr(file{:},'_'); % Generate average data file name + avFileName = file{:}(1:iunder(end)); + Mod = {'MEG','EEG','OTHER'}; + avFileName = [avFileName,Mod{current},'avr.mat']; + Data = load(file{:}); + + else + + if get(hDATAPLOT.SetPeakLatency,'Value') % Adjust peak latency + % Find sample corresponding to time 0ms + zeroLat = round(abs(Visu.Data.Time(1))/srate)+1; + if zeroLat < zeroLatOld + Fav = Fav(:,zeroLatOld-zeroLat+1:end); + % F = F(:,1:end-zeroLatOld+zeroLat); + Fav = Fav(:,1:min([size(F,2),size(Fav,2)])); + F = F(:,1:min([size(F,2),size(Fav,2)])); + zeroLatOld = zeroLat; + else + F = F(:,zeroLat-zeroLatOld+1:end); + % Fav = Fav(:,1:end-zeroLat+zeroLatOld); + Fav = Fav(:,1:min([size(F,2),size(Fav,2)])); + F = F(:,1:min([size(F,2),size(Fav,2)])); + zeroLat = zeroLatOld; + end + end + + Fav = Fav+F; + % Find maximum latency of this running average + Time(1) = sign(Visu.Data.Time(1))*(zeroLat-1)*srate; + Time = Time(1):srate:(Time(1)+(size(Fav,2)-1)*srate); + Visu.Data.Time = Time; + Visu.Data.F = Fav; + set(DATAPLOT,'Userdata',Visu) + Users.CurrentData.DataFile = avFileName; + guidata(TASKBAR,Users) + + dataplot_cb SetPeakLatency + + Visu = get(DATAPLOT,'Userdata'); + zeroLat = round(abs(Visu.Data.Time(1))/srate)+1; + zeroLatOld = zeroLat + end + end + end + + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2)); + % Find sample corresponding to time 0ms + + % New time vector + Time(1) = sign(Visu.Data.Time(1))*(zeroLat-1)*srate; + Time = Time(1):srate:(Time(1)+(size(Fav,2)-1)*srate); + Visu.Data.Time = Time; + set(hDATAPLOT.time_min,'String',num2str(Time(1)*1000,'%3.2f')); + set(hDATAPLOT.time_max,'String',num2str(Time(end)*1000,'%3.2f')); + + Data.F = Fav/ndatafiles; + Data.Time = Time; + + save_fieldnames(Data,avFileName); + disp('Time-locked averaging all data files from current study...->DONE') + disp([num2str(ndatafiles),' files averaged']) + + +%---------------------------------------------------------------------------- + +case 'channel_select_done' % Update the channel information / plots + + Visu = get(DATAPLOT,'Userdata'); + + if length(current) > 1 + errordlg('Please select either MEG, EEG or OTHER data subset') + return + end + + str = {'MEG','EEG','OTHER'}; + + channel_select_win = gcbf; + removed = findobj(channel_select_win,'Tag','removed'); + + [tmp,IDs] = intersect({Visu.Channel(Visu.ChannelID{current}).Name},get(removed,'String')); + + % Keep Removed Channels in Memory + channel_removed = get(channel_select_win,'Userdata'); + if ~isempty(channel_removed) + eval(['channel_removed.',str{current},' = IDs;']) + set(channel_select_win,'Userdata',channel_removed); + end + + if isempty(IDs) + Visu.Data.ChannelFlag(Visu.ChannelID{current}) = ones(size(Visu.ChannelID{current})); %Restore to Good Channel + else + Visu.Data.ChannelFlag(IDs + min(Visu.ChannelID{current}) - 1) = -ones(size(IDs)); % Mark as bad, i.e. -1 + end + + Visu.Alter = 1; % Data set is altered from original version (channels were removed - keep that in mind when calling SourceImaging tools) + + set(DATAPLOT,'Userdata',Visu) + + figsingle = findobj(0,'Tag',['waves_single',int2str(current)]); % Figure of overlaping plots for the current modality + if isempty(figsingle) + return + end + +% if current==2 % In case of EEG data - remove average reference when requested +% dataplot_cb RemoveEEGAverage +% end + + ChannelSelectAllDataSets = findobj(channel_select_win,'Tag','ChannelSelectAllDataSets');; + if get(ChannelSelectAllDataSets,'Value') % Apply this selection to all the data setsfrom this study + disp('Updating all data files from current study...') + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + + [DataDir,DataPopup,Leader] = find_brainstorm_files('data',fullfile(Users.STUDIES,path)); + ndatafiles = 0; + clear ChannelFlag + for file = DataDir + cd(fullfile(Users.STUDIES,path)) + if isempty(findstr(file{:},'results')) + load(file{:},'ChannelFlag') + end + if exist('ChannelFlag','var') % Skip this file + ndatafiles = ndatafiles+1 + ChannelFlag = Visu.Data.ChannelFlag; + save(file{:},'ChannelFlag','-append') + clear ChannelFlag + end + end + disp('Updating all data files from current study...-> DONE') + disp([num2str(ndatafiles),' file updated']) + else + disp('Updating current data file...') + cd(Users.STUDIES) + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + cd(path) + clear ChannelFlag + load(Users.CurrentData.DataFile,'ChannelFlag') + if exist('ChannelFlag','var') % Skip this file + ChannelFlag = Visu.Data.ChannelFlag; + save(Users.CurrentData.DataFile,'ChannelFlag','-append') + clear ChannelFlag + end + disp('Updating current data file... -> DONE') + end + + dataplot_cb quicklook + + %---------------------------------------------------------------------------- + +case '2dlayout' + Visu = get(DATAPLOT,'Userdata'); + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + channel_select_win = findobj(0,'Tag','channel_select'); + layout = findobj(0,'Tag',['layout_',modality{current}]); + + timescale = 10; + + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1; + else + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ;;%Visu.ChannelID{current}; + badchannels = []; + end + + TIME_MIN = str2num(get(findobj(DATAPLOT,'Tag','time_min'),'String')); + TIME_MAX = str2num(get(findobj(DATAPLOT,'Tag','time_max'),'String')); + delta_t = 1000*(Visu.Data.Time(2)-Visu.Data.Time(1)); + samples = round(([TIME_MIN:delta_t:TIME_MAX]-Visu.Data.Time(1)*1000)/delta_t)+1; + + + j = 0; + for chan = goodchannels%Visu.ChannelID{current} + j = j+1; + chanloc(:,j) = Visu.Channel(chan).Loc(:,1); + end + + figure + set(gcf,'Color','k') + + minn = min(chanloc')'; + maxx = max(chanloc')'; + chanloc(3,:) = chanloc(3,:) - maxx(3); + + [TH,PHI,R] = cart2sph(chanloc(1,:),chanloc(2,:),chanloc(3,:)); + PHI2 = zeros(size(PHI)); + R2 = R./cos(PHI).^.2; + + [Y,X] = pol2cart(TH,R2); + dat = Visu.Data.F(goodchannels,samples); + M = max(abs(dat(:))); + + My = max(abs(Y)); + Mx = max(abs(X)); + Mt = TIME_MAX-TIME_MIN; + + + for i = 1:length(goodchannels) + dat = Visu.Data.F(goodchannels(i),samples); + h = plot(Mx*[TIME_MIN:delta_t:TIME_MAX]/(timescale*Mt)-X(i),(My*dat/(10*M)+Y(i)),'color',[.9 .9 .9]); + set(h,'ButtondownFcn','dataplot_cb line_select') + hold on + ttl = text(Mx*TIME_MIN/(timescale*Mt)-X(i),.5*My*M/(10*M)+Y(i),Visu.Channel((goodchannels(i))).Name); + set(ttl,'fontsize',8,'color',.8*[1 1 1]) + end + axis equal + axis off + + %---------------------------------------------------------------------------- +case 'mapping_create' % Generates SLIDES and/or MOVIES + + Visu = get(DATAPLOT,'Userdata'); + MEG = get(findobj(DATAPLOT,'Tag','MEG'),'value'); + EEG = get(findobj(DATAPLOT,'Tag','EEG'),'value'); + OTHER = get(findobj(DATAPLOT,'Tag','OTHER'),'value'); + current = find([MEG,EEG,OTHER] == 1); + + mapping_win = findobj(0,'Tag','mapping'); + if isempty(mapping_win) + open mapping.fig; + mapping_win = findobj(0,'Tag','mapping'); + else + return + end + + RAW = findobj(mapping_win ,'Tag','raw'); + GRADIENT = findobj(mapping_win ,'Tag','gradient'); + MAGNETIC = findobj(mapping_win,'Tag','magnetic'); + + if current == 1 % If MEG + set([RAW,GRADIENT,MAGNETIC],'enable','on') + set(RAW,'Value',1) + else + set([RAW,GRADIENT,MAGNETIC],'enable','off') + end + + start = findobj(mapping_win,'Tag','start'); + step = findobj(mapping_win,'Tag','step'); + stop = findobj(mapping_win,'Tag','stop'); + current_time = findobj(mapping_win,'Tag','current_time'); + slider_time = findobj(mapping_win,'Tag','slider_time'); + go = findobj(mapping_win,'Tag','go'); + SPHERE = findobj(mapping_win,'Tag','sphere'); + fit = findobj(mapping_win,'Tag','fit'); + ROTATE = findobj(mapping_win,'Tag','rotate'); + fit = findobj(mapping_win,'Tag','fit'); + slides = findobj(mapping_win,'Tag','slides'); + single = findobj(mapping_win,'Tag','single'); + MOVIE = findobj(mapping_win,'Tag','movie'); + + handles = guihandles(mapping_win); + + set(mapping_win,'Name',[get(mapping_win,'Name'), ' - ', modality{current}]) + + set(start,'String', num2str(1000*Visu.Data.Time(1))) + set(stop,'String', num2str(1000*Visu.Data.Time(end))) + if length(Visu.Data.Time) > 1 + set(step,'String', num2str(1000*(Visu.Data.Time(2)-Visu.Data.Time(1)),2)) + else + set(step,'String', 0) + end + + + TIME_MIN = str2num(get(findobj(DATAPLOT,'Tag','time_min'),'String')); + TIME_MAX = str2num(get(findobj(DATAPLOT,'Tag','time_max'),'String')); + + if TIME_MAX > Visu.Data.Time(end) * 1000 + TIME_MAX = Visu.Data.Time(end) * 1000; + set(findobj(DATAPLOT,'Tag','time_max'),'String',num2str(TIME_MAX,5)) + end + + if TIME_MIN < Visu.Data.Time(1) * 1000 + TIME_MIN = Visu.Data.Time(1) * 1000; + set(findobj(DATAPLOT,'Tag','time_min'),'String',num2str(TIME_MIN,5)) + end + + if ~isempty(mapping_win) + slider_time = findobj(mapping_win,'Tag','slider_time'); + if length(Visu.Data.Time) > 1 + set(slider_time,'enable','on') + set(slider_time,'Min',TIME_MIN,'Max',TIME_MAX) + else + set(slider_time,'Min',TIME_MIN,'Max',2*TIME_MAX) + set(slider_time,'enable','off') + end + + end + set(slider_time,'Value',TIME_MIN,'enable','on') + + set(current_time,'String',num2str(get(slider_time,'Value'),4)) + set(single,'Value',1) + mutincomp([single,slides,MOVIE]) + set(SPHERE,'Value',1) + mutincomp([SPHERE,fit,handles.scalp]) + + % Draw time cursor + figsingle = findobj(0,'Tag',['waves_single',int2str(current)]); % Figure of overlaping plots for the current modality + if ~isempty(figsingle) + figure(figsingle) + ctime = get(slider_time,'Value'); + cursor = line([ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + end + + fignplot = findobj(0,'Tag','nplot_win'); % superimposed n-plots + if ~isempty(fignplot) + figure(fignplot) + ctime = get(slider_time,'Value'); + cursor = line([ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + end + %---------------------------------------------------------------------------- + +case 'mapping_slider' % Update of the current time sample using the slider + + Visu = get(DATAPLOT,'Userdata'); + + mapping_win = openfig('mapping.fig','reuse'); + current_time = findobj(mapping_win,'Tag','current_time'); + slider_time = findobj(mapping_win,'Tag','slider_time'); + step = findobj(mapping_win,'Tag','step'); + + set(current_time,'String',num2str(get(slider_time,'Value'),5)) + + ctime = get(slider_time,'Value')/1000; + + % Draw time cursor + for k=1:length(current) + % Figure of overlaping plots for the current modality + figsingle{k} = findobj(0,'Tag',['waves_single',int2str(current(k))]); + if ~isempty(figsingle{k}) + figure(figsingle{k}) + cursor = findobj(figsingle{k},'Tag','cursor'); + if isempty(cursor) + cursor = line(1000*[ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',1,'Tag','cursor','erasemode','Xor') + else + set(cursor,'Xdata',1000*[ctime ctime]) + end + + text_cursor = findobj(figsingle{k},'Tag','text_cursor'); + if isempty(text_cursor) + text_cursor = text(1000*[ctime],max(get(gca,'Ylim'))/1.1,num2str(1000*ctime,4)); + set(text_cursor ,'Horizontalalignment','right','Fontweight','bold','color','k','fontsize',12,... + 'Tag','text_cursor','erasemode','xor') + else + set(text_cursor,'Position',[1000*[ctime],max(get(gca,'Ylim'))/1.1],'String',num2str(1000*ctime,4)) + end + end + end + + fignplot = findobj(0,'Tag','nplot_win'); % Figure of overlaping plots for the current modality + if ~isempty(fignplot) + figure(fignplot) + cursor = findobj(fignplot,'Tag','cursor'); + if isempty(cursor) + cursor = line(1000*[ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + else + set(cursor,'Xdata',1000*[ctime ctime]) + end + + text_cursor = findobj(fignplot,'Tag','text_cursor'); + if isempty(text_cursor) + text_cursor = text(1000*[ctime],.98*max(get(gca,'Ylim')),num2str(1000*ctime,4)); + set(text_cursor ,'Horizontalalignment','right','Fontweight','demi','color','k',... + 'fontsize',10,'fontunits','points',... + 'Tag','text_cursor','erasemode','xor') + else + set(text_cursor,'Position',[1000*[ctime],.98*max(get(gca,'Ylim'))],'String',num2str(1000*ctime,4)) + end + end + + % SurfaceViewer update + TessSelectWin = findobj(0,'Tag','tesselation_select'); + if ~isempty(TessSelectWin) % Check if Surface Viewer is open + handles = guihandles(TessSelectWin ); + ScalpMaps = get(handles.ScalpMaps,'Value'); + ColorSensors = get(handles.ColorSensors,'Value'); + CorticalMap = get(handles.CorticalMap,'Value'); + dataplot_cb tesselation_select_done + end + + %Update data mapping if exists + for k = 1:length(current) + map_single_win = findobj(0,'Tag',['map_single',int2str(current(k))]); + if isempty(map_single_win), return, end + map_sph = get(map_single_win,'Userdata'); + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2) ); + ctime = round(( get(slider_time,'Value')/1000-Visu.Data.Time(1))/srate)+1; + mapping_win = findobj(0,'Tag','mapping'); + RAW = findobj(mapping_win ,'Tag','raw'); + GRADIENT = findobj(mapping_win ,'Tag','gradient'); + MAGNETIC = findobj(mapping_win,'Tag','magnetic'); + if strcmp(get(RAW,'enable'),'on') % MEG Case + RAW = get(RAW,'Value'); + GRADIENT = get(GRADIENT,'Value'); + MAGNETIC = get(MAGNETIC,'Value'); + current_visu = find([RAW,GRADIENT,MAGNETIC] == 1); + else + current_visu = NaN; + end + ABSOLUTE = get(findobj(mapping_win,'Tag','ABSOLUTE'),'value'); + RELATIVE = get(findobj(mapping_win,'Tag','RELATIVE'),'value'); + + % Channels Locations: + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1; + else + goodchannels = setdiff(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; + badchannels = []; + end + data = Visu.Data.F(goodchannels,ctime) ; + + if (current_visu == 2) & (current(k) == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + channels = [1:length(Visu.ChannelID{current(k)})]; + odd_channels = channels(find(rem(channels,2) == 1)); + if ~isempty(badchannels) + odd = badchannels(find(rem(badchannels,2) == 1)); + even = setdiff(badchannels,odd); + odd = unique([odd',intersect(odd_channels ,(even - 1))]); + else + odd = []; + even = []; + end + + good_odd_channels = setdiff(odd_channels,odd); + grad_meg = []; + j = 0; + for i = (good_odd_channels) + j = j+1; + grad_meg(j) = norm([Visu.Data.F(i,ctime),Visu.Data.F(i+1,ctime)]); + end + data = grad_meg; + elseif current_visu == 3 & current(k) == 1 + data = Visu.MNEdata(:,ctime); + end + + try + cdata_map = griddata(map_sph.x,map_sph.y,data,map_sph.xs,map_sph.ys,'invdist'); + catch + errordlg('First Hit the Refresh Button of the Mapping Window when Channels are Removed') + return + end + + set(map_sph.handle,'CData',cdata_map) + + if RELATIVE == 1 + if current_visu == 3 + datacomplete = Visu.MNEdata; + else + datacomplete = Visu.Data.F(goodchannels,:); + end + + Max = max(abs(datacomplete(:))); + figure(map_single_win) + if (current_visu == 2) & (current(k) == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + caxis([0,Max]) + else + caxis([-Max,Max]) + end + else + figure(map_single_win) + if (current_visu == 2) & (current(k) == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + caxis([0,max(abs(data))]) + else + caxis([-max(abs(data)),max(abs(data))]) + end + + end + end + + %---------------------------------------------------------------------------- + +case 'set_current_time' + Visu = get(DATAPLOT,'Userdata'); + + mapping_win = findobj(0,'Tag','mapping'); + current_time = findobj(mapping_win,'Tag','current_time'); + slider_time = findobj(mapping_win,'Tag','slider_time'); + step = findobj(mapping_win,'Tag','step'); + + ctime = str2num(get(current_time,'String'))/1000; + + set(slider_time,'Value',1000*ctime); + dataplot_cb mapping_slider + + % Draw time cursor + figsingle = findobj(0,'Tag',['waves_single',int2str(current)]); % Figure of overlaping plots for the current modality + if ~isempty(figsingle) + figure(figsingle) + cursor = findobj(figsingle,'Tag','cursor'); + if isempty(cursor) + cursor = line(1000*[ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + else + set(cursor,'Xdata',1000*[ctime ctime]) + end + + text_cursor = findobj(figsingle,'Tag','text_cursor'); + if isempty(text_cursor) + text_cursor = text([1000*ctime],max(get(gca,'Ylim'))/1.1,num2str(1000*ctime,4)); + set(text_cursor ,'Horizontalalignment','right','Fontweight','bold','color','k','fontsize',12,... + 'Tag','text_cursor','erasemode','xor') + else + set(text_cursor,'Position',[1000*[ctime],max(get(gca,'Ylim'))/1.1],'String',num2str(1000*ctime,4)) + end + end + + + % Draw time cursor + fignplot = findobj(0,'Tag','nplot_win'); + if ~isempty(fignplot) + figure(fignplot) + cursor = findobj(fignplot,'Tag','cursor'); + if isempty(cursor) + cursor = line(1000*[ctime ctime],get(gca,'Ylim')); + set(cursor,'color','r','linewidth',3,'Tag','cursor','erasemode','Xor') + else + set(cursor,'Xdata',1000*[ctime ctime]) + end + + text_cursor = findobj(fignplot,'Tag','text_cursor'); + if isempty(text_cursor) + text_cursor = text(1000*[ctime],max(get(gca,'Ylim')),num2str(1000*ctime,4)); + set(text_cursor ,'Horizontalalignment','right','Fontweight','bold','color','k','fontsize',12,... + 'Tag','text_cursor','erasemode','xor') + else + set(text_cursor,'Position',[1000*[ctime],max(get(gca,'Ylim'))],'String',num2str(1000*ctime,4)) + end + end + + %Update data mapping if exists + map_single_win = findobj(0,'Tag',['map_single',int2str(current)]); + if isempty(map_single_win), return, end + map_sph = get(map_single_win,'Userdata'); + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2) ); + ctime = round((ctime-Visu.Data.Time(1))/srate)+1; + mapping_win = findobj(0,'Tag','mapping'); + RAW = findobj(mapping_win ,'Tag','raw'); + GRADIENT = findobj(mapping_win ,'Tag','gradient'); + MAGNETIC = findobj(mapping_win,'Tag','magnetic'); + if strcmp(get(RAW,'enable'),'on') % MEG Case + RAW = get(RAW,'Value'); + GRADIENT = get(GRADIENT,'Value'); + MAGNETIC = get(MAGNETIC,'Value'); + current_visu = find([RAW,GRADIENT,MAGNETIC] == 1); + else + current_visu = NaN; + end + ABSOLUTE = get(findobj(mapping_win,'Tag','ABSOLUTE'),'value'); + RELATIVE = get(findobj(mapping_win,'Tag','RELATIVE'),'value'); + + % Channels Locations: + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1; + else + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));%- min(Visu.ChannelID{current})+1 ; + badchannels = []; + end + data = Visu.Data.F(goodchannels,ctime) ; + + if (current_visu == 2) & (current == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + channels = [1:length(Visu.ChannelID{current})]; + odd_channels = channels(find(rem(channels,2) == 1)); + if ~isempty(badchannels) + odd = badchannels(find(rem(badchannels,2) == 1)); + even = setdiff(badchannels,odd); + odd = unique([odd',intersect(odd_channels ,(even - 1))]); + else + odd = []; + even = []; + end + + good_odd_channels = setdiff(odd_channels,odd); + grad_meg = []; + j = 0; + for i = (good_odd_channels) + j = j+1; + grad_meg(j) = norm([Visu.Data.F(i,ctime),Visu.Data.F(i+1,ctime)]); + end + data = grad_meg; + end + + try + cdata_map = griddata(map_sph.x,map_sph.y,data,map_sph.xs,map_sph.ys,'invdist'); + catch + errordlg('First Hit the Refresh Button of the Mapping Window when Channels are Removed') + return + end + + set(map_sph.handle,'CData',cdata_map) + if RELATIVE == 1 + + if current_visu == 3 + datacomplete = Visu.MNEdata; + else + datacomplete = Visu.Data.F(goodchannels,:); + end + Max = max(abs(datacomplete(:))); + figure(map_single_win) + if (current_visu == 2) & (current == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + caxis([0,Max]) + else + caxis([-Max,Max]) + end + + else + figure(map_single_win) + if (current_visu == 2) & (current == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + caxis([0,max(abs(data))]) + else + caxis([-max(abs(data)),max(abs(data))]) + end + + end + + + %----------------------------------------------------------------------------------------------- + +case 'gomapping' % Display the map according to featured parameters + + set(findobj(0,'Tag','rotate'),'Value',0) + + Visu = get(DATAPLOT,'Userdata'); + + str = {'MEG','EEG','OTHER'}; + mapping_win = findobj(0,'Tag','mapping'); + + ABSOLUTE = get(findobj(mapping_win,'Tag','ABSOLUTE'),'value'); + RELATIVE = get(findobj(mapping_win,'Tag','RELATIVE'),'value'); + + RAW = findobj(mapping_win ,'Tag','raw'); + GRADIENT = findobj(mapping_win ,'Tag','gradient'); + MAGNETIC = findobj(mapping_win,'Tag','magnetic'); + if strcmp(get(RAW,'enable'),'on') % MEG Case + RAW = get(RAW,'Value'); + GRADIENT = get(GRADIENT,'Value'); + MAGNETIC = get(MAGNETIC,'Value'); + current_visu = find([RAW,GRADIENT,MAGNETIC] == 1); + else + current_visu = NaN; + end + + handles = guihandles(mapping_win); + + % Detect Display/Type + display_type = get([handles.single,handles.slides,handles.movie],'Value'); + head_shape =(get([handles.sphere,handles.fit,handles.scalp],'Value')); % Sphere, Adujst to sensors or map to scalp. + head_shape =find([head_shape{:}]); + + for k = 1:length(current) + % Channels Locations: + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels{k} = setdiff(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1)); + badchannels{k} = intersect(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1)); + else + goodchannels{k} = setdiff(Visu.ChannelID{current(k)},find(Visu.Data.ChannelFlag == -1)); + badchannels{k} = []; + end + + j = 0; + for chan = goodchannels{k} + j = j+1; + chanloc{k}(:,j) = Visu.Channel(chan).Loc(:,1); + end + end + + %------------------------------------------------------------- + + % Check if we have access to the projection of the magnetic field + + % Load MNE matrix in the headmodel.mat file + if ~isfield(Visu.Data,'System') + Visu.Data.System = 'ctf'; + end + if ~isfield(Visu,'MNEdata') & ~strcmp(Visu.Data.System,'ctf') % non ctf systems only + + rooot = findstr(Users.CurrentData.StudyFile,'brainstormstudy.mat'); + if isempty(rooot) + errordlg('Study file name should be of the form ''*brainstormstudy.mat''') + return + end + rooot = Users.CurrentData.StudyFile(1:rooot-2); + HeadModelFile = fullfile(Users.STUDIES,[rooot ,'_headmodel.mat']); + MEG = (find(current == 1)); + if ~isempty(MEG) % MEG was selected as a modality + if verbose + disp('Computing gain matrix for Min. Norm estimate of the magnetic field from sensors...') + drawnow + end + + sensMEGMNE = goodchannels{MEG}; + global ChannelFlag + ChannelFlag = ones(length(Visu.Channel),1); + ChannelFlag(badchannels{MEG}) = -1; + nsrc = length(sensMEGMNE); + mne_src = [ones(size(chanloc{MEG})).*chanloc{MEG}/3]; % Choose sources this way -> hence they are inside the sensor helmet + % Sources should be quite deep to smooth out their contribution to the sensors + Chan = Visu.Channel(sensMEGMNE); + [Chan.Weight] = deal([1 0]); % Null weight associated to second coil of the gradiometer + + mass = mean(chanloc{MEG}'); % center of mass of the scalp vertex locations + R0 = mean(norlig(chanloc{MEG}' - ones(size(chanloc{MEG}',1),1)*mass)); % Average distance betw + vec0 = [mass,R0]; + [minn,brp] = fminsearch('dist_sph',vec0,[],chanloc{MEG}'); + center = minn(1:end-1)'; % 3x1 + R = minn(end); + + [Param(1:length(sensMEGMNE))] = deal(struct('Center',center,'Radii',R)); + Par = Param; + + Gmne2mag = os_meg(mne_src, Chan, Par, -1); + Gmne2mag = Gmne2mag(:,1:3:end); + Gmne2grad = os_meg(mne_src, Visu.Channel(sensMEGMNE), Par, -1); + Gmne2grad = Gmne2grad(:,1:3:end); + + matt = Gmne2grad'*Gmne2grad; + MNEMag = Gmne2mag * inv(matt+1e-6*norm(matt,'fro')*eye(size(matt)))*Gmne2grad'; + + clear Par Chan + + if verbose + disp('Computing gain matrix for Min. Norm estimate of the magnetic field from sensors...-> DONE') + drawnow + end + + if ~exist(HeadModelFile,'file') + save(HeadModelFile,'MNEMag') + else + save(HeadModelFile,'MNEMag','-append') + end + + Visu.MNEdata = MNEMag*Visu.Data.F(goodchannels{MEG},:); + else + load(HeadModelFile,'MNEMag'); + end + + set(DATAPLOT,'Userdata',Visu) + end + + %------------------------------------------------------------- + + % Sampling rate + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2) ); % Assuming time is in sec. + + for kur = 1:length(current) + + switch find([display_type{:}]) + + case 1 % Single Window + % Detect 'Single-Map' window; creates if does not exist + map_single_win = findobj(0,'Tag',['map_single',int2str(current(kur))]); + if isempty(map_single_win) + map_single_win = open('map_single.fig'); + set(map_single_win,'Tag',['map_single',int2str(current(kur))],'Name',... + [str{current(kur)},' Mapping'],... + 'color',backcolor); + else + figure(map_single_win) + end + + ctime = round((get(handles.slider_time,'Value')/1000-Visu.Data.Time(1))/srate)+1; + data = Visu.Data.F(goodchannels{kur},ctime) ; + + if (current_visu == 2) & (current(kur) == 1)% & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + channels = [1:length(goodchannels{kur})]; + odd_channels = goodchannels{kur}(find(rem(goodchannels{kur},2) == 1)); + + if ~isempty(badchannels{kur}) + odd = badchannels{kur}(find(rem(badchannels{kur},2) == 1)); + even = setdiff(badchannels{kur},odd); + odd = unique([odd',intersect(odd_channels,(even - 1))]); + else + odd = []; + even = []; + end + + good_odd_channels = setdiff(odd_channels,odd); + [c,ia,ib] = intersect(goodchannels{kur},good_odd_channels);%-goodchannels(1)+1); + chanloc = chanloc(:,ia); + grad_meg = []; + j = 0; + for i = good_odd_channels + j = j+1; + grad_meg(j) = norm([Visu.Data.F(i,ctime),Visu.Data.F(i+1,ctime)]); + end + data = grad_meg; + + elseif current_visu == 3 & current(kur) == 1 % MEG and MN estimation of the magnetic field at the planar gradiometers + data = Visu.MNEdata(:,ctime); + end + + switch head_shape + case 1 % Sphere + [x,y,z,xs,ys,sensor,map_sph] = carto_sph((chanloc{kur})',data,[0 0 0]); + if get(handles.ShowSensorLocs,'Value') + set(sensor,'Visible','on'); + else + set(sensor,'Visible','off'); + end + + if current(kur) == 1 + if exist('good_odd_channels','var') + n_chan = length(good_odd_channels); + name = good_odd_channels; + else + n_chan = length(goodchannels{kur}); + name = goodchannels{kur} - min(Visu.ChannelID{current(kur)})+1 ; + end + + if get(handles.ShowSensorLabels,'Value') + for i = 1:n_chan + h = text(1.05*x(i),1.05*y(i),1.05*z(i),Visu.Channel(goodchannels{kur}(i)).Name); + set(h,'horizontalalignment','center','fontsize',8,'color',... + textcolor,'fontweight','normal') + end + end + else + if get(handles.ShowSensorLabels,'Value') + for i = 1:length(goodchannels{kur}) + h = text(1.05*x(i),1.05*y(i),1.05*z(i),Visu.Channel(goodchannels{kur}(i)).Name); + set(h,'horizontalalignment','center','fontsize',10,'color',... + textcolor,'fontweight','bold') + end + end + end + axis vis3d, %axis equal + if ~isfield(Visu.Data,'Device'); + Visu.Data.Device = 'jpol'; % Default setting + end + + if findstr(lower(Visu.Data.Device),'ctf') + view(-90,90) % Noise pointing upwards + end + + case 2 % Sensors shape + [x,y,xs,ys,sensors,map_sph] = carto_sensors(chanloc{kur}',data); + + case 3 % Scalp Surface + close(map_single_win) + + dataplot_cb mesh_rendering + TessWin = findobj(0,'Tag','tesselation_select'); + figure(TessWin) + set(findobj(TessWin,'Tag','DataVisualization'),'Value',2) + dataplot_cb AddData + return + end + + if RELATIVE == 1 + + if current_visu == 3 + datacomplete = Visu.MNEdata; + else + datacomplete = Visu.Data.F(goodchannels{kur},:); + end + M = max(abs(datacomplete(:))); + % MEG with bad channels and visualization of the gradient amplitude + if (current_visu == 2) & (current(kur) == 1) + caxis([0,M]) + colormap hot + clrbr = colorbar('horiz'); + set(clrbr,'xcolor',frontcolor,'ycolor',frontcolor) + else + caxis([-M,M]) + end + + else + if (current_visu == 2) & (current(kur) == 1)% MEG with bad channels and visualization of the gradient amplitude + caxis([0,max(abs(data))]) + else + caxis([-max(abs(data)),max(abs(data))]) + end + + end + + dataplot_cb Colorbar_mapping + + map_sph.handle = map_sph; + map_sph.x = x; + map_sph.y = y; + map_sph.xs = xs; + map_sph.ys = ys; + set(map_single_win,'Userdata',map_sph) + + + case 2 % Slides + sstart = str2num(get(handles.start,'String'))/1000; + if sstart < Visu.Data.Time(1) + sstart = Visu.Data.Time(1); + end + + sstep = str2num(get(handles.step,'String'))/1000; + + sstop = str2num(get(handles.stop,'String'))/1000; + if sstop > Visu.Data.Time(end) + sstop = Visu.Data.Time(end); + end + + samples = round(([sstart,sstop]-Visu.Data.Time(1))/srate)+1; + sstep = round(sstep/srate); + samples = samples(1):sstep:samples(2); + nsamples = length(samples); + if nsamples > 40 % Warning, too many slides may take a while to create. + button = questdlg({'You have requested ',int2str(nsamples),' slide(s)','Do you still want to proceed ?'},'','Yes','No','Yes'); + if strcmp(button,'No') + return + end + end + + map_slides_win = findobj(0,'Tag',['map_slides',int2str(current(kur)),'_',get(handles.start,'String'),'_',get(handles.step,'String'),'_',get(handles.stop,'String')]); + + if isempty(map_slides_win ) + map_slides_win = open('map_single.fig'); + set(map_slides_win ,'Tag',['map_slides',int2str(current(kur)),'_',get(handles.start,'String'),'_',get(handles.step,'String'),'_',get(handles.stop,'String')],... + 'color',backcolor); + + drawnow + + else + figure(map_slides_win) + end + + % Figure Layout + k = size(samples,2); + c = ceil(sqrt(k)); + r = ceil(sqrt(k)); + switch head_shape + case 1 % Sphere + iplot = 0; + for ctime = samples + iplot = iplot+1; + figure(map_slides_win) + subplot(c,r,iplot) + axis off + data = Visu.Data.F(goodchannels{kur},ctime)+eps; + + if (current_visu == 2) & (current == 1) % & ~isempty(badchannels) % MEG with bad channels and visualization of the gradient amplitude + if ctime == samples(1) + channels = [1:length(Visu.ChannelID{current(kur)})]; + odd_channels = channels(find(rem(channels,2) == 1)); + if ~isempty(badchannels{kur}) + odd = badchannels{kur}(find(rem(badchannels{kur},2) == 1)); + even = setdiff(badchannels{kur},odd); + odd = unique([odd',intersect(odd_channels,(even - 1))]); + + else + odd = []; + even = []; + end + good_odd_channels = setdiff(odd_channels,odd); + [cc,ia,ib] = intersect(goodchannels{kur},good_odd_channels-goodchannels{kur}(1)+1); + chanloc{kur} = chanloc{kur}(:,ia); + end + grad_meg = []; + j = 0; + for i = (good_odd_channels) + j = j+1; + grad_meg(j) = norm([Visu.Data.F(i,ctime),Visu.Data.F(i+1,ctime)]); + end + data = grad_meg; + elseif current_visu == 3 & current(kur) == 1 + data = Visu.MNEdata(:,ctime); + end + + if iplot == 1 + [x,y,z,xs,ys,sensor,map_sph] = carto_sph(chanloc{kur}',data,[0 0 0]); + set(findobj(get(gca,'Children'),'Type','line'),'Visible','off') + axorig = get(map_sph,'Parent'); + set(gcf,'CurrentAxes',axorig) + cmap = get(gcf,'Colormap'); + map_sph2 = copyobj(map_sph,gca); % Trick to enforce proper scaling of the axis + delete(map_sph) + map_sph = map_sph2; + else + map_sph2 = copyobj(map_sph,gca); + cdata_map = griddata(x,y,data,xs,ys,'invdist'); + set(map_sph2,'CData',cdata_map) + end + + if RELATIVE == 1 + if iplot == 1 + if current_visu == 3 + datacomplete = Visu.MNEdata; + else + datacomplete = Visu.Data.F(goodchannels{kur},:); + end + M = max(abs(datacomplete(:))); + end + caxis([-M,M]) + else + caxis([-max(abs(data)),max(abs(data))]) + end + axis equal + if findstr(lower(Visu.Data.Device),'ctf') + view(-90,90) % Noise pointing upwards + end + axis tight + + h = title(num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4)); + set(h,'fontweight','normal','color',frontcolor,'Fontname','helvetica','Fontsize',8,'FontUnits','Point') + %set(h,'fontunits','normal') + % SurfaceViewer update + TessSelectWin = findobj(0,'Tag','tesselation_select'); + if ~isempty(TessSelectWin) % Check if Surface Viewer is open + cortx_handles = guihandles(TessSelectWin ); + ScalpMaps = get(cortx_handles.ScalpMaps,'Value'); + ColorSensors = get(cortx_handles.ColorSensors,'Value'); + CorticalMap = get(cortx_handles.CorticalMap,'Value'); + previous = findobj(0,'tag','tessellation_window'); + if ctime == samples(1); + pprevious = findobj(0,'tag','tesselation_select'); + hpprevious = guihandles(pprevious); + OrthoViews = get(hpprevious.OrthoViews,'Value'); +% clear hprevious + end + + SlidesWin = findobj(0,'tag','subplot_tess_window'); + if OrthoViews == 0 + if isempty(SlidesWin) + SlidesWin = open('tessellation_window.fig'); + set(SlidesWin,'tag','subplot_tess_window'); + end + else % Open a new window for each time sample when OrthoViews are requested + SlidesWin = open('tessellation_window.fig'); + set(SlidesWin,'tag','subplot_tess_window'); + end + + mapping_win = findobj(0,'Tag','mapping'); + + if ctime == samples(1) | OrthoViews == 1 + phandles = guihandles(previous); + VIEW = get(phandles.MainAxes,'view'); + Lights = findobj(phandles.MainAxes,'type','light'); + Colormap = get(previous,'Colormap'); + set(SlidesWin,'Colormap',Colormap) + end + + if ~isempty(mapping_win) + slider_time = findobj(mapping_win,'Tag','slider_time'); + current_time= findobj(mapping_win,'Tag','current_time'); + end + + set(slider_time,'Value',1000*Visu.Data.Time(ctime)) + set(current_time,'String',1000*Visu.Data.Time(ctime)) + figure(SlidesWin) + if OrthoViews == 0 + hold on + ax = subplot(c,r,iplot); + axis off, axis tight + % copyobj(Lights,ax); + else + set(previous,'Tag','') + set(SlidesWin,'Tag','tessellation_window'); + + end + dataplot_cb tesselation_select_done + axis equal, axis tight + if OrthoViews == 1 + dataplot_cb OrthoViews + set(SlidesWin,'Name',[num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4), ' ms']) + else + set(ax,'view',VIEW) + end + + figure(SlidesWin) + h = title(num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4)); + set(h,'fontweight','normal','color',frontcolor,'Fontname','helvetica','Fontsize',8,'FontUnits','Point') + %set(h,'Fontunits','normal') + + if OrthoViews == 1 & get(findobj(mapping_win,'Tag','SaveFigures'),'Value') % OrthoVoews are requested : Save each slide in a separate window + if ctime == samples(1) + ResFiles = get(hpprevious.ResultFiles,'String'); + ResFile = ResFiles{get(hpprevious.ResultFiles,'Value')}; + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + ResFile = fullfile(Users.STUDIES,path,ResFile); + [path,ResFile,ext] = fileparts(ResFile); + end + + time = num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4); + + ImageFile = fullfile(path,[ResFile,'_OrthoViews_',time,'.jpg']); + saveas(SlidesWin,ImageFile,'t') + + end + + end + + end + end + map_sph.handle = map_sph; + map_sph.x = x; + map_sph.y = y; + map_sph.xs = xs; + map_sph.ys = ys; + set(map_slides_win,'Userdata',map_sph) + + if OrthoViews == 0 & get(findobj(mapping_win,'Tag','SaveFigures'),'Value') % Regular single slide window - no orthoview + ResFiles = get(hpprevious.ResultFiles,'String'); + ResFile = ResFiles{get(hpprevious.ResultFiles,'Value')}; + [path,file,ext] = fileparts(Users.CurrentData.StudyFile); + ResFile = fullfile(Users.STUDIES,path,ResFile); + [path,ResFile,ext] = fileparts(ResFile); + + time = [num2str(((samples(1)-1)*srate + Visu.Data.Time(1))*1000,4),'_', num2str(((samples(end)-1)*srate + Visu.Data.Time(1))*1000,4)]; + + ImageFile = fullfile(path,[ResFile,'_Slides_',time,'.jpg']); + saveas(SlidesWin,ImageFile,'jpg') + + end + + if get(findobj(mapping_win,'Tag','SaveFigures'),'Value') + ImageFile = fullfile(path,[ResFile,'_Data_Slides_',time,'.jpg']); + saveas(map_slides_win,ImageFile,'jpg') + end + + case 3 % Movie + sstart = str2num(get(handles.start,'String'))/1000; + if sstart < Visu.Data.Time(1) + sstart = Visu.Data.Time(1); + end + + sstep = str2num(get(handles.step,'String'))/1000; + + sstop = str2num(get(handles.stop,'String'))/1000; + if sstop > Visu.Data.Time(end) + sstop = Visu.Data.Time(end); + end + + samples = round(([sstart,sstop]-Visu.Data.Time(1))/srate)+1; + sstep = round(sstep/srate); + samples = samples(1):sstep:samples(2); + nsamples = length(samples); + if nsamples > 40 % Warning, too many slides may take a while to create. + button = questdlg({'You have requested ',int2str(nsamples),' slide(s)','Do you still want to proceed ?'},'','Yes','No','Yes'); + if strcmp(button,'No') + return + end + end + + map_movie_win = findobj(0,'Tag',['map_movie',int2str(current(kur)),'_',get(handles.start,'String'),'_',get(handles.step,'String'),'_',get(handles.stop,'String')]); + if isempty(map_movie_win) + map_single = open('map_single.fig'); % Create a new window + set(map_single,'Tag',['map_movie',int2str(current(kur)),'_',get(handles.start,'String'),'_',get(handles.step,'String'),'_',get(handles.stop,'String')],... + 'color','w') + map_movie_win = findobj(0,'Tag',['map_movie',int2str(current(kur)),'_',get(handles.start,'String'),'_',get(handles.step,'String'),'_',get(handles.stop,'String')]); + else + figure(map_movie_win) + end + + switch head_shape + case 1 % Sphere + iplot = 0; + + [moviefile, moviepath] = uiputfile('*.avi', 'Save Movie File as...'); + if moviefile == 0, return, end + cd(moviepath) + + mov = avifile(moviefile,'FPS',2,'QUALITY',50); + moviefiletopo = moviefile; + [path,file,ext] = fileparts(moviefiletopo); + moviefiletopo = [file,'_topo.avi']; + + movtopo = avifile(moviefiletopo,'FPS',2,'QUALITY',50); + + for ctime = samples + iplot = iplot+1; + + data = Visu.Data.F(goodchannels{kur},ctime)+eps ; + if (current_visu == 2) & (current(kur) == 1) %MEG with bad channels and visualization of the gradient amplitude + if ctime == samples(1) + channels = [1:length(Visu.ChannelID{current(kur)})]; + odd_channels = channels(find(rem(channels,2) == 1)); + if ~isempty(badchannels{kur}) + odd = badchannels{kur}(find(rem(badchannels{kur},2) == 1)); + even = setdiff(badchannels{kur},odd); + odd = unique([odd',intersect(odd_channels ,(even - 1))]); + else + odd = []; + even = []; + end + good_odd_channels = setdiff(odd_channels,odd); + [c,ia,ib] = intersect(goodchannels{kur},good_odd_channels-goodchannels{kur}(1)+1); + chanloc{kur} = chanloc{kur}(:,ia); + end + grad_meg = []; + j = 0; + for i = (good_odd_channels) + j = j+1; + grad_meg(j) = norm([data(i),data(i+1)]); + end + data = grad_meg; + elseif current_visu == 3 & current(kur) == 1 + data = Visu.MNEdata(:,ctime); + end + + + if ctime == samples(1) + [x,y,z,xs,ys,sensor,map_sph] = carto_sph(chanloc{kur}',data,[0 0 0]); + set(findobj(get(gca,'Children'),'Type','line'),'Visible','off') % Erase the sensor positions + axorig = get(map_sph,'Parent'); + set(gcf,'CurrentAxes',axorig) + %M = moviein(nsamples,map_movie_win); + %h = title(num2str(((ctime-1)*srate+Visu.Data.Time(1))*1000,4)); + h = text(0.05,0.05,0,num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4),'units','normalized'); + set(h,'fontweight','normal','color',frontcolor,'Fontname','helvetica','Fontsize',8,'FontUnits','Point') + + set(h,'fontweight','normal','color',frontcolor,'Fontname','helvetica','Fontsize',8,'FontUnits','Point') + axis manual % Freeze Axes limits + set(gca,'nextplot','replacechildren'); + if RELATIVE == 1 + if current_visu == 3 + datacomplete = Visu.MNEdata; + else + datacomplete = Visu.Data.F(goodchannels{kur},:); + end + Max = max(abs(datacomplete(:))); + caxis([-Max,Max]) + else + caxis([-max(abs(data)),max(abs(data))]) + end + if findstr(lower(Visu.Data.Device),'ctf') + view(-90,90) % Noise pointing upwards + end + axis tight + + else + cdata_map = griddata(x,y,data,xs,ys,'invdist'); + set(h,'String',num2str(((ctime-1)*srate+Visu.Data.Time(1))*1000,4)); + set(map_sph,'CData',cdata_map) + end + % axis equal, axis vis3d + Ftopo = getframe(get(map_sph,'Parent')); + movtopo = addframe(movtopo,Ftopo); + + %[M(:,iplot)] = getframe(map_movie_win); + + % SurfaceViewer update + TessSelectWin = findobj(0,'Tag','tesselation_select'); + if ~isempty(TessSelectWin) % Check if Surface Viewer is open + handles = guihandles(TessSelectWin ); + ScalpMaps = get(handles.ScalpMaps,'Value'); + ColorSensors = get(handles.ColorSensors,'Value'); + CorticalMap = get(handles.CorticalMap,'Value'); + previous = findobj(0,'tag','tessellation_window'); + + if isempty(previous) + previous = open('tessellation_window.fig'); + end + figure(previous) + mapping_win = findobj(0,'Tag','mapping'); + if ~isempty(mapping_win) + slider_time = findobj(mapping_win,'Tag','slider_time'); + current_time= findobj(mapping_win,'Tag','current_time'); + end + + set(slider_time,'Value',1000*Visu.Data.Time(ctime)) + set(current_time,'String',1000*Visu.Data.Time(ctime)) + + dataplot_cb tesselation_select_done + + figure(previous) + if ctime == samples(1) + hxt = text(0.05,0.05,0,num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4),'units','normalized'); + set(hxt,'fontweight','normal','color',frontcolor,'Fontname','helvetica','Fontsize',8,'FontUnits','Point') + + set(gca,'nextplot','replacechildren'); + + else +% set(hxt,'String',' '), drawnow + set(hxt,'String',num2str(((ctime-1)*srate + Visu.Data.Time(1))*1000,4)) + end + + drawnow + + F = getframe(gca); + mov = addframe(mov,F); + + end + + end + cmap = colormap; % Retrieves Current Colormap + + end + + mov = close(mov); + movtopo = close(movtopo); + + % Save Movie file +% [moviefile, moviepath] = uiputfile('*.mpg', 'Save Movie File as...'); +% if moviefile == 0, return, end +% cd(moviepath) +% %save(moviefile,'cmap','M') Matlab format +% disp('Saving Movie File...') +% mpgwrite(M,cmap,moviefile) + msgbox('Movie Save Completed') + disp('Saving Movie File... -> Done') + + map_sph.handle = map_sph; + map_sph.x = x; + map_sph.y = y; + map_sph.xs = xs; + map_sph.ys = ys; + set(map_movie_win,'Userdata',map_sph) + end + end + + set(findobj(0,'Tag','rotate'),'Userdata',get(map_sph.handle,'Parent')) % Axes handle for possible future rotattion using 'rotate' + + + %---------------------------------------------------------------------------- + +case 'mapping_rotate' % Make the last 3D view rotate + ax = get(gcbo,'Userdata'); + if isempty(ax), return, end + axes(ax) + switch get(gcbo,'Value') + case 1 + rotate3d on + otherwise + rotate3d off + end + + %---------------------------------------------------------------------------- + +case 'mapping_display_type' % Checkboxes Mutually incompatible + DATAPLOT = findobj(0,'Tag','mapping'); + MEG = findobj(DATAPLOT,'Tag','single'); + EEG = findobj(DATAPLOT,'Tag','slides'); + OTHER = findobj(DATAPLOT,'Tag','movie'); + mutincomp([MEG,EEG,OTHER]) + h = findobj([MEG,EEG,OTHER],'Value',1); + if length(h)>1 + set(h(2),'Value',0) % Just one modality at a time please ! + end + + %---------------------------------------------------------------------------- + +case 'quit' + close gcbf + + %---------------------------------------------------------------------------- +case 'see_sensors' % Visualize sensor locations using 3D spheres + + TessWin = findobj(0,'Tag','tesselation_select'); + hTessWin = guihandles(TessWin); + + % mutincomp([hTessWin.Sensors3D,hTessWin.SensorsMarkers]); + previous = openfig('tessellation_window.fig','reuse'); + + if get(hTessWin.Sensors3D,'Value') == 0 + if get(hTessWin.SensorsMarkers,'Value') == 1 + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + dataplot_cb see_sensors_markers + return + else + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + return + end + end + + Visu = get(DATAPLOT,'Userdata'); + previous = openfig('tessellation_window.fig','reuse'); + + + SIZE = sqrt(str2num(get(hTessWin.SensorSize,'String'))/10); % get sensor size + if isempty(SIZE), SIZE = 1; end + + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + + % Channels Locations: + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + goodchannels = Visu.ChannelID{current}; + badchannels = []; + end + j = 0; + chanloc = [Visu.Channel(goodchannels).Loc]; + chanloc = chanloc(:,1:2:end); + for chan = goodchannels %Visu.ChannelID{current} + j = j+1; + figure(previous) + hold on + if j == 1 + maxx = max(abs(get(gca,'Xlim')/50))*SIZE; + [X,Y,Z] = sphere; + end + sph(j) = surf(maxx*X+chanloc(1,j),maxx*Y+chanloc(2,j),maxx*Z+chanloc(3,j),'Visible','off'); + end + + set(sph,'Userdata',SIZE,'Visible','on','facelighting','Gouraud','edgelighting','Gouraud','Tag','SENSORS','facecolor',[.1 .1 .9],'Edgecolor','none') + axis equal, axis vis3d + varargout{1} = sph; + + %-------------------------------------------------------------------------------------------------------------------- +case 'see_sensors_markers' % Visualize sensor locations using regular markers + + TessWin = findobj(0,'Tag','tesselation_select'); + hTessWin = guihandles(TessWin); + + % mutincomp([hTessWin.Sensors3D,hTessWin.SensorsMarkers]); + previous = openfig('tessellation_window.fig','reuse'); + + if get(hTessWin.SensorsMarkers,'Value') == 0 + if get(hTessWin.Sensors3D,'Value') == 1 + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + dataplot_cb see_sensors + return + else + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + return + end + end + + Visu = get(DATAPLOT,'Userdata'); + + SIZE = sqrt(str2num(get(hTessWin.SensorSize,'String'))); % get sensor size + if isempty(SIZE), SIZE = 1; end + + sph= findobj(previous,'Tag','SENSORS'); + delete(sph); set(previous,'Userdata',[]) % Redraw all sensors - to avoid mess with handles when resizing and coloring the sphere + + % Channels Locations: + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + goodchannels = Visu.ChannelID{current}; + badchannels = []; + end + j = 0; + chanloc = [Visu.Channel(goodchannels).Loc]; + chanloc = chanloc(:,1:2:end); + hold on + sph = scatter3(chanloc(1,:),chanloc(2,:),chanloc(3,:),'filled'); + + set(sph,'Userdata',SIZE,'Visible','on','Tag','SENSORS',... + 'Markerfacecolor',[.1 .1 .9],'Markeredgecolor','k', 'MarkerSize',SIZE); + axis equal, axis vis3d + varargout{1} = sph; + + %-------------------------------------------------------------------------------------------------------------------- + + +case 'DataOnSensors' % Sensors are color-coded according to the data at each location + + dataplot_cb mapping_create + Visu = get(DATAPLOT,'Userdata'); + previous = openfig('tessellation_window.fig','reuse'); + + + % Handles to the spherical representation of the sensors + sph = findobj(previous,'Tag','SENSORS'); + if isempty(sph) | isempty(get(previous,'userdata')) + + if ~isempty(sph) + if strcmp(get(sph(1),'type'),'surface') + sph = dataplot_cb('see_sensors'); + else + sph = dataplot_cb('see_sensors_markers'); + end + else + TessWin = findobj(0,'Tag','tesselation_select'); + hTessWin = guihandles(TessWin); + if get(hTessWin.Sensors3D,'Value') + sph = dataplot_cb('see_sensors'); + else + sph = dataplot_cb('see_sensors_markers'); + end + end + set(previous,'UserData',sph); + else + sph = get(previous,'Userdata'); % Need this and line above to keep sensor ordering correct - sph = findobj creates an arbitrary ordering otherwise + end + + % Bring the time slider - call the mapping window if available + MAPPING = openfig('mapping.fig','reuse'); + hMAPPING = guihandles(MAPPING); + + % Good/Bad Channels + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)); + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)); + else + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1)); + badchannels = []; + end + + % Sampling rate + srate = abs(Visu.Data.Time(1)-Visu.Data.Time(2) ); % Assuming time is in sec. + ctime = round((get(hMAPPING.slider_time,'Value')/1000-Visu.Data.Time(1))/srate)+1; + axx = get(sph(1),'Parent'); + + data = Visu.Data.F(goodchannels,:); clear Visu + %set(axx,'Clim',[-max(abs(data(:))) max(abs(data(:)))]); + caxis(axx,[-max(abs(data(:))) max(abs(data(:)))]); + data = data(:,ctime); + + C = [flipud(fliplr(hot(128)));hot(128)]; + colormap(axx,C); + + % Manipulation to get the color properly for each sensor sphere + + set(sph,'visible','off') + TessWin = findobj(0,'Tag','tesselation_select'); + hTessWin = guihandles(TessWin); + + if get(hTessWin.Sensors3D,'Value') + zdata = get(sph(1),'Zdata'); + for k=1:length(sph) + cdata = data(k)*ones(size(get(sph(k),'zdata'))); + set(sph(k),'CData',cdata,'facecolor','flat','CDataMapping','scaled'); + end + else + for k=1:length(sph) + set(sph(k),'Markerfacecolor',C( max([round(size(C,1)*(data(k)-min(caxis(axx)))/(max(caxis(axx))-min(caxis(axx)))),1]),:)); + end + + end + + set(sph,'visible','on') + + %-------------------------------------------------------------------------------------------------------------------- +case 'DataOnScalp' % Scalp topography + + dataplot_cb mapping_create + + TessSelect = findobj(0,'Tag','tesselation_select'); + hSelect = guihandles(TessSelect); + ActiveTess = get(hSelect.removed,'String'); % Find the active scalp surface + % Check if the CORTEX keyword is present + for k = 1:length(ActiveTess) + flag(k) = ~isempty(findstr(lower(ActiveTess{k}),'head')); %KND:scalp->head + end + iScalp = find(flag); + iScalp = iScalp(1); + if isempty(iScalp) + h = msgbox('Please select a scalp envelope from the tessellated surfaces available.'); + return + end + TessWin = openfig('tessellation_window.fig','reuse'); + + Visu = get(DATAPLOT,'Userdata'); + if ~isempty(find(Visu.Data.ChannelFlag == -1)) + goodchannels = setdiff(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; % Discard bad channels + badchannels = intersect(Visu.ChannelID{current},find(Visu.Data.ChannelFlag == -1));% - min(Visu.ChannelID{current})+1; + else + goodchannels = Visu.ChannelID{current}; + badchannels = []; + end + + Scalp = findobj(TessWin,'Type','patch','Tag',ActiveTess{iScalp}); % Need to find a better way to identify scalp when multiple surfaces are present in tessellation_win + if isempty(Scalp), tesselation_select_done, return, end + + if isempty(get(Scalp,'Userdata')) + figure(TessWin) + C = [flipud(fliplr(grayish(hot(128),.3)));grayish(hot(128),.3)]; + colormap(C) + + scalp.vertices = get(Scalp,'vertices'); + % Channels Locations + j = 0; + for chan = goodchannels + j = j+1; + %Projection of sensors on surface + celec = ones(size(scalp.vertices,1),1)*Visu.Channel(chan).Loc(:,1)'; + dist = norlig(scalp.vertices-celec); + [minn(j) imin(j)] = min(dist); + end + scalp.chanloc = [scalp.vertices(imin,1),scalp.vertices(imin,2),scalp.vertices(imin,3)]; + + % Sampling rate + scalp.srate = abs((Visu.Data.Time(2)-Visu.Data.Time(1))); + data = Visu.Data.F(goodchannels,:); + axx= get(Scalp,'Parent'); + set(axx,'Clim',[-max(abs(data(:))) max(abs(data(:)))]); + set(Scalp,'Userdata',scalp) + else + scalp = get(Scalp,'Userdata'); + end + + + % Get the data from the mapping window + MAPPING = openfig('mapping.fig','reuse'); + hMAPPING = guihandles(MAPPING); + ctime = round((get(hMAPPING.slider_time,'Value')/1000-Visu.Data.Time(1))/scalp.srate)+1; + vertxcolor = interp_mail(scalp.vertices,scalp.chanloc,Visu.Data.F(goodchannels,ctime)); + set(Scalp,'FaceVertexCData',vertxcolor,'facecolor','interp'); + + %-------------------------------------------------------------------------------------------------------------------- + +case 'CorticalMap' % See cortical current maps interpolated on the proper cortical surface + + TessSelect = findobj(0,'Tag','tesselation_select'); + hSelect = guihandles(TessSelect); + ActiveTess = get(hSelect.removed,'String'); % Find the active scalp surface + iCortex = get(hSelect.removed,'Value'); % Find the active scalp surface + + if isempty(iCortex) + h = msgbox('Please select a cortex surface from the tessellations available.'); + return + end + TessWin = findobj(0,'Tag','tessellation_window'); + SlidesWin = findobj(0,'Tag','subplot_tess_window'); + if ~isempty(SlidesWin) + TessWin = SlidesWin; % Subplot or movie window + end + + if isempty(TessWin) + TessWin = openfig('tessellation_window.fig'); + dataplot_cb('loaddata',Users.CurrentData.StudyFile,Users.CurrentData.DataFile); % Refresh by reloading data + end + + % Check if loaded Results match this surface (ie number of sources = number of vertices of selected cortical surface) + Results = get(hSelect.ResultFiles,'Userdata'); + nSources = size(Results.ImageGridAmp,1); + + if nargin == 1 & get(hSelect.OrthoViews,'Value') == 0 + if iscell(ActiveTess) + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess{iCortex}); %CHEAT - need to be improved ? + else + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess); %CHEAT - need to be improved ? + end + elseif nargin == 1 & get(hSelect.OrthoViews,'Value') == 1 % Orthogonal views are requested + Cortex = findobj(get(TessWin,'CurrentAxes'),'Type','patch','Tag',ActiveTess,'Visible','on'); %CHEAT - need to be improved ? + Cortex = Cortex(1); + else + Cortex = varargin{1}(1); + end + + %set(Cortex,'Visible','off') + if ~isfield(get(Cortex,'Userdata'),'srate') + Visu = get(DATAPLOT,'Userdata'); + figure(TessWin) + + cortex = get(Cortex,'Userdata'); + + cortex.vertices = get(Cortex,'vertices'); + % Sampling rate + cortex.srate = abs(Visu.Data.Time(2)-Visu.Data.Time(1)); + data = Results.ImageGridAmp; + axx= get(Cortex,'Parent'); + set(axx,'Clim',[-max(abs(data(:))) max(abs(data(:)))]); + set(Cortex,'Userdata',cortex) + + % Result time window has priority over the original time window for the data - replace + Visu.Data.Time = Results.ImageGridTime; % Need to do better than that - CHEAT + try + Visu.Data.F = Visu.Data.F(:,Results.Time(1):Results.Time(end)); % Should work only the first time the result time series are called - otherwise do nothing + catch + Visu.Data.F = Visu.Data.F; % Do nothing + end + + set(DATAPLOT,'Userdata',Visu); + + M = max(abs(Results.ImageGridAmp(:))); + set(hSelect.Colorbar,'Userdata',M); + + else + cortex = get(Cortex,'Userdata'); + end + + dataplot_cb mapping_create + + % Get the data from the mapping window + MAPPING = findobj(0,'Tag','mapping'); + hMAPPING = guihandles(MAPPING); + + if iscell(cortex) + ctime = round((get(hMAPPING.slider_time,'Value')/1000- Results.ImageGridTime(1))/cortex{1}.srate)+1; + else + ctime = round((get(hMAPPING.slider_time,'Value')/1000- Results.ImageGridTime(1))/cortex.srate)+1; + end + if ctime < 0, ctime =1; end + + if get(hSelect.AbsoluteCurrent,'Value') + set(Cortex,'FaceVertexCData',abs(Results.ImageGridAmp(:,ctime))); + else + set(Cortex,'FaceVertexCData',Results.ImageGridAmp(:,ctime)); + end + + figure(TessWin) + hTessWin = guihandles(TessSelect); + if get(hTessWin.Normalize,'Value') + TessWin = findobj(0,'Tag','tessellation_window'); + axx = findobj(TessWin,'tag','MainAxes'); + set(axx,'ClimMode','auto') + M = max(abs(Results.ImageGridAmp(:,ctime))); + set(hSelect.Normalize,'Userdata',M) + + SlidesWin = findobj(0,'Tag','subplot_tess_window'); + if ~isempty(SlidesWin) + TessWin = SlidesWin; % Subplot or movie window + axx = findobj(TessWin,'type','axes'); + set(axx,'ClimMode','auto') + end + + else + if get(hTessWin.FreezeColormap,'Value') + data = get(Cortex,'FaceVertexCData'); + FreezeTime = get(hTessWin.FreezeColormap,'Userdata'); + M = max(abs(Results.ImageGridAmp(:,FreezeTime))); + else + M = max(abs(Results.ImageGridAmp(:))); + end + + if get(hSelect.AbsoluteCurrent,'Value') + set(findobj(TessWin,'type','axes'),'ClimMode','manual','Clim',[0 M]) + else + set(findobj(TessWin,'type','axes'),'ClimMode','manual','Clim',[-M M]) + end + end + + if isempty(get(hSelect.ColorMAP,'Userdata')) + %if ~isfield(cortex,'CDepth') & ~get(hSelect.MapCurvature,'Value')% No curvature mapping + if ~get(hSelect.MapCurvature,'Value')% No curvature mapping + if ~get(hSelect.AbsoluteCurrent,'Value') + C = [flipud(fliplr(grayish(hot(128),.3)));grayish(hot(128),.3)]; + else + %C = [(grayish(hot(128),.3))]; + load bst_cactivCmap + C = map; + end + else + [FVC,C]=catci(get(Cortex,'FaceVertexCData'),cortex.CDepth,M); + set(Cortex,'FaceVertexCData',FVC); + end + + else % Truncated Colormap + if ~isfield(cortex,'CDepth') % No curvature mapping + C = get(hSelect.ColorMAP,'Userdata'); % Truncated Colormap + if get(hSelect.ZScoreThresholdApply,'Value') & get(hSelect.ZScore,'Value') + cThres = str2num(get(hSelect.ZScoreThreshold,'String')); + else + cThres = str2num(get(hTessWin.TruncateFactor,'String')); + end + FVC = get(Cortex,'FaceVertexCData'); + if get(hSelect.OrthoViews,'Value') == 0 + set(Cortex,'FaceVertexCData',FVC); + Cortex = findobj(TessWin,'Type','patch','Tag',ActiveTess,'Visible','on'); %CHEAT - need to be improved ? + FVC(FVC 0 + ColorMap(1:round(ScaleFactor*end/100),:) = ... + repmat(min([.3,sum(ColorMap(round(ScaleFactor*end/100),:))])*[1 1 1],length(1:round(ScaleFactor*size(ColorMapOld,1)/100)),1); + else + ColorMap = ColorMapOld; + end + + set(TessWin,'Colormap',ColorMap); + set(hTessSelect.ColorMAP,'Userdata',ColorMap) + + dataplot_cb CorticalMap + %-------------------------------------------------------------------------------------------------------------------- + + +case 'Colorbar' % Add colorbar to the Surface Viewer window + handles = guihandles(gcbf); + ViewColorbar = get(handles.Colorbar,'Value'); % Add or remove colorbar + TessWin = findobj(0,'Tag','tessellation_window'); + + if isempty(TessWin), return, end + if isempty(get(handles.Colorbar,'Userdata')) | (ViewColorbar == 1) + figure(TessWin); + Colorbar = colorbar('horiz'); + set(handles.Colorbar,'Userdata',Colorbar); + set(Colorbar,'Xcolor',textcolor,'Ycolor',textcolor) + elseif ~isempty(get(handles.Colorbar,'Userdata')) + delete(get(handles.Colorbar,'Userdata')); + set(handles.Colorbar,'Userdata',[]) + end + figure(TessWin) + rotate3d on + hTessSelect = guihandles(findobj(0,'Tag','tesselation_select')); + if get(hTessSelect.Normalize,'Value') & ViewColorbar == 1% Normalized colorbar + M=get(hTessSelect.Normalize,'Userdata'); + set(get(handles.Colorbar,'Userdata'),'XTickLabel',num2str(linspace(0,M,6)',1)) + end + %-------------------------------------------------------------------------------------------------------------------- +case 'Colorbar_mapping' % Add colorbar to the Surface Viewer window + handles = guihandles(gcbf); + ViewColorbar = get(handles.Colorbar,'Value'); % Add or remove colorbar + for k = 1:length(current) + TessWin = findobj(0,'Tag',['map_single',int2str(current(k))]); + + if isempty(TessWin), return, end + if (ViewColorbar == 1) + figure(TessWin); + axes(get(TessWin,'CurrentAxes')); + Colorbar{k} = colorbar('horiz'); + set(handles.Colorbar,'Userdata',Colorbar); + set(Colorbar{k},'Xcolor',textcolor,'Ycolor',textcolor) + elseif ~isempty(get(handles.Colorbar,'Userdata')) + Colorbar = get(handles.Colorbar,'Userdata'); + if isempty(Colorbar) + return + end + delete([Colorbar{:}]); + set(handles.Colorbar,'Userdata',[]) + end + end + + %-------------------------------------------------------------------------------------------------------------------- +case 'QuitTessSelect' % Bye + delete(findobj(0,'tag','tesselation_select')); + delete(findobj(0,'tag','tessellation_window')); + + +end % Switch action + diff --git a/epilepsie/mergedata.m b/epilepsie/mergedata.m new file mode 100644 index 0000000..7e925a3 --- /dev/null +++ b/epilepsie/mergedata.m @@ -0,0 +1,41 @@ +function mergedata() + +for istud=1:3 + studyname=sprintf('debcrise%d-long',istud) + local=sprintf('/tmp/epil/debcrise%d-long.ds/',istud) + switch(istud) + case 1 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART1/debcrise1-long.ds/' + Time=84+(cumsum(ones(1,12500))-1)*8e-4; + case 2 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART2/debcrise2-long.ds/' + Time=33+(cumsum(ones(1,12500))-1)*8e-4; + case 3 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART2/debcrise3-long.ds/' + Time=106+(cumsum(ones(1,12500))-1)*8e-4; + end + F=[]; + ChannelFlag=[]; + + if 0 + for i=1:10 + clear d + f=fullfile(distal, sprintf('%s_data_trial_%d.mat',studyname, i)); + disp(sprintf('Loading... %s',f)); + d=load(f); + F=[F d.F(:,1:end-1)]; + ChannelFlag=d.ChannelFlag; + Time=[Time, d.Time(1:end-1)]; + disp(sprintf('Saving... %s',studyname)); + save(sprintf('%s%s_data_trial_0.mat', local,studyname),'F', 'ChannelFlag', 'Time' ) + end + F=[F d.F(:,end)]; + % Time=[Time, d.Time(end)]; + save(sprintf('%s%s_data_trial_0.mat', local,studyname),'F', 'ChannelFlag', 'Time' ) + copyfile(sprintf('%ssensor_result.mat', distal),sprintf('%s', local)) + copyfile(sprintf('%s%s_brainstormstudy.mat', distal,studyname),sprintf('%s', local)) + copyfile(sprintf('%s%s_channel.mat', distal,studyname),sprintf('%s', local)) + end + save(sprintf('%s%s_data_trial_0.mat', local,studyname),'-APPEND', 'Time' ) + end +return diff --git a/epilepsie/mergeresults.m b/epilepsie/mergeresults.m new file mode 100644 index 0000000..dc0567d --- /dev/null +++ b/epilepsie/mergeresults.m @@ -0,0 +1,47 @@ +function mergeresults() +% Fusionne les donnees epilepsie du sujet bern en 1 seul gros fichier + for istud=1:3 + ImageGridAmp=single(zeros(12501,10569)); + studyname=sprintf('debcrise%d-long',istud) + local=sprintf('/tmp/epil/debcrise%d-long.ds/',istud) + switch(istud) + case 1 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART1/debcrise1-long.ds/' + ImageGridTime=84+(cumsum(ones(1,12500))-1)*8e-4; + case 2 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART2/debcrise2-long.ds/' + ImageGridTime=33+(cumsum(ones(1,12500))-1)*8e-4; + case 3 + distal='/epilepsie/data/EPILEPSIE/03Mar18/PART2/debcrise3-long.ds/' + ImageGridTime=106+(cumsum(ones(1,12500))-1)*8e-4; + end + %f=dir(sprintf('*_data_trial_1.mat')); + %studyname=f(1).name(1:findstr('_data_trial_',f(1).name)-1); + %data=load(f(1).name, 'Time'); + if 1 + for i=1:10 + clear d + pack; + T=((i-1)*1250+1):i*1250; + f=dir(sprintf('%s*_data_trial_%d_MNE_*.mat',distal,i)); + disp(sprintf('Loading... %s',f(1).name)); + d=load([distal f(1).name], 'ImageGridAmp'); + ImageGridAmp(:,T)=single(d.ImageGridAmp(:,1:end-1)); + disp(sprintf('Saving... %s',studyname)); + % save(sprintf('%s%s_data_trial_0_MNE_MEGresults.mat', local,studyname),'ImageGridAmp') + end + ImageGridAmp(:,12501)=single(d.ImageGridAmp(:,end)); + %ImageGridTime=getfield(load(sprintf('%s%s_data_trial_0.mat',local, studyname), 'Time'),'Time'); + save(sprintf('%s%s_data_trial_0_MNE_MEGresults.mat', local,studyname),'ImageGridAmp','ImageGridTime') + + end + + SourceLoc=[]; + Comment=studyname; + save(sprintf('%s%s_data_trial_0_MNE_MEGresults.mat', local, ... + studyname),'-APPEND','SourceLoc', 'Comment', 'ImageGridTime') + + end + + return + \ No newline at end of file diff --git a/epilepsie/scriptStudySubject.m b/epilepsie/scriptStudySubject.m new file mode 100644 index 0000000..b81be0a --- /dev/null +++ b/epilepsie/scriptStudySubject.m @@ -0,0 +1,50 @@ + + +load /tmp/epil/test/debcrise1-long_data_trial_1_MNE_MEGresults_1747.mat + +StudySubject.Subject = 'bern_brainstormsubject.mat' +StudySubject.SubjectImage = 'bern_subjectimage.mat' +StudySubject.SubjectTess = 'tri/bern_Lwhite-CTF_tess.mat' +StudySubject.SubjectTriConn = [] +StudySubject.SubjectVertConn = 'bern_Lwhite-CTF_tess_vertconn.mat' +StudySubject.Results = [] + + +for STUDY=1:3 + + +if STUDY==1 +StudySubject.Study = 'deb1/debcrise1-long_brainstormstudy.mat' +StudySubject.Channel = 'deb1/debcrise1-long_channel.mat' +StudySubject.HeadModel = '' +StudySubject.Data = {'deb1/debcrise1-long_data_trial_0.mat'} +GUI.DataName='deb1/debcrise1-long_data_trial_0.mat' + +r='deb1/debcrise1-long_data_trial_0_MNE_MEGresults.mat' +end + +if STUDY==2 +StudySubject.Study = 'deb2/debcrise2-long_brainstormstudy.mat' +StudySubject.Channel = 'deb2/debcrise2-long_channel.mat' +StudySubject.HeadModel = '' +StudySubject.Data = {'deb2/debcrise2-long_data_trial_0.mat'} +GUI.DataName='deb2/debcrise2-long_data_trial_0.mat' + +r='deb2/debcrise2-long_data_trial_0_MNE_MEGresults.mat' +end + +if STUDY==3 +StudySubject.Study = 'deb3/debcrise3-long_brainstormstudy.mat' +StudySubject.Channel = 'deb3/debcrise3-long_channel.mat' +StudySubject.HeadModel = '' +StudySubject.Data = {'deb3/debcrise3-long_data_trial_0.mat'} +GUI.DataName='deb3/debcrise3-long_data_trial_0.mat' + +r='deb3/debcrise3-long_data_trial_0_MNE_MEGresults.mat' +end + +disp(sprintf('Saving... %s', r)) + + % save(r, '-append', 'StudySubject') + save(r, '-append', 'Comment', 'GUI') +end \ No newline at end of file diff --git a/epilepsie/splitdata.m b/epilepsie/splitdata.m new file mode 100644 index 0000000..e9a44c3 --- /dev/null +++ b/epilepsie/splitdata.m @@ -0,0 +1,20 @@ +function []=splitdata() +load('debcrise1-f_data_trial_0.mat') +G=F; +T=Time; + +for i=1:10 + if i<10 + t=1250*(i-1)+1:1250*(i); + else + t=1250*(i-1)+1:1250*(i)+1; + end + + Time=T(t)'; + F=G(:,t); + size(Time) + size(F) + save(sprintf('debcrise1-f_data_trial_%d.mat', i), 'ChannelFlag', 'Comment', 'Device', 'F', 'NoiseCov', 'Projector','SourceCov', 'System', 'Time') +end + + diff --git a/epilepsie/view_cortex.m b/epilepsie/view_cortex.m new file mode 100644 index 0000000..3b72b40 --- /dev/null +++ b/epilepsie/view_cortex.m @@ -0,0 +1,54 @@ +function [h,g]=view(faces,vertices, data) +% function [h,g]=view(faces,vertices, data) + +if nargin==1 + data=faces; + global faces + global vertices +end + + +if(size(vertices,2) > 3), % assume transposed + vertices = vertices'; % if the assumption is wrong, will crash below anyway +end + +% if(~exist('cdata','var')), +% cdata = rownorm(vertices); +% end + +% h = windfind(figname); +% figure(h) +% windclf +% h=figure +cla +h = patch('faces',faces,'vertices',vertices,... + 'facevertexcdata',data(:),'facecolor','interp','edgecolor','none'); + + +hl(1) = camlight(-20,30); +hl(2) = camlight(20,30); +hl(3) = camlight(-20,-30); +for i = 1:length(hl), + set(hl(i),'color',[.8 1 1]/length(hl)/1.2); % mute the intensity of the lights +end +g=light; +set(g, 'position', [0 -1 0]) +g=light; +set(g, 'position', [0 1 0]) + +% h=view_surface('',faces, vertices, data); + + +view(2) +axis image +axis off +rotate3d +view([0 0]) + + +lighting phong +material dull +colormap(hot(256)) +setmycolormap(50) + +set(h, 'Userdata', {'Cortex'}) diff --git a/epilepsie/view_minnorm_cb.m b/epilepsie/view_minnorm_cb.m new file mode 100644 index 0000000..47b1012 --- /dev/null +++ b/epilepsie/view_minnorm_cb.m @@ -0,0 +1,451 @@ +function view_minnorm_cb(action); +% VIEW_MINNORM_CB Callback for viewing minimum norm solutions +% function view_minnorm_cb(action); +% Call with no arguments to build gui. + +% John C. Mosher, Ph.D., See Copyright.m file for information. +% $Date: 4/19/01 6:15a $ $Revision: 4 $ +% Additions: +% +% +% 04-03-01 +% Sylvain Baillet - CNRS-UPR640 +% Added orthogonal views button and callbacks +% + +if(~exist('action','var')), + action = 'build'; +end + +hf = gcbf; % who called me + +switch deblank(lower(action)) +case 'build' + open('view_minnorm_cb.fig'); + +case 'reset' + % Reset all of the buttons to initial values, refresh the studies list + % Objects: AxisStudy, AxisSignal, AxisNoise, AxisSVD + % EditMinTime, EditMaxTime, EditRank, EditCorr, EditReg + % SliderRank, SliderCorr, + % PopupSVD, PopupReg, PopupOrder, ExecuteRAP + + % Set the menu action + + hur = findobj(hf,'Tag','UimenuReset'); % handle of uimenu for reseting + hud = findobj(hf,'Tag','UimenuDataSets'); + hub = findobj(hf,'Tag','UimenuBSTStudy'); % the studies + delete(hur); + delete(hud); + delete(hub); + + find_brainstorm_files('studies',[],hf); % restablish the menu + hub = findobj(hf,'Tag','UimenuBSTStudy'); % the studies created by that call + % now create a menu to find the datasets for those studies + hud = uimenu('Label','DataSets','Tag','UimenuDataSets'); + % and the call to reset this gui + hur = uimenu('Label','Reset GUI','Tag','UimenuReset',... + 'Callback','view_minnorm_cb(''reset'')'); + + % So the studies menu has a list of StudySubjects to write to UserData + % now append to each study menu callback a datasets menu action + hub1 = get(hub,'children'); % what are all of the studies + % hub1r = findobj(hub1,'Label','Refresh Studies'); + % hub1(find(hub1==hub1r)) = []; % don't update the refresher child + + for i = 1:length(hub1), % each submenu of the study menu + cb = get(hub1(i),'Callback'); + % datamenu will make a menu of data sets for min norm + set(hub1(i),'Callback',[cb 'viewminnormdatamenu;']); + end + + %So the menus are rebuilt. Now for the other objects. Activate all of them + TAGS = {'AxisStudy', 'AxisSeries', 'AxisView'}; + + for i = 1:length(TAGS), + + axes(findobj(hf,'Tag',TAGS{i})); + cla reset + set(gca,'Tag',TAGS{i},'Units','Normalized'); % set tag back in + box on + + if i==3 + set(gca,'color',[.35 .35 .35]) + set(gca,'Xtick',[],'Ytick',[]) + end + + set(gca,'xcolor',[.7 .7 0],'ycolor',[.7 .7 0]); + axis on + grid off + + end + + hm = findobj(gcf,'Label','Toggle Face'); + delete(hm) + hm = findobj(gcf,'Label','Toggle Lighting'); + delete(hm) + + uimenu(gcf,'Label','Toggle Face','callback','toggleface(get(gcbo,''UserData''))','UserData',[]); + uimenu(gcf,'Label','Toggle Lighting','callback','togglelight(get(gcbo,''UserData''))','UserData',[]); + + + % end of reset + +case 'view data' + % user has clicked on some data in the data menu. + ht = findobj(0,'Tag','TASKBAR'); + UD = get(ht,'UserData'); % get the userdata + % interested in StudySubject information and DataName string + Results = load_brainstorm_file(UD.DataName); + + if(~isempty(findstr('_results',deblank(lower(Results.GUI.DataName))))), + % CHEAT + % The DataName has the string '_results' in it + % We are trying to view independent topographies as min norm data. Eventually this + % capability will be moved to a new routine. + OrgData= load(Results.GUI.DataName); % the original data + % now synthesize a Data structure from this + [ignorm,Anrm] = colnorm(OrgData.IndepTopo); + Data = struct('F',Anrm,'Channel',OrgData.Channel,... + 'Time',[1:size(OrgData.IndepTopo,2)],... % time is now simply an indexer + 'NoiseCov',OrgData.NoiseCov,'SourceCov',OrgData.SourceCov,'Projector',OrgData.Projector,... + 'Comment',sprintf('Synthesized Data Set from Results: %s',OrgData.Comment)); + GoodChannel = [1:size(Anrm,2)]; % all channels good in the IndepTopo + else + % CHEAT + % the GUI.DataName does not have the word "results" in it, so we are viewing legitimate + % minimum norm results. In the future, we might key in on the letters "mn" , for instance + % assume it is a data file + User = get_user_directory; + cd(User.STUDIES) + Data = load(Results.GUI.DataName,'F','Channel','Time','Projector','Comment'); + Channel = load(Results.StudySubject.Channel); + Channel = Channel.Channel; + GoodChannel = good_channel(Channel,Results.ChannelFlag,'MEG'); + + % CHEAT SILVIN + %GoodChannel = good_channel(Channel,Results.ChannelFlag,'EEG'); + %% CHEAT, show data and residual in a separate window for now + figure(windfind(sprintf('MinNorm Data and Residuals: %s',Results.GUI.DataName))) + windclf + plot([Data.F(GoodChannel,Results.Time) Results.Fsynth Data.F(GoodChannel,Results.Time)-Results.Fsynth]'); + title(sprintf('%s: Data, Synth, Resid',Results.GUI.DataName),'interpreter','none') + drawnow + + end + + ha = findobj(hf,'Tag','AxisStudy'); + axes(ha) + cla + line(1000*Data.Time(Results.Time),Data.F(GoodChannel,Results.Time)') + title(Data.Comment) + axis tight + grid on + + % now we can only handle a couple hundred lines + MAXLINE = 500; + MAXLINE = min(MAXLINE,size(Results.ImageGridAmp)); % in case there are fewer sources + AmpNrm = rownorm(Results.ImageGridAmp); + [ignore,iAmpNrm] = sort(AmpNrm); + iAmpNrm = iAmpNrm(end:-1:1); % biggest to smallest + + ha = findobj(hf,'Tag','AxisSeries'); + axes(ha) + cla + line(1000*Data.Time(Results.Time),Results.ImageGridAmp(iAmpNrm(1:MAXLINE),:)') + axis tight + grid on + + [ignore,GUI.iTime] = max(max(abs(Results.ImageGridAmp(iAmpNrm(1:MAXLINE),:)))); + % gives us the max time index + + V = axis; % what's the settings + UD = struct('iTime',GUI.iTime,'Time',Data.Time(Results.Time)); + % iTime is the integer time index in the array of data. Time is the time in engineering units + hline = line(1000*[UD.Time(UD.iTime);UD.Time(UD.iTime)],[V(3);V(4)],'Color','b','linewidth',2); + set(ha,'UserData',setfield(UD,'hline',hline)); + + drawnow + + view_minnorm_gui(Results,GUI) + + hpatch = findobj(gca,'Type','patch'); % find the patch + set(hpatch,'FaceLighting','flat'); % much faster rendering + hm = findobj(gcf,'Label','Toggle Face'); + set(hm,'UserData',hpatch); + hm = findobj(gcf,'Label','Toggle Lighting'); + set(hm,'UserData',hpatch); + + + hud = findobj(hf,'Tag','UimenuDataSets'); + set(hud,'UserData',Results); % set results into ram + + rotate3d on + axis vis3d % freeze the size for three d rotation + +case 'set time' + ha = findobj(hf,'Tag','AxisSeries'); + UD = get(ha,'UserData'); + % UD.Time tells us where we are in true unit + set(UD.hline,'Xdata',[1000 1000]*UD.Time(floor(UD.time_scale *(UD.iTime-1)+1))); % move it + axes(ha); + xlabel(sprintf('Time: %7.1f',1000*UD.Time(floor(UD.time_scale *(UD.iTime-1)+1)))); + +case 'scale_colormap' + % let the user adjust the color scaling for greater saturation + hv = findobj(hf,'Tag','AxisView'); + axes(hv); % set to the current figure + org_caxis = caxis; % what is the color axis + ScaleFactor = inputdlg('Enter Caxis Scaling Factor','BrainStorm Movie Maker',[1 50],{'1'}); + ScaleFactor = str2num(ScaleFactor{:}); + %caxis(str2num(ScaleFactor{:})*org_caxis); + cmap_orig = grayish(hot(128),.33); + %cmap_orig(1:round(size(cmap_orig,1)/5),:) = brighten(round(size(cmap_orig,1)/5)); + + ind_trim = min([128,floor(128*( 1 - exp(-(ScaleFactor-1)/6 )))+1]); + cmap = (cmap_orig); + cmap(1:ind_trim,:) = (repmat(cmap(1,:),length(1:ind_trim),1)); + cmap(ind_trim+1:end,:) = (grayish(hot(size(cmap(ind_trim+1:end,:),1)),.33)); + + hud = findobj(hf,'Tag','UimenuDataSets'); + Results = get(hud,'UserData'); % the results data + M = max(abs(Results.ImageGridAmp(:))); + colormap((cmap)) + caxis([0,M]) + +case 'create movie' + hud = findobj(hf,'Tag','UimenuDataSets'); + hv = findobj(hf,'Tag','AxisView'); + hp = findobj(hv,'Type','Patch'); % get the patch + Results = get(hud,'UserData'); % the results data + if(isempty(Results)), + msgbox('Load data first','Notice','modal'); + return + end + + NF = getframe(hf); % the whole figure + + mpg_limits = size(NF.cdata); %the size of the figure + if ((mpg_limits(1) > 480) | (mpg_limits(2) > 640)), + ButtonName = questdlg(sprintf('Resize your window to 480 x 640?')); + switch ButtonName + case 'Yes' + set(hf,'units','pixels') + Vposition = get(hf,'Position'); + set(hf,'Position',[Vposition(1:2) 640 480]); % don't know why this translates to 480 x 640 + %NF = getframe(hf); % the whole figure again + case 'No' + % do nothing + case 'Cancel' + % user punted, so will we + return + end + end + + + % let the user adjust the color scaling for greater saturation + axes(hv); % set to the current figure + org_caxis = caxis; % what is the color axis + if 0 + ScaleFactor = inputdlg('Enter Caxis Scaling Factor','BrainStorm Movie Maker',[1 50],{'1'}); + caxis(str2num(ScaleFactor{:})*org_caxis); + end + + + % Check if we have enough memory + MovieSiz = length(Results.Time)*prod(size(NF.cdata)); + if MovieSiz > 128e6 + disp(['The memory requirement might be too large for your system : ', round(num2str(MovieSiz/1e6,'%4.0f')),' MBytes']) + ans = input('Would you like to decimate the time series ? (Y/N) ','s'); + switch(lower(ans)) + case 'y' + disp(['Current number of time samples: ', int2str(length(Results.Time))]) + num = input('How many time samples would you like to achieve ? : '); + oldtime = Results.Time; + Results.Time = linspace(Results.Time(1),Results.Time(end),num); + time_scale = abs(Results.Time(2)-Results.Time(1))/abs(oldtime(2)-oldtime(1)); + otherwise + % nothing + time_scale = 1; + end + else + time_scale = 1; + end + + ha = findobj(hf,'Tag','AxisSeries'); + UD = get(ha,'UserData'); % get the userdata + UD.time_scale = time_scale; + set(ha,'UserData',UD); + + %[NF(1:length(Results.Time))] = (deal(NF)); % allocate memory + + ha = findobj(hf,'Tag','AxisSeries'); + disp(sprintf('Making movie of %.0f slices',length(Results.Time))); + Results.ImageGridAmp = abs(Results.ImageGridAmp); + for i = 1:length(Results.Time), + set(ha,'UserData',setfield(get(ha,'UserData'),'iTime',i)); + view_minnorm_cb('set time') % set the time bar + set(hp,'FaceVertexCdata',(Results.ImageGridAmp(:,floor((i-1)*time_scale+1)))); + drawnow + disp(' ') + % NF(i) = getframe(hf); + end + caxis(org_caxis); % reset the color axis back to original + + + set(hv,'UserData',struct('Movie',NF)); + msgbox('Done. You may save and/or play the movie','Make Movie','modal'); + +case 'save movie' + ht = findobj(0,'Tag','TASKBAR'); + UD = get(ht,'UserData'); % get the userdata + % want UD.DataName + + ha = findobj(hf,'Tag','AxisView'); + UD1 = get(ha,'UserData'); + % want the movie + if(~isfield(UD1,'Movie')), + msgbox('No movie to save','Notice','modal'); + return + end + + [PATH,NAME,EXT,VER] = fileparts(UD.DataName); + + ButtonName = questdlg('Save as Matlab Movie or MPEG','Movie Save','Matlab','MPEG','Tiff','MPEG'); + switch ButtonName + case 'Matlab' + EXT = '.mat'; + case 'MPEG' + EXT = '.mpg'; + case 'Tiff' + EXT = '.tif'; + end + + cd(PATH); + switch ButtonName + case {'Matlab' 'MPEG'} + [NAME,PATH] = uiputfile([NAME '_movie' EXT],'Save the Movie information'); + case 'Tiff' + [NAME,PATH] = uiputfile([NAME '_movie' EXT],'Establish a Tif Root Name'); + end + + if(~NAME), % user punted + return + end + + Movie = UD1.Movie; + switch ButtonName + case 'Matlab' + save(fullfile(PATH,NAME),'Movie'); + case 'MPEG' + % note that in Matlab 5.3, the colormap is bogus in mpgwrite + mpgwrite(Movie,hot(64),fullfile(PATH,NAME)); + case 'Tiff' + [PATH,NAME,EXT,VER] = fileparts(NAME); % knock the extension back off + for i = 1:length(Movie) + imwrite(frame2im(Movie(i)),fullfile(PATH,sprintf('%s_%03.0f.tif',NAME,i)),'tif'); + end + end + + msgbox('Done Saving','BrainStorm Movie Maker','modal'); + +case 'load movie' + [NAME,PATH] = uigetfile('*movie.mat','Load the Matlab Movie File'); + if(NAME==0), + return + end + + UD = load(fullfile(PATH,NAME)); + if(~isfield(UD,'Movie')), + msgbox('No movie to load','Notice','modal'); + return + end + ha = findobj(hf,'Tag','AxisView'); + set(ha,'UserData',setfield(get(ha,'UserData'),'Movie',UD.Movie)); + + +case 'play movie' + ha = findobj(hf,'Tag','AxisView'); + UD1 = get(ha,'UserData'); + % want the movie + if(~isfield(UD1,'Movie')), + msgbox('No movie to play','Notice','modal'); + return + end + movie_player(UD1.Movie); + + +case 'orthoviews' + %delete(findobj(gcf,'Type','Light')); + ha = findobj(gcf','Tag','AxisView'); + hp = findobj(ha,'Type','Patch'); + ha1= findobj(gcf','Tag','axsub1'); + ha2= findobj(gcf','Tag','axsub2'); + ha3= findobj(gcf','Tag','axsub3'); + ha4= findobj(gcf','Tag','axsub4'); + hps= findobj([ha1,ha2,ha3,ha4],'Type','Patch'); + + TAG = get(gcbo,'Userdata'); + + if isempty(TAG)|TAG == 1 + TAG = 0; + %set(ha,'Visible','off') + if isempty(hps) + hps= copyobj([hp,hp,hp,hp],[ha1,ha2,ha3,ha4]); + axes(ha1), view(-180, 90), axis equal, axis off, camlight + axes(ha2), view(-180, 0), axis equal, axis off, camlight + axes(ha3), view(-90, 0), axis equal, axis off, camlight + axes(ha4), view(0, 0), axis equal, axis off, camlight + else + set(hps,'visible','on') + end + set(hp,'visible','off') + else + TAG = 1; + set(hps,'visible','off') + set(hp,'visible','on') + end + set(gcbo,'Userdata',TAG); + +case 'normalize_colormap' % Normalize colormap to maximum + ha(1) = findobj(gcf','Tag','AxisView'); + ha(2)= findobj(gcf','Tag','axsub1'); + ha(3)= findobj(gcf','Tag','axsub2'); + ha(4)= findobj(gcf','Tag','axsub3'); + ha(5)= findobj(gcf','Tag','axsub4'); + + hps= findobj(gcbf,'Type','Patch'); + hps = hps(1); + crtx_amp = get(hps,'FaceVertexCData'); + set(ha,'clim',[0 max(crtx_amp)]); + + +case 'gotime' % Map the current map at a specified time instant + gotime = findobj(gcf','Tag','gotime'); + time = str2num(get(gotime,'String'))/1000; + + ht = findobj(0,'Tag','TASKBAR'); + h = findobj(gcf,'Type','Patch'); + Results = get(h(1),'Userdata'); + if isempty(Results) + UD = get(ht,'UserData'); % get the userdata + cd(UD.Users.STUDIES) + Results = load(UD.DataName,'ImageGridTime','ImageGridAmp'); + set(h(1),'Userdata',Results) + end + + [mm, itime] = min(abs(Results.ImageGridTime - time)); + Results.ImageGridAmp = Results.ImageGridAmp(:,itime); + set(h,'FaceVertexCData',abs(Results.ImageGridAmp)) + + ha = findobj(gcf,'Tag','AxisSeries'); + axes(ha) + UD = get(ha,'UserData'); + set(UD.hline,'Xdata',[Results.ImageGridTime(itime)... + Results.ImageGridTime(itime)]*1000) + +end + + + +return diff --git a/epilepsie/view_topography_cb.m b/epilepsie/view_topography_cb.m new file mode 100644 index 0000000..27bb17e --- /dev/null +++ b/epilepsie/view_topography_cb.m @@ -0,0 +1,849 @@ +function view_topography_cb(action); +% VIEW_TOPOGRAPHY_CB Callback for viewing topographies as min norm solutions +% function view_topography_cb(action); +% Call with no arguments to build gui. +% Calls view_minnorm_gui to actually create the first minimum norm solution +% Sequence is to call rap music first, then this routine applied to the results file + +% John C. Mosher, Ph.D., See Copyright.m file for information. +% $Date: 1/24/01 5:50p $ $Revision: 1 $ + +if(~exist('action','var')), + action = 'build'; +end + +hf = gcbf; % who called me + +switch deblank(lower(action)) +case 'build' + open('view_topography_cb.fig'); + +case 'reset' + % Reset all of the buttons to initial values, refresh the studies list + % Objects: AxisStudy, AxisSignal, AxisNoise, AxisSVD + % EditMinTime, EditMaxTime, EditRank, EditCorr, EditReg + % SliderRank, SliderCorr, + % PopupSVD, PopupReg, PopupOrder, ExecuteRAP + + % Set the menu action + + hur = findobj(hf,'Tag','UimenuReset'); % handle of uimenu for reseting + hud = findobj(hf,'Tag','UimenuDataSets'); + hub = findobj(hf,'Tag','UimenuBSTStudy'); % the studies + delete(hur); + delete(hud); + delete(hub); + + find_brainstorm_files('studies',[],hf); % restablish the menu + hub = findobj(hf,'Tag','UimenuBSTStudy'); % the studies created by that call + % now create a menu to find the datasets for those studies + hud = uimenu('Label','DataSets','Tag','UimenuDataSets'); + % and the call to reset this gui + hur = uimenu('Label','Reset GUI','Tag','UimenuReset',... + 'Callback','view_topography_cb(''reset'')'); + + % So the studies menu has a list of StudySubjects to write to UserData + % now append to each study menu callback a datasets menu action + + hub1 = get(hub,'children'); % what are all of the studies + % These line unnecessary now that JCM dropped the refresh + % hub1r = findobj(hub1,'Label','Refresh Studies'); + % hub1(find(hub1==hub1r)) = []; % don't update the refresher child + + for i = 1:length(hub1), % each submenu of the study menu + cb = get(hub1(i),'Callback'); + % datamenu will make a menu of data sets for min norm + set(hub1(i),'Callback',[cb 'viewtopographydatamenu;']); + end + + % so the menus are rebuilt. Now for the other objects. Activate all of them + % Study has the original data, Series has the time series, View has the patch rendering + + TAGS = {'AxisStudy', 'AxisSeries', 'AxisView'}; + + for i = 1:length(TAGS), + axes(findobj(hf,'Tag',TAGS{i})); + cla reset + set(gca,'Tag',TAGS{i},'Units','Normalized'); % set tag back in + axis on + grid off + end + + hm = findobj(gcf,'Label','Toggle Face'); + delete(hm) + hm = findobj(gcf,'Label','Toggle Lighting'); + delete(hm) + + uimenu(gcf,'Label','Toggle Face','callback','toggleface(get(gcbo,''UserData''))','UserData',[]); + uimenu(gcf,'Label','Toggle Lighting','callback','togglelight(get(gcbo,''UserData''))','UserData',[]); + + % end of reset + +case 'view data' + % user has clicked on some data in the data menu. + ht = findobj(0,'Tag','TASKBAR'); + UD = get(ht,'UserData'); % get the userdata + % interested in StudySubject information and DataName string + + SourceResults = load_brainstorm_file(UD.DataName); + + % we expect this file to be the results file of Rap music (or least squares). + % so the DataName should have the name "results" in it. + if(~isempty(findstr('_results',deblank(lower(UD.DataName))))), + % name has the string '_results' in it, see if it is has indep topographies + if(isempty(SourceResults.IndepTopo)), + msgbox('Data has no IndepTopo to view','Wrong Data Set','modal'); + return + end + % Get the original Data structure + Data = load_brainstorm_file(SourceResults.GUI.DataName); + else + % assume it is a data file + msgbox('DataName does not have the name ''results''','Wrong Data Set','modal') + return + end + + Channel = load_brainstorm_file(SourceResults.StudySubject.Channel); + Channel = Channel.Channel; + GoodChannel = good_channel(Channel,Data.ChannelFlag,'MEG'); + + %% CHEAT, show data and residual in a separate window for now + figure(windfind(sprintf('Synthesized Data and Residuals: %s',UD.DataName))) + windclf + plot([Data.F(GoodChannel,SourceResults.Time) ... + SourceResults.Fsynth Data.F(GoodChannel,SourceResults.Time)-SourceResults.Fsynth]'); + title(sprintf('%s: Data, Synth, Resid',UD.DataName),'interpreter','none') + drawnow + + ha = findobj(hf,'Tag','AxisStudy'); + axes(ha) + cla + line(Data.Time(SourceResults.Time),Data.F(GoodChannel,SourceResults.Time)') + title(Data.Comment) + axis tight + grid on + + ha = findobj(hf,'Tag','AxisSeries'); + axes(ha) + cla + line(Data.Time(SourceResults.Time),SourceResults.TimeSeries) + axis tight + grid on + + drawnow + + hud = findobj(hf,'Tag','UimenuDataSets'); + set(hud,'UserData',SourceResults); % set results into ram of UimenuDataSets + + view_topography_cb('make topographies') + + rotate3d on + +case 'make topographies' + + hud = findobj(hf,'Tag','UimenuDataSets'); + SourceResults = get(hud,'UserData'); + ha = findobj(hf,'Tag','AxisView'); + axes(ha) + cla + User = get_user_directory; % default directory + % want to understand how many vertices there are, partial load + HeadModel = load(fullfile(User.STUDIES,SourceResults.StudySubject.HeadModel),'ImageGridLoc'); + + % just how many grid points are there? + % CHEAT, always looks at grid 1 + if ~isfield(HeadModel,'ImageGridLoc') + errordlg('Please Compute the Gain Matrix (ie an Image Grid) over the Cortical Surface First ') + return + end + + GUI.iGrid = [HeadModel.ImageGridLoc{:}]; + % CHEAT: expects only one ImageGridLOc + GUI.iGrid = GUI.iGrid(1); + + User = get_user_directory; + load(fullfile(User.SUBJECTS,SourceResults.StudySubject.SubjectTess),'Vertices'); + Vertices = Vertices{HeadModel.ImageGridLoc{GUI.iGrid}}; + NumVerts = size(Vertices,2); % number of grid points Cheat ImageGridLoc + + % CHEAT, hidden string to trigger a simulated patch + DataStored = whos('-file',SourceResults.GUI.DataName); + if(~isempty(strmatch('pndx',{DataStored.name}))), + % Yes! We stored a pndx matrix in the original data file. + % synthesize the ImageGridAmp from this information + Answer = questdlg('Min Norm or Use the Patch','Patch Index Detected',... + 'Min Norm','Patch','Patch'); + switch Answer + case 'Patch' + % which patch, the true or the estimated + if(~isempty(strmatch('pndxs',{DataStored.name}))), + TrueOrFound = questdlg('True or Estimated Patch','Patch Solution Detected',... + 'True','Estimated','True'); + switch TrueOrFound + case 'True' + temp = load_brainstorm_file(SourceResults.GUI.DataName,'pndx'); + pndx = temp.pndx; % the patch indices + case 'Estimated' + temp = load_brainstorm_file(SourceResults.GUI.DataName,'pndxs'); + pndx = temp.pndxs; % the patch indices + %CHEAT: For IPMI, the first dipolar source can't be seen. Replace it with the + % the bigger true patch + msgbox('Overwriting the first estimated source with the true patch',... + 'IPMI Viewchart Cheat for Presentation','modal'); + temp = load_brainstorm_file(SourceResults.GUI.DataName,'pndx'); + pndx{1} = temp.pndx{1}; + end + else + % Estimated patch not detected + temp = load_brainstorm_file(SourceResults.GUI.DataName,'pndx'); + pndx = temp.pndx; % the patch indices + end + % clear the min norm answer + SourceResults.ImageGridAmp = zeros(NumVerts,length(pndx)); + for i = 1:length(pndx), + SourceResults.ImageGridAmp(pndx{i},i) = 1; % unity patch + end + [ignore,SourceResults.ImageGridAmp] = colnorm(SourceResults.ImageGridAmp); + set(hud,'UserData',SourceResults); % save back in + otherwise + % do nothing, we calculated the min norm below + end + end + + % if it is still empty, then we minimum norm the data + if(isempty(SourceResults.ImageGridAmp)), % topo's have not been converted + % Cheat, I always want Tikhonov Condition on the min norm data + SourceResults.GUI.REG = 'Tikhonov'; + SourceResults.GUI.Tikhonov = inputdlg('Enter the Tikhonov Condition Number: ',... + 'Topography Mininum Norm',[1 50],{'1000'}); + if(isempty(SourceResults.GUI.Tikhonov)), % user bailed so will we + return + end + SourceResults.GUI.Tikhonov = str2num(SourceResults.GUI.Tikhonov{1}); + + MinResults = minnorm(SourceResults); % local call below + [ignore,SourceResults.ImageGridAmp] = colnorm(MinResults.ImageGridAmp); + % CHEAT notice, would love to save these results, but as of 6/17 have become + % worried about overwriting the original filename in taskbar. + % Stored results would also not allow different regularization parameters. + set(hud,'UserData',SourceResults); % save back in + end + + SimulateMinNorm = questdlg('Synthesize a "mininmum norm" sequence for viewing?'); + SourceResults.SimulateMinNorm = SimulateMinNorm; % save into ram version + switch SimulateMinNorm + case 'Yes' + % Lets Synthesize the ImageGridAmp information as though it were a minimum norm + % Each column of ImageGridAmp is the new min norm solution to the topography. + % Let's column normalize each, then multiply it by it's time series, which already + % anticipates a unity column norm signal + [ignore,TempIndepTopo] = colnorm(SourceResults.ImageGridAmp); % make these the topographies + SourceResults.ImageGridAmp = zeros(size(SourceResults.ImageGridAmp,1),size(SourceResults.TimeSeries,1)); + for i = 1:size(TempIndepTopo,2), % for each topography + SourceResults.ImageGridAmp = SourceResults.ImageGridAmp + ... + TempIndepTopo(:,i)*SourceResults.TimeSeries(:,i)'; + end + end + + set(hud,'UserData',SourceResults); % save back in, including min norm answer + + + cdata = SourceResults.ImageGridAmp(:,1); + SubjectTess = load_brainstorm_file(SourceResults.StudySubject.SubjectTess); + + view_minnorm(SubjectTess.Faces{GUI.iGrid},SubjectTess.Vertices{GUI.iGrid}',cdata,grayish(bluehot(128),.33),ha); % local call below + % creates a patch in the axisview + + mx_val = max(SourceResults.ImageGridAmp(:)); + mn_val = min(SourceResults.ImageGridAmp(:)); + + if(0) + if(mn_val < 0), % we have negative values + % balance the colors + caxis(max(abs([mx_val mn_val]))*[-1 1]); + else + caxis([0 mx_val]) + end + else + % always balance the colors + caxis(max(abs([mx_val mn_val]))*[-1 1]); + end + + rotate3d on + axis vis3d + + hpatch = findobj(gca,'Type','patch'); % find the patch + set(hpatch,'FaceLighting','flat'); % much faster rendering + hm = findobj(gcf,'Label','Toggle Face'); + set(hm,'UserData',hpatch); + hm = findobj(gcf,'Label','Toggle Lighting'); + set(hm,'UserData',hpatch); + + switch SimulateMinNorm + case 'Yes' + % set time marker + ha = findobj(hf,'Tag','AxisSeries'); + axes(ha) + V = axis; % what's the settings + hline = findobj(ha,'Type','line'); % get the lines + Xdata = get(hline(1),'Xdata'); % get the time line + UD = struct('iTime',1,'Time',Xdata); + % iTime is the integer time index in the array of xdata. Time is the time in engineering units + hline = line([UD.Time(UD.iTime);UD.Time(UD.iTime)],[V(3);V(4)],'Color','b','linewidth',2); + set(ha,'UserData',setfield(UD,'hline',hline)); + +case 'No' % making topographies + depth_point = SourceResults.SourceLoc{1}; %first solution + depth_point = depth_point(:,1); % first source points + [ignore,ignore,ignore,ignore,hlinedepth,hstringdepth] = ... + depthgauge(depth_point,depth_point/norm(depth_point),100/1000,5/1000,1000,gca); + hseries = findobj(gcbf,'Tag','AxisSeries'); % the time series + tempcolor = get(hseries,'ColorOrder'); % colororder + % set the color of the depthgauge to that of the default line colors in the axes + set(hlinedepth,'Color',tempcolor(1,:),'MarkerFaceColor',tempcolor(1,:)) +end + +case 'create movie' + hud = findobj(hf,'Tag','UimenuDataSets'); + hv = findobj(hf,'Tag','AxisView'); + hp = findobj(hv,'Type','Patch'); % get the patch + SourceResults = get(hud,'UserData'); % the results data + if(isempty(SourceResults)), + msgbox('Load data first','Notice','modal'); + return + end + + axes(hv); + org_caxis = caxis; % the original axis + + ScaleFactor = inputdlg('Enter Caxis Scaling Factor','BrainStorm Movie Maker',[1 50],{'1'}); + caxis(str2num(ScaleFactor{:})*org_caxis); + + NF = getframe(hf); % the whole figure + mpg_limits = size(NF.cdata); %the size of the figure + if ((mpg_limits(1) > 480) | (mpg_limits(2) > 640)), + ButtonName = questdlg(sprintf('Resize your window to 480 x 640?')); + switch ButtonName + case 'Yes' + Vposition = get(hf,'Position'); + set(hf,'Position',[Vposition(1:2) 480 360]); % don't know why this translates to 480 x 640 + NF = getframe(hf); % the whole figure again + case 'No' + % do nothing + case 'Cancel' + % user punted, so will we + return + end + end + + [NF(1:size(SourceResults.ImageGridAmp,2))] = deal(NF); % allocate memory + + hobjs = get(hv,'chil'); % the children of the view axis + for i = 1:length(hobjs), + switch deblank(lower(get(hobjs(i),'type'))) + case {'text','line'} % get rid of the old depthgauges + delete(hobjs(i)) + end + end + + hlinedepth = []; % the depthgauge information + hstringdepth = []; + disp(sprintf('Making movie for %.0f topographies',size(SourceResults.ImageGridAmp,2))); + for i = 1:size(SourceResults.ImageGridAmp,2), % for each source + delete(hlinedepth) + delete(hstringdepth) + set(hp,'FaceVertexCdata',SourceResults.ImageGridAmp(:,i)); + + switch SourceResults.SimulateMinNorm + case 'Yes' + % we are simulating the time series, update the time index in the time series + ha = findobj(hf,'Tag','AxisSeries'); + UD = get(ha,'UserData'); + % UD.Time tells us where we are in true unit + set(UD.hline,'Xdata',[1 1]*UD.Time(i)); % move it + axes(ha); + xlabel(sprintf('Time: %7.1f',UD.Time(i))); + + case 'No' + % we are viewing topographies, drop in a depthgauge + depth_point = SourceResults.SourceLoc{i}; % next source points + hlinedepth = zeros(size(depth_point,2),1); % each location + hstringdepth = hlinedepth; % numbers, initial + for i =1:length(hlinedepth), + [ignore,ignore,ignore,ignore,hlinedepth(i),hstringdepth(i)] = ... + depthgauge(depth_point(:,i),... + depth_point(:,i)/norm(depth_point(:,i)),100/1000,5/1000,1000,gca); + end + hseries = findobj(gcbf,'Tag','AxisSeries'); % the time series + tempcolor = get(hseries,'ColorOrder'); % colororder + % set the color of the depthgauge to that of the default line colors in the axes + mod_i = mod(i-1,size(tempcolor,1))+1; % modulo the length + set(hlinedepth,'Color',tempcolor(mod_i,:),'MarkerFaceColor',tempcolor(mod_i,:)) + end + + drawnow + NF(i) = getframe(hf); % get the entire frame + end + + axes(hv); + caxis(org_caxis); % reset the scale axes + + set(hv,'UserData',struct('Movie',NF)); + + msgbox('Done. You may save and/or play the movie','Make Movie','modal'); + +case 'save movie' + ht = findobj(0,'Tag','TASKBAR'); + UD = get(ht,'UserData'); % get the userdata + % want UD.DataName + + ha = findobj(hf,'Tag','AxisView'); + UD1 = get(ha,'UserData'); + % want the movie + if(~isfield(UD1,'Movie')), + msgbox('No movie to save','Notice','modal'); + return + end + + [PATH,NAME,EXT,VER] = fileparts(UD.DataName); + % overwrite the extension with the desired form + ButtonName = questdlg('Save as Matlab Movie or MPEG','Movie Save','Matlab','MPEG','Tiff','MPEG'); + switch ButtonName + case 'Matlab' + EXT = '.mat'; + case 'MPEG' + EXT = '.mpg'; + case 'Tiff' + EXT = '.tif'; + end + + cd(PATH); + switch ButtonName + case {'Matlab' 'MPEG'} + [NAME,PATH] = uiputfile([NAME '_movie' EXT],'Save the Movie information'); + case 'Tiff' + [NAME,PATH] = uiputfile([NAME '_movie' EXT],'Establish a Tif Root Name'); + end + + if(~NAME), % user punted + return + end + + Movie = UD1.Movie; + switch ButtonName + case 'Matlab' + save(fullfile(PATH,NAME),'Movie'); + case 'MPEG' + % note that in Matlab 5.3, the colormap is bogus in mpgwrite + mpgwrite(Movie,hot(64),fullfile(PATH,NAME)); + case 'Tiff' + [PATH,NAME,EXT,VER] = fileparts(NAME); % knock the extension back off + for i = 1:length(Movie) + imwrite(frame2im(Movie(i)),fullfile(PATH,sprintf('%s_%03.0f.tif',NAME,i)),'tif'); + end + end + + msgbox('Done Saving','BrainStorm Movie Maker','modal'); + +case 'load movie' + [NAME,PATH] = uigetfile('*movie.mat','Load the Matlab Movie File'); + if(NAME==0), + return + end + + UD = load(fullfile(PATH,NAME)); + if(~isfield(UD,'Movie')), + msgbox('No movie to load','Notice','modal'); + return + end + ha = findobj(hf,'Tag','AxisView'); + set(ha,'UserData',setfield(get(ha,'UserData'),'Movie',UD.Movie)); + +case 'play movie' + ha = findobj(hf,'Tag','AxisView'); + UD1 = get(ha,'UserData'); + % want the movie + if(~isfield(UD1,'Movie')), + msgbox('No movie to play','Notice','modal'); + return + end + movie_player(UD1.Movie); + +end + +return + +%-----------------------------------------------------% + +function view_minnorm(faces,vertices,cdata,cmap,ha); +% VIEW_MINNORM view neural activity on the cortex with emphasis on speed for min norm solutions +% function [hf,hs,hl,tconn] = view_minnorm(faces,vertices,cdata,tconn,cmap,fname); +% faces, vertices, cdata is the standard patch or trisurf information. +% tconn is the triangle connectivity, if not given then will be computed and +% returned in the outputs. +% cmap is the colormap to apply to cdata, defaults to bluehot with a gray minimum +% fname is the window to write, defaults to current + +% Ambient, Diffusion, Specular, spec exp, spec reflect (see material +MaterialBack = [0.5 0.7 0.3 10 1]; % qualities of the background image +MaterialSource = [0.8 0.7 0.8 20 1]; % qualities for the data + +% handle user inputs +if(~exist('cmap')), + cmap= []; % activate default +end + +%% keep the text on how to create the triangle connectivity +%% TriConn +if(0) + if(isempty(tconn)), % create it for the user + tconn=cell(size(vertices,1),1); % one empty cell per vertex + disp(sprintf('Processing %.0f faces into triangle connectivity',nf)) + for iface = 1:size(faces,1), %for each triangle, what are the vertices + if(~rem(iface,25000)), + fprintf(' %.0f',iface); + end + for iside = 1:size(faces,2), %each vertex of the face + tconn{faces(iface,iside)}(end+1) = iface; % map face number to vertex cell + end + end + fprintf('\n'); + end +end + +% check out the vertex data + +mn = min(cdata(:)); % minimum non-zero, could be negative +mx = max(cdata(:)); % maximum non-zero + +cmap = grayish(hot(128),.33); % CHEAT +if (1)%isempty(cmap)), % need to generate a good colormap CHEAt + if(mn >= 0), % all positive information + cmap = grayish(hot(128),.33); + else + % we have negative values as well + cmap = grayish(bluehot(128),.33); + end +end + +% now lets plot +hs = zeros(2,1); % 1 is data, 2 is background + +axes(ha); +cla + +% form the data +hs(1) = patch('faces',faces,'vertices',vertices,... + 'facevertexcdata',cdata,'facecolor','interp','edgecolor','none',... + 'facelighting','phong'); +set_material(hs(1),MaterialSource); % local function + +colormap(cmap) + +if(mn < 0), %balance for negative values + cx = caxis; + caxis(max(abs(cx))*[-1 1]); +end + +view(2) +axis image +axis off + +hl(1) = camlight(-20,30); +hl(2) = camlight(20,30); +hl(3) = camlight(-20,-30); +for i = 1:length(hl), + set(hl(i),'color',[.8 1 1]/length(hl)/1.2); % mute the intensity of the lights +end + +return + +function set_material(isurf,data); +% set material, set only for specified handle +ka = data(1); +kd = data(2); +ks= data(3); +n= data(4); +sc= data(5); +set(isurf,'AmbientStrength', ka, 'DiffuseStrength', kd, 'SpecularStrength', ks, ... + 'SpecularExponent', n, 'SpecularColorReflectance', sc) +return + +function Results = minnorm(SourceResults); +% MINNORM Mininum norm solution as called from above, dedicated to topographies only +% As kluged up from the original minnorm_gui call: +% Parameters in GUI are: +% .DataName, string of actual data file used +% we want to minnorm the indeptopo, so let GUI.DataName = IndepTopo matrix +% .Results, optional file to write results +% don't write anywhere +% .Segment, two element vector giving the start and stop index numbers to use in +% the spatiotemporal data matrix. +% all +% .iGrid, which imaging grid to use in the subject information +% CHEAT, always set to 1 for now +% .Rank, rank to use, e.g. 10 +% no svd of topographies +% .ChannelFlag, an index of channels in the data file to process +% the full indeptopo, since it's already good +% +% The following three structure fields are optional for regularization purposes. +% They may be null or missing to represent unused. If multiple fields are given, +% then precedence is given in the order given below. +% .Condition, condition number to use in truncation, e.g. 100 +% .Energy, fractional energy to use in truncation, e.g. .95 +% .Column_norm, string of 'y' or 'n' to use in regularization +% Whatever was originally used in the call +% +% If all are null, no regularization is performed in the RAP-MUSIC loops. +% If GUI.Results is non-null,then writes results to that file. + + +BLOCK = 10000; % process by blocks + + +User = get_user_directory; +% load up the information needed for the gain matrix, partial load +HeadModel = load(fullfile(User.STUDIES,SourceResults.StudySubject.HeadModel),'Function','Param',... + 'ImageGridLoc','ImageGain','ImageGainCovar'); % expensive load + +GUI.iGrid = [HeadModel.ImageGridLoc{:}]; +% CHEAT: expects only one ImageGridLOc +GUI.iGrid = GUI.iGrid(1); + +if(isempty(HeadModel.ImageGain{GUI.iGrid})), + msgbox('Your Grid Gain Matrix is empty, please run Head Modeler to build','Error','modal'); + return +end +if 0%(isempty(HeadModel.ImageGainCovar{GUI.iGrid})), + disp(' ') + disp('Your Grid Gain Correlation matrix is empty, consider running Head Modeler to build'); + disp(' ') +end + +% ImageGains are assumed stored in the local directory to the subject head model +[path,name,ext,ver] = fileparts(fullfile(User.STUDIES,SourceResults.StudySubject.HeadModel)); +cd(path) +fid = fopen(... + fullfile(path,char(HeadModel.ImageGain{GUI.iGrid})),... + 'rb','ieee-be'); +if(fid == -1), + msgbox(sprintf('Failed to open %s',HeadModel.ImageGain{GUI.iGrid}),'Error','modal') + error(sprintf('Failed to open %s',HeadModel.ImageGain{GUI.iGrid})); + return +end + +% synthesize data +Channel = load_brainstorm_file(SourceResults.StudySubject.Channel); +Channel = Channel.Channel; +Data = struct('F',SourceResults.IndepTopo,... + 'ChannelFlag',SourceResults.ChannelFlag,... + 'Projector',SourceResults.Projector,'Comment',SourceResults.Comment); + +% now alter the data according to the bad channels +GoodChannel = good_channel(Channel,SourceResults.ChannelFlag,'MEG'); %good channels + +if(isempty(HeadModel.ImageGainCovar{GUI.iGrid})), + hwaitbar = waitbar(0,'Creating Gain matrix Covariance'); + + % just how many grid points are there? + User = get_user_directory; + load(fullfile(User.SUBJECTS,SourceResults.StudySubject.SubjectTess),'Vertices'); + Vertices = Vertices{HeadModel.ImageGridLoc{GUI.iGrid}}; + nv = size(Vertices,2); % number of grid points + + disp(sprintf('Processing for %.0f grid points . . .',nv)); + + frewind(fid); + rows = fread(fid,1,'uint32'); + + AAt = zeros(rows); + + for i = 1:BLOCK:nv, + + waitbar(i/nv,hwaitbar); + + ndx = [0:(BLOCK-1)]+i; + if(ndx(end) > nv), % last block too long + ndx = [ndx(1):nv]; + end + + cols = length(ndx); % how many columns to retrieve this time + + % 8 bytes per element, find starting point + offset = 4 + (ndx(1)-1)*rows*4; + status = fseek(fid,offset,'bof'); + if(status == -1), + error(sprintf('Error reading file at column %.0f',i)); + end + + temp = fread(fid,[rows,cols],'float32'); + + AAt = AAt + temp*temp'; % next chunk of correlations + + end + + close(hwaitbar); + + disp('Saving the gain covar back into your head model'); + % CHEAT, only works on first imaging matrix + ImageGainCovar{1} = AAt; + save(SourceResults.StudySubject.HeadModel,'ImageGainCovar','-append'); + + +else + + % already exists, load it + AAt = HeadModel.ImageGainCovar{GUI.iGrid}{1}; + +end % creating gain covariance matrix + +% knock out the rows and columns of the correlation matrix + +AAt = AAt(GoodChannel,:); +AAt = AAt(:,GoodChannel); + +% the ImageGain matrix is handled separately, due to it's size + +% did the user provide an existing control. Decompose it +if(isfield(Data,'Projector')), + if(isempty(Data.Projector)), + A = []; + Ua = []; + else + A = Data.Projector; % initialize + Ua = orth(A); + end +else % user did not give a projector + A = []; + Ua = []; +end + +% use all of the "data" (all of the indeptopographies) +F = Data.F; + +% handle this in the call +% [ignore,F] = colnorm(F); % column norm the topographies + +% use all time (all of the topographies), time is indexer to topography +Time = [1:size(F,2)]; + +% Begin the minimum norm estimate + +% recall the y = Ax, let x = A'c -> y = AA'c, solve for c, the 'coefs' of x. +% c = pinv(AA')*y, and we will regularize the inverse of AA' based on user selection +% Then form x = A'c. + +[U,S,V] = svd(AAt); +% NOTE: we regularize the indep topographies the same way as the data + +U = regsubspace(SourceResults.GUI,U,sqrt(S)); % condition based on svd of gain matrix +reg_rank = size(U,2); % reduced rank based on regularization +S = diag(S); +switch deblank(lower(SourceResults.GUI.REG)) +case 'tikhonov' + % pinv(A)*b is inv(A'*A)*A'*b. Let A = [A;lamb I]. inv(A'*A + lamb^2 I)*A'*b + Lambda = sqrt(S(1))/SourceResults.GUI.Tikhonov; % sing values already squared + Si = 1../(S(1:reg_rank)+Lambda^2); % filtered inverse +otherwise + % do nothing, truncation only + Si = 1../S(1:reg_rank); +end + +% the min norm coefs +coefs = V(:,1:reg_rank)*... + ((spdiags(Si,0,reg_rank,reg_rank)*U(:,1:reg_rank)') * F); + +% let rAAt = regularized(AAt), as found by the above +% So F = AAt *c, c = inv(rAAt), so Fsynth = AAt*c, let's calculate and stick into results +Fsynth = AAt * coefs; +% Store conveniently in the Results, Fsynth here is the regularized topography + +% now calculate the final solution + + +% just how many grid points are there? +User = get_user_directory; +load(fullfile(User.SUBJECTS,SourceResults.StudySubject.SubjectTess),'Vertices'); +Vertices = Vertices{HeadModel.ImageGridLoc{GUI.iGrid}}; +nv = size(Vertices,2); % number of grid points + +ImageGridAmp = zeros(nv,size(F,2)); % one column per topography + +hwaitbar = waitbar(0,sprintf('Processing %.0f point final inverse transform',nv)); + +disp(sprintf('Processing for %.0f grid points . . .',nv)); + +frewind(fid); +rows = fread(fid,1,'uint32'); + +for i = 1:BLOCK:nv, + + waitbar(i/nv,hwaitbar); + + ndx = [0:(BLOCK-1)]+i; + if(ndx(end) > nv), % last block too long + ndx = [ndx(1):nv]; + end + + cols = length(ndx); % how many columns to retrieve this time + + % 8 bytes per element, find starting point + offset = 4 + (ndx(1)-1)*rows*4; + status = fseek(fid,offset,'bof'); + if(status == -1), + error(sprintf('Error reading file at column %.0f',i)); + end + + temp = fread(fid,[rows,cols],'float32'); + temp = temp(GoodChannel,:); + + ImageGridAmp(ndx,:) = temp'*coefs; % next chunk of solutions + +end + +close(hwaitbar); + +fclose(fid); + + +% now map to results +if(0) % only care about a few things + + Comment = sprintf('MIN NORM, rank %.0f',GUI.Rank); + Date = datestr(datenum(now),0); + Subject = SourceResults.Subject; + Study = Study; + Time = [GUI.Segment(1):GUI.Segment(2)]; + ChannelFlag = GUI.ChannelFlag; + NoiseCov = []; + SourceCov = []; + Projector = Data.Projector; + SourceLoc = []; + SourceOrder = []; + SourceOrientation = cell(1); + ModelGain = []; + IndepTopo = []; + TimeSeries = []; + PatchNdx = []; + PatchAmp = []; + % ImageGridAmp = ImageGridAmp; + ImageGridTime = Data.Time(Time); + Function = mfilename; % name of this calling routine + + Results = struct('Comment',Comment,'Function',mfilename,'StudySubject',StudySubject,... + 'GUI',GUI,'Date',Data,'Subject',Subject,'Study',Study,'Time',Time,... + 'ChannelFlag',ChannelFlag,'NoiseCov',NoiseCov,'SourceCov',SourceCov,... + 'Projector',Projector,'SourceLoc',SourceLoc,'SourceOrder',SourceOrder,... + 'SourceOrientation',[],'ModelGain',ModelGain,... + 'IndepTopo',IndepTopo,'TimeSeries',TimeSeries,'PatchNdx',PatchNdx,... + 'PatchAmp',PatchAmp,'ImageGridAmp',ImageGridAmp,'ImageGridTime',ImageGridTime,'Fsynth',Fsynth); + Results.SourceOrientation = SourceOrientation; % struct command could kron out +end + +% we only care about imagegrid amp and Fsynth + +Results = struct('ImageGridAmp',ImageGridAmp,'Fsynth',Fsynth); + + +return % to the calling routine above diff --git a/extrema.m b/extrema.m new file mode 100644 index 0000000..2a9d265 --- /dev/null +++ b/extrema.m @@ -0,0 +1,146 @@ +function [xmax,imax,xmin,imin] = extrema(x) +%EXTREMA Gets the global extrema points from a time series. +% [XMAX,IMAX,XMIN,IMIN] = EXTREMA(X) returns the global minima and maxima +% points of the vector X ignoring NaN's, where +% XMAX - maxima points in descending order +% IMAX - indexes of the XMAX +% XMIN - minima points in descending order +% IMIN - indexes of the XMIN +% +% DEFINITION (from http://en.wikipedia.org/wiki/Maxima_and_minima): +% In mathematics, maxima and minima, also known as extrema, are points in +% the domain of a function at which the function takes a largest value +% (maximum) or smallest value (minimum), either within a given +% neighbourhood (local extrema) or on the function domain in its entirety +% (global extrema). +% +% Example: +% x = 2*pi*linspace(-1,1); +% y = cos(x) - 0.5 + 0.5*rand(size(x)); y(40:45) = 1.85; y(50:53)=NaN; +% [ymax,imax,ymin,imin] = extrema(y); +% plot(x,y,x(imax),ymax,'g.',x(imin),ymin,'r.') +% +% See also EXTREMA2, MAX, MIN + +% Written by +% Lic. on Physics Carlos Adrián Vargas Aguilera +% Physical Oceanography MS candidate +% UNIVERSIDAD DE GUADALAJARA +% Mexico, 2004 +% +% nubeobscura@hotmail.com + +% From : http://www.mathworks.com/matlabcentral/fileexchange +% File ID : 12275 +% Submited at: 2006-09-14 +% 2006-11-11 : English translation from spanish. +% 2006-11-17 : Accept NaN's. +% 2007-04-09 : Change name to MAXIMA, and definition added. + + +xmax = []; +imax = []; +xmin = []; +imin = []; + +% Vector input? +Nt = numel(x); +if Nt ~= length(x) + error('Entry must be a vector.') +end + +% NaN's: +inan = find(isnan(x)); +indx = 1:Nt; +if ~isempty(inan) + indx(inan) = []; + x(inan) = []; + Nt = length(x); +end + +% Difference between subsequent elements: +dx = diff(x); + +% Is an horizontal line? +if ~any(dx) + return +end + +% Flat peaks? Put the middle element: +a = find(dx~=0); % Indexes where x changes +lm = find(diff(a)~=1) + 1; % Indexes where a do not changes +d = a(lm) - a(lm-1); % Number of elements in the flat peak +a(lm) = a(lm) - floor(d/2); % Save middle elements +a(end+1) = Nt; + +% Peaks? +xa = x(a); % Serie without flat peaks +b = (diff(xa) > 0); % 1 => positive slopes (minima begin) + % 0 => negative slopes (maxima begin) +xb = diff(b); % -1 => maxima indexes (but one) + % +1 => minima indexes (but one) +imax = find(xb == -1) + 1; % maxima indexes +imin = find(xb == +1) + 1; % minima indexes +imax = a(imax); +imin = a(imin); + +nmaxi = length(imax); +nmini = length(imin); + +% Maximum or minumim on a flat peak at the ends? +if (nmaxi==0) && (nmini==0) + if x(1) > x(Nt) + xmax = x(1); + imax = indx(1); + xmin = x(Nt); + imin = indx(Nt); + elseif x(1) < x(Nt) + xmax = x(Nt); + imax = indx(Nt); + xmin = x(1); + imin = indx(1); + end + return +end + +% Maximum or minumim at the ends? +if (nmaxi==0) + imax(1:2) = [1 Nt]; +elseif (nmini==0) + imin(1:2) = [1 Nt]; +else + if imax(1) < imin(1) + imin(2:nmini+1) = imin; + imin(1) = 1; + else + imax(2:nmaxi+1) = imax; + imax(1) = 1; + end + if imax(end) > imin(end) + imin(end+1) = Nt; + else + imax(end+1) = Nt; + end +end +xmax = x(imax); +xmin = x(imin); + +% NaN's: +if ~isempty(inan) + imax = indx(imax); + imin = indx(imin); +end + +% Same size as x: +imax = reshape(imax,size(xmax)); +imin = reshape(imin,size(xmin)); + +% Descending order: +[temp,inmax] = sort(-xmax); clear temp +xmax = xmax(inmax); +imax = imax(inmax); +[xmin,inmin] = sort(xmin); +imin = imin(inmin); + + +% Carlos Adrián Vargas Aguilera. nubeobscura@hotmail.com \ No newline at end of file diff --git a/extrema2.m b/extrema2.m new file mode 100644 index 0000000..53a5e76 --- /dev/null +++ b/extrema2.m @@ -0,0 +1,174 @@ +function [xymax,smax,xymin,smin] = extrema2(xy,varargin) +%EXTREMA2 Gets the extrema points from a surface. +% [XMAX,IMAX,XMIN,IMIN] = EXTREMA2(X) returns the maxima and minima +% elements of the matriz X ignoring NaN's, where +% XMAX - maxima points in descending order (the bigger first and so on) +% IMAX - linear indexes of the XMAX +% XMIN - minima points in descending order +% IMIN - linear indexes of the XMIN. +% The program uses EXTREMA. +% +% The extrema points are searched only through the column, the row and +% the diagonals crossing each matrix element, so it is not a perfect +% mathematical program and for this reason it has an optional argument. +% The user should be aware of these limitations. +% +% [XMAX,IMAX,XMIN,IMIN] = EXTREMA2(X,1) does the same but without +% searching through the diagonals (less strict and perhaps the user gets +% more output points). +% +% DEFINITION (from http://en.wikipedia.org/wiki/Maxima_and_minima): +% In mathematics, maxima and minima, also known as extrema, are points in +% the domain of a function at which the function takes a largest value +% (maximum) or smallest value (minimum), either within a given +% neighbourhood (local extrema) or on the function domain in its entirety +% (global extrema). +% +% Note: To change the linear index to (i,j) use IND2SUB. +% +% Example: +% [x,y] = meshgrid(-2:.2:2,3:-.2:-2); +% z = x.*exp(-x.^2-y.^2); z(10,7)= NaN; z(16:19,13:17) = NaN; +% surf(x,y,z), shading interp +% [zmax,imax,zmin,imin] = extrema2(z); +% hold on +% plot3(x(imax),y(imax),zmax,'bo',x(imin),y(imin),zmin,'ro') +% for i = 1:length(zmax) +% text(x(imax(i)),y(imax(i)),zmax(i),[' ' num2str(zmax(i))]) +% end +% for i = 1:length(zmin) +% text(x(imin(i)),y(imin(i)),zmin(i),[' ' num2str(zmin(i))]) +% end +% hold off +% +% See also EXTREMA, MAX, MIN + +% Written by +% Lic. on Physics Carlos Adrián Vargas Aguilera +% Physical Oceanography MS candidate +% UNIVERSIDAD DE GUADALAJARA +% Mexico, 2005 +% +% nubeobscura@hotmail.com + +% From : http://www.mathworks.com/matlabcentral/fileexchange +% File ID : 12275 +% Submited at: 2006-09-14 +% 2006-11-11 : English translation from spanish. +% 2006-11-17 : Accept NaN's. +% 2006-11-22 : Fixed bug in INDX (by JaeKyu Suhr) +% 2007-04-09 : Change name to MAXIMA2, and definition added. + +M = size(xy); +if length(M) ~= 2 + error('Entry must be a matrix.') +end +N = M(2); +M = M(1); + +% Search peaks through columns: +[smaxcol,smincol] = extremos(xy); + +% Search peaks through rows, on columns with extrema points: +im = unique([smaxcol(:,1);smincol(:,1)]); % Rows with column extrema +[smaxfil,sminfil] = extremos(xy(im,:).'); + +% Convertion from 2 to 1 index: +smaxcol = sub2ind([M,N],smaxcol(:,1),smaxcol(:,2)); +smincol = sub2ind([M,N],smincol(:,1),smincol(:,2)); +smaxfil = sub2ind([M,N],im(smaxfil(:,2)),smaxfil(:,1)); +sminfil = sub2ind([M,N],im(sminfil(:,2)),sminfil(:,1)); + +% Peaks in rows and in columns: +smax = intersect(smaxcol,smaxfil); +smin = intersect(smincol,sminfil); + +% Search peaks through diagonals? +if nargin==1 + % Check peaks on down-up diagonal: + [iext,jext] = ind2sub([M,N],unique([smax;smin])); + [sextmax,sextmin] = extremos_diag(iext,jext,xy,1); + + % Check peaks on up-down diagonal: + smax = intersect(smax,[M; (N*M-M); sextmax]); + smin = intersect(smin,[M; (N*M-M); sextmin]); + + % Peaks on up-down diagonals: + [iext,jext] = ind2sub([M,N],unique([smax;smin])); + [sextmax,sextmin] = extremos_diag(iext,jext,xy,-1); + + % Peaks on columns, rows and diagonals: + smax = intersect(smax,[1; N*M; sextmax]); + smin = intersect(smin,[1; N*M; sextmin]); +end + +% Extrema points: +xymax = xy(smax); +xymin = xy(smin); + +% Descending order: +[temp,inmax] = sort(-xymax); clear temp +xymax = xymax(inmax); +smax = smax(inmax); +[xymin,inmin] = sort(xymin); +smin = smin(inmin); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [smax,smin] = extremos(matriz) +% Peaks through columns or rows. + +smax = []; +smin = []; + +for n = 1:length(matriz(1,:)) + [temp,imaxfil,temp,iminfil] = extrema(matriz(:,n)); clear temp + if ~isempty(imaxfil) % Maxima indexes + imaxcol = repmat(n,length(imaxfil),1); + smax = [smax; imaxfil imaxcol]; + end + if ~isempty(iminfil) % Minima indexes + imincol = repmat(n,length(iminfil),1); + smin = [smin; iminfil imincol]; + end +end + + +function [sextmax,sextmin] = extremos_diag(iext,jext,xy,A) +% Peaks through diagonals (down-up A=-1) + +[M,N] = size(xy); +if A==-1 + iext = M-iext+1; +end +[iini,jini] = cruce(iext,jext,1,1); +[iini,jini] = ind2sub([M,N],unique(sub2ind([M,N],iini,jini))); +[ifin,jfin] = cruce(iini,jini,M,N); +sextmax = []; +sextmin = []; +for n = 1:length(iini) + ises = iini(n):ifin(n); + jses = jini(n):jfin(n); + if A==-1 + ises = M-ises+1; + end + s = sub2ind([M,N],ises,jses); + [temp,imax,temp,imin] = extrema(xy(s)); clear temp + sextmax = [sextmax; s(imax)']; + sextmin = [sextmin; s(imin)']; +end + + +function [i,j] = cruce(i0,j0,I,J) +% Indexes where the diagonal of the element io,jo crosses the left/superior +% (I=1,J=1) or right/inferior (I=M,J=N) side of an MxN matrix. + +arriba = 2*(I*J==1)-1; + +si = (arriba*(j0-J) > arriba*(i0-I)); +i = (I - (J+i0-j0)).*si + J+i0-j0; +j = (I+j0-i0-(J)).*si + J; + + +% Carlos Adrián Vargas Aguilera. nubeobscura@hotmail.com \ No newline at end of file diff --git a/fakebar.m b/fakebar.m new file mode 100644 index 0000000..9accb9f --- /dev/null +++ b/fakebar.m @@ -0,0 +1,43 @@ +function fakebar(varargin) +% fakebar(value) displays progressing waitbars until you press cancel +% value: how many loops are to be done until a waitbar is full. Try +% values > 1000 (optional parameter) +% +% Example: +% fakebar(20000); +% +% Creates a waitbar with changing random progress. Use it to show +% your boss that you can't work at the moment because systemload +% is 100% and the calculations will take some time -> coffee ;-) +% +% Version 1.0 by Stefan Eireiner (stefan@algorithmus.info) +% last change 18.06.2004 + +if nargin > 0 + divisor = varargin{1}; +else + divisor = 1000; +end + +while(true) + fb = waitbar(0, 'Calculating Data...', 'CreateCancelBtn', 'delete(get(0,''CurrentFigure''))', 'Name', 'Analyzer 1.0'); + counter = 0; + while(counter < divisor && ishandle(fb)) + il = round((rand^2)*divisor*0.5); + adder = rand; + for m=1:il + counter = counter + adder^2; + try + waitbar(counter/divisor,fb); + catch + disp('Calculations done!'); + return; + end + end + end + if(ishandle(fb)) + delete(fb); + else + return; + end +end \ No newline at end of file diff --git a/fftfilter.m b/fftfilter.m new file mode 100644 index 0000000..abbcdae --- /dev/null +++ b/fftfilter.m @@ -0,0 +1,183 @@ +function [xf] = fftfilter(x,Fc,SR,tdim,df) +% fftfilter - Filter signal (using FFT transform) +% [xf]=fftfilter(x,Fc,SR) +% Fc =[ HPFc LPFc ] are high- and low-pass cutoff frequencies +% SR: Sampling rate +% Set one Fc to NaN to use one-sided filter. For a notch (band-stop) +% filter use one single value. +% +% [xf]=fftfilter(x,Fc,SR,tdim) +% Filtering is done along dimension tdim (default: the longest +% dimension) +% +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Based on EEGLAB eegfiltfft() & Matlab's fftfilt +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-06-09 Creation +% +% ----------------------------- Script History --------------------------------- + + +% A causal fft algorithm is applied (i.e. no phase shift). The filter +% functions is constructed from a Hamming window. +notch=0; +if nargin<3 + error +end +if numel(Fc)==1 + notch = 1; + Fc(2)=Fc(1); +end +sx=size(x); +if nargin<4 % Default longest dimension + [ignore,tdim]=max(sx); +end + +%Ensure x has an even number of data point +if rem(sx(tdim),2) + sx0 = sx; + sX0(tdim) = 1; + x = cat(tdim, x, zeros(sx0)); +end + +nyq = sx(tdim)/2; + +f = [0:nyq-1 nyq:-1:1]./sx(tdim)*SR; % Frequency vector for plotting + +% find closest freq in fft decomposition +if ~isnan(Fc(1)) && Fc(1) ~= 0 + [tmp idxl]=min(abs(f-Fc(1))); +else + idxl = 0; +end; +if ~isnan(Fc(2)) && Fc(2) ~= 0 + [tmp idxh]=min(abs(f-Fc(2))); +else + %idxh = ceil(length(fv)/2); + idxh = nyq; +end; + +% filter the data +xf=fft(x,[],tdim); +if notch + xf(idxl+1:idxh-1)=0; + if mod(length(xf),2) == 0 + xf(end/2:end)=0; + else + xf((end+1)/2:end)=0; + end; +else + xf(1:idxl)=0; + xf(end-idxl:end)=0; + xf(idxh:end)=0; +end; +xf = 2*real(ifft(xf)); + +return + + + +% Construct the filter function H(f) using frequencies in Nyquist units +N = sx(tdim)+rem(sx(tdim),2); +B = fir2(N-1,[0 rf*2 (rf+df)*2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +H=repmat(H',[ 1 sx(px(2:end))] ); +k=1; +xf = real(ifft(fft(x) .* H)); +xf = ipermute(reshape(xf(1:sx(tdim),:),sx(px)),px); + + +% This is the original function by Mario: + +function xf = lowpassFilter(x,Fs,Fp2) +% function XF = lowpassFilter(X,FS,FP2) +% +% Bandpass filter for the signal x. An causal fft algorithm +% is applied (i.e. no phase shift). The filter functions is +% constructed from a Hamming window. +% +% Fs : sampling frequency +% +% The passband (Fp2) and stop band (Fs2) are defined as +% +% --------------------------- +% |\ +% | \ +% | \ +% | \ +% | ----------------- +% | | +% Fp2 Fs2 = Fp2 + 0.5 (Hz) +% +% +% +% If NO OUTPUTS arguments are assigned the filter function H(f) and +% impulse response are plotted. +% +% NOTE: for long data traces the filter is very slow. +% +% EXEMPLE +% x= sin(2*pi*12*[0:1/200:10])+sin(2*pi*30*[0:1/200:10]) +% y=lowpassFilter(x,200,10); lowpass filter between 0 and 10 Hz +%------------------------------------------------------------------------ +% Originally produced by the Helsinki University of Technology, +% Adapted by Mariecito SCHMUCKEN 2001 +%------------------------------------------------------------------------ +Fs2 = Fp2 + 0.5; + +if size(x,1) == 1 + x = x'; +end +% Make x even +Norig = size(x,1); +if rem(Norig,2) + x = [x' zeros(size(x,2),1)]'; +end + +% Normalize frequencies +Ns2 = Fs2/(Fs/2); +Np2 = Fp2/(Fs/2); + +% Construct the filter function H(f) +N = size(x,1); +Nh = N/2; + +% B = fir2(N-1,[0 Ns1 Np1 Np2 Ns2 1],[0 0 1 1 0 0]); +B = fir2(N-1,[0 Np2 Ns2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +IPR = real(ifft(H)); + +% Visual display if off +% if nargout == 0 +% figure, +% subplot(2,1,1) +% f = Fs*(0:Nh-1)/(N); +% plot(f,H(1:Nh)); +% xlim([0 2*Fs2]) +% ylim([0 1]); +% title('Filter function H(f)') +% xlabel('Frequency (Hz)') +% subplot(2,1,2) +% plot((1:Nh)/Fs,IPR(1:Nh)) +% xlim([0 2/Fp2]) +% xlabel('Time (sec)') +% ylim([min(IPR) max(IPR)]) +% title('Impulse response') +% end + + +if size(x,2) > 1 + for k=1:size(x,2) + xf(:,k) = real(ifft(fft(x(:,k)) .* H')); + end + xf = xf(1:Norig,:); +else + xf = real(ifft(fft(x') .* H)); + xf = xf(1:Norig); +end diff --git a/field2struct.m b/field2struct.m new file mode 100644 index 0000000..07e6c3c --- /dev/null +++ b/field2struct.m @@ -0,0 +1,39 @@ +function B = field2struct(A,label,target) +%FIELD2STRUCT - Export values from a field as a fields of a new struct +% [B] = field2struct(A,label,target) uses field named label in structure +% A to create a new structure B whose fieldnames are the +% 'A.label' values and values are the corresponding 'A.target' +% +% +% Example +% >> field2struct +% +% See also: + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-06-08 Creation +% +% ----------------------------- Script History --------------------------------- +B = []; +for i=1:numel(A) + if isfield(B,getfield(A(i),label)) + warning('field2struct:DuplicatedLabel',sprintf('Duplicated label: %s', getfield(A(i),label))); + end + try + B=setfield(B,getfield(A(i),label), getfield(A(i),target)); + catch ME + switch (ME(end).identifier) + case 'MATLAB:AddField:InvalidFieldName' + warning('field2struct:InvalidFieldName','%s is not a valid field name. It will be discarded', getfield(A(i),label)) + otherwise + rethrow(ME) + end + end +end \ No newline at end of file diff --git a/fieldtriptopo.m b/fieldtriptopo.m new file mode 100644 index 0000000..0faddce --- /dev/null +++ b/fieldtriptopo.m @@ -0,0 +1,162 @@ +function fieldtriptopo(Channel,data) +xyz=getChannelLoc(Channel); +labels={Channel.Name}; +cfg.zlim='absmax'; +cfg.colorbar='yes'; +cfg.showlabels='no'; +cfg.showzlim='yes'; +cfg.fontsize=8; +topoplot(cfg,xyz(:,1),xyz(:,2),data,labels); +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% This is a subfunction for topoplotTFR and topoplotER that takes care of +% the actual interpolation and plotting. +% +% It is a modified version from the topoplot function of EEGLAB +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Copyright (C) Andy Spydell, Colin Humphries & Arnaud Delorme +% CNL / Salk Institute, Aug, 1996 +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +function topoplot(cfg,X,Y,Values,Labels) + +% User Defined Defaults: +MAXCHANS = 256; +INTERPLIMITS = 'head'; % head, electrodes +GRID_SCALE = 67; % 67 in original +CONTOURNUM = 6; +STYLE = 'both'; % both,straight,fill,contour,blank +HCOLOR = [0 0 0]; +ECOLOR = [0 0 0]; +CONTCOLOR = [0 0 0]; +EMARKERSIZE = 8; +EFSIZE = get(0,'DefaultAxesFontSize'); +HLINEWIDTH = 2; +EMARKER = '.'; +SHADING = 'flat'; % flat or interp +INTERPOLATION = 'v4'; + +Ypos = -0.45+0.9*(X - min(X)) /(max(X) - min(X)); +Xpos = -0.45+0.9*(Y - min(Y)) /(max(Y) - min(Y)); + +rmax = .5; + +ha = gca; +cla +hold on + +if ~strcmp(STYLE,'blank') + % find limits for interpolation + if strcmp(INTERPLIMITS,'head') + xmin = min(-.5,min(Xpos)); xmax = max(0.5,max(Xpos)); + ymin = min(-.5,min(Ypos)); ymax = max(0.5,max(Ypos)); + else + xmin = max(-.5,min(Xpos)); xmax = min(0.5,max(Xpos)); + ymin = max(-.5,min(Ypos)); ymax = min(0.5,max(Ypos)); + end + + xi = linspace(xmin,xmax,GRID_SCALE); % x-axis description (row vector) + yi = linspace(ymin,ymax,GRID_SCALE); % y-axis description (row vector) + + [Xi,Yi,Zi] = griddata(Ypos,Xpos,Values,yi',xi,INTERPOLATION); % Interpolate data + + % Take data within head + mask = (sqrt(Xi.^2+Yi.^2) <= rmax); + ii = find(mask == 0); + Zi(ii) = NaN; + + % calculate colormap limits + m = size(colormap,1); + if isstr(cfg.zlim) + if strcmp(cfg.zlim,'absmax') + amin = -max(max(abs(Zi))); + amax = max(max(abs(Zi))); + elseif strcmp(cfg.zlim,'maxmin') + amin = min(min(Zi)); + amax = max(max(Zi)); + end + else + amin = cfg.zlim(1); + amax = cfg.zlim(2); + end + delta = xi(2)-xi(1); % length of grid entry + + % Draw topoplot on head + if strcmp(STYLE,'contour') + contour(Xi,Yi,Zi,CONTOURNUM,'k'); + elseif strcmp(STYLE,'both') + surface(Xi-delta/2,Yi-delta/2,zeros(size(Zi)),Zi,'EdgeColor','none',... + 'FaceColor',SHADING); + contour(Xi,Yi,Zi,CONTOURNUM,'k'); + elseif strcmp(STYLE,'straight') + surface(Xi-delta/2,Yi-delta/2,zeros(size(Zi)),Zi,'EdgeColor','none',... + 'FaceColor',SHADING); + elseif strcmp(STYLE,'fill') + contourf(Xi,Yi,Zi,CONTOURNUM,'k'); + else + error('Invalid style') + end + caxis([amin amax]) % set coloraxis +end + +set(ha,'Xlim',[-rmax*1.3 rmax*1.3],'Ylim',[-rmax*1.3 rmax*1.3]) + +% Define the contours of the head +l = 0:2*pi/100:2*pi; +basex = .18*rmax; +tip = rmax*1.15; base = rmax-.004; +EarX = [.497 .510 .518 .5299 .5419 .54 .547 .532 .510 .489]; +EarY = [.0555 .0775 .0783 .0746 .0555 -.0055 -.0932 -.1313 -.1384 -.1199]; + +% Plot Electrodes +if strcmp(cfg.showlabels,'markers') + hp2 = plot(Ypos,Xpos,EMARKER,'Color',ECOLOR,'markersize',EMARKERSIZE); +elseif strcmp(cfg.showlabels,'yes') + for i = 1:length(Xpos) + text(Ypos(i),Xpos(i),Labels(i),'HorizontalAlignment','center',... + 'VerticalAlignment','middle','Color',ECOLOR,... + 'FontSize',EFSIZE) + end +elseif strcmp(cfg.showlabels,'numbers') + for i = 1:length(Xpos) + text(Ypos(i),Xpos(i),int2str(i),'HorizontalAlignment','center',... + 'VerticalAlignment','middle','Color',ECOLOR,... + 'FontSize',EFSIZE) + end +end + +% Plot Head, Ears, Nose +plot(cos(l).*rmax,sin(l).*rmax,... + 'color',HCOLOR,'Linestyle','-','LineWidth',HLINEWIDTH); +plot([.18*rmax;0;-.18*rmax],[base;tip;base],... + 'Color',HCOLOR,'LineWidth',HLINEWIDTH); + +plot(EarX,EarY,'color',HCOLOR,'LineWidth',HLINEWIDTH) +plot(-EarX,EarY,'color',HCOLOR,'LineWidth',HLINEWIDTH) + +if strcmp(cfg.colorbar,'yes') + colorbar +end + +if strcmp(cfg.showzlim,'yes') + text(0,-0.6,sprintf('Color limits:\n %.2e to %.2e ',amin,amax),'fontsize',cfg.fontsize,'HorizontalAlignment','center') +end + +hold off +axis off diff --git a/fig2pdf.m b/fig2pdf.m new file mode 100644 index 0000000..a11a2be --- /dev/null +++ b/fig2pdf.m @@ -0,0 +1,68 @@ +function [filename] = fig2pdf(varargin) +%FIG2PDF - Save a figure into a PDF file +% fig2pdf() savethe current figure in the current folder using its name +% as filename, if name is empty, filename will be like: fig_N.pdf +% A '_datetime' suffix is added if a file already exists with that name. +% +% fig2pdf(h) save the figure specified by handle h +% +% fig2pdf(h,filename) uses the specified filename (may overwrite it) +% +% Example +% >> fig2pdf +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-02-27 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/figure_call.m b/figure_call.m new file mode 100644 index 0000000..bc1f87d --- /dev/null +++ b/figure_call.m @@ -0,0 +1,62 @@ +function varargout = figure_call(name, focus) +%FIGURE_CALL - One line description goes here. +% [hf] = figure_call(name) creates figure with name if it does not exist +% [hf] = figure_call(name,focus) if focus=1 (default) the figuer get the +% focus (it is then the current window) +% +% Example +% >> figure_call(name,focus) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-01-21 Creation +% +% ----------------------------- Script History --------------------------------- + +hf = findobj(0,'-depth', 1, 'type', 'figure', 'name',name); +if isempty(hf) + hf=figure('name',name); + set(hf, 'PaperType', 'a4letter'); +end +if nargin<2 || isempty(focus) + focus=1; +end +if focus + figure(hf) +end +if nargout>0 + vaerargout= {hf}; +end +% +% % Example how to adjust your figure properties for +% % publication needs +% s = hf; +% % Select the default font and font size +% % Note: Matlab does internally round the font size +% % to decimal pt values +% set(s, 'DefaultTextFontSize', 10); % [pt] +% set(s, 'DefaultAxesFontSize', 10); % [pt] +% set(s, 'DefaultAxesFontName', 'Times New Roman'); +% set(s, 'DefaultTextFontName', 'Times New Roman'); +% % Select the preferred unit like inches, centimeters, +% % or pixels +% set(s, 'Units', 'centimeters'); +% pos = get(s, 'Position'); +% pos(3) = 8; % Select the width of the figure in [cm] +% pos(4) = 6; % Select the height of the figure in [cm] +% set(s, 'Position', pos); +% set(s, 'PaperType', 'a4letter'); +% % From SVG 1.1. Specification: +% % "1pt" equals "1.25px" +% % "1pc" equals "15px" +% % "1mm" would be "3.543307px" +% % "1cm" equals "35.43307px" +% % "1in" equals "90px" \ No newline at end of file diff --git a/filefinder.m b/filefinder.m new file mode 100644 index 0000000..340ccb6 --- /dev/null +++ b/filefinder.m @@ -0,0 +1,62 @@ +function = filefind(p,wd) +%FILEFIND - Find files using wildcards & recursive search +% [] = filefind.m(input) +% +% Example +% >> filefind.m +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-10-14 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/fileparts2.m b/fileparts2.m new file mode 100644 index 0000000..2b235bc --- /dev/null +++ b/fileparts2.m @@ -0,0 +1,74 @@ +function S = fileparts2(fname,arg, mode) +%FILEPARTS2 - One line description goes here. +% [S] = fileparts2(FILE,ARG) returns a specific part of a filename +% ARG can be specified as text or as a numerical value: +% 'path' [0] (default) +% 'name' [1] +% 'ext' [0.1] +% 'name.ext' [1.1] +% 'shortname' [2] +% 'path\name' [3] +% 'root' [-Inf] +% if ARG is a negative integer, retrieves the n-th folder up. +% [S] = fileparts2(FILE,ARG,MODE) +% if MODE is: +% 'none', retrieves path as given in the FILE argument +% 'absolute' converts output to an absolute path +% 'relative' force output to be a relative path +% +% Example +% >> fileparts2('d:\tmp\test.ext','name') returns 'test' +% >> fileparts2('d:\tmp\test.ext','root') returns 'd:' +% >> fileparts2('d:\tmp\test.ext','root') returns 'd:' +% +% See also: fileparts + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-18 Creation +% +% ----------------------------- Script History --------------------------------- +[p,n,e]=fileparts(fname); +if nargin==1 + S = p; + return; +end +switch arg + case {'path' 0} + S = p; + case {'root' -Inf} + S = regexp(p, [filesep '.*\'], 'split'); + i=find(~cellfun('isempty',S)); + S = [repmat(filesep,1,i(1)-1) S{i(1)} filesep]; + case {'shortname' 2} + if ispc + % shortname for windows 95, XP, Vista, etc. + if not(exist(fname,'file')) + error('File not found: %s', fname) + end + [ok,w]=system(sprintf('dir "%s" /x/a-d/-c',fname)); + if ok + error(w); + end + w=strread(w, '%s', 'delimiter',char(10)); + w=strread(w{6}, '%s'); + S = w{4}; + else + warning('Shortname is irrelevant in non-Windows OS.'); + S = [n e]; + end + case {'name',1} + S = n; + case {'ext' .1} + S = e; + case {'path\name' 3} + S= fullfile(p,n); + case {'name.ext' 1.1} + S = [n e]; +end \ No newline at end of file diff --git a/fillarray.m b/fillarray.m new file mode 100644 index 0000000..55be553 --- /dev/null +++ b/fillarray.m @@ -0,0 +1,117 @@ +function Y = fillarray(C,X,S,O) +%FILLARRAY - Fill an array with given values +% [Y] = fillarray(C,X,S) +% Creates an array of size S whose values in position C are X +% C and X should be either numerical arrays or cell lists of the same +% length. Each cell should be of the same length, but X or X{i} may be +% scalar, in which case it is expanded to match C{i} length. If X is +% an array +% [Y] = fillarray(C,[],S) and [Y] = fillarray(C,1,S) +% Fills the array of size S with ones (default value). +% [Y] = fillarray(C,X) +% Fills a vertical array at positions C with values in X. +% The length of Y is the maximum index found in C +% [Y] = fillarray(C) +% Fills a vertical array of size [max(C) 1] with 1's at positions C +% [Y] = fillarray(C,X,S,O) +% Non specified values are O (O=1, if you want ones instead of zeros) +% +% Example +% >> fillarray +% +% See also: sparse + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-05 Creation +% KND 2008-01-23 Input size S is no more mandatory +% KND 2010-03-22 Corr. Bug. & parsing inputs +% ----------------------------- Script History --------------------------------- + +if nargin<1 || nargin>4 + error('Wrong number of inputs') +end + +if nargin<2 + X=[]; +end +if ~iscell(C) + C={C}; + if ~iscell(X) && ~isempty(X) + X={X}; + end +end +if ~isempty(X) + nX=numel(X); + nC=numel(C); + if ~iscell(X) + if nX==1 + X = repmat({X},nC,1); + nX=nC; + else + X = num2cell(X); + end + end + + if nC~=nX + error('Sizes of C and X do not match'); + end +end + + +if nargin<3 + S=[]; +end +if nargin<4 + O=0; +end +if isempty(S) + S=[NaN]; +end +if length(S)<2 && ~isnan(S(1)) + S=[S 1]; +end +if all(~isnan(S)) + Y=zeros(S); +else + Y=[]; +end +twopass=1; +if ~isequal(O,0) + twopass=2; +end +while twopass + Y(:)=O; + if isempty(X) + Y([C{:}])=ones(length([C{:}]),1); + else %if max(S)==prod(S) + for i=1:length(C) + if length(X{i})==1 + X{i}=repmat(X{i}, length(C{i}),1); + end + if isvector(C{i}) + Y(C{i})=X{i}; + elseif size(C{i},2) == 2 + if all(isnan(NaN)) + S=[Inf]; + end + for j=1:size(C{i},1) + Y(C{i}(j,1),C{i}(j,2))=X{i}(j); + end + else + error('C must be a 1-D list of absolute indices or subs indices (currently for 2D arrays only)') + end + end + end + twopass = twopass-1; +end + +if all(isnan(S)) %verticalize Y + Y=Y(:); +end diff --git a/findTessellationHandles.m b/findTessellationHandles.m new file mode 100644 index 0000000..e6cbdb4 --- /dev/null +++ b/findTessellationHandles.m @@ -0,0 +1,92 @@ +function [ hp, ha, hf ] = findTessellationHandles( varargin ) +%findTessellationHandles - Find ancestors handles related to a patch surface +% +% [ hp, ha, hf ] = findTessellationHandles +% Try to guess the handles to the patch, its axes and it figure +% +% [ hp, ha, hf ] = findTessellationHandles( h ) +% h may be a (list of) handle to a patch, axes or figure + +h=[]; +hf=[]; +ha=[]; +hp=[]; +if nargin>0 + h=varargin{1}; +end +h=h(ishandle(h)); +if isempty(h) + h=0; + h=[get(h(1), 'CurrentFigure') h ]; + h=[get(h(1), 'CurrentAxes') h ]; + h=[gco h ]; +end +if ~isempty(h) + if isequal(get(get(h(end), 'Parent'), 'Type'), 'axes') + h=[h get(h, 'Parent')]; + end + if isequal(get(get(h(end), 'Parent'), 'Type'), 'figure') + h=[h get(h(end), 'Parent')]; + end +end +for i=1:length(h) + hp=[findobj([h(i)], 'Type', 'patch'); ... + ]; % findobj([h(i)], 'Type', 'surface');]; + if ~isempty(hp) + break + end +end +switch length(hp) + case 0 + hp=[]; + ha=findobj([h], 'Type', 'axes'); + hf=findobj([h], 'Type', 'figure'); + return + case 1 + % nothing to do + otherwise + hp=hp(1); +end + +ha=get(hp, 'Parent'); +hf=get(ha, 'Parent'); + +return + + +% +% OLDIES +% + + + + + +if isequal(get(get(h, 'Parent'), 'Type'), 'axes') + +end + +if ~isempty(hp) + ha=get(hp, 'Parent'); +elseif isequal(htype, 'axes') + ha=h; +end + +if ~isempty(ha) + hf=get(ha, 'Parent'); +elseif isequal(ha, 'figure') + hf=h; +end + +if isempty(hp) + + try, hp=hp(1); end +end + +if isempty(hp) + ha=get(hp, 'Parent'); + if isempty(ha) + ha=findobj(hf, 'type', 'axes'); + end + hf=get(ha, 'Parent'); +end \ No newline at end of file diff --git a/findclosest2.m b/findclosest2.m new file mode 100644 index 0000000..7f81fc7 --- /dev/null +++ b/findclosest2.m @@ -0,0 +1,60 @@ +function [VecInd,minn] = findclosest2(VecGuess, VecRef, mode) +% FINDCLOSEST: Find entries of closest elements between two vectors. +% +% USAGE: VecInd = findclosest(VecGuess, VecRef); +% USAGE: VecInd = findclosest(VecGuess, VecRef, mode); +% +% DESCRIPTION: +% VecGuess is a vector for which one wants to find the closest entries in vector VecRef +% VecInd is the vector of indices pointing at the entries in +% vector VecRef that are the closest to VecWin +% VecInd is of the same length as VecGuess +% 'mode' is a string specifying how the search is made: +% - 'closest': find the closest value (above or below) +% - 'above': find the closest value above the VecGuess +% - 'below': +% In other words, VecRef(VecInd(i)) is the element of VecRef closest to VecGuess(j) +% VecRef and VecGuess do not need to be the same length + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2010 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: ? +% ----------------------------- Script History --------------------------------- +% +% ------------------------------------------------------------------------------ + +if isvector(VecRef) + if size(VecRef,1) == 1 + VecRef = VecRef'; + end +end +if nargin<3 + mode='closest'; +end +tmp = repmat(VecRef,1,length(VecGuess)); +switch(mode) + case 'closest' + [minn VecInd] = min(abs(repmat(VecGuess(:)',length(VecRef),1) - tmp)); + case 'above' + [minn VecInd] = min(abs(repmat(VecGuess(:)',length(VecRef),1) - tmp)); + case 'below' + [minn VecInd] = min(abs(repmat(VecGuess(:)',length(VecRef),1) - tmp)); +end +VecInd = reshape(VecInd, size(VecGuess)); +minn = reshape(minn, size(VecGuess)); \ No newline at end of file diff --git a/findinstruct.m b/findinstruct.m new file mode 100644 index 0000000..980b77a --- /dev/null +++ b/findinstruct.m @@ -0,0 +1,57 @@ +function y = findinstruct(x,S,fun,varargin) +%FINDINSTRUCT - Finds a value in the fields (and subfields) of a structure +% [y] = findinstruct(x,S) +% Searches in structure S any field equal to x and outputs a cell +% array of subscripted references to the matching elements +% +% [y] = findinstruct(x,S,fun) +% Allows user to specify his/her own function to be tested using +% input x and S content. E.g. 'strmatch(x,S)' +% +% Example +% >> a.b=1;a.c='toto'; +% >> findinstruct(1,a) +% >> findinstruct('tot',a,'strmatch(x,S)') +% +% See also: subsref + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-12-06 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<3 || isempty(fun) + fun='isequal(x,S)'; +end +y=[]; +if isstruct(S) + f=fieldnames(S); + for j=1:numel(S) + for i=1:length(f) + s=struct('type', '.', 'subs', f{i}); + z=findinstruct(x,subsref(S(j),s),fun,varargin{:}); + if ~isempty(z) + if numel(S)>1 + s=[struct('type', '()', 'subs', {{j}}) s]; + end + for k=1:length(z) + y{end+1}=[s z{k}]; + end + end + end + end +else + try + if eval(fun) + y={[]}; + end + end +end + + diff --git a/findn.m b/findn.m new file mode 100644 index 0000000..4e6c057 --- /dev/null +++ b/findn.m @@ -0,0 +1,33 @@ +function ind=findn(arr); + +%FINDN Find indices of nonzero elements. +% I = FINDN(X) returns the indices of the vector X that are +% non-zero. For example, I = FINDN(A>100), returns the indices +% of A where A is greater than 100. See RELOP. +% +% This is the same as find but works for N-D matrices using +% ind2sub function +% +% It does not return the vectors as the third output arguement +% as in FIND +% +% The returned I has the indices (in actual dimensions) +% +% x(:,:,1) x(:,:,2) x(:,:,3) +% = [ 1 2 3 =[11 12 13 =[21 22 23 +% 4 5 6 14 15 16 24 25 26 +% 7 8 9] 17 18 19] 27 28 29] +% +% I=find(x==25) will return 23 +% but findn(x==25) will return 2,2,3 +% +% Also see find, ind2sub + +% Loren Shure, Mathworks Inc. improved speed on previous version of findn +% by Suresh Joel Mar 3, 2003 + +in=find(arr); +sz=size(arr); +if isempty(in), ind=[]; return; end; +[out{1:ndims(arr)}] = ind2sub(sz,in); +ind = cell2mat(out); \ No newline at end of file diff --git a/finitefun.m b/finitefun.m new file mode 100644 index 0000000..9e88328 --- /dev/null +++ b/finitefun.m @@ -0,0 +1,37 @@ +function [y,nonfinite]=finitefun(x,D,fun,varargin) +%FINITEFUN Apply a function on finite values, discarding NaN, Inf... +% [y,nonfinite]=finitefun(X,D,fun,...) apply (vectorized) function 'fun' +% along dimension D, on the finite values only in an array X +% +% If D > 0 +% Apply function along dimension D, ignoring non-finite values +% If D < 0 +% Do not include complementary dimensions of the data array if any +% nonfinite found along the given dimension (ie. discard the whole +% hyperplan) +% +% Example: +% a = cat(3,magic(5), cumsum(ones(5)));a([3 35])=[ NaN Inf ] +% finitefun(a,1,@mean) +% meannan(a,-2) +% +%See also: meannan() + +nonfinite=~isfinite(x); +dim = abs(D); +x = nd2array(x,dim); +nonfinite(any(nonfinite(:,:),2),:)=1; +if dim < 0 + dim=-dim; + otherdims = setdiff(1:ndims(x),dim); + permdims = [dim otherdims]; + nonfinite=permute(nonfinite,permdims); + nonfinite(any(nonfinite(:,:),2),:)=1; + nonfinite=ipermute(nonfinite,permdims); +end +x(nonfinite)=0; +nonfinite=double(nonfinite); +y = sum(x,dim)./(size(x,dim)-sum(nonfinite,dim)); +if nargin>1 + nonfinite=logical(nonfinite); +end \ No newline at end of file diff --git a/forcecell.m b/forcecell.m new file mode 100644 index 0000000..a600f9b --- /dev/null +++ b/forcecell.m @@ -0,0 +1,10 @@ +function [x]=forcecell(x) +% forcecell - make sure x is cell +% +% Some functions inconsistently return cell or numeric array (even native +% ones as get: get(h, 'Xdata') returns cells when h is an array of handles, +% but the same would returns a double array when h is a single handle... +if ~iscell(x) + x={x}; +end + diff --git a/fread2.m b/fread2.m new file mode 100644 index 0000000..d79f972 --- /dev/null +++ b/fread2.m @@ -0,0 +1,86 @@ +function A = fread2(file,precision,volume,selection,offset) +%FREAD2 - Optimize fread call for reading subsets of N-dimensional data +% A = fread2(FILE,PRECISION,SIZE,SUBS) reads N-dimensional binary data +% from specified file +% Inputs: +% FILE: File name or FID (from FOPEN) +% PRECISION: See help FREAD +% SIZE: a N-element vector equals to the size of the data in the file +% SUBS: a N-element cell array of the list of indices of the elemnts +% to read in the file, may be non-continuous ranges. +% +% Example +% >> fread2('data.bin','float32',[100 3 12],{ [1:50 55 6] [-2] 'all' }) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-05-12 Creation +% +% ----------------------------- Script History --------------------------------- + +error('not yet') + +switch(precision) + case {'uint8','int8','uchar','schar','char'} + f_bytes = 2; + case {'uint16','int32','short','ushort'} + f_bytes = 2; + case {'float32','single', 'float','uint32','int32','int','uint','long'} + f_bytes = 4; + case {'float64','double','uint64','int64'} + f_bytes = 8; + otherwise + precision = 'float32'; + % error('read_lena:UnknownPrecision','Unknown precision: %s -- Go through the Full monthy', precision); + % return +end +if nargin<5 + offset = 0; +end + +ndim = numel(selection); +%% Bounding box +% Compute the bounding box of the volume of data to read +range = zeros(4,ndim); +f_selection = cell(1,ndim); +for i=1:ndim + range(1:2,i)=[min(selection{i});max(selection{i})]; + f_selection{i} = selection{i}-range(1,i)+1; +end +% Line 3 of 'range' is the length of the bounding box on each dimension +% equivalent to what would be f_volume in the convtion used here +range(3,:)= range(2,:)-range(1,:)+1; +% Line 4 of 'range' is the number of elements outsidethe bounding box +range(4,:) = volume-range(3,:) +volume +%% Segments to read +cumvol = cumprod([1 volume]) +% The first segment to read starts after skipping a whole block of data +f_offset = sum(cumvol(1:end-1).*(range(1,:)-1)) +% To skip between each read +f_skip = sum(cumvol(1:end-1).*(range(4,:))) +% Extent of the segment to read +f_selection = [cumvol(1:end-2).*(range(3,1:end-1)-1)] +f_selection(1) = 1+f_selection(1); +%f_size = (1+cumsum(f_selection(1:end)))./cumprod([1 +%f_selection(1:end-1)+1]) +f_precision = sum(f_selection); + +f_size = [ f_selection(1) f_precision/f_selection(1)] + + +fid = fopen(file, 'rb'); + +fseek(fid,offset + f_offset,'bof'); +A = fread(fid,f_size,[num2str(f_precision) '*' precision], f_skip*f_bytes); +numel(A) +A = reshape(A,range(3,:)); +fclose(fid); diff --git a/fullfiles.m b/fullfiles.m new file mode 100644 index 0000000..02df11a --- /dev/null +++ b/fullfiles.m @@ -0,0 +1,41 @@ +function [f]=fullfiles(varargin) +%fullfiles - Build full filenames from parts (allow multiple path/basename/ext). +% fullfiles(D1, D2, ... , FILES) with D1 being { D1a D1b ...} idem for D2 and FILES +% will (recursively) produce a cell array of full filenames +% { D1a/D2a/FILE1 ; D1a/D2a/FILE2 ; D1a/D2b/FILE1 ; D1a/D2b/FILE2 ; ... } +% +% See: fullfile() + + +% THE FOLLOWING OPTION DOES NOT WORK YET ! + +% fullfiles(D1, D2, ... , FILES, [n1 n2]) will match the n1-th and n2-th +% arguments on a 1-by-1 basis so that: +% >> fullfiles({'a' 'b'}, 'c', {'e' 'f'}, [1 3]) +% 'a/c/e' +% 'b/c/f' +% instead of: +% 'a/c/e' +% 'a/c/f' +% 'b/c/e' +% 'b/c/f' + +if nargin<2 + f=varargin{1}; + if ischar(f) + f={f}; + end + return +end + +d=varargin{1}; +g=fullfiles(varargin{2:end}); +f=[]; +if ischar(d) + d={d}; +end +for i=1:length(d) + for j=1:length(g); + f=[ f; {fullfile(d{i}, g{j})}]; + end +end \ No newline at end of file diff --git a/geod_cluster.m b/geod_cluster.m new file mode 100644 index 0000000..1f24002 --- /dev/null +++ b/geod_cluster.m @@ -0,0 +1,218 @@ +function [GD,TC, GDbis, PCL]=geod_cluster(VC, Coord, SS) + +% function [GD, TC, GDbis, PCL] = geod_cluster(VC , Coord, SS ) +% la function geodbis est la fonction geod qui +% construit - à partir du vecteur de connectivité VC et du +% tableau Coord des coordonnées de chacune des sources (c'est le FV.vertices) - les distances géodésiques +% de chacune des sources aux graines de la liste SS. +% +% +% 'GD' sera le tableau des distances géodésiques de chacune de nos sources +% à chacune des graines +% 'TC' sera le tableau donnant les no de chacune des sur-parcelles +% auxquelles appartiennent chacune des sources +% 'GDbis' est la liste des distances (GDbis(s,1)) de chacune des sources s a sa graine la +% plus proche (GDbis(s,2)) +% PCL est la liste des sources de chacune des parcelles + + +K=size(SS,1); %nombre de graines + +nv= size(Coord, 1); % nombre de sources +TC = cell(nv,1); % la 'cell' TC sera la liste des sur-parcelles dont + % fait partie chaque source, initialisée au vide. + +Vis = zeros(nv,1); % Vis[i] indique si la source i a déjà été visitée + +PH = cell(K,1); % PH sera une structure cell de taille K x dmax x Nmax qui sera le + % tableau de "piles hierarchiques" de G. Flandin. + % Attention: dans la colonne d de PH(k) on a les + % sources à la distance d-1 (en mm) + +infty = 10000; + +GD = infty*ones(K,nv); % tableau des distances géodésiques de la source i à + % la graine k (en mm). Il est initialisé à infty, qui + % est pour nous la distance infinie (on pourrait + % plutot prendre un 'sparse' mais bon...) + +GDbis = ones(nv,2); % nous donne pour chaque source s, sa graine la plus + % proche GDbis(s,2), et la distance a cette graine GDbis(s,1) + + +PCL = cell(K,1); % liste de chacune des parcelles, ie pour la graine k les sources associees + + +GDbis(:,1)=infty*GDbis(:,1); +GDbis(:,2)=0*GDbis(:,2); + +S=SS; + +% on initialise les valeurs de nos tableaux pour nos graines + +for k=1:K, + S(k,2)=0; + TC(S(k,1))={[k]}; + GD(k,S(k,1))=0; + GDbis(S(k,1),1)=0; + GDbis(S(k,1),2)=k; + Vis(S(k,1))=1; + PH(k,1)={[S(k,1)]}; +end + + + + + +nsv=K ; % nsv indique le nombre de sources visitées, initialisé à K car + % les graines ont déjà été visitées + +d=0 ; % d est la distance à laquelle on se trouve dans nos piles hierarchiques + +while nsvS(k,2)), + S(k,2)=dist; + PH(k,dist+1)={[V]}; + else + PH(k,dist+1)={[PH{k,dist+1},V]}; + end + + + if dist20 + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},s]}; + end +end + +while Nbsourcesnonvisitees>0 + +for s=1:nv % c'est juste une boucle rajoutee car je suis tombe + % sur des sources qui 'boguaient' systematiquement + % sans comprendre pourquoi. Donc on attribue aux sources + % pas suffisamment visitees la mm parcelle que son premier + % voisin. L'indicateur 'nsf' dans le reste du programme + l=1; % sert ainsi a eviter les boucles sans fin dues + % a ces sources a probleme + + if GDbis(s,2)==0 + % s + while (GDbis(s,2)==0 & (l0 + for i=1:size(VC{s},2) + if GDbis(VC{s}(i),2)==0 + GDbis(VC{s}(i),2)=GDbis(s,2); + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},VC{s}(i)]}; + end + end + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},s]}; + end + end + +end + +I=find(GDbis(:,2)==0); +Nbsourcesnonvisitees=size(I,1); + +end + + diff --git a/geod_cluster2.m b/geod_cluster2.m new file mode 100644 index 0000000..d349de2 --- /dev/null +++ b/geod_cluster2.m @@ -0,0 +1,218 @@ +function [GD,TC, GDbis, PCL]=geod_cluster2(VC, Coord, SS, varargin) + +% function [GD, TC, GDbis, PCL] = geod_cluster2(VC , Coord, SS [, options]) +% la function geodbis est la fonction geod qui +% construit - à partir du vecteur de connectivité VC et du +% tableau Coord des coordonnées de chacune des sources (c'est le FV.vertices) - les distances géodésiques +% de chacune des sources aux graines de la liste SS. +% +% +% 'GD' sera le tableau des distances géodésiques de chacune de nos sources +% à chacune des graines +% 'TC' sera le tableau donnant les no de chacune des sur-parcelles +% auxquelles appartiennent chacune des sources +% 'GDbis' est la liste des distances (GDbis(s,1)) de chacune des sources s a sa graine la +% plus proche (GDbis(s,2)) +% PCL est la liste des sources de chacune des parcelles + +debug=1; + +K=size(SS,1); %nombre de graines + +nv= size(Coord, 1); % nombre de sources +TC = cell(nv,1); % la 'cell' TC sera la liste des sur-parcelles dont + % fait partie chaque source, initialisée au vide. + +Vis = zeros(nv,1); % Vis[i] indique si la source i a déjà été visitée + +PH = cell(K,1); % PH sera une structure cell de taille K x dmax x Nmax qui sera le + % tableau de "piles hierarchiques" de G. Flandin. + % Attention: dans la colonne d de PH(k) on a les + % sources à la distance d-1 (en mm) + +infty = 10000; + +GD = infty*ones(K,nv); % tableau des distances géodésiques de la source i à + % la graine k (en mm). Il est initialisé à infty, qui + % est pour nous la distance infinie (on pourrait + % plutot prendre un 'sparse' mais bon...) + +GDbis = ones(nv,2); % nous donne pour chaque source s, sa graine la plus + % proche GDbis(s,2), et la distance a cette graine GDbis(s,1) + + +PCL = cell(K,1); % liste de chacune des parcelles, ie pour la graine k les sources associees + + +GDbis(:,1)=infty*GDbis(:,1); +GDbis(:,2)=0*GDbis(:,2); + +S=SS; + +% on initialise les valeurs de nos tableaux pour nos graines + +for k=1:K, + S(k,2)=0; + TC(S(k,1))={[k]}; + GD(k,S(k,1))=0; + GDbis(S(k,1),1)=0; + GDbis(S(k,1),2)=k; + Vis(S(k,1))=1; + PH(k,1)={[S(k,1)]}; +end + + + + + +nsv=K ; % nsv indique le nombre de sources visitées, initialisé à K car + % les graines ont déjà été visitées + +d=0 ; % d est la distance à laquelle on se trouve dans nos piles hierarchiques + +while nsvS(k,2)), + S(k,2)=dist; + PH(k,dist+1)={[V]}; + else + PH(k,dist+1)={[PH{k,dist+1},V]}; + end + + + if dist20 + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},s]}; + end +end + +while Nbsourcesnonvisitees>0 + +for s=1:nv % c'est juste une boucle rajoutee car je suis tombe + % sur des sources qui 'boguaient' systematiquement + % sans comprendre pourquoi. Donc on attribue aux sources + % pas suffisamment visitees la mm parcelle que son premier + % voisin. L'indicateur 'nsf' dans le reste du programme + l=1; % sert ainsi a eviter les boucles sans fin dues + % a ces sources a probleme + + if GDbis(s,2)==0 + % s + while (GDbis(s,2)==0 & (l0 + for i=1:size(VC{s},2) + if GDbis(VC{s}(i),2)==0 + GDbis(VC{s}(i),2)=GDbis(s,2); + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},VC{s}(i)]}; + end + end + PCL(GDbis(s,2))={[PCL{GDbis(s,2)},s]}; + end + end + +end + +I=find(GDbis(:,2)==0); +Nbsourcesnonvisitees=size(I,1); + +end + + diff --git a/getfield2.m b/getfield2.m new file mode 100644 index 0000000..d51aafd --- /dev/null +++ b/getfield2.m @@ -0,0 +1,117 @@ +function [f,index,a] = getfield2(s,varargin) +%GETFIELD2 Get structure field contents (even for array). +% F = GETFIELD2(S,'field') returns the contents of the specified +% field. It expands the native GETFIELD to structure arrays. +% GETFIELD2(F,'field) is equivalent to the syntax F = S.field when S is a +% 1-by-1 structure. If S is NOT a 1-by-1 structure, the output is a cell +% array with the same size as S. +% +% F = GETFIELD2(S,{i,j},'field',{k}) is equivalent to the syntax +% F = S(i,j).field(k). +% +% F = GETFIELD2(S,N) retrieves the n-th field (to be used with caution!) +% See: orderfields() +% +% [F,I,A] = GETFIELD2(S,...) may output: +% I: vector of indices of S elements which had the requested field +% A: a struct array equal to the cell array [F{:}] +% +% See: GETFIELD + +% Check for sufficient inputs +if (isempty(varargin)) + error('MATLAB:GETFIELD2:DeprecatedFunction:InsufficientInputs','Not enough input arguments.') +end + +index = varargin{1}; +if iscell(s) + warning('MATLAB:GETFIELD2:Cell arrays of struct may not be supported in the future'); + sz=size(s); + s = [s{:}]; + [f,index]=getfield2(s,varargin{:}); + if numel(f) == prod(sz) + f = reshape(f,sz); + end +elseif (length(varargin)==1 && isstr(index)) + % The most common case + if any(index=='.') + [f1,f2]=strtok(index,'.'); + % strtok keeps delimiter at the beginning of f2 + % in case f1 is addressing something like : x.f(n) + paren_f1 = regexp(f1, '\(.*\)'); + if isempty(paren_f1) + if iscell(s) + + else + s = [s.(deblank(f1))]; + end + else + s = [s.(deblank(f1(1:paren_f1-1)))]; + s = eval(['s' f1(paren_f1:end)]); + end + if nargout<3 + [f,index]=getfield2(s,f2(2:end)); + else + [f,index,a]=getfield2(s,f2(2:end)); + end + return + else + if numel(s)==1 + f = s.(deblank(index)); + else + sf=size(s); + f = {s.(deblank(index))}; + f=reshape(f, sf); + end + %warning('MATLAB:GETFIELD:DeprecatedFunction:SingleInput', ... + % sprintf(['GETFIELD is deprecated. Please use: \n' ... + % 's.(fieldname) instead of getfield(s,fieldname)'])); + + end + + +else + f = s; + %warnflag = false; + for i = 1:length(varargin) + index = varargin{i}; + if (isa(index, 'cell')) + f = f(index{:}); + elseif isstr(index) + if length(f)==1 + f = f.(deblank(index)); % deblank field name + else + sf=size(f); + f = {f.(deblank(index))}; + f=reshape(f, sf); + end + %if (~warnflag) + %warning('MATLAB:GETFIELD:DeprecatedFunction:MultiInput', ... + % sprintf(['GETFIELD is deprecated. Please use: \n' ... + % 's(i,j).(fieldname)(k) instead of getfield(s,{i,j},fieldname,{k}) OR \n' ... + % 's(i,j).(field1).(field2) instead of getfield(s,{i,j},field1,field2)'])); + %warnflag = true; + %end + elseif isnumeric(index) + if numel(index)>1 + error('Only one field at a time!') + end + fn=fieldnames(s); + index=[fn{index}]; + f = f.(deblank(index)); + else + error('MATLAB:GETFIELD:DeprecatedFunction:InvalidType', 'Inputs must be either cell arrays or strings.'); + end + end +end +if nargout<3 + return +end +a = [f{:}]; +if numel(a) == numel(f) + a=reshape(a,size(f)); +else + warning('The requested field was absent in some elements of the struct array') +end +return + diff --git a/gfp.m b/gfp.m new file mode 100644 index 0000000..4b5336c --- /dev/null +++ b/gfp.m @@ -0,0 +1,6 @@ +function [g]=gfp(F) +% gfp - Global Field Power of data +% Computes global field power (ie. root-mean-square) of data +% See: rootmeansquare() +g=rootmeansquare(F); + diff --git a/globaldissimilarity.m b/globaldissimilarity.m new file mode 100644 index 0000000..874a8c6 --- /dev/null +++ b/globaldissimilarity.m @@ -0,0 +1,29 @@ +function [gd]=globaldissimilarity(F1,F2); +%globalfieldpower() - compute global dissimilarity between two fields +% +% [gd]=globaldissimilarity(F1,F2) +% F1 and F2 are two [N (N2=N1) channels]x[T samples] fields +% +% Defined in Lehman & Skandries, 1980 as: +% gd=rms(F1/rms(F1) - F2/rms(F2)); +% +% Typical use: +% >> g=globaldissimilarityd(F(:,1:end-1), F(:,2:end)) +% will give you maxima when the field abruptly change. +% +% See also: rootmeansquare() +% +% Ref: +% Lehmann D (1987): Principles of spatial analysis. In: Gevins +% AS , R?mond A , editors. Methods of analysis of brain electrical +% and magnetic signals. EEG handbook. Vol. 1. Amsterdam: Elsevier. +% +% Brandeis D, Lehmann D. Event-related potentials of the brain +% and cognitive processes: approaches and +% applications. Neuropsychologia 1986; 24: 151-168). + +gd=F1./repmat(std(F1,1,1),[ size(F1,1) 1 ])- ... + F2./repmat(std(F2,1,1),[ size(F2,1) 1 ]); +gd=std(gd,1,1); + + diff --git a/gower.m b/gower.m new file mode 100644 index 0000000..e86a16a --- /dev/null +++ b/gower.m @@ -0,0 +1,23 @@ +function Y = gower(X) +%GOWER - Gower Centered Matrix +% [Y] = gower(X) +% Y(i,j)= X(i,j) - mean(X(:,j)) - mean(X(i,:)) + mean(X(:)) + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-14 Creation +% +% ----------------------------- Script History --------------------------------- + +n=size(X); +if ~isequal(n(1), n(2:end)) + error('Squared matrix needed'); +end +n=n(1); +Y=(eye(n) - ones(n)./n)* X *(eye(n) - ones(n).he/n); diff --git a/grayhot.m b/grayhot.m new file mode 100644 index 0000000..fed7bc3 --- /dev/null +++ b/grayhot.m @@ -0,0 +1,9 @@ +function [c]=grayhot(n) +%GRAYHOT - Gray-hot colormap +% grayhot(n) returns a n-by-3 matrix +% grayhot by itself is the same length as the current colormap +if nargin<1 + n=length(colormap); +end +b=([[n:-1:1]/n]'*[1 1 1]).^(300); +c=hot(n).*(1-b*.6)+ (b*.6); \ No newline at end of file diff --git a/grayish.m b/grayish.m new file mode 100644 index 0000000..0d7e0ed --- /dev/null +++ b/grayish.m @@ -0,0 +1,37 @@ +function [cmap]=grayish(cmap,p,graycolor) +%GRAYISH - Make a colormap more gray +% [cmap2]=grayish(cmap,p,graycolor) +% Make the colors in cmap (default: current color map) to go from a +% gray color (default: .6 .6 .6) to the hues already present. The amount +% of gray-ing is given by p (default: p=1/3). Greater p make the colormap +% more gray. +% +if nargin<1 + cmap=colormap; +end +if nargin<2 + p=1/3; +end +if p==0 + return +end +if nargin<3 + graycolor=[.6 .6 .6]; +end +n=abs(p); +if n<=1 + n=round(length(cmap)*n); +end +x=linspace(0,1,n+1)'*[1 1 1]; +x(end,:)=[]; +%x=x.^(1 - min(1-sqrt(eps),abs(beta))); +if p>0 + cmap(1:n,:)=repmat(graycolor,n,1).*(1-x)+cmap(1:n,:).*x; +else + nc=length(cmap); + cmap(nc+1-[1:n],:)=repmat(graycolor,n,1).*flipud(x)+cmap(nc+1-[1:n],:).*x; +end + +return +b=([[n:-1:1]/n]'*[1 1 1]).^(300); +c=hot(n).*(1-b*.6)+ (b*.6); \ No newline at end of file diff --git a/greyish.m b/greyish.m new file mode 100644 index 0000000..f2b4633 --- /dev/null +++ b/greyish.m @@ -0,0 +1,75 @@ +function [cmap]=greyish(cmap,p,greycolor,style) +%GREYISH - Make a colormap more grey +% [cmap2]=greyish(cmap,p,greycolor) +% Make the colors in cmap (default: current color map) to go from a +% grey color (default: .6 .6 .6) to the hues already present. The amount +% of grey-ing is given by p (default: p=1/3). Greater p make the colormap +% more grey. +% +% [cmap2]=greyish(cmap,p,greycolor,style) +% style = 'bottom'(default) 'middle' 'top' + +if nargin<1 + cmap=colormap; +end +if nargin<2 || isempty(p) + p=1/3; +end +if p==0 + return +end +if nargin<3 || isempty(greycolor) + greycolor=[.6 .6 .6]; +end +if nargin<4 + style=0; +end +if ischar(style) + switch(style) + case 'bottom', style = 0 ; + case 'top', style = 1; + case 'middle', style = 0.5 ; + end +end + +if p<0 + %in earlier versions, negative p's put the grey at the top + p=-p; + style=1-style; +end +nc = size(cmap,1); +if p<=1 + n=round(nc*p); +else + n=p; +end +if style == .5 + n=(n/2); + x=linspace(0,1,ceil(n)+1)'*[1 1 1]; + x(end,:)=[]; + if size(x,1)<=n + x=[flipud(x); 0 0 0; x(2:end,:)]; + else + x=[flipud(x);x(2:end,:)]; + end +else + x=linspace(0,1,n+1)'*[1 1 1]; + x(end,:)=[]; +end +%x=x.^(1 - min(1-sqrt(eps),abs(beta))); + +if style == 0 && p > 0 + cmap(1:n,:)=repmat(greycolor,n,1).*(1-x)+cmap(1:n,:).*x; +elseif (style ==1 && p > 0) || (style == 0 && p < 0) + nc=length(cmap); + cmap(nc+1-[1:n],:)=repmat(greycolor,n,1).*flipud(x)+cmap(nc+1-[1:n],:).*x; +elseif style==.5 + i = nc*style+ceil([-(n):(n-1)]); + i=i(i>0 & i<=nc); + cmap(i,:)=repmat(greycolor,length(i),1).*(1-x)+cmap(i,:).*x; +end + + +return +b=([[n:-1:1]/n]'*[1 1 1]).^(300); +c=hot(n).*(1-b*.6)+ (b*.6); \ No newline at end of file diff --git a/groupfun.m b/groupfun.m new file mode 100644 index 0000000..c183c75 --- /dev/null +++ b/groupfun.m @@ -0,0 +1,85 @@ +function [R,uG,XG,n] = groupfun(X,G,varargin) +%GROUPFUN - Perform computation according grouping variables +% [R,uG] = groupfun(X,G,fun) +% e.g. groupfun(randn(100,1),round(rand(100,1)),'mean') +% e.g. +% +% [R,uG,XG,n] = ... also outputs: +% uG: the list of the unique values for groups +% XG: a cell array of X values split into groups +% n: number of matches for each group +% +% Example +% >> groupfun +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-11-19 Creation +% +% ----------------------------- Script History --------------------------------- +s=size(X); +if size(G,1) ~= s(1) + error('The number of line of X must match the number of lines in G') +end +if prod(s)==max(s) & numel(G)==max(s) & s(1)==1 + % Transpose + G=G'; + X=X'; + s=size(X); +end + if nargin<3 + %default: mean + varargin = {'mean' 1}; +end +[g,uG] = unicize_groups(G); +ng = size(uG,1); +n=zeros(ng,1); +R=[]; +for i=1:ng + if isnan(uG(i)) + r=X(g==i,:); + else + r = feval(varargin{1},X(g==i,:),varargin{2:end}); + if numel(r) < sum(s(2:end)) % && numel(r)~= prod(size(r)) [this was obviously true!] + error('Wrong output of function %s (maybe 1-line vector issue with sum and the like)', varargin{1}); + end + end + R(i,:) = r; + if nargout>2 || nargout==0 + n(i,1) = sum(g==i); + s(1)= n(i); + XG{i,1} = reshape(X(g==i,:),s); + end +end +s(1)=ng; +R=reshape(R,s); +if nargout==0 +<<<<<<< .mine + disp([ 'Grouping by ' inputname(2) ':']); + disp(uG) + disp(n) +======= + disp('Grouping: Result'); + for i=1:ng + disp([ sprintf2(uG(i)) ' (n=' sprintf2(n(i)) '): ' sprintf2(R(i,:)) ]); + end +>>>>>>> .r684 + if any(isnan(uG)) + disp('For NaN''s:') + disp(feval(varargin{1},X(isnan(uG(g)),:),varargin{2:end})); + end +end +return + +% Unicize groups +function [g,uG] = unicize_groups(G) +[uG,ignore,g] = unique(G, 'rows'); +return \ No newline at end of file diff --git a/groupfun.m.mine b/groupfun.m.mine new file mode 100644 index 0000000..3c81731 --- /dev/null +++ b/groupfun.m.mine @@ -0,0 +1,78 @@ +function [R,uG,XG,n] = groupfun(X,G,varargin) +%GROUPFUN - Perform computation according grouping variables +% [R,uG] = groupfun(X,G,fun) +% e.g. groupfun(randn(100,1),round(rand(100,1)),'mean') +% e.g. +% +% [R,uG,XG,n] = ... also outputs: +% uG: the list of the unique values for groups +% XG: a cell array of X values split into groups +% n: number of matches for each group +% +% Example +% >> groupfun +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-11-19 Creation +% +% ----------------------------- Script History --------------------------------- +s=size(X); +if size(G,1) ~= s(1) + error('The number of line of X must match the number of lines in G') +end +if prod(s)==max(s) & numel(G)==max(s) & s(1)==1 + % Transpose + G=G'; + X=X'; + s=size(X); +end + if nargin<3 + %default: mean + varargin = {'mean' 1}; +end +[g,uG] = unicize_groups(G); +ng = size(uG,1); +n=zeros(ng,1); +R=[]; +for i=1:ng + if isnan(uG(i)) + r=X(g==i,:); + else + r = feval(varargin{1},X(g==i,:),varargin{2:end}); + if numel(r) < sum(s(2:end)) % && numel(r)~= prod(size(r)) [this was obviously true!] + error('Wrong output of function %s (maybe 1-line vector issue with sum and the like)', varargin{1}); + end + end + R(i,:) = r; + if nargout>2 || nargout==0 + n(i,1) = sum(g==i); + s(1)= n(i); + XG{i,1} = reshape(X(g==i,:),s); + end +end +s(1)=ng; +R=reshape(R,s); +if nargout==0 + disp([ 'Grouping by ' inputname(2) ':']); + disp(uG) + disp(n) + if any(isnan(uG)) + disp('For NaN''s:') + disp(feval(varargin{1},X(isnan(uG(g)),:),varargin{2:end})); + end +end +return + +% Unicize groups +function [g,uG] = unicize_groups(G) +[uG,ignore,g] = unique(G, 'rows'); +return \ No newline at end of file diff --git a/groupfun.m.r565 b/groupfun.m.r565 new file mode 100644 index 0000000..1be30e5 --- /dev/null +++ b/groupfun.m.r565 @@ -0,0 +1,74 @@ +function [R,uG,XG,n] = groupfun(X,G,varargin) +%GROUPFUN - Perform computation according grouping variables +% [R,uG] = groupfun(X,G,fun) +% e.g. groupfun(randn(100,1),round(rand(100,1)),'mean') +% e.g. +% +% [R,uG,XG,n] = ... also outputs: +% uG: the list of the unique values for groups +% XG: a cell array of X values split into groups +% n: number of matches for each group +% +% Example +% >> groupfun +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-11-19 Creation +% +% ----------------------------- Script History --------------------------------- +s=size(X); +if size(G,1) ~= s(1) + error('The number of line of X must match the number of lines in G') +end +if prod(s)==max(s) & numel(G)==max(s) & s(1)==1 + % Transpose + G=G'; + X=X'; + s=size(X); +end + if nargin<3 + %default: mean + varargin = {'mean' 1}; +end +[g,uG] = unicize_groups(G); +ng = length(uG); +n=zeros(ng,1); +R=[]; +for i=1:ng + r = feval(varargin{1},X(g==i,:),varargin{2:end}); + if numel(r) < sum(s(2:end)) % && numel(r)~= prod(size(r)) [this was obviously true!] + error('Wrong output of function %s (maybe 1-line vector issue with sum and the like)', varargin{1}); + end + R(i,:) = r; + if nargout>2 || nargout==0 + n(i,1) = sum(g==i); + s(1)= n(i); + XG{i,1} = reshape(X(g==i,:),s); + end +end +s(1)=ng; +R=reshape(R,s); +if nargout==0 + disp('Grouping:'); + disp(uG) + disp(n) + if any(isnan(uG)) + disp('For NaN''s:') + disp(feval(varargin{1},X(isnan(uG(g)),:),varargin{2:end})); + end +end +return + +% Unicize groups +function [g,uG] = unicize_groups(G) +[uG,ignore,g] = unique(G, 'rows'); +return \ No newline at end of file diff --git a/groupfun.m.r684 b/groupfun.m.r684 new file mode 100644 index 0000000..8eecda9 --- /dev/null +++ b/groupfun.m.r684 @@ -0,0 +1,75 @@ +function [R,uG,XG,n] = groupfun(X,G,varargin) +%GROUPFUN - Perform computation according grouping variables +% [R,uG] = groupfun(X,G,fun) +% e.g. groupfun(randn(100,1),round(rand(100,1)),'mean') +% e.g. +% +% [R,uG,XG,n] = ... also outputs: +% uG: the list of the unique values for groups +% XG: a cell array of X values split into groups +% n: number of matches for each group +% +% Example +% >> groupfun +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-11-19 Creation +% +% ----------------------------- Script History --------------------------------- +s=size(X); +if size(G,1) ~= s(1) + error('The number of line of X must match the number of lines in G') +end +if prod(s)==max(s) & numel(G)==max(s) & s(1)==1 + % Transpose + G=G'; + X=X'; + s=size(X); +end + if nargin<3 + %default: mean + varargin = {'mean' 1}; +end +[g,uG] = unicize_groups(G); +ng = length(uG); +n=zeros(ng,1); +R=[]; +for i=1:ng + r = feval(varargin{1},X(g==i,:),varargin{2:end}); + if numel(r) < sum(s(2:end)) % && numel(r)~= prod(size(r)) [this was obviously true!] + error('Wrong output of function %s (maybe 1-line vector issue with sum and the like)', varargin{1}); + end + R(i,:) = r; + if nargout>2 || nargout==0 + n(i,1) = sum(g==i); + s(1)= n(i); + XG{i,1} = reshape(X(g==i,:),s); + end +end +s(1)=ng; +R=reshape(R,s); +if nargout==0 + disp('Grouping: Result'); + for i=1:ng + disp([ sprintf2(uG(i)) ' (n=' sprintf2(n(i)) '): ' sprintf2(R(i,:)) ]); + end + if any(isnan(uG)) + disp('For NaN''s:') + disp(feval(varargin{1},X(isnan(uG(g)),:),varargin{2:end})); + end +end +return + +% Unicize groups +function [g,uG] = unicize_groups(G) +[uG,ignore,g] = unique(G, 'rows'); +return \ No newline at end of file diff --git a/hash.m b/hash.m new file mode 100644 index 0000000..bfc4450 --- /dev/null +++ b/hash.m @@ -0,0 +1,79 @@ +function h = hash(inp,meth) +% HASH - Convert an input variable into a message digest using any of +% several common hash algorithms +% +% USAGE: h = hash(inp,'meth') +% +% inp = input variable, of any of the following classes: +% char, uint8, logical, double, single, int8, uint8, +% int16, uint16, int32, uint32, int64, uint64 +% h = hash digest output, in hexadecimal notation +% meth = hash algorithm, which is one of the following: +% MD2, MD5, SHA-1, SHA-256, SHA-384, or SHA-512 +% +% NOTES: (1) If the input is a string or uint8 variable, it is hashed +% as usual for a byte stream. Other classes are converted into +% their byte-stream values. In other words, the hash of the +% following will be identical: +% 'abc' +% uint8('abc') +% char([97 98 99]) +% The hash of the follwing will be different from the above, +% because class "double" uses eight byte elements: +% double('abc') +% [97 98 99] +% You can avoid this issue by making sure that your inputs +% are strings or uint8 arrays. +% (2) The name of the hash algorithm may be specified in lowercase +% and/or without the hyphen, if desired. For example, +% h=hash('my text to hash','sha256'); +% (3) Carefully tested, but no warranty. Use at your own risk. +% (4) Michael Kleder, Nov 2005 +% +% EXAMPLE: +% +% algs={'MD2','MD5','SHA-1','SHA-256','SHA-384','SHA-512'}; +% for n=1:6 +% h=hash('my sample text',algs{n}); +% disp([algs{n} ' (' num2str(length(h)*4) ' bits):']) +% disp(h) +% end + +inp=inp(:); +% convert strings and logicals into uint8 format +if ischar(inp) || islogical(inp) + inp=uint8(inp); +else % convert everything else into uint8 format without loss of data + inp=typecast(inp,'uint8'); +end + +% verify hash method, with some syntactical forgiveness: +meth=upper(meth); +switch meth + case 'SHA1' + meth='SHA-1'; + case 'SHA256' + meth='SHA-256'; + case 'SHA384' + meth='SHA-384'; + case 'SHA512' + meth='SHA-512'; + otherwise +end +algs={'MD2','MD5','SHA-1','SHA-256','SHA-384','SHA-512'}; +if isempty(strmatch(meth,algs,'exact')) + error(['Hash algorithm must be ' ... + 'MD2, MD5, SHA-1, SHA-256, SHA-384, or SHA-512']); +end + +% create hash +x=java.security.MessageDigest.getInstance(meth); +x.update(inp); +h=typecast(x.digest,'uint8'); +h=dec2hex(h)'; +if(size(h,1))==1 % remote possibility: all hash bytes < 128, so pad: + h=[repmat('0',[1 size(h,2)]);h]; +end +h=lower(h(:)'); +clear x +return \ No newline at end of file diff --git a/headplot2.m b/headplot2.m new file mode 100644 index 0000000..1b0bf2a --- /dev/null +++ b/headplot2.m @@ -0,0 +1,797 @@ +% headplot() - plot a spherically-splined EEG field map on a semi-realistic +% 3-D head model. Rotate head using left mouse button. +% Example: +% >> headplot example - show an example spherical 'eloc_angles' file +% >> headplot cartesian - show an example cartesian 'eloc_angles' file +% +% Usage (do once): +% >> headplot('setup',['eloc_angles'],['splinefile'],['comment'],['type']) +% +% Inputs: +% 'eloc_angles' - file of electrode locations in spherical (or cartesian) coords. +% cf. functions: cart2topo() and topo2sph() +% 'splinefile' - name of spline file to save splining info into +% 'comment' - optional string vector containing info for spline file +% 'type' - type of electrode location file ('cartesian' or default +% 'spherical') +% +% General usage: +% >> headplot(values,'spline_file','Param','Value',...) +% +% Inputs: +% values - vector containing value at each electrode position +% 'spline_file' - spline filename computed and saved by running 'setup' +% +% Optional Parameters: +% 'title' - Plot title {default none} +% 'electrodes' - 'on'|'off' -> show electrode positions {default 'on'} +% 'labels' - 2 -> plot stored electrode labels; +% 1 -> plot channel numbers; 0 -> no labels {default} +% 'cbar' - 0 -> Plot colorbar {default: no colorbar} +% H -> Colorbar axis handle (e.g., choose location) +% 'view' - Camera viewpoint in deg. [azimuth elevation] +% 'back'|'b'=[ 0 30]; 'front'|'f'=[180 30] +% 'left'|'l'=[-90 30]; 'right'|'r'=[ 90 30]; +% 'frontleft'|'bl','backright'|'br', etc., +% 'top'=[0 90] {default [143 18]} +% 'maplimits' - 'absmax' -> make limits +/- the absolute-max +% 'maxmin' -> scale to data range +% [min,max] -> user-definined values +% {default = 'absmax'; red +, blue -, green 0} +% 'lights' - (3,N) matrix whose rows give x,y,z pos. of +% N lights {default: 4 lights at corners} +% 'lighting' - 'off' = show wire frame {default 'on'} +% 'colormap' - 3-column colormap matrix {default jet(64)} +% 'verbose' - 'off' -> no msgs, no rotate3d {default 'on'} +% +% Note: if an error is generated, headplot may close the current figure +% +% Authors: Colin Humphries & Scott Makeig, SCCN/INC/UCSD, La Jolla, 1998 + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Copyright (C) Colin Humphries and Scott Makeig, CNL / Salk Institute, Feb. 1998 +% +% Spherical spline method: Perrin et al. (1989) Electroenceph clin Neurophys +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: headplot.m,v $ +% Revision 1.17 2003/08/02 00:24:10 scott +% nothing +% +% Revision 1.16 2002/11/26 19:42:24 arno +% /2 to sqrt in extentricity calculation (thanks to Tyler Lorig) +% +% Revision 1.15 2002/11/19 20:08:28 arno +% allowing ascii and binary read of mhead +% +% Revision 1.14 2002/11/19 19:45:09 arno +% back to original +% +% Revision 1.13 2002/11/19 19:34:00 arno +% mhead.dat -> mhead +% +% Revision 1.12 2002/11/19 19:30:37 arno +% mhead -> mhead.dat +% +% Revision 1.11 2002/11/19 19:29:59 arno +% mhead.mat -> mhead for windows compatibility +% +% Revision 1.10 2002/10/23 19:21:24 arno +% fixing division error +% +% Revision 1.9 2002/10/23 19:01:51 arno +% nothing +% +% Revision 1.8 2002/10/23 17:19:10 arno +% cleaning up, removing ls for windows +% +% Revision 1.7 2002/10/23 17:06:26 arno +% saving syntax change for windows +% +% Revision 1.6 2002/10/23 16:52:23 arno +% testing +% +% Revision 1.5 2002/08/27 00:35:39 arno +% closing current figure +% +% Revision 1.4 2002/08/14 16:48:54 arno +% remove ICADIR +% +% Revision 1.3 2002/07/25 18:24:08 arno +% debugging +% +% Revision 1.2 2002/04/17 20:56:14 arno +% changing XYZ coordinate transformation for eloc structure +% +% Revision 1.1 2002/04/05 17:36:45 jorn +% Initial revision +% + +% 12-12-98 changed electrode label lines to MarkerColor -sm +% 12-12-98 added colorbar option -sm (still graphically marred by tan rect.) +% 12-13-98 implemented colorbar option using enhanced cbar -sm +% 12-13-98 implemented 'setup' comment option -sm +% 03-20-00 added cartesian electrode locations option -sm +% 07-14-00 fixed line in calgx() -sm from -ch +% 03-23-01 documented 'cartesian' locfile option -sm +% 01-25-02 reformated help & license, added links -ad +% 03-21-02 added readlocs and the use of eloc input structure -ad + +function [] = headplot(values,arg1,p1,v1,p2,v2,p3,v3,p4,v4,p5,v5,p6,v6) + +if nargin < 1 + help headplot + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%% Set Defaults %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% icadefs % load definitions +BACKCOLOR = [.93 .96 1]; % Background figure color + +set(gca,'Color',BACKCOLOR); +% mesh_file = [ICADIR '/newupper.mat']; % whole head model file (183K) +% mesh_file = ['mhead.mat']; % upper head model file (987K) +mesh_file = ['head1.mat'] + +Lighting = 'on'; +Maplimits = 'absmax'; +Lights = [-125 125 80; ... + 125 125 80; ... + 125 -125 125; ... + -125 -125 125]; % default lights at four corners + +View = [143 18]; % default viewpoint +Colorbar = 0; % default no colorbar (Note: has tan top - bug) +ColorbarAxes = 0; + +HeadCenter = [0 0 30]; % Center ?? + + +Cmap = jet(64); % default colormap +FaceColor = [.8 .55 .35]*1.1; % ~= ruddy Caucasian - pick your complexion! +Electrodes = 'on'; % show electrode positions by default +MAX_ELECTRODES = 1024; +Elecnums = 0; % 0 is 'off; 1 is 'on' +Elecnames = 0; % 0 is 'off; 1 is 'on' +ElectDFac = 1.06; % plot electrode marker dots out from head surface +NamesDFac = 1.05; % plot electrode names/numbers out from markers +NamesColor = 'k'; % 'r'; +NamesSize = 10; % FontSize for electrode names +MarkerColor= 'k'; + +sqaxis = 1; % if non-zero, make head proportions anatomical +title_font = 18; +titl = []; +verbose = 'on'; +if isstr(values) + values = lower(values); + if strcmp(values,'setup') + % + %%%%%%%%%%%%%%%%%%% Perform splining file setup %%%%%%%%%%%%%%%%%%%%%%%%%%%% + % + if nargin<3|nargin>5 + error(['headplot(): setup requires 3-5 arguments.\n']) + end + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Compute and save splining matrix for the electrode array + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + fprintf('Setting up splining matrix.\n'); + + eloc_file = arg1; + if nargin==5 + loctype = p2; + else + loctype = 'spherical'; + end + spline_file = p1; + if nargin >= 4 + comment = v1; + end + %%%%%%%%%%%%%%%%%%%%%%%%%%% + % Open electrode file + %%%%%%%%%%%%%%%%%%%%%%%%%%% + if isstr(eloc_file) + + if strcmp(loctype,'spherical') + [a,b,c, s]=textread(eloc_file, '%d %f %f %s'); + A=[a b c]; + ElectrodeNames=char(s); + elseif strcmp(loctype,'cartesian') + [a,x,y,z, s]=textread(eloc_file, '%d %f %f %f %s'); + A=[a x y z]; + ElectrodeNames=char(s); + else + error(['headplot: unknown electrode location file type.\n']); + end + if 0 % OLD THING WITH dot in EEGnames etc ! + fid = fopen(eloc_file); + if fid == -1 + error(['headplot(): Error opening file: ',eloc_file]) + end + if strcmp(loctype,'spherical') + A = fscanf(fid,'%d %f %f %s',[7 MAX_ELECTRODES]); + elseif strcmp(loctype,'cartesian') + A = fscanf(fid,'%d %f %f %f %s',[8 MAX_ELECTRODES]); + else + error(['headplot: unknown electrode location file type.\n']); + end + fclose(fid); + fprintf(['Electrode file ',eloc_file,' opened.\n']) + A = A'; + fprintf('Location data for %d electrodes read.\n',size(A,1)); + + %%%%%%%%%%%%%%%%%%%%%%%%%%% + % Record ElectrodeNames + %%%%%%%%%%%%%%%%%%%%%%%%%%% + ElectrodeNames = zeros(size(A,1),4); + for r = 1:size(ElectrodeNames,1) + if strcmp(loctype,'spherical') + ElectrodeNames(r,:) = sprintf('%s',A(r,4:7)); + elseif strcmp(loctype,'cartesian') + ElectrodeNames(r,:) = sprintf('%s',A(r,5:8)); + end + for c=1:4 + if ElectrodeNames(r,c) == '.' + ElectrodeNames(r,c) = ' '; + end + end + if ElectrodeNames(r,3)== ' ' & ElectrodeNames(r,4)== ' ' + ElectrodeNames(r,[2 3]) = ElectrodeNames(r,[1 2]); + ElectrodeNames(r,1) = ' '; % move 1|2-letter label to center + end + end + end % That was the old thing + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Convert from spherical coords to Cartesian + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if strcmp(loctype,'spherical') + Th = pi/180*A(:,2); + Phi = pi/180*A(:,3); + Xe = cos(Th).*cos(Phi); + Ye = sin(Th).*cos(Phi); + Ze = sin(Phi); + elseif strcmp(loctype,'cartesian') + Xe = A(:,2); + Ye = A(:,3); + Ze = A(:,4); + dists = sqrt(Xe.^2+Ye.^2+Ze.^2); + Xe = Xe./dists; + Ye = Ye./dists; + Ze = Ze./dists; + end + else + %%%%%%%%%%%%%%%%%%%%% + % Electrode structure + %%%%%%%%%%%%%%%%%%%%% + if ~isfield(eloc_file, 'X') | isempty(eloc_file(1).X) % no X Y Z coordinates + [tmp labels Th Rd] = readlocs(eloc_file); + ElectrodeNames = strvcat(labels); + labels = strvcat(labels); + [Phi Th] = topo2sph( [Th(:) Rd(:)]); + Th = pi/180*Th; + Phi = pi/180*Phi; + [Xe Ye Ze] = sph2cart( Th, Phi, ones(size(Th))); + fprintf('Headplot: generating XYZ coordinates from polar coordinates\n'); + dists = sqrt(Xe.^2+Ye.^2+Ze.^2); + Xe = Xe./dists; + Ye = Ye./dists; + Ze = Ze./dists; + else + fprintf('Headplot: using existing XYZ coordinates\n'); + ElectrodeNames = strvcat({ eloc_file.labels }); + Xe = cell2mat( { eloc_file.X } )'; + Ye = cell2mat( { eloc_file.Y } )'; + Ze = cell2mat( { eloc_file.Z } )'; + dists = sqrt(Xe.^2+Ye.^2+Ze.^2); + Xe = Xe./dists; + Ye = Ye./dists; + Ze = Ze./dists; + end; + Xetmp = Xe; + Xe = -Ye; + Ye = Xetmp; + end; + Xe = Xe(:); + Ye = Ye(:); + Ze = Ze(:); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Calculate g(x) for electrodes + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + enum = length(Xe); + onemat = ones(enum,1); + G = zeros(enum,enum); + for i = 1:enum + ei = onemat-sqrt((Xe(i)*onemat-Xe).^2 + (Ye(i)*onemat-Ye).^2 + ... + (Ze(i)*onemat-Ze).^2); % default was /2 and no sqrt + %ei = onemat-((Xe(i)*onemat-Xe).^2 + (Ye(i)*onemat-Ye).^2 + ... + % (Ze(i)*onemat-Ze).^2)/2; + gx = zeros(1,enum); + for j = 1:enum + gx(j) = calcgx(ei(j)); + end + G(i,:) = gx; + end + fprintf('Calculating splining matrix...\n') + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Open mesh file - contains POS and index1 + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if ~exist(mesh_file) + fprintf('headplot(): mesh_file "%s" not found.\n',mesh_file); + fprintf(' Change file name in headplot.m.\n'); + return + end + try, eval(['load ',mesh_file,' -mat']); + catch, + POS = load('mheadpos.txt', '-ascii'); + TRI1 = load('mheadtri1.txt', '-ascii'); + TRI2 = load('mheadtri2.txt', '-ascii'); + index1 = load('mheadindex1.txt', '-ascii'); + center = load('mheadcenter.txt', '-ascii'); + end; + fprintf('Loaded mesh file %s\n',mesh_file); + newPOS = POS(index1,:); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Project head vertices onto unit sphere + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + nPOS = newPOS-ones(size(newPOS,1),1)*HeadCenter; + spherePOS = sqrt(ones./(sum((nPOS.*nPOS)')))'*ones(1,3).*nPOS; + x = spherePOS(:,1); + y = spherePOS(:,2); + z = spherePOS(:,3); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Calculate new electrode positions + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + fprintf('Computing electrode locations on head...\n'); + for i=1:length(Xe) + elect = [Xe(i) Ye(i) Ze(i)]; + dists = distance(elect,spherePOS'); + [S,I] = sort(dists); + npoints = I(1:3); + diffe = newPOS(npoints,:)-spherePOS(npoints,:); + newElect(i,:) = elect+mean(diffe)*ElectDFac; + if Ze(i) < -1 % WAS 0 !!!! % HeadCenter(3) ???? + newElect(i,:) = [0 0 0]; % mark as electrode position not to be plotted + end + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Calculate g(x) for sphere mesh vertices + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + fprintf('Computing %d vertices. Should take a while (see wait bar)\n',... + length(x)) + fprintf(' but doesnt have to be done again for this montage...\n'); + hwb = waitbar(0,'Computing spline file (percent done)...'); + + %figure; plot3(x (:), y(:), z(:), '.' ); + %figure; plot3(Xe(:), Ye(:), Ze(:), '.' ); + hwbend = length(x); + for j = 1:length(x) + % fprintf('%d ',j) + X = x(j); + Y = y(j); + Z = z(j); + ei = onemat-sqrt((X*onemat-Xe).^2 + (Y*onemat-Ye).^2 + (Z*onemat-Ze).^2); %default /2 no sqrt + %ei = onemat-((X*onemat-Xe).^2 + (Y*onemat-Ye).^2 + (Z*onemat-Ze).^2)/2; + for i = 1:length(ei) + gx(j,i) = calcgx(ei(i)); + end + waitbar(j/hwbend) + end + close(hwb) + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Save spline file + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + fprintf('Saving (587k) file %s\n',spline_file); + if nargin == 3 + save(spline_file, '-mat', 'Xe', 'Ye', 'Ze', 'G', 'gx', 'newElect', 'ElectrodeNames'); + else + save(spline_file, '-mat', 'Xe', 'Ye', 'Ze', 'G', 'gx', 'newElect', 'ElectrodeNames', 'comment'); + end; + return + + elseif strcmp(values,'example') | strcmp(values,'demo') + % + %%%%%%%%%%%%%%%%%% Show an example electrode angles file %%%%%%%%%%%%%%%%%%%%%%%% + % + fprintf(['\nExample of a headplot() electrode angles file (spherical coords.)\n',... + 'Fields: chan_num cor_deg horiz_deg channel_name\n\n',... + ' 1 -90 -72 Fp1.\n',... + ' 2 90 72 Fp2.\n',... + ' 3 -62 -57 F3..\n',... + ' 4 62 57 F4..\n',... + ' 5 -45 0 C3..\n',... + ' 6 45 0 C4..\n',... + ' 7 -118 2 A1..\n',... + ' 8 118 -2 A2..\n',... + ' 9 -62 57 P3..\n',... + ' 10 62 -57 P4..\n',... + ' 11 -90 72 O1..\n',... + ' 12 90 -72 O2..\n',... + ' 13 -90 -36 F7..\n',... + ' 14 90 36 F8..\n',... + ' 15 -90 0 T3..\n',... + ' 16 90 0 T4..\n',... + ' 17 -90 36 T5..\n',... + ' 18 90 -36 T6..\n',... + ' 19 45 90 Fz..\n',... + ' 20 0 0 Cz..\n',... + ' 21 45 -90 Pz..\n',... + '\nA 90 deg coronal rotation points to right ear, -90 to left.\n' ,... + 'A positive horizontal rotation is counterclockwise from above.\n',... + 'Use pol2sph() to convert from topoplot() format to spherical.\n',... + 'Channel names should have 4 chars (. = space).\n\n\n']); + return + elseif strcmp(values,'cartesian') + % + %%%%%%%%%%%%%%%%%% Show an example cartesian electrode file %%%%%%%%%%%%%%%%%%% + % + fprintf(['\nExample of a headplot() electrode location file (cartesian coords.)\n',... + 'Fields: chan_num x y z channel_name\n\n',... + ' 1 0.4528 0.8888 -0.0694 Fp1.\n',... + 'Channel names should have 4 chars (. = space).\n\n\n']); + return + else + fprintf('headplot(): Unknown first argument (%s).\n',values) + help headplot + end +else + % + %%%%%%%%%%%%%%%%%%%%%%%%%% Make the plot %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % + if nargin < 2 + help headplot + return + end + spline_file = arg1; + nargs = nargin; + if nargs > 2 + if ~(floor(nargs/2) == nargs/2) + error('headplot(): Cannot have an odd number of inputs.') + end + for i = 3:2:nargs + Param = eval(['p',int2str((i-3)/2 +1)]); + Value = eval(['v',int2str((i-3)/2 +1)]); + if ~isstr(Param) + error('headplot(): Parameters must be strings.') + end + switch lower(Param) + case 'cbar' + if isstr(Value) + error('headplot(): Colorbar value must be 0 or axis handle.') + end + Colorbar = 1; + if size(Value,1) == 1 & size(Value,2) == 1 + ColorbarAxes = 0; + else + ColorbarAxes = Value; + end + case 'lighting' + if ~isstr(Value) + close; error('headplot(): Lighting value must be on or off.') + end + Value = lower(Value); + if ~strcmp(Value,'on') & ~strcmp(Value,'off') + close; error('headplot(): Lighting value must be on or off.') + end + Lighting = lower(Value); + case 'maplimits' + Maplimits = Value; + case 'title' + titl = Value; + case 'lights' + Lights = Value; + if size(Lights,2) ~= 3 + close; error('headplot(): Light matrix must be (3,N).') + end + case 'view' + View = Value; + case 'verbose' + if ~isstr(Value) + close; error('headplot(): verbose value must be on or off.') + end + Value = lower(Value); + if ~strcmp(Value,'on') & ~strcmp(Value,'off') + close; error('headplot(): verbose value must be on or off.') + end + verbose = Value; + case {'colormap','cmap'} + if size(Value,2) ~= 3 + close; error('Colormap must be an n x 3 matrix.') + end + Cmap = Value; + case {'electrodes','elec'} + if ~isstr(Value) + close; error('headplot(): electrodes value must be on or off.') + elseif ~strcmp(Value,'on') & ~strcmp(Value,'off') + close; error('headplot(): electrodes value must be on or off.') + end + Electrodes = Value; + case 'labels' + if isstr(Value) + close; error(['headplot(): labels value must be 0, 1, or 2.']) + end + if Value>2 | Value<0 + close; error(['headplot(): labels value must be 0, 1, or 2.']) + end + if Value == 1 + Elecnums = 1; + elseif Value == 2 + Elecnames = 1; + end + case 'facecolor' + FaceColor=Value; + otherwise + fprintf('headplot(): Unknown Parameter %s\n',Param) + return + end + end + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Open head mesh and electrode spline files + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + if ~exist(spline_file) + fprintf(... + 'headplot(): spline_file "%s" not found. Run headplot in "setup" mode.\n',... + spline_file); + return + end + eval(['load ',spline_file, ' -mat']) + + if ~exist(mesh_file) + close; + error(['headplot(): head mesh file ',mesh_file,... + ' not found.\n Change file name in headplot.m.\n']) + end + try, eval(['load ',mesh_file,' -mat']) + catch, + POS = load('mheadpos.txt', '-ascii'); + TRI1 = load('mheadtri1.txt', '-ascii'); + TRI2 = load('mheadtri2.txt', '-ascii'); + index1 = load('mheadindex1.txt', '-ascii'); + center = load('mheadcenter.txt', '-ascii'); + end; + + %KND + POS=rotation(POS, [0,0,0], [0 1 0] , -30); + + enum = length(values); + if enum ~= length(Xe) + close; + error(['headplot(): Number of values in spline file should equal number of electrodes.']) + end + + %%%%%%%%%%%%%%%%%%%%%%%%%% + % Perform interpolation + %%%%%%%%%%%%%%%%%%%%%%%%%% + + meanval = mean(values); + values = values - meanval; + onemat = ones(enum,1); + lamd = 0.1; + C = pinv([(G + lamd);ones(1,enum)])*[values(:);0]; % fixing division error + P = zeros(1,size(gx,1)); + for j = 1:size(gx,1) + P(j) = dot(C,gx(j,:)); + end + P = P + meanval; + + %%%%%%%%%%%%%%%%%%%%%%%%%% + % Plot surfaces + %%%%%%%%%%%%%%%%%%%%%%%%%% + cla % clear axis + HeadAxes = gca; + + W = zeros(1,size(POS,1)); + m = size(Cmap,1); + if size(Maplimits) == [1,2] + amin = Maplimits(1); + amax = Maplimits(2); + elseif strcmp(Maplimits,'maxmin') | strcmp(Maplimits,'minmax') + amin = min(min(abs(P)))*1.02; % 2% shrinkage keeps within color bounds + amax = max(max(abs(P)))*1.02; + elseif strcmp(Maplimits,'absmax') + amin = -max(max(abs(P)))*1.02; % 2% shrinkage keeps within color bounds + amax = -amin; + end + idx = min(m,round((m-1)*(P-amin)/(amax-amin))+1); % get colormap indices + W(index1) = idx; + colormap(Cmap) + p1 = patch('Vertices',POS,'Faces',TRI1,'FaceVertexCdata',W(:),... + 'FaceColor','interp'); %%%%%%%%% plot scalp map %%%%%%%%% + + FCmap = [Cmap; Cmap(end,:); FaceColor; FaceColor; FaceColor]; + colormap(FCmap) + W = ones(1,size(POS,1))*(m+2); + p2 = patch('Vertices',POS,'Faces',TRI2,'FaceColor','interp',... + 'FaceVertexCdata',W(:)); %%%%%%%% plot face and lower head %%%%%% + + axis([-125 125 -125 125 -125 125]) + axis off % hide axis frame + + %%%%%%%%%%%%%%%%%%%%%%%%% + % Draw colorbar - Note: uses enhanced cbar() function by Colin Humphries + %%%%%%%%%%%%%%%%%%%%%%%%% + if Colorbar==1 + BACKCOLOR = get(gcf,'Color'); + if ColorbarAxes == 0 + ColorbarHandle = cbar(0,3,[amin amax]); + else + ColorbarHandle = cbar(ColorbarAxes,3,[amin amax]); + end + pos = get(ColorbarHandle,'position'); % move left & shrink to match head size + set(ColorbarHandle,'position',[pos(1)-.05 pos(2)+0.13 pos(3)*0.7 pos(4)-0.26]); + end + axes(HeadAxes); + + %%%%%%%%%%%%%%%%%%%%%%%%% + % Turn on lights + %%%%%%%%%%%%%%%%%%%%%%%%% + + if strcmp(Lighting,'on') + set([p1 p2],'EdgeColor','none') + + for i = 1:size(Lights,1) + hl(i) = light('Position',Lights(i,:),'Color',[1 1 1],... + 'Style','infinite'); + end + set(p2,'DiffuseStrength',.6,'SpecularStrength',0,... + 'AmbientStrength',.4,'SpecularExponent',5) + set(p1,'DiffuseStrength',.6,'SpecularStrength',0,... + 'AmbientStrength',.3,'SpecularExponent',5) + lighting phong % all this gives a matte reflectance + end + + %%%%%%%%%%%%%%%%%%%%%%%%% + % Set viewpoint + %%%%%%%%%%%%%%%%%%%%%%%%% + + if isstr(View) + switch lower(View) + case {'front','f'} + view(-180,30) + case {'back','b'} + view(0,30) + case {'left','l'} + view(-90,30) + case {'right','r'} + view(90,30) + case {'frontright','fr'} + view(135,30) + case {'backright','br'} + view(45,30) + case {'frontleft','fl'} + view(-135,30) + case {'backleft','bl'} + view(-45,30) + case 'top' + view(0,90) + case 'bottom' % undocumented option! + view(0,-90) + Lights = [-125 125 80; ... + 125 125 80; ... + 125 -125 125; ... + -125 -125 125; ... + 0 10 -80]; % add light from below! + otherwise + close; error(['headplot(): Invalid View value %s',View]) + end + else + if ~isstr(View) + [h,a] = size(View); + if h~= 1 | a~=2 + close; error('headplot(): View matrix size must be (1,2).') + end + end + view(View) % set camera viewpoint + end + + if strcmp(Electrodes,'on') % plot the electrode locations + if exist('newElect') + newNames = newElect*NamesDFac; % Calculate electrode label positions + if Elecnames | Elecnums + LineColor = MarkerColor; % 'y'; + else + LineColor = MarkerColor; + end + for i = 1:size(newElect,1) + if newElect(i,:) ~= [0 0 0] % plot radial lines to electrode sites + line([newElect(i,1) HeadCenter(1)],[newElect(i,2) HeadCenter(2)],... + [newElect(i,3) HeadCenter(3)],'color',LineColor,'linewidth',1); + + if Elecnums % plot electrode numbers + t=text(newNames(i,1),newNames(i,2),newNames(i,3),int2str(i)); + set(t,'Color',NamesColor,'FontSize',NamesSize,'FontWeight','bold',... + 'HorizontalAlignment','center'); + + elseif Elecnames % plot electrode names + if exist('ElectrodeNames') + name = sprintf('%s',ElectrodeNames(i,:)); + t=text(newNames(i,1),newNames(i,2),newNames(i,3),name); + set(t,'Color',NamesColor,'FontSize',NamesSize,'FontWeight','bold',... + 'HorizontalAlignment','center'); + else + fprintf('Variable ElectrodeNames not read from spline file.\n'); + end + else % plot electrode markers + line(newElect(:,1),newElect(:,2),newElect(:,3),'marker',... + '.','markersize',20,'color',MarkerColor,'linestyle','none'); + end + end + end + else + fprintf('Variable newElect not read from spline file.\n'); + end + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Turn on rotate3d, allowing rotation of the plot using the mouse + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + if strcmp(verbose,'on') + rotate3d on; % Allow 3-D rotation of the plot by dragging the + else % left mouse button while cursor is on the plot + rotate3d off + end + % Make axis square + if sqaxis + axis image % keep the head proportions human and as large as possible + end + % Add a plot title + if ~isempty(titl); + % title(['\n' titl],'fontsize',title_font); + title([titl],'fontsize',title_font); % Note: \n not interpreted by matlab-5.2 + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% calcgx() - function used in 'setup' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [out] = calcgx(in) + +out = 0; +m = 4; % 4th degree Legendre polynomial +for n = 1:7 % compute 7 terms + L = legendre(n,in); + % out = out + ((2*n+1)/n^m*(n+1)^m)*L(1) ; + out = out + ((2*n+1)/(n^m*(n+1)^m))*L(1) ; % bug fix by Colin 7/00 +end +out = out/(4*pi); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% distance() - function used in 'setup' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [out] = distance(w,p) +% w is a matrix of row vectors +% p is a matrix of column vectors + +l1 = size(w,1); +l2 = size(p,2); +out = zeros(l1,l2); + +for i = 1:l1 + x = w(i,:)'*ones(1,l2); + out(i,:) = sum((x-p).^2).^.5; +end diff --git a/hindex.m b/hindex.m new file mode 100644 index 0000000..b5d9e5e --- /dev/null +++ b/hindex.m @@ -0,0 +1,176 @@ +function [h ncited]=hindex(name,varargin) +%HINDEX Computes the h-index of an author from Google Scholar. +% HINDEX(AUTHORNAME) computes the h-index of the author AUTHORNAME, on +% the basis of the publications referenced by Google Scholar +% (http://scholar.google.com). An active internet connection is required. +% +% The index h is defined as "the number of papers with citation number +% higher or equal to h", and has been proposed by J.E. Hirsch to +% "characterize the scientific output of a researcher" [Proc. Nat. Acad. +% Sci. 46, 16569 (2005)]. Note that the number of citations referenced by +% Google Scholar may be lower than the actual one (old publications are +% not available online). +% +% The string AUTHORNAME should contain the last name, or the initial(s) +% of the first name(s) followed by the last name, of the author (eg, +% 'A. Einstein'). Do not put the initial(s) after the last name. The scan +% is not case sensitive. Points (.) and spaces ( ) are not taken into +% account. See Google Scholar Help for more details about the syntax. +% +% Example: HINDEX('A. Einstein') returns 43 (ie: 43 papers by A. Einstein +% have been cited at least 43 times, according to Google Scholar). +% +% H = HINDEX(AUTHORNAME) only returns the h-index, without display. +% +% HINDEX(AUTHORNAME, 'Property1',...) specifies the properties: +% 'verb' also displays the list of papers returned by Google +% Scholar, rejecting the ones for which AUTHORNAME is not +% one of the authors. +% 'plot' also plots the 'Cited by' number as a function of the +% paper rank. +% +% HINDEX should be used with care. Many biases exist (homonyms, errors +% from Google Scholar, old papers are not available online, but +% unpublished or draft papers are...) For the true h-index of an author, +% it is recommended to use an official citation index database (eg, ISI). +% Use HINDEX just for fun. +% +% Remark: Massive usage of hindex may be considered by the Google +% Scholar server as a spam attack, and may invalidate the IP number of +% your computer. If this happens, you get an 'Internet connection failed' +% error message -- but you still can use Google Scholar from a web +% browser. +% +% F. Moisy, moisy@fast.u-psud.fr +% Revision: 1.11, Date: 10-jul-2006 + + +% History: +% 22-jan-2006: v1.00-1.10, first versions. +% 07-jul-2006: v1.11, check ML version; help text improved; use properties + + +% check the matlab version: +if str2double(version('-release'))<14, + error('hindex requires Matlab 7 (R14) or higher.'); +end; + +error(nargchk(1,2,nargin)); + +% clean the input text: +name=lower(name); +name=strrep(name,'.',' '); +name=strrep(name,' ',' '); + +ncit=0; % total number of citation +ncitinthispage=0; % number of citation in the current page +ncited=[]; + +seenextpage=1; +numpage=0; +while seenextpage, + numpage=numpage+1; + % find the web page: + pagename=['http://scholar.google.com/scholar?num=100&start=' num2str(100*(numpage-1)) '&q=%22author%3A' strrep(name,' ','+author%3A') '%22']; + if nargout==0, + disp(['Scanning: ' pagename]); + end; + [s, res]=urlread(pagename); + if ~res, + error('Internet connection failed.'); + end; + + rem=s; % remainder of the string + + while strfind(rem,'Cited by '), + pauth1 = strfind(rem,'')+18; pauth1=pauth1(1); + pauth2 = strfind(rem(pauth1:min(end,(pauth1+500))),'')-1; pauth2=pauth2(1); + authstring = lower(rem(pauth1:(pauth1+pauth2-1))); % list of authors of the paper + authstring = strrep(authstring,'',''); + authstring = strrep(authstring,'',''); + authstring = strrep(authstring,'…','...'); + + % check that the required name is indeed in the author list. + paperok=0; + pos=strfind(authstring,name); + if length(pos), + pos=pos(1); + paperok=1; + if pos>1, + % check for wrong initials (eg, 'ga einstein' should not + % match for 'a einstein') + pl=authstring(pos-1); + if ((pl>='a')&&(pl<='z'))||(pl=='-'), + paperok=0; + end; + end; + if pos<(length(authstring)-length(name)), + % check for wrong 'suffix' (eg, 'einstein-joliot' should not + % match for 'einstein') + nl=authstring(pos+length(name)); + if ((nl>='a')&&(nl<='z'))||(nl=='-'), + paperok=0; + end; + end; + end; + + if paperok, % if the required name is indeed in the author list + ncit = ncit+1; + ncitinthispage = ncitinthispage +1; + p=strfind(rem,'Cited by ')+9; p=p(1); + substr=rem(p:(p+5)); + pend=strfind(substr,'<'); pend=pend(1); + ncited(ncit)=str2double(substr(1:(pend-1))); + rem=rem((p+2):end); + if any(strncmpi(varargin,'verb',1)) + disp(['#' num2str(ncit) ': (' num2str(ncited(ncit)) '), ' authstring]); + end; + else + if any(strncmpi(varargin,'verb',1)) + disp(['rejected: ' authstring]); + end; + p=strfind(rem,'Cited by ')+9; p=p(1); + rem=rem((p+2):end); + end; + end; + if any(strncmpi(varargin,'verb',1)) + disp(' '); + end; + if ncit==0, + seenextpage=0; + else + if ((ncited(ncit)<2)||(~length(findstr(rem,'Next')))), + seenextpage=0; + end; + end; +end; % while seenextpage + +if length(ncited), + % sort the list (it should be sorted, but sometimes GS produces unsorted results) + ncited=sort(ncited); ncited=ncited(ncit:-1:1); + + % computes the H-factor: + h=sum(ncited>=(1:ncit)); + + % plot the 'Cited by' number: + if any(strncmpi(varargin,'plot',1)) + loglog(1:ncit,ncited,'.-',1:ncit,1:ncit,'--',h,h,'o'); + xlabel('Paper rank'); ylabel('Number of citations'); + title(['h-index plot for ''' name ''' (h=' num2str(h) ')']); + end; + + % some displays if no output argument: + if nargout==0, + disp(['Number of cited papers: ' num2str(length(ncited))]); + disp(['''Cited by'' list: ' num2str(ncited)]); + disp(['Total number of citations: ' num2str(sum(ncited))]); + disp(['h-index = ' num2str(h)]); + clear h; + end; +else + h=0; + if nargout==0, + disp('No result found'); + clear h; + end; +end; diff --git a/hist2d.m b/hist2d.m new file mode 100644 index 0000000..4580eb4 --- /dev/null +++ b/hist2d.m @@ -0,0 +1,67 @@ +%function mHist = hist2d ([vY, vX], vYEdge, vXEdge) +%2 Dimensional Histogram +%Counts number of points in the bins defined by vYEdge, vXEdge. +%size(vX) == size(vY) == [n,1] +%size(mHist) == [length(vYEdge) -1, length(vXEdge) -1] +% +%EXAMPLE +% mYX = rand(100,2); +% vXEdge = linspace(0,1,10); +% vYEdge = linspace(0,1,20); +% mHist2d = hist2d(mYX,vYEdge,vXEdge); +% +% nXBins = length(vXEdge); +% nYBins = length(vYEdge); +% vXLabel = 0.5*(vXEdge(1:(nXBins-1))+vXEdge(2:nXBins)); +% vYLabel = 0.5*(vYEdge(1:(nYBins-1))+vYEdge(2:nYBins)); +% pcolor(vXLabel, vYLabel,mHist2d); colorbar +function mHist = hist2d (mX, vYEdge, vXEdge) +[nRow, nCol] = size(mX); +if nCol < 2 + error ('mX has less than two columns') +end + +nRow = length (vYEdge)-1; +nCol = length (vXEdge)-1; + +vRow = mX(:,1); +vCol = mX(:,2); + +mHist = zeros(nRow,nCol); + +for iRow = 1:nRow + rRowLB = vYEdge(iRow); + rRowUB = vYEdge(iRow+1); + + [mIdxRow] = find (vRow > rRowLB & vRow <= rRowUB); + vColFound = vCol(mIdxRow); + + if (~isempty(vColFound)) + + + vFound = histc (vColFound, vXEdge); + + nFound = (length(vFound)-1); + + if (nFound ~= nCol) + [nFound nCol] + error ('hist2d error: Size Error') + end + + [nRowFound, nColFound] = size (vFound); + + nRowFound = nRowFound - 1; + nColFound = nColFound - 1; + + if nRowFound == nCol + mHist(iRow, :)= vFound(1:nFound)'; + elseif nColFound == nCol + mHist(iRow, :)= vFound(1:nFound); + else + error ('hist2d error: Size Error') + end + end + +end + + diff --git a/histfun.m b/histfun.m new file mode 100644 index 0000000..22b3b42 --- /dev/null +++ b/histfun.m @@ -0,0 +1,69 @@ +function [Z,C,B] = histfun(X,Y,E,fun) +%HISTFUN - Apply a function to each class of a histogram +% [Z,C] = histfun(X,Y,E,fun) +% +% Example +% >> x = randn(100,1); +% >> y = x.^2 +% >> histfun(x,y,10,'mean') +% +% See also: histc, cellfun, histk() + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-02-10 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<4 + fun = @mean; +end +if isempty(Y) + Y=X; +end +if isempty(E) + E=10; +end + +if numel(E)==1 + [C] = bins(X,E-1); + C = [-Inf C Inf]; + [N,B] = histc(X,C); +else + C=E; + [N,B] = histc(X,[E]); +end +for i=1:(length(C)-1) + if any(B==i) + Z(i)=feval(fun, Y(B==i)); + else + Z(i)=NaN; + end +end +return + +function n=count(x) +n=length(x); + +function [b]=bins(y,n) +% Compute n bins from data +% +miny = min(y(~isnan(y))); +maxy = max(y(~isnan(y))); +if (isempty(miny)) + % In acase all nan... + miny = NaN; + maxy = NaN; +end +if miny == maxy, + miny = miny - floor(n/2) - 0.5; + maxy = maxy + ceil(n/2) - 0.5; +end +bw = (maxy - miny) ./ n; +b = miny + bw/2 + bw*(0:n-1) ; \ No newline at end of file diff --git a/histk.m b/histk.m new file mode 100644 index 0000000..4cef025 --- /dev/null +++ b/histk.m @@ -0,0 +1,69 @@ +function [E,N,J] = histk(X,varargin) +%HISTK - Histogram count and ranking +% [E,N,J] = histk(X) +% E is the list of values in X ranked by their relative frequency +% N is their number of occurences +% J is the class to which each element of X belongs to, so: E(J) == X +% +% [E,...] = histk(X, 'rows') works on rows +% +% Note: histk() works even if (numeric) X contains NaN and Inf +% +% See also: hist, histc, histfun() + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-22 ReCreation +% KND 2006-10-23 Fix NaN issue +% ----------------------------- Script History --------------------------------- +if ischar(X) + [U,I,J]=unique(X, 'rows'); +else + if nargin<2 || ~isequal(lower(varargin{1}), 'rows') + if ~isvector(X) + for i=1:size(X(:,:),2) + if nargout<3 + [E{i},N{i}]=histk(X(:,i)); + else + [E{i},N{i},J{i}]=histk(X(:,i)); + end + end + return + end + end + [U,I,J]=unique(X,varargin{:}); +end +if isnumeric(X) + % special treatment for possible NaNs in numeric arrays + nans = isnan(U); + if any(nans) + U(nans)=[]; + U(end+1)=NaN; + J(ismember(J,find(nans)))=length(U); + end +end +% Bin data into classes and sort them classes according to their +% cardinality (in decreasing order) +[N,i]=sort(-histc(J,1:length(U))); +% Because we tricked sort using negative values : +N=-N; +if ischar(X) + % In case X is a char array, keep the rest of the rows with "(i,:)" instead + % of only "(i)" + E=U(i,:); +elseif size(U,2)>1 + E=U(i,:); +else +E=U(i); +end +if nargout>2 + [J,J]=ismember(J,i); +elseif nargout==0 + E=[E N]; +end diff --git a/histo2D.m b/histo2D.m new file mode 100644 index 0000000..f39308c --- /dev/null +++ b/histo2D.m @@ -0,0 +1,31 @@ +% function H = histo2D(D,[Xlo Xhi],Xn,[Ylo Yhi],Yn,Xlab,Ylab,Title) +% +% 2 Dimensional Histogram (size(H) == [Yn Xn]) +% Counts number of points in the bins defined by +% X = linspace(Xlo,Xhi,Xn) and +% Y = linspace(Ylo,Yhi,Yn) + +function H = histo2D(D,Xrange,Xn,Yrange,Yn,Xlab,Ylab,Title) + +Xlo = Xrange(1) ; Xhi = Xrange(2) ; +Ylo = Yrange(1) ; Yhi = Yrange(2) ; +X = linspace(Xlo,Xhi,Xn)' ; +Y = linspace(Ylo,Yhi,Yn)' ; + +Dx = D(:,1) ; Dy = D(:,2) ; +n = length(D) ; + +H = zeros(Yn,Xn) ; + +for i = 1:n + x = dsearchn(X,Dx(i)) ; + y = dsearchn(Y,Dy(i)) ; + H(y,x) = H(y,x) + 1 ; +end ; + +figure , pcolor(X,Y,H) ; +% Xmid = 0.5*(X(1:end-1)+X(2:end)) ; +% Ymid = 0.5*(Y(1:end-1)+Y(2:end)) ; +% figure , pcolor(Xmid,Ymid,H) ; +colorbar ; shading flat ; axis square tight ; grid on ; +xlabel(Xlab) ; xlabel(Ylab) ; title(Title) ; \ No newline at end of file diff --git a/hline.m b/hline.m new file mode 100644 index 0000000..61d9972 --- /dev/null +++ b/hline.m @@ -0,0 +1,58 @@ +function varargout = hline(y,varargin) +%HLINE - Create a horizontal line on a plot +% [h] = hline(y) +% Adds as many horizontal lines on the current plot as there are values in y. +% +% See also: line, vline + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-02 Creation +% +% ----------------------------- Script History --------------------------------- + +%x=max(abs(get(gca, 'Xlim')))*[-1 1]; +%x=x*10; +x=get(gca, 'Xlim'); +y=y(:); +y=[y*ones(1,2)]'; +x=repmat(x,size(y,2),1)'; + +holdstate=ishold; +hold on; +if nargin>1 && ischar(varargin{1}) && mod(nargin-1,2)==1 + opt=[]; + c = ismember(varargin{1}, 'bgrcmykw'); + m = ismember(varargin{1}, '.ox+*sdv^<>ph'); + if any(c) + opt=[{'Color', varargin{1}(c)} opt]; + end + if any(m) + opt=[{'Marker', varargin{1}(m)} opt]; + end + if any(~c & ~m) + opt=[{'LineStyle', varargin{1}(~c & ~m)} opt]; + end + varargin(1)=[]; + varargin = [opt varargin]; +end +h=line(x,y,varargin{:}); +if ~holdstate + hold off; +end +if nargin==1 + LineStyles={'-', ':', '--', '-.'}; + for i=1:length(h); + set(h(i), 'LineStyle', LineStyles{ceil(i/size(get(gca, 'ColorOrder'),1))}); + end +end +if nargout==0 + return +end +varargout={h}; diff --git a/horizalign.m b/horizalign.m new file mode 100644 index 0000000..e44d1b5 --- /dev/null +++ b/horizalign.m @@ -0,0 +1,30 @@ +function [s]=horizalign(s,FLAG) +% horizalign - NOT WORKING !!! Horizontal Alignment of a char array + + + +error('') + +% [s]=horizalign(s,FLAG) +% FLAG: -1 for left alignment, +1 for right, 0: centered [default:-1] +if nargin<2 + FLAG=-1; +end +if ~isequal(FLAG,1) & ~isequal(FLAG,-1) & ~isequal(FLAG,0) + error('FLAG should be -1 or +1') +end + +% + + +m= + +for i=1:size(s,1) + k=strfind(s(1,:), ' ') + + z=find(diff(k)>1) + if ~isempty(z) | + s(i,:)=circshift(s(i,:), [0 FLAG*(z(1))]); + end +end + diff --git a/hostname.m b/hostname.m new file mode 100644 index 0000000..06ce73b --- /dev/null +++ b/hostname.m @@ -0,0 +1,4 @@ +function h=hostname() +[h,h]=system('hostname'); +h=deblank(h); + diff --git a/hot2.m b/hot2.m new file mode 100644 index 0000000..ca9c1d4 --- /dev/null +++ b/hot2.m @@ -0,0 +1,32 @@ +function h = hot2(m,pR,pY) +%HOT2 Alternative Black-red-yellow-white color map. +% HOT2(M,R,Y) returns an M-by-3 matrix containing a "hot" colormap in +% which the proportion of red is set by R (default: 0.5) +% and that of yellow by Y (default: 0.25). +% HOT2, by itself, is the same length as the current colormap. +% +% For example, to reset the colormap of the current figure: +% +% colormap(hot2) +% +% See also HSV, GRAY, PINK, COOL, BONE, COPPER, FLAG, +% COLORMAP, RGBPLOT. + +% K.N'Diaye +% C. Moler, 8-17-88, 5-11-91, 8-19-92. +% Copyright 1984-2002 The MathWorks, Inc. +% $Revision: 5.7 $ $Date: 2002/04/08 22:00:14 $ + +if nargin < 1, m = size(get(gcf,'colormap'),1); end +if nargin < 2, pR = .5; end +if nargin < 3, pY = .1; end + +n1 = fix(pR*m); +n3 = fix(pY*m); +n2 = m-n1-n3; + +r = [(1:n1)'/n1; ones(n2+n3,1)]; +g = [zeros(n1,1); (1:n2)'/n2; ones(n3,1)]; +b = [zeros(n1+n2,1); (1:m-n1-n2)'/(n3)]; + +h = [r g b]; \ No newline at end of file diff --git a/huemap.m b/huemap.m new file mode 100644 index 0000000..b4062ce --- /dev/null +++ b/huemap.m @@ -0,0 +1,52 @@ +function [cmap]=huemap(hue,n,beta,skew) +% huemap - creates a colormap around a given hue +% +% [cmap]=huemap(hue,n,beta) +% The colormap is from black to white, centered around the hue +% INPUTS: +% hue: a 1x3 or 3x3 RGB colormap. First line is the hue. Other are +% optional +% Second is the bottom of the spectrum (default: black). +% Third is the top default: white. +% n: number of colors in the colormap, default the size of the current +% colormap +% beta: a parameter for the shape of the spectrum, default=0 +% beta>0 => more contrast +% If beta is a 2x1 vector, beta(1) apply to the darker part of the +% spectrum and beta(2) apply to its lighter part. +% OUTUTS: +% cmap: a nx3 colormap +if size(hue,1)<2 + hue(2,:)=[0 0 0]; +end +if size(hue,1)<3 + hue(3,:)=[1 1 1]; +end +if nargin<3 + beta=0; +end +if length(beta)==1 + beta=[beta beta]; +end +if nargin<2 + n=size(colormap,1); +end +% From BRIGHTEN function: +tol = sqrt(eps); +glight=1 - min(1-tol,beta(2)); +gdark=1/(1 + max(-1+tol,-beta(1))); + +% lighter hues +b=linspace(0,1,n-round(n/2)+1).^glight'; +cmap = [ ones(n-round(n/2)+1,1)*hue(1,:) + b*[hue(3,:)-hue(1,:)] ]; + +% remove duplicated center hue +cmap(1,:)=[]; +% darker hues +b=linspace(0,1,round(n/2)).^gdark'; +b=flipud(b); +cmap=[ ones(round(n/2),1)*(hue(1,:)) + b*(hue(2,:)-hue(1,:)) ; cmap]; + +cmap=max(cmap,0); +cmap=min(cmap,1); +return diff --git a/icatb/icatb_check_path.m b/icatb/icatb_check_path.m new file mode 100644 index 0000000..28b9179 --- /dev/null +++ b/icatb/icatb_check_path.m @@ -0,0 +1,92 @@ +function icatb_check_path +% Check path + +% Check startup file +checkStartup; + +% Check required paths for the toolboxes +checkReqdPaths; + +% run only on windows +icatb_openMatlabServer; + + +function checkStartup +% check gift start up file + +if (exist('gift_startup.m', 'file') == 2) || (exist('gift_startup.m', 'file') == 6) + fprintf( 'Executing gift_startup ...\n' ); + % execute gift start up file + gift_startup; + +else + + % Get the full file path of the gift file + giftPath = which('gift.m'); + % Folder location of the gift + giftPath = fileparts(giftPath); + + % all directories on path + pathstr = path; + + % Get the directories on path + allDirs = strread(pathstr, '%s', 'delimiter', pathsep); + + if ~isempty(allDirs) + + [indices] = regexp(allDirs, 'icatb$'); + indices = good_cells(indices); + matchedDirs = allDirs(indices); + matchedDirs(good_cells(regexp(matchedDirs, 'matlab')))=[]; + + if length(matchedDirs) > 1 + error(['Fix MATLAB path such that it has only one version of GIFT at a time']); + elseif length(matchedDirs) == 1 + if strcmpi(giftPath, matchedDirs{1}) + return; + else + error(['Fix MATLAB path such that it has only one version of GIFT at a time']); + end + end + + end + +end +% end for adding path + +function ind = good_cells( mycell ) + +if ~iscell(mycell) + mycell = {mycell}; +end + +for j=1:length(mycell) + ind(j)=~isempty(mycell{j}); +end + + +function checkReqdPaths +% Check required paths + +% Get the full file path of the gift file +giftPath = which('gift.m'); +% Folder location of the gift +giftPath = fileparts(giftPath); + +reqdDirs = str2mat(giftPath, strcat(giftPath, filesep, str2mat('icatb_analysis_functions', 'icatb_batch_files', 'icatb_display_functions', ... + 'icatb_helpManual', 'icatb_helper_functions', 'icatb_io_data_functions', 'icatb_spm2_files', ... + 'icatb_spm5_files', ['toolbox', filesep, 'eegiftv1.0a']))); + +pathstr = path; + +allDirs = strread(pathstr, '%s', 'delimiter', pathsep); + +% Add required paths +for nDir = 1:size(reqdDirs, 1) + currentPath = deblank(reqdDirs(nDir, :)); + check = strmatch(currentPath, allDirs, 'exact'); + if isempty(check) + addpath(genpath(currentPath), '-end'); + end +end +% End for adding required paths \ No newline at end of file diff --git a/icatb/icatb_displayGUI.m b/icatb/icatb_displayGUI.m new file mode 100644 index 0000000..1fc331e --- /dev/null +++ b/icatb/icatb_displayGUI.m @@ -0,0 +1,1690 @@ +function icatb_displayGUI(paramFile) +% Purpose: Display GUI is used to switch between different visualization +% methods. There are four visualization methods like Component Explorer, +% Subect Explorer, Orthogonal Viewer, Composite Viewer. +% These visualization methods except Subject Explorer can be called +% independently of Display GUI by +% clicking on the buttons like Composite Viewer, Component Explorer, +% Orthogonal Viewer + +icatb_defaults; + +global BG_COLOR; +global BG2_COLOR; +global BUTTON_COLOR; +global FG_COLOR; +global AXES_COLOR; +global FONT_COLOR; +global BUTTON_FONT_COLOR; +global COMPONENT_EXPLORER_PIC; +global COMPOSITE_VIEWER_PIC; +global ORTHOGONAL_VIEWER_PIC; +global UI_FONTNAME; +global UI_FONTUNITS; +global UI_FS; +global SORT_COMPONENTS; +global PARAMETER_INFO_MAT_FILE; +global ZIP_IMAGE_FILES; + +% load parameters file +filterP = ['*', PARAMETER_INFO_MAT_FILE, '*.mat']; +if ~exist('paramFile', 'var') + [paramFile] = icatb_selectEntry('typeEntity', 'file', 'title', 'Select Parameter File', ... + 'filter', filterP); +end + +drawnow; + +[pathstr, fileName] = fileparts(paramFile); + +cd(pathstr); % Cd to parameter file location +load(paramFile); + +if ~exist('sesInfo', 'var') + error('Please select the ICA parameter file'); +end + +if ~sesInfo.isInitialized + error('Please run the analysis to display the results'); +end + + +if isfield(sesInfo, 'modality') + if ~strcmpi(sesInfo.modality, 'fmri') + error('Use EEGIFT toolbox to display EEG results'); + end +end + + +%try + displayGUIMsg = 'Opening display GUI. Please wait ...'; + disp(displayGUIMsg); + helpHandle = helpdlg(displayGUIMsg, 'Opening Display GUI'); + [sesInfo, complexInfoRead] = icatb_name_complex_images(sesInfo, 'read'); + [sesInfo, complexInfoWrite] = icatb_name_complex_images(sesInfo, 'write'); + + + zipContents.zipFiles = {}; + zipContents.files_in_zip(1).name = {}; + if isfield(sesInfo, 'zipContents') + zipContents = sesInfo.zipContents; + end + + %%%%%%%% Test if the data sets have different number of time points %%% + % Count the number of files in each of the datasets + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + varCount = 0; + countFiles = zeros(1, sesInfo.numOfSub*sesInfo.numOfSess); + + % check the time points information + if isfield(sesInfo, 'diffTimePoints') + + for numSubjects = 1:sesInfo.numOfSub + for numSessions = 1:sesInfo.numOfSess + varCount = varCount + 1; + % get the time points information + countFiles(varCount) = sesInfo.diffTimePoints(varCount); + % end for getting the count for time points + countTimePoints.sub(numSubjects).sess(numSessions) = countFiles(varCount); + end + end + + else + for numSubjects = 1:sesInfo.numOfSub + for numSessions = 1:sesInfo.numOfSess + varCount = varCount + 1; + % get the time points information + countFiles(varCount) = icatb_get_countTimePoints(sesInfo.userInput.files(varCount).name); + % end for getting the count for time points + countTimePoints.sub(numSubjects).sess(numSessions) = countFiles(varCount); + end + end + % set the time points info to sesInfo + sesInfo.userInput.diffTimePoints = countFiles; + sesInfo.diffTimePoints = countFiles; + end + % end for checking time points information + + % check for same number of time points or different + checkTimePoints = find(countFiles ~= countFiles(1)); + + if ~isempty(checkTimePoints) + flagTimePoints = 'different_time_points'; + else + flagTimePoints = 'same_time_points'; + end + + %get results from sesInfo file + dispParameters.icaOutputFiles = sesInfo.icaOutputFiles; + dispParameters.numOfSess = sesInfo.numOfSess; + dispParameters.numOfSub = sesInfo.numOfSub; + dispParameters.numOfComp = sesInfo.numComp; + dispParameters.inputFiles = sesInfo.inputFiles; + dispParameters.HInfo = sesInfo.HInfo; + dispParameters.spmMatrices = sesInfo.userInput.designMatrix; + dispParameters.outputDir = pathstr; % save the output directory + dispParameters.paramFile = paramFile; % parameter file + dispParameters.inputPrefix = sesInfo.userInput.prefix; + dispParameters.complexInfoRead = complexInfoRead; + dispParameters.complexInfoWrite = complexInfoWrite; + dispParameters.zipContents = zipContents; + dispParameters.mask_ind = sesInfo.mask_ind; + dispParameters.button_original_font_color = BUTTON_FONT_COLOR; + dispParameters.button_new_font_color = [0 1 0]; + + if isfield(sesInfo, 'flip_analyze_images') + dispParameters.flip_analyze_images = sesInfo.flip_analyze_images; + end + + + maskImage = fullfile(dispParameters.outputDir, [dispParameters.inputPrefix, 'Mask.img']); + % save mask image + dispParameters.mask_file = maskImage; + + %%%%%%%%% Construct a mask Image for dealing with z scores%%%%%%%%%%%%%%% + % get voxel dimensions + voxelDim = sesInfo.HInfo.DIM; + % Initialise mask data + maskData = zeros(1, prod(voxelDim)); + % use indices in the mask as one + maskData(sesInfo.mask_ind) = 1; + % convert to 3D data + maskData = reshape(maskData, voxelDim); + + % first scan of the functional data + firstScan = deblank(sesInfo.inputFiles(1).name(1, :)); + + [firstScan, fileNum] = icatb_parseExtn(firstScan); + + if ~exist(firstScan, 'file') + disp(['file: ', firstScan, ' is missing.']); + firstScan = icatb_selectEntry('typeEntity', 'file', 'typeSelection', 'single', 'filter', '*.img;*.nii', ... + 'title', 'Select first scan of functional data', 'fileType', 'image', 'fileNumbers', 1); + if isempty(firstScan) + error('file is not selected'); + end + % update the files information + sesInfo.inputFiles(1).name = str2mat(firstScan, sesInfo.inputFiles(1).name(2:end, :)); + sesInfo.userInput.files = sesInfo.inputFiles; + dispParameters.inputFiles = sesInfo.inputFiles; + end + + % get the first image volume + V = icatb_getVol(firstScan, fileNum); + V.fname = maskImage; + V.n(1) = 1; + icatb_write_vol(V, maskData); + %%%%%%%%%%%%% end for creating mask %%%%%%%%%%% + + % include spm mat flag + if isfield(sesInfo.userInput, 'spmMatFlag') + dispParameters.spmMatFlag = sesInfo.userInput.spmMatFlag; + else + dispParameters.spmMatFlag = 'not_specified'; + end + + % include data type + if isfield(sesInfo.userInput, 'dataType') + dispParameters.dataType = lower(sesInfo.userInput.dataType); + else + dispParameters.dataType = 'real'; + end + + % include data type + if isfield(sesInfo.userInput, 'write_complex_images') + dispParameters.write_complex_images = lower(sesInfo.userInput.write_complex_images); + else + dispParameters.write_complex_images = 'real&imaginary'; + end + + % sorting text file (optional way to enter the regressors) + if isfield(sesInfo.userInput, 'sortingTextFile') + dispParameters.sortingTextFile = sesInfo.userInput.sortingTextFile; + else + dispParameters.sortingTextFile = []; + end + + icatb_save(paramFile, 'sesInfo'); + + clear sesInfo; + + % store the information about the structural file + [dispParameters] = icatb_getStructuralFile(dispParameters); + + dispParameters.flagTimePoints = flagTimePoints; + dispParameters.countTimePoints = countTimePoints; + outputFiles = dispParameters.icaOutputFiles; + + % delete a previous figure of display GUI + checkDispGUI = findobj('tag', 'displaywindow'); + + if ~isempty(checkDispGUI) + for ii = 1:length(checkDispGUI) + delete(checkDispGUI(ii)); + end + end + + % display figure + graphicsHandle = icatb_getGraphics('Display GUI', 'displayGUI', 'displaywindow', 'off'); + + set(graphicsHandle, 'CloseRequestFcn', @figCloseCallback); + + % set graphics handle menu none + set(graphicsHandle, 'menubar', 'none'); + + dispParameters.diffTimePoints = countFiles; % store the count for the images + + % plot display defaults + display_defaultsMenu = uimenu('parent', graphicsHandle, 'label', 'Display Defaults', 'callback', ... + {@display_defaults_callback, graphicsHandle}); + + % Display GUI Options Menu + dispGUIOptionsMenu = uimenu('parent', graphicsHandle, 'label', 'Display GUI Options'); + designMatrixMenu = uimenu(dispGUIOptionsMenu, 'label', 'Design Matrix', 'callback', ... + {@designMatrixOptionsCallback, graphicsHandle}); + + + % IC navigator + %icNavigatorMenuH = uimenu(dispGUIOptionsMenu, 'label', 'IC Navigator', 'callback', @icNavigatorCallback); + + % save display parameters using save option in options menu + saveDataMenu = uimenu(dispGUIOptionsMenu, 'label', 'Save Display Parameters', 'callback', ... + {@saveDispParametersCallback, graphicsHandle}); + + + % load display parmeters + loadDataMenu = uimenu(dispGUIOptionsMenu, 'label', 'Load Display Parameters', 'callback', ... + {@loadDispParametersCallback, graphicsHandle}); + + % enter sorting text file + sortingTextFileMenu = uimenu(dispGUIOptionsMenu, 'label', 'Load file for temporal sorting', 'callback', ... + {@sortingTextFileCallback, graphicsHandle}); + + % Help Menu + helpMenu = uimenu('parent', graphicsHandle, 'label', 'GIFT-Help'); + htmlHelpMenu = uimenu(helpMenu, 'label', 'Display GUI', 'callback', 'icatb_openHTMLHelpFile(''icatb_displayGUI.htm'');'); + + + % parameters to plot in a menu + + % offsets + xOffset = 0.02; yOffset = 0.02; + + %%%%%%%%%%%%% Draw Title here %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % title color + titleColor = [0 0.9 0.9]; + % fonts + titleFont = 13; + axes('Parent', graphicsHandle, 'position', [0 0 1 1], 'visible', 'off'); + xPos = 0.5; yPos = 0.97; + text(xPos, yPos, 'Visualization Methods', 'color', titleColor, 'FontAngle', 'italic', 'fontweight', 'bold', ... + 'fontsize', titleFont, 'HorizontalAlignment', 'center', 'FontName', UI_FONTNAME); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Plot controls in two frames + % Upper frame: Images + % Lower frame: UIcontrols + + % plot display button + buttonWidth = 0.2; buttonHeight = 0.05; + displayButtonPos = [0.75 yOffset buttonWidth buttonHeight]; + + + displayButtonH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', displayButtonPos, 'string', 'Display', 'tag', 'display_button', 'callback', ... + {@displayButtonCallback, graphicsHandle}); + % extentPos = get(displayButtonH, 'extent'); % get the extent of the load anatomical button + % displayButtonPos(3) = extentPos(3) + 0.02; displayButtonPos(4) = extentPos(4) + 0.002; + % % get the new position for load anatomical position + % set(displayButtonH, 'position', displayButtonPos); + + % plot load anatomical + buttonWidth = 0.26; buttonHeight = 0.05; + loadAnatomicalPos = [0.05 yOffset buttonWidth buttonHeight]; + loadAnatomicalH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', loadAnatomicalPos, 'string', 'Load Anatomical', 'tag', 'load_anatomical_button', ... + 'callback', {@loadAnatomicalCallback, graphicsHandle}); + % extentPos = get(loadAnatomicalH, 'extent'); % get the extent of the load anatomical button + % loadAnatomicalPos(3) = extentPos(3) + 0.01; loadAnatomicalPos(4) = extentPos(4) + 0.001; + % % get the new position for load anatomical position + % set(loadAnatomicalH, 'position', loadAnatomicalPos); + + paramFrameYOrigin = loadAnatomicalPos(2) + loadAnatomicalPos(4) + yOffset; + availableSpace = yPos - paramFrameYOrigin - yOffset; + + paramHeight = 0.65*availableSpace; + + % define frame positions + parameterFramePos = [xOffset paramFrameYOrigin 1 - 2*xOffset paramHeight]; + + paramFrameYOrigin = parameterFramePos(2) + parameterFramePos(4) + yOffset; + paramFrameWidth = 1 - 2*xOffset; + paramFrameHeight = yPos - 2*yOffset - paramFrameYOrigin; + + buttonFramePos = [parameterFramePos(1) paramFrameYOrigin paramFrameWidth paramFrameHeight]; + + parametersFrameH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'frame', 'position', ... + parameterFramePos, 'tag', 'parameters-frame', 'visible', 'off'); + + buttonsFrameH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'frame', 'position', ... + buttonFramePos, 'tag', 'button-frame', 'visible', 'off'); + + % component Button + buttonWidth = (1 - 2*xOffset - 5*xOffset) / 4; + buttonHeight = 0.05; + componentButtonPos = [buttonFramePos(1) + xOffset buttonFramePos(2) + buttonFramePos(4) - yOffset - 0.5*buttonHeight ... + buttonWidth buttonHeight]; + + componentButtonH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', componentButtonPos, 'string', 'Component', 'tag', 'component_button', ... + 'callback', {@componentExplorerCallback, graphicsHandle}); + % subject explorer button + subjectButtonPos = componentButtonPos; + subjectButtonPos(1) = subjectButtonPos(1) + subjectButtonPos(3) + xOffset; + subjectButtonH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', subjectButtonPos, 'string', 'Subject', 'tag', 'subject_button', 'callback', ... + {@subjectExplorerCallback, graphicsHandle}); + + % Orthogonal Viewer button + orthButtonPos = subjectButtonPos; + orthButtonPos(1) = orthButtonPos(1) + orthButtonPos(3) + xOffset; + orthoButtonH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', orthButtonPos, 'string', 'Orthogonal', 'tag', 'ortho_button', ... + 'callback', {@orthoViewerCallback, graphicsHandle}); + + % Orthogonal Viewer button + compositeButtonPos = orthButtonPos; + compositeButtonPos(1) = compositeButtonPos(1) + compositeButtonPos(3) + xOffset; + compositeButtonH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'pushbutton', ... + 'position', compositeButtonPos, 'string', 'Composite', 'tag', 'composite_button', ... + 'callback', {@compositeViewerCallback, graphicsHandle}); + + % Component Explorer Picture + componentPicPos = componentButtonPos; + componentPicPos(2) = buttonFramePos(2); + componentPicPos(4) = componentButtonPos(2) - 0.5*componentButtonPos(4) - componentPicPos(2); + componentPicture = axes('Parent', graphicsHandle, 'units','normalized', 'position', componentPicPos); + pic1 = imread(COMPONENT_EXPLORER_PIC); + ImageAxis1 = image(pic1, 'parent', componentPicture, 'CDataMapping', 'scaled'); + axis(componentPicture, 'off'); + + % Subject Explorer Picture + subjectPicPos = componentPicPos; + subjectPicPos(1) = subjectButtonPos(1); + subjectPicture = axes('Parent', graphicsHandle, 'units','normalized', 'position', subjectPicPos); + pic2 = imread(COMPONENT_EXPLORER_PIC); + ImageAxis2 = image(pic2, 'parent', subjectPicture, 'CDataMapping', 'scaled'); + axis(subjectPicture, 'off'); + + % Orthogonal Viewer Picture + orthoPicPos = componentPicPos; + orthoPicPos(1) = orthButtonPos(1); + orthoPicture = axes('Parent', graphicsHandle, 'units','normalized', 'position', orthoPicPos); + pic3 = imread(ORTHOGONAL_VIEWER_PIC); + ImageAxis3 = image(pic3, 'parent', orthoPicture, 'CDataMapping', 'scaled'); + axis(orthoPicture, 'off'); + + % Composite Viewer Picture + compositePicPos = componentPicPos; + compositePicPos(1) = compositeButtonPos(1); + compositePicture = axes('Parent', graphicsHandle, 'units','normalized', 'position', compositePicPos); + pic4 = imread(COMPOSITE_VIEWER_PIC); + ImageAxis4 = image(pic4, 'parent', compositePicture, 'CDataMapping', 'scaled'); + axis(compositePicture, 'off'); + + dispParameters.slicePlane = 'axial'; + dispParameters.compList = zeros(dispParameters.numOfComp, 1); + dispParameters.displayType = 'component explorer'; + + % Plot sort components followed by listboxes for viewing set and + % component number + + % plot sort components here + textHeight = 0.05; textWidth = 0.35; + control_width = 0.2; control_height = 0.05; + % text origin + textYOrigin = parameterFramePos(2) + parameterFramePos(4) - xOffset - textHeight; + textPos = [parameterFramePos(1), textYOrigin, textWidth, textHeight]; + + % plot text + textH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'text', 'position', ... + textPos, 'string', 'Sort Components', 'HorizontalAlignment', 'center'); + + % horizontal alignment - center, vertical alignment - middle + align(textH,'center','middle'); + + popupPos = [textPos(1) + textPos(3) + 2*xOffset, textPos(2), ... + control_width, control_height]; + + clear options; + + % Sort Options + options(1).str = SORT_COMPONENTS; + sortOptions = {'No', 'Yes'}; + % Apply defaults from icatb_defaults + sortOptions = checkDefaults_gui(options(1).str, sortOptions, 'exact'); + + for jj = 1:length(sortOptions) + options(jj).str = sortOptions{jj}; + end + + popupH = icatb_getUIPopUp(graphicsHandle, str2mat(options.str), popupPos, '', 'on', 'sort_components'); + + clear options; + + % plot component listbox and viewing set listbox + textPos(2) = textPos(2) - textHeight - yOffset; + + textWidth = 0.25; textHeight = 0.05; + % draw listbox + listWidth = 0.5; listHeight = 0.3; + + textPos = [textPos(1) + 0.5*listWidth - 0.5*textWidth textPos(2) textWidth textHeight]; + + % plot text + textH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'text', 'position', ... + textPos, 'string', 'Viewing Set', 'HorizontalAlignment', 'center'); + + % horizontal alignment - center, vertical alignment - middle + align(textH,'center','middle'); + + counter = 1; + numOfSets = length(outputFiles); + % loop over number of sets + for jj = 1 : numOfSets + % loop over sessions + for kk = 1 : length(outputFiles(jj).ses) + str = outputFiles(jj).ses(kk).name(1, :); + [pathstr fileName] = fileparts(str); + underScoreIndex = icatb_findstr(fileName, '_'); + str = fileName(1:underScoreIndex(end) - 1); + str = [num2str(jj),'-', num2str(kk), ' ', str]; + options(counter).str = str; + counter = counter + 1; + end + + end + + listboxPos = [parameterFramePos(1) textPos(2) - listHeight - yOffset listWidth listHeight]; + % list box position + listH = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'listbox', 'position', ... + listboxPos, 'HorizontalAlignment', 'center', 'string', str2mat(options.str), 'value', 1, 'tag', ... + 'viewing_set', 'min', 0, 'max', 1); + + + listWidth = 0.25; + + listboxPos = [parameterFramePos(1) + parameterFramePos(3) - 2*xOffset - listWidth, listboxPos(2), listWidth, ... + listHeight]; + textPos = [listboxPos(1) + 0.5*listWidth - 0.5*textWidth textPos(2) textWidth textHeight]; + + text2H = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'text', 'position', ... + textPos, 'string', 'Component No:', 'HorizontalAlignment', 'center'); + + % horizontal alignment - center, vertical alignment - middle + align(text2H, 'center', 'middle'); + + % number of components + numComp = dispParameters.numOfComp; + + clear options; + + % return component index + for ii = 1:numComp + options(ii).str = icatb_returnFileIndex(ii); + end + + % list box position + list2H = icatb_uicontrol('parent', graphicsHandle, 'units', 'normalized', 'style', 'listbox', 'position', ... + listboxPos, 'string', str2mat(options.str), 'HorizontalAlignment', 'center', ... + 'tag', 'component_number', 'min', 0, 'max', 2); + + clear options + % store the data to handles data + %handles_data.dispParameters = dispParameters; + + [dispParameters, inputText] = icatb_displayGUI_defaults('init', [], dispParameters, 'off'); + %dispParameters.visualizationmethods = 'component explorer'; + handles_data.dispParameters = dispParameters; handles_data.inputText = inputText; + + % set the figure data + set(graphicsHandle, 'userdata', handles_data); + + clear handles_data; + + % by default execute the component explorer callback + componentExplorerCallback(componentButtonH, [], graphicsHandle); + + try + delete(helpHandle); + catch + end + + % Make the figure visible + set(graphicsHandle, 'visible', 'on'); + + +%catch +% if exist('helpHandle', 'var') +% if ishandle(helpHandle) +% delete(helpHandle); +% end +% end +% icatb_displayErrorMsg; +%end + + +%%%%%%%%%%%%%% Function Callbacks %%%%%%%%%%%%%%%%%%%%%%%%% + +function componentExplorerCallback(hObject, event_data, handles) +% Component explorer callback +% set the visualization methods field to component explorer + + +subjectH = findobj(handles, 'tag', 'subject_button'); +orthoH = findobj(handles, 'tag', 'ortho_button'); +compositeH = findobj(handles, 'tag', 'composite_button'); + +handles_data = get(handles, 'userdata'); +dispParameters = handles_data.dispParameters; +dispParameters.visualizationmethods = 'component explorer'; + +% set all the other buttons normal font +set(hObject, 'fontweight', 'bold', 'ForegroundColor', dispParameters.button_new_font_color); +set(subjectH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(orthoH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(compositeH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); + +% Viewing set listbox +viewingsetH = findobj(handles, 'tag', 'viewing_set'); +set(viewingsetH, 'enable', 'on'); + +% component listbox +compListH = findobj(handles, 'tag', 'component_number'); +set(compListH, 'enable', 'off'); + +handles_data.dispParameters = dispParameters; +% set the user data +set(handles, 'userdata', handles_data); + +% sort parameters popup control +sortCompH = findobj(handles, 'tag', 'sort_components'); +set(sortCompH, 'enable', 'on'); + + +function subjectExplorerCallback(hObject, event_data, handles) +% Subject Component explorer callback +% set the visualization methods field to subject component explorer + +componentH = findobj(handles, 'tag', 'component_button'); +orthoH = findobj(handles, 'tag', 'ortho_button'); +compositeH = findobj(handles, 'tag', 'composite_button'); + +handles_data = get(handles, 'userdata'); +dispParameters = handles_data.dispParameters; +dispParameters.visualizationmethods = 'subject component explorer'; + + +% set all the other buttons normal font +set(hObject, 'fontweight', 'bold', 'ForegroundColor', dispParameters.button_new_font_color); +set(componentH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(orthoH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(compositeH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); + + +% component listbox +compListH = findobj(handles, 'tag', 'component_number'); +set(compListH, 'enable', 'on'); + +% viewing set listbox +viewingsetH = findobj(handles, 'tag', 'viewing_set'); +set(viewingsetH, 'enable', 'off'); + +compVal = get(compListH, 'value'); +if length(compVal) > 1 + set(compListH, 'value', compVal(1)); + % single selection listbox +end +% make the component listbox single selection +set(compListH, 'max', 1, 'min', 0); + +% set the user data +handles_data.dispParameters = dispParameters; +set(handles, 'userdata', handles_data); + +% sort parameters popup control +sortCompH = findobj(handles, 'tag', 'sort_components'); +set(sortCompH, 'enable', 'off'); + +function orthoViewerCallback(hObject, event_data, handles) +% Orthogonal viewer callback +% set the visualization methods field to orthogonal viewer + +componentH = findobj(handles, 'tag', 'component_button'); +subjectH = findobj(handles, 'tag', 'subject_button'); +compositeH = findobj(handles, 'tag', 'composite_button'); + + +handles_data = get(handles, 'userdata'); +dispParameters = handles_data.dispParameters; +dispParameters.visualizationmethods = 'orthogonal viewer'; + +% set all the other buttons normal font +set(hObject, 'fontweight', 'bold', 'ForegroundColor', dispParameters.button_new_font_color); +set(componentH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(subjectH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(compositeH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); + +% Viewing set listbox +viewingsetH = findobj(handles, 'tag', 'viewing_set'); +set(viewingsetH, 'enable', 'on'); + +% component listbox +compListH = findobj(handles, 'tag', 'component_number'); +set(compListH, 'enable', 'on'); + +compVal = get(compListH, 'value'); + +if length(compVal) > 1 + set(compListH, 'value', compVal(1)); +end + +% make the component listbox single selection +set(compListH, 'min', 0, 'max', 1); + +% set the figure data +handles_data.dispParameters = dispParameters; +set(handles, 'userdata', handles_data); + +% sort parameters popup control +sortCompH = findobj(handles, 'tag', 'sort_components'); +set(sortCompH, 'enable', 'off'); + +% case subject component explorer +function compositeViewerCallback(hObject, event_data, handles) +% Composite viewer callback +% set the visualization methods field to composite viewer + + +componentH = findobj(handles, 'tag', 'component_button'); +subjectH = findobj(handles, 'tag', 'subject_button'); +orthoH = findobj(handles, 'tag', 'ortho_button'); + +handles_data = get(handles, 'userdata'); +dispParameters = handles_data.dispParameters; +dispParameters.visualizationmethods = 'composite viewer'; + +% set all the other buttons normal font +set(hObject, 'fontweight', 'bold', 'ForegroundColor', dispParameters.button_new_font_color); +set(componentH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(subjectH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); +set(orthoH, 'fontweight', 'normal', 'ForegroundColor', dispParameters.button_original_font_color); + +% viewing set listbox +viewingsetH = findobj(handles, 'tag', 'viewing_set'); +set(viewingsetH, 'enable', 'on'); + +% component listbox +compListH = findobj(handles, 'tag', 'component_number'); +set(compListH, 'enable', 'on'); + +compVal = get(compListH, 'value'); + +if length(compVal) > 5 + disp('A maximum of five components can be plotted in Composite Viewer with different color bars'); + set(compListH, 'value', compVal(1:5)); + % single selection listbox +end + +% make the component listbox multiple selection +set(compListH, 'min', 0, 'max', 2); + +% set the figure data +handles_data.dispParameters = dispParameters; +set(handles, 'userdata', handles_data); + +% sort parameters popup control +sortCompH = findobj(handles, 'tag', 'sort_components'); +set(sortCompH, 'enable', 'off'); + +function loadAnatomicalCallback(hObject, event_data, handles) +% load structural image +% change the inputText structure array where index matches slice_range: +% set the structural file location to dispParameters + +handles_data = get(handles, 'userdata'); +% display parameters +dispParameters = handles_data.dispParameters; +% get the input text Structure +inputText = handles_data.inputText; +% get the structural file +structFile = icatb_selectEntry('typeEntity', 'file', 'title', 'Select Structural File', 'filter', ... + '*.img;*.nii', 'fileType', 'image', 'fileNumbers', 1); + +if ~isempty(structFile) + dispParameters.structFile = structFile; + + % get the anatomical plane + getIndex = strmatch('anatomical_plane', str2mat(inputText.tag), 'exact'); + % get the three views + allStrs = inputText(getIndex).answerString; + % get the current value + selectVal = inputText(getIndex).value; + + if iscell(allStrs) + selectStr = allStrs{selectVal}; + else + selectStr = deblank(allStrs(selectVal, :)); + end + % end for checking + + if isempty(selectStr) + selectStr = 'axial'; + end + + selectStr = lower(selectStr); + % find slice_range location + getIndex = strmatch('slice_range', str2mat(inputText.tag), 'exact'); + % get structVol + %imagVol = icatb_returnHInfo(structFile); + imagVol = icatb_get_vol_nifti(structFile); + % get the slices in mm for the corresponding plane + [sliceParameters] = icatb_get_slice_def(imagVol, selectStr); + % get the slices in mm + slices_in_mm = sliceParameters.slices; + clear sliceParameters; + % construct string + slices_in_mm = icatb_constructString(slices_in_mm); + % set the slice range + inputText(getIndex).answerString = slices_in_mm; + % set display parameters + [dispParameters, inputText] = icatb_displayGUI_defaults('no-init', inputText, dispParameters, 'off'); +end + + +% set the user data to the figure +handles_data.dispParameters = dispParameters; +handles_data.inputText = inputText; +set(handles, 'userdata', handles_data); + +function displayButtonCallback(hObject, event_data, handles) +% display button callback + +try + + % get the figure data + handles_data = get(handles, 'userdata'); + dispParameters = handles_data.dispParameters; + % load parameter file + load(dispParameters.paramFile); + % indices in the mask + dispParameters.mask_ind = sesInfo.mask_ind; + mask_ind = sesInfo.mask_ind; + zipContents.zipFiles = {}; + zipContents.files_in_zip(1).name = {}; + if isfield(sesInfo, 'zipContents') + zipContents = sesInfo.zipContents; + end + % zip contents + dispParameters.zipContents = zipContents; + [sesInfo, complexInfoRead] = icatb_name_complex_images(sesInfo, 'read'); + [sesInfo, complexInfoWrite] = icatb_name_complex_images(sesInfo, 'write'); + % complex information + dispParameters.complexInfoRead = complexInfoRead; + dispParameters.complexInfoWrite = complexInfoWrite; + clear sesInfo; + + % put a check for the visualization methods + if isfield(dispParameters, 'visualizationmethods') + displayMethod = dispParameters.visualizationmethods; + else + error('Visualization method is not selected'); + end + + % find viewing set listbox + viewListH = findobj(handles, 'tag', 'viewing_set'); + viewingsetStr = get(viewListH, 'string'); + viewingsetVal = get(viewListH, 'value'); + + % viewing set selected + viewingset = deblank(viewingsetStr(viewingsetVal, :)); + + % component listbox + compListH = findobj(handles, 'tag', 'component_number'); + % get the component numbers + component_numbers = get(compListH, 'value'); + + if isempty(component_numbers) + component_numbers = 1; + end + + % checking display method + if strcmpi(displayMethod, 'composite viewer') + if length(component_numbers) > 5 + component_numbers = component_numbers(1:5); + disp('A maximum of five components can be plotted in Composite Viewer with different color bars'); + end + else + if strcmpi(displayMethod, 'subject component explorer') | strcmpi(displayMethod, 'orthogonal viewer') + if length(component_numbers) > 1 + component_numbers = component_numbers(1); + end + end + end + % end for checking display method + + dispParameters.componentnumber = component_numbers; + + % store viewing set + dispParameters.viewingset = viewingset; + returnValue = dispParameters.returnValue; + convertToZ = dispParameters.convertToZ; + threshValue = dispParameters.thresholdvalue; + + % sort parameters + sortCompH = findobj(handles, 'tag', 'sort_components'); + sortCompStr = get(sortCompH, 'string'); sortCompVal = get(sortCompH, 'value'); + sortcomponents = deblank(sortCompStr(sortCompVal, :)); + dispParameters.sortcomponents = sortcomponents; + + handles_data.dispParameters = dispParameters; + set(handles, 'userdata', handles_data); + if isfield(handles_data.dispParameters, 'text_left_right') + parameters.text_left_right = handles_data.dispParameters.text_left_right; + end + clear handles_data; + + + % parameters or variables common to all the display methods + + % load structural file + P = dispParameters.structFile; % structural file name + [pathstr, name, ext, versn] = fileparts(P); + if isempty(pathstr) + P = fullfile(pwd, P); + end + + icatb_defaults; + global DETRENDNUMBER; + global SMOOTHPARA; + global SMOOTHINGVALUE; + + parameters.flip_analyze_images = []; + if isfield(dispParameters, 'flip_analyze_images') + parameters.flip_analyze_images = dispParameters.flip_analyze_images; + end + + % parameter structure used to display components according to the + % visualization selected + parameters.structFile = dispParameters.structFile; + parameters.imagevalues = returnValue; + parameters.convertToZ = convertToZ; + parameters.thresholdvalue = threshValue; + % actual subjects, sessions and components + parameters.numOfSub = dispParameters.numOfSub; + parameters.numOfSess = dispParameters.numOfSess; + parameters.numComp = dispParameters.numOfComp; + parameters.filesOutputDir = dispParameters.outputDir; + parameters.inputPrefix = dispParameters.inputPrefix; + + % initialise model time course + modelTimecourse = []; + % field required for detecting the type of complex images + parameters.write_complex_images = dispParameters.write_complex_images; + complexInfoWrite.complexInfoRead = complexInfoRead; + % add complex type to the structure + parameters.complexInfoRead = complexInfoRead; + parameters.complexInfoWrite = complexInfoWrite; + parameters.dataType = dispParameters.dataType; + parameters.zipContents = dispParameters.zipContents; + parameters.outputDir = dispParameters.outputDir; + parameteres.mask_file = dispParameters.mask_file; + + switch lower(displayMethod) + case 'component explorer' + %icatb_defaults; + global TMAP_AN3_FILE; + global COMPLEXVIEWER; % get the viewer type (real&imaginary or magnitude&phase) + + % check the viewing set + if ~isfield(dispParameters, 'viewingset') + error('Viewing set is not selected'); + else + if isempty(dispParameters.viewingset) + error('Viewing set is not selected'); + end + end + + % load components + dashIndex = icatb_findstr(dispParameters.viewingset, '-'); + spaceIndex = icatb_findstr(dispParameters.viewingset, ' '); + a = dispParameters.viewingset(1 : dashIndex(1) - 1); + b = dispParameters.viewingset(dashIndex(1) + 1 : spaceIndex(1)); + P = dispParameters.icaOutputFiles(str2num(a)).ses(str2num(b)).name; + + compFiles = P; + + % get the files from the zip file + [zipFileName, files_in_zip] = icatb_getViewingSet_zip(compFiles, complexInfoWrite, ... + dispParameters.dataType, zipContents); + + % component files + compFiles = icatb_fullFile('directory', dispParameters.outputDir, 'files', compFiles); + + % number of components + numOfComp = parameters.numComp; + + % end loop over component files + figLabel = dispParameters.viewingset; + + % put a default spm flag + if isfield(dispParameters, 'spmMatFlag') + spmMatFlag = dispParameters.spmMatFlag; + else + spmMatFlag = 'not_specified'; + end + + % do interpolation of images separately for components that are + % not sorted and sorted + + % when components are not sorted + if strcmpi(dispParameters.sortcomponents, 'no') + set(handles, 'pointer', 'watch'); + % resize the image and return header Info + [icasig, icaTimecourse, structuralImage, coords, HInfo, text_left_right] = icatb_loadICAData('structFile', ... + dispParameters.structFile, 'compFiles', compFiles, 'slicePlane', dispParameters.anatomicalplane, ... + 'sliceRange', dispParameters.slicerange, 'comp_numbers', [1:1:parameters.numComp], ... + 'convertToZ', convertToZ, 'returnValue', returnValue, 'threshValue', threshValue, ... + 'dataType', dispParameters.dataType, 'complexInfo', complexInfoWrite, ... + 'zipfile', zipFileName, 'files_in_zip_file', files_in_zip, 'mask_file', parameteres.mask_file, 'flip_analyze_images', ... + parameters.flip_analyze_images); + set(handles, 'pointer', 'arrow'); + + % set up default labels and sorting Index + for ii = 1:parameters.numComp + compLabels(ii).string = ['Component ', num2str(ii), ' Not Sorted']; + end + % smooth ica time course + if strcmpi(SMOOTHPARA, 'yes') + icaTimecourse = icatb_gauss_smooth1D(icaTimecourse, SMOOTHINGVALUE); + end + spatialTemplate = []; + parameters.compLabels = compLabels; + parameters.undetrendICA = icaTimecourse; + % linearly detrend ICA Timecourse + parameters.icaTimecourse = icatb_detrend(icaTimecourse, 1, size(icaTimecourse, 1), DETRENDNUMBER); + %detrend(icaTimecourse); % linearly detrended ica time course + clear icaTimecourse; + parameters.modelTimecourse = modelTimecourse; + clear modelTimecourse; + parameters.refInfo = []; + parameters.icasig = icasig; % store component images + clear icasig; + parameters.figLabel = figLabel; + parameters.htmlFile = 'icatb_component_explorer.htm'; + else + % display GUI parameters + dispGUI_Parameters = struct('returnValue', returnValue, 'convertToZ', convertToZ, 'threshValue', ... + threshValue, 'flagTimePoints', dispParameters.flagTimePoints, 'countTimePoints', ... + dispParameters.countTimePoints, 'icaOutputFiles', dispParameters.icaOutputFiles, 'numOfSub', ... + dispParameters.numOfSub, 'numOfSess', dispParameters.numOfSess, 'numOfComp', ... + dispParameters.numOfComp, 'spmMatrices', dispParameters.spmMatrices, 'outputDir', ... + dispParameters.outputDir, 'paramFile', dispParameters.paramFile, 'spmMatFlag', ... + spmMatFlag, 'sortingTextFile', dispParameters.sortingTextFile, 'structFile', ... + dispParameters.structFile, 'slicePlane', dispParameters.anatomicalplane, ... + 'sliceRange', dispParameters.slicerange, 'dataType', dispParameters.dataType, ... + 'complexInfo', complexInfoWrite, 'displayGUI', handles, 'inputPrefix', ... + dispParameters.inputPrefix, 'zipContents', zipContents); + % Output contains the sorted parameters information + [sortParameters] = icatb_sortComponentsGUI(dispGUI_Parameters); + if isempty(sortParameters) + return; %error('error in getting data from sorting gui.'); + end + + clear dispGUI_Parameters; + parameters.sortParameters = sortParameters; + clear sortParameters; + spmMatFlag = parameters.sortParameters.stateDesignMatrix; + + % consider temporal and spatial cases + if strcmpi(parameters.sortParameters.sortingType, 'temporal') + set(handles, 'pointer', 'watch'); + % load ICA images and time courses + [icasig, icaTc, structuralImage, coords, HInfo, text_left_right] = icatb_loadICAData(... + 'structFile', dispParameters.structFile, 'compFiles', compFiles, 'slicePlane', ... + dispParameters.anatomicalplane, 'sliceRange', dispParameters.slicerange, ... + 'comp_numbers', [1:1:parameters.numComp], 'convertToZ', convertToZ, 'returnValue', ... + returnValue, 'threshValue', threshValue, 'dataType', dispParameters.dataType, ... + 'complexInfo', complexInfoWrite, 'zipfile', zipFileName, ... + 'files_in_zip_file', files_in_zip, 'mask_file', parameteres.mask_file, ... + 'flip_analyze_images', parameters.flip_analyze_images); + set(handles, 'pointer', 'arrow'); + + else + + spatialInfo = parameters.sortParameters.spatialInfo; + + % spatialInfo.files = compFiles; + % spatialInfo.viewingSet = figureData.viewingSet; + % spatialInfo.zipFileName = zipFileName; + % spatialInfo.files_in_zip = files_in_zip; + + %compFiles = parameters.sortParameters.compFiles; + + %parameters.sortParameters = rmfield(parameters.sortParameters, 'icasig'); % remove the field + + % load ICA images and time courses + [icasig, icaTc, structuralImage, coords, HInfo, text_left_right] = icatb_loadICAData(... + 'structFile', dispParameters.structFile, 'compFiles', spatialInfo.files, 'slicePlane', ... + dispParameters.anatomicalplane, 'sliceRange', dispParameters.slicerange, ... + 'comp_numbers', [1:1:parameters.numComp], 'convertToZ', convertToZ, 'returnValue', ... + returnValue, 'threshValue', threshValue, 'dataType', dispParameters.dataType, ... + 'complexInfo', complexInfoWrite, 'mask_file', parameteres.mask_file, 'flip_analyze_images', ... + parameters.flip_analyze_images); + + + if ~isempty(spatialInfo.zipFileName) + files_in_zip = str2mat(spatialInfo.files_in_zip); + %fileN = icatb_fullFile('files', files_in_zip, 'directory', parameters.outputDir); + icatb_delete_file_pattern(files_in_zip, parameters.outputDir); + end + + + figLabel = spatialInfo.viewingSet; + + % get the left and right convention + %text_left_right = parameters.sortParameters.text_left_right; + %parameters.text_left_right = text_left_right; + + % get the component image + %icasig = parameters.sortParameters.icasig; + + %parameters.sortParameters = rmfield(parameters.sortParameters, 'icasig'); % remove the field + + % get the structural image + %structuralImage = parameters.sortParameters.structuralImage; + % get the header infomation + %HInfo = parameters.sortParameters.structHInfo; + % remove both component images and structural image + %parameters.sortParameters = rmfield(parameters.sortParameters, 'structuralImage'); % remove the field + + end + % end for checking the sorting type (temporal or spatial) + + parameters.htmlFile = 'icatb_component_explorer.htm'; + % keyword for datasets + keywd_SubnSess = parameters.sortParameters.keywd; + %sort icasig using sorting index + tempicasig = zeros(size(icasig)); + for ii = 1:numOfComp + tempicasig(ii, :) = icasig(parameters.sortParameters.sortedIndices(ii), :); + end + clear icasig; + icasig = tempicasig; + clear tempicasig; + % get the sorted order of the spatial maps + parameters.icasig = icasig; + clear icasig; + parameters.figLabel = figLabel; + end + % end for checking whether the components are sorted or not + + if ~exist('keywd_SubnSess', 'var') + keywd_SubnSess = 'not-specified'; + end + + switch keywd_SubnSess + case 'all_subjects_sessions' + % Parameters to report number of subjects and sessions + parameters.numSubjects = dispParameters.numOfSub; + parameters.numSessions = dispParameters.numOfSess; + case 'single_session' + % Parameters to report number of subjects and sessions + parameters.numSubjects = dispParameters.numOfSub; + parameters.numSessions = 1; + case 'single_subject' + % Parameters to report number of subjects and sessions + parameters.numSubjects = 1; + parameters.numSessions = dispParameters.numOfSess; + otherwise + % Parameters to report number of subjects and sessions + parameters.numSubjects = 1; + parameters.numSessions = 1; + end + + %%%%%%%%% Apply structural image parameters %%%%%%%% + parameters.structHInfo = HInfo; + structDIM = HInfo.DIM; + parameters.structuralImage = structuralImage; + + % pass the correponding selected display parameters + parameters.anatomicalplane = dispParameters.anatomicalplane; + parameters.slicerange = dispParameters.slicerange; + parameters.imagesperfigure = dispParameters.imagesperfigure; + parameters.imagevalues = returnValue; + parameters.spmMatFlag = spmMatFlag; + % New component explorer that takes parameters structure as + % input. + + % structural file + parameters.structFile = dispParameters.structFile; + + + if ~isfield(parameters, 'text_left_right') + parameters.text_left_right = text_left_right; + end + + icatb_componentExplore(parameters); + + case 'composite viewer' + + % put a check for the component number + if ~isfield(dispParameters, 'componentnumber') + error('Component number is not selected'); + end + + %icatb_defaults; + global TMAP_AN3_FILE; + + if ~isfield(dispParameters, 'viewingset') + error('Viewing set is not selected'); + else + if isempty(dispParameters.viewingset) + error('Viewing set is not selected'); + end + end + + % load components + dashIndex = icatb_findstr(dispParameters.viewingset,'-'); + spaceIndex = icatb_findstr(dispParameters.viewingset,' '); + a = dispParameters.viewingset(1:dashIndex(1)-1); + b = dispParameters.viewingset(dashIndex(1)+1:spaceIndex(1)); + P = dispParameters.icaOutputFiles(str2num(a)).ses(str2num(b)).name; + if threshValue == 0 + warning('Please set the threshold to view the components.'); + end + + if length(dispParameters.componentnumber) == 0 + icatb_error('No Components Selected'); + end + % get the full file path + files_to_load = P; + % get the files from the zip file + [zipFileName, files_in_zip] = icatb_getViewingSet_zip(files_to_load, complexInfoWrite, ... + dispParameters.dataType, zipContents); + files_to_load = icatb_fullFile('directory', dispParameters.outputDir, 'files', files_to_load); + set(handles, 'pointer', 'watch'); + clear P; + % parameters structure + parameters.numComp = length(dispParameters.componentnumber(:)); %size(files_to_load, 1); + % load ICA images and time courses + [icasig, icaTimecourse, structuralImage, coords, HInfo, text_left_right] = icatb_loadICAData('structFile', dispParameters.structFile, ... + 'compFiles', files_to_load, 'slicePlane', dispParameters.anatomicalplane, 'sliceRange', ... + dispParameters.slicerange, 'comp_numbers', dispParameters.componentnumber, ... + 'convertToZ', convertToZ, 'returnValue', returnValue, 'threshValue', threshValue, 'complexInfo', ... + complexInfoWrite, 'dataType', dispParameters.dataType, ... + 'zipfile', zipFileName, 'files_in_zip_file', files_in_zip, 'mask_file', parameteres.mask_file, ... + 'flip_analyze_images', parameters.flip_analyze_images); + + set(handles, 'pointer', 'arrow'); + + %%%%%%%%% Apply structural image parameters %%%%%%%% + parameters.structHInfo = HInfo; + structDIM = HInfo.DIM; + parameters.structuralImage = structuralImage; + + tdim = size(icaTimecourse, 1); + % show only the first field + if isa(icasig, 'complex_data') + icasig = getfield(icasig, 'firstField'); + end + + if isa(icaTimecourse, 'complex_data') + icaTimecourse = getfield(icaTimecourse, 'firstField'); + end + + % take only the absolute value of the data + % component dimensions + xdim = HInfo.DIM(1); + ydim = HInfo.DIM(2); + zdim = HInfo.DIM(3); + tdim = size(icaTimecourse, 1); + % put icasig into correct dimensions + icasig = reshape(icasig, size(icasig, 1), xdim, ydim, zdim); + parameters.icasig = icasig; + clear icasig; + parameters.slicePlane = dispParameters.anatomicalplane; + parameters.sliceRange = dispParameters.slicerange; + parameters.componentnumber = dispParameters.componentnumber; + % detrend ica Time course + parameters.icaTimecourse = icatb_detrend(icaTimecourse, 1, size(icaTimecourse, 1), DETRENDNUMBER); + parameters.icaDIM = [xdim ydim zdim tdim]; + parameters.htmlFile = 'icatb_composite_viewer.htm'; + + + if ~isfield(parameters, 'text_left_right') + parameters.text_left_right = text_left_right; + end + + % composite viewer + icatb_compositeViewer(parameters); + + case 'orthogonal viewer' + % put a check for the component number + if ~isfield(dispParameters, 'componentnumber') + error('Component number is not selected'); + end + %icatb_defaults; + global TMAP_AN3_FILE; + + % load original data files for timecourse information + subNum = 1; + P = dispParameters.inputFiles(subNum).name; + outputDir = dispParameters.outputDir; + count = 0; + for ii = 1:dispParameters.numOfSub + for jj = 1:dispParameters.numOfSess + count = count + 1; + fmriFiles(ii).ses(jj).name = dispParameters.inputFiles(count).name; + end + end + clear fmri; + clear HInfo; + + % setup icaData + dashIndex = icatb_findstr(dispParameters.viewingset, '-'); + spaceIndex = icatb_findstr(dispParameters.viewingset, ' '); + a = dispParameters.viewingset(1:dashIndex(1)-1); + b = dispParameters.viewingset(dashIndex(1)+1:spaceIndex(1)); + if isempty(dispParameters.componentnumber) + error('Component is not selected for orthogonal viewer.'); + end + compNum = dispParameters.componentnumber(end); + %P = dispParameters.icaOutputFiles(str2num(a)).ses(str2num(b)).name(compNum,:); + P = dispParameters.icaOutputFiles(str2num(a)).ses(str2num(b)).name; + icaFiles = P; + % if(~isempty(findstr(TMAP_AN3_FILE,P))) + % icatb_new_directions('displayGUI-tmap'); + % end + parameters.compNum = compNum; + lastUnderscore = icatb_findstr(deblank(P(1, :)), '_'); + parameters.title = [P(1, 1:lastUnderscore(end)), icatb_returnFileIndex(compNum)]; + + % use the component file + files_to_load = P; + % get the files from the zip file + [zipFileName, files_in_zip] = icatb_getViewingSet_zip(files_to_load, complexInfoWrite, ... + dispParameters.dataType, zipContents); + files_to_load = icatb_fullFile('directory', dispParameters.outputDir, 'files', files_to_load); + set(handles, 'pointer', 'watch'); + + clear P; + + % Interpolate the ICA images + [icasig, icaTimecourse, structuralImage, coords, HInfo, text_left_right] = icatb_loadICAData('structFile', ... + dispParameters.structFile, 'compFiles', files_to_load, ... + 'convertToZ', convertToZ, 'returnValue', returnValue, 'threshValue', ... + threshValue, 'imreshape', 'yes', 'open_dialog', 'no', 'complexInfo', ... + complexInfoWrite, 'dataType', dispParameters.dataType, 'comp_numbers', compNum, ... + 'zipfile', zipFileName, 'files_in_zip_file', files_in_zip, 'mask_file', parameteres.mask_file, ... + 'flip_analyze_images', parameters.flip_analyze_images); + + set(handles, 'pointer', 'arrow'); + + structuralImage = squeeze(structuralImage); + + icasig = squeeze(icasig); + + % show only the first field + if isa(icasig, 'complex_data') + icasig = getfield(icasig, 'firstField'); + end + + if isa(icaTimecourse, 'complex_data') + icaTimecourse = getfield(icaTimecourse, 'firstField'); + end + + %%%%%%%%% Apply structural image parameters %%%%%%%% + parameters.structHInfo = HInfo; + structDIM = HInfo.DIM; + parameters.structuralImage = structuralImage; + parameters.icasig = icasig; + clear icasig; + parameters.icaTimecourse = icatb_detrend(icaTimecourse, 1, size(icaTimecourse, 1), DETRENDNUMBER); + clear icaTimecourse; + parameters.icaFiles = icaFiles; + clear icaFiles; + parameters.fmriFiles = fmriFiles; + clear fmriFiles; + % store the new dimensions + parameters.icaHInfo = HInfo; + parameters.fmriHInfo = HInfo; + parameters.htmlFile = 'icatb_ortho_viewer.htm'; + % structural file + parameters.structFile = dispParameters.structFile; + parameters.diffTimePoints = dispParameters.diffTimePoints; + parameters.real_world_coords = coords; + + if ~isfield(parameters, 'text_left_right') + parameters.text_left_right = text_left_right; + end + + icatb_orthoViewer(parameters); + + case 'subject component explorer' + % put a check for the component number + if ~isfield(dispParameters, 'componentnumber') + error('Component number is not selected'); + end + %icatb_defaults; + global TMAP_AN3_FILE; + global WRITE_COMPLEX_IMAGES; + + if isempty(dispParameters.componentnumber) + error('Component is not selected'); + end + + numTimePoints = min(dispParameters.diffTimePoints); + + %numComp = length(dispParameters.icaOutputFiles); + numComp = 0; + % get the total number of components + for ii = 1:length(dispParameters.icaOutputFiles) + numComp = numComp + length(dispParameters.icaOutputFiles(ii).ses); + end + + + compNum = dispParameters.componentnumber(end); + counter = 0; + outputDir = dispParameters.outputDir; + if strcmp(lower(dispParameters.flagTimePoints), 'different_time_points') + %error('Subject explorer cannot be used with different number of images over data-sets. Please use other visualization methods.'); + disp('Time points are different across subjects'); + disp(['Using first ', num2str(numTimePoints), ' time points to display the time courses']); + end + + % get the write type of complex images + WRITE_COMPLEX_IMAGES = parameters.complexInfoRead.complexType; + + set(handles, 'pointer', 'watch'); + + % resize the image and return header Info + helpHandle = helpdlg('Interpolating component images. Please wait ...', 'Interpolating components'); + % loop over remaining files + for kk = 1:length(dispParameters.icaOutputFiles) + for ii = 1:length(dispParameters.icaOutputFiles(kk).ses) + counter = counter + 1; + %P = dispParameters.icaOutputFiles(kk).ses(ii).name(compNum, :); + P = str2mat(dispParameters.icaOutputFiles(kk).ses(ii).name); + PFullFiles = P; + % get the files from the zip file + [zipFileName, files_in_zip] = icatb_getViewingSet_zip(PFullFiles, complexInfoWrite, ... + dispParameters.dataType, zipContents); + PFullFiles = icatb_fullFile('directory', dispParameters.outputDir, 'files', PFullFiles); + % load ICA images and time courses + [tempicasig, tempA, structuralImage, coords, HInfo, textLR] = icatb_loadICAData('structFile', ... + dispParameters.structFile, 'compFiles', PFullFiles, 'slicePlane', ... + dispParameters.anatomicalplane, 'sliceRange', dispParameters.slicerange, ... + 'convertToZ', convertToZ, 'returnValue', returnValue, 'threshValue', ... + threshValue, 'imreshape', 'no', 'open_dialog', 'no', 'complexInfo', ... + complexInfoWrite, 'dataType', dispParameters.dataType, 'comp_numbers', compNum, ... + 'zipfile', zipFileName, 'files_in_zip_file', files_in_zip, 'mask_file', parameteres.mask_file, ... + 'flip_analyze_images', parameters.flip_analyze_images); + + tempA = tempA(1:numTimePoints, :); + + % smooth ica time course + if strcmpi(SMOOTHPARA, 'yes') + tempA = icatb_gauss_smooth1D(tempA, SMOOTHINGVALUE); + end + + % initialise component tc's and images + if kk == 1 & ii == 1 + icaTimecourse = zeros(size(tempA, 1), numComp); + icasig = zeros(numComp, size(tempicasig, 2)); + if strcmpi(parameters.dataType, 'complex') + icasig = complex_data(icasig); + icaTimecourse = complex_data(icaTimecourse); + end + end + + icasig(counter, :) = tempicasig; + clear tempicasig; + + + + icaTimecourse(:, counter) = tempA; + clear tempA; + % end for checking the data type structure or double + [pathstr, fileName, extn] = fileparts(deblank(P(1, :))); + % image extension + under_score_positions = icatb_findstr(fileName, '_'); + fileName = [fileName(1:under_score_positions(end)), icatb_returnFileIndex(compNum)]; + compLabels(counter).string = fileName; + % store text for left right + text_left_right = textLR; + clear P1; clear P: + end + + end + + if ishandle(helpHandle) + delete(helpHandle); + end + + % make the pointer arrow + set(handles, 'pointer', 'arrow'); + figLabel = ['Component ', num2str(compNum)]; + clear P; + tdim = size(icaTimecourse, 1); + % number of components + numOfComp = counter; + %%%%%%%%% Apply structural image parameters %%%%%%%% + parameters.structHInfo = HInfo; + structDIM = HInfo.DIM; + parameters.structuralImage = structuralImage; + %%%%%%%%%%%%%%%%%%%%%%%%%%% + DIM = [HInfo.DIM, tdim]; + % handle structure data type + icasig = reshape(icasig, [counter, DIM(1:end-1)]); + % parameters data structure + parameters.numComp = numComp; + parameters.icasig = icasig; + clear icasig; + parameters.icaTimecourse = icatb_detrend(icaTimecourse, 1, size(icaTimecourse, 1), DETRENDNUMBER); + parameters.undetrendICA = icaTimecourse; + clear icaTimecourse; + parameters.numSubjects = 1; % number of subjects concatenated + parameters.numSessions = 1; % number of sessions concatenated + otherFields = {'modelTimecourse', 'refInfo', 'diffTimePoints'}; % fields to be added + for ii = 1:length(otherFields) + if ~isfield(parameters, otherFields{ii}) + parameters = setfield(parameters, otherFields{ii}, []); + end + end + parameters.anatomicalplane = dispParameters.anatomicalplane; + parameters.slicerange = dispParameters.slicerange; + parameters.imagesperfigure = dispParameters.imagesperfigure; + parameters.compLabels = compLabels; + parameters.figLabel = figLabel; + parameters.htmlFile = 'icatb_subject_explorer.htm'; + % structural file + parameters.structFile = dispParameters.structFile; + % store text for left right + %parameters.text_left_right = str2mat(text_left_right.tag); + + if ~isfield(parameters, 'text_left_right') + parameters.text_left_right = text_left_right; + end + + % Component Explorer function + icatb_componentExplore(parameters); + end + + handles_data = get(handles, 'userdata'); + + handles_data.dispParameters.text_left_right = parameters.text_left_right; + + set(handles, 'userdata', handles_data); + +catch + set(handles, 'pointer', 'watch'); + icatb_displayErrorMsg; +end + + +function designMatrixOptionsCallback(hObject, event_data, handles) +% design matrix menu callback +% +% Options menu for the design matrix: +% saves the selected design matrix information in the parameter file and +% subject file as well. +% Useful when many data sets are involved and if 'no' option is selected +% during the analysis. + +% get the user data +designMatrixData = get(hObject, 'userdata'); + +% get the figure data +figureData = get(handles, 'userdata'); + +% set the spm matrices +icatb_selectDesignMatrix(handles); + +function saveDispParametersCallback(hObject, event_data, handles) +% save display parameters menu callback + +handles_data = get(handles, 'userdata'); +% display parameters +dispParameters = handles_data.dispParameters; +% get outputDir information +outputDir = dispParameters.outputDir; +% open input dialog box +prompt = {'Enter Valid File Name:'}; +dlg_title = 'Save Display Parameters as'; +num_lines = 1; +def = {'dispParameters'}; +% save the file with the file name specified +fileName = icatb_inputdlg2(prompt, dlg_title, num_lines, def); + +if ~isempty(fileName) + % make a full file + fileName = fullfile(outputDir, [fileName{1}, '.mat']); + icatb_save(fileName, 'dispParameters'); + disp(['Display parameters are saved in file: ', fileName]); +end + +function loadDispParametersCallback(hObject, event_data, handles) +% load display parameters menu callback + +global DISP_PARAMETERS +handles_data = get(handles, 'userdata'); + +dispParameters = handles_data.dispParameters; + +% get outputDir information +outputDir = dispParameters.outputDir; + +clear handles_data; + +clear dispParameters; + +% open file selection box +[P] = icatb_selectEntry('typeEntity', 'file', 'title', 'Select Display Parameter File', 'filter', '*.mat', ... + 'startPath', outputDir); +if ~isempty(P) + load(P); + if ~exist('dispParameters', 'var') + error('Not a valid display parameter file'); + end + DISP_PARAMETERS = dispParameters; + D(1).string = 'Global DISP_PARAMETERS variable is created.'; + D(size(D, 2) + 1).string = ''; + D(size(D, 2) + 1).string = 'Type the following statements at the command prompt:'; + D(size(D, 2) + 1).string = ''; + D(size(D, 2) + 1).string = 'global DISP_PARAMETERS; DISP_PARAMETERS'; + disp(str2mat(D.string)); +end + + +function openHelpDesignMatrix(hObject, event_data, handles) + +% get the user data +helpDetails = get(hObject, 'userdata'); +helpH = icatb_dialogBox('textType', 'large', 'textBody', helpDetails.str, 'title', helpDetails.title); +waitfor(helpH); + +function sortingTextFileCallback(hObject, event_data, handles) +% function callback for sorting text file + +% user data for the figure +handles_data = get(handles, 'userdata'); + +% disp parameters +dispParameters = handles_data.dispParameters; + +% parameter file +paramFile = dispParameters.paramFile; + +% load the parameter file +load(paramFile); + +% sorting text file +sesInfo.userInput.sortingTextFile = icatb_selectEntry('title', 'Select text file for regressors', 'typeSelection', ... + 'single', 'typeEntity', 'file', 'filter', '*.txt'); + +icatb_save(paramFile, 'sesInfo'); + +% set the file to display parameters +dispParameters.sortingTextFile = sesInfo.userInput.sortingTextFile; + +clear sesInfo; + +% set display parameters +handles_data.dispParameters = dispParameters; + +% set the figure data +set(handles, 'userdata', handles_data); + + +function [dispParameters] = icatb_getStructuralFile(dispParameters) +% get the structural file for plotting component images + +currentFile = dispParameters.inputFiles(1).name(1, :); + +[currentFile] = icatb_parseExtn(currentFile); + +% check the existence of the input file +if ~exist(currentFile, 'file') + msgString = [deblank(dispParameters.inputFiles(1).name(1, :)), ' file doesn''t exist.' ... + ' Do you want to select the structural file?']; + [answerQuestion] = icatb_questionDialog('title', 'Select Structural File', 'textbody', msgString); + if answerQuestion == 1 + % structural file + [structuralFile] = icatb_selectEntry('typeEntity', 'file', 'title', 'Select Structural File', 'filter', ... + '*.img;*.nii', 'fileType', 'image'); + else + error(deblank(dispParameters.inputFiles(1).name(1, :)), ' file doesn''t exist.'); + end +else + % structural file + structuralFile = dispParameters.inputFiles(1).name(1, :); + % create magnitude image for complex data type + if ~strcmpi(dispParameters.dataType, 'real') + complexFile = dispParameters.inputFiles(1).name(1, :); + [data, HInfo] = icatb_loadData(complexFile, dispParameters.dataType, ... + dispParameters.complexInfoRead, 'read', 1); + data = abs(data); + structuralFile = fullfile(dispParameters.outputDir, [dispParameters.inputPrefix, 'structFile.img']); + V = HInfo.V(1); + V.fname = structuralFile; + icatb_write_vol(V, data); + clear data; clear V; + end + % create magnitude image +end + +% add structural file to the dispParameters structure +dispParameters.structFile = structuralFile; + + +function display_defaults_callback(hObject, event_data, handles) +% get the display defaults + +handles_data = get(handles, 'userdata'); + +[parameters, inputText] = icatb_displayGUI_defaults('no-init', handles_data.inputText, handles_data.dispParameters); + +handles_data.dispParameters = parameters; +handles_data.inputText = inputText; + +set(handles, 'userdata', handles_data); + +function optionsString = checkDefaults_gui(choiceString, optionsString, stringChar) +% put the defaults at the Top + +temp = optionsString; % Assign options string to a temporary variable + +if strcmp(stringChar, 'exact') + matchIndex = strmatch(lower(choiceString), lower(temp), stringChar); % find the index of the choice string +else + matchIndex = strmatch(lower(choiceString), lower(temp)); % find the index of the choice string +end + +jj = 1; optionsString{1} = temp{matchIndex}; % choice string + +for numOptions = 1:length(optionsString) + if numOptions ~= matchIndex + jj = jj + 1; + optionsString{jj} = temp{numOptions}; % collect other options below the choice string + end +end + +function figCloseCallback(hObject, event_data, handles) +% figure close callback + +delete(hObject); + +function icNavigatorCallback(hObject, event_data, handles) + +icatb_ic_navigator; diff --git a/icatb/icatb_drawTimecourses.m b/icatb/icatb_drawTimecourses.m new file mode 100644 index 0000000..1a7ad3c --- /dev/null +++ b/icatb/icatb_drawTimecourses.m @@ -0,0 +1,924 @@ +function icatb_drawTimecourses(parameters) +% Expanded view of the time course +% uses function callbacks and menus to display the options and the +% utilities + +% load defaults +icatb_defaults; + +% Screen Color Defaults +global BG_COLOR; +global BG2_COLOR; +global BUTTON_COLOR; +global BUTTON_FONT_COLOR; +global FG_COLOR; +global AXES_COLOR; +global FONT_COLOR; +global UI_FONTNAME; +global UI_FONTUNITS; +global UI_FS; + +% set figure data the parameters +figureData = parameters; +outputDir = parameters.filesOutputDir; +clear parameters; + +% open time course figure +timecourse_handle = icatb_getGraphics(figureData.titleFig, 'timecourse', 'expaned_view_timecourse'); + +% get all the options to include in options menu +input_parameters = icatb_displayOptions; + +% Plot Options menu +optionsMenu = uimenu(timecourse_handle, 'label', 'Options'); +timecourseOptionsMenu = uimenu(optionsMenu, 'label', 'Timecourse Options', 'callback', ... + {@optionsWindowCallback, timecourse_handle}, 'userdata', input_parameters); +clear input_parameters; + +figureData.optionsMenu = timecourseOptionsMenu; + +% Plot Utilities menu +utilitiesMenu = uimenu(timecourse_handle, 'label', 'Utilities'); +% FFT +fftMenu = uimenu(utilitiesMenu, 'label', 'Power Spectrum', 'callback', {@fftCallback, timecourse_handle}); +figureData.fftMenu = fftMenu; + + +% show split time course menu +if figureData.num_DataSets > 1 + splitTimecourseMenu = uimenu(utilitiesMenu, 'label', 'Split Timecourses', 'callback', ... + {@splitTimecoursesCallback, timecourse_handle}); % SPLIT TIME COURSES + figureData.splitTimecourseMenu = splitTimecourseMenu; +end + +% Plot Help menu +helpMenu = uimenu(timecourse_handle, 'label', 'GIFT-Help'); +% Time courses help +timecoursesHelpMenu = uimenu(helpMenu, 'label', 'Expanded View of Timecourse', 'callback', ... + 'icatb_openHTMLHelpFile(''icatb_expanded_view_tc.htm'');'); +figureData.fftMenu = fftMenu; + +% Initialise vars +sortingCriteria = []; +sortingType = []; + +% get the sorting criteria and sorting type +if isfield(figureData, 'sortParameters') + sortingCriteria = lower(figureData.sortParameters.sortingCriteria); + sortingType = lower(figureData.sortParameters.sortingType); +end + +if strcmp(sortingCriteria, 'multiple regression') & ~strcmp(sortingType, 'spatial') + % adjust ICA only for multiple regression + adjustICAMenu = uimenu(optionsMenu, 'label', 'Adjust ICA', 'callback', ... + {@adjustICACallback, timecourse_handle}); % ADJUST ICA + % Regular method to compute event average + eventAvgMenu = uimenu(utilitiesMenu, 'label', 'Event Average (Regular Method)', 'callback', ... + {@eventRelatedCallback, timecourse_handle}, 'userdata', figureData.sortParameters.refInfo, 'tag', 'event_avg_regular'); % EVENT AVG + % Deconvolution method to compute event average + deconv_eventAvgMenu = uimenu(utilitiesMenu, 'label', 'Event Average (Deconvolution Method)', 'callback', ... + {@eventRelatedCallback, timecourse_handle}, 'userdata', figureData.sortParameters.refInfo, 'tag', 'event_avg_deconv'); % Deconv method for EVENT AVG + figureData.adjustICAMenu = adjustICAMenu; + figureData.eventAvgMenu = eventAvgMenu; + figureData.deconv_eventAvgMenu = deconv_eventAvgMenu; +elseif strcmp(sortingCriteria, 'correlation') & ~strcmp(sortingType, 'spatial') + % Regular method to compute event average + eventAvgMenu = uimenu(utilitiesMenu, 'label', 'Event Average (Regular Method)', 'callback', ... + {@eventRelatedCallback, timecourse_handle}, 'userdata', figureData.sortParameters.refInfo, 'tag', 'event_avg_regular'); % EVENT AVG + % Deconvolution method to compute event average + deconv_eventAvgMenu = uimenu(utilitiesMenu, 'label', 'Event Average (Deconvolution Method)', 'callback', ... + {@eventRelatedCallback, timecourse_handle}, 'userdata', figureData.sortParameters.refInfo, 'tag', 'event_avg_deconv'); % Deconv method for EVENT AVG + figureData.eventAvgMenu = eventAvgMenu; + figureData.deconv_eventAvgMenu = deconv_eventAvgMenu; +end + +% Save figure data menu +saveTimecourseDataMenu = uimenu(optionsMenu, 'label', 'Save Figure Parameters', 'callback', ... + {@saveTimecourseDataCallback, timecourse_handle}, 'userdata', outputDir); + +% Save figure data menu +loadTimecourseDataMenu = uimenu(optionsMenu, 'label', 'Load Figure Parameters', 'callback', ... + {@loadTimecourseDataCallback, timecourse_handle}, 'userdata', outputDir); + +% Procedure: Initial plot will be an exact replica of the draw time courses +% figure but plots in expanded view. Options can be selected using ICA +% Options window. The results can be viewed using plot button. + +% draw axis +axesPosition = [0.05 .1 .8 .8]; +axesTag = 'plot'; +% draw plot button +plotWidth = 0.1; plotHeight = 0.1; +pos = [axesPosition(1) + axesPosition(3) + 0.02 0.5 - 0.5*plotHeight plotWidth plotHeight]; +plotH = icatb_uicontrol('parent', timecourse_handle, 'units', 'normalized', 'style', 'pushbutton', 'string', ... + 'Plot', 'position', pos, 'callback', {@plotTC_expandedMode, timecourse_handle}, 'tag', 'plot_button'); +figureData.axesPosition = axesPosition; +figureData.axesTag = axesTag; + +set(timecourse_handle, 'userdata', figureData); + +plotTC_expandedMode(plotH, [], timecourse_handle); % execute the plot time course callback + +function plotTC_expandedMode(handleObj, event_data, handles) +% plot time courses in expanded mode + +% get the options from the Time course options menu +% pass the handle visibility off +% get the results here. + +% use the undetrended timecourse +% apply smoothing defaults +% remove the mean (detrend(.., 0)) +% use the sorting criteria as selected in sort components GUI + +% adjust ICA uses the modeling parameters to remove the nuisance parameters +% and plots in the same axis + +% Utilities menu use the options from the plot of the timecourse: +% 1ike split timecourse, event average + +set(handles, 'pointer', 'watch'); + +if ~exist('flag_calculate_stats', 'var') + flag_calculate_stats = 'yes'; +end + +% set the fields from timecourse options to figure data +figureData = get(handles, 'userdata'); % get the figure data + +%%%%%%%%%%%% Options from options window %%%%%%%%%%%%%%%%%%%% +% get the options from the Time course options menu +% pass the handle visibility off +% get the results here. +optionsWindowCallback(figureData.optionsMenu, [], handles, 'off'); % options callback +input_parameters = get(figureData.optionsMenu, 'userdata'); % input parameters +timeCourseOptions = input_parameters.results; % get the time course options +clear input_parameters; +%%%%%%%%%%%% End of Options from options window %%%%%%%%%%%%%%%%%%%% +timecourseFields = fieldnames(timeCourseOptions); % get all the fields + +for ii = 1:length(timecourseFields) + figureData = setfield(figureData, timecourseFields{ii}, getfield(timeCourseOptions, timecourseFields{ii})); +end + +clear timecourseFields; +clear timeCourseOptions; + +% get all the options from the options window +smoothPara = figureData.icaSmoothPara; +smoothValue = figureData.icaSmoothValue; +modelNormalize = figureData.modelNormalize; +%modelZeroMean = figureData.modelZeroMean; +modelLinearDetrend = figureData.modelLinearDetrend; +icaDetrend = figureData.icaDetrend; +icaFlip = figureData.icaFlip; +icaSmoothPara = figureData.icaSmoothPara; +icaSmoothValue = figureData.icaSmoothValue; +eventWindowSize = figureData.eventWindowSize; +eventInterpFactor = figureData.eventInterpFactor; + +% data sets information +num_DataSets = figureData.num_DataSets; +numSubjects = figureData.numSubjects; +numSessions = figureData.numSessions; +diffTimePoints = []; +if isfield(figureData, 'sortParameters') + % different time points variable + if isfield(figureData.sortParameters, 'diffTimePoints') + diffTimePoints = figureData.sortParameters.diffTimePoints; + else + diffTimePoints = figureData.diffTimePoints; + end +end + +% Depending on the title name +% Select the appropriate sorting criteria +title_fig = get(handles, 'name'); +compareTitle = lower(title_fig); +sortingCriteria = []; +sortingType = []; + +if isfield(figureData, 'sortParameters') + sortingCriteria = lower(figureData.sortParameters.sortingCriteria); + sortingType = lower(figureData.sortParameters.sortingType); +end + +% load defaults +icatb_defaults; + +% Screen Color Defaults +global BG_COLOR; +global BG2_COLOR; +global FG_COLOR; +global AXES_COLOR; +global FONT_COLOR; +global LEGENDCOLOR; + +currentAxes = get(handles, 'currentaxes'); + +delete(currentAxes); + +axisH = axes('parent', handles, 'position', figureData.axesPosition, 'tag', figureData.axesTag); + +%%%%%%%%%%% Time course calculations %%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Use original ICA Timecourse and detrend ICA by removing mean +undetrendICA = figureData.undetrendICA; + +if isempty(sortingType) | strcmp(sortingType, 'spatial') + % remove the mean using the specified information in the options window + timecourse = icatb_detrend(undetrendICA, num_DataSets, diffTimePoints, icaDetrend); +else + timecourse = icatb_detrend(undetrendICA, num_DataSets, diffTimePoints, 0); % remove the mean +end + +%timecourse = figureData.icaTimecourse; + +% apply smoothing values +timecourse = icatb_smoothTimecourse(timecourse, diffTimePoints, num_DataSets, 1, ... + icaSmoothPara, icaSmoothValue); + +% ica timecourse calculations +if icaFlip == 1 + timecourse = timecourse*-1; +end +%%%%%%%%%%% End for Time course calculations %%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +%%%%%%%%%%%%%%%%%% MODEL TC Calculations %%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Model Timecourse calculations +if ~isempty(figureData.modelTimecourse) + % get the model time course + modelTimecourse = figureData.modelTimecourse; + + if modelLinearDetrend == 1 + % remove the linear trend + modelTimecourse = icatb_detrend(modelTimecourse, num_DataSets, diffTimePoints, 1); + end + + % if modelZeroMean == 1 + % % remove the mean + % modelTimecourse = icatb_detrend(modelTimecourse, num_DataSets, diffTimePoints, 0); + % end + % normalize the model time course + if modelNormalize == 1 + modelTimecourse = icatb_normalizeTimecourse(modelTimecourse, timecourse, diffTimePoints, num_DataSets); + end +end + +%%%%%%%%%%%%%%%%%% End for Model Time course Calculations %%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Plot appropriate sorting criteria title +if strcmp(sortingCriteria, 'correlation') & ~strcmp(sortingType, 'spatial') + [sortingVal, timecourse] = icatb_correlateFunctions(modelTimecourse, timecourse, num_DataSets, diffTimePoints, icaDetrend); + titlestr = ['Correlation = ', num2str(sortingVal)]; +elseif strcmp(sortingCriteria, 'kurtosis') & ~strcmp(sortingType, 'spatial') + [sortingVal, timecourse] = icatb_kurtosis(timecourse, num_DataSets, diffTimePoints, icaDetrend); + titlestr = ['Kurtosis = ', num2str(sortingVal)]; + % Plot the linefit to model timecourse and the ICA timecourse +elseif strcmp(sortingCriteria, 'multiple regression') & ~strcmp(sortingType, 'spatial') + [sortingVal, bRegress, ModelIndices, otherIndices, linearRegress, removeTrend, timecourse] = ... + icatb_multipleRegression(modelTimecourse, timecourse, size(modelTimecourse, 2), num_DataSets, ... + diffTimePoints, icaDetrend); + % store the data for adjusting timecourses + adjustData = struct('bRegress', bRegress, 'ModelIndices', ModelIndices, 'otherIndices', otherIndices, ... + 'linearRegress', linearRegress, 'removeTrend', removeTrend, 'icaLine', 'icaline'); + + set(figureData.adjustICAMenu, 'userdata', adjustData); + + titlestr = ['R-Square Statistic = ', num2str(sortingVal)]; +else + titlestr = title_fig; +end + +titlestr = [titlestr, ' (Temporal Detrend value = ' num2str(icaDetrend), ')']; + +figureData.timecourse = timecourse; % set the field time course to figure data +if num_DataSets > 1 + parameters.numSubjects = numSubjects; % number of subjects + parameters.numSessions = numSessions; % number of sessions + parameters.titleFig = 'Time courses window'; + %parameters.timecourse = timecourse; % time course + if exist('modelTimecourse', 'var') + parameters.modelTimecourse = modelTimecourse; % model time course + else + parameters.modelTimecourse = []; + end + set(figureData.splitTimecourseMenu, 'userdata', parameters); % split time courses menu +end + +storeHandlesCount = 0; legendString = {}; + +% check the model time courses +if ~isempty(figureData.modelTimecourse) + referenceString = 'Reference Function'; + + + %KND: + [nrows, ncols] = size(modelTimecourse); + referenceString = repmat({'Reference Function'},ncols,1); + + %if length(figureData.sortParameters.refInfo.selectedRegressors)==1 + referenceString = cellstr(figureData.sortParameters.refInfo.selectedRegressors.name); + %end + + % plot the reference functions and append the legend string + % Plot all the model timecourses + + for i = 1:ncols + modelPlotHandle(i) = plot(modelTimecourse(:, i), 'y:', 'parent', axisH, 'tag', 'regressor'); + set(modelPlotHandle(i), 'ButtonDownFcn', [ ... + 'set(findobj(gcbf, ''tag'', ''regressor'', ''Type'', ''line''),''Color'',''y'',''LineWidth'',1,''LineStyle'', '':'');' ... + 'set(gcbo,''LineWidth'',2,''LineStyle'', '':'',''Color'', ''y'')' ... + ]); + legendString{length(legendString) + 1} = referenceString{i}; + hold on; + end + % store handles to be used later for plotting legend + storeHandlesCount = storeHandlesCount + 1; + %legendString{length(legendString) + 1} = referenceString; % store the reference string + storeHandles(storeHandlesCount) = modelPlotHandle(end); % store only the end handle + hold on; + if strcmp(sortingCriteria, 'multiple regression') & ~strcmp(sortingType, 'spatial') + % Plot ICA Timecourses + icaTimecourseLine = plot(timecourse, 'm', 'tag', adjustData.icaLine, 'parent', axisH); + hold on; + storeHandlesCount = storeHandlesCount + 1; + storeHandles(storeHandlesCount) = icaTimecourseLine; + legendString{length(legendString) + 1} = 'ICA Timecourse'; + % % plot regressor + lineRegressH = plot(linearRegress, '-.c', 'parent', axisH); + hold off; + storeHandlesCount = storeHandlesCount + 1; + storeHandles(storeHandlesCount) = lineRegressH; + legendString{length(legendString) + 1} = 'Linefit to ICA'; + else + % Plot ICA Time course + icaTimecourseLine = plot(timecourse, 'm', 'parent', axisH); + storeHandlesCount = storeHandlesCount + 1; + storeHandles(storeHandlesCount) = icaTimecourseLine; + legendString{length(legendString) + 1} = 'ICA Timecourse'; + hold off; + end +else + icaTimecourseLine = plot(timecourse, 'm', 'parent', axisH); + storeHandlesCount = storeHandlesCount + 1; + storeHandles(storeHandlesCount) = icaTimecourseLine; + legendString{length(legendString) + 1} = 'ICA Timecourse'; + hold off; +end + +icatb_legend(legendString{:}); + +% Plot a dotted line separating the subjects +% Change later to incorporate different timepoints for each subject +if num_DataSets > 1 + lengthTotalTimecourse = length(timecourse); + %lengthIndividualTimecourse = lengthTotalTimecourse/num_DataSets; + axisYlim = get(axisH, 'ylim'); + ySpacing = (axisYlim(2) - axisYlim(1))/4; + plotYY = (axisYlim(1):ySpacing:axisYlim(2)); + for numdataSets = 2:num_DataSets + hold on; + %lengthIndividualTimecourse = sum(figureData.refInfo.diffTimePoints(1:numdataSets - 1)); + %valX = lengthIndividualTimecourse*(numdataSets - 1); + valX = sum(figureData.sortParameters.diffTimePoints(1:numdataSets - 1)); + plotXX(1:length(plotYY)) = valX; + plot(plotXX, plotYY, '--g', 'parent', axisH); + end +end + +axis(axisH, 'tight'); + +set(axisH, 'YColor', FONT_COLOR, 'XColor', FONT_COLOR); + +set(handles, 'userdata', figureData); + +clear figureData; + +hold off; + +title(titlestr, 'parent', axisH); +set(handles, 'pointer', 'arrow'); + +%%%%%%%%%%%%%%%%%% Function callbacks %%%%%%%%%%%%%%%% +function fftCallback(hObject, event_data, handles) +% powerSpectrum + +psdFile = which('psd.m'); + +if ~isempty(psdFile) + + figureData = get(handles, 'userdata'); + + icatb_defaults; + % Screen Color Defaults + global BG_COLOR; + global BG2_COLOR; + global FG_COLOR; + global AXES_COLOR; + global FONT_COLOR; + global SMOOTHINGVALUE; + global SMOOTHPARA; + + fftHandle = icatb_getGraphics('Power Spectrum', 'normal', 'Power Spectrum Figure'); + timecourse = figureData.timecourse; + fftH = axes('parent', fftHandle, 'units', 'normalized', 'position', [0.1 0.1 0.8 0.8]); + % calculate power spectrum + psd(timecourse, 500); + axis(fftH, 'tight'); + set(fftH, 'YColor', FONT_COLOR, 'XColor', FONT_COLOR); + % set the color to magenta + set(get(gca, 'children'), 'color', [1 0 1]); + clear figureData; +else + disp('Need signal processing toolbox to view power spectrum'); + return; +end +% end for checking psd + +% Splits time courses in the main window if there are more than one time +% course +function splitTimecoursesCallback(handleObj, evd, handles) + +% get the user data associated with the push button +parameters = get(handleObj, 'userdata'); +handles_data = get(handles, 'userdata'); +% Get the variables here +numSubjects = parameters.numSubjects; +numSessions = parameters.numSessions; +titleFig = parameters.titleFig; +%timecourse = parameters.timecourse; +timecourse = handles_data.timecourse; +modelTimecourse = parameters.modelTimecourse; +diffTimePoints = []; +% get different time points +if isfield(handles_data, 'sortParameters') + diffTimePoints = handles_data.sortParameters.diffTimePoints; +end +% convert all vars to structure format +[timeCourseStruct, modelTimeCourseStruct, xAxis] = icatb_convertTo_struct('timecourse', timecourse, 'model', ... + modelTimecourse, 'numSubjects', numSubjects, 'numSessions', numSessions, 'difftimepoints', diffTimePoints); + +% show multiple plots in a figure +icatb_showTimeCourses('TC', timeCourseStruct, 'x_axis', xAxis, 'numsubjects', numSubjects, ... + 'numsessions', numSessions, 'titlefig', 'Splitting Time courses', 'meandisplay', 'yes', 'SEM', ... + 'yes', 'model', modelTimeCourseStruct, 'timecourse_color', 'm', 'model_timecourse_color', 'y:'); + +function eventRelatedCallback(hObject, evd, handles) + +% Computes the event related averages. Gets the ICA time course under +% consideration. If the units is seconds then selected onsets will be +% divided by TR. +% get the event related vector (correct Onset???). Interpolate the time course by a factor +% which is factor to multiply * TR. + +% Get the related sequence where the events occur + +% get the user data +figureData = get(handles, 'userdata'); + +eventAvgObjTag = get(hObject, 'tag'); + +if strcmpi(eventAvgObjTag, 'event_avg_regular') + figTitle = 'Event Average (Regular Method)'; + fprintf('\n'); + disp('Using regular method to compute event average ...'); + fprintf('\n'); +else + figTitle = 'Event Average (Deconvolution Method)'; + fprintf('\n'); + disp('Using deconvolution method to compute event average ...'); + fprintf('\n'); +end + +% get the options from the options menu handle +optionsWindowCallback(figureData.optionsMenu, [], handles, 'off'); % options callback +input_parameters = get(figureData.optionsMenu, 'userdata'); % input parameters +timeCourseOptions = input_parameters.results; % get the time course options +clear input_parameters; +%%%%%%%%%%%% End of Options from options window %%%%%%%%%%%%%%%%%%%% + +timecourseFields = fieldnames(timeCourseOptions); % get all the fields +% set the figure data with the corresponding fields +for ii = 1:length(timecourseFields) + figureData = setfield(figureData, timecourseFields{ii}, getfield(timeCourseOptions, timecourseFields{ii})); +end + +icatb_defaults; + +global FONT_COLOR; + +% Window size +windowSize = figureData.eventWindowSize; % in seconds +interpFactor = figureData.eventInterpFactor; % interpolation factor + +eventData = struct('eventInterpFactor', interpFactor, 'eventWindowSize', windowSize); + +icaTimecourse = figureData.timecourse; % time course + +% Get the information about the data sets here +% number of subjects and sessions +num_DataSets = figureData.num_DataSets; +numSubjects = figureData.numSubjects; +numSessions = figureData.numSessions; +numOfSub = figureData.numOfSub; +numOfSess = figureData.numOfSess; +actualDataSets = numOfSub*numOfSess; +detrendNumber = figureData.icaDetrend; + +% get the subject string to be displayed as a string in listbox +if numSubjects > 1 & numSessions > 1 + count = 0; + for ii = 1:numSubjects + for jj = 1:numSessions + count = count + 1; + subject_string(count).name = ['Subject ', num2str(ii), ' Session ', num2str(jj)]; + end + end +elseif numSubjects > 1 & numSessions == 1 + for ii = 1:numSubjects + subject_string(ii).name = ['Subject ', num2str(ii)]; + end +elseif numSubjects == 1 & numSessions > 1 + for ii = 1:numSessions + subject_string(ii).name = ['Session ', num2str(ii)]; + end +else + subject_string.name = ['Subject''s Session']; +end + +diffTimePoints = []; +% get different time points +if isfield(figureData, 'sortParameters') + diffTimePoints = figureData.sortParameters.diffTimePoints; + if isfield(figureData.sortParameters, 'session_number') + data_sessionNumber = figureData.sortParameters.session_number; + end +end + +% check the spm mat flag +if isfield(figureData, 'spmMatFlag') + spmMatFlag = figureData.spmMatFlag; +else + spmMatFlag = 'not_specified'; +end + +clear figureData; +% convert timecourses to required structure format: incorporate different +% time points +[timeCourses] = icatb_convertTo_struct('timecourse', icaTimecourse, 'numSubjects', numSubjects, 'numSessions', ... + numSessions, 'diffTimePoints', diffTimePoints); + +clear icaTimecourse; + +% get the figure data +refInfo = get(hObject, 'userdata'); + +%%%%%%%%%%%%%%%%% REGRESSOR GUI %%%%%%%%%%%%%%%%%%% +[selectedRegressors] = icatb_returnRegressor(refInfo, num_DataSets, numSubjects, ... + numSessions, spmMatFlag, subject_string); + +countDataSet = 0; +% Loop over number of subjects and sessions +for numSub = 1:numSubjects + % check if the size of the SPM file is greater than one + if size(refInfo.SPMFile, 2) > 1 + spmFileNumber = (numSub - 1)*numSessions + 1; + % get the current spm file + SPMfileName = refInfo.SPMFile(spmFileNumber).name; + spmData = refInfo.spmAppData(spmFileNumber).data; + else + % get the current spm file + SPMfileName = refInfo.SPMFile.name; + % check the special case for session specific regressors + if length(refInfo.spmAppData) > 1 + spmData = refInfo.spmAppData(1).data; + else + spmData = refInfo.spmAppData.data; + end + end + + % SPM information + spmVar = spmData.SPM; + + flag_refFunc = spmData.flag_refFunc; + + clear spmData; + + % get the SPM mat file + TimeResponse = spmVar.xY.RT; + + % Original Interpolation factor + origInterpFactor = eventData.eventInterpFactor; + + % Interpolation factor + interpFactor = ceil(origInterpFactor*TimeResponse); + + % loop over the sessions + for numSess = 1:numSessions + countDataSet = countDataSet + 1; + % pull the session number from the selected regressors + currentRegressor = deblank(selectedRegressors(countDataSet, :)); % get the current regressor + % get the onsets and data session number using the regressor + % name + + if strcmp(lower(flag_refFunc), 'session_specific') + if numSessions == numOfSess + data_sessionNumber = numSess; + end + [temp_data_sessionNumber, onset_number] = icatb_get_onsets(currentRegressor, spmVar); + else + [data_sessionNumber, onset_number] = icatb_get_onsets(currentRegressor, spmVar); + end + + if numSubjects*numSessions == 1 + % displaying the reference function + disp(['Selected reference function to compute event related average for subject''s session is ', currentRegressor]); + elseif numSubjects == 1 & numSessions > 1 + % displaying the reference function + disp(['Selected reference function to compute event related average for session ', num2str(numSess), ' is ', currentRegressor]); + elseif numSessions == 1 & numSubjects > 1 + % displaying the reference function + disp(['Selected reference function to compute event related average for subject ', num2str(numSub), ' is ', currentRegressor]); + else + % displaying the reference function + disp(['Selected reference function to compute event related average for subject ', num2str(numSub), ... + ' session ', num2str(numSess), ' is ', currentRegressor]); + end + + % % determine the selected onset + % % or current onset number + if data_sessionNumber > length(spmVar.Sess) + data_sessionNumber = length(spmVar.Sess); + end + + %%%%%% Modifying selected onset + if strcmp(lower(spmVar.xBF.UNITS), 'scans') + selectedOnset = round(spmVar.Sess(data_sessionNumber).U(onset_number).ons); + else + selectedOnset = round((spmVar.Sess(data_sessionNumber).U(onset_number).ons) / TimeResponse); + end + + timeCourses.sub(numSub).sess(numSess).tc = icatb_detrend(timeCourses.sub(numSub).sess(numSess).tc, 1, ... + length(timeCourses.sub(numSub).sess(numSess).tc), detrendNumber); + + if strcmpi(eventAvgObjTag, 'event_avg_regular') + % Calculate event average + eventAvg = icatb_calculate_eventAvg(timeCourses.sub(numSub).sess(numSess).tc, origInterpFactor, TimeResponse, eventData.eventWindowSize, selectedOnset); + timeAxis = (1:length(eventAvg)) / origInterpFactor; % time axis + else + eventAvg = icatb_calculate_eventAvg_deconv(timeCourses.sub(numSub).sess(numSess).tc, TimeResponse, eventData.eventWindowSize, selectedOnset); + timeAxis = (1:length(eventAvg)); + end + + timeCourseStruct.sub(numSub).sess(numSess).tc = eventAvg; % event average + xAxis.sub(numSub).sess(numSess).tc = timeAxis; % time axis + end + if exist('spmVar', 'var') + clear spmVar; + end +end +% end for loop over number of subjects and sessions + + +% number of data sets is more than 1 +if num_DataSets == 1 + % if the number of data sets is 1 else show the plots in a figure + % browse + + plotH = icatb_getGraphics(figTitle, 'normal', 'figure'); + + plot(timeAxis, eventAvg, 'm'); + + title(figTitle, 'color', FONT_COLOR, 'HorizontalAlignment', 'center'); + + xlabel(['Time in seconds where ', ' window size = ', num2str( eventData.eventWindowSize)]); + + set(gca, 'YColor', FONT_COLOR, 'XColor', FONT_COLOR, 'position', [0.1 0.1 0.8 0.8]); + + axis(gca, 'tight'); + +else + icatb_showTimeCourses('TC', timeCourseStruct, 'x_axis', xAxis, 'numsubjects', numSubjects, 'numsessions', numSessions, ... + 'titlefig', figTitle, 'meandisplay', 'yes', 'SEM', 'yes', 'timecourse_color', 'm'); +end + +% context callback +function adjustICACallback(hObject, evd, handles) +% context menu callback +% open figure window prompting the user to select the reference function +% remove the nuisance parameters and the other model coefficients from the +% ica timecourse +% plot the new ica timecourse + +% get the userdata +adjustData = get(hObject, 'userdata'); + +% store the data for adjusting timecourses +bRegress = adjustData.bRegress; ModelIndices = adjustData.ModelIndices; +otherIndices = adjustData.otherIndices; linearRegress = adjustData.linearRegress; +removeTrend = adjustData.removeTrend; +icaLine = adjustData.icaLine; + +% figure data +figData = get(handles, 'userdata'); + +timecourse = figData.timecourse; +detrendNumber = figData.icaDetrend; + +% check the spm mat flag +if isfield(figData, 'spmMatFlag') + spmMatFlag = figData.spmMatFlag; +else + spmMatFlag = 'not_specified'; +end + +% data information +numSubjects = figData.numSubjects; +numSessions = figData.numSessions; +num_DataSets = figData.num_DataSets; +modelTimecourse = figData.modelTimecourse; + +% reference function information +if ~isfield(figData, 'sortParameters') + error('sortParameters field is missing in figData'); +end +diffTimePoints = figData.sortParameters.diffTimePoints; +refInfo = figData.sortParameters.refInfo; +num_Regress = size(refInfo.modelIndex, 2); + +% spm file names +SPMFile = refInfo.SPMFile; + +if length(SPMFile) > 1 + % spmNames + spmNames = str2mat(SPMFile.name); +else + spmNames = SPMFile.name; +end + +% % details of the help push button +% helpDetails.title = 'Adjust ICA time course'; +% +% D(1).string = ['For adjusting ICA time-course, only one reference function is used. Please click on the left top listbox to select the data set and the reference functions for that data set will be displayed in the left bottom listbox.']; +% D(size(D,2)+1).string = ''; +% D(size(D,2)+1).string = ['Select the reference function in the left bottom listbox and the selected string will appear in the right top listbox. These selections can be made as long as Ok button is pressed.']; +% str = {D.string}; + +% string for help button +%helpDetails.str = str; + +% get the subject string to be displayed as a string in listbox +if numSubjects > 1 & numSessions > 1 + count = 0; + for ii = 1:numSubjects + for jj = 1:numSessions + count = count + 1; + subject_string(count).name = ['Subject ', num2str(ii), ' Session ', num2str(jj)]; + end + end +elseif numSubjects > 1 & numSessions == 1 + for ii = 1:numSubjects + subject_string(ii).name = ['Subject ', num2str(ii)]; + end +elseif numSubjects == 1 & numSessions > 1 + for ii = 1:numSessions + subject_string(ii).name = ['Session ', num2str(ii)]; + end +else + subject_string.name = ['Subject''s Session']; +end + +if (size(refInfo.modelIndex, 2) == 1) + icatb_dialogBox('title', 'Adjust ICA', 'textBody', 'Cannot adjust ICA timecourse as only one regressor is selected during sorting.', ... + 'textType', 'large'); + return; +end + +%%%%%%%%%%%%%%%%% REGRESSOR GUI %%%%%%%%%%%%%%%%%%% + +[selectedRegressors, selectedIndices] = icatb_returnRegressor(refInfo, num_DataSets, numSubjects, ... + numSessions, spmMatFlag, subject_string, 'adjust_ica'); + +% Remove the nuisance parameters and the other than selected model indices +rowStart = 1; +for nn = 1:num_DataSets + rowEnd = sum(diffTimePoints(1:nn)); + % Regressor matrix + [X] = icatb_modelX(modelTimecourse(rowStart:rowEnd, :), diffTimePoints(nn), detrendNumber); + % Total terms + TotalTerms = size(X, 2); + regressIndices = [1:TotalTerms]; + % Not selected indices + not_selected_indices = find(regressIndices ~= selectedIndices(nn)); + % Other indices + otherIndxs = TotalTerms*(nn - 1) + (num_Regress + 1 : TotalTerms); + % Model indices + modelIndxs = TotalTerms*(nn - 1) + (1:num_Regress); + allIndxs = [modelIndxs, otherIndxs]; + notSelIndices = allIndxs(not_selected_indices); + timecourse(rowStart:rowEnd) = timecourse(rowStart:rowEnd) - X(:, not_selected_indices)*bRegress(notSelIndices); + rowStart = rowEnd + 1; +end + +icaTimecourseLine = findobj(handles, 'tag', icaLine); + +axisH = get(handles, 'currentaxes'); + +newStr = ['ICA time course (ICA tc) adjusted by the selected reference function. Click plot to view the old ICA tc.']; +title(newStr, 'parent', axisH); + +% plot the adjusted time course +% Only plot the adjusted time course and don't calculate the ICA time +% course +set(icaTimecourseLine, 'Ydata', timecourse); + +axis(axisH, 'tight'); + +figData.timecourse = timecourse; + +set(handles, 'userdata', figData); + +function optionsWindowCallback(hObject, event_data, handles, figVisibility) +% hObject - menu string +% handles - time course figure + +if ~exist('figVisibility', 'var') + figVisibility = 'on'; +end +input_parameters = get(hObject, 'userdata'); % get the menu user data +defaults = input_parameters.defaults; % get the defaults +inputParameters = input_parameters.inputParameters; % get the input parameters +clear input_parameters; +% plot the figure window to display the options +[output_parameters, valueButton] = icatb_OptionsWindow(inputParameters, defaults, figVisibility); +input_parameters.inputParameters = output_parameters.inputParameters; +input_parameters.defaults = defaults; +input_parameters.results = output_parameters.results; % get the results +set(hObject, 'userdata', input_parameters); % set the object user data (updated options) +% Show the title after the options are updated by clicking on the ok button +if valueButton == 1 + plotH = findobj(handles, 'tag', 'plot_button'); + plotTC_expandedMode(plotH, [], handles); % execute the plot time course callback + % % set the title at the plot window + % axisH = get(handles, 'currentaxes'); + % newStr = ['Click plot to view the time courses with the updated options.']; + % title(newStr, 'parent', axisH); + + % call the plot function here + +end + +function saveTimecourseDataCallback(hObject, event_data, handles) +% save figure data + +outputDir = get(hObject, 'userdata'); +if isempty(outputDir) + outputDir = pwd; +end +figureData = get(handles, 'userdata'); + +% open input dialog box +prompt = {'Enter Valid File Name:'}; +dlg_title = 'Save Figure Parameters as'; +num_lines = 1; +def = {'TimecourseParameters'}; +% save the file with the file name specified +fileName = icatb_inputdlg2(prompt, dlg_title, num_lines, def); + +if ~isempty(fileName) + % make a full file + fileName = [fileName{1}, '.mat']; + fileName = fullfile(outputDir, fileName); + icatb_save(fileName, 'figureData'); + disp(['Figure parameters are saved in file: ', fileName]); +end + +function loadTimecourseDataCallback(hObject, event_data, handles) +% load figure data + +try + outputDir = get(hObject, 'userdata'); + + global FIGURE_DATA + + % open file selection box + [P] = icatb_selectEntry('typeEntity', 'file', 'title', 'Select Timecourse Parameters File', 'filter', '*.mat', ... + 'startPath', outputDir); + if ~isempty(P) + load(P); + if ~exist('figureData', 'var') + error('Not a valid timecourse parameters file'); + end + FIGURE_DATA = figureData; + clear figureData; + D(1).string = 'Global FIGURE_DATA variable is created.'; + D(size(D, 2) + 1).string = ''; + D(size(D, 2) + 1).string = 'Type the following statements at the command prompt:'; + D(size(D, 2) + 1).string = ''; + D(size(D, 2) + 1).string = 'global FIGURE_DATA; FIGURE_DATA'; + disp(str2mat(D.string)); + end +catch + icatb_errorDialog(lasterr, 'Figure Parameters'); + icatb_displayErrorMsg; +end \ No newline at end of file diff --git a/icatb/icatb_loadSPM_new.m b/icatb/icatb_loadSPM_new.m new file mode 100644 index 0000000..a239034 --- /dev/null +++ b/icatb/icatb_loadSPM_new.m @@ -0,0 +1,467 @@ +function [spmData] = icatb_loadSPM_new(varargin) + +% Procedure: There are four steps: +% First Step: Check SPM design matrix and do error checking. +% ************** Store the data in spmData ****************** +% Store the following fields: nscan, flag_refFunc ('all' or +% 'session_specfic') and data_sessionNumber. +% Update SPM.Sess and store in spmData as field SPM. +% +% Second Step: Get session specific regressors if possible. +% ************** Store the data in spmData ****************** +% store sel_refnames and sel_indices as fields in spmData +% +% Third Step: Select regressors +% get model time course information as modelT +% store modelT in spmData with the following fields: +% 1. designMatrixName +% 2. selectedRegressors +% 3. name (all regressors available) +% 4. nsess - modified length of scans +% 5. actualIndices W.r.t SPM.xX.name as sel_indices +% ************** Store the data in spmData ****************** +% store modelT information +% +% Fourth Step: Getting time course information +% Use SPM and modelT fields in spmData to get the time courses and modified +% SPM structure +% +% Inputs: +% 1. spmName - full file name of the spm design matrix +% 2. countTimePoints - length of time points for each session and is a +% vector tor like [220 220 ...] depending on the number of sessions used. +% 3. optional argument: sessionNumber to pull out the reference function names +% time courses of that session. +% +% Output: +% spmData containing the information about selected time courses and +% regressors + +% Initialise vars +spmName = []; +countTimePoints = []; +data_sessionNumber = []; % session number is used to pull the reference function names +flag_refFunc = 'all'; % by default pull all the reference functions names and timecourses +analType = 'gui'; % default is GUI +prompt = 'Select Timecourse'; % title of the listbox +typeStr = 'single'; % selection is single by default +maxSelection = []; % Maximum selection +check_spm_design_matrix = 'yes'; +check_regressors = 'no'; +flag_selecting_regressors = 'no'; +get_timecourses = 'no'; +title_fig = 'Reference Time courses'; + +% loop over number of input arguments +for ii = 1:2:nargin + if strcmp(lower(varargin{ii}), 'spmname') + spmName = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'counttimepoints') + countTimePoints = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'data_sessionnumber') + data_sessionNumber = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'analtype') + analType = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'typestr') + typeStr = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'maxselection') + maxSelection = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'flag_selecting_regressors') + flag_selecting_regressors = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'check_spm_design_matrix') + check_spm_design_matrix = lower(varargin{ii + 1}); + elseif strcmp(lower(varargin{ii}), 'check_regressors') + check_regressors = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'get_timecourses') + get_timecourses = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'spmdata') + spmData = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'prompt') + prompt = varargin{ii + 1}; + elseif strcmp(lower(varargin{ii}), 'title_fig') + title_fig = varargin{ii + 1}; + end +end + +try + + if isempty(data_sessionNumber) + data_sessionNumber = 1; + end + + % check the design matrix + if strcmp(check_spm_design_matrix, 'yes') + + % load the spm file + % Note: storing in spmVar as loading SPM design matrix produces SPM variable + % which is same as function name + spmVar = load(spmName); + + % Check the existence of SPM variable + if ~exist('spmVar', 'var') + error('SPM variable doesn''t exist. Please check the .MAT file.'); + end + + fieldNamesOfSPM = fieldnames(spmVar); % get the field names + + spmMat = getfield(spmVar, fieldNamesOfSPM{1}); % get the SPM design matrix here + + clear spmVar; + + % get the number of scans + if isfield(spmMat , 'nscan') + nscan = spmMat.nscan; + else + error('Field nscan doesn''t exist in structure SPM .'); + end + + % number of reference functions + if isfield(spmMat , 'xX') + numRefFunc = length(spmMat.xX.name); + if not(isempty(spmMat.xCon)) + for iCon=1:length(spmMat.xCon) + if isequal('T', spmMat.xCon(iCon).STAT) + spmMat.xX.X = [ spmMat.xX.X spmMat.xX.X(:,1:numRefFunc)*spmMat.xCon(iCon).c ]; + spmMat.xX.name = [spmMat.xX.name {spmMat.xCon(iCon).name}]; + end + end + end + numRefFunc = length(spmMat.xX.name); + else + error('Field xX doesn''t exist in structure SPM .'); + end + + + + errorString = ['SPM design matrix doesn''t match with the data']; + + % Modifying nscan + % check the nscan with the time points + % takes care of different or same session timings + % automatically converts to vector form. + if length(nscan) == 1 + if nscan == sum(countTimePoints) + nscan = countTimePoints; % update nscan with time points + SessInfo = spmMat.Sess; % session information + flag_refFunc = 'session_specific'; % pass flag + else + if nscan == countTimePoints(data_sessionNumber) + data_sessionNumber = 1; % update data_sessionNumber + else + error(errorString); + end + end + else + lengthScan = length(nscan); + lengthTimePoints = length(countTimePoints); + if sum(nscan) == sum(countTimePoints) & lengthScan == lengthTimePoints + if nscan == countTimePoints + flag_refFunc = 'session_specific'; + else + error(errorString); + end + else + matchedIndex = find(nscan == countTimePoints(data_sessionNumber)); % find the matching entries + if isempty(matchedIndex) + error(errorString); + elseif length(matchedIndex) == 1 + data_sessionNumber = matchedIndex; % update the data_sessionNumber + flag_refFunc = 'session_specific'; % pass flag + end + end + end + + if exist('SessInfo', 'var') + % get correct onsets from the vectorized session information + if length(nscan) > length(SessInfo) & length(SessInfo) == 1 + temp = repmat(SessInfo, 1, length(nscan)); % replicate with length of the nscan + % loop over number of onsets + for jj = 1:length(SessInfo.U) + % get the concatenated onset + currentOnset = SessInfo.U(jj).ons; + startTp = 1; numberToSubtract = 0; + % loop over number of nscan + for ii = 1:length(nscan) + endTp = sum(nscan(1:ii)); + subtractedOnset = currentOnset - numberToSubtract; % get the corrected onset for that session + temp(ii).U(jj).ons = subtractedOnset(find(subtractedOnset < nscan(ii) & subtractedOnset >= 0)); % get the onsets + startTp = endTp + 1; + numberToSubtract = endTp; + end + % end loop for number of nscan + end + % end loop for number of onsets + spmMat.Sess = temp; + clear temp; + end + end + + % clear variables in SPM structure to save memory + xBF.UNITS = spmMat.xBF.UNITS; + repetition_time = spmMat.xY.RT; + spmMat = rmfield(spmMat, 'xBF'); + spmMat.xBF = xBF; + clear xBF; + spmMat = rmfield(spmMat, 'xY'); + spmMat.xY.RT = repetition_time; + + + % remove all the other fields + fieldsReq1 = {'nscan', 'xX', 'xBF', 'xY', 'Sess'}; + % include only the required fields + spmMat = icatb_includeFields_struct(spmMat, fieldsReq1); + clear fieldsReq1; + Sess_new = spmMat.Sess; + spmMat = rmfield(spmMat, 'Sess'); + + if isfield(Sess_new, 'U') + + if ~isempty(Sess_new(1).U) + Sess_new = icatb_includeFields_struct(Sess_new, {'U'}); + fieldsReq1 = {'name', 'ons'}; + % include only the required fields + for ii = 1:length(Sess_new) + Sess_new(ii).U = icatb_includeFields_struct(Sess_new(ii).U, fieldsReq1); + end + clear fieldsReq1; + end + + end + + spmMat.Sess = Sess_new; + clear Sess_new; + + % remove unnecessary fields + XField = spmMat.xX.X; + nameField = spmMat.xX.name; + spmMat = rmfield(spmMat, 'xX'); + spmMat.xX.X = XField; + spmMat.xX.name = nameField; + clear XField; clear nameField; + + + spmMat.nscan = nscan; + % store the data in spmData + spmData.SPM = spmMat; + spmData.nscan = nscan; + spmData.flag_refFunc = flag_refFunc; + spmData.data_sessionNumber = data_sessionNumber; + clear spmMat; + end + % end for checking SPM design matrix + + % get session specific regressors if possible + if strcmp(lower(check_regressors), 'yes') + if ~exist('spmData', 'var') + error('spmData structure should be passed'); + end + spmMat = spmData.SPM; % number of scans + nscan = spmData.nscan; + flag_refFunc = spmData.flag_refFunc; + data_sessionNumber = spmData.data_sessionNumber; + %%%%%%%%%%%%%%%%%%% + % selection process + + allNames = spmMat.xX.name; % all reference function names + % Initialise selected reference function names and indices + sel_refnames = {}; + sel_indices = []; + if strcmp(lower(flag_refFunc), 'session_specific') & ~isempty(data_sessionNumber) + count = 0; + % pull the session specific or all regressors names + for ii = 1:numRefFunc + firstBracket = find(allNames{ii} == '('); + endBracket = find(allNames{ii} == ')'); + if isempty(firstBracket) || isempty(endBracket) + warning('Contrasts appear in all sessions') + currentNumber = data_sessionNumber;%:length(spmMat.Sess); + else + currentNumber = str2num(allNames{ii}(firstBracket(1) + 1:endBracket(1) - 1)); % get the session number + end + if currentNumber == data_sessionNumber + count = count + 1; + sel_refnames{count} = allNames{ii}; + sel_indices(count) = ii; + end + end + end + % check if the selected reference function names is empty + if isempty(sel_refnames) + sel_refnames = allNames; + sel_indices = (1:length(sel_refnames)); + end + + for ii = 1:length(sel_refnames) + options(ii).string = sel_refnames{ii}; + end + sel_refnames = str2mat(options.string); % convert cell to matrix + clear options; + % store the data + spmData.sel_refnames = sel_refnames; % selected reference function names + spmData.sel_indices = sel_indices; % selected session specific indices + end + % end for checking regressors + + % get the regressors of interest + if strcmp(lower(flag_selecting_regressors), 'yes') + if ~exist('spmData', 'var') + error('spmData structure should be passed'); + end + sel_refnames = spmData.sel_refnames; % selected reference function names + sel_indices = spmData.sel_indices; % selected session specific indices + spmMat = spmData.SPM; + nscan = spmData.nscan; + + % get the indices of the selected regressor names + if strcmp(lower(analType), 'batch') + if isfield(design_Info, 'refFunNames') + selectedRefFunNames = design_Info.refFunNames; + else + error('Specify the reference function names for the batch analysis'); + end + % check the index + for ii = 1:length(selectedRefFunNames) + tempIndex = strmatch(lower(selectedRefFunNames{ii}), lower(sel_refnames), 'exact'); + if isempty(tempIndex) + error(['Specified reference function with name ', selectedRefFunNames{ii}, ' doesn''t exist']); + end + % store the indices + getIndex(ii) = tempIndex; + end + else + if strcmp(typeStr, 'single') + [getIndex, name_button] = icatb_listdlg('PromptString', prompt, 'SelectionMode','single', 'ListString', sel_refnames, ... + 'movegui', 'center', 'windowStyle', 'modal', 'title_fig', title_fig); + else + if isempty(maxSelection) + [getIndex, name_button] = icatb_listdlg('PromptString', prompt, 'SelectionMode','multiple',... + 'ListString', sel_refnames, 'movegui', 'center', 'windowStyle', 'modal', ... + 'title_fig', title_fig); + else + [getIndex, name_button] = icatb_listdlg('PromptString', prompt, 'SelectionMode','multiple',... + 'ListString', sel_refnames, 'movegui', 'center', 'windowStyle', 'modal', ... + 'maxSelection', maxSelection, 'title_fig', title_fig); + end + end + if isempty(getIndex) + error('Reference function name should be selected in order to select the model time course'); + end + end + clear options; + %get information from SPM design matrix + spmData.selectedRegressors = sel_refnames(getIndex, :); % store the selected regressors + spmData.getIndex = getIndex; + spmData.nsess = length(nscan); % get the number of sessions in design matrix + + end + % end for getting the regressors of interest + + % get the time courses of interest + if strcmp(lower(get_timecourses), 'yes') + if ~exist('spmData', 'var') + error('spmData structure should be passed'); + end + spmMat = spmData.SPM; % get the SPM structure + numRefFunc = length(spmMat.xX.name); % number of reference functions + nscan = spmMat.nscan; % number of scans + data_sessionNumber = spmData.data_sessionNumber; % session number + flag_refFunc = spmData.flag_refFunc; + sel_refnames = spmData.sel_refnames; % selected reference function names + sel_indices = spmData.sel_indices; % selected session specific indices + getIndex = spmData.getIndex; + selectedRegressors = spmData.selectedRegressors; + + % check the size of the time course + if isfield(spmMat.xX, 'X') + % pull the time course + checkX = spmMat.xX.X; + % check the size of the design matrix + sizeX = size(checkX); + + if sizeX(1) == 1 & sizeX(2) == numRefFunc*sum(nscan) + checkX = checkX'; + % check the size of the design matrix + sizeX = size(checkX); + end + + if sizeX(1) == numRefFunc & sizeX(2) == sum(nscan) + checkX = checkX'; + checkX = reshape(checkX, prod(size(checkX)), 1); + % check the size of the design matrix + sizeX = size(checkX); + end + + % modify the model time course as nrows == sum(nscan), ncols = num + % reference functions + %disp('Checking SPM.Mat file ...'); + if sizeX(2) == numRefFunc + %disp('SPM.mat is compatible with the GIFT.'); + elseif sizeX(2) == 1 & sizeX(1) == sum(nscan)*numRefFunc + numberScans = sum(nscan); + temp = zeros(numberScans, numRefFunc); + for ii = 1:numRefFunc + temp(:, ii) = checkX(numberScans*(ii - 1) + 1 : numberScans*ii, 1); + end + clear checkX; + %SPMFile = fullfile(inputDir, 'newSPM.mat'); + spmMat.xX.X = temp; + clear temp; + disp('Modified the model time course to make compatible with the GIFT'); + % save the modified file + %save(SPMFile, 'SPM'); + %disp(['Modified the model time course. Please use the new SPM design matrix ', SPMFile, ' to do temporal sorting.']); + else + disp('The specified design matrix is not compatible with the GIFT software.'); + end + + else + error('Field X doesn''t exist in structure SPM .xX'); + end + + % converted SPM time course to (sum(nscans) by numRefFunc) format + % check if the reference functions are session_specific or all + if strcmp(lower(flag_refFunc), 'session_specific') & ~isempty(data_sessionNumber) + selTimecourses = spmMat.xX.X(:, sel_indices(getIndex)); + startTp = 1; + for ii = 1:data_sessionNumber + endTp = sum(nscan(1:ii)); + temp = selTimecourses(startTp:endTp, :); + startTp = endTp + 1; + end + timecourse = temp; % modified time course + spmData.nsess = 1; % number of sessions + clear temp; + else + for ii = 1:length(getIndex) + % get the data session number + [sesNum] = icatb_get_onsets(deblank(selectedRegressors(ii, :)), spmMat); + if sesNum == 1 + startTp = 1; + endTp = nscan(1); + else + startTp = sum(nscan(1 : sesNum - 1)) + 1; % sum until length of nscans - 1 + endTp = sum(nscan(1:sesNum)); % sum until length of nscans + end + timecourse(:, ii) = spmMat.xX.X(startTp:endTp, sel_indices(getIndex(ii))); + end + end + spmData.timecourse = timecourse; + clear timecourse; + % Fields required: + fieldsRequired = {'xBF', 'xY', 'Sess', 'nscan'}; + spmTemp = struct; + for ii = 1:length(fieldsRequired) + spmTemp = setfield(spmTemp, fieldsRequired{ii}, getfield(spmMat, fieldsRequired{ii})); + end + clear spmMat; + % % clear variables in SPM structure to save memory + spmData.SPM = spmTemp; + + end + % end for getting time courses of interest + +catch + + icatb_displayErrorMsg; + +end \ No newline at end of file diff --git a/idxmember.m b/idxmember.m new file mode 100644 index 0000000..717a11d --- /dev/null +++ b/idxmember.m @@ -0,0 +1,28 @@ +function [loc,nzloc,nmemb]=idxmember(A,S,varargin) +% [loc,nzloc,nmemb]=idxmember(A,S) indexes of values A in the set S. +% loc: indices of values from A found in S (0 if not found) +% nzloc: list of non-null indices, ie: S(nzloc) == intersect(A,S) +% nmemb: values of A that are not in S, ie: nmemb == setdiff(A,S) +% +% [...] = idxmember(A,S,'rows') +% +% See: ISMEMBER + +sizeS=size(S); +sizeA=size(A); +if (iscell(S)) + S=S(:); +end +if ischar(A) + sizeA=[1 1]; +elseif (iscell(A)) + A=A(:); +end +[ignore,loc]=ismember(A,S,varargin{:}); +loc=reshape(loc, sizeA); +if nargout>1 + nzloc=nonzeros(loc); +end +if nargout>2 + nmemb=A(find(loc==0)); +end \ No newline at end of file diff --git a/iff.m b/iff.m new file mode 100644 index 0000000..2bf9dc3 --- /dev/null +++ b/iff.m @@ -0,0 +1,42 @@ +function [x]=iff(test,vt,vf) +% iff - +% [val] = iff(X,vtrue,vfalse) outputs vtrue (resp. vfalse) if X is true +% (resp. false) +% +% vtrue/vfalse can be numeric, char or a cell of char +% X can be a ND array +% +% [val] = iff(X,@fun) returns those values in X that match the test +% function @fun +% +% [val] = iff(X,@fun,vf) returns val(i)=X(i) that match the test +% function @fun, and val(i) = vf otherwise. +% +converted2cell=0; +if isa(vt, 'function_handle') + if ~exist('vf','var') + x=test(vt(test)); + return + else + x=test; + x(~vt(test))=vf; + return + end +end +if isempty(vt) | isempty(vf) | (ischar(vt) & length(vt)>1) | (ischar(vf) & length(vf)>1) + x=repmat([{vt} ; {vf}], [1 size(test)]); + converted2cell=1; +else + x=repmat([vt ; vf], [1 size(test)]); +end +x=x([reshape(logical(test), [1 size(test)]) ; reshape(~logical(test), [1 size(test)]) ]); +x=reshape(x, size(test)); +if converted2cell + if length(x)==1 + x=x{1}; + else + warning('IFF:ConversionToCell', 'array was converted to cell') + end +end + +return diff --git a/image_spm.m b/image_spm.m new file mode 100644 index 0000000..88de1bd --- /dev/null +++ b/image_spm.m @@ -0,0 +1,59 @@ +function [hp]=image_spm(y,v,pos) +% image_spm - display a MRI slice +% [hp]=image_spm(hdr,vol,pos) +% hdr: SPM Analyze header +% vol: SPM Analyze volume +% pos: position of the slice in mm. +% To slice along one direction, put the other dimension to NaN. +% E.g. [NaN NaN 0] will display a Z=0 slice (default) +% + +if nargin<3 + pos=[0 0 0]; +end + +slicing=find(~isnan(pos)); +if length(slicing)~=1 + slicing=3; +end + +xyz=[[eye(3) ; diag(y.dim(1:3))]-1 ones(6,1)]*y.mat'; +xyz=[diag(xyz(1:3,1:3)) diag(xyz(4:6,1:3))]; +dims=y.dim(1:3); +xyz=[xyz dims(:)]; + +% Position of the slice in the voxel cube +vpos=diag(diag(pos(:)-y.mat(1:3,4))*inv(y.mat(1:3,1:3))'); + +switch slicing + case 1 + img=v(vpos(1),:,:); + case 2 + img=v(:,vpos(2),:); + case 3 + img=v(:,:,vpos(3)); +end +xyz(slicing,:)=[pos(slicing) pos(slicing) 1]; + +[X,Y,Z]=ndgrid(... + linspace(xyz(1,1),xyz(1,2),xyz(1,3)),... + linspace(xyz(2,1),xyz(2,2),xyz(2,3)),... + linspace(xyz(3,1),xyz(3,2),xyz(3,3))); +X=squeeze(X); +Y=squeeze(Y); +Z=squeeze(Z); +img=squeeze(img); +if isempty(get(0, 'CurrentFigure')) | isempty(get(gcf, 'CurrentAxes')) + NewAxes=1; +else + NewAxes=0; +end +hp=surf(X,Y,Z,img) +set(hp, 'edgecolor', 'none') +set(hp, 'AlphaData', double(img>0)) +set(hp, 'FaceAlpha', 'interp') +axis image +if NewAxes + view(60,30) +end + diff --git a/imagepval.m b/imagepval.m new file mode 100644 index 0000000..2576581 --- /dev/null +++ b/imagepval.m @@ -0,0 +1,10 @@ +function [hp]=imagepval(p,thd) +% imaepval - image p-values +if nargin<2 + thd=0, +end +imagesc(-log(p)) +colorbar +colormap([.6 .6 .6 ; jet]) +set(gca,'CLim', [-log(thd) max(get(gca,'CLim'))]) + diff --git a/imax.m b/imax.m new file mode 100644 index 0000000..9aa0d6e --- /dev/null +++ b/imax.m @@ -0,0 +1,28 @@ +function [i,v] = imax(x,varargin) +%IMAX - Retrieves the index of the maximum value across multiple dimensions +% [I,V] = imax(X); +% [I,V] = imax(X,[],dim) +% I is the index (in the given dimension) of the maximum +% V is/are the values +% +% Example: +% >> imax(magic(3), [], [1 2]) +% ans= 3 2 +% I.e. the maximum of the magic square is on the 3rd row and 2nd column +% +% See also: max2 + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-20 Creation +% +% ----------------------------- Script History --------------------------------- + + +[v,i]=max2(x,varargin{:}); \ No newline at end of file diff --git a/img_labels.m b/img_labels.m new file mode 100644 index 0000000..8df2729 --- /dev/null +++ b/img_labels.m @@ -0,0 +1,18 @@ +function [h]=img_labels(xyz,ref,labels) +% img_labels - add labels on a MR slice +% [h]=img_labels(xyz,ref,labels) + +if nargin<3 + labels=cellstr(num2str([1:max(ref)]')); +end +h=[]; +for i=unique(ref)' + if i>0 + centroid=mean(xyz(find(i==ref),:),1); + h=[h; .... + text( centroid(1),centroid(2),centroid(3), labels{i}) ... + plot3(centroid(1),centroid(2),centroid(3), 'x', 'MarkerSize', 10)]; + + end +end +set(h(:,1), 'Interpreter', 'none') \ No newline at end of file diff --git a/img_slice.m b/img_slice.m new file mode 100644 index 0000000..1d0196e --- /dev/null +++ b/img_slice.m @@ -0,0 +1,175 @@ +function [hp]=img_slice(hdr,pos,v) +%IMG_SLICE - display a MRI slice +% +% [hp]=img_slice(hdr,pos,v) +% hdr: SPM Analyze header (or filename) +% pos: position of the slice in mm. +% To slice along one direction, put the other dimensions to NaN. +% E.g. [NaN NaN 0] will display a Z=0 slice +% Default, Z=0 if = in the cube, otherwise in the middle +% v: SPM Analyze volume of data (if empty, read the hdr.fname) +% +% [hp]=img_slice(hdr,pos,['calculation'],...) does a calculation on the data +% before plotting 3D data are in X. +% Ex: img_slice(hdr,'X=X(:)-min(X(:))',...) +% Note: Data are reshaped to their original size if vectorized. +% +% Example +% >> img_slice +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-07-03 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<1 + hdr=[]; +end +if nargin<3 + v=[]; +end +if isempty(hdr) && isempty(v) + hdr = fullfile(spm('dir'), 'canonical','single_subj_T1.nii'); + if ~exist(hdr,'file') + hdr = fullfile(spm('dir'), 'canonical','single_subj_T1.img'); + end + if ~exist(hdr,'file') + hdr = fullfile(spm('dir'), 'canonical','single_subj_T1.mnc'); + end +end +if ischar(hdr) + if exist(hdr,'file') + hdr=spm_vol(hdr); + else + error('File doesn''t exist: %s',y) + end +end +if nargin<2 + pos=[]; +end +if ischar(v) + calc=v; + v=[]; +else + calc=[]; +end +if size(calc, 1)>1 + error('Calculation should be a 1-line text'); +end +if isempty(v) + v=spm_read_vols(hdr); +end +if nargin<4 + thd=0; +end +if nargin<5 + dynamic=0; +end + +xyz=[[eye(3) ; diag(hdr.dim(1:3))]-1 ones(6,1)]*hdr.mat'; +xyz=[diag(xyz(1:3,1:3)) diag(xyz(4:6,1:3))]; +dims=hdr.dim(1:3); +XYZ=[xyz dims(:)]; +if isempty(pos) + if XYZ(3,1)<0 & XYZ(3,2)>0 + pos=[NaN NaN 0]; + else + pos=[NaN NaN (XYZ(3,2)-XYZ(3,1))/2]; + end +end +if numel(pos) ~= 3 + error('Position of the slices should be given in XYZ 3-coordinate vector'); +end +pos = pos(:); + +if isempty(get(0, 'CurrentFigure')) | isempty(get(gcf, 'CurrentAxes')) + NewAxes=1; +else + NewAxes=0; +end +holdstate=ishold; +if ~isempty(calc) + [v]=calculation(v,calc); +end + +bbox = [XYZ(:,1:2)]'; + +hp=[]; +for slicing = find(~isnan(pos(:)')); + p=zeros([1 3]); + p(slicing)=pos(slicing); + if not((XYZ(slicing,1)<=p(slicing) & p(slicing)<=XYZ(slicing,2)) | (XYZ(slicing,2)<=p(slicing) & p(slicing)<=XYZ(slicing,1))) + Slice out of bound! + letter = 'XYZ'; + warning('Slice at %s=%g is out of bounds [%g %g]!', letter(slicing), p(slicing), XYZ(slicing,1),XYZ(slicing,2)); + else + + % Position of the slice in the voxel cube + vpos=diag(diag(p(:)-hdr.mat(1:3,4))*inv(hdr.mat(1:3,1:3))'); + + vpos=round(vpos); + switch slicing + case 1 + img=v(vpos(1),:,:); + case 2 + img=v(:,vpos(2),:); + case 3 + img=v(:,:,vpos(3)); + end + xyz=XYZ; + xyz(slicing,:)=[p(slicing) p(slicing) 1]; + + [X,Y,Z]=ndgrid(... + linspace(xyz(1,1),xyz(1,2),xyz(1,3)),... + linspace(xyz(2,1),xyz(2,2),xyz(2,3)),... + linspace(xyz(3,1),xyz(3,2),xyz(3,3))); + X=squeeze(X); + Y=squeeze(Y); + Z=squeeze(Z); + img=squeeze(img); + + hp=[hp surf(X,Y,Z,img)]; + set(hp(end), 'AlphaData', double(img>thd)) + hold on + + l = [bbox].*[logical(p);logical(p)] + ones(2,1)*(pos'.*(~p)) + + line(l(:,1),l(:,2),l(:,3)) + if 1%dynamic + setappdata(hp(end),'data', v); + setappdata(hp(end),'XYZ', XYZ); + setappdata(hp(end),'pos', pos); + end + end +end +if ~isempty(hp) + set(hp, 'edgecolor', 'none') + %set(hp, 'FaceAlpha', 'interp') + set(hp, 'FaceAlpha', 1) + axis image + if NewAxes + view(60,30) + end + if ~holdstate + hold('off') + end +end + + +function [v]=calculation(v,calc) +% Process this independently of the main workspace +X=v; +try + [t,X]=evalc(calc); +catch + evalc(calc); +end +v=reshape(X,size(v)); \ No newline at end of file diff --git a/imgfilt.m b/imgfilt.m new file mode 100644 index 0000000..9777819 --- /dev/null +++ b/imgfilt.m @@ -0,0 +1,143 @@ +function [Y,w,ft,ft2]=imgfilt(X,lf,hf,revfilt,filtorder,phaseshift) +%imgfilt - filters image +% [Y,w,ft,ft2]=imgfilt(X,lf,hf,revfilt,filtorder,phaseshift) +% X: +% lf: lowest frequency in output (default: 0) +% hf: highest frequency in output (default: infinity) +% [lf,hf] produces a bandpass filte or a stop-band if revfilter=1 +% +% revfilt: reverse filter properties +% filteorder: default 50, see: help fir1 +% phaseshift: 'random' = random permutation of phases +%Requires: Image Processing Toolbox + + +if nargin==0 + load mandrill + subplot(2,2,1); imagesc(X) + subplot(2,2,2); imagesc(imgfilt(X,0,10,0,50)); + subplot(2,2,3); imagesc(imgfilt(X,5,50,1)); + subplot(2,2,4); imagesc(imgfilt(X,0,5,[],[],'random')); + colormap(gray) + return +end + +X=double(X); +sx=[size(X) 1]; +fnyquist = min(sx(1),sx(2))/2; +%fnyquist = sx(1)/2; +if nargin<2 + lf=[]; +end +if nargin<3 + hf=[]; +end +if nargin<4 + revfilt = []; +end +if nargin<5 + filtorder = []; +end +if nargin<6 + phaseshift = []; +end + + +if isempty(hf) + hf=inf; +end +if isempty(lf) + lf=0; +end +if isempty(revfilt) + revfilt = 0; +end +if revfilt + if lf==0 + lf=hf; + hf=0; + revfilt=0; + elseif isinf(hf) + hf=lf; + lf=0; + revfilt=0; + end +end +if isempty(filtorder) + filtorder = 50; +end +if ischar(phaseshift) + switch phaseshift + case 'random' + %shouldn't permute the dc component + phaseshift = [1 randperm(prod(sx(1:2))-1)+1]; + end +end + +if ~isempty(phaseshift) + sp=[size(phaseshift) 1]; + if prod(sp(1:2))==prod(sx(1:2)) + phaseshift = reshape(phaseshift,sx(1:2)); + sp=[size(phaseshift) 1]; + end + if sp(1)==1 + phaseshift = repmat(phaseshift, [sx(1) 1 1]); + end + if sp(2)==1 + phaseshift = repmat(phaseshift, [1 sx(2) 1]); + end + if sp(3)==1 + phaseshift = repmat(phaseshift, [1 1 sx(3)]); + end +end + +for ilayer=1:sx(3); + % Compute Fourier transform + ft = fft2(X(:,:,ilayer)); + dc=ft(1); + ft(1)=0; + % Move quadrants so that low freq are in the middle + ft = fftshift(ft); + if isinf(hf) & lf == 0 + % do nothing + ft2 = ft; + else + if isinf(hf) + % User asked for a high-pass filter + w = ftrans2(fir1(filtorder, lf/fnyquist,'high')); + elseif lf==0 + % User asked for a low-pass filter + w = ftrans2(fir1(filtorder, hf/fnyquist)); + else + % User asked for a band-pass / stop-band filter + if revfilt + w = ftrans2(fir1(filtorder, [lf,hf]/fnyquist, 'stop')); + else + w = ftrans2(fir1(filtorder, [lf,hf]/fnyquist, 'bandpass')); + end + end + % Compute filter in the frequency space + w=freqz2(w, size(ft)); + % Apply filter + ft2 = w .* ft; + end + % Restore quadrant positions + ft2 = ifftshift(ft2); + if ~isempty(phaseshift) + ft2 = abs(ft2) .* exp(i*angle(ft2(phaseshift(:,:,ilayer)))); + end + ft2(1) = dc; + % Inverse FFT + Y(:,:,ilayer)=real(ifft2(ft2)); +end +if all(X(:)>=0 & X(:)<=1) + Y=max(min(Y,1),0); +end +return + +x=imread('C:\Documents and Settings\ndiayek\My Documents\My Pictures\photos\Karim & Anne Sénégal Hiver 2006-2007\DSC02099.JPG'); +x=mean(x,3); +f=fftshift(fft2(x)); +g=gausswin2([size(f)],[.2]); + + diff --git a/ind2sub2.m b/ind2sub2.m new file mode 100644 index 0000000..4902a37 --- /dev/null +++ b/ind2sub2.m @@ -0,0 +1,49 @@ +function varargout = ind2sub(siz,ndx) +%IND2SUB2 - Multiple subscripts from linear index. +% IND2SUB2 is used to determine the equivalent subscript values +% corresponding to a given single index into an array. +% It is an extension of the native IND2SUB (R14) as it returns a +% multicolumn matrix of subscripts S, each column being a dimension. +% S =[ I1 I2 ... In ] +% when a single output is asked for. +% +% [I,J] = IND2SUB(SIZ,IND) returns the arrays I and J containing the +% equivalent row and column subscripts corresponding to the index +% matrix IND for a matrix of size SIZ. +% For matrices, [I,J] = IND2SUB(SIZE(A),FIND(A>5)) returns the same +% values as [I,J] = FIND(A>5). +% +% [I1,I2,I3,...,In] = IND2SUB(SIZ,IND) returns N subscript arrays +% I1,I2,..,In containing the equivalent N-D array subscripts +% equivalent to IND for an array of size SIZ. +% +% See also SUB2IND, FIND. + +% Copyright 1984-2000 The MathWorks, Inc. +% $Revision: 1.11 $ $Date: 2000/06/01 16:46:44 $ + +siz=siz(:)'; +nout = max(nargout,1); +if nout==1 + % do nothing +elseif length(siz)<=nout, + siz = [siz ones(1,nout-length(siz))]; +else + siz = [siz(1:nout-1) prod(siz(nout:end))]; +end +n = length(siz); +k = [1 cumprod(siz(1:end-1))]; +ndx = ndx(:) - 1; +for i = n:-1:1, + if nout<=1 + if i==n + vout{1}=NaN*zeros(length(ndx), n); + end + vout{1}(1:length(ndx),i) = floor(ndx./k(i))+1; + else + vout{i} = floor(ndx./k(i))+1; + end + ndx = rem(ndx,k(i)); +end + +varargout=vout; \ No newline at end of file diff --git a/interpolate_cortex1.m b/interpolate_cortex1.m new file mode 100644 index 0000000..511de80 --- /dev/null +++ b/interpolate_cortex1.m @@ -0,0 +1,107 @@ +function [InterpMatrix] = interpolate_cortex(sparseFV,denseFV,vertConn) +% INTERPOLATE_CORTEX Interpolate current density from a sparse tesselation to a dense tesselation +% function InterpMatrix = interpolate_cortex(sparseFV,denseFV,vertConn); +% sparseFV is the sparse Faces/Vertices structure +% denseFV is the dense Faces/Vertices structure +% vertConn is the vertices connectivity of the dense Faces/Vertices structure +% +% InterpMatrix returned is a sparse matrix (nDenseVertices x nSparseVertices) used for interpolation, +% where nDenseVertices in the number of vertices in the dense structure and nSparseVertices is the +% number of vertices in the sparse structure +% Interpolated current density is given by DenseCurrentDensity = InterpMatrix * SparseCurrentDensity +% +% Remarks: Every vertex in sparseFV should have a corresponding one in denseFV (i.e. same coordinates) +% sparseFV=reducepatch(denseFV) matlab function produces such tesselations +% Surfaces should be connected, i.e. there should exist a path through triangles connecting every pair +% of vertices on the surface +% interpolate_cortex performs interpolation in terms of surface neighbours and not in terms of volume +% neighbours +% +% See also REDUCEPATCH VERTICES_CONNECTIVITY PATCH_SWELL + +% Dimitrios Pantazis, Ph.D. +% 11-Apr-02 +% +% + + +%choose whether to display bars +if(~exist('VERBOSE','var')), + VERBOSE = 1; % default non-silent running of waitbars +end + +%Initialize variables +nDenseVertices=size(denseFV.vertices,1); +nSparseVertices=size(sparseFV.vertices,1); +existInSparse=zeros(nDenseVertices,1); +InterpMatrix=sparse(nDenseVertices,nSparseVertices); + + +%find vertices that have been preserved in sparse patch +if(VERBOSE) + commonVertices=0; + hwait = waitbar(0,sprintf('Finding common vertices for interpolation... %.0f found',commonVertices)); + drawnow %flush the display + step=round(nDenseVertices/10); +end +for i=1:nDenseVertices + if(VERBOSE) + if(~rem(i,step)) % ten updates + commonVertices=length(find(existInSparse>0)); + waitbar(i/nDenseVertices,hwait,sprintf('Finding common vertices for interpolation... %.0f found',commonVertices)); + drawnow %flush the display + end + end + x=sparseFV.vertices(:,1)-denseFV.vertices(i,1); + I=find(x==0); %get vertices that have the same x coord. I is the index in sparseFV + if(I) %if coordinate x is same + for j=1:length(I) + distance=sum(abs(denseFV.vertices(i,:)-sparseFV.vertices(I(j),:))); + if (distance==0) %the point is the same! + existInSparse(i)=I(j); + InterpMatrix(i,I(j))=1; + end + end + end +end +close(hwait); + + +%interpolate the rest of the vertices +if(VERBOSE) + hwait = waitbar(0,sprintf('Interpolating the %.0f remaining vertices...',nDenseVertices-nSparseVertices)); + drawnow %flush the display + step=round(nDenseVertices/20); +end +for i=1:nDenseVertices + if(VERBOSE) + if(~rem(i,step)) % ten updates + waitbar(i/nDenseVertices,hwait); + drawnow %flush the display + end + end + if(~existInSparse(i)) + startPatch=i; + nLayer=0; + neighboursKnown=[]; + neighboursKnownScale=[]; + while(length(neighboursKnown)<3 & nLayer <10 ) + swelledPatch=patch_swell(startPatch,vertConn); %swell patch to find know vertices + if(isempty(swelledPatch)) + %disp('surface not closed'); + break; + end + temp=existInSparse(swelledPatch); + neighboursNew=temp(temp>0)'; + nLayer=nLayer+1; + neighboursKnown=[neighboursKnown neighboursNew]; + neighboursKnownScale=[neighboursKnownScale nLayer*ones(1,length(neighboursNew))]; + startPatch=[swelledPatch startPatch]; + end + %update InterpMatrix + InterpMatrix(i,neighboursKnown)=(1./neighboursKnownScale)/sum(1./neighboursKnownScale); + end +end +if(VERBOSE) + close(hwait); +end \ No newline at end of file diff --git a/isfield2.m b/isfield2.m new file mode 100644 index 0000000..cf1f7a4 --- /dev/null +++ b/isfield2.m @@ -0,0 +1,42 @@ +function [TF,index] = isfield2(s,varargin) +%ISFIELD2 - Advanced ISFIELD, to test if a field is in structure array +% [TF] = isfield2(S,F) returns true if the string F is the name of a +% field or a subfield in the structure array S. +% +% Example +% >> isfield2( +% +% See also: getfield2 + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-31 Creation +% +% ----------------------------- Script History --------------------------------- + +if (isempty(varargin)) + error('MATLAB:GETFIELD:DeprecatedFunction:InsufficientInputs','Not enough input arguments.') +end +TF=0; +% The most common case +index = varargin{1}; +if (length(varargin)==1 && isstr(index)) + if any(index=='.') + [f1,f2]=strtok(index,'.'); + if ~isfield(s, deblank(f1)) + return + end + TF=isfield2([s.(deblank(f1))],f2(2:end)); + else + TF = isfield(s, deblank(index)); + return + end +end + +return diff --git a/ismember2.m b/ismember2.m new file mode 100644 index 0000000..f917ba3 --- /dev/null +++ b/ismember2.m @@ -0,0 +1,13 @@ +function [tf, loc]=ismember2(a,s) +% ISMEMBER2 : ISMEMBER function compliant with older versions of Matlab +v=ver; +if str2num(v(1).Version)>= 6.5 + [tf, loc]=ismember(a,s); +else + % In Matlab 6.1, ISMEMBER function does not allow multiple varargout + [tf]=ismember(a, s); + for i=find(tf) + idx=max(find(a(i)==s)); + loc(i)=idx(1); + end +end diff --git a/isort.m b/isort.m new file mode 100644 index 0000000..1e83aa5 --- /dev/null +++ b/isort.m @@ -0,0 +1,4 @@ +function [j,v] = isort(x) +%ISORT +% Index of the sort +[v,j]=sort(x); \ No newline at end of file diff --git a/isscalar2.m b/isscalar2.m new file mode 100644 index 0000000..6e31c8a --- /dev/null +++ b/isscalar2.m @@ -0,0 +1,13 @@ +function t = isscalar(x) +%ISSCALAR True for scalar input. +% +% ISSCALAR(X) returns 1 if it's argument is a scalar and 0 otherwise. +% Note that this function does not consider the empty matrix a scalar. + +% Author: Peter J. Acklam +% Time-stamp: 2002-03-03 13:50:54 +0100 +% E-mail: pjacklam@online.no +% URL: http://home.online.no/~pjacklam +error(nargchk(1, 1, nargin)); +t = numel(x)==1; +% t = all(size(x) == 1); diff --git a/issfield.m b/issfield.m new file mode 100644 index 0000000..351f1d8 --- /dev/null +++ b/issfield.m @@ -0,0 +1,12 @@ +function tf = issfield(s,f) +%ISSFIELD True if field.subfield is in structure array +% F = SISFIELD(S,'field.subfield...') returns true if 'field.subfield' is the +% name of a field and its subfield in the structure array S. +% +% See also SSTRUCT, SSETFIELD, SFIELDNAMES. + +if isa(s,'struct') + tf = any(strcmp(sfieldnames(s(1)),f)); +else + tf = logical(0); +end diff --git a/javauigetfiles/MatlabR13FileFilter.class b/javauigetfiles/MatlabR13FileFilter.class new file mode 100644 index 0000000000000000000000000000000000000000..c61c6d03829bcce4a0e1a48fcaf5b8ce55925e62 GIT binary patch literal 1870 zcmZ`)SyLNF5dKCItPl%^<@6!EAqUb5kg*+N0w%G+BuWH6aB#pmJS>B>&azAGt^)ok zR37r^s+1p+svxT3s`w!fsmhN^rF$igitvMaW_$Yh`s<$2KmY#mCz66G$!iTT0+U+40m$ZD&&jkL9LI8l&vn z(p{5*!{1G1Dyll6z(9FfMy}j^G<9RiaTWa{6%elUF)oT5Mlui(C9*yT45x0Fwyky} zf!?Np;}<#HY<`3Mw`nKP-9UYOLMd49$sIncsA%ylSN*wsYmow(RlgS4jFOy&&p|%P z6zg~&>jEREbg$H0_kr(tRNK9MMjAKdT3MQBI%MYjnt5Dy-t?5Yt7?(?*Dq0^OphW= za^Rwd4INK0O^jGNzQMNwNo$g}-{E@!=y(^SI^JXPj1NaoVU%1~Rit|-sML0p7oCAJ zx7r*7)0Up+N2cw2k#szB$EV~`ReGjRfGWyUfn%F?RR+?gYRoZfj9^J@vaof$gHeIO z)0B-tyIb4dR@}p!jx7*(BClf`(_GL88Y()faCAIp%@1&O?7$W1JBQ$AJ^RIQj|RBN zEwrn?AF3d3ICX|l5hFPsi=O}EpeqsiWq(fv3o;}an&WM${rlT*nJk*Pu0U0&S%k!{ zDw@~fT&Z<1N+q7NPFIFe={R6VSlbNaTSk23$fDJav!1VSm%F>l+Y%T*Z{S-ZHR$DA z6Zs9o1@yS~=Cl(yCtP%b_@=*z=^?-xP5nwd{~5kwQTW7(s&Ao!%+rJ@HlZe8r8f@r z+$Ff-v`g^R#VZXSttkj@Ey*!J2(*y~cwrqu6#honYb4f<NN~t1{bk_OIXGgJfxGSRIWn> zdUUHoDrg@$Un2iC|hK~^JH;Whf# zk1${i)-gm>3>m{D>bQ7>OQ)FmUj&pROYu4HV8i<)??^MRAoNqs9D8JwB-;s!dielt zsaLeQLS!$GTfd{Tjx3SPTfL5v18Aw2NF`s9LxPF}k-`0%f`;qpz)d3P!#K6s2zruw ug3fPH%3h-CW?Zr$%jqTvE|}?Pqda}To&;}?mAB%6dc&X@P~fB3>eheQ`<~GN literal 0 HcmV?d00001 diff --git a/javauigetfiles/MatlabR13FileFilter.java b/javauigetfiles/MatlabR13FileFilter.java new file mode 100644 index 0000000..ce7cd51 --- /dev/null +++ b/javauigetfiles/MatlabR13FileFilter.java @@ -0,0 +1,58 @@ +import java.io.File; +import java.util.*; +import javax.swing.*; +import javax.swing.filechooser.*; + +public class MatlabR13FileFilter extends FileFilter{ + + private String description; + private String selector1,selector2; + + //Constructor + public MatlabR13FileFilter(String selector,String description){ + if(selector == null){ + throw new NullPointerException("La description (ou selector) ne peut être null."); + } + selector=selector.toLowerCase(); + int star = selector.indexOf("*"); + if (selector.regionMatches(0, "*.*", 0, 3)) + { + this.selector1 = ""; + this.selector2 = ""; + } + else + { + if(selector.lastIndexOf("*") != star){ + throw new IllegalArgumentException("Selector cannot contain more than one generic character '*'."); + } + if (star>=0) + { + this.selector1 = selector.substring(0,star); + this.selector2 = selector.substring(star+1); + } + else + { + this.selector1 = selector; + this.selector2 = selector; + } + } + this.description = description; + } + + public MatlabR13FileFilter(String selector){ + this(selector,"(" + selector + ")"); + } + + + // FileFilter methods + public boolean accept(File file){ + if(file.isDirectory()) { + return true; + } + String filename = file.getName().toLowerCase(); + return filename.startsWith(selector1) && filename.endsWith(selector2); + } + public String getDescription(){ + return description; + } +} \ No newline at end of file diff --git a/javauigetfiles/uiGetFiles.m b/javauigetfiles/uiGetFiles.m new file mode 100644 index 0000000..939730b --- /dev/null +++ b/javauigetfiles/uiGetFiles.m @@ -0,0 +1,88 @@ +function [filenames, pathname] = uigetfiles(varargin) +% This is a Java interfaced version of UIGETFILES, that brings multiple file +% open dialog box. +% +% [filenames, pathname] = uigetfiles; displays a dialog box file browser +% from which the user can select multiple files. The selected files are +% returned to FILENAMES as an arrayed strings. The directory containing +% these files is returned to PATHNAME as a string. +% +% A successful return occurs only if the files exist. If the user selects +% a file that does not exist, an error message is displayed to the command +% line. If the Cancel button is selected, zero is assigned to FILENAMES +% and current directory is assigned to PATHNAME. +% +% Allows the same syntax for file filter as Matlab (R13) function UIGETFILE : +% uigetfiles(filterspec, title) +% filterspec should be a N-by-2 cell array of strings. +% See: UIGETFILE +% +% This program has an equivalent function to that of a C version of +% "uigetfiles.dll" downloadable from www.mathworks.com under support, file +% exchange (ID: 331). +% +% It should work for matlab with Java 1.3.1 or newer. +% +% Modified by KND, 2005-11-08, kndiaye01yahoo.fr +% +% Shanrong Zhang +% Department of Radiology +% University of Texas Southwestern Medical Center +% 02/09/2004 +% +% email: shanrong.zhang@utsouthwestern.edu + +% mainFrame = com.mathworks.ide.desktop.MLDesktop.getMLDesktop.getMainFrame; +filechooser = javax.swing.JFileChooser(pwd); +filechooser.setMultiSelectionEnabled(true); +filechooser.setFileSelectionMode(filechooser.FILES_ONLY); +if nargin>0 + filechooser.setAcceptAllFileFilterUsed(false); + filter=varargin{1}; + for i=1:size(filter, 1) + % Parse string sith multiple '*.ext' + ext=strread(filter{i}, '%s', 'delimiter', ';'); + for j=1:length(ext) + if size(filter,2)>1 + flt=javaObject('MatlabR13FileFilter', ext{j}, filter{i,2}); + else + flt=javaObject('MatlabR13FileFilter', ext{j}); + end + filechooser.addChoosableFileFilter(flt); + end + end +end +if nargin>1 + filechooser.setDialogTitle(varargin{2}) +end +% The following does NOT work. I dunno why... +% if nargin>2 +% if ~iscell(varargin{3}) +% varargin{3}={varargin{3}}; +% end +% selfiles=javaArray('java.io.File',length(varargin{3}) ); +% for i=1:length(varargin{3}) +% selfiles(i)=java.io.File(varargin{3}{i}) +% end +% filechooser.setSelectedFiles(selfiles) +% end +if nargin>2 + error('uiGetFiles cannot deal with pre-selected files') +end + +selectionStatus = filechooser.showOpenDialog(com.mathworks.mwswing.MJFrame); + +if selectionStatus == filechooser.APPROVE_OPTION + pathname = [char(filechooser.getCurrentDirectory.getPath), ... + java.io.File.separatorChar]; + selectedfiles = filechooser.getSelectedFiles; + for k = 1:1:size(selectedfiles) + filenames(k) = selectedfiles(k).getName; + end + filenames = char(filenames); +else + pathname = pwd; + filenames = 0; +end + +% End of code \ No newline at end of file diff --git a/karim.m b/karim.m new file mode 100644 index 0000000..63368cd --- /dev/null +++ b/karim.m @@ -0,0 +1,28 @@ +%donnee +[Channel,F,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] = ds2brainstorm(fic_ds,0); +%1er essai +champ=F{1}; +%MEG +champ_meg = champ(imegsens,:); +%EEG +champ_eeg = champ(ieegsens,:); + +%maillage (.tri) +[noeud,face,n_noeud,n_face] = lfictri(fic_tri);-----------> 120000 noeuds + +%matrice de gain et maillage format olivier +load(fic_gain) gain_5000.mat +-->vmat [imegsens,n_noeud] +load(fic_maillage) maillage_5000.mat +-->noeud, face,xyz=noeud(1:3,:), voisin (voisinage des noeuds), aire (surface des dipoles) + +%minimum norm +[[J_meg;J_oculaire],residus] = mne(champ_meg,[vmat oculaire],lambda); +lambda = 1e-4; (explique pratiquement toutes les donnees) + +%projection +meg_corrige = vmat*J_meg; + +%svd +[U,S,V] = svd(champ_oculaire); +%vecteurs spatiaux V horizontal (a verifier) diff --git a/labelbads.m b/labelbads.m new file mode 100644 index 0000000..1844095 --- /dev/null +++ b/labelbads.m @@ -0,0 +1,33 @@ +function [Bads]=labelbads(ctfdata) +% labelbads - label as BAD channels / trials / channel&trial + +% Bads.Trials : Bad trials +% Bads.Channels : +% Bads.TrialChannel : Isolated events + + +Bads=cell(1,3); + +if size(ctfdata.data, 1) == ctfdata.setup.number_samples + ctfdata.data=permute(ctfdata.data, [2 1 3]); +end + +x=ctfdata.data(ctfdata.sensor.index.eeg_sens,:,:); +sx=size(x); +figure +[h,t]=hist(abs(x(:)),10); +[i,j,k]=ind2sub(sx, find(abs(x)>t(5))); + +b=zeros(sx([1 3])); +b(i,k)=1; +% b(i,1)=NaN; +pcolor(b) +ylabel('Channels') +xlabel('Trials') + +x(i,j,k)=NaN; +figure +hist(abs(x(:)),100); +[h,t]=hist(abs(x(:)),10) +[i,j,k]=ind2sub(sx, find(abs(x)>t(5))); + diff --git a/labelize2.m b/labelize2.m new file mode 100644 index 0000000..673795f --- /dev/null +++ b/labelize2.m @@ -0,0 +1,57 @@ +function [r]=labelize(vertices, t_xyz, t_ref,varargin) +% labelize - labelize vertrices according to a reference template +% +% [r]=labelize(vertices, t_xyz, t_ref,['TimeBar']) +% +% Each item of the vertices will be labeled with the t_ref value +% of the closest vertex in the t_xyz template (geometrical distance). +% +% Input: +% vertices: [Nvx3] coordinates of Nv vertices for which labels are computed +% t_xyz: [Ntx3] matrix, positions of the Nt template vertices +% t_ref: [Ntx1] vector, labels of the template vertices +% +% Output: +% r: [Nvx1] vector of the labels +% +% Options: +% TimeBar 1 or 'on' to show a progress bar +if nargin>3 +options=struct(varargin{:}); +end +if isfield(options, 'TimeBar') + if strmatch('on', lower(options.TimeBar)) + options.TimeBar=1; + else + options.TimeBar=0; + end +else + options.TimeBar=0; +end + +r=zeros(length(vertices),1)*NaN; +if options.TimeBar + h=timebar('Progres...','Labeling vertices'); +end + +nxyz=size(t_xyz,1); +nv=size(vertices,1); + +for i=1:nv + d=sum(power(t_xyz-repmat(vertices(i,:),nxyz,1),2),2); + + % local "smoothing" + % r(i)=imax(hist(ref(d<5e-3), .5:length(labels))); + + [r(i),r(i)]=min(d); + r(i)=t_ref(r(i)); + + if options.TimeBar + timebar(h, i/nv,1); + end + %set(p, 'FaceVertexCData',r); drawnow;w +end +if options.TimeBar + close(h) +end + diff --git a/labels2parcels.m b/labels2parcels.m new file mode 100644 index 0000000..81c8bf3 --- /dev/null +++ b/labels2parcels.m @@ -0,0 +1,46 @@ +function [C,labels,ROI] = labels2parcels(r,norli,labels) +%LABELS2PARCELS - Creates a parcellation matrix from labels on a mesh +% [C,labels,ROI] = labels2parcels(r) +% From a labelling vector (r) of N points, it creates a [M-by-N] +% parcellation matrix with ones (1) in a given line indicates that +% the points of the corresponding columns belong to that region. +% +% [C,labels,ROI] = labels2parcels(r,norli) +% When norli=1, normalizes each line of C by the number of points +% belonging to it (default: norli=0, ie don't normalize); +% +% [C,labels,ROI] = labels2parcels(r,norli,labels) +% The values in r are referenced according to the labels given. +% +% +% Example +% >> C=labels2parcels(mni.atlas.r,0,1:116) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-06 Creation +% +% ----------------------------- Script History --------------------------------- +[l,i,j]=unique(r(:)); +if nargin>2 + [ign,ll]=ismember(l,labels); + j=ll(j); +else + labels=l; +end +M=length(labels); +N=length(r); +C=sparse(j,(1:N)',ones(N,1),M,N,N); +if norli + nC=1./(sum(C,2)+eps); + nC(isnan(nC))=0; + C=diag(nC)*C; +end \ No newline at end of file diff --git a/labnic/Labnic_1st_analysis.m b/labnic/Labnic_1st_analysis.m new file mode 100644 index 0000000..709bd5a --- /dev/null +++ b/labnic/Labnic_1st_analysis.m @@ -0,0 +1,203 @@ +function [] = Labnic_analyse +% analysing of the subjects you will define: +% you must have a structure like +% **...\data_fMRI\populations\subjects\scans\sessions\swaf\** +% your behavioral data are in a matrix begining by ONS in: +% **...\data_fMRI\populations\subjects\behavior\** +% your analysis will be in : +% **...\data_fMRI\populations\subjects\analyse\ana1\** +% for your processed images. + +% this function has been adapted by Yann Cojan (yann.cojan@unige.ch) +% improved by Virginie Sterpenich (Virginie.Sterpenich@unige.ch) + +global TR Session_filter im_format Cnam ons_unit name_ana Ons; +% defaults.modality = 'FMRI'; + + +%% parameters to specify for each study +TR = 1.7; +im_format = 'nii'; %or 'img'; +Session_filter ='*RUN*'; %name of the study in the directory of the sessions +root_path = 'C:\experiments\FLANKER'; % directory where are the populations, main directory +name_ana = 'ana'; %or 'ana2'; etc +ons_unit = 'secs'; %or 'scans'; + +%% defining the pop_style +cd (root_path) +Population = spm_select(Inf,'dir','which population do you want to process?'); +npop = size(Population,1); + +%% Definition of subjects to process +for pop=1:npop + cd(Population(pop,1:end)) + Subject{pop}= spm_select(Inf,'dir','which subjects do you want to process?'); +end +Subject = char(Subject); +nsuj = size(Subject,1); + +%% analysis +for pop = 1:npop + % go to the population folder + Pop{pop} = deblank(Population(pop,:)); + sep_pop = findstr(filesep,Pop{pop}); + popu = Pop{pop}(1,sep_pop(end-1)+1:sep_pop(end)); + for sub = 1:nsuj + %create the subject's analyse folder + sufolder= deblank(Subject(sub,:)); + sep_suj = findstr(filesep,Subject(sub,:)); + sujet = Subject(sub,sep_suj(end-1)+1:sep_suj(end)-1); + su = Subject(sub,sep_suj(end-1)+2:sep_suj(end)-1); + if ~exist([sufolder 'analyse' filesep],'dir'); + mkdir(sufolder, 'analyse'); + end + mkdir([sufolder 'analyse' filesep],name_ana); + wkdir=[sufolder 'analyse' filesep name_ana]; + eval(['cd ' wkdir]); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % read the behavior files to define onsets and conditions + % this is the tricky part of reading the behavior files, + % contact the script writers for help.... + + %[Ons Cnam] = readres_FLANKER_missed_pooled([sufolder 'behavior' filesep],su); + %% onsets definition + % load your ONS* mat in the behavior directory + % ONS = spm_select('List',[path 'behavior'],strcat('^ONS+.+\.mat$')); + % cd([path 'behavior']); + % load(ONS); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % do the 1st level analysis for each subject + ana(sufolder); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + end +end + +%% FUNCTION SECTION + +%% function analyse +function [] = ana(suj_path) +global TR Session_filter im_format Cnam Ons ons_unit name_ana; + +% select the sessions of interest +Session=get_directories(fullfile([suj_path 'scans'],Session_filter)); +nses = size(Session,2); + +% select swaf images for each Session +%=================================================================== +im_style = 'swaf'; +image_filter = '*swaf*'; +nscans = []; +SPM.xY.P = []; + +% selection of the swaf img of each session +%=================================================================== +for ses = 1:nses + smoothfolder = [suj_path 'scans' filesep deblank(Session{ses}) filesep 'swaf' filesep]; + tmp{ses} = spm_select('List',smoothfolder,['^' im_style '.*' im_format]); + nscans = [nscans size(tmp{ses},1)]; + SPM.xY.P = strvcat(SPM.xY.P,[repmat(smoothfolder,nscans(ses),1),tmp{ses}]); +end +SPM.nscan = nscans; +cd([suj_path 'analyse' filesep name_ana]); + +% building matrix +%==================================================================== +for ses = 1:nses + nconds=length(Cnam{ses}); + for c=1:nconds + SPM.Sess(ses).U(c).name = {Cnam{ses}{c}}; + SPM.Sess(ses).U(c).ons = Ons{ses}{c}; + SPM.Sess(ses).U(c).dur = 0; + + % define the parametric modulation according to your sessions + % (comment the adequate modulation: parametric modulation(if you + % already specify it before), or time modulation (nothing to + % specify in modul) or none (nothing to specify in modul) + %% parametric modulation + % SPM.Sess(ses).U(c).P(1).name ='modul'; + % SPM.Sess(ses).U(c).P(1).i = [1 2]; + % SPM.Sess(ses).U(c).P(1).P = eval(modul{ses}{c}); + % SPM.Sess(ses).U(c).P(1).h = 1; + %% time modulation + % SPM.Sess(ses).U(c).P(1).name ='time'; + % SPM.Sess(ses).U(c).P(1).i = [1 2]; + % SPM.Sess(ses).U(c).P(1).P = eval(Cnam{ses}{c}); + % SPM.Sess(ses).U(c).P(1).h = 1; + %% no modulation + SPM.Sess(ses).U(c).P(1).name = 'none'; + end +end + +% multiple regressors for mvts parameters +%=================================================================== +rnam = {'X','Y','Z','x','y','z'}; +for ses=1:nses + fn = spm_select('List',[suj_path 'scans' filesep deblank(Session{ses})],['^rp_.*txt']); + [r1,r2,r3,r4,r5,r6] = textread([suj_path 'scans' filesep deblank(Session{ses}) filesep fn(1,:)],'%f%f%f%f%f%f'); + SPM.Sess(ses).C.C = [r1 r2 r3 r4 r5 r6]; + SPM.Sess(ses).C.name = rnam; +end + +% basis functions and timing parameters +%==================================================================== +defaults.stats.fmri.t = 16; +defaults.stats.fmri.t0 = 8; + +SPM.xY.RT = TR; +SPM.xBF.name = 'hrf'; % 'hrf (with time derivative)' +SPM.xBF.order = 1; % 2 = hrf + time deriv +SPM.xBF.length = 32; % length in seconds + +% find number of slices +%==================================================================== +V = spm_vol(SPM.xY.P(1,:)); +if iscell(V) + nslices = V{1}{1}.dim(3); +else + nslices = V(1).dim(3); +end +ref_slice = floor(nslices/2); % middle slice in time +SPM.xBF.T = defaults.stats.fmri.t; % number of time bins per scan % useless? cf. defaults above +SPM.xBF.T0 = defaults.stats.fmri.t/2; % middle slice/timebin % useless? cf. defaults above +SPM.xBF.UNITS = ons_unit; % OPTIONS: 'scans'|'secs' for onsets +SPM.xBF.Volterra = 1; % OPTIONS: 1|2 = order of convolution + +% global normalization: OPTIONS:'Scaling'|'None' +%--------------------------------------------------------------------------- +SPM.xGX.iGXcalc = 'None'; + +% low frequency confound: high-pass cutoff (secs) [Inf = no filtering] +%--------------------------------------------------------------------------- +SPM.xX.K(1).HParam = 128; + +% intrinsic autocorrelations: OPTIONS: 'none'|'AR(1) + w' +%----------------------------------------------------------------------- +SPM.xVi.form = 'AR(1)'; %AR(0.2)???? SOSART + +% specify SPM working dir for this sub +%=========================================================================== +SPM.swd = pwd; + +% Configure design matrix +%=========================================================================== +SPM = spm_fmri_spm_ui(SPM); + +% Estimate parameters +%========================================================================== +SPM = spm_spm(SPM); +return + +function dirs = get_directories(suj_path) +% returns a cell array holding true directories located at path +D=dir(suj_path); +dirs={D(~(strcmp({D.name},'.')+strcmp({D.name},'..')+~[D.isdir])).name}; +% dirs = {'morphing_titrage_run1',... +% 'morphing_titrage_run2',... +% 'morphing_test_run5',... +% 'morphing_faceloc_run11'}; + +return \ No newline at end of file diff --git a/labnic/Labnic_1st_contrast_spm5.m b/labnic/Labnic_1st_contrast_spm5.m new file mode 100644 index 0000000..8380fdc --- /dev/null +++ b/labnic/Labnic_1st_contrast_spm5.m @@ -0,0 +1,107 @@ +function [] = Labnic_contrast_spm5 +% analysing of the subjects you will define: +% you must have a structure like +% **...\data_fMRI\populations\subjects\scans\sessions\swaf\** +% your behavioral data are in a matrix begining by ONS in: +% **...\data_fMRI\populations\subjects\behavior\** +% your analysis will be in : +% **...\data_fMRI\populations\subjects\analyse\ana1\** +% for your processed images. + +% this function has been adapted by Yann Cojan (yann.cojan@unige.ch) +% improved by Virginie Sterpenich (Virginie.Sterpenich@unige.ch) + +global name_ana; + +%% parameters to specify for each study +root_path = 'D:\'; % directory where are the populations, main directory +name_ana = 'ana'; %or 'ana2'; etc + +%% defining the pop_style +cd (root_path) +Population = spm_select(Inf,'dir','which population do you want to process?'); +npop = size(Population,1); + +%% Definition of subjects to process +for pop=1:npop + cd(Population(pop,1:end)) + Subject{pop}= spm_select(Inf,'dir','which subjects do you want to process?'); +end +Subject = char(Subject); +nsuj = size(Subject,1); + +%% starting analysing +for pop = 1:npop + % go to the population folder + Pop{pop} = deblank(Population(pop,:)); + sep_pop = findstr(filesep,Pop{pop}); + popu = Pop{pop}(1,sep_pop(end-1)+1:sep_pop(end)); + for sub = 1:nsuj + %go to the subject's analyse folder + sufolder= deblank(Subject(sub,:)); + path_ana =[sufolder 'analyse' filesep name_ana]; + eval(['cd ' path_ana]); + %select SPM.mat + [files]=spm_select('List',path_ana,'^SPM.mat$'); + jobs{1}.stats{1}.con.spmmat = {fullfile(path_ana,files)}; + % create the F contrasts + [Cf,Cnamesf] = f_con; + for iconf = 1:size(Cf,2) + % put the contrast in the job + jobs{1}.stats{1}.con.consess{iconf}.fcon.name = Cnamesf{iconf}; + jobs{1}.stats{1}.con.consess{iconf}.fcon.convec = {Cf{iconf}}; + end + +% create the T contrasts + [Ct,Cnamest] = t_con; + for icont = 1:size(Ct,1) + % put the contrast in the job + jobs{1}.stats{1}.con.consess{iconf+icont}.tcon.name = Cnamest{icont}; + jobs{1}.stats{1}.con.consess{iconf+icont}.tcon.convec = Ct(icont,:); + end + % save a matrix with the names of the contrasts + eval('save contrasts_name Ct Cnamest'); + eval('save contrast jobs'); + % run the job + spm_jobman('run',jobs) + end +end + +%% FUNCTION SECTION: create contrasts + +function [Cf,Cnamesf] = f_con +load SPM +SPM.xCon = []; +save SPM SPM + +Cf = []; Cnamesf = []; +for i = 1:length(SPM.xX.name)% creating a variable connam which contain all possible contrasts + b = strfind(SPM.xX.name{i},'*bf'); + connam{i} = SPM.xX.name{i}(7:b-1); +end + +%% then named the contrasts +Lbissec_placebo = double(strcmp(connam,'Lbissec_placebo')); + +Cnamesf{end+1} = 'F-Task'; +Cf{end+1} = [Lbissec_placebo;Mbissec_placebo;Rbissec_placebo;Lmemo_placebo;Mmemo_placebo;Rmemo_placebo;Lsearch_placebo;Msearch_placebo;Rsearch_placebo;... + Lbissec_nico;Mbissec_nico;Rbissec_nico;Lmemo_nico;Mmemo_nico;Rmemo_nico;Lsearch_nico;Msearch_nico;Rsearch_nico];% example + +return + +function [Ct,Cnamest] = t_con +load SPM + +Ct = []; Cnamest = []; +for i = 1:length(SPM.xX.name)% creating a variable connam which contain all possible contrasts + b = strfind(SPM.xX.name{i},'*bf'); + connam{i} = SPM.xX.name{i}(7:b-1); +end + +%% then named the contrasts +Mmemo_nico = double(strcmp(connam,'Mmemo_nico')); + +Cnamest{end+1} = 'Lbissec_placebo'; +Ct(end+1,:) = Lbissec_placebo;% example + +return \ No newline at end of file diff --git a/labnic/Labnic_1stlevel_spm8.m b/labnic/Labnic_1stlevel_spm8.m new file mode 100644 index 0000000..5fb9057 --- /dev/null +++ b/labnic/Labnic_1stlevel_spm8.m @@ -0,0 +1,205 @@ +function [] = Labnic_1stlevel_spm8 +% analysing of the subjects you will define: +% you must have a structure like +% **...\data_fMRI\populations\subjects\scans\sessions\swaf\** +% your behavioral data are in a matrix begining by ONS in: +% **...\data_fMRI\populations\subjects\behavior\** +% your analysis will be in : +% **...\data_fMRI\populations\subjects\analyse\ana1\** +% for your processed images. + +% this function has been adapted by Yann Cojan (yann.cojan@unige.ch) +% improved by Virginie Sterpenich (Virginie.Sterpenich@unige.ch) +clear global +global TR Session_filter im_format Cnam ons_unit name_ana Ons Modul; + +%% parameters to specify for each study +TR = 1.7; +im_format = 'nii'; %or 'img'; +Session_filter ='*ATTHYPNO_RUN*'; %name of the study in the directory of the sessions +root_path = 'F:\FLANKER'; % directory where are the populations, main directory +name_ana = 'ana_E_CI_parametric_1back_2mm'; %or 'ana2'; etc +ons_unit = 'secs'; %or 'scans'; + +%% Definition of subjects to process +cd ([root_path '\controls']) +Subject{1}= spm_select(Inf,'dir','which subjects do you want to process?'); + +Subject = char(Subject); +nsuj = size(Subject,1); + +%% analysis +for sub = 1:nsuj + %create the subject's analyse folder + sufolder= deblank(Subject(sub,:)); + sep_suj = findstr('\',Subject(sub,:)); + su = Subject(sub,sep_suj(end-1)+2:sep_suj(end)-1); + if ~exist([sufolder 'analyse\'],'dir'); + mkdir(sufolder, 'analyse\'); + end + mkdir([sufolder 'analyse\'],name_ana); + wkdir=[sufolder 'analyse\' name_ana]; + eval(['cd ' wkdir]); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % read the behavior files to define onsets and conditions + % this is the tricky part of reading the behavior files, + % contact the script writers for help.... + [Ons Modul Cnam] = readres_flanker_E_CI_parametric([sufolder 'behavior\'],su); + %% onsets definition + % load your ONS* mat in the behavior directory + % ONS = spm_select('List',[path 'behavior'],strcat('^ONS+.+\.mat$')); + % cd([path 'behavior']); + % load(ONS); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % do the 1st level analysis for each subject + ana(sufolder); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % do the 1st level analysis for each subject + con(sufolder); + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +end + +%% FUNCTION SECTION + +%% function analyse +function [] = ana(suj_path) +global TR Session_filter im_format Cnam Ons ons_unit name_ana Modul; + +% select the sessions of interest +Session=get_directories(fullfile([suj_path 'scans'],Session_filter)); +nses = size(Session,2); + +% select swaf images for each Session +%=================================================================== +im_style = 'swf'; +nscans = []; + +matlabbatch{1}.spm.stats.fmri_spec.dir = {[suj_path 'analyse\' name_ana '\']}; + + +% selection of the swaf img of each session +%=================================================================== +for ses = 1:nses + matlabbatch{1}.spm.stats.fmri_spec.sess(ses) = struct('scans',[],'cond',[],'multi',{{''}},'regress',struct('name',{},'val',{}),'multi_reg',[],'hpf',128); + smoothfolder = [suj_path 'scans\' deblank(Session{ses}) '\swf']; + tmp{ses} = spm_select('ExtFPList',smoothfolder,['^' im_style '.*' im_format]); + nscans = [nscans size(tmp{ses},1)]; + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).scans = cellstr(tmp{ses}); + + % building matrix + %==================================================================== + nconds=length(Cnam{ses}); + for c=1:nconds + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).name = Cnam{ses}{c}; + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).onset = Ons{ses}{c}; + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).duration = 0; + + % no modulation + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).tmod = 0;%1 for time modulation + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).pmod = struct('name',{},'param',{},'poly',{}); +% % modulation +% if c < 3 +% count = 0; +% count = count +1; +% matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).pmod(count).name ='preE'; +% matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).pmod(count).param = Modul{ses}{c}(:,1); +% matlabbatch{1}.spm.stats.fmri_spec.sess(ses).cond(c).pmod(count).poly = 1; +% end + end + + % multiple regressors for mvts parameters + %=================================================================== + fn = spm_select('FPList',[suj_path 'scans\' deblank(Session{ses})],'^rp_.*txt'); + matlabbatch{1}.spm.stats.fmri_spec.sess(ses).multi_reg = {fn}; +end + +% basis functions and timing parameters +%==================================================================== +matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t = 16; +matlabbatch{1}.spm.stats.fmri_spec.timing.fmri_t0 = 8; + +matlabbatch{1}.spm.stats.fmri_spec.timing.RT = TR; %TR + +matlabbatch{1}.spm.stats.fmri_spec.bases.hrf.derivs = [0 0]; %time derivatives +matlabbatch{1}.spm.stats.fmri_spec.timing.units = ons_unit; % OPTIONS: 'scans'|'secs' for onsets +matlabbatch{1}.spm.stats.fmri_spec.volt = 1; % OPTIONS: 1|2 = order of convolution +matlabbatch{1}.spm.stats.fmri_spec.mask = {''}; % explicit masking + +% global normalization: OPTIONS:'Scaling'|'None' +%--------------------------------------------------------------------------- +matlabbatch{1}.spm.stats.fmri_spec.global = 'None'; + +matlabbatch{1}.spm.stats.fmri_spec.fact = struct('name',{},'levels',{}); + +% intrinsic autocorrelations: OPTIONS: 'none'|'AR(1) + w' +%--------------------------------------------------------------------------- +matlabbatch{1}.spm.stats.fmri_spec.cvi = 'AR(1)'; %AR(0.2)???? SOSART + +matlabbatch{2}.spm.stats.fmri_est.spmmat = {[matlabbatch{1}.spm.stats.fmri_spec.dir{1} '\SPM.mat']}; +matlabbatch{2}.spm.stats.fmri_est.method.Classical = 1; + +save analyse matlabbatch +% Configure & Estimate +%========================================================================== +spm_jobman('run',matlabbatch); +return + +function [] = con(sudir) +global name_ana; + +cd ([sudir '\analyse\' name_ana]); +load('SPM.mat'); +SPM.xCon =[]; % reset xCon + +for i = 1:length(SPM.xX.name)%adding 6 for mvt regressors that are in SPM.xX.name + b = strfind(SPM.xX.name{i},'*bf'); +% connam{i} = SPM.xX.name{i}([7:b-1 end-1]); + connam{i} = SPM.xX.name{i}(7:b-1); +end + +C = double(strcmp(connam,'C')); C_preE = double(strcmp(connam,'CxpreE^1')); C_postE = double(strcmp(connam,'CxpostE^1')); +I = double(strcmp(connam,'I')); I_preE = double(strcmp(connam,'IxpreE^1')); I_postE = double(strcmp(connam,'IxpostE^1')); +C_preE0 = double(strcmp(connam,'CxpreE0^1')); C_postE0 = double(strcmp(connam,'CxpostE0^1')); +I_preE0 = double(strcmp(connam,'IxpreE0^1')); I_postE0 = double(strcmp(connam,'IxpostE0^1')); +EC = double(strcmp(connam,'EC')); +EI = double(strcmp(connam,'EI')); +%---------- +%F TASK +%---------- +cn=1; +Cnames{cn} = 'F-task'; +cwgt{cn} = [C;I;EC;EI]; +ctyp{cn} = 'F'; + +%% main effects +cn=cn+1; +Cnames{cn} = 'C'; +cwgt{cn} = C; +ctyp{cn} = 'T'; +cn=cn+1; +Cnames{cn} = 'I'; +cwgt{cn} = I; +ctyp{cn} = 'T'; + + +save contrasts_name Cnames +for c = 1:cn + cw = [cwgt{c}]'; % pad with zero for constant + tmp(c) = spm_FcUtil('Set',Cnames{c},ctyp{c},'c',cw,SPM.xX.xKXs); +end +SPM.xCon = tmp; +%save SPM SPM and evaluate--------------------------------------------------------------------------- +SPM = spm_contrasts(SPM); +return + +function dirs = get_directories(suj_path) +% returns a cell array holding true directories located at path +D=dir(suj_path); +dirs={D(~(strcmp({D.name},'.')+strcmp({D.name},'..')+~[D.isdir])).name}; +return \ No newline at end of file diff --git a/labnic/Labnic_Anova_2groups_spm8.m b/labnic/Labnic_Anova_2groups_spm8.m new file mode 100644 index 0000000..5563fef --- /dev/null +++ b/labnic/Labnic_Anova_2groups_spm8.m @@ -0,0 +1,187 @@ +function [] = Labnic_rfx_anova_2groups + +%% parameters to specify for each study +root_path = 'D:\SEXO\'; % directory where are the populations, main directory +name_ana = 'analyse_fMRI\ana_sexo_rating\'; %or 'ana2'; etc +dirname = 'RFX_sexo_2groups'; % name for the directory of the random analysis +cons = [7 9 11 13];% which contrast is it in the 1st level analysis? + +%% defining the pop_style +cd (root_path) +Population = spm_select(Inf,'dir','which population do you want to process?'); +npop = size(Population,1); + +%% Definition of subjects to process +for pop=1:npop + cd(Population(pop,1:end)) + subject{pop}= spm_select(Inf,'dir','which subjects do you want to process?'); +end +Subject = char(subject); +nsuj = size(Subject,1); +n1 = size(subject{1},1); +n2 = size(subject{2},1); +%% Creation of directory for the rfx +dirstr = strcat(root_path,dirname); +if ~exist(strcat(root_path,dirname)) + mkdir(strcat(root_path,dirname)) +end +cd (dirstr) +ncon = length(cons); + +fnm = 'con'; +% get image files names +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).name = 'group';%second factor +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).name = 'condition'; %first factor +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(3).name = 'subject'; + +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).dept = 0; %conditions are dept because coming from the same subject +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).dept = 1; %deriv are dept +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(3).dept = 0; %subjects are not dept + +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).variance = 1; %unequal variance for groups +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).variance = 0; %equal variance for condition +matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(3).variance = 0; %equal variance for subjects + +for s = 1:nsuj + su = deblank(Subject(s,:)); + scans = []; + conds = []; + count = 0; + for cond = 1:ncon + count = count+1; + con = cons(count); + scans = [scans;{sprintf('%s%s_%04d.img',su,fnm,con)}]; + if s<16 + group = 1; + else + group = 2; + end + conds = [conds; group cond s]; + end + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fsuball.fsubject(s).scans = scans; + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fsuball.fsubject(s).conds = conds; +end +matlabbatch{1}.spm.stats.factorial_design.des.fblock.maininters{1}.fmain.fnum = 1; +matlabbatch{1}.spm.stats.factorial_design.des.fblock.maininters{2}.fmain.fnum = 2; +matlabbatch{1}.spm.stats.factorial_design.des.fblock.maininters{3}.inter.fnums = [1 2]; +matlabbatch{1}.spm.stats.factorial_design.dir = {dirstr}; + +%%for covariation +% matlabbatch{1}.spm.stats.factorial_design.cov.c = repmat([20 24 32 23 30 31 24 17 25 26 25 27 21 29 20 21 25 22 29 26 25 25 25 28]',1,ncon); +% %matlabbatch{1}.spm.stats.factorial_design.cov.c = repmat([92 106 92 105 91 96 89 94 107 112 106 107 101 105 87 93 89 105 118 80 95 85 90 105]',1,8); +% matlabbatch{1}.spm.stats.factorial_design.cov.cname = 'impulsivity'; +% matlabbatch{1}.spm.stats.factorial_design.cov.iCFI = 1; +% matlabbatch{1}.spm.stats.factorial_design.cov.iCC = 1; + +matlabbatch{2}.spm.stats.fmri_est.spmmat = {[dirstr filesep 'SPM.mat']}; +matlabbatch{2}.spm.stats.fmri_est.method.Classical = 1; +save('ANOVA_2groups','matlabbatch') +spm_jobman('run',matlabbatch); + +%% Contrast part +load ([dirstr filesep 'SPM.mat']) +SPM = rmfield(SPM,'xCon'); + +%% F contrast +cn=1; +cnam{cn} = 'F-task'; +cwgt{cn} = [kron(eye(npop),ones(ncon,1)) repmat(eye(ncon),npop,1) eye(ncon*npop)]; +ctyp{cn} = 'F'; +%% main effect of group +cn = cn+1; +cnam{cn} = 'C-P'; +cwgt{cn} = [1 -1 zeros(1,ncon) ones(1,ncon)/ncon -ones(1,ncon)/ncon]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'P-C'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +%% main effect of conditions +cn = cn+1; +cnam{cn} = 'E-N'; +con = [1 1 -1 -1]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'N-E'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'M-C'; +con = [1 -1 1 -1]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'C-M'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'EM-NM'; +con = [1 0 -1 0]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'NM-EM'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'EC-NC'; +con = [0 1 0 -1]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'NC-EC'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'EC-EM'; +con = [-1 1 0 0]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'EM-EC'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'NC-NM'; +con = [0 0 -1 1]; +cwgt{cn} = [zeros(1,npop) con con*n1/nsuj con*n2/nsuj]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'NM-NC'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; +%% interactions +cn = cn+1; +cnam{cn} = 'E-N_C-P'; +con = [1 1 -1 -1]; +cwgt{cn} = [zeros(1,npop+ncon) con -con]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'E-N_P-C'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +cn = cn+1; +cnam{cn} = 'M-C_C-P'; +con = [1 -1 1 -1]; +cwgt{cn} = [zeros(1,npop+ncon) con -con]; +ctyp{cn} = 'T'; +cn = cn+1; +cnam{cn} = 'M-C_P-C'; +cwgt{cn} = -cwgt{cn-1}; +ctyp{cn} = 'T'; + +for c = 1:cn + cw = [cwgt{c}]'; % pad with zero for constant + SPM.xCon(c) = spm_FcUtil('Set',cnam{c},ctyp{c},'c',cw,SPM.xX.xKXs); +end + +spm_contrasts(SPM); +return \ No newline at end of file diff --git a/labnic/Labnic_Anova_spm8.m b/labnic/Labnic_Anova_spm8.m new file mode 100644 index 0000000..749a6cc --- /dev/null +++ b/labnic/Labnic_Anova_spm8.m @@ -0,0 +1,97 @@ +function [] = Labnic_rfx_anova_with_covariates_spm8 +% create the second level analyis (random effect analysis RFX) +% create an ANOVA with 2 factors in this example +% you must specified the 4 first lines of the script +% name_ana_grp is the directory for the main RFX analysis +% Analysis of each subjects must be in: +% **...\populations\subjects\analyse\ana1\** + +%% parameters to specify for each study %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +myjob = [1 1]; % myjob(1)==1 : build + estimate model myjob(2)==1 : build contrasts +root_path = 'e:\Data XP\fMRI EWA\data_fMRI\'; % directory where are the populations, main directory +name_ana_ind = '3. analyse\quadriface\'; % Folder name of 1st level analysis +name_ana_grp = 'grp_analysis\Quadri_ANOVA12_21S'; % name for the directory of the random analysis +cons = [3:6 8:11 13:16]; % which contrast is it in the 1st level analysis? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +dirstr = strcat(root_path,name_ana_grp); +ncon = length(cons); + +if myjob(1) + %% defining the subject list + dbstop if error + cd (root_path) + Subject{1}= spm_select(Inf,'dir','which subjects do you want to process?'); + + Subject = char(Subject); + nsuj = size(Subject,1); + + %% Creation of directory for the rfx + if ~exist(strcat(root_path,name_ana_grp)) + mkdir(strcat(root_path,name_ana_grp)) + end + cd (dirstr) + fnm = 'con'; + + answer_sphericity = questdlg('Do you want to correct for potential violations of sphericity of the factor condition ?','Sphericity correction', 'Yes' , 'No' ,'Yes'); + answer_sphericity = strcmp(answer_sphericity, 'Yes'); + + %% defining the factors + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).name = 'condition'; % first factor condition + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).name = 'subject'; % second factor subject + + %% Dependance within factors + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).dept = 1; % Conditions are dependant (=1) because the measure is performed several times within each subject + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).dept = 0; % Subjects are independant (=0) because they are assumed to pertain to the same group + + %% Variance within factors (ie sphericity assumed or not) + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(1).variance = answer_sphericity; % Unequal variance assumed (0: equal; 1:unequal) + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fac(2).variance = 0; % Unequal variance assumed (0: equal; 1:unequal) + + %% get the images from each subject + for s = 1:nsuj + su = deblank(Subject(s,:)); + scans = []; + conds = []; + for cond = 1:ncon + con = cons(cond); + scans = [scans;{sprintf('%s%s%s%s%s_%04d.img',su,filesep,name_ana_ind,filesep,fnm,con)}]; + conds = [conds; cond s]; + end + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fsuball.fsubject(s).scans = scans; + matlabbatch{1}.spm.stats.factorial_design.des.fblock.fsuball.fsubject(s).conds = conds; + end + matlabbatch{1}.spm.stats.factorial_design.des.fblock.maininters{1}.fmain.fnum = 1; + matlabbatch{1}.spm.stats.factorial_design.des.fblock.maininters{2}.fmain.fnum = 2; + matlabbatch{1}.spm.stats.factorial_design.dir = {dirstr}; + + %% covariates if any + % matlabbatch{1}.spm.stats.factorial_design.cov(1).c = [10,9,11,7,10,9,3,7,11,10,10,8,6,10,7,10,2,5,7,3,10,4,6,7,2,1,11,9,8,6,4,8,]; + % matlabbatch{1}.spm.stats.factorial_design.cov(1).cname = 'age';%name of the covariate + % matlabbatch{1}.spm.stats.factorial_design.cov(1).iCFI = 2; + % matlabbatch{1}.spm.stats.factorial_design.cov(1).iCC = 1;% do you want interaction with factor iCFI-1? + + matlabbatch{2}.spm.stats.fmri_est.spmmat = {[dirstr filesep 'SPM.mat']}; + matlabbatch{2}.spm.stats.fmri_est.method.Classical = 1; + save('ANOVA','matlabbatch') %save the .mat + spm_jobman('run',matlabbatch); + +end + +if myjob(2) + %% Contrast part + cd (dirstr) + load ([dirstr filesep 'SPM.mat']) + SPM = rmfield(SPM,'xCon'); + matlabbatch = []; + + matlabbatch{1}.spm.stats.con.spmmat = {[pwd filesep 'SPM.mat']}; + matlabbatch{1}.spm.stats.con.consess{1}.fcon.name = 'F(Task)'; + matlabbatch{1}.spm.stats.con.consess{1}.fcon.convec = {ones(ncon)*(-1/ncon)+eye(ncon)}; + matlabbatch{1}.spm.stats.con.consess{1}.fcon.sessrep = 'none'; + matlabbatch{1}.spm.stats.con.delete = 1; + + spm_jobman('run',matlabbatch); +end + +return \ No newline at end of file diff --git a/labnic/Labnic_PPI_spm8.m b/labnic/Labnic_PPI_spm8.m new file mode 100644 index 0000000..10e05aa --- /dev/null +++ b/labnic/Labnic_PPI_spm8.m @@ -0,0 +1,753 @@ +function [] = Labnic_PPI_spm8 +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +global Session_filter scandir namevar psyconvar rad_sphere TR nslices region + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +mypoints = [42 -43 -23]; %% seed voxel +region = 'rFFA'; %% region corresponding to the voxel +namevar={'Cf' 'If' 'Cs' 'Is'}; +psyconvar=[1 1 -1 -1]; +root_path = 'C:\experiments\FLANKER\'; % directory where are the populations, main directory +anadir = 'ana_woST\'; %or 'ana2'; etc +Session_filter = '*ATTHYPNO_RUN*'; +rad_sphere = 8; % radius of the sphere in mm +TR = 1.7; % your TR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +mycon=1; %will take the F-task contrast (1) to define the conditions of the task +%% defining the pop_style +cd (root_path) +Population = spm_select(Inf,'dir','which population do you want to process?'); +npop = size(Population,1); + +%% Definition of subjects to process +for pop=1:npop + cd(Population(pop,1:end)) + Subject{pop}= spm_select(Inf,'dir','which subjects do you want to process?'); +end +Subject = char(Subject); +nsuj = size(Subject,1); + +for sub = 1:size(Subject,1) + su = deblank(Subject(sub,:)); + scandir = [su 'scans']; + + xyz= mypoints; + path_ana =fullfile(deblank(Subject(sub,:)),'analyse',anadir); + [SPM,xSPM] = spm_getSPM_PPI(path_ana,mycon); + + % find number of slices +%==================================================================== +V = spm_vol(SPM.xY.P(1,:)); +if iscell(V) + nslices = V{1}{1}.dim(3); +else + nslices = V(1).dim(3); +end + + XYZ = SPM.xVol.XYZ; + XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + [xyz,i] = spm_XYZreg('NearestXYZ',xyz,XYZmm); + + %% extract neural signal from seed region + myPPI = spm_regions_PPI(SPM,xSPM,xyz); + + %% create a new model and estimates it + Labnic_analyse_PPI(su,myPPI,region); + + %% make the contrasts + Labnic_contrast_PPI(su,region); +end + +return + +%% subfunctions +function dirs = get_directories(suj_path) +% returns a cell array holding true directories located at path +D=dir(suj_path); +dirs={D(~(strcmp({D.name},'.')+strcmp({D.name},'..')+~[D.isdir])).name}; +% dirs = {'morphing_titrage_run1',... +% 'morphing_titrage_run2',... +% 'morphing_test_run5',... +% 'morphing_faceloc_run11'}; + +return + +function PPI = Labnic_extract_PPI(SPM, myvoi,psyconvar,namevar) +% Bold deconvolution to create physio- or psycho-physiologic interactions + + +% check inputs and set up variables +%---------------------------------------------------------------------- +RT = SPM.xY.RT; +dt = SPM.xBF.dt; +NT = round(RT/dt); + + +% Ask whether to perform physiophysiologic or psychophysiologic interactions +%-------------------------------------------------------------------------- +% set(Finter,'name','PPI Setup') +% ppiflag = 'psychophysiologic interaction'; + +% case 'psychophysiologic interaction' % get hemodynamic response +%===================================================================== +% spm_input('physiological variable:... ',2,'d'); +% P = spm_get(1,'VOI*.mat',{'select VOIs'}); +P = myvoi; +p = load(P,'xY'); +xY(1) = p.xY; +Sess = SPM.Sess(xY(1).Sess); + +% get 'causes' or inputs U +%---------------------------------------------------------------------- +%spm_input('Psychological variable:... ',2,'d'); +U.name = {}; +U.u = []; +U.w = []; + +for i = 1:length(Sess.U) + Name(i) = Sess.U(i).name; +end +count = 0; +for i = 1:length(namevar) + if any(strcmp(namevar(i),Name)); + count = count +1; + mypsyconvar = psyconvar(i); + for j = 1:length(Sess.U(count).name) + U.u = [U.u Sess.U(count).u(33:end,j)];% don't understand + U.name{end + 1} = Sess.U(count).name{j}; + U.w = [U.w mypsyconvar]; + end + end +end +if sum(U.w) < 0 + U.w(U.w == 1) = 4/(4+sum(U.w)); +end + +% name of PPI file to be saved +%------------------------------------------------------------------------- +[tmp, myfile]= fileparts(myvoi); +PPI.name = ['PPI_' myfile] + +% Setup variables +%------------------------------------------------------------------------- +N = length(xY(1).u); +k = 1:NT:N*NT; % microtime to scan time indices + +% create basis functions and hrf in scan time and microtime +%------------------------------------------------------------------------- +%spm('Pointer','watch') +hrf = spm_hrf(dt); + +% create convolved explanatory {Hxb} variables in scan time +%------------------------------------------------------------------------- +xb = spm_dctmtx(N*NT + 128,N); +Hxb = zeros(N,N); +for i = 1:N + Hx = conv(xb(:,i),hrf); + Hxb(:,i) = Hx(k + 128); +end +xb = xb(129:end,:); + + +% get confounds (in scan time) and constant term +%------------------------------------------------------------------------- +X0 = xY(1).X0; +M = size(X0,2); + + +% get response variable, +%------------------------------------------------------------------------- +for i = 1:size(xY,2) + Y(:,i) = xY(i).u; +end + + +% remove confounds and save Y in ouput structure +%------------------------------------------------------------------------- +% Yc = Y - X0*inv(X0'*X0)*X0'*Y; %SOSART +Yc = Y - X0*pinv(X0'*X0)*X0'*Y; +PPI.Y = Yc(:,1); +if size(Y,2) == 2 + PPI.P = Yc(:,2); +end + + +% specify covariance components; assume neuronal response is white +% treating confounds as fixed effects +%------------------------------------------------------------------------- +Q = speye(N,N)*N/trace(Hxb'*Hxb); +Q = blkdiag(Q, speye(M,M)*1e6 ); + +% get whitening matrix (NB: confounds have already been whitened) +%------------------------------------------------------------------------- +W = SPM.xX.W(Sess.row,Sess.row); + +% create structure for spm_PEB +%------------------------------------------------------------------------- +clear P +P{1}.X = [W*Hxb X0]; % Design matrix for lowest level +P{1}.C = speye(N,N)/4; % i.i.d assumptions +P{2}.X = sparse(N + M,1); % Design matrix for parameters (0's) +P{2}.C = Q; + + +% case 'psychophysiologic interaction' +%===================================================================== + +% COMPUTE PSYCHOPHYSIOLOGIC INTERACTIONS +% use basis set in microtime +%--------------------------------------------------------------------- +% get parameter estimates and neural signal; beta (C) is in scan time +% This clever trick allows us to compute the betas in scan time which is +% much quicker than with the large microtime vectors. Then the betas +% are applied to a microtime basis set generating the correct neural +% activity to convolve with the psychological variable in mircrotime +%--------------------------------------------------------------------- +C = spm_PEB(Y,P); +xn = xb*C{2}.E(1:N); +xn = spm_detrend(xn); + +% setup psychological variable from inputs and contast weights +%--------------------------------------------------------------------- +PSY = zeros(N*NT,1); +for i = 1:size(U.u,2) + tmp = full(U.u(:,i)*U.w(:,i)); + tmp = tmp(1:(N*NT)); + PSY = PSY + tmp; +end +PSY = spm_detrend(PSY); + +% multiply psychological variable by neural signal +%--------------------------------------------------------------------- +PSYxn = PSY.*xn; + +% convolve and resample at each scan for bold signal +%--------------------------------------------------------------------- +ppi = conv(PSYxn,hrf); +ppi = ppi(k); + +% similarly for psychological effect +%--------------------------------------------------------------------- +PSYHRF = conv(PSY,hrf); +PSYHRF = PSYHRF(k); + +% save psychological variables +%--------------------------------------------------------------------- +PPI.psy = U; +PPI.P = PSYHRF; +PPI.xn = xn; +PPI.ppi = spm_detrend(ppi); + +return + +function [myPPI] = spm_regions_PPI(SPM,xSPM,xyz) +xY.xyz = xyz; + +global Session_filter scandir psyconvar namevar rad_sphere +%-Get adjustment options and VOI name +%----------------------------------------------------------------------- +spm_input(sprintf('at [%3.0f %3.0f %3.0f]',xY.xyz),1,'d',... + 'VOI time-series extraction') + +if ~isfield(xY,'name') + tmp = deblank(num2str(xyz')); + xY.name = strrep(tmp, ' ',''); +end + +xY.Ic = 1; + +xY.def = 'sphere'; +Q = ones(1,size(xSPM.XYZmm,2)); + +if ~isfield(xY,'spec') + xY.spec = rad_sphere; % radius of the sphere +end +d = [xSPM.XYZmm(1,:) - xyz(1); + xSPM.XYZmm(2,:) - xyz(2); + xSPM.XYZmm(3,:) - xyz(3)]; +Q = find(sum(d.^2) <= xY.spec^2); + +%% Get raw data, whiten and filter +y = spm_get_data(SPM.xY.VY,xSPM.XYZ(:,Q)); +y = spm_filter(SPM.xX.K,SPM.xX.W*y); +xY.XYZmm = xSPM.XYZmm(:,Q); + +%-Parameter estimates: beta = xX.pKX*xX.K*y +%--------------------------------------------------------------- +beta = spm_get_data(SPM.Vbeta,xSPM.XYZ(:,Q)); + +%-subtract Y0 = XO*beta, Y = Yc + Y0 + e +%--------------------------------------------------------------- +y = y - spm_FcUtil('Y0',SPM.xCon(xY.Ic),SPM.xX.xKXs,beta); + +% extract session-specific rows from data and confounds +%----------------------------------------------------------------------- +Session=get_directories(fullfile(scandir,Session_filter)); +nses = size(Session,2); + +for ses=1:nses + clear xY.X0 y2 + xY.X0 = SPM.xX.xKXs.X(:,[SPM.xX.iB SPM.xX.iG]); + xY.Sess = ses; + + try + i = SPM.Sess(xY.Sess).row; + y2 = y(i,:); + xY.X0 = xY.X0(i,:); + end + + % and add session-specific filter confounds + %----------------------------------------------------------------------- + try + xY.X0 = [xY.X0 SPM.xX.K(xY.Sess).X0]; + end + + %======================================================================= + try + xY.X0 = [xY.X0 SPM.xX.K(xY.Sess).KH]; % Compatibility check + end + + % compute regional response in terms of first eigenvariate + %----------------------------------------------------------------------- + [m n] = size(y2); + if m > n + [v s v] = svd(spm_atranspa(y2)); + s = diag(s); + v = v(:,1); + u = y2*v/sqrt(s(1)); + else + [u s u] = svd(spm_atranspa(y2')); + s = diag(s); + u = u(:,1); + v = y2'*u/sqrt(s(1)); + end + d = sign(sum(v)); + u = u*d; + v = v*d; + Y = u*sqrt(s(1)/n); + + % set in structure + %----------------------------------------------------------------------- + xY.y = y2; + xY.u = Y; + xY.v = v; + xY.s = s; + + str = ['VOI_' xY.name]; + if isfield(xY,'Sess') + if length(xY.Sess) == 1 + str = sprintf('VOI_%s_%i',xY.name,xY.Sess); + end + end + myvoi= [fullfile(SPM.swd,str) '.mat']; + save(fullfile(SPM.swd,str),'Y','xY') + myPPI{ses} = Labnic_extract_PPI(SPM,myvoi,psyconvar,namevar); +end +return + +function [SPM,xSPM] = spm_getSPM_PPI(swd,Ic) +SCCSid = '2.51'; + +%-GUI setup +%----------------------------------------------------------------------- +SPMid = spm('SFnBanner',mfilename,SCCSid); +spm_help('!ContextHelp',mfilename) + +%-Select SPM.mat & note SPM results directory +%----------------------------------------------------------------------- +% swd = spm_str_manip(spm_get(1,'SPM.mat','Select SPM.mat'),'H'); + +%-Preliminaries... +%======================================================================= + +%-Load SPM.mat +%----------------------------------------------------------------------- +load(fullfile(swd,'SPM.mat')); +SPM.swd = swd; + +%-Get volumetric data from SPM.mat +%----------------------------------------------------------------------- +try + xX = SPM.xX; %-Design definition structure + XYZ = SPM.xVol.XYZ; %-XYZ coordinates + S = SPM.xVol.S; %-search Volume {voxels} + R = SPM.xVol.R; %-search Volume {resels} + M = SPM.xVol.M(1:3,1:3); %-voxels to mm matrix + VOX = sqrt(diag(M'*M))'; %-voxel dimensions +catch + + % check the model has been estimated + %--------------------------------------------------------------- + str = { 'This model has not been estimated.';... + 'Would you like to estimate it now?'}; + if spm_input(str,1,'bd','yes|no',[1,0],1) + [SPM] = spm_spm(SPM); + else + return + end +end + + +%-Contrast definitions +%======================================================================= + +%-Load contrast definitions (if available) +%----------------------------------------------------------------------- +try + xCon = SPM.xCon; +catch + xCon = {}; +end + +nc = length(Ic); % Number of contrasts + +n = 1; + +%-Enforce orthogonality of multiple contrasts for conjunction +% (Orthogonality within subspace spanned by contrasts) +%----------------------------------------------------------------------- +Im = []; +pm = []; +Ex = []; + +%-Create/Get title string for comparison +%----------------------------------------------------------------------- +str = xCon(Ic).name; +if Ex + mstr = 'masked [excl.] by'; +else + mstr = 'masked [incl.] by'; +end +if length(Im) == 1 + str = sprintf('%s (%s %s at p=%g)',str,mstr,xCon(Im).name,pm); + +elseif ~isempty(Im) + str = [sprintf('%s (%s {%d',str,mstr,Im(1)),... + sprintf(',%d',Im(2:end)),... + sprintf('} at p=%g)',pm)]; +end +titlestr = str; + +%-Compute & store contrast parameters, contrast/ESS images, & SPM images +%======================================================================= +SPM.xCon = xCon; +SPM = spm_contrasts(SPM,unique([Ic,Im])); +xCon = SPM.xCon; +VspmSv = cat(1,xCon(Ic).Vspm); +STAT = xCon(Ic(1)).STAT; + +%-Check conjunctions - Must be same STAT w/ same df +%----------------------------------------------------------------------- +if (nc > 1) && (any(diff(double(cat(1,xCon(Ic).STAT)))) || ... + any(abs(diff(cat(1,xCon(Ic).eidf))) > 1)) + error('illegal conjunction: can only conjoin SPMs of same STAT & df') +end + +%-Degrees of Freedom and STAT string describing marginal distribution +%----------------------------------------------------------------------- +df = [xCon(Ic(1)).eidf xX.erdf]; +if nc>1 + if n>1 + str = sprintf('^{%d \\{Ha:k\\geq%d\\}}',nc,(nc-n)+1); + else + str = sprintf('^{%d \\{Ha:k=%d\\}}',nc,(nc-n)+1); + end +else + str = ''; +end + +switch STAT + case 'T' + STATstr = sprintf('%c%s_{%.0f}','T',str,df(2)); + case 'F' + STATstr = sprintf('%c%s_{%.0f,%.0f}','F',str,df(1),df(2)); + case 'P' + STATstr = sprintf('%s^{%0.2f}','PPM',df(1)); +end + +%-Compute (unfiltered) SPM pointlist for masked conjunction requested +%======================================================================= +fprintf('\t%-32s: %30s\n','SPM computation','...initialising') %-# + +%-Compute conjunction as minimum of SPMs +%----------------------------------------------------------------------- +Z = Inf; +for i = Ic + Z = min(Z,spm_get_data(xCon(i).Vspm,XYZ)); +end + +% P values for False Discovery FDR rate computation (all search voxels) +%======================================================================= +switch STAT + case 'T' + Ps = (1 - spm_Tcdf(Z,df(2))).^n; + case 'P' + Ps = (1 - Z).^n; + case 'F' + Ps = (1 - spm_Fcdf(Z,df)).^n; +end + +%-Compute mask and eliminate masked voxels +%----------------------------------------------------------------------- +for i = Im + fprintf('%s%30s',sprintf('\b')*ones(1,30),'...masking') + + Mask = spm_get_data(xCon(i).Vspm,XYZ); + um = spm_u(pm,[xCon(i).eidf,xX.erdf],xCon(i).STAT); + if Ex + Q = Mask <= um; + else + Q = Mask > um; + end + XYZ = XYZ(:,Q); + Z = Z(Q); + if isempty(Q) + fprintf('\n') %-# + warning(sprintf('No voxels survive masking at p=%4.2f',pm)) + break + end +end + +%-clean up interface +%----------------------------------------------------------------------- +fprintf('\t%-32s: %30s\n','SPM computation','...done') %-# +spm('Pointer','Arrow') + + + +%======================================================================= +% - H E I G H T & E X T E N T T H R E S H O L D S +%======================================================================= + +%-Height threshold - classical inference +%----------------------------------------------------------------------- +u = -Inf; +k = 0; +u = 1; +if u <= 1; u = spm_u(u^(1/n),df,STAT); end + + + +%-Calculate height threshold filtering +%------------------------------------------------------------------- +Q = find(Z > u); + +%-Apply height threshold +%------------------------------------------------------------------- +Z = Z(:,Q); +XYZ = XYZ(:,Q); +if isempty(Q) + warning(sprintf('No voxels survive height threshold u=%0.2g',u)) +end + + +%-Extent threshold (disallowed for conjunctions) +%----------------------------------------------------------------------- +if ~isempty(XYZ) + + %-Get extent threshold [default = 0] + %------------------------------------------------------------------- + k = 0; + + %-Calculate extent threshold filtering + %------------------------------------------------------------------- + A = spm_clusters(XYZ); + Q = []; + for i = 1:max(A) + j = find(A == i); + if length(j) >= k; Q = [Q j]; end + end + + % ...eliminate voxels + %------------------------------------------------------------------- + Z = Z(:,Q); + XYZ = XYZ(:,Q); + if isempty(Q) + warning(sprintf('No voxels survive extent threshold k=%0.2g',k)) + end + +else + + k = 0; + +end % (if ~isempty(XYZ)) + + +%======================================================================= +% - E N D +%======================================================================= +fprintf('\t%-32s: %30s\n','SPM computation','...done') %-# + +%-Assemble output structures of unfiltered data +%======================================================================= +xSPM = struct('swd', swd,... + 'title', titlestr,... + 'Z', Z,... + 'n', n,... + 'STAT', STAT,... + 'df', df,... + 'STATstr', STATstr,... + 'Ic', Ic,... + 'Im', Im,... + 'pm', pm,... + 'Ex', Ex,... + 'u', u,... + 'k', k,... + 'XYZ', XYZ,... + 'XYZmm', SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))],... + 'S', SPM.xVol.S,... + 'R', SPM.xVol.R,... + 'FWHM', SPM.xVol.FWHM,... + 'M', SPM.xVol.M,... + 'iM', SPM.xVol.iM,... + 'DIM', SPM.xVol.DIM,... + 'VOX', VOX,... + 'Vspm', VspmSv,... + 'Ps', Ps); + +% RESELS per voxel (density) if it exists +%----------------------------------------------------------------------- +if isfield(SPM,'VRpv'), xSPM.VRpv = SPM.VRpv; end +return + +function [] = Labnic_analyse_PPI(su,myPPI,region) + +global Session_filter scandir TR nslices + +anatype = ['analyse' filesep 'PPI' filesep]; +% select the sessions of interest +Session=get_directories(fullfile(scandir,Session_filter)); +nses = size(Session,2); + +myana= ['PPI_' region filesep]; %ROI + +% specify data: matrix of filenames and TR +%=========================================================================== +nscans=[]; +SPM.xY.P=[]; +clear tmp + +for ses= 1:nses + smoothfolder = fullfile(scandir,deblank(Session{ses}),[filesep 'swf' filesep]); + tmp{ses} = spm_select('List',smoothfolder,'^sw.*nii'); + nscans = [nscans size(tmp{ses},1)]; + SPM.xY.P = strvcat(SPM.xY.P,[repmat(smoothfolder,nscans(ses),1),tmp{ses}]); +end + +% basis functions and timing parameters +%--------------------------------------------------------------------------- +ref_slice=floor(nslices/2); % middle slice in time +SPM.xBF.T = nslices; % number of time bins per scan % useless? cf. defaults above +SPM.xBF.T0 = ref_slice; % middle slice/timebin % useless? cf. defaults above +SPM.xBF.UNITS = 'scans'; % OPTIONS: 'scans'|'secs' for onsets +SPM.xBF.Volterra = 1; +SPM.xBF.name = 'hrf'; +SPM.xBF.order = 1; %2= hrf + time deriv --> 'hrf (with time derivative)'; +SPM.xBF.length = 32; % length in seconds + +SPM.xY.RT = TR; + +% number of scans and sessions +%--------------------------------------------------------------------------- +SPM.nscan = nscans; + +for ses=1:nses + SPM.Sess(ses).U=[]; +end + +rnam = {'PPI' 'contrast' region 'X','Y','Z','x','y','z'}; +for ses=1:nses + fn = spm_select('List',fullfile(scandir,deblank(Session{ses})),'^rp_.*txt'); + [r1,r2,r3,r4,r5,r6] = textread(fullfile(scandir,deblank(Session{ses}),fn(1,:)),'%f%f%f%f%f%f'); + SPM.Sess(ses).C.C = [myPPI{ses}.ppi myPPI{ses}.P myPPI{ses}.Y r1 r2 r3 r4 r5 r6]; + SPM.Sess(ses).C.name = rnam; +end + +defaults.stats.fmri.t = nslices; +defaults.stats.fmri.t0 = ref_slice; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% subject specific bit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +wkdir = [su anatype myana]; +if ~exist(wkdir, 'dir'); + mkdir(wkdir); +end +eval(['cd ' (wkdir)]); + +% global normalization: OPTIONS:'Scaling'|'None' +%--------------------------------------------------------------------------- +SPM.xGX.iGXcalc = 'None'; + +% low frequency confound: high-pass cutoff (secs) [Inf = no filtering] +%--------------------------------------------------------------------------- +SPM.xX.K(1).HParam = 128; + +% intrinsic autocorrelations: OPTIONS: 'none'|'AR(1) + w' +%----------------------------------------------------------------------- +SPM.xVi.form = 'AR(1)'; %AR(0.2)???? SOSART + +% specify SPM working dir for this sub +%=========================================================================== +SPM.swd = wkdir; + +% Configure design matrix +%=========================================================================== +SPM = spm_fmri_spm_ui(SPM); + +% Estimate parameters +%=========================================================================== +SPM = spm_spm(SPM); +return + + +function [] = Labnic_contrast_PPI(su,region) + +cd (fullfile(su,['analyse' filesep 'PPI'],['PPI_' region])) +load('SPM.mat'); + +SPM.xCon =[]; % reset xCon + +for i = 1:length(SPM.xX.name)%adding 6 for mvt regressors that are in SPM.xX.name + connam{i} = SPM.xX.name{i}(7:end); +end +PPI = double(strcmp(connam,'PPI')); +contrast = double(strcmp(connam,'contrast')); +vox = double(strcmp(connam,region)); +%---------- +%MAIN EFFECTS +%---------- +cn = 1; +Cnames{cn} = 'PPI'; +cwgt{cn} = PPI; +ctyp{cn} = 'F'; +cn = cn+1; +Cnames{cn} = 'contrast'; +cwgt{cn} = contrast; +ctyp{cn} = 'T'; +cn = cn+1; +Cnames{cn} = region; +cwgt{cn} = vox; +ctyp{cn} = 'T'; +cn = cn+1; +Cnames{cn} = 'PPI'; +cwgt{cn} = PPI; +ctyp{cn} = 'T'; +cn = cn+1; +Cnames{cn} = '-PPI'; +cwgt{cn} = -PPI; +ctyp{cn} = 'T'; + +save contrasts_name Cnames +for c = 1:cn + cw = [cwgt{c}]'; % pad with zero for constant + tmp(c) = spm_FcUtil('Set',Cnames{c},ctyp{c},'c',cw,SPM.xX.xKXs); +end +SPM.xCon = tmp; + +SPM = spm_contrasts(SPM); +return \ No newline at end of file diff --git a/labnic/Labnic_rfx_ones_spm8.m b/labnic/Labnic_rfx_ones_spm8.m new file mode 100644 index 0000000..8496cf3 --- /dev/null +++ b/labnic/Labnic_rfx_ones_spm8.m @@ -0,0 +1,196 @@ +function [] = Labnic_rfx_ones_spm8 +% create the second level analyis (random effect analysis RFX) +% create a one sample t-test with one group of subjects + +% you must speficied the 3 first line of the script +% dirname is the direcotry for the main RFX analysis +% it create a dir for each contrast in this main dir +% this code take into account that some of the subjects do not have all the +% contrasts +% Analysis of each subjects must be in: +% **...\data_fMRI\populations\subjects\analyse\ana1\** +% At the begining, the script create a mean strucutral image to display the +% results of the group analysis + +% this function has been adapted by Virginie Sterpenich (Virginie.Sterpenich@unige.ch) +% and optimised by Yann Cojan (yann.cojan@unige.ch) + +global name_ana; + +%% parameters to specify for each study +root_path = 'C:\experiments\FLANKER\'; % directory where are the populations, main directory +name_ana = 'ana_woST\'; %or 'ana2'; etc +dirname = 'RFX\RFX_ones_hypnosis_subjective_31s'; % name for the directory of the random analysis + +%% defining the pop_style +cd ([root_path filesep 'controls']) +Subject{1}= spm_select(Inf,'dir','which subjects do you want to process?'); +Subject = char(Subject); +nsuj = size(Subject,1); + +%% Creation of directory for the rfx +dirstr = strcat(root_path,filesep,dirname); +if ~exist(strcat(root_path,filesep,dirname)) + mkdir(strcat(root_path,filesep,dirname)) +end +cd(dirstr) + +%% starting analysing +% load the names of the contrasts from the first subject +% it use the contrasts_name matrix created in the Labnic_contrast script +path_suj1 =[deblank(Subject(1,:)) 'analyse' filesep name_ana]; + +% loop over contrasts + +% defaults.modality='FMRI'; +% disp(['Processing contrast ' num2str(icon) ' : ' char(Cnames(icon))]); +% disp('-----------------------------'); +%initialise variables +P = {}; scans = {}; + +% % Create the dir for the contrast of interest +% mkdir(char(Cnames(icon))); +Cnames = {'slatency_Cf' 'slatency_If' 'slatency_Cs' 'slatency_Is' 'slatency_ECf' 'slatency_EIf' 'slatency_ECs' 'slatency_EIs'}; +nb_con = size(Cnames,2); +% loop over subjects +count = 0; +for sub = 1:nsuj + count = count+1; + %go to the subject's analyse folder + path_ana =[deblank(Subject(sub,:)) 'analyse' filesep name_ana]; + + % check the name of the contrast + % Find for this subject the con.img corresponding to the contrast of + % interest (icon) + con = 0; + for icon = 1:nb_con %for td %10:19 %for hrf % 20:26 %for tdd % depending on F and T contrast at the first level + con = con+1; + if sub == 1 %for initialising the struct + matlabbatch{con}.spm.stats.factorial_design.des.t1.scans = {}; + matlabbatch{con}.spm.stats.factorial_design.dir = {char(strcat(dirstr,filesep,Cnames{icon}))}; + if ~exist(matlabbatch{con}.spm.stats.factorial_design.dir{1}) + mkdir(matlabbatch{con}.spm.stats.factorial_design.dir{1}) + end + end + %% mask + matlabbatch{con}.spm.stats.factorial_design.masking.im = 0; + matlabbatch{con}.spm.stats.factorial_design.masking.em = {'C:\experiments\FLANKER\RFX\RFX_anova_woST\mask.img,1'}; + % Take the adequate 'latency' img + str = Cnames{icon}; + files = spm_select('ExtFPList',path_ana,str); + % put the image con in the appropriate group + matlabbatch{con}.spm.stats.factorial_design.des.t1.scans{end+1} = files; + + + % %matlabbatch{con}.spm.stats.factorial_design.cov(1).c = [139 198 + % 178 184 161 172 123 142 125 174 214 177 102 145 121 136 174 109 105 139 175 131 148 130 142 183 ]'; + matlabbatch{con}.spm.stats.factorial_design.cov(1).c = [10,9,11,7,10,9,3,7,11,10,10,8,6,10,7,10,2,5,7,3,10,4,6,7,2,1,11,9,8,6,4,8;]'; %hypnosis subj + matlabbatch{con}.spm.stats.factorial_design.cov(1).cname = 'hypnosis subjective'; + matlabbatch{con}.spm.stats.factorial_design.cov(1).iCFI = 1; + matlabbatch{con}.spm.stats.factorial_design.cov(1).iCC = 1; + + % matlabbatch{con}.spm.stats.factorial_design.cov(1).c = [527.93,430.56,544.31,437.01,418.69,606.21,516.66,373.88,612.50,499.77,430.23,577.45,462.00,454.70,460.17,521.39,395.60,429.86,531.31,484.48,465.62,426.93,420.84,681.16,638.34,447.86,407.31,461.15,370.47,473.02]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(1).cname = 'reaction time'; + % matlabbatch{con}.spm.stats.factorial_design.cov(1).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(1).iCC = 1; + % + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [23.18,27.08,80.97,25.36,17.07,73.28,36.61,21.03,22.30,42.92,34.49,116.21,57.44,54.08,40.86,24.04,33.38,58.98,33.16,83.69,58.14,15.97,34.38,-22.34,10.28,78.25,19.23,19.67,49.42,10.67,52.88]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'incongruency effect'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + % + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [-7.2105,1.6933,-10.3191,-5.9564,12.103,-27.4546,11.0383,-8.5667,-9.85,4.7017,-4.4777,5.3444,-17.0412,-7.1307,4.0314,7.9951,-5.6508,14.6891,-17.6318,10.7182,-2.3345,4.404,9.8678,6.1827,5.8837,-1.9921,8.745,-5.7231,-2.1239,-3.0548;]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'TR_F-S'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [-18.9881,-24.9904,-85.9272,-28.1663,-7.4509,-69.0327,-33.1592,-21.4825,-22.5177,-31.5774,-30.9564,-119.0013,-63.5359,-54.963,-36.2025,-19.6949,-36.909,-57.6552,-38.0087,-91.712,-55.8303,-16.1885,-24.5821,23.7739,-69.5856,-16.0828,-14.7308,-50.3663,-10.876,-47.7222;]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'TR_Cf-If'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + % + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [20.0982,31.4695,72.5183,18.2599,27.5145,81.5441,52.4209,16.9066,7.8373,56.2911,37.8267,129.6121,59.0775,51.9855,40.9023,30.59,33.1506,63.7293,33.5807,88.6858,59.559,17.5099,38.3411,-39.5562,90.8655,21.9729,24.6094,44.8306,14.6509,53.9644;]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'TR_Cs-Is'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [-3.0502,4.0862,-11.864,-7.9314,16.0833,-7.4716,15.15,-6.5713,-12.2652,14.7077,1.1963,7.9776,-10.7498,-5.0541,4.3656,9.4451,-4.7046,10.3816,-11.0299,3.846,0.6971,2.8627,11.8134,-4.7998,13.5818,1.949,9.3118,-5.6294,0.8255,1.5937;]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'TR_Cf-Cs'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + + % matlabbatch{con}.spm.stats.factorial_design.cov(2).c = [-4.1603,-2.6332,-1.9456,-7.6981,-3.9411,-0.5668,-0.0937,-2.9494,-4.6485,-2.3929,1.5449,1.975,-3.9803,-19.983,-4.1117,-1.9954,2.4152,-10.006,-5.674,-6.2914,-2.0766,-0.3342,-1.45,-0.9462,4.3075,-6.6019,6.8722,-3.0316,1.5413,10.9825;]'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).cname = 'TR_If-Is'; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCFI = 1; + % matlabbatch{con}.spm.stats.factorial_design.cov(2).iCC = 1; + + if sub == 1 %for initialising the struct + matlabbatch{con}.spm.stats.factorial_design.masking.tm.tm_none = []; + matlabbatch{con}.spm.stats.factorial_design.masking.im = 1; + matlabbatch{con}.spm.stats.factorial_design.masking.em = {''}; + matlabbatch{con}.spm.stats.factorial_design.globalc.g_omit = []; + matlabbatch{con}.spm.stats.factorial_design.globalm.gmsca.gmsca_no = []; + matlabbatch{con}.spm.stats.factorial_design.globalm.glonorm = 1;% precise the contrasts between both groups + end + %% for estimation + con = con+1; + matlabbatch{con}.spm.stats.fmri_est.spmmat = {char(strcat(dirstr,filesep,Cnames{icon},filesep,'SPM.mat'))}; + matlabbatch{con}.spm.stats.fmri_est.method = 1; + %% for creating contrasts + con = con+1; + matlabbatch{con}.spm.stats.con.spmmat = {char(strcat(dirstr,filesep,Cnames{icon},filesep,'SPM.mat'))}; + matlabbatch{con}.spm.stats.con.consess{1}.tcon.name = Cnames{icon}; + matlabbatch{con}.spm.stats.con.consess{1}.tcon.convec = 1; + matlabbatch{con}.spm.stats.con.consess{1}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{2}.tcon.name = ['-' Cnames{icon}]; + % matlabbatch{con}.spm.stats.con.consess{2}.tcon.convec = -1; + % matlabbatch{con}.spm.stats.con.consess{2}.tcon.sessrep = 'none'; + matlabbatch{con}.spm.stats.con.consess{2}.tcon.name = matlabbatch{con-2}.spm.stats.factorial_design.cov(1).cname; + matlabbatch{con}.spm.stats.con.consess{2}.tcon.convec = [0 1]; + matlabbatch{con}.spm.stats.con.consess{2}.tcon.sessrep = 'none'; + matlabbatch{con}.spm.stats.con.consess{3}.tcon.name = ['-' matlabbatch{con-2}.spm.stats.factorial_design.cov(1).cname]; + matlabbatch{con}.spm.stats.con.consess{3}.tcon.convec = [0 -1]; + matlabbatch{con}.spm.stats.con.consess{3}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{4}.tcon.name = [matlabbatch{con-2}.spm.stats.factorial_design.cov(2).cname]; + % matlabbatch{con}.spm.stats.con.consess{4}.tcon.convec = [0 0 1]; + % matlabbatch{con}.spm.stats.con.consess{4}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.name = ['-' matlabbatch{con-2}.spm.stats.factorial_design.cov(2).cname]; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.convec = [0 0 -1]; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.name = ['-' matlabbatch{con-2}.spm.stats.factorial_design.cov(2).cname]; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.convec = [0 0 -1]; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.name = matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(2).cname; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.convec = [0 0 1]; + % matlabbatch{con}.spm.stats.con.consess{5}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.name = ['-' matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(2).cname]; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.convec = [0 0 -1]; + % matlabbatch{con}.spm.stats.con.consess{6}.tcon.sessrep = 'none'; + % + % matlabbatch{con}.spm.stats.con.consess{7}.tcon.name = matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(3).cname; + % matlabbatch{con}.spm.stats.con.consess{7}.tcon.convec = [0 0 0 1]; + % matlabbatch{con}.spm.stats.con.consess{7}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{8}.tcon.name = ['-' matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(3).cname]; + % matlabbatch{con}.spm.stats.con.consess{8}.tcon.convec = [0 0 0 -1]; + % matlabbatch{con}.spm.stats.con.consess{8}.tcon.sessrep = 'none'; + % + % matlabbatch{con}.spm.stats.con.consess{9}.tcon.name = matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(4).cname; + % matlabbatch{con}.spm.stats.con.consess{9}.tcon.convec = [0 0 0 0 1]; + % matlabbatch{con}.spm.stats.con.consess{9}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{10}.tcon.name = ['-' matlabbatch{con}.spm.stats{con-2}.factorial_design.cov(4).cname]; + % matlabbatch{con}.spm.stats.con.consess{10}.tcon.convec = [0 0 0 0 -1]; + % matlabbatch{con}.spm.stats.con.consess{10}.tcon.sessrep = 'none'; + % + % matlabbatch{con}.spm.stats.con.consess{11}.tcon.name = 'impulsivity'; + % matlabbatch{con}.spm.stats.con.consess{11}.tcon.convec = [0 1 1 1 1]; + % matlabbatch{con}.spm.stats.con.consess{11}.tcon.sessrep = 'none'; + % matlabbatch{con}.spm.stats.con.consess{12}.tcon.name = '-impulsivity'; + % matlabbatch{con}.spm.stats.con.consess{12}.tcon.convec = [0 -1 -1 -1 -1]; + % matlabbatch{con}.spm.stats.con.consess{12}.tcon.sessrep = 'none'; + end % end icon loop +end % end isub loop +save test_latency matlabbatch +% run the job for the design specification +spm_jobman('run',matlabbatch) + +return \ No newline at end of file diff --git a/labnic/Labnic_rfx_twos_spm5.m b/labnic/Labnic_rfx_twos_spm5.m new file mode 100644 index 0000000..74a346b --- /dev/null +++ b/labnic/Labnic_rfx_twos_spm5.m @@ -0,0 +1,205 @@ +function [] = Labnic_rfx_twos_spm5 + +% create the second level analyis (random effect analysis RFX) +% create a two sample t-test between 2 populations of subjects + +% you must speficied the 3 first line of the script +% dirname is the direcotry for the main RFX analysis +% it create a dir for each contrast in this main dir +% this code take into account that some of the subjects do not have all the +% contrasts +% Analysis of each subjects must be in: +% **...\data_fMRI\populations\subjects\analyse\ana1\** +% At the beginning, the script create a mean structural image to display the +% results of the group analysis + +% this function has been adapted by Virginie Sterpenich (Virginie.Sterpenich@unige.ch) + +global name_ana; + +%% parameters to specify for each study +root_path = 'D:\vs1'; % directory where are the populations, main directory +name_ana = 'ana1'; %or 'ana2'; etc +dirname = ['RFX_ana_2s']; % name for the directory of the random analysis + +%% defining the pop_style +cd (root_path) +Population = spm_select(Inf,'dir','which population do you want to process?'); +npop = size(Population,1); + +%% Definition of subjects to process +for pop=1:npop + cd(Population(pop,1:end)) + Subject{pop}= spm_select(Inf,'dir','which subjects do you want to process?'); +end +Subject = char(Subject); +nsuj = size(Subject,1); + +%% Creation of directory for the rfx +dirstr = strcat(root_path,filesep,dirname); +if ~exist(strcat(root_path,filesep,dirname)) + mkdir(strcat(root_path,filesep,dirname)) +end + +%% create mean structural image to display results of the group +disp('Creating mean structural image'); +PM = cell(nsuj,1); +ii=0; +for sub = 1:nsuj + %go to the subject's analyse folder + sufolder= deblank(Subject(sub,:)); + path_ana =[sufolder 'scans' filesep 'struct']; + eval(['cd ' path_ana]); + % select the struct img + struct_img = spm_select('List',path_ana,'^ws*'); + PM{sub} = [path_ana filesep struct_img]; + ii=ii+1; +end +% create the expression for the mean +expression = '(i'; +for jj = [1:ii] + expression = [expression num2str(jj) '+i']; +end +expression = [expression(1:end-2) ')/' num2str(ii)]; +% fil the job and calculate +jobs{1}.util{1}.imcalc.input = PM; +jobs{1}.util{1}.imcalc.output = strcat([dirstr filesep 'meanstruct.nii']); +jobs{1}.util{1}.imcalc.expression = expression; + +jobs{1}.util{1}.imcalc.options.dmtx = 0; +jobs{1}.util{1}.imcalc.options.mask = 0; +jobs{1}.util{1}.imcalc.options.interp = 0; +jobs{1}.util{1}.imcalc.options.dtype = 4; +% run the job +spm_jobman('run',jobs) +clear jobs + +%% starting analysing + +cd(dirstr) +% load the names of the contrasts from the first subject +% it use the contrasts_name matrix created in the Labnic_contrast script +path_suj1 =[Subject(1,:) 'analyse' filesep name_ana]; +load(strcat(path_suj1,filesep,'contrasts_name')); +% Cnames = Cnames(:,[2:7]);% if you don't want analyse all the contrasts (ex: only 2 to 7) +nb_con = size(Cnames,2); + +% loop over contrasts +for icon = 1:nb_con + defaults.modality='FMRI'; + disp(['Processing contrast ' num2str(icon) ' : ' char(Cnames(icon))]); + disp('-----------------------------'); + %initialise variables + P = {}; scans1 = {}; scans2 = {}; + % go to the main dir + cd(dirstr) + % Create the dir for the contrast of interest + mkdir(char(Cnames(icon))); + + % loop over subjects + for sub = 1:nsuj + %go to the subject's analyse folder + path_ana =[deblank(Subject(sub,:)) 'analyse' filesep name_ana]; + eval(['cd ' path_ana]); + %select SPM.mat + load SPM + % check the name of the contrast + % Find for this subject the con.img corresponding to the contrast of interest (icon) + % This works even if the name of the con.img differs from one subject to the other !watch out for multiple matches! + contrastindice = []; + for icontrast = 1:size(SPM.xCon,2) + contrastmatch = findstr(SPM.xCon(icontrast).name,Cnames{icon}); + if ~isempty(contrastmatch) + contrastindice = icontrast; + break + end + end + %%alternative to loop above, adding some error messages + %contrastmatch = find(~cellfun('isempty',regexp(cellstr(char(SPM.xCon.name)),Cnames{icon}))); + % if isempty(contrastmatch) ...no contrast was found + % error('No matching contrast found - check names'); + % elseif length(contrastmatch)>1 ... more than 1 contrasts found + % error('Multiple matches found - check names'); + % else + % contrastindice = icontrast; ...found exactly 1 match + % end + + % Take the adequate 'con' img + if ~isempty(contrastindice)% au cas ou le contraste n'existe pas chez un sujet + if contrastindice < 10 + str = ['^con_000+' num2str(contrastindice) filesep '.img$']; + elseif contrastindice < 100 + str = ['^con_00+' num2str(contrastindice) filesep '.img$']; + else + str = ['^con_0+' num2str(contrastindice) filesep '.img$']; + end + files = spm_select('List',pwd,str); + P{end+1,1} = strcat(path_ana,filesep,files,',1'); + % put the image con in the appropriate group + if any(strcmp(P{end}(1:size(deblank(Population(1,:)),2)),deblank(Population(1,:)))); + scans1{end+1,1} = P{end,:}; + elseif any(strcmp(P{end}(1:size(deblank(Population(2,:)),2)),deblank(Population(2,:)))); + scans2{end+1,1} = P{end,:}; + end + end + clear SPM + end % end isub loop + %affiche les img con sélectionnées + scans1 + scans2 + % fil the job + jobs{1}.stats{1}.factorial_design.des.t2.scans1 = scans1; + jobs{1}.stats{1}.factorial_design.des.t2.scans2 = scans2; + jobs{1}.stats{1}.factorial_design.dir = {char(strcat(dirstr,filesep,Cnames{icon}))}; + % normal parameters + jobs{1}.stats{1}.factorial_design.des.t2.dept = 0; + jobs{1}.stats{1}.factorial_design.des.t2.variance = 1; + jobs{1}.stats{1}.factorial_design.des.t2.gmsca = 0; + jobs{1}.stats{1}.factorial_design.des.t2.ancova = 0; + jobs{1}.stats{1}.factorial_design.masking.tm.tm_none = []; + jobs{1}.stats{1}.factorial_design.masking.im = 1; + jobs{1}.stats{1}.factorial_design.masking.em = {''}; + jobs{1}.stats{1}.factorial_design.globalc.g_omit = []; + jobs{1}.stats{1}.factorial_design.globalm.gmsca.gmsca_no = []; + jobs{1}.stats{1}.factorial_design.globalm.glonorm = 1; + + % run the job for the design specification + spm_jobman('run',jobs) + clear jobs + + %% Estimate parameters + cd(strcat(dirstr,filesep,Cnames{icon})) + load SPM + SPM = spm_spm(SPM); + + %% Create contrasts + % select the SPM.mat + jobs{1}.stats{1}.con.spmmat = {char(strcat(dirstr,filesep,Cnames{icon},filesep,'SPM.mat'))}; + + % precise the contrasts between both groups + jobs{1}.stats{1}.con.consess{1}.tcon.name = 'Gr1 vs Gr2'; + jobs{1}.stats{1}.con.consess{1}.tcon.convec = [1 -1]; + jobs{1}.stats{1}.con.consess{1}.tcon.sessrep = 'none'; + + jobs{1}.stats{1}.con.consess{2}.tcon.name = 'Gr2 vs Gr1'; + jobs{1}.stats{1}.con.consess{2}.tcon.convec = [-1 1]; + jobs{1}.stats{1}.con.consess{2}.tcon.sessrep = 'none'; + + jobs{1}.stats{1}.con.consess{3}.tcon.name = 'Gr1'; + jobs{1}.stats{1}.con.consess{3}.tcon.convec = [1 0]; + jobs{1}.stats{1}.con.consess{3}.tcon.sessrep = 'none'; + + jobs{1}.stats{1}.con.consess{4}.tcon.name = 'Gr2'; + jobs{1}.stats{1}.con.consess{4}.tcon.convec = [0 1]; + jobs{1}.stats{1}.con.consess{4}.tcon.sessrep = 'none'; + + jobs{1}.stats{1}.con.consess{5}.tcon.name = 'Gr1_and_Gr2'; + jobs{1}.stats{1}.con.consess{5}.tcon.convec = [1 1]; + jobs{1}.stats{1}.con.consess{5}.tcon.sessrep = 'none'; + % run the job + spm_jobman('run',jobs) + clear jobs + cd(dirstr) + +end % end icond loop over contrasts +return \ No newline at end of file diff --git a/labnic/extract_clubetas.m b/labnic/extract_clubetas.m new file mode 100644 index 0000000..9025142 --- /dev/null +++ b/labnic/extract_clubetas.m @@ -0,0 +1,292 @@ +function [Data] = extract_clubetas(SPM,xSPM) +sub2pr=[1:SPM.nscan]; +clear Data +[xyzmm,i] = spm_XYZreg('NearestXYZ',spm_results_ui('GetCoords'),xSPM.XYZmm); +spm_results_ui('SetCoords',xSPM.XYZmm(:,i)); +A = spm_clusters(xSPM.XYZ); +j = find(A == A(i)); +xyz = xSPM.XYZmm(:,j)'; + +pathlist = SPM.xY.P; + +allbetas= []; +Allbetas = []; +allxyz = []; + +%--- to write +XYZ = SPM.xVol.XYZ; +XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; +bob = spm_input('nature of extraction','+1','b','VOI|cluster',[0,1]); + +if ~bob + [xyz xyzmm] = spm_VOI_yann(SPM,xSPM); + xyz = xyzmm'; +end + +cond_list = []; +for sub = 1:length(sub2pr) + mydir = fileparts(pathlist{sub}); + sSPM = load([mydir filesep 'SPM.mat']); + nses = length(sSPM.SPM.Sess);%num of session + convec = zeros(1,length(sSPM.SPM.Vbeta)); + for ses = 1:nses + for j = 1:length(sSPM.SPM.Sess(ses).Fc) + index = sSPM.SPM.Sess(ses).col(sSPM.SPM.Sess(ses).Fc(1,j).i); + convec(ses,index) = 1; + end + end + real = sSPM.SPM.xX.name(any(convec,1)); + for j = 1:length(real) + b = strfind(real{j},'*bf'); + list_cond{j} = real{j}(7:b-1); + end + [b,c,d] = unique(list_cond,'first'); + [m n] = sort(c); + cond_list = [cond_list b(n)]; +end +[b,c,d] = unique(cond_list,'first'); +[m n] = sort(c); +thelist = b(n); + +Allbetas = NaN(length(sub2pr),length(thelist)); + + +messages = {'hot baby... hot...' 'what are you thinking about?...' 'wait and see...' 'wait for reaching heaven...' 'Please wait... (no luck! the basic)'}; +colors = {[1,0.4,0.6] [1,0.6,0.4] [0.4,1,0.6] [0.4,0.6,1] [1,0.4,1]}; +[m n] = sort(rand(1,5)); +h = waitbar(0,messages{n(1)},'Color',colors{n(1)}); + +for sub = 1:length(sub2pr) + mydir = fileparts(pathlist{sub}); + sSPM = load([mydir filesep 'SPM.mat']); + nses = length(sSPM.SPM.Sess);%num of session + for i = 1:length(sSPM.SPM.Vbeta) + sSPM.SPM.Vbeta(i).fname = [mydir filesep sSPM.SPM.Vbeta(i).fname]; + end + tmpallbetas= []; + tmpallxyz = []; + Tmpallbetas= []; + list_cond = []; + for cluvox = 1:size(xyz,1) + [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + govox=1; + if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=1.7321 %one voxel in each dimZ + govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',... + num2str(xyz(cluvox,:)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0]); + end + vXYZ = XYZ(:,i) ; % coordinates in voxels + + %-Get parameter and hyperparameter estimates + beta= spm_get_data(sSPM.SPM.Vbeta, vXYZ); + + convec = zeros(1,length(sSPM.SPM.Vbeta)); + for ses = 1:nses + for j = 1:length(sSPM.SPM.Sess(ses).Fc) + index = sSPM.SPM.Sess(ses).col(sSPM.SPM.Sess(ses).Fc(1,j).i); + convec(ses,index) = 1; + end + + end + real = sSPM.SPM.xX.name(any(convec,1)); + for j = 1:length(real) + b = strfind(real{j},'*bf'); + list_cond{j} = real{j}(7:b-1); + end + tmpallbetas = [tmpallbetas; beta(any(convec,1))']; + end + + for c = 1:length(thelist) + C = strcmp(thelist{c},list_cond); + Tmpallbetas = [Tmpallbetas mean(sum(tmpallbetas(:,C)))]; + end + + Allbetas(sub,:) = Tmpallbetas; + %allxyz= [allxyz;mean(tmpallxyz,1)]; + waitbar(sub/length(sub2pr),h) +end +close(h) + +ctitle = [num2str(nxyz') ' nvox = ' num2str(size(xyz,1))]; +tmpaxe = thelist(1:length(thelist)); + +npop = size(SPM.xX.X,2); +for pop = 1:npop + Data{pop}(:,:) = reshape(Allbetas(logical(repmat(SPM.xX.X(:,pop),1,size(Allbetas,2)))),sum(SPM.xX.X(:,pop)),size(Allbetas,2)); +end +[Maj,ST,SE] = yann_bar(Data); +switch spm_input('errorbar?',2,'b','yes|no'); + case 'yes' + figure + h = bar(Maj'); + for i = 1:size(Maj,1) + if i == 1 & npop > 1 + N = -0.08; + elseif i == 1 + N = 0; + else + N = 0.08; + end + for j = 1:size(Maj,2) + coef = j+npop*N; + line([coef coef],([SE(i,j) 0 - SE(i,j)] + Maj(i,j)),... + 'LineWidth',1.5,'Color','k') + line ([coef-0.05 coef+0.05],([SE(i,j)+Maj(i,j) SE(i,j)+Maj(i,j)]),... + 'LineWidth',1.5,'Color','k') + line ([coef-0.05 coef+0.05],([-SE(i,j)+Maj(i,j) -SE(i,j)+Maj(i,j)]),... + 'LineWidth',1.5,'Color','k') + end + end + case 'no' + figure + h = bar(Maj'); + set(h,'FaceColor',[1 1 1]*.8) +end +set(gca, 'XTickLabel',tmpaxe, 'XTick' , [1:length(tmpaxe)],'FontSize',6); +title(ctitle,'FontSize',16) + +%% Functions +function [Maj,ST,SE] = yann_bar(Data) +% function [Maj,ST,SE] = yann_bar(Data) +% calculate Mean, stdev and std error for Data +% developed by Yann Cojan (yann.cojan@unige.ch) + +npop = length(Data) + +switch spm_input('Reset lowest value to:?',1,'b','zero|mean|unchanged'); + case 'zero' + for pop = 1:npop + if isempty(find(mean(Data{pop})<0)) + Maj(pop,:) = mean(Data{pop},1)- min(mean(Data{pop},1)); + else + Maj(pop,:) = mean(Data{pop},1) + abs(min(mean(Data{pop},1))); + end + end + case 'mean' + for pop = 1:npop + Maj(pop,:) = mean(Data{pop},1) - mean(mean(Data{pop},1)); + end + case 'unchanged' + for pop = 1:npop + if any(any(isnan(Data{pop}))) + count = 1; + for hu = 1:size(Data{pop},2) + Maj(pop,hu) = mean(Data{pop}(~isnan(Data{pop}(:,hu)),hu)); + end + else + Maj(pop,:) = mean(Data{pop},1); + end + end +end +for pop = 1:npop + if size(Data{pop},1)>1 + if any(any(isnan(Data{pop}))) + for hu = 1:size(Data{pop},2) + SE(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu))/sqrt(size(Data{pop}(~isnan(Data{pop}(:,hu))),1)); + ST(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu)); + end + else + SE(pop,:) = std(Data{pop})/sqrt(size(Data{pop},1)); + ST(pop,:) = std(Data{pop}); + end + else + if any(any(isnan(Data{pop}))) + for hu = 1:size(Data{pop},2) + SE(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu))/sqrt(size(Data{pop}(~isnan(Data{pop}(:,hu))),1)); + ST(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu)); + end + else + SE(pop,:) = zeros(1,size(Data{pop},2)); + ST(pop,:) = zeros(1,size(Data{pop},2)); + end + end +end + +function [XYZ XYZmm] = spm_VOI_yann(SPM,xSPM,hReg) +% see spm_VOI for help + +%-Parse arguments +%----------------------------------------------------------------------- +if nargin < 2, error('insufficient arguments'), end +if nargin < 3, hReg = []; end + +Num = 16; % maxima per cluster +Dis = 04; % distance among maxima (mm) + +%-Title +%----------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Small Volume Correction']); + +%-Get current location {mm} +%----------------------------------------------------------------------- +xyzmm = spm_results_ui('GetCoords'); + +%-Specify search volume +%----------------------------------------------------------------------- +str = sprintf(' at [%.0f,%.0f,%.0f]',xyzmm(1),xyzmm(2),xyzmm(3)); +SPACE = spm_input('Search volume...',-1,'m',... + {['Sphere',str],['Box',str],'Image'},['S','B','I']); + +% voxels in entire search volume {mm} +%----------------------------------------------------------------------- +XYZmm = SPM.xVol.M(1:3,:)*[SPM.xVol.XYZ; ones(1, SPM.xVol.S)]; +Q = ones(1,size(xSPM.XYZmm,2)); +O = ones(1,size( XYZmm,2)); +FWHM = xSPM.FWHM; + + +switch SPACE + + case 'S' %-Sphere + %--------------------------------------------------------------- + D = spm_input('radius of VOI {mm}',-2); + str = sprintf('%0.1fmm sphere',D); + j = find(sum((xSPM.XYZmm - xyzmm*Q).^2) <= D^2); + k = find(sum(( XYZmm - xyzmm*O).^2) <= D^2); + D = D./xSPM.VOX; + + + case 'B' %-Box + %--------------------------------------------------------------- + D = spm_input('box dimensions [k l m] {mm}',-2); + str = sprintf('%0.1f x %0.1f x %0.1f mm box',D(1),D(2),D(3)); + j = find(all(abs(xSPM.XYZmm - xyzmm*Q) <= D(:)*Q/2)); + k = find(all(abs( XYZmm - xyzmm*O) <= D(:)*O/2)); + D = D./xSPM.VOX; + + + case 'I' %-Mask Image + %--------------------------------------------------------------- + Msk = spm_select(1,'image','Image defining search volume'); + D = spm_vol(Msk); + str = sprintf('image mask: %s',spm_str_manip(Msk,'a30')); + VOX = sqrt(sum(D.mat(1:3,1:3).^2)); + FWHM = FWHM.*(xSPM.VOX./VOX); + XYZ = D.mat \ [xSPM.XYZmm; ones(1, size(xSPM.XYZmm, 2))]; + j = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + XYZ = D.mat \ [ XYZmm; ones(1, size( XYZmm, 2))]; + k = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + +end + +xSPM.S = length(k); +xSPM.R = spm_resels(FWHM,D,SPACE); +xSPM.Z = xSPM.Z(j); +xSPM.XYZ = xSPM.XYZ(:,j); +xSPM.XYZmm = xSPM.XYZmm(:,j); +xSPM.Ps = xSPM.Ps(k); +XYZ = xSPM.XYZ; +XYZmm = xSPM.XYZmm; +%-Tabulate p values +%----------------------------------------------------------------------- +str = sprintf('search volume: %s',str); +if any(strcmp(SPACE,{'S','B'})) + str = sprintf('%s at [%.0f,%.0f,%.0f]',str,xyzmm(1),xyzmm(2),xyzmm(3)); +end + +TabDat = spm_list('List',xSPM,hReg,Num,Dis,str); + +%-Reset title +%----------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Results']); \ No newline at end of file diff --git a/labnic/nic_spm_explorer.m b/labnic/nic_spm_explorer.m new file mode 100644 index 0000000..eab8e05 --- /dev/null +++ b/labnic/nic_spm_explorer.m @@ -0,0 +1,80 @@ +function [varargout] = nic_spm_explorer(input,varargin) +%NIC_SPM_EXPLORER - SPM results explorer +% [] = nic_spm_explorer() will open a new window asking for a SPM file +% +% +% [] = nic_spm_explorer(SPM) +% [] = nic_spm_explorer('/some/path/SPM.mat') +% [] = nic_spm_explorer('/some/path/SPM.mat','option1', value1, ...) +% [] = nic_spm_explorer('/some/path/SPM.mat','option1', value1, ...) +% +% Example +% >> nic_spm_explorer +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-16 Creation +% +% ----------------------------- Script History --------------------------------- + +% TO DO +% Everything! based on xjview.m plus: +% - no conflict with the spm_figure (Graphics) window +% - yoke windows "à la" MRICro(n) +% - remove uicontrol for cleaner export via "copy figure" +% - + +if nargin<1 + action='start'; +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='start'; +end + +% equivalent to +varargout={eval(sprintf('action_%s(varargin{:});',action))}; + +%% ACTION CALLS =========================================================== + +function [hf]=action_start(varargin) +OPTIONS = load_options(varargin) + + +%% PRIVATE FUNCTIONS ====================================================== +% +function OPTIONS=load_options(varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +return; % load_options +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/labnic/nifti2img.m b/labnic/nifti2img.m new file mode 100644 index 0000000..c5b4987 --- /dev/null +++ b/labnic/nifti2img.m @@ -0,0 +1,860 @@ +function varargout = nifti2ana(P) +% NIFTI2ANA converts images from nifti to analyze format readable in SPM2 +% V = NIFTI2ANA(P) converts files that are in SPM5's nifti format to the +% analyze format that was readable by SPM2. This allows one to use files +% processed in SPM5 to be analyzed in SPM2. +% +% P are the filenames to be converted. If P is empty the user is +% prompted to select the files. +% +% V is a structure array of mapped volumes. This can be used to read the +% new files or discarded. +% +% SPM5 must be in the Matlab path. +% +% The converted files are prepended with 'n2a_' +% +% The program REQUIRES SPM5 image files (either .nii or .img) as input, +% and outputs SPM2 compatible analyze-type files. This program is not +% for converting SPM5 .nii to SPM5 .img files. To do that simply read +% in the data, change the filename to have a .img extension, and write +% out the new file. For example: +% v = spm_vol('my_file_name.nii'); +% img = spm_read_vols(v); +% vnew = v; +% vnew.fname = [vnew.fname(1:end-3), 'img']; +% vnew = spm_create_vol(vnew); +% vnew = spm_write_vol(vnew,img); +% +% Author: Darren Gitelman +% $Id: nifti2ana.m,v 1.3 2008-07-22 13:06:43-05 drg Exp drg $ +% updated 2010-07-14 by drg. + +% Get image filenames if none are provided +if nargin < 1 + P = spm_select(Inf,'image','Select images to convert'); +end +if isempty(P) + disp('No files selected. Aborting conversion.') + return; +end + +% Map the volumes using SPM5 file handling tools +fprintf('Reading SPM5 NIFTI volume headers..'); +Vin = spm_vol(deblank(P)); +fprintf('Done\n'); +fprintf('There are %i files to be converted.\n',numel(Vin)); + +Vout = struct('fname' , '',... + 'dim' , [],... + 'mat' , [],... + 'pinfo' , [],... + 'descrip', '',... + 'n' , [],... + 'private', []); +V = Vout; +% Convert the volume structures to be analyze compatible +fprintf('Creating SPM2-compatible headers..') + +for i = 1:numel(Vin) + fprintf('%5i',i); + [tmppth tmpfn tmpext] = fileparts(Vin(i).fname); + dt = Vin(i).dt(1); + tmpfn = ['n2a_',tmpfn]; + Vtmp.fname = fullfile(tmppth,[tmpfn,tmpext]); + Vtmp.dim = [Vin(i).dim dt]; + Vtmp.mat = Vin(i).mat; + if spm_flip_analyze_images + fprintf(' : Flipping image L/R\n') + Vtmp.mat = spm_matrix([0 0 0 0 0 0 -1 1 1 0 0 0])*Vtmp.mat; + fprintf('Creating SPM2-compatible headers..%5i',i) + end + Vtmp.pinfo = Vin(i).pinfo; + Vtmp.descrip = ['nifti2analyze converted: ',Vin(i).descrip]; + + dtype = Vin(i).private.dat.dtype; + + % must pass the dtype to figure out if endianness is swapped. + Vout(i)= my_spm2_create_vol(Vtmp,'noopen',dtype); + fprintf(sprintf(repmat('\b',1,5))) +end +fprintf('Done\n') + +fprintf('Writing SPM2-compatible image files..') +for i = 1:numel(Vout) + fprintf('%5i',i); + y = spm_read_vols(Vin(i)); + V(i) = my_spm2_write_vol(Vout(i),y,dtype); + fprintf(sprintf(repmat('\b',1,5))) +end +fprintf('All Done!\n') +if nargout == 1 + varargout{1} = V; +end + +%_______________________________________________________________________ +%_______________________________________________________________________ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THESE FUNCTIONS COME FROM THE SPM2 VERSION OF SPM_CREATE_VOL +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function V = my_spm2_create_vol(V,varargin) +% Create an image file. +% FORMAT Vo = spm_create_vol(Vi,['noopen']) +% Vi - data structure containing image information. +% - see spm_vol for a description. +% 'noopen' - optional flag to say "don't open/create the image file". +% Vo - data structure after modification for writing. +% varargin can now have 2 arguments, 'noopen' and the dtype. +%_______________________________________________________________________ +% @(#)spm_create_vol.m 2.14 John Ashburner 03/07/31 +for i=1:numel(V) + if nargin>1, + v = my_spm2_internal_create_vol(V(i),varargin{:}); + else + v = my_spm2_internal_create_vol(V(i)); + end; + f = fieldnames(v); + for j=1:size(f,1), + %eval(['V(i).' f{j} ' = v.' f{j} ';']); + V = setfield(V,{i},f{j},getfield(v,f{j})); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function V = my_spm2_internal_create_vol(V,varargin) +if ~isfield(V,'n') || isempty(V.n) + V.n = 1; +end; + +if ~isfield(V,'descrip') || isempty(V.descrip) + V.descrip = 'SPM2 compatible'; +end; +V.private = struct('hdr',[]); + +% Orientation etc... +M = V.mat; +if spm_flip_analyze_images, M = diag([-1 1 1 1])*M; end; +vx = sqrt(sum(M(1:3,1:3).^2)); +if det(M(1:3,1:3))<0, vx(1) = -vx(1); end; +origin = M\[0 0 0 1]'; +origin = round(origin(1:3)); + +[pth nam] = fileparts(V.fname); +fname = fullfile(pth,[nam, '.hdr']); +try + [hdr swapped] = my_spm2_spm_read_hdr(fname); +catch + warning(['Could not read "' fname '"']); + swapped = 0; + hdr = []; +end; + +if ~isempty(hdr) && (hdr.dime.dim(5)>1 || V.n>1), + % cannot simply overwrite the header + + hdr.dime.dim(5) = max(V.n,hdr.dime.dim(5)); + if any(V.dim(1:3) ~= hdr.dime.dim(2:4)) + error('Incompatible image dimensions'); + end; + + if sum((vx-hdr.dime.pixdim(2:4)).^2)>1e-6, + error('Incompatible voxel sizes'); + end; + + V.dim(4) = spm_type(spm_type(hdr.dime.datatype)); + mach = 'native'; + if swapped, + V.dim(4) = V.dim(4)*256; + if spm_platform('bigend'), + mach = 'ieee-le'; + else + mach = 'ieee-be'; + end; + end; + + if isfinite(hdr.dime.funused1) && hdr.dime.funused1 + scal = hdr.dime.funused1; + if isfinite(hdr.dime.funused2), + dcoff = hdr.dime.funused2; + else + dcoff = 0; + end; + else + if hdr.dime.glmax-hdr.dime.glmin && hdr.dime.cal_max-hdr.dime.cal_min + scal = (hdr.dime.cal_max-hdr.dime.cal_min)/(hdr.dime.glmax-hdr.dime.glmin); + dcoff = hdr.dime.cal_min - scal*hdr.dime.glmin; + else + scal = 1; + dcoff = 0; + warning(['Assuming a scalefactor of 1 for "' V.fname '".']); + end; + end; + V.pinfo(1:2) = [scal dcoff]'; + V.private.hdr = hdr; +else + + V.private.hdr = my_spm2_create_defaults; + + my_endianess = spm_platform('bigend'); + if nargin == 3 + dtype = varargin{2}; + elseif nargin ==2 + dtype = varargin{1}; + end + + if my_endianess && ~isempty(findstr(dtype,'BE')) || ... + ~my_endianess && isempty(findstr(dtype,'BE')) + swapped = 0; + else + swapped = 1; + end + dt = spm_type(spm_type(V.dim(4))); + if any(dt == [128+2 128+4 128+8]), + % Convert to a form that Analyze will support + dt = dt - 128; + end; + V.dim(4) = dt; + mach = 'native'; + if swapped + V.dim(4) = V.dim(4)*256; + if spm_platform('bigend'), + mach = 'ieee-le'; + else + mach = 'ieee-be'; + end; + end; + V.private.hdr.dime.datatype = dt; + V.private.hdr.dime.bitpix = spm_type(dt,'bits'); + + if spm_type(dt,'intt'), + + V.private.hdr.dime.glmax = spm_type(dt,'maxval'); + V.private.hdr.dime.glmin = spm_type(dt,'minval'); + + if 0, % Allow DC offset + V.private.hdr.dime.cal_max = max(V.private.hdr.dime.glmax*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.cal_min = min(V.private.hdr.dime.glmin*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.funused1 = 0; + scal = (V.private.hdr.dime.cal_max - V.private.hdr.dime.cal_min)/... + (V.private.hdr.dime.glmax - V.private.hdr.dime.glmin); + dcoff = V.private.hdr.dime.cal_min - V.private.hdr.dime.glmin*scal; + V.pinfo = [scal dcoff 0]'; + else % Don't allow DC offset + cal_max = max(V.private.hdr.dime.glmax*V.pinfo(1,:) + V.pinfo(2,:)); + cal_min = min(V.private.hdr.dime.glmin*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.funused1 = cal_max/V.private.hdr.dime.glmax; + if V.private.hdr.dime.glmin, + V.private.hdr.dime.funused1 = max(V.private.hdr.dime.funused1,... + cal_min/V.private.hdr.dime.glmin); + end; + V.private.hdr.dime.cal_max = V.private.hdr.dime.glmax*V.private.hdr.dime.funused1; + V.private.hdr.dime.cal_min = V.private.hdr.dime.glmin*V.private.hdr.dime.funused1; + V.pinfo = [V.private.hdr.dime.funused1 0 0]'; + end; + else + V.private.hdr.dime.glmax = 1; + V.private.hdr.dime.glmin = 0; + V.private.hdr.dime.cal_max = 1; + V.private.hdr.dime.cal_min = 0; + V.private.hdr.dime.funused1 = 1; + end; + + V.private.hdr.dime.pixdim(2:4) = vx; + V.private.hdr.dime.dim(2:4) = V.dim(1:3); + V.private.hdr.dime.dim(5) = V.n; + V.private.hdr.hist.origin(1:3) = origin; + + d = 1:min([length(V.descrip) 79]); + V.private.hdr.hist.descrip = char(zeros(1,80)); + V.private.hdr.hist.descrip(d) = V.descrip(d); + V.private.hdr.hk.db_name = char(zeros(1,18)); + [pth, nam] = fileparts(V.fname); + d = 1:min([length(nam) 17]); + V.private.hdr.hk.db_name(d) = nam(d); +end; + +V.pinfo(3) = prod(V.private.hdr.dime.dim(2:4))*V.private.hdr.dime.bitpix/8*(V.n-1); + +fid = fopen(fname,'w',mach); +if (fid == -1), + error(['Error opening ' fname '. Check that you have write permission.']); +end; + +my_spm2_write_hk(fid,V.private.hdr.hk); +my_spm2_write_dime(fid,V.private.hdr.dime); +my_spm2_write_hist(fid,V.private.hdr.hist); +fclose(fid); + +fname = fullfile(pth,[nam, '.mat']); +off = -vx'.*origin; +mt = [vx(1) 0 0 off(1) ; 0 vx(2) 0 off(2) ; 0 0 vx(3) off(3) ; 0 0 0 1]; +if spm_flip_analyze_images, mt = diag([-1 1 1 1])*mt; end; + +if sum((V.mat(:) - mt(:)).*(V.mat(:) - mt(:))) > eps*eps*12 || exist(fname,'file')==2 + if exist(fname,'file')==2, + clear mat + str = load(fname); + if isfield(str,'mat'), + mat = str.mat; + elseif isfield(str,'M'), + mat = str.M; + if spm_flip_analyze_images, + for i=1:size(mat,3), + mat(:,:,i) = diag([-1 1 1 1])*mat(:,:,i); + end; + end; + end; + mat(:,:,V.n) = V.mat; + mat = my_spm2_fill_empty(mat,mt); + M = mat(:,:,1); + if spm_flip_analyze_images + M = diag([-1 1 1 1])*M; + end; + try + save(fname,'mat','M','-append'); + catch % Mat-file was probably Matlab 4 + save(fname,'mat','M'); + end; + else + clear mat + mat(:,:,V.n) = V.mat; + mat = my_spm2_fill_empty(mat,mt); + M = mat(:,:,1); + if spm_flip_analyze_images + M = diag([-1 1 1 1])*M; + end; + save(fname,'mat','M'); + end; +end; + +if nargin==1 || ~strcmp(varargin{1},'noopen') + fname = fullfile(pth,[nam, '.img']); + V.private.fid = fopen(fname,'r+',mach); + if (V.private.fid == -1), + V.private.fid = fopen(fname,'w',mach); + if (V.private.fid == -1), + error(['Error opening ' fname '. Check that you have write permission.']); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function Mo = my_spm2_fill_empty(Mo,Mfill) +todo = []; +for i=1:size(Mo,3) + if ~any(any(Mo(:,:,i))), + todo = [todo i]; + end; +end; +if ~isempty(todo) + for i=1:length(todo), + Mo(:,:,todo(i)) = Mfill; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_spm2_write_hk(fid,hk) +% write (struct) header_key +%----------------------------------------------------------------------- +fseek(fid,0,'bof'); +fwrite(fid,hk.sizeof_hdr, 'int32'); +fwrite(fid,hk.data_type, 'char' ); +fwrite(fid,hk.db_name, 'char' ); +fwrite(fid,hk.extents, 'int32'); +fwrite(fid,hk.session_error,'int16'); +fwrite(fid,hk.regular, 'char' ); +if fwrite(fid,hk.hkey_un0, 'char' )~= 1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_spm2_write_dime(fid,dime) +% write (struct) image_dimension +%----------------------------------------------------------------------- +fseek(fid,40,'bof'); +fwrite(fid,dime.dim, 'int16'); +fwrite(fid,dime.vox_units, 'uchar' ); +fwrite(fid,dime.cal_units, 'uchar' ); +fwrite(fid,dime.unused1, 'int16' ); +fwrite(fid,dime.datatype, 'int16'); +fwrite(fid,dime.bitpix, 'int16'); +fwrite(fid,dime.dim_un0, 'int16'); +fwrite(fid,dime.pixdim, 'float'); +fwrite(fid,dime.vox_offset, 'float'); +fwrite(fid,dime.funused1, 'float'); +fwrite(fid,dime.funused2, 'float'); +fwrite(fid,dime.funused2, 'float'); +fwrite(fid,dime.cal_max, 'float'); +fwrite(fid,dime.cal_min, 'float'); +fwrite(fid,dime.compressed, 'int32'); +fwrite(fid,dime.verified, 'int32'); +fwrite(fid,dime.glmax, 'int32'); +if fwrite(fid,dime.glmin, 'int32')~=1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_spm2_write_hist(fid,hist) +% write (struct) data_history +%----------------------------------------------------------------------- +fseek(fid,148,'bof'); +fwrite(fid,hist.descrip, 'uchar'); +fwrite(fid,hist.aux_file, 'uchar'); +fwrite(fid,hist.orient, 'uchar'); +fwrite(fid,hist.origin, 'int16'); +fwrite(fid,hist.generated, 'uchar'); +fwrite(fid,hist.scannum, 'uchar'); +fwrite(fid,hist.patient_id, 'uchar'); +fwrite(fid,hist.exp_date, 'uchar'); +fwrite(fid,hist.exp_time, 'uchar'); +fwrite(fid,hist.hist_un0, 'uchar'); +fwrite(fid,hist.views, 'int32'); +fwrite(fid,hist.vols_added, 'int32'); +fwrite(fid,hist.start_field,'int32'); +fwrite(fid,hist.field_skip, 'int32'); +fwrite(fid,hist.omax, 'int32'); +fwrite(fid,hist.omin, 'int32'); +fwrite(fid,hist.smax, 'int32'); +if fwrite(fid,hist.smin, 'int32')~=1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hdr = my_spm2_create_defaults +hk.sizeof_hdr = 348; +hk.data_type = ['dsr ' 0]; +hk.db_name = char(zeros(1,18)); +hk.extents = 0; +hk.session_error= 0; +hk.regular = 'r'; +hk.hkey_un0 = 0; + +dime.dim = [4 0 0 0 1 0 0 0]; +dime.vox_units = ['mm ' 0]; +dime.cal_units = char(zeros(1,8)); +dime.unused1 = 0; +dime.datatype = -1; +dime.bitpix = 0; +dime.dim_un0 = 0; +dime.pixdim = [0 1 1 1 1 0 0 0]; +dime.vox_offset = 0; +dime.funused1 = 1; +dime.funused2 = 0; +dime.funused3 = 0; +dime.cal_max = 1; +dime.cal_min = 0; +dime.compressed = 0; +dime.verified = 0; +dime.glmax = 1; +dime.glmin = 0; + +hist.descrip = char(zeros(1,80)); +hist.descrip(1:length('SPM2 compatible')) = 'SPM2 compatible'; +hist.aux_file = char(zeros(1,24)); +hist.orient = char(0); +hist.origin = [0 0 0 0 0]; +hist.generated = char(zeros(1,10)); +hist.scannum = char(zeros(1,10)); +hist.patient_id = char(zeros(1,10)); +hist.exp_date = char(zeros(1,10)); +hist.exp_time = char(zeros(1,10)); +hist.hist_un0 = char(zeros(1,3)); +hist.generated(1:5) = 'today'; +hist.views = 0; +hist.vols_added = 0; +hist.start_field= 0; +hist.field_skip = 0; +hist.omax = 0; +hist.omin = 0; +hist.smax = 0; +hist.smin = 0; + +hdr.hk = hk; +hdr.dime = dime; +hdr.hist = hist; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THESE FUNCTIONS COME FROM THE SPM2 VERSION OF SPM_READ_HDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [hdr,otherendian] = my_spm2_spm_read_hdr(fname) +% Read (SPM customised) Analyze header +% FORMAT [hdr,otherendian] = spm_read_hdr(fname) +% fname - .hdr filename +% hdr - structure containing Analyze header +% otherendian - byte swapping necessary flag +%_______________________________________________________________________ +% @(#)spm_read_hdr.m 2.2 John Ashburner 03/07/17 + +fid = fopen(fname,'r','native'); +otherendian = 0; +if (fid > 0) + dime = my_spm2_read_dime(fid); + if dime.dim(1)<0 || dime.dim(1)>15 % Appears to be other-endian + % Re-open other-endian + fclose(fid); + if spm_platform('bigend'), fid = fopen(fname,'r','ieee-le'); + else fid = fopen(fname,'r','ieee-be'); end; + otherendian = 1; + dime = my_spm2_read_dime(fid); + end; + hk = my_spm2_read_hk(fid); + hist = my_spm2_read_hist(fid); + hdr.hk = hk; + hdr.dime = dime; + hdr.hist = hist; + fclose(fid); +else + hdr = []; + otherendian = NaN; + %error(['Problem opening header file (' fopen(fid) ').']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hk = my_spm2_read_hk(fid) +% read (struct) header_key +%----------------------------------------------------------------------- +fseek(fid,0,'bof'); +hk.sizeof_hdr = fread(fid,1,'int32'); +hk.data_type = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hk.db_name = my_spm2_mysetstr(fread(fid,18,'uchar'))'; +hk.extents = fread(fid,1,'int32'); +hk.session_error = fread(fid,1,'int16'); +hk.regular = my_spm2_mysetstr(fread(fid,1,'uchar'))'; +hk.hkey_un0 = my_spm2_mysetstr(fread(fid,1,'uchar'))'; +if isempty(hk.hkey_un0) + error(['Problem reading "hk" of header file (' fopen(fid) ').']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function dime = my_spm2_read_dime(fid) +% read (struct) image_dimension +%----------------------------------------------------------------------- +fseek(fid,40,'bof'); +dime.dim = fread(fid,8,'int16')'; +dime.vox_units = my_spm2_mysetstr(fread(fid,4,'uchar'))'; +dime.cal_units = my_spm2_mysetstr(fread(fid,8,'uchar'))'; +dime.unused1 = fread(fid,1,'int16'); +dime.datatype = fread(fid,1,'int16'); +dime.bitpix = fread(fid,1,'int16'); +dime.dim_un0 = fread(fid,1,'int16'); +dime.pixdim = fread(fid,8,'float')'; +dime.vox_offset = fread(fid,1,'float'); +dime.funused1 = fread(fid,1,'float'); +dime.funused2 = fread(fid,1,'float'); +dime.funused3 = fread(fid,1,'float'); +dime.cal_max = fread(fid,1,'float'); +dime.cal_min = fread(fid,1,'float'); +dime.compressed = fread(fid,1,'int32'); +dime.verified = fread(fid,1,'int32'); +dime.glmax = fread(fid,1,'int32'); +dime.glmin = fread(fid,1,'int32'); +if isempty(dime.glmin) + error(['Problem reading "dime" of header file (' fopen(fid) ').']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hist = my_spm2_read_hist(fid) +% read (struct) data_history +%----------------------------------------------------------------------- +fseek(fid,148,'bof'); +hist.descrip = my_spm2_mysetstr(fread(fid,80,'uchar'))'; +hist.aux_file = my_spm2_mysetstr(fread(fid,24,'uchar'))'; +hist.orient = fread(fid,1,'uchar'); +hist.origin = fread(fid,5,'int16')'; +hist.generated = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hist.scannum = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hist.patient_id = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hist.exp_date = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hist.exp_time = my_spm2_mysetstr(fread(fid,10,'uchar'))'; +hist.hist_un0 = my_spm2_mysetstr(fread(fid,3,'uchar'))'; +hist.views = fread(fid,1,'int32'); +hist.vols_added = fread(fid,1,'int32'); +hist.start_field= fread(fid,1,'int32'); +hist.field_skip = fread(fid,1,'int32'); +hist.omax = fread(fid,1,'int32'); +hist.omin = fread(fid,1,'int32'); +hist.smax = fread(fid,1,'int32'); +hist.smin = fread(fid,1,'int32'); +if isempty(hist.smin) + error(['Problem reading "hist" of header file (' fopen(fid) ').']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function out = my_spm2_mysetstr(in) +tmp = find(in == 0); +tmp = min([min(tmp) length(in)]); +out = char([in(1:tmp)' zeros(1,length(in)-(tmp))])'; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THESE FUNCTIONS COME FROM THE SPM2 VERSION OF SPM_WRITE_VOL +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function V = my_spm2_write_vol(V,Y,dtype) +% Write an image volume to disk, setting scales and offsets as appropriate +% FORMAT V = my_spm2_write_vol(V,Y) +% V (input) - a structure containing image volume information (see spm_vol) +% Y - a one, two or three dimensional matrix containing the image voxels +% V (output) - data structure after modification for writing. +%_______________________________________________________________________ +% @(#)spm_write_vol.m 2.9 John Ashburner 03/02/26 + +if ndims(Y)>3, error('Can only handle a maximum of 3 dimensions.'), end + +if ~isfield(V,'pinfo'), V.pinfo = [1,0,0]'; end + +dim = [size(Y) 1 1 1]; +if ~all(dim(1:3) == V.dim(1:3)) || (size(V.pinfo,2)~=1 && size(V.pinfo,2)~=dim(3)), + error('Incompatible dimensions.'); +end + + +% Set scalefactors and offsets +%----------------------------------------------------------------------- +dt = V.dim(4); if dt>256, dt = dt/256; end; +if any(dt == [128+2 128+4 128+8]), + % Convert to a form that Analyze will support + dt = dt - 128; +end; +s = find(dt == [2 4 8 128+2 128+4 128+8]); +dmnmx = [0 -2^15 -2^31 -2^7 0 0 ; 2^8-1 2^15-1 2^31-1 2^7-1 2^16 2^32]; +dmnmx = dmnmx(:,s); +V.pinfo(1,:) = 1; +V.pinfo(2,:) = 0; +mxs = zeros(dim(3),1)+NaN; +mns = zeros(dim(3),1)+NaN; +if ~isempty(s), + for p=1:dim(3), + tmp = double(Y(:,:,p)); + tmp = tmp(isfinite(tmp)); + if ~isempty(tmp), + mxs(p) = max(tmp); + mns(p) = min(tmp); + end; + end; + + if size(V.pinfo,2) ~= 1 + for p=1:dim(3), + mx = mxs(p); + mn = mns(p); + if ~isfinite(mx), mx = 0; end; + if ~isfinite(mn), mn = 0; end; + if mx~=mn, + V.pinfo(1,p) = (mx-mn)/(dmnmx(2)-dmnmx(1)); + V.pinfo(2,p) = ... + (dmnmx(2)*mn-dmnmx(1)*mx)/(dmnmx(2)-dmnmx(1)); + else + V.pinfo(1,p) = 0; + V.pinfo(2,p) = mx; + end; + end; + else + mx = max(mxs(isfinite(mxs))); + mn = min(mns(isfinite(mns))); + if isempty(mx), mx = 0; end; + if isempty(mn), mn = 0; end; + if mx~=mn + V.pinfo(1,1) = (mx-mn)/(dmnmx(2)-dmnmx(1)); + V.pinfo(2,1) = (dmnmx(2)*mn-dmnmx(1)*mx)/(dmnmx(2)-dmnmx(1)); + else + V.pinfo(1,1) = 0; + V.pinfo(2,1) = mx; + end; + end; +end; + +%-Create and write image +%----------------------------------------------------------------------- +V = my_spm2_create_vol(V,dtype); + +for p=1:V.dim(3), + V = my_spm2_write_plane(V,Y(:,:,p),p); +end; +V = my_spm2_close_vol(V); +%_______________________________________________________________________ +%_______________________________________________________________________ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THESE FUNCTIONS COME FROM THE SPM2 VERSION OF SPM_WRITE_PLANE +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function V = my_spm2_write_plane(V,A,p) +% Write a transverse plane of image data. +% FORMAT V = my_spm2_write_plane(V,A,p) +% V - data structure containing image information. +% - see spm_vol for a description. +% A - the two dimensional image to write. +% p - the plane number (beginning from 1). +% +% VO - (possibly) modified data structure containing image information. +% It is possible that future versions of spm_write_plane may +% modify scalefactors (for example). +% +%_______________________________________________________________________ +% @(#)spm_write_plane.m 2.19 John Ashburner 03/07/16 + +if any(V.dim(1:2) ~= size(A)), error('Incompatible image dimensions'); end; +if p>V.dim(3), error('Plane number too high'); end; + +% Write Analyze image by default +V = my_spm2_write_analyze_plane(V,A,p); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function V = my_spm2_write_analyze_plane(V,A,p) + +types = [ 2 4 8 16 64 130 132 136, 512 1024 2048 4096 16384 33280 33792 34816]; +maxval = [2^8-1 2^15-1 2^31-1 Inf Inf 2^7-1 2^16-1 2^32-1, 2^8-1 2^15-1 2^31-1 Inf Inf 2^8-1 2^16-1 2^32-1]; +minval = [ 0 -2^15 -2^31 -Inf -Inf -2^7 0 0, 0 -2^15 -2^31 -Inf -Inf -2^7 0 0]; +intt = [ 1 1 1 0 0 1 1 1, 1 1 1 0 0 1 1 1]; +prec = str2mat('uint8','int16','int32','float','double','int8','uint16','uint32','uint8','int16','int32','float','double','int8','uint16','uint32'); +swapped = [ 0 0 0 0 0 0 0 0, 1 1 1 1 1 1 1 1]; +bits = [ 8 16 32 32 64 8 16 32, 8 16 32 32 64 8 16 32]; + +dt = find(types==V.dim(4)); +if isempty(dt), error('Unknown datatype'); end; + +A = double(A); + +% Rescale to fit appropriate range +if intt(dt), + A(isnan(A)) = 0; + mxv = maxval(dt); + mnv = minval(dt); + A = round(A*(1/V.pinfo(1)) - V.pinfo(2)); + A(A > mxv) = mxv; + A(A < mnv) = mnv; +end; + +[pth,nam] = fileparts(V.fname); +fname = fullfile(pth,[nam, '.img']); +if ~isfield(V,'private') || ~isfield(V.private,'fid') || isempty(V.private.fid) + mach = 'native'; + if swapped(dt) + if spm_platform('bigend') + mach = 'ieee-le'; + else + mach = 'ieee-be'; + end; + end; + fid = fopen(fname,'r+',mach); + if fid == -1 + fid = fopen(fname,'w',mach); + if fid == -1 + error(['Error opening ' fname '. Check that you have write permission.']); + end; + end; +else + if isempty(fopen(V.private.fid)), + mach = 'native'; + if swapped(dt) + if spm_platform('bigend') + mach = 'ieee-le'; + else + mach = 'ieee-be'; + end; + end; + V.private.fid = fopen(fname,'r+',mach); + if V.private.fid == -1 + error(['Error opening ' fname '. Check that you have write permission.']); + end; + end; + fid = V.private.fid; +end; + +% Seek to the appropriate offset +datasize = bits(dt)/8; +off = (p-1)*datasize*prod(V.dim(1:2)) + V.pinfo(3,1); +fseek(fid,0,'bof'); % A bug in Matlab 6.5 means that a rewind is needed +if fseek(fid,off,'bof')==-1, + % Need this because fseek in Matlab does not seek past the EOF + fseek(fid,0,'bof'); % A bug in Matlab 6.5 means that a rewind is needed + fseek(fid,0,'eof'); + curr_off = ftell(fid); + blanks = zeros(off-curr_off,1); + if fwrite(fid,blanks,'uchar') ~= numel(blanks) + my_spm2_write_error_message(V.fname); + error(['Error writing ' V.fname '.']); + end; + fseek(fid,0,'bof'); % A bug in Matlab 6.5 means that a rewind is needed + if fseek(fid,off,'bof') == -1, + my_spm2_write_error_message(V.fname); + error(['Error writing ' V.fname '.']); + end; +end; + +if fwrite(fid,A,deblank(prec(dt,:))) ~= numel(A) + my_spm2_write_error_message(V.fname); + error(['Error writing ' V.fname '.']); +end; + +if ~isfield(V,'private') || ~isfield(V.private,'fid') || isempty(V.private.fid), fclose(fid); end; + +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function my_spm2_write_error_message(q) +str = {... + 'Error writing:',... + ' ',... + [' ',spm_str_manip(q,'k40d')],... + ' ',... + 'Check disk space / disk quota.'}; +spm('alert*',str,mfilename,sqrt(-1)); + +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% THIS FUNCTION COMES FROM THE SPM2 VERSION OF SPM_CLOSE_VOL +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function V = my_spm2_close_vol(V) +% Close image volume +% See: spm_create_vol and spm_write_plane. +%_______________________________________________________________________ +% @(#)spm_close_vol.m 2.4 John Ashburner 02/08/16 +for i=1:numel(V), + if isfield(V,'private') && isfield(V(i).private,'fid') && ~isempty(V(i).private.fid), + if ~isempty(fopen(V(i).private.fid)), + fclose(V(i).private.fid); + end; + V(i).private = rmfield(V(i).private,'fid'); + end; +end; \ No newline at end of file diff --git a/labnic/ps2pdf.m b/labnic/ps2pdf.m new file mode 100644 index 0000000..e64a8ca --- /dev/null +++ b/labnic/ps2pdf.m @@ -0,0 +1,385 @@ +function ps2pdf(varargin) +%PS2PDF Function to convert a PostScript file to PDF using Ghostscript +% +% Converts a postscript file into PDF. The resulting PDF file will contain +% one page for each page defined in the postscript files, so a multi-page +% postscript file, like those generated by using the '-append' option of +% MATLAB's print command, can be used to generate a multi-page PDF file. +% +% Ghostscript is a third-party application currently supplied with +% MATLAB. The caller may also specify a different version of Ghostscript +% to use. +% +% PS2PDF expects to be called with a set of parameter-value pairs. The +% order of these is unimportant, but required parameters MUST be +% specified +% +% In the list below, required parameters are marked with an asterisk * +% Parameter: Value: +% * psfile full or relative path to the postscript file to convert +% +% * pdffile full or relative path to the pdf file to create +% +% gscommand path to Ghostscript executable to use; this will try +% to default to the version of Ghostscript shipped with +% MATLAB, if any. If this value is specified you should +% also specify the gsfontpath and gslibpath values. +% +% gsfontpath full path to the Ghostscript font files +% If a gscommand is specified then this path should +% also be specified and reference the same Ghostscript +% version +% +% If gscommand is NOT specified and we can determine +% the version of Ghostscript, if any, shipped with +% MATLAB, then this value will be overridden to use the +% path that references MATLAB's version of Ghostscript +% +% gslibpath full path to the Ghostscript library (.ps) files. +% If a gscommand is specified then this path should +% also be specified and reference the same Ghostscript +% version +% +% If gscommand is NOT specified and we can determine +% the version of Ghostscript, if any, shipped with +% MATLAB, then this value will be overridden to use the +% path that references MATLAB's version of Ghostscript +% +% gspapersize paper size to use in the created .pdf file. If not +% specified or the specified value is not recognized +% it will use whatever default paper size is +% built into the version of Ghostscript being run +% +% NOTE: no scaling of the input occurs - it's simply +% placed on a page with the specified paper size. +% +% Valid values for gspapersize are: +% 'letter', 'ledger', 'legal', '11x17', +% 'archA', 'archB', 'archC', 'archD', 'archE', +% 'a0', 'a1', 'a2', 'a3','a4', 'a5', +% 'a6', 'a7', 'a8', 'a9', 'a10' +% +% deletepsfile 0 to keep the input ps file after creating pdf +% non-zero to delete the input ps file after creating pdf +% Default is 0: keep the input ps file (do NOT delete it) +% NOTE: if the pdf creation process fails, the input +% PS file will be kept regardless of this setting +% +% verbose 0 to suppress display of status/progress info; +% non-zero to allow display of status/progress info +% Default is 0 (no display) +% +% Example usage: +% use MATLAB's version of Ghostscript to generate an A4 pdf file +% ps2pdf('psfile', 'input.ps', 'pdffile', 'output.pdf', 'gspapersize', 'a4') +% +% use a local copy of Ghostcript to generate a file, and display some +% status/progress info while doing so. +% ps2pdf('psfile', '../reports/input.ps', 'pdffile', 'c:\temp\output3.pdf', ... +% 'gspapersize', 'a4', 'verbose', 1, ...) +% 'gscommand', 'C:\Program Files\GhostScript\bin\gswin32c.exe', ... +% 'gsfontpath', 'C:\Program Files\GhostScript\fonts', ... +% 'gslibpath', 'C:\Program Files\GhostScript\lib') +% +% use MATLAB's version of Ghostscript to generate a pdf file and delete +% the input.ps file when done +% ps2pdf('psfile', 'input.ps', 'pdffile', 'output.pdf', 'gspapersize', 'a4', 'deletepsfile', 1) + +% Update log: +% Aug 15, 2008: fixed bug where embedded space in location of +% MATLAB's version of Ghostscript caused ps2pdf to fail. +% Apr 16, 2008: added deletepsfile option + +% Copyright 2008 The MathWorks, Inc. + + if nargin < 1 + error('ps2pdf:parameters', 'No parameters specified. Type ''help ps2pdf'' for details on how to use this function.'); + end + + % parse input args + gsData = LocalParseArgs(varargin{:}); + + % setup the file that tells GS what we want it to do + gsData = LocalCreateResponseFile(gsData); + + gsDebug = 0; + if gsData.verbose + fprintf('ps2pdf: input settings are:\n'); + if isfield(gsData, 'paperSizes') + gsData = rmfield(gsData, 'paperSizes'); + end + gsData %#ok + fprintf('ps2pdf: response file for Ghostscript is:\n'); + type(gsData.responseFile); + gsDebug = 1; + end + + %to hold results/status from system call + s = 0; %#ok + r = ''; %#ok + + % run Ghostscript to convert the file + if gsData.useBuiltin + [s, r] = gsData.cmd(['@' gsData.responseFile], gsData.psFile, gsDebug); + else + [s, r] = system([gsData.cmd ' @' gsData.responseFile ' ' gsData.psFile]); + end + + if gsData.verbose + disp( ['Ghostscript STDOUT: ' num2str(s) ] ); + disp( ['Ghostscript STDERR: ' r ] ); + else + delete(gsData.responseFile) + end + + if s && ~isempty(r) + error('ps2pdf:ghostscript', ['Problem converting PostScript. System returned error: ' num2str(s) '.' r]) + elseif s + error('ps2pdf:ghostscript', ['Problem calling GhostScript. System returned error: ' num2str(s)]) + end + + %if after all this we still couldn't create the file, report the error + fid = fopen( gsData.pdfFile, 'r'); + if ( fid == -1 ) + error('ps2pdf:ghostscript', '%s', [ 'Ghostscript could not create ''' gsData.pfdFile '''.' ]) + else + fclose( fid ); + end + + % if we get here, we successfully created pdf file; delete ps file if + % requested to do so + if gsData.deletePSFile + delete(gsData.psFile); + end + +end + +%local function to parse arguments and fill in the gsData structure +% .psFile - postscript file to convert +% .pdfFile - pdf file to create +% .cmd - path/name of Ghostscript command to run or handle to gscript +% builtin +% .useBuiltin - 1 if using builtin gs command +% .fontPath - path to the Ghostscript fonts, if any +% .libPath - path to the Ghostscript libs (Ghostscript .ps files), if any) +% .paperSize - paper size to set for resulting .pdf file +% .deletePSFile - 0 to keep (not delete) the input ps file if pdf created ok +% .verbose - if non-zero, display some status/progress info to command window +function gsData = LocalParseArgs(varargin) + gsData.paperSizes = {'letter', 'ledger', 'legal', '11x17', 'archA', 'archB', ... + 'archC', 'archD', 'archE', 'a0', 'a1', 'a2', 'a3','a4', 'a5', ... + 'a6', 'a7', 'a8', 'a9', 'a10'}; + + %default values for some settings + gsData.verbose = 0; + gsData.useBuiltin = 0; + gsData.deletePSFile = 0; + + for i = 1 : 2 : length(varargin)-1 + param_arg = varargin{i}; + param_value = varargin{i+1}; + switch(lower(param_arg)) + % path to ps file to conver + case 'psfile' + if ~exist(param_value, 'file') + error('print:ghostscript', ... + 'Can not find postscript file <%s> to convert', ... + param_value) + end + gsData.psFile = param_value; + + % path to pdf file to create + case 'pdffile' + %verify we can create file at that location + pdf_fid = fopen(param_value,'w'); + if pdf_fid < 0 + error('ps2pdf:invalidPDFFIle', ... + 'Can not open <%s> for writing', ... + param_value); + end + fclose(pdf_fid); + %delete temp file we created + delete(param_value); + gsData.pdfFile = param_value; + + % full path to gs executable + case 'gscommand' + if ~exist(param_value, 'file') + error('ps2pdf:ghostscriptCommand', ... + 'Can not find Ghostscript executable (''gscommand'') <%s>',... + param_value) + end + if ispc && ~isempty(findstr(param_value, ' ')) + param_value = ['"' param_value '"']; %#ok + end + gsData.cmd = param_value; + + % full path to gs font dir + case 'gsfontpath' + if ~exist(param_value, 'dir') + error('ps2pdf:ghostscriptFontPath', ... + 'Can not find the directory <%s> for Ghostscript fonts (''gsfontpath'')', ... + param_value) + end + gsData.fontPath = param_value; + + % full path to gs lib dir + case 'gslibpath' + if ~exist(param_value, 'dir') + error('ps2pdf:ghostscriptLibPath', ... + 'Can not find the directory <%s> for Ghostscript library files (''gslibpath'')', ... + param_value) + end + gsData.libPath = param_value; + + % paper size + case 'gspapersize' + idx = strcmpi(param_value, gsData.paperSizes); + if ~any(idx) + warning('ps2pdf:papersize', ... + '''gspapersize'' value <%s> not found in the list of known sizes, ignoring it.', param_value); + else + gsData.paperSize = gsData.paperSizes{idx}; + end + + % deletePSFile + case 'deletepsfile' + if isnumeric(param_value) + gsData.deletePSFile = param_value; + else + warning('ps2pdf:deletepsfile', ... + '''deletepsfile'' value <%s> class <%s> should be numeric, defaulting to 0', ... + param_value, class(param_value)); + end + + % verbose + case 'verbose' + if isnumeric(param_value) + gsData.verbose = param_value; + else + warning('ps2pdf:verbose', ... + '''verbose'' value <%s> class <%s> should be numeric, defaulting to 0', ... + param_value, class(param_value)); + end + + otherwise + if isnumeric(param_value) + param_value = num2str(param_value); + end + warning('ps2pdf:unknown', ... + 'ignoring unknown parameter <%s> with value <%s>.', param_arg, param_value); + end + end + + if ~isfield(gsData, 'psFile') + error('ps2pdf:noInputFile', ... + 'No input (psfile) file specified'); + end + + if ~isfield(gsData, 'pdfFile') + error('ps2pdf:noOutputFile', ... + 'No output (pdffile) file specified'); + end + + if ~isfield(gsData, 'cmd') + + v = ver('MATLAB'); + if str2double(v.Version) < 7.4 + [gsCmd, ghostDir] = Local_GetOldGhostscript(); + gsData.cmd = gsCmd; + else + % version 7.4 or later + % the path to Ghostscript changed in 7a + ghostDir = fullfile( matlabroot, 'sys', 'gs8x' ); + if ~exist(ghostDir, 'dir') + error('ps2pdf:ghostscriptCommand', ... + 'Can not find Ghostscript installed with MATLAB in <%s>',... + ghostDir); + end + gsData.cmd = Local_GetGscriptFcnHandle; + if ~isempty(gsData.cmd) + gsData.useBuiltin = 1; % use builtin Ghostscript + end + end + + if ~isempty(gsData.cmd) + % if using MATLAB's version of GhostScript, use same set of fonts and library files + if isfield(gsData, 'fontPath') || isfield(gsData, 'libPath') + warning('ps2pdf:ghostscriptPathOverride', ... + 'Using MATLAB''s version of Ghostscript; overriding ''gsfontpath'' and ''gslibpath'' to use builtin MATLAB version'); + end + gsData.fontPath = fullfile( ghostDir, 'fonts', ''); + gsData.libPath = fullfile( ghostDir, 'ps_files', ''); + else + error('ps2pdf:noGhostscriptCommand', ... + 'Can not find Ghostscript program in MATLAB'); + end + else + % if gscommandpath was specified, + if ~isfield(gsData, 'fontPath') || ~isfield(gsData, 'libPath') + warning('ps2pdf:ghostscriptCommandSuggestion', ... + ['When specifying a Ghostscript executable (''gscommand'') you should also '... + 'specify both the ''gsfontpath'' and ''gslibpath'' locations']); + + end + end +end + +%local function to create the input file needed for Ghostscript +function gsData = LocalCreateResponseFile(gsData) + % open a response file to write out Ghostscript commands + rsp_file = [tempname '.rsp']; + rsp_fid = fopen (rsp_file, 'w'); + + if (rsp_fid < 0) + error('ps2pdf:responseFileCreate', 'Unable to create response file') + end + + fprintf(rsp_fid, '-dBATCH -dNOPAUSE\n'); + if ~gsData.verbose + fprintf(rsp_fid, '-q\n'); + end + if isfield(gsData, 'libPath') + fprintf(rsp_fid, '-I"%s"\n', gsData.libPath); + end + if isfield(gsData, 'fontPath') + fprintf(rsp_fid, '-I"%s"\n', gsData.fontPath); + end + if isfield(gsData, 'paperSize') + fprintf( rsp_fid, '-sPAPERSIZE=%s\n', gsData.paperSize ); + end + fprintf(rsp_fid, '-sOutputFile="%s"\n', gsData.pdfFile); + fprintf(rsp_fid, '-sDEVICE=%s\n', 'pdfwrite'); + fclose(rsp_fid); + gsData.responseFile = rsp_file; +end + +%local function to get a handle to MATLAB's Ghostscript implementation +%NOTE: this may change or be removed in future releases +function gs = Local_GetGscriptFcnHandle() + gs = ''; + p = which('-all', 'gscript'); + if ~isempty(p) + p = p{1}; + fpath = fileparts(p); + olddir = cd(fpath); + gs = @gscript; + cd(olddir); + end +end + +% local function to try and get location of Ghostscript in older MATLAB +function [gsCmd, ghostDir] = Local_GetOldGhostscript + ghostDir = fullfile( matlabroot, 'sys', 'ghostscript' ); + gsCmd = ''; + if ispc + if exist(fullfile(ghostDir,'bin','win32','gs.exe'), 'file') + gsCmd = fullfile(ghostDir,'bin','win32','gs.exe'); + end + else + if exist(fullfile(ghostDir,'bin',lower(computer),'gs'), 'file') + gsCmd = fullfile(ghostDir,'bin',lower(computer), 'gs'); + end + end + gsCmd = ['"' gsCmd '"']; +end \ No newline at end of file diff --git a/labnic/read_eprimetxt.m b/labnic/read_eprimetxt.m new file mode 100644 index 0000000..b7204ae --- /dev/null +++ b/labnic/read_eprimetxt.m @@ -0,0 +1,252 @@ +function [hnames,A,B,tvals,rowlevel] = read_eprimetxt(filename, varnames) +% read_eprimetxt - reads E-prime text files as edat +% V = read_eprimetxt('FILENAME') returns in V, the names of variables found in +% the E-Prime text file FILENAME (in alphabetical order) +% +% [V, A, B] = read_eprimetxt('FILENAME') also returns numeric data, stored in A, and text +% data, stored in B. +% +% See also: xlsread + +txt=textread(filename, '%s', 1, 'delimiter', '\n'); +if isequal(double(textread(filename, '%c', 3))', [65535 65534 42]) + % Null separated characters... + fid=fopen(filename,'rt'); + txt=char(fread(fid, getfield(dir(filename), 'bytes'), 'char'))'; + fclose(fid); + txt(txt==255)=[]; + txt(txt==254)=[]; + txt(txt==0)=[]; + txt=strread(txt, '%s', 'delimiter', '\n'); +elseif isequal(txt, {'*** Header Start ***'}) + txt=textread(filename, '%s', 'delimiter', '\n'); +else + hnames{1} = 'impossible'; + A = []; + B = []; + tvals = []; + rowlevel = []; + return + error('Wrong type of file, it should be an E-prime generated text file, starting with a header'); +end +% Header.nvars=strmatch('*** Header End ***', txt)-strmatch('*** Header Start ***', txt)-1; + + +%% Vars +v=txt; +v(strmatch('*** ', txt))=[]; +if datenum(version('-date')) > 733044 %732892 % 732687 % 732341 + [vnames, vvals]=strread(v,'%s%s',1,'delimiter', ': '); + % elseif str2num(version('-release'))>=14 + % %it still bugs with Matlab 7.0.4.365 (R14) Service Pack 2 !! + % for i=1:size(v,1) + % [vnames(i), vvals(i)]=strread(v{i},'%s%s',1,'delimiter', ': '); + % end +else + vnames=cell(length(v),1); + vvals=vnames; + for i=1:length(v) + [vnames{i},b]= strtok(v{i}, ': '); + vvals{i}=b(3:end); + end +end + +%% LevelNames +LevelNames=vvals(strmatch('LevelName', vnames)); +vvals(strmatch('LevelName', vnames))=[]; +vnames(strmatch('LevelName', vnames))=[]; + +% Identical variable names across levels should be specified using [] +ilevels=strmatch('Level', vnames, 'exact'); +levels=str2num(strvcat(vvals(ilevels))); +vlevels=zeros(length(vnames),1); +for i=1:length(ilevels) + vlevels(ilevels(i):end)=levels(i); +end +% vvals(strmatch('Level', vnames))=[]; +% vlevels(strmatch('Level', vnames))=[]; +% vnames(strmatch('Level', vnames))=[]; + + +% List of column headers +[hnames,i,j]=unique(vnames); +%j( strmatch('Level', hnames, 'exact'))=NaN; + + +for i=1:length(hnames) + if ~isequal(hnames{i},'Level') + l=unique(vlevels(j==i)); + l=nonzeros(l); + if length(l)>1 + %hnames(i) + for k=2:length(l) + hnames{end+1}=[ hnames{i} '[' LevelNames{l(k)} ']']; + vnames(intersect(find(vlevels==l(k)),strmatch(hnames{i},vnames,'exact')))=hnames(end); + end + hnames{i} = [ hnames{i} '[' LevelNames{l(1)} ']']; + vnames(intersect(find(vlevels==l(1)),strmatch(hnames{i},vnames,'exact')))=hnames(i); + end + end +end +hnames(strmatch('Level', hnames, 'exact'))=[]; +hnames=[hnames ; LevelNames(2:max(levels)) ]; +[i,i]=sort(lower(hnames)); +hnames=hnames(i)'; +if nargout <= 1 + %returns headers only + % k=strmatch('Level',hnames, 'exact'); + % hnames(k)=[]; + % k=strmatch('LevelName',hnames, 'exact'); + % hnames(k)=[]; + k=strmatch('VersionPersist',hnames, 'exact'); + hnames(k)=[]; + return +end + + +%% Converts text to numerical values +% To tease apart numerical/text values, we create a new array containing +% mixed data types +% try +% % With version > 7.0 +% xvals=cellfun(str2func('str2num'), vvals, 'UniformOutput', 0); +% +% %Where non numerical data were... +% tvals=cellfun('isempty', xvals); +% % We also need to check for a strange behavior of str2num +% tvals=tvals | cellfun('length',xvals) > 1; +% +% % we put them back in the mixed type array xvals +% xvals(tvals)=vvals(tvals); +% catch +% xvals=cell(length(vvals),1); +% tvals=logical(zeros(length(vvals),1)); +% for i=1:length(vvals) +% xvals{i}=str2num(vvals{i}); +% if isempty(xvals{i}) & ~isempty(vvals{i}) +% xvals{i}=vvals{i}; +% tvals(i)=1; +% end +% end +% end + +nrows=sum(diff(levels)==0)+sum(diff(levels)>0)+1; +nvars= length(hnames); +%table of values +tvals=cell(nrows,length(hnames)); + +rowlevel=zeros(nrows,1); +row=0; +for i=1:length(levels)-1 + if i==1 || levels(i)>=levels(i-1) + row=row(end)+1; + else + row=find(rowlevel>levels(i)); + end + rowlevel(row)=levels(i); + for j=ilevels(i)+1:ilevels(i+1)-1 + % Fills with values for the corresponding level + k=strmatch(vnames(j),hnames, 'exact'); + if strcmp(vvals{j},'i') + v = NaN; + else + v=str2double(vvals{j}); + end + if isnan(v) && ~isempty(vvals{j}) + v=vvals{j}; + end + tvals(row,k)={v}; + end + k=strmatch(LevelNames(levels(i)),hnames, 'exact'); + if row(1)>1 + tvals(row,k)={tvals{row(1)-1,k}+1}; + else + tvals(row,k)={1}; + end +end + +for j=ilevels(end)+1:length(vvals) + % Fills with values for the corresponding level + k=strmatch(vnames(j),hnames, 'exact'); + if strcmp(vvals{j},'i') + v = NaN; + else + v=str2double(vvals{j}); + end + if isnan(v) && ~isempty(vvals{j}) + v=vvals{j}; + end + tvals(:,k)={v}; +end + + +%% Converts to Number and Text arrays +B = cell(nrows,nvars); +B(:) = {''}; +vIsNaN = false(nrows,nvars); +% find non-numeric entries in data cell array +vIsText = cellfun('isclass',tvals,'char'); +% place text cells in text array +% then replace them with NaN +if any(vIsText(:)) + vIsText=any(vIsText); + B(:,vIsText) = deblank(tvals(:,vIsText)); + % Replace [] in char array... + B(cellfun('isempty',B))={''}; + tvals(:,vIsText)={NaN}; +end +% place NaN in empty numeric cells +vIsNaN = ... + cellfun('isempty',tvals)|... + cellfun('isclass',tvals,'char'); +if any(vIsNaN(:)) + tvals(vIsNaN)={NaN}; +end +A = cell2mat(tvals); +B=reshape(B,[nrows,nvars]); + +%% Ouputs requested variables +if nargin>1 + if ~iscell(varnames) + varnames={varnames}; + end + k=zeros(1,length(varnames)); + for i=1:length(varnames) + if ismember(varnames(i),hnames) + k(i)=strmatch(varnames{i},hnames,'exact'); + else + %k(i)=strmatch(varnames{i},hnames,'exact'); + end + end + if any(k==0) + error('Variable name not found'); + end + hnames=hnames(k); + A=A(:,k); + B=B(:,k); + return +end + +% add: Procedure[Block] Procedure[Trial] Running[Block] Running[Trial] +k=strmatch('Level',hnames, 'exact'); +A(:,k)=[];B(:,k)=[];hnames(k)=[]; +k=strmatch('LevelName',hnames, 'exact'); +A(:,k)=[];B(:,k)=[];hnames(k)=[]; +k=strmatch('VersionPersist',hnames, 'exact'); +A(:,k)=[];B(:,k)=[];hnames(k)=[]; +k=strmatch('Procedure',hnames, 'exact'); +A(:,k)=[];B(:,k)=[];hnames(k)=[]; +k=strmatch('Running',hnames, 'exact'); +A(:,k)=[];B(:,k)=[];hnames(k)=[]; + +return + +function [tvals,rowlevel,varlevel]=filllevels(tvals,rowlevel,varlevel,curlevel,row,nlevels) +% fill lower levels in the hierarchy +for j=nlevels:-1:curlevel + k=(varlevel0; + tvals(row-[0:rowlevel(j)-1],k)=repmat(tvals(row,k),rowlevel(j),1); +end +varlevel(varlevel>=curlevel)=0; +rowlevel(curlevel:end)=0; +return \ No newline at end of file diff --git a/labnic/references_batches_spm8 [WikiNIC].html b/labnic/references_batches_spm8 [WikiNIC].html new file mode 100644 index 0000000..d9d4d2b --- /dev/null +++ b/labnic/references_batches_spm8 [WikiNIC].html @@ -0,0 +1,6432 @@ + + + + + references:batches_spm8 [WikiNIC] + + + + + + + + + + + + + + + + + + + + + + + + + + +

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    + [[references:batches_spm8]] +
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    + You are here: start » references » batches_spm8
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    −Table of Contents
    +
    + + +
    +
    + + +

    Import your data

    +
    +

    use this function for converting your data and save it as swr_import_DICOM.m

    +

    +It will open a first window to catch the folder where the original data +are and a second window to ask you where to save your converted data. +

    + +
    +
    +

    Convert NIFTI to old Analyze format

    +
    +

    As backward +compatibility is not insured in SPM for image formats, this fonction is +sometimes useful ; use this function for converting your NIFTI files +(.nii or nifti .img/.hdr) to ANALYSE format (.img/.hdr) and save it as +nifti2img.m ; Requires at least SPM5 to run

    +
    +
    +

    Preprocessing

    +
    +

    SPM5: save this function as spm5_preprocessing_labnic.m

    +

    +updated by YC on the 10th of October 2011 +

    +

    SPM8: Save this function as spm8_preprocessing_labnic.m to preprocess with spm8

    +

    + +You must have a structure like …main_dir\populations\subjects\scans\sessions\f*img +

    + +

    +If you have a structural image for the subject, it should be in a structure like: …main_dir\populations\subjects\scans\struct\s*img
    + +If you have no structural image, do not create the dir 'struct' and the coregistration will not be processed. +

    + +

    +It will create \af \waf and \swaf folders with the processed images.
    + +

    + +

    +Processing include: +

    +
      +
    1. realignment (with option to realign on mean or first scan of session)
      +
      +
      2. +
    2. coregistration (if struct image exists)
      +
      +
      3. +
    3. slice timing (suggested for TR > 2.5s)
      +
      +
      4. +
    4. normalization (on EPI template with +voxel size of [3 3 3]mm for functional images and on T1 template with +voxel size of [1 1 1]mm for struct image)
      +
      +
      5. +
    5. smoothing (Gaussian filter of 8 mm).
      +
      +
      6. +
    + +

    + +These steps can be now specified line 28 and options for each line 29 to 33. +

    + +

    +You must specify some details of your study in lines 23 to 33 of the +function. If you have specific names or specific order for sessions, +specify it at the end of this function.
    + +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +
    +
    +

    First Level Analysis

    +
    + +

    + +updated by YC on 17th Dec 2009 +

    + +

    +Works with spm8 without adaptation +

    +

    SPM5 or SPM8 : save this function as Labnic_1st_analysis.m

    +

    +updated by YC on 24th Jan 2012 +

    + +

    +if you want to be able to launch the batch in spm8 use this one: + +

    +

    SPM8 : save this function as Labnic_1stlevel_spm8.m

    +

    +You must specify some details of your study in lines 19 to 24 of the +function. If you have specific names or specific order for sessions, +specify it at the end of this function. +

    + +

    +Between lines 58-68, you have to specify how to load onsets and +conditions of your experiments. Several choices are possible (reading +eprime files, creating ons.mat and loading them, etc…). For help on +this topic, please contact anyone who has already the script running, +Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich +(virginie.sterpenich@unige.ch). +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +

    +for connectivity fans… PPIs +

    +

    SPM8 : save this function as Labnic_PPI_spm8.m

    +

    +You have to specify the first lines of the script, then it should work +correctly… As contrasts are consistent across studies (PPI, psycho, +physio factors), they are set and computed by default. If you have +comments, suggestions, bugs reports, feel free to contact Yann Cojan (yann.cojan@unige.ch) +

    + +
    +
    +

    First Level Contrasts

    +
    + +

    + +Updated by YC on July 17th 2009 +

    +

    SPM5 or SPM8 : save this function as Labnic_1st_contrast_spm5.m

    +

    + +You must specify some details of your study in lines 17-18 of the function. +

    + +

    +You have to specify your contrast from line 68 to as many contrasts you +want. For help on this topic, please contact anyone who has already the +script running, Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich +(virginie.sterpenich@unige.ch). +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +
    +
    +

    Second Level Analysis

    +
    + +

    + +Updated by YC on Dec 17th 2009 +

    + +
    + +

    1 sample ttest

    +
    +

    SPM5 : save this function as Labnic_rfx_ones_spm5.m

    SPM8 : save this function as Labnic_rfx_ones_spm8.m

    +

    +You must specify some details of your study in lines 21-23 of the function. +

    + +

    +It's taking the first subject analysis and conditions and reproduce this + analysis at the group level. Be sure that every subjects have the +contrasts in the same order… For help on this topic, please contact +anyone who has already the script running, Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +
    + +

    2 sample ttest

    +
    +

    SPM5 : save this function as Labnic_rfx_twos_spm5.m

    +

    +You must specify some details of your study in lines 21-23 of the function. +

    + +

    +This function is taking the first subject analysis and conditions and +reproduce this analysis at the group level. Be sure that every subjects +have the contrasts in the same order… A 2 sample ttest is computed for +each contrast of interest made at the first level. +

    + +

    +For help please contact anyone who has already the script running, Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +
    + +

    Anovas

    +
    +

    SPM5 : save this function as Labnic_Anova_spm5.m

    +

    +Updated by SP March 7th 2011 +

    + +

    +Note that if you want to correct for potential violations of sphericity +(ie what you usually do when looking at the p-value in the +Greenhouse-Geiser line), you need to set the variance of the condition +factor 'condition' to unequal (==1). The following code asks you this +question using a popup window. +

    +

    SPM8: Save this function as Labnic_Anova_spm8.m

    +

    +This function is functioning by taking the contrasts (define in cons +line 10) for simple HRF modeling (like Face_emotional, Face_neutral) and + make the anova directly at the second level. Furthermore it is doing +some contrasts at line 146 that you should define. +

    + +

    +For help please contact anyone who has already the script running, Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    + +

    +If you notice some problems or need some help, please contact Yann Cojan (yann.cojan@unige.ch) or Virginie Sterpenich (virginie.sterpenich@unige.ch). +

    +

    SPM5 : or Labnic_Anova_2groups_spm5.m

    SPM8: or Labnic_Anova_2groups_spm8.m

    +

    +You must specify some details of your study in lines 7-10 of the +functions. +As contrasts as not as easy to enter than for more classical analysis, +main contrasts are set by default by feel free to contact Yann Cojan (yann.cojan@unige.ch) for problems or suggestions… +

    + +
    +
    +

    Note on sphericity correction in SPM 2nd level analyses

    +
    + +

    + +Updated by SP on June 22th 2011 +

    + +

    +Very often, when doing ANOVAs with SPM, people assume that the error +variance between experimental conditions is equal, ie it is spheric. +Sphericity is an extension of the homoscedasticity of variance for the +population being sampled. It is one of the prerequisites to perform an +ANOVA. Concretely, sphericity is an assumption about the structure of +the covariance matrix - between experimental conditions -, namely that +covariance values should be roughly equal. +

    + +

    +In SPSS, when sphericity is violated, you generally read the p values +from the GreenHouse Geiser or Huynh and Feldt correction lines. This +correction works by decreasing the degree of freedom of your analysis +and p values are adjusted as a function of how much the variance differs + between conditions. +

    + +

    +In SPM, sphericity correction is achieved by answering YES to the +question 'unequal variance between conditions' (or setting this +parameter value to 1). +

    + +

    +Be aware that by default, this parameter is set to 0 in many labnic +scripts, meaning that you don't correct for sphericity violation, if +any. Be also aware that in a lot of example you find on the web, many do + not correct for sphericity. +

    + +

    +So you wonder, “well, how do I notice whether or not my dataset is spheric †? +

    + +

    +You can check this by looking at your ANOVA GLM matrix, once estimated.
    + +- If your dataset is spheric, you should see an nice-looking eye matrix, ie a white diagonal on a greyish background.
    + +- If your dataset is not spheric, the matrix will look 'messy' and the diagonal will be hardly distinguishable. +

    + +

    +Once estimated, SPM displays the whitened (ie scaled) design matrix. +This scaling will be adjusted if sphericity correction is required and +enabled in your script by setting unequal variance of your condition +factor to 1. Since sphericity correction rescales your design matrix, it + will also change and improve the design orthogonality. +

    + +

    +You may also wonder, “what in my experimental design, renders my dataset non spheric ?â€. +

    + +

    +Well if you have, in the same model, conditions that have been estimated + using different numbers of trials (n versus 2n for instance), you will +probably end up with a problem of sphericity. Concretely, you can be +faced with such a problem in designs where you analyse errors or when +using a condition with rare events (e.g. oddballs). +

    + +
    +
    +

    Plotting spheres instead of voxels

    +
    + +

    + +Updated by SP on Sep 28th 2010 +

    + +

    +This snippet adds a button to SPM GUI + in the plot function that will make SPM plot the beta for one / several + voxels contained into a sphere. +The step added to the plot function concerns the specification of the +sphere radius. Choose 0 and you will plot the beta for 1 voxel, as +usual. Choose N and you will plot the mean beta for all voxels located +into a sphere of N mm radious. +It has been tested for SPM8 only and might require adaptations for +earlier versions of SPM. +1. You need to edit spm_graph.m +3. Replace the following code (around line 219) +

    +

    Code to remove / comment

    +
        beta  = spm_get_data(SPM.Vbeta, XYZ);
+    ResMS = spm_get_data(SPM.VResMS,XYZ);
+    Bcov  = ResMS*SPM.xX.Bcov;
    +
    +

    +and add the following lines +

    +

    Code to add

    +
        % BEGINNING OF MODIFICATION : plots the mean/SE of a voxel / a bunch of voxels contained into a sphere of Nmm radius
+    % This code replaces the following SPM initial code
+    %     beta  = spm_get_data(SPM.Vbeta, XYZ);
+    %     ResMS = spm_get_data(SPM.VResMS,XYZ);
+    %     Bcov  = ResMS*SPM.xX.Bcov;
+ 
+    rad = spm_input(['Plot voxel (0) or sphere (radius mm)'],'+0','r',0,1);
+    d     = [xSPM.XYZ(1,:) - XYZ(1); xSPM.XYZ(2,:) - XYZ(2); xSPM.XYZ(3,:) - XYZ(3)];  % Center the contrast on the voxel / sphere coordinates
+    Q     = find(sum(d.^2) <= rad^2);                                                  % Find surrounding voxels if rad > 0
+    XYZ = xSPM.XYZ(:,Q);                                                               % Get their coords
+    beta  = spm_get_data(SPM.Vbeta, XYZ);                                              % Get their beta
+    ResMS = spm_get_data(SPM.VResMS,XYZ);                                              % Get their VResMS values
+ 
+    if size(beta, 2)>1                                                                 % If more than 1 voxel, then average the stuff before calculating Bcov, SE ..
+        beta = mean(beta')';
+        ResMS = mean(ResMS);
+    end
+    Bcov  = ResMS*SPM.xX.Bcov;
+ 
+    % END OF MODIFICATION
    +
    +

    +then when opening spm, you will have a new fuschia button on the left bottom panel of spm.
    + +

    + +
    +
    +

    Beta Extraction

    +
    + +

    +Updated by YC +

    + +
    + +

    Beta Extraction for SPM

    +
    + +

    + +Before using the following function, you may change one little thing in spm_results_ui.m to activate a new button in the spm GUI.
    + +

    + +

    +1. search for the %-Not currently used sentence (around line 570) and replace the old paragraph by this: + +

    +

    this little part

    +

    + +then when opening spm, you will have a new fuschia button on the left bottom panel of spm.
    + +

    + +

    +2. save the following function as +

    +

    extract_clubetas.m

    +
    + +

    Beta Extraction for xjview

    +
    +

    First add this little part (around line 353) in xjview.m

    +

    + between 'callback', @CallBack_commonRegionPush); and handles.displayPush +

    +

    Then add the following part at the end of xjview.m just before the last return

    +
    function CallBack_extract_clubetas(hObject, eventdata, readdata)
+if nargin<3
+    readdata=1;
+end
+ 
+ handles = guidata(hObject);
+[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1});
+spmfile=fullfile(img.p,'SPM.mat');
+ 
+if exist(spmfile(3:end), 'file')
+    warning('Possible disk swapping in xjview.m');
+    spmfile=spmfile(3:end);
+end
+if ~exist(spmfile)
+    if findstr('SPM2',spm('ver'))
+        spmfile = spm_get([0 1],'SPM.mat','locate the RFX SPM.mat');
+    elseif findstr('SPM5',spm('ver'))
+        spmfile = spm_select([0:1],'SPM.mat','locate the RFX SPM.mat');
+    end
+end
+if ~exist(spmfile)
+    return
+end
+xSPM=load(spmfile, 'SPM');
+[glmpath, glmpath]=fileparts(fileparts(fileparts(xSPM.SPM.swd)));
+clu = handles.currentDisplayMNI{1};
+center = handles.currentxyz;
+mni = cell2mat(handles.currentDisplayMNI');
+cor = mni2cor(mni, handles.M{1});
+[xyzmm,i] = spm_XYZreg('NearestXYZ',center,mni');
+A = spm_clusters(cor');
+j = find(A == A(i));
+xyz = mni(j,:);
+sub2pr=[1:xSPM.SPM.nscan];
+clear Data
+pathlist = xSPM.SPM.xY.P;
+ 
+allbetas= [];
+Allbetas = [];
+allxyz = [];
+ 
+%--- to write
+XYZ  = xSPM.SPM.xVol.XYZ;
+XYZmm = xSPM.SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))];
+bob = spm_input('nature of extraction','+1','b','VOI|cluster',[0,1]);
+ 
+if ~bob
+    radius=inputdlg('Radius of the sphere?');
+    if isempty(radius)
+        return
+    end
+    radius=str2num(radius{1});
+    [d] = spm_XYZreg('Edist',center,XYZmm);
+    i=find(d<=radius);
+    clus=XYZmm(:,i);
+    xyz = clus';
+end
+ 
+cond_list = [];
+for sub = 1:length(sub2pr)
+    mydir = fileparts(pathlist{sub});
+    %% initiation of matrix Allbetas and Tmpallbetas with the max
+    %% number of conditions
+    sSPM = load([mydir filesep 'SPM.mat']);
+    nses = length(sSPM.SPM.Sess);%num of session
+    convec = zeros(1,length(sSPM.SPM.Vbeta));
+    for ses = 1:nses
+        for j = 1:length(sSPM.SPM.Sess(ses).Fc)
+            index = sSPM.SPM.Sess(ses).col(sSPM.SPM.Sess(ses).Fc(1,j).i);
+            convec(ses,index) = 1;
+        end
+    end
+    real = sSPM.SPM.xX.name(any(convec));
+    for j = 1:length(real)
+        b = strfind(real{j},'*bf');
+        list_cond{j} = real{j}(7:b-1);
+    end
+    cond_list = [cond_list unique(list_cond)];
+end
+thelist = unique(cond_list);
+Allbetas = NaN(length(sub2pr),length(thelist));
+ 
+h = waitbar(0,'Please Wait...');
+for sub = 1:length(sub2pr)
+    mydir = fileparts(pathlist{sub});
+    sSPM = load([mydir filesep 'SPM.mat']);
+    for i = 1:length(sSPM.SPM.Vbeta)
+        sSPM.SPM.Vbeta(i).fname = [mydir filesep sSPM.SPM.Vbeta(i).fname];
+    end
+    tmpallbetas= [];
+    tmpallxyz = [];
+    Tmpallbetas= [];
+    list_cond = [];
+    for cluvox = 1:size(xyz,1)
+        [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm);
+        govox=1;
+        if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=1.7321 %one voxel in each dimZ
+            govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',...
+                num2str(xyz(cluvox,:)),...
+                'Continue anyway?'},...
+                1,'bd',{'OK','NO'},[1,0]);
+        end
+        vXYZ     = XYZ(:,i)  ;         % coordinates in voxels
+ 
+        %-Get parameter and hyperparameter estimates
+        beta= spm_get_data(sSPM.SPM.Vbeta, vXYZ);
+ 
+        convec = zeros(1,length(sSPM.SPM.Vbeta));
+        for ses = 1:nses
+            for j = 1:length(sSPM.SPM.Sess(ses).Fc)
+                index = sSPM.SPM.Sess(ses).col(sSPM.SPM.Sess(ses).Fc(1,j).i);
+                convec(ses,index) = 1;
+            end
+ 
+        end
+        real = sSPM.SPM.xX.name(any(convec));
+        for j = 1:length(real)
+            b = strfind(real{j},'*bf');
+            list_cond{j} = real{j}(7:b-1);
+        end
+        tmpallbetas  = [tmpallbetas; beta(any(convec))'];
+    end
+ 
+    for c = 1:length(thelist)
+        C = strcmp(thelist{c},list_cond);
+        Tmpallbetas = [Tmpallbetas mean(mean(tmpallbetas(:,C)))];
+    end
+ 
+    Allbetas(sub,:) = Tmpallbetas;
+    waitbar(sub/length(sub2pr),h)
+end
+close(h)
+ 
+ctitle = [num2str(nxyz') '  nvox = ' num2str(size(xyz,1))];
+tmpaxe = thelist(1:length(thelist));
+ 
+npop = size(xSPM.SPM.xX.X,2);
+for pop = 1:npop
+    Data{pop}(:,:) = reshape(Allbetas(logical(repmat(xSPM.SPM.xX.X(:,pop),1,size(Allbetas,2)))),sum(xSPM.SPM.xX.X(:,pop)),size(Allbetas,2));
+end
+[Maj,ST,SE] = yann_bar(Data);
+switch spm_input('errorbar?',2,'b','yes|no');
+    case 'yes'
+        figure
+        h  = bar(Maj');
+        for  i = 1:size(Maj,1)
+            if i == 1 & npop > 1
+                N = -0.08;
+            elseif i == 1
+                N = 0;
+            else
+                N = 0.08;
+            end
+            for j = 1:size(Maj,2)
+                coef = j+npop*N;
+                line([coef coef],([SE(i,j) 0 - SE(i,j)] + Maj(i,j)),...
+                    'LineWidth',1.5,'Color','k')
+                line ([coef-0.05 coef+0.05],([SE(i,j)+Maj(i,j) SE(i,j)+Maj(i,j)]),...
+                    'LineWidth',1.5,'Color','k')
+                line ([coef-0.05 coef+0.05],([-SE(i,j)+Maj(i,j) -SE(i,j)+Maj(i,j)]),...
+                    'LineWidth',1.5,'Color','k')
+            end
+        end
+    case 'no'
+        figure
+        h  = bar(Maj');
+        set(h,'FaceColor',[1 1 1]*.8)
+end
+set(gca, 'XTickLabel',tmpaxe, 'XTick' , [1:length(tmpaxe)],'FontSize',6);
+title(ctitle,'FontSize',16)
+ 
+function [Maj,ST,SE] = yann_bar(Data)
+% function [Maj,ST,SE] = yann_bar(Data)
+% calculate Mean, stdev and std error for Data
+% adapted by Yann Cojan (yann.cojan@unige.ch)
+ 
+npop = length(Data)
+ 
+switch spm_input('Reset lowest value to:?',1,'b','zero|mean|unchanged');
+    case 'zero'
+        for pop = 1:npop
+            if isempty(find(mean(Data{pop})<0))
+                Maj(pop,:) = mean(Data{pop},1)- min(mean(Data{pop},1));
+            else
+                Maj(pop,:) = mean(Data{pop},1) + abs(min(mean(Data{pop},1)));
+            end
+        end
+    case 'mean'
+        for pop = 1:npop
+            Maj(pop,:) = mean(Data{pop},1) - mean(mean(Data{pop},1));
+        end
+    case 'unchanged'
+        for pop = 1:npop
+            if any(any(isnan(Data{pop})))
+                count = 1;
+                for hu = 1:size(Data{pop},2)
+                    Maj(pop,hu) = mean(Data{pop}(~isnan(Data{pop}(:,hu)),hu));
+                end
+            else
+                Maj(pop,:) = mean(Data{pop},1);
+            end
+        end
+end
+for pop = 1:npop
+    if size(Data{pop},1)>1
+        if any(any(isnan(Data{pop})))
+            for hu = 1:size(Data{pop},2)
+                SE(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu))/sqrt(size(Data{pop}(~isnan(Data{pop}(:,hu))),1));
+                ST(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu));
+            end
+        else
+            SE(pop,:) = std(Data{pop})/sqrt(size(Data{pop},1));
+            ST(pop,:) = std(Data{pop});
+        end
+    else
+        if any(any(isnan(Data{pop})))
+            for hu = 1:size(Data{pop},2)
+                 SE(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu))/sqrt(size(Data{pop}(~isnan(Data{pop}(:,hu))),1));
+                ST(pop,hu) = std(Data{pop}(~isnan(Data{pop}(:,hu)),hu));
+            end
+        else
+            SE(pop,:) = zeros(1,size(Data{pop},2));
+            ST(pop,:) = zeros(1,size(Data{pop},2));
+        end
+    end
+end
    +
    +
    + +

    Remark concerning the standard error estimated by SPM

    +
    + +

    +Updated by SP June 22th 2011 +

    + +

    +You will notice that if you estimate the SEM of your extracted beta - +using std(beta)/sqrt(n) - you will find a very different estimate than +the one calculated by SPM. +This is because SPM derives the SE from the unexplained variance in the +model, ie the variance of the residual. This is calculated in spm_graph, + line ~328. +SE = sqrt(diag(SPM.xCon(Ic).c'*Bcov*SPM.xCon(Ic).c)); +% knowing that Bcov = ResMS*SPM.xX.Bcov +

    + +

    +In a traditional ANOVA language, this is equivalent to the root mean +square error (RMSE = sqrt(MSE) = SQRT(STD/SQRT(n))^2 = SQRT(SE)^2) aka +the standard error. +http://en.wikipedia.org/wiki/Root_mean_square_deviation +http://en.wikipedia.org/wiki/Mean_squared_error +

    + +

    +You can find some useful SPM posts here:
    + +https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind0708&L=SPM&P=R20753&1=SPM&9=A&I=-3&J=on&d=No+Match%3BMatch%3BMatches&z=4
    + +https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind0708&L=SPM&P=R27896&1=SPM&9=A&I=-3&J=on&d=No+Match%3BMatch%3BMatches&z=4 +

    + +
    +
    +

    Code Snippets

    +
    + +

    + +Need help with SPM? Want to program something? +

    + +

    +First, have a look at the SPM mailing-list (Search page). +

    + +

    +Second, hasn't John Ashburner already done it in his SPM99, SPM2, SPM5 Gems? +

    + +

    +Third, you may find it below… +

    + +
    + +

    Image Calculator

    +
    + +

    + +This is an example how to batch the Image Calculator function (spm_imcalc) for several subjects (SPM2): + +

    +

    How to Batch a Image Calculator function for several subjects

    +
    + +

    Moving Data or SPM.mat

    +
    + +

    + +In case your data have “moved hose†from one computer to another or within the computer, SPM.mat needs to know the new adress. +This is an example how to move house for SPM.mat: + +

    +

    Moving house script for SPM.mat

    + +
    function MG_moveSPM
+ 
+if spm('ver')=='SPM2'
+    mypath = spm_get(-1,pwd,'Select parent directory with all SPM.mat to move in its childs!');
+else
+    mypath = spm_select(1,'dir','Select parent directory with all SPM.mat to move in its childs!','',pwd)
+end
+mypathlist = genpath(mypath);
+mypathlist = strread(mypathlist,'%s','delimiter',';');
+ 
+for d=2:size(mypathlist)
+    cd(mypathlist{d})
+    if exist('SPM.mat')
+        load SPM;
+        xSPM=SPM;
+        xSPM.swd = pwd;
+        SPM=xSPM;
+        warning('SPM.mat is changed!!')
+        save SPM.mat SPM
+        disp(xSPM.swd)
+    end
+end
    +
    +
    + +

    Read Eprime text files

    +
    +

    save this function as read_eprimetxt.m

    +
    + +

    Several SPM Versions

    +
    + +

    + +In case you must use several SPM versions in the same MATLAB you'll have to change the path and clear the global variables. +For that purpose you can create a function that does all this (example +from SPM2 to SPM5). Copy and paste this into your matlab-batches +directory (name p_spm5) and edit the SPM path according to your PC: + + +

    +

    Change between SPM2 and SPM5

    +

    +Loading the data contained in a MR volume in SPM (I always forget that) + +

    +
    IMAGE=spm_read_vols(spm_vol(spm_select('List',your_file_directory,'your_filename.img'))
    + +
    + +

    Matlab figure in PDF

    +
    +

    Save your Matlab figure as a PDF in exactly the present appearance and size (needs GHOSTSCRIPT installed)

    +

    +Here a handy function to convert PS files to PDF (found here). + +You can use it for example to convert the PS files created by SPM during + preprocessing to verify realignment, normalisation, etc. Works straight + out of the box in Matlab. +

    +

    ps2pdf.m

    +
    +
    ps2pdf.m
    +
    function ps2pdf(varargin)
+%PS2PDF Function to convert a PostScript file to PDF using Ghostscript
+%
+%  Converts a postscript file into PDF. The resulting PDF file will contain
+%  one page for each page defined in the postscript files, so a multi-page
+%  postscript file, like those generated by using the '-append' option of 
+%  MATLAB's print command, can be used to generate a multi-page PDF file. 
+%
+%   Ghostscript is a third-party application currently supplied with 
+%   MATLAB. The caller may also specify a different version of Ghostscript
+%   to use.
+%
+%   PS2PDF expects to be called with a set of parameter-value pairs. The
+%   order of these is unimportant, but required parameters MUST be
+%   specified
+%
+%   In the list below, required parameters are marked with an asterisk *
+%   Parameter:        Value:  
+%   *  psfile         full or relative path to the postscript file to convert
+%
+%   *  pdffile        full or relative path to the pdf file to create
+%
+%      gscommand      path to Ghostscript executable to use; this will try
+%                     to default to the version of Ghostscript shipped with 
+%                     MATLAB, if any. If this value is specified you should 
+%                     also specify the gsfontpath and gslibpath values.
+%
+%      gsfontpath     full path to the Ghostscript font files
+%                     If a gscommand is specified then this path should
+%                     also be specified and reference the same Ghostscript
+%                     version
+%
+%                     If gscommand is NOT specified and we can determine
+%                     the version of Ghostscript, if any, shipped with
+%                     MATLAB, then this value will be overridden to use the
+%                     path that references MATLAB's version of Ghostscript
+%
+%      gslibpath      full path to the Ghostscript library (.ps) files. 
+%                     If a gscommand is specified then this path should
+%                     also be specified and reference the same Ghostscript
+%                     version
+%
+%                     If gscommand is NOT specified and we can determine
+%                     the version of Ghostscript, if any, shipped with
+%                     MATLAB, then this value will be overridden to use the
+%                     path that references MATLAB's version of Ghostscript
+%
+%      gspapersize    paper size to use in the created .pdf file. If not 
+%                     specified or the specified value is not recognized 
+%                     it will use whatever default paper size is 
+%                     built into the version of Ghostscript being run
+%
+%                         NOTE: no scaling of the input occurs - it's simply
+%                         placed on a page with the specified paper size. 
+%
+%                         Valid values for gspapersize are: 
+%                              'letter', 'ledger', 'legal', '11x17', 
+%                              'archA', 'archB', 'archC', 'archD', 'archE', 
+%                              'a0', 'a1', 'a2', 'a3','a4', 'a5',
+%                              'a6', 'a7', 'a8', 'a9', 'a10'
+%                         
+%      deletepsfile   0 to keep the input ps file after creating pdf
+%                     non-zero to delete the input ps file after creating pdf
+%                     Default is 0: keep the input ps file (do NOT delete it)
+%                        NOTE: if the pdf creation process fails, the input
+%                        PS file will be kept regardless of this setting
+%
+%      verbose        0 to suppress display of status/progress info; 
+%                     non-zero to allow display of status/progress info
+%                     Default is 0 (no display)
+%
+% Example usage: 
+%    use MATLAB's version of Ghostscript to generate an A4 pdf file
+%      ps2pdf('psfile', 'input.ps', 'pdffile', 'output.pdf', 'gspapersize', 'a4')
+%
+%    use a local copy of Ghostcript to generate a file, and display some 
+%    status/progress info while doing so.
+%      ps2pdf('psfile', '../reports/input.ps', 'pdffile', 'c:\temp\output3.pdf', ...
+%            'gspapersize', 'a4', 'verbose', 1, ...)
+%            'gscommand', 'C:\Program Files\GhostScript\bin\gswin32c.exe', ...
+%            'gsfontpath', 'C:\Program Files\GhostScript\fonts', ...
+%            'gslibpath', 'C:\Program Files\GhostScript\lib')
+%
+%    use MATLAB's version of Ghostscript to generate a pdf file and delete
+%    the input.ps file when done 
+%      ps2pdf('psfile', 'input.ps', 'pdffile', 'output.pdf', 'gspapersize', 'a4', 'deletepsfile', 1)
+ 
+%   Update log: 
+%      Aug 15, 2008: fixed bug where embedded space in location of 
+%                    MATLAB's version of Ghostscript caused ps2pdf to fail.
+%      Apr 16, 2008: added deletepsfile option
+ 
+%   Copyright 2008 The MathWorks, Inc.
+ 
+   if nargin < 1 
+      error('ps2pdf:parameters', 'No parameters specified. Type ''help ps2pdf'' for details on how to use this function.');
+   end
+ 
+   % parse input args
+   gsData = LocalParseArgs(varargin{:});
+ 
+   % setup the file that tells GS what we want it to do
+   gsData = LocalCreateResponseFile(gsData); 
+ 
+   gsDebug = 0;
+   if gsData.verbose 
+      fprintf('ps2pdf: input settings are:\n');
+      if isfield(gsData, 'paperSizes')
+          gsData = rmfield(gsData, 'paperSizes');
+      end
+      gsData  %#ok<NOPRT>
+      fprintf('ps2pdf: response file for Ghostscript is:\n');
+      type(gsData.responseFile);
+      gsDebug = 1;
+   end
+ 
+   %to hold results/status from system call
+   s = 0; %#ok<NASGU>
+   r = ''; %#ok<NASGU>
+ 
+   % run Ghostscript to convert the file
+   if gsData.useBuiltin 
+      [s, r] = gsData.cmd(['@' gsData.responseFile], gsData.psFile, gsDebug);
+   else 
+      [s, r] = system([gsData.cmd ' @' gsData.responseFile ' ' gsData.psFile]);
+   end
+ 
+   if gsData.verbose
+      disp( ['Ghostscript STDOUT: ' num2str(s) ] );
+      disp( ['Ghostscript STDERR: ' r ] );
+   else
+      delete(gsData.responseFile)
+   end
+ 
+   if s && ~isempty(r)
+      error('ps2pdf:ghostscript',  ['Problem converting PostScript. System returned error: ' num2str(s) '.' r]) 
+   elseif s
+      error('ps2pdf:ghostscript',  ['Problem calling GhostScript. System returned error: ' num2str(s)]) 
+   end
+ 
+   %if after all this we still couldn't create the file, report the error
+   fid = fopen( gsData.pdfFile, 'r');
+   if ( fid == -1 )
+      error('ps2pdf:ghostscript', '%s', [ 'Ghostscript could not create ''' gsData.pfdFile '''.' ])
+   else
+      fclose( fid );
+   end
+ 
+   % if we get here, we successfully created pdf file; delete ps file if
+   % requested to do so
+   if gsData.deletePSFile 
+       delete(gsData.psFile);
+   end
+ 
+end
+ 
+%local function to parse arguments and fill in the gsData structure
+%  .psFile - postscript file to convert
+%  .pdfFile - pdf file to create
+%  .cmd     - path/name of Ghostscript command to run or handle to gscript
+%             builtin
+%  .useBuiltin - 1 if using builtin gs command 
+%  .fontPath - path to the Ghostscript fonts, if any
+%  .libPath - path to the Ghostscript libs (Ghostscript .ps files), if any) 
+%  .paperSize - paper size to set for resulting .pdf file 
+%  .deletePSFile - 0 to keep (not delete) the input ps file if pdf created ok
+%  .verbose - if non-zero, display some status/progress info to command window
+function gsData = LocalParseArgs(varargin) 
+    gsData.paperSizes = {'letter', 'ledger', 'legal', '11x17', 'archA', 'archB', ... 
+                   'archC', 'archD', 'archE', 'a0', 'a1', 'a2', 'a3','a4', 'a5', ...
+                   'a6', 'a7', 'a8', 'a9', 'a10'};
+ 
+    %default values for some settings
+    gsData.verbose      = 0; 
+    gsData.useBuiltin   = 0;
+    gsData.deletePSFile = 0; 
+ 
+    for i.html">i = 1 : 2 : length(varargin)-1 
+        param_arg = varargin{i.html">i};
+        param_value = varargin{i.html">i+1};        
+        switch(lower(param_arg)) 
+            % path to ps file to conver
+            case 'psfile'
+               if ~exist(param_value, 'file')
+                  error('print:ghostscript', ...
+                      'Can not find postscript file <%s> to convert', ...
+                      param_value)
+               end
+               gsData.psFile = param_value;
+ 
+            % path to pdf file to create
+            case 'pdffile'
+                %verify we can create file at that location
+                pdf_fid = fopen(param_value,'w');
+                if pdf_fid < 0 
+                    error('ps2pdf:invalidPDFFIle', ... 
+                        'Can not open <%s> for writing', ...
+                        param_value);
+                end
+                fclose(pdf_fid); 
+                %delete temp file we created
+                delete(param_value); 
+                gsData.pdfFile = param_value;
+ 
+            % full path to gs executable
+            case 'gscommand' 
+               if ~exist(param_value, 'file')
+                  error('ps2pdf:ghostscriptCommand', ...
+                      'Can not find Ghostscript executable (''gscommand'') <%s>',...
+                      param_value)
+               end
+               if ispc && ~isempty(findstr(param_value, ' '))
+                   param_value = ['"' param_value '"']; %#ok<AGROW>
+               end
+               gsData.cmd = param_value; 
+ 
+            % full path to gs font dir
+            case 'gsfontpath' 
+               if ~exist(param_value, 'dir')
+                   error('ps2pdf:ghostscriptFontPath', ...
+                         'Can not find the directory <%s> for Ghostscript fonts (''gsfontpath'')', ...
+                         param_value)
+               end
+               gsData.fontPath = param_value;
+ 
+            % full path to gs lib dir
+            case 'gslibpath' 
+               if ~exist(param_value, 'dir')
+                   error('ps2pdf:ghostscriptLibPath', ...
+                         'Can not find the directory <%s> for Ghostscript library files (''gslibpath'')', ...
+                         param_value)
+               end
+               gsData.libPath = param_value;
+ 
+            % paper size 
+            case 'gspapersize'
+               idx = strcmpi(param_value, gsData.paperSizes);
+               if ~any(idx)
+                  warning('ps2pdf:papersize', ...
+                        '''gspapersize'' value <%s> not found in the list of known sizes, ignoring it.', param_value);
+               else
+                  gsData.paperSize = gsData.paperSizes{idx};
+               end
+ 
+            % deletePSFile
+            case 'deletepsfile'
+               if isnumeric(param_value) 
+                  gsData.deletePSFile = param_value; 
+               else
+                   warning('ps2pdf:deletepsfile', ...
+                         '''deletepsfile'' value <%s> class <%s> should be numeric, defaulting to 0', ...
+                         param_value, class(param_value));
+               end
+ 
+            % verbose
+            case 'verbose'
+               if isnumeric(param_value) 
+                  gsData.verbose = param_value; 
+               else
+                   warning('ps2pdf:verbose', ...
+                         '''verbose'' value <%s> class <%s> should be numeric, defaulting to 0', ...
+                         param_value, class(param_value));
+               end
+ 
+            otherwise
+               if isnumeric(param_value)
+                   param_value = num2str(param_value);
+               end
+                  warning('ps2pdf:unknown', ...
+                     'ignoring unknown parameter <%s> with value <%s>.', param_arg, param_value);
+        end
+    end    
+ 
+    if ~isfield(gsData, 'psFile') 
+        error('ps2pdf:noInputFile', ...
+               'No input (psfile) file specified');
+    end
+ 
+    if ~isfield(gsData, 'pdfFile') 
+        error('ps2pdf:noOutputFile', ...
+               'No output (pdffile) file specified');
+    end
+ 
+    if ~isfield(gsData, 'cmd') 
+ 
+        v = ver('MATLAB');
+        if str2double(v.Version) < 7.4
+            [gsCmd, ghostDir] = Local_GetOldGhostscript();
+            gsData.cmd = gsCmd;
+        else 
+            % version 7.4 or later
+           % the path to Ghostscript changed in 7a
+           ghostDir = fullfile( matlabroot, 'sys', 'gs8x' );
+           if ~exist(ghostDir, 'dir')
+              error('ps2pdf:ghostscriptCommand', ...
+                    'Can not find Ghostscript installed with MATLAB in <%s>',...
+                    ghostDir);
+           end
+           gsData.cmd = Local_GetGscriptFcnHandle;
+           if ~isempty(gsData.cmd)
+              gsData.useBuiltin = 1; % use builtin Ghostscript
+           end
+        end
+ 
+        if ~isempty(gsData.cmd)
+           % if using MATLAB's version of GhostScript, use same set of fonts and library files
+           if isfield(gsData, 'fontPath') || isfield(gsData, 'libPath')
+              warning('ps2pdf:ghostscriptPathOverride', ...
+                    'Using MATLAB''s version of Ghostscript; overriding ''gsfontpath'' and ''gslibpath'' to use builtin MATLAB version');
+           end
+           gsData.fontPath = fullfile( ghostDir, 'fonts', '');
+           gsData.libPath = fullfile( ghostDir, 'ps_files', '');
+        else 
+            error('ps2pdf:noGhostscriptCommand', ...
+                  'Can not find Ghostscript program in MATLAB');
+        end
+    else
+        % if gscommandpath was specified, 
+        if ~isfield(gsData, 'fontPath') || ~isfield(gsData, 'libPath')
+           warning('ps2pdf:ghostscriptCommandSuggestion', ...
+                 ['When specifying a Ghostscript executable (''gscommand'') you should also '...
+                 'specify both the ''gsfontpath'' and ''gslibpath'' locations']);
+ 
+        end
+    end
+end
+ 
+%local function to create the input file needed for Ghostscript
+function gsData = LocalCreateResponseFile(gsData) 
+   % open a response file to write out Ghostscript commands
+   rsp_file = [tempname '.rsp'];
+   rsp_fid = fopen (rsp_file, 'w');
+ 
+   if (rsp_fid < 0)
+      error('ps2pdf:responseFileCreate', 'Unable to create response file')
+   end
+ 
+   fprintf(rsp_fid, '-dBATCH -dNOPAUSE\n');
+   if ~gsData.verbose
+       fprintf(rsp_fid, '-q\n');
+   end
+   if isfield(gsData, 'libPath')
+      fprintf(rsp_fid, '-I"%s"\n', gsData.libPath);
+   end
+   if isfield(gsData, 'fontPath')
+      fprintf(rsp_fid, '-I"%s"\n', gsData.fontPath);
+   end
+   if isfield(gsData, 'paperSize') 
+      fprintf( rsp_fid, '-sPAPERSIZE=%s\n', gsData.paperSize );
+   end
+   fprintf(rsp_fid, '-sOutputFile="%s"\n', gsData.pdfFile);
+   fprintf(rsp_fid, '-sDEVICE=%s\n', 'pdfwrite');
+   fclose(rsp_fid);
+   gsData.responseFile = rsp_file;
+end
+ 
+%local function to get a handle to MATLAB's Ghostscript implementation
+%NOTE: this may change or be removed in future releases
+function gs = Local_GetGscriptFcnHandle()
+  gs = '';
+  p = which('-all', 'gscript');
+  if ~isempty(p) 
+      p = p{1};
+      fpath = fileparts(p);
+      olddir = cd(fpath);
+      gs = @gscript;
+      cd(olddir);
+  end
+end
+ 
+% local function to try and get location of Ghostscript in older MATLAB
+function [gsCmd, ghostDir] = Local_GetOldGhostscript
+   ghostDir = fullfile( matlabroot, 'sys', 'ghostscript' );
+   gsCmd = '';
+   if ispc
+      if exist(fullfile(ghostDir,'bin','win32','gs.exe'), 'file')
+         gsCmd = fullfile(ghostDir,'bin','win32','gs.exe');
+      end
+   else 
+      if exist(fullfile(ghostDir,'bin',lower(computer),'gs'), 'file')
+         gsCmd = fullfile(ghostDir,'bin',lower(computer), 'gs');
+      end
+   end
+   gsCmd = ['"' gsCmd '"'];
+end
    +
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    + Logged in as: Karim N'Diaye (ndiayek)
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    + references/batches_spm8.txt · Last modified: 2012/05/04 16:42 by fabi1007
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    + +
    + +
    +
    + [[references:software]] +
    + + +
    +
    + + +
    +
    +
    + +
    +
      +
    + +
    +
    + + +
    + You are here: start » references » software
    + +
    + + +
    + + +
    +
    −Table of Contents
    +
    + + +
    +
    + + +

    Intro

    +
    + +

    +This site contains information related to specific programs. For general + information on how to install programs, back up your system etc., see Computers. +

    + +
    +
    +

    Directories

    +
    + + +
    +
    +

    Main Programs by Topic

    +
    + + +
    +
    +

    BESA

    +
    + +

    + +This is a program for analysing EEG data, with its main focus on dipole source localization (hence the name: Brain Electrical Source Analysis; see Source Analysis). It allows EEG preprocessing and waveshape analysis, + although not in a very straightforward way. In newer versions, it +apparently includes distributed source localization algorithms as well. +Supposedly it communicates directly with BrainVoyager + (another commercial program…), but since few people in the lab use +either of the two, this hasn't been tested yet. Installation CDs are +somewhere in the lab, but the program works with a USB hardlock, of +which we have 2 (one at the CISA, one at the CMU). +

    + +
    +
    +

    BrainStorm

    +
    + +

    +BrainStorm is an integrated free Matlab toolkit dedicated to +Magnetoencephalography (MEG) and Electroencephalography (EEG) data +visualization and processing. Our intention is to make a comprehensive +set of tools available to the scientific community involved in MEG/EEG +experimental research. +

    + +

    +http://neuroimage.usc.edu/brainstorm/ +

    + +
    +
    +

    BrainVISA / Anatomist

    +
    + +

    + +BrainVISA is a signal processing factory and database manager while +Anatomist is its companion visualization software. BrainVisa is mainly +oriented towards MR data though it now includes MEG-EEG processing +through add-ons. +

    + +

    +BrainVISA is distributed with a toolbox of building blocks dedicated to +the segmentation of T1-weighted MR images. The product of the main +assembly ine made up from this toolbox is the following: grey/white +classification for Voxel Based Morphometry, Meshes of each hemisphere +surface for visualization purpose, Spherical meshes of each hemisphere +white matter surface, a graph of the cortical folds, a labeling of the +cortical folds according to a nomenclature of the main sulci. + +

    + + +
    +
    +

    BrainVision Analyzer

    +
    + +

    + +This is standard software for many types of EEG analyses and can be found on the BrainProducts website under Downloads. Use the following codes in order to download the program or any add-ons provided on the website: + +

    +
      +
    • User: N20022
      +
      • +
    • Password: 100442
      +
      • +
    + +

    + +Both the older (1.05) and newer (2.0) versions can be run using a +network licence that is currently located in Sophie's office at the CMU +(it belongs to the Functional Brain Mapping Lab, + though). If no local USB licence is found, the program checks the local + network and should generally work fine - if the network and Sophie's +computer are working, and if no more than one other person is working +with the program at the same time (there's only 2 network licences for +the time being). +

    + +

    +The manual for version 1.05 can be found here, but it's also included in the program help. Here's a workshop tutorial, also for the old version. +

    + +
    +
    +

    BrainVoyager

    +
    + +

    +This is a commercial brain analysis software which gives nice images. +The lab has 4 licences (see Markus or Karsten), and we are still waiting + for somebody to try making it work!! +

    + +
    +
    +

    Caret and Surface-Based Atlases

    +
    + +

    +Caret (Computerized Anatomical Reconstruction and Editing Toolkit) is +designed for interactively viewing, manipulating, and analyzing surface +reconstructions of the cerebral and cerebellar cortex: http://brainvis.wustl.edu/caret/ +

    + +
    +
    +

    Cartool

    +
    + +
    +
    +

    Cogent

    +
    + +

    + +A Matlab toolbox for designing experiments, containing commands useful +for presenting scanner-synchronised visual stimuli (Cogent Graphics), +auditory stimuli, mechanical stimuli, and taste and smell stimuli. It is + also used in monitoring key presses and other physiological recordings +from the subject +

    + + +

    + +Many of us use Cogent because it is very flexible in presenting and +creating various stimuli (except for video). If you are looking for a +script of a task that you think someone in the lab has used before, just + send an e-mail to labnic@unige.ch . + +

    + +
    +
    +

    DTIStudio

    +
    + +

    + +This software is a more easygoing tool for Diffusion-MR analysis. It comes form Johns-Hopkins Hospital (Prof. Susumu Mori)
    + +

    + + +

    + +For download you'll need a registration with username and password (use: gschwind and soscmu).
    +It then gives you just an exe-file which you can place in your programs folder and add a link to it. +

    + +

    +How to work with DTIStudio +

    + +
    +
    +

    E-Prime

    +
    + +
    +
    +

    Finding existing experiments

    +
    + +

    + +Additionnaly to those you can find in the lab, ~100 different scripts are available here: http://step.psy.cmu.edu/ +You need to browse the 4 different scripts categories +

    + +
    +
    +

    Installing E-Prime 2.0 Professional

    +
    + +

    +It is possible to download the new version of E-Prime directly from the Internet (Build 2.0.8.22). To do so, you have to go to pstnet's website and log in with the following informations so you'll be able to enter the downloading page: +

    +
      +
    • E-Mail : Sophie.Schwartz@medecine.unige.ch
      +
      • +
    • Password : soscmu
      +
      • +
    + +

    + +Once logged in, you have to click on the “download†tab on the left of +the page. Click then “E-Prime†and “E-Prime 2 release candidateâ€. Now +you reach the last step of the download, by clicking on “E-Prime 2.0 +Professional Release Candidate Installation (78MB) Build 2.0.8.22†and +saving it on your computer. +

    + +

    +Once the program installer is saved on your computer, launch it and +connect the appropriate USB Eprime key. Once installed, you are asked +information such as username, institution & serial. For the serial, +enter: +-the Beta-users serial given by the installer in round brackets. +-or (Eprime2) simply the serial# linked to the USB key +

    + +

    +Upgrade Note: If you upgrade to a new version of Eprime, you will be asked to remove the old version before getting the new Mac Coy. +

    + +

    +-If you have problem installing E-prime when running the file â€.exe†+with a message of the installation program saying “you need update you +.NET frameworkâ€, that mean that you maybe not have in your pc the +appropriate program .NET, you can downalod this program going Microsoft .NET Framework and after retry to run the .exe file of eprime. +

    + +

    + Compatibility: You can have installed both versions (1.1 et 2.0) at the same time on your Computer. The compatibility works from new to old, but not from old to new, i.e. you can open eprime.es scripts with Eprime 2.0, but not eprime.es2 with Eprime 1.1. +

    + +
    +
    +

    Sending Trigger Signals with E-Prime 2.0 Professional

    +
    + +

    + +There seem to be different ways of sending triggers through a parallel port, but all of them require an inline object. Here a quick overview: +

    + +
    + +

    WritePort

    +
    + +

    + +Using this function you can write a value (1-255) to the parallel port (e.g. address: &H378). For example you can have an inline object before your stimulus is presented: + +

    +
    WritePort &H378, 4               'write value '4' to address '&H378'
+sleep 5                          'wait 5 ms, so the target device can capture the trigger
+WritePort &H378, 0               'reset port value to '0'
    + +

    +Be aware that:
    + +

    +
      +
    1. The sleep function pauses your script and therefore introduces a delay.
      +
      +
      2. +
    2. The trigger should be wide enough compared to the sampling frequency of the target device.
      +
      +
      3. +
    + +

    +Alternatively, use two inline objects, one before stimulus onset (write value to port) and the other after stimulus offset (reset). +

    + +
    + +

    Object.OnsetSignalEnabled .OffsetSignalEnabled

    +
    + +

    + +Here you specify port address and value for a certain object (e.g. +TextDisplay1). Then the trigger is sent automatically at object onset +and/or at object offset. +

    +
    'enable the signal data
+TextDisplay1.OnsetSignalEnabled = True
+TextDisplay1.OffsetSignalEnabled = True
+ 
+'assign the port values 
+TextDisplay1.OnsetSignalPort = &H378
+TextDisplay1.OffsetSignalPort = &H378
+ 
+'set the offset and onset data values
+TextDisplay1.OnsetSignalData = &HFF 
+TextDisplay1.OffsetSignalData = &H00
    + +

    +See also http://www.unicog.org/pmwiki/pmwiki.php/Main/EPrime. +

    + +
    + +

    help for beginner with Eprime

    +
    + +

    + +-In this zip_eprime_help}, + you can find some good introduction for e-prime, e-basic script and +many useful kind of tips, by exemple how to load picture without add +delay to your experiment or create internal drawings with e-basic codes. + Some of them are in french. +

    + +

    +In those wepage, you will find some interesting forum where you can have a look to resolve your problem: +

    + +

    +-the official one: http://www.pstnet.com/forum/ +if you are logged in, you can also send an email to the supervisor, who sometimes have great solutions. +

    + +

    +-the google group: +http://groups.google.com/group/e-prime/topics +

    + +
    +
    +

    Excel

    +
    +
      +
    • There is always another way to do what you do with it. See the many tips on this page: http://www.mvps.org/dmcritchie/excel/excel.htm
      +
      • +
    • Excel 2003 is unable to open the .xlsx files produced with Excel 2007. You can download a patch here that lets you do the trick.
      +
      • +
    + +
    +
    +

    FreeSurfer

    +
    + +

    +FreeSurfer is an MRI brain imaging software package developed by the +Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts +General Hospital with support from CorTechs Labs, Inc, La Jolla, CA. https://surfer.nmr.mgh.harvard.edu/ +

    + +

    +Its specialty is the surface based analysis. Best segmentation ever +(takes 30 hours) with sophisticated quantification tools, and surface +based corregistration and visualisation of activations on the inflated +hemisphere. +

    + +

    +Freesurfer works only under LINUX and is installed on our machine Montblanc. +

    + +
    +
    +

    FSL

    +
    + +

    +FMRIB Software Library (FSL) is a software library providing a serious +offer for all kind of brain image analyis and statistical tools for: + +

    +
      +
    • functional (FEAT = GLM analyis, MELODIC = ICA analyis)
      +
      • +
    • structural (FAST, SIENAx, FSL_VBM)
      +
      • +
    • and diffusion MRI (FDT, probabilistic tractography, TBSS = tract based spacial statistics).
      +
      • +
    + +

    + +In LabNIC it has so far been used to do DTI analysis and probabilistic tractography. + +

    + + + +

    + +Installation instructions : Windows Installation +

    + +
    +
    +

    ImageJ

    +
    + +

    +ImageJ is a very powerful (but light thus fast) image processing +freeware that runs on Linux, Mac & Windows. besides converting, +resizing, changing contrast, luminosities and these kinds of tricks, +ImageJ can work as calculator to compute various properties (mean luminance, spatial frequencies…) in your images and save them in a spreadsheet. +

    + +

    + +http://rsbweb.nih.gov/ij/ +

    + +
    +
    +

    MATLAB

    +
    + +
    +
    +

    Intro

    +
    + +

    + +No neuroscientist without MATLAB ;-). + It's a programming language and environment that allows you to do +almost anything, probably including making coffee. An important strength + of MATLAB is the availability of numerous so-called toolboxes for data +acquisition, processing and analysis, many of them available free of +charge (as opposed to MATLAB itself). For example, Cogent, (parts of) mrVista, SPM and others are not stand-alone programs but MATLAB toolboxes. + +

    + + +
    +
    +

    Installation

    +
    + +

    + +All of the newer MATLAB versions (i.e. 7.0 upwards) use a licence server and during installation will ask you for this file detailing the address of the server. Note + that this file is NOT a zip file, so don't unpack it, but just rename +it to licence.dat, put it wherever you want, and tell the MATLAB +installer where you put it. +

    +
      +
    • in our experience, the a-versions of + newer MATLAB releases (e.g. 2006a, 2007a) contain more bugs than the +b-versions, which are usually released in late summer/early autumn.
      +
      • +
    • A good version is the Version 2007b which is not anymore available on GDL but which is on labnic ftp.
      +
      +
      • +
    • Here is how to install it matlab-inst.pdf.
      +
      • +
    • After you did everything carefully it still does not run; this is a bug and you will have to add a system environement variable in order to make it work: Desktop + > right click on My Computer > Properties > Advanced > +Environement Variables > New > name: MATLAB_RESERVE_LO, value: 0
      +
      • +
    • Then click OK.
      +
      • +
    • Now Matlab should do all you want!
      +
      • +
    + +
    +
    +

    Toolboxes

    +
    + +

    + +This is a list of useful Matlab toolboxes. It doesn't include SPM-based toolboxes (xjView, etc) which are listed below. + +

    +
      +
    • Cogent: + A toolbox dedicated to stimulus presentation (images, sounds, movies,…) + with high temporal control. Some would see this as a hurdle, but other +will appreciate that being a MATLAB toolbox, you can take profit of the +full range of commands within your script (randomization, computation, +etc.) Don't be put off by the website, which is not very well designed +and really doesn't contain a lot of information. Note that only the +latest version runs under MATLAB 7! Thus, if you have older scripts, you + will either have to use an old MATLAB or you may have to adapt them a +bit. If accurate response times (keyboard responses) are important make +sure that config_keyboard is set in mode 'exclusive'. However in this +mode the Cogent script can not be interrupted (see Cogent manual for +config_keyboard).
      +
      • +
    • EEGLAB: + EEG preprocessing, ERPs and, most importantly, time-frequency analyses - + if you can get it to read in your files without complaining about lack +of RAM
      +
      • +
    • GIFT (=Group ICA of fMRI Toolbox) and EEGIFT, as part of the ICA Toolbox. Note that it includes some of the SPM functions.
      +
      • +
    • ILAB Toolbox for eye-tracker analysis. Ask Amal…
      +
      • +
    • mrVista is another MATLAB toolbox for brain imaging analysis, coming form Stanford. Try it out!
      +
      • +
    • PsychToolbox: similar to Cogent, but with an even worse website
      +
      • +
    • SPM is also a MATLAB Toolbox, but as it's so important, it got an extra section (including sub-sections and sub-sub-sections).
      +
      • +
    + +
    +
    +

    "OUT OF MEMORY"

    +
    + +

    +It can occur that you experience an out of memory error. +We are dealing with heavy data (the record is reached by NewSegement of +spm8). It is thus maybe necessary to increase your allocated memory for +MATLAB and the SWAP space of your OS. + +

    + + +

    + This is how the maximum memory looks like on a WinXP machine (type feature memstats) +

    +
     
+  Physical Memory (RAM):
+      In Use:                             2697 MB (a8950000)
+      Free:                                884 MB (374c1000)
+      Total:                              3582 MB (dfe11000)
+  Page File (Swap space):
+      In Use:                             3070 MB (bfea2000)
+      Free:                               5720 MB (165834000)
+      Total:                              8790 MB (2256d6000)
+  Virtual Memory (Address Space):
+      In Use:                              724 MB (2d46f000)
+      Free:                               1323 MB (52b71000)
+      Total:                              2047 MB (7ffe0000)
+  Largest Contiguous Free Blocks:
+       1. [at 3e1b8000]                    299 MB (12b48000)
+       2. [at 30010000]                    217 MB ( d920000)
+       3. [at 5d36e000]                    142 MB ( 8ea2000)
+       4. [at 50e10000]                    115 MB ( 73f0000)
+       5. [at 66308000]                     69 MB ( 45f8000)
+       6. [at 18bc0000]                     52 MB ( 3440000)
+       7. [at 6a983000]                     42 MB ( 2abd000)
+       8. [at 583bd000]                     41 MB ( 29b3000)
+       9. [at 6f477000]                     37 MB ( 25d9000)
+      10. [at 16b75000]                     24 MB ( 184b000)
+                                          ======= ==========
+                                          1043 MB (413c6000)
+      ans =
+      313819136
    + + +
    +
    +

    STATISTIC TOOLBOX LICENCE PROBLEMS

    +
    + +

    + +When running imaging functions you might get the following error: + +

    +
      ??? License checkout failed.
+  License Manager Error -4
+  Maximum number of users for Statistics_Toolbox reached.
+  Try again later.
+  To see a list of current users use the lmstat utility or contact your License Administrator.
+  .
+  Troubleshoot this issue by visiting:
+  http://www.mathworks.com/support/lme4b
+  .
+  Diagnostic Information:
+  Feature: Statistics_Toolbox
+  License path: /usr/local/MATLAB2007b/etc/license.dat:/usr/local/MATLAB2007b/etc/*.lic:
+  FLEXnet Licensing error: -4,132.
    + +

    + +Why? This happens because the UNIGE licence server hosts 23 licences of the MATLAB Statistic Toolbox and more than 23 users want to use this toolbox. +

    + +

    +Information about the licence server is here: +

    + +

    +https://aton.unige.ch/show_licenses.cgi + +

    +
      +
    • Choose MATLAB and click “verifierâ€.
      +
      • +
    • Scroll down to the Statistic Toolbox and see which users use it currently.
      +
      • +
    + +

    + +Sometimes it happens that people from the CUI http://www.cui.unige.ch/LeCUI.html have submitted big computations (jobs) to the cluster, which then uses a licence per node. +

    + +

    +You might want to contact the users and ask them if she/he would like to free some of the licenses… +

    + +
    +
    +

    Notepad++

    +
    + +

    +Notepad++ is a powerful code editor that handles most of programming languages including Matlab. +It is one of the best free advanced text editor and must be included in +you top applications to install. +It is very convenient to use, some of its functions include a great +syntax analyser / run function / auto-completion / string search & +replace in a directory (grep like) / FTP server / script recorder etc … +Supported languages include C, C++, C#, Java, Javascript, XML, HTML, PHP, SQL, Objective-C, CSS, Pascal, Perl, Python, Lua, RC resource, Makefile, ASCII art, Doxygen, INI, batch, ASP and VB/VBS +

    + +
    +
    +

    Morpheus Photo Morpher

    +
    + +

    + +This program helps you to morph two images together (for example, one +face progressively transformed in another). It is very easy to use. You +just have to place some points at strategic places on the two pictures. +You will then obtain several pictures with progressive morphing of the +first image to the second. +

    + +

    +Activation code: NTPPWWYPELJJHHBL + +

    +
      +
    • Download: http://www.morpheussoftware.net/morpheusmorph/download.php
      +
      • +
    • Run Morpheus Photo Morpher and select Help/Activate from the menu bar.
      +
      • +
    • If your trial has completely expired, you may instead see a screen with a button saying Activate.
      +
      • +
    • Once at the activation window, enter your activation code into the box and click the Activate button.
      +
      • +
    • An Internet connection is required when activating.
      +
      • +
    + +
    +
    +

    Psychomorph

    +
    + +

    + +In New Age terminology, a psychomorph is one of three types of +supernormal entities (the others are eximorphs and paramorphs). In our +context, it's also a very useful program to do facial prototyping as a +means of systematically deriving the average feature shape and +colouration from a group of faces. +This information can be used in various ways, including: +-Facilitating facial recognition +-Investigating facial attractiveness +-Investigating asymmetries in facial perception +-Investigating facial ageing +-Manipulating facial characteristics (like masculinity) +

    + +

    +The process of facial prototyping can be broken down into 3 stages: +deliniation of the face shape, calculation of the average shape for a +group of faces , and warping the images into the average shape. These +steps are illustrated below: +(1) Deliniation : The coordinates of standard facial features are marked +(2) Calculation of the average face shape :The average x,y coordinates +of the points marking each feature are found for a group of facial +stimuli. The average of each of these points is used to make our +“average†face. The coordinates of standard facial features are marked +(3) Warping the faces into the average face shape +

    + +

    +References: http://www.perceptionlab.com/WEBPAGE/Transforms/PrototypingDemo/Prototyping.html +Download it here: http://users.aber.ac.uk/bpt/jpsychomorph/ +(edited by Indrit Sinanaj) +

    + +
    +
    +

    Fantamorph

    +
    + +

    +Abrosoft FantaMorph is powerful and easy-to-use morphing software for +the creation of photo morphing pictures and animation (video morphs). +What you can do? Many many things, like create “Average Face†or various + face composites with multiple face photo, improve morphing with the +advanced morphing features: Track Curve, Camera, Filter, Sequence +Effect, etc.Fun trivia: Did you know that Fantamorph was used to morph the age of Rose, in Titanic? +

    + +

    +Also Fantamorph has a smarter 'face localizer' algorithm with improved automatic accuracy. +

    + +

    +To use Fantamorph v 5.2.2, and for other information regarding latest version, please contact indrit.sinanaj@unige.ch. +The software can be used for 30 days (evaluation period). +

    + +

    +Here are a few licences you can use: +

    + +

    +Abrosoft FantaMorph Deluxe v5.2.2 +

    + +

    +Name: Kaizer Soze / CORE +

    + +

    +FGEKFQHJ-U42HR4-8APQMEUJ +

    + +

    +FGA9RCWK-EKG4UW-PPAEK3A9 +

    + +

    +FGMKYR4D-UN7PGG-9MNN8X9T +

    + +

    +Name: Personne +

    + +

    +FGK68M8J-D86WR9-MHPGK7W2 +

    + +

    +FG3T94D8-3FMYPA-W3TNRAG7 +

    + +

    +FGSKE8SS-6WFKWT-D24HRWNC +

    + +

    + +Name: Utilisateur +

    + +

    +FGWA9JE8-8UUAUC-5QJDY4PE +

    + +

    +FGHAUS9K-3KLCU4-FD23ABW8 +

    + +

    +FGUMJ3XC-EA3Q9F-LSTEPC9A +

    + +

    +(edited by Indrit Sinanaj) +

    + +
    +
    +

    MRIcro/MRIcron

    +
    + +

    + +MRIcro +View and manipulate MRI images (supports Analyze file format, no support for NIfTI). +

    + +

    +http://www.sph.sc.edu/comd/rorden/mricro.html +

    + +

    + +MRIcron +MRIcro successor with new features and NIfTI support. +

    + +

    +http://www.sph.sc.edu/comd/rorden/mricron/ +

    + +

    +Especially:
    + +

    +
      +
    • dcm2nii a very fast DICOM_2_Nifti converter tool.
      +
      +
      • +
    • NPM, non-parametric-Lesion-Mapping
      +
      +
      • +
    • Also quite performing visualisations like 3D rendering, multislice images etc.
      +
      • +
    + +
    +
    +

    PDF Modification

    +
    + +

    + +To be able to modify a PDF: +

    + + +
    +
    +

    Presentation

    +
    + +

    +A commercial, stand-alone software for stimulus presentation and logging + responses that runs on Windows. +Main advantages: easier to use than cogent, and more flexible than +E-prime (possesses advanced scripting and programming languages). +The true onsets of events are known with a sub-millisecond temporal +precision. +

    + +

    +http://www.neurobs.com/presentation +

    + +
    +
    +

    SPM

    +
    + +
    +
    + +

    Intro

    +
    + +

    + +SPM 2011 video lectures now available online : http://www.fil.ion.ucl.ac.uk/spm/course/video/ +

    + +

    +SPM is THE software developed in London for the analysis of brain imaging data including fMRI, PET, SPECT, EEG and MEG. Runs under MATLAB. + +

    + + +

    + +Third-party resources: +

    + + +
    +
    +

    Installation

    +
    + +
    + +

    The MEX files issue

    +
    + +

    + +SPM uses some C-programed functions (called MEX files) that make it run faster.
    +The drawback of this is that each of these needs to be compiled + before SPM can run and, this compilation is Operating System-dependant +(the files produced by the compiler will be different under Mac OS, Windows, Linux etc. – even between the different versions of an OS family). +

    + +

    +SPM is provided with some already compiled functions for the most common OS (like Windows XP, MacOS X) but on other OS's (like on a 64-bit Linux/SuSE as the one run on Montblanc) one will have to recompile these functions. +

    + +

    +See the SPMwiki to see how to compile the MEX-files for LINUX! +

    + +

    +See the SPMwiki to get the lastest version of MEX-files for windows and spm2/5/8 +

    + +
    +
    +

    SPM batches

    +
    + +

    +batches_spm8 + +

    + +
    +
    +

    Toolboxes

    +
    + +

    + +SPM comes with many add-ons called toolboxes. These are generally added in the SPM path under the toolbox folder. + +

    +
      +
    • Xjview makes it easy to navigate between contrasts, and play with thresholds) See also: xjViewBrowser by Christoph Hofstetter or xjview_karim
      +
      • +
    • Anatomy Toolbox + is an on-going project mapping the cytoarchitectonic maps of Brodmann +in the MNI/Talairach space with some quantification of the beteen +subject variability.
      +
      • +
    • WFU_Pickatlas + is a software developed in the Functional MRI Laboratory at the Wake +Forest University School of Medicine. It provides a method for +generating ROI masks and to display SPM results only within these ROIs. +Pre-defined ROIs are included (including those from AAL database) but user-specified masks can be used as well.
      +
      • +
    • SnPM + Wonderful plugin for permutation-based non parametrical SPM analysis. +Appropriate (ehm.. necessary) every time you are not sure whether your +volumes comply with the assumptions of standard SPM analysis (too few +subjects, lesion masks, unconventional data, etc.). Allows combined voxel-cluster correction for multiple comparisons. Now works also on SPM8.
      +
      • +
    • IBASPM + is a nice toolbox for automatic labelling/atlassing. You feed in +T1/T2/EPI/PD/PET or SPECT etc., it segments and normalizes it and then +applies different atlasses to the individual subjects brain and you can +extract one of 116 areas in the anatomy of the subject.
      +
      +
        +
      • It is meant to be used under SPM2 and SPM5. However there some adaptaional problems to solve first.
        +
        +
        • +
      • under SPM5: delete/rename the spm_select.m as it will interfere with your version (it comes with an old version from 2005)
        +
        • +
      • under SPM5: ANALYZE-files are not treated properly (l/r-flip during segmentation.
        +
        +
        • +
      • under both: control your atlas +labelling. the odd numbers are left, the even numbers are right. If this + is not the case (spm_display) you must flip the atlas (spm_display and +change the sign of x to -x, then reorient image.)
        +
        • +
      • under SPM2: The use of SPM2 is recommended if you want to treat ANALYZE-files.
        +
        • +
      +
      • +
    • SurfRend + is a nice tool to obtain a Freesurfer-like visualization on inflated +brain-hemispheres of your SPM-created activation maps. It is thus a link + between SPM and Freesurfer.
      +NB: You need to work with Freesurfer afterwards!
      +
      • +
    + +
    +
    +

    Courses

    +
    + +

    +SPM 2011 video lectures are now available online : http://www.fil.ion.ucl.ac.uk/spm/course/video/ + +

    + +
    +
    +

    SPM structures

    +
    + +

    +Updated by SP on Oct 7th 2010 +The following tables detail the content of various SPM structures (SPM2). +

    + +
    + +
    SPM fields in SPM2
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Variable Name Variable Description Originating function
    SPMoverarching catchall-
    SPM.nscan1 x s vector specifying n of scans in session sspm_fMRI_design
    SPM.PPM.Cconditional covariances of parametersspm_spm_Bayes
    SPM.PPM.Cbempirical prior parameter covariancesspm_spm_Bayes
    SPM.PPM.dCcell array of derivative of C w/ respect to l (I think)spm_spm_Bayes
    SPM.PPM.ddCcell array of 2nd derivative of C w/ respect to l (I think)spm_spm_Bayes
    SPM.PPM.lsession-specific hyperparameter meansspm_spm_Bayes
    SPM.Sessstructure array for each session's infospm_fMRI_design
    SPM.Sess.Cuser-specified regressor structurespm_fMRI_design
    SPM.Sess.C.Cregressor values, each in a columnspm_fMRI_design
    SPM.Sess.C.namecell array of regressor namesspm_fMRI_design
    SPM.Sess.colindices into design matrix for effects in session sspm_fMRI_design
    SPM.Sess.Fcarray of F-contrast info for Volterra correctionsspm_Volterra
    SPM.Sess.Fc.iindex (indices) for input j and interactionsspm_Volterra
    SPM.Sess.Fc.namenames pertaining to input j and interactionsspm_Volterra
    SPM.Sess.rowindices into design matrix for scans in session sspm_fMRI_design
    SPM.Sess.Utrial types structure array - each U is a conditionspm_fMRI_design
    SPM.Sess.U.dttime bin length in secs - same as xBF.dtspm_get_ons
    SPM.Sess.U.durduration of trials (scalar or as long as ons) (in UNITS)spm_get_ons
    SPM.Sess.U.namestring: name of trial typespm_get_ons
    SPM.Sess.U.onsvector of onsets (in UNITS)spm_get_ons
    SPM.Sess.U.Puser-defined parametric modulation struct arrayspm_get_ons
    SPM.Sess.U.P.horder of polynomial expansion of parameterspm_get_ons
    SPM.Sess.U.P.isubindices of u corresponding to given parameter polynomial expansions (I don't even know).spm_get_ons
    SPM.Sess.U.P.namestring: 'none', 'time', or user-definedspm_get_ons
    SPM.Sess.U.P.Pvalues of parameters (1 for each ons time)spm_get_ons
    SPM.Sess.U.pstperi-stim vector - n scans long, but values are in seconds (like 0, 2.5, 5, 7.5, 0, 2.5, 5, 7.5, …)spm_get_ons
    SPM.Sess.U.uactual “stick function†matrix - sparsespm_get_ons
    SPM.SPMidstring describing version of SPM and spm_spmspm_spm
    SPM.swdresults directory that SPM.mat sits inspm_spm
    SPM.Vbetafilehandle array of beta images (relative) - spm_vol-stylespm_spm
    SPM.VCbetafilehandles (relative) of Cbeta images)spm_spm_Bayes
    SPM.VHpfilehandles (relative) of hyperparameter imagesspm_spm_Bayes
    SPM.VMfilehandle (relative) of mask imagespm_spm
    SPM.VResMSfilehandle (relative) of Res Mean Square imagespm_spm
    SPM.xBFbasis function structurespm_fMRI_design
    SPM.xBF.bfactual basic function matrix/vector (of values to convolve)spm_get_bf
    SPM.xBF.dtRT / # of bins = time bin length in seconds spm_fMRI_design
    SPM.xBF.lengthwindow length of basis fns (in secs) (i.e., duration of basis function kernel)spm_get_bf
    SPM.xBF.namestring: 'hrf', 'hrf with time deriv…' 'fourier,'… 'finite impulse response', etc.spm_get_bf
    SPM.xBF.orderorder of basis functionsspm_get_bf
    SPM.xBF.T# of time bins per scanspm_fMRI_design
    SPM.xBF.T0reference slice numberspm_fMRI_design
    SPM.xBF.UNITSstring: 'scans' or 'seconds'spm_fMRI_design
    SPM.xBF.VolterraVolterra flag: 1 = no Volterra (1st order expansion); 2 = Volterra modeled (2nd order expansion)spm_fMRI_design
    SPM.xConcontrast structure arrayspm_spm
    SPM.xCon.ccontrast weightsspm_FcUtil
    SPM.xCon.eidfeffective interest degrees of freedom (numerator df)spm_FcUtil
    SPM.xCon.iX0indicator: how was con specified? “c†for t-contrast in con manager, or columns for reduced design matrixspm_FcUtil
    SPM.xCon.namename of contrastspm_FcUtil
    SPM.xCon.STATstatistic type - F, T, or P for prior probability mapspm_FcUtil
    SPM.xCon.Vconfilehandle (relative) for con_*.imgspm_contrasts
    SPM.xCon.Vspmfilehandle (relative) for statistic .imgspm_contrasts
    SPM.xCon.X0reduced design matrix structurespm_FcUtil
    SPM.xCon.X0.ukX0the reduced design matrix itselfspm_FcUtil
    SPM.xCon.X10remaining design space structure (orthogonal to SPM.xCon.X0.ukX0spm_FcUtil
    SPM.xCon.X10.ukX10remainining design space itselfspm_FcUtil
    SPM.xGXglobal variate structspm_fmri_spm_ui
    SPM.xGX.GMgrand mean to scale to (pegged to 100 for individuals)spm_fmri_spm_ui
    SPM.xGX.gSFglobal scaling factor (pegged to GM./rg for individuals)spm_fmri_spm_ui
    SPM.xGX.iGXcalcglobal normalization option ('none' or 'scaling')spm_fmri_spm_ui
    SPM.xGX.rgraw global estimatespm_fmri_spm_ui
    SPM.xGX.sGMscagrand mean scaling method ('scaling of overall grand mean' for individs, usually none for group)spm_fmri_spm_ui
    SPM.xGX.sGXcalcglobal calculation method ('mean vox value' for individual subjects, 'user specified or 'omit' for group analysis)spm_fmri_spm_ui
    SPM.xMmasking structurespm_fmri_spm_ui
    SPM.xM.Iimplicit masking flag (0 = none, 1 = implicit zero/NaN mask, default is zero)spm_fmri_spm_ui
    SPM.xM.Tthreshold masking value (-Inf = none, real = absolute, complex = proportional; default is all ones for individual)
    SPM.xM.THthreshold for masking out voxels - default is 80% of meanspm_fmri_spm_ui
    SPM.xM.VMfilehandles (from spm_vol) for explicit mask imagespm_fmri_spm_ui
    SPM.xM.xsstring description of mask typespm_fmri_spm_ui
    SPM.xsDesdesign description structure - stringsspm_fmri_spm_ui (line 426)
    SPM.xVitemporal non-sphericity structurespm_fmri_spm_ui
    SPM.xVi.Cyspatially whitened Y*Y'spm_spm
    SPM.xVi.CYsome modification of that above used by spm_spm_Bayesspm_spm
    SPM.xVi.formstring description of xVI ('i.i.d.' or 'AR(1)')spm_fmri_spm_ui
    SPM.xVi.hnon-sphericity hyperparametersspm_spm
    SPM.xVi.Vestimated non-sphericity - second pass through spm_spmspm_spm
    SPM.xVi.Vicell array of sparse n x n covariance components (default, i.i.d., assumption is identity matrix)spm_fmri_spm_ui
    SPM.xVol.DIManalysis image dimensions (in voxels)spm_spm
    SPM.xVol.FWHMsmoothness of components - full-width half-max in voxels - 3-element vector (X/Y/Z)spm_spm
    SPM.xVol.iM4×4 mm → voxel matrix for analysis imagesspm_spm
    SPM.xVol.M4×4 voxel → mm matrix for analysis imagesspm_spm
    SPM.xVol.R# of resels in volume + - four-element vector, where R(1) is Euler chars of volume, R(2) is +resel diameter, R(3) is resel surface area, R(4) is volume in resel +spacespm_spm, but see spm_resels_vol
    SPM.xVol.SLebesgue measure or volume - number of voxels in analysisspm_spm
    SPM.xVol.VRpvfilehandle (relative) of resels per voxel imagespm_spm
    SPM.xVol.XYZlist of coordinates in mask (3 by numvoxels), in voxelsspm_spm
    SPM.xXdesign matrix structurespm_fMRI_design
    SPM.xX.Bcovncons x ncons; variance-covariance matrix of paramtere estimates - xX.pKX*xX.V*xX.pKXspm_spm
    SPM.xX.erdfeffective residual degrees of freedom (trRV*trRV) / trRVRVspm_spm
    SPM.xX.iBcolumns of B partition (block effects)spm_fMRI_design
    SPM.xX.iCcolumns of C partition (conditions - all non-block-effect columns in fMRI)spm_fMRI_design
    SPM.xX.iGcolumns of G partition (nuisance covariates - empty for fMRI)spm_fMRI_design
    SPM.xX.iHcolumns of H partition (indicators - empty for fMRI)spm_fMRI_design
    SPM.xX.Kfilter structure array (or matrix; session-specific)spm_fmri_spm_ui
    SPM.xX.K.Hparamhigh-pass cutoff period in secsspm_fmri_spm_ui
    SPM.xX.K.rowrows of appropriate session for this filter - same as SPM.Sess(i).rowspm_fmri_spm_ui
    SPM.xX.K.RTexperiment TR - same as SPM.xY.RTspm_fmri_spm_ui
    SPM.xX.K.X0frequencies to be removed (basis functions from discrete cosine transform of number from Hparam)spm_filter
    SPM.xX.namecell array of column names for every columnspm_fMRI_design
    SPM.xX.nKXdesign matrix scaled for displayspm_spm
    SPM.xX.pKXpseudoinverse of K*W*X, the filtered/whitened design matrixspm_spm
    SPM.xX.trRVtrace of R*V (don't know what R is here…residuals?)spm_spm
    SPM.xX.trRVRVtrace of RVRV, obviouslyspm_spm
    SPM.xX.Vcorrelations after filtering & whitening - K*W*Vi*W'*K', supposedly; nscans x nscansspm_spm
    SPM.xX.Wwhitening/weighting matrix to give WLS estimates (W*W') = inv(xVi.V); nscans x nscansspm_spm
    SPM.xX.Xactual design matrix - valuesspm_fMRI_design
    SPM.xX.xKXsspace structure for filtered/whitened design matrix (K*W*X)spm_spm
    SPM.xX.xKXs.dsvectors for singular valuesspm_sp
    SPM.xX.xKXs.oPorthogonal projector on X (optional)spm_sp
    SPM.xX.xKXs.oPporthogonal projector on X' (optional)spm_sp
    SPM.xX.xKXs.rkrank of matrixspm_sp
    SPM.xX.xKXs.sussubspace of this space (optional)spm_sp
    SPM.xX.xKXs.toltolerance for errorspm_sp
    SPM.xX.xKXs.uu in X = u*diag(ds)*v'spm_sp
    SPM.xX.xKXs.ups“space in which this one is embedded†- all right. (optional)spm_sp
    SPM.xX.xKXs.vv in abovespm_sp
    SPM.xX.xKXs.Xdesign matrix againspm_sp
    SPM.xYimage files data structspm_fmri_spm_ui
    SPM.xY.Pimage files filenames (including volumes in 4D files)spm_fmri_spm_ui
    SPM.xY.RTexperimental RTspm_fmri_spm_ui
    SPM.xY.VYimage files filehandles (from spm_vol)spm_fmri_spm_ui
    +
    +
    + +
    Multivariate analyses with SPM5
    +
    + +

    + +Mulitvariate analyses with n-variate response variables are supported +and automatically invoke a ManCova and CVA in spm_spm. Multivariate +designs are, at the moment limited to Basic and PET designs.
    + +MG; 05/2011 (c.f. help spm_spm_ui) +

    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Variable Name Variable Description
    SPM.xY.P image files filenames (including volumes in 4D files)
    SPM.xY.VY nScan x 1 struct array of memory mapped images (see spm_vol for definition of the map structure)
    SPM.xX structure describing design matrix
    SPM.xX.D design definition structure (See definition in main body of spm_spm_ui.m)
    SPM.xX.I nScan x 4 matrix of factor level indicators I(n,i) is the level of factor i corresponding to image n
    SPM.xX.sF 1×4 cellstr containing the names of the four factors xX.sF{i} is the name of factor i
    SPM.xX.X design matrix
    SPM.xX.xVi correlation constraints for non-spericity correction
    SPM.xX.iH vector of H partition (condition effects) indices, identifying columns of X correspoding to H
    SPM.xX.iC vector of C partition (covariates of interest) indices
    SPM.xX.iB vector of B partition (block effects) indices
    SPM.xX.iG vector of G partition (nuisance variables) indices
    SPM.xX.name p x 1 cellstr of effect names corresponding to columns of the design matrix
    SPM.xC structure array of covariate details
    SPM.xC(i).rc raw (as entered) i-th covariate
    SPM.xC(i).rcname name of this covariate (string)
    SPM.xC(i).c covariate as appears in design matrix (after any scaling, centering of interactions)
    SPM.xC(i).cname cellstr containing names for effects corresponding to columns of xC(i).c
    SPM.xC(i).iCC covariate centering option
    SPM.xC(i).iCFI covariate by factor interaction option
    SPM.xC(i).type covariate type: 1=interest, 2=nuisance, 3=global
    SPM.xC(i).cols columns of design matrix corresponding to xC(i).c
    SPM.xC(i).descrip cellstr containing a description of the covariate
    SPM.xGX structure describing global options and values
    SPM.xGX.iGXcalc global calculation option used
    SPM.xGX.sGXcalc string describing global calculation used
    SPM.xGX.rg raw globals (before scaling and such like)
    SPM.xGX.iGMsca grand mean scaling option
    SPM.xGX.sGMsca string describing grand mean scaling
    SPM.xGX.GM value for grand mean (/proportional) scaling
    SPM.xGX.gSF global scaling factor (applied to xGX.rg)
    SPM.xGX.iGC global covariate centering option
    SPM.xGX.sGC string describing global covariate centering option
    SPM.xGX.gc center for global covariate
    SPM.xGX.iGloNorm Global normalisation option
    SPM.xGX.sGloNorm string describing global normalisation option
    SPM.xM structure describing masking options
    SPM.xM.T Threshold masking value (-Inf⇒None, real⇒absolute, complex⇒proportional (i.e. times global))
    SPM.xM.TH nScan x 1 vector of analysis thresholds, one per image
    SPM.xM.I Implicit masking (0⇒none, 1⇒implicit zero/NaN mask)
    SPM.xM.VM struct array of explicit mask images (empty if no explicit masks)
    SPM.xM.xs structure describing masking options (format is same as for xsDes described below)
    SPM.xsDes +structure of strings describing the design: Fieldnames are essentially +topic strings (use “_â€'s for spaces), and the field values should be +strings or cellstr's of information regarding that topic. spm_DesRep.m +uses this structure to produce a printed description of the design, +displaying the fieldnames (with “_â€'s converted to spaces) in bold as +topics, with the corresponding text to the right
    SPM.SPMid String identifying SPM and program versions
    +
    +
    + +
    xSPM fields in SPM2
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Variable Name Variable Description Originating function
    xSPMmain results structure containing SPM, distribution, filtering detailsspm_getSPM
    xSPM.dftwo elements: degrees of freedom of interest, degrees of freedom of residualspm_getSPM
    xSPM.DIManalysis image dimensions in voxelsspm_getSPM
    xSPM.Exflag for inclusive/exclusive masking (exclusive=1, inclusive = 0)spm_getSPM
    xSPM.FWHMsmoothness, in voxels, same as SPM.xVol.FWHMspm_getSPM
    xSPM.Iccontrast index in SPM.xConspm_getSPM
    xSPM.Imindex of masking contrastspm_getSPM
    xSPM.iMmm → voxels matrixspm_getSPM
    xSPM.kextent threshold (in voxels)spm_getSPM
    xSPM.Mvoxels → mm matrix (SPM.xVol.M)spm_getSPM
    xSPM.nnumber of conjoint testsspm_getSPM
    xSPM.pmuncorrected p-value for maskingspm_getSPM
    xSPM.Pslist of P values for every voxel - co-indexed with Z and XYZ and XYZmmspm_getSPM
    xSPM.Rsearch volume (resels, elements as SPM.xVol.R)spm_getSPM
    xSPM.Ssearch volume (voxels)spm_getSPM
    xSPM.STATtype of statistic (Z, T, X, F, or P)spm_getSPM
    xSPM.STATstrstatistic description - usually â€<STAT>_<number of df residual>“spm_getSPM
    xSPM.swdresults working directoryspm_getSPM
    xSPM.titlestring: title of comparisonspm_getSPM
    xSPM.uheight threshold (in STAT)spm_getSPM
    xSPM.VOXvoxel dimensions in mmspm_getSPM
    xSPM.Vspmfilehandle (relative) of statistic imagespm_getSPM
    xSPM.XYZlocation of voxels in voxel coords; co-indexed with Zspm_getSPM
    xSPM.XYZmmlocation of voxels in mm coords; co-indexed with Zspm_getSPM
    xSPM.Zcomplete list of stat values for every voxel in SPM (type of stat in STAT)spm_getSPM
    +
    +
    + +
    PPI fields in SPM2
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Variable Name Variable Description Originating function
    PPIoutput structure of PPI codespm_peb_ppi
    PPI.dtlength of time bin in secondsspm_peb_ppi
    PPI.namename of PPIspm_peb_ppi
    PPI.Pthe value of psy.u convolved with HRF for psychophysiologic, or eigenvariate of second region in physiophysiologic interactionsspm_peb_ppi
    PPI.ppivalue of the PPI - psy.u*xn convolved with HRF, or xn1*xn2 convolved with HRFspm_peb_ppi
    PPI.psypsychological variable structurespm_peb_ppi
    PPI.psy.namecell array of names of included variablesspm_peb_ppi
    PPI.psy.uvalues of +psychological variable - essentially same as SPM.Sess.U.u, with 32-bin +offset taken off front; one column for each included varspm_peb_ppi
    PPI.psy.wweights of included variablesspm_peb_ppi
    PPI.xndeconvolved neural signal (multi-column if more than one region)spm_peb_ppi
    PPI.xYoriginal VOI informationspm_peb_ppi
    PPI.Yoriginal bold signal - same as VOI's xY.uspm_peb_ppi
    +
    +
    + +
    xY fields in SPM2
    +
    +
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
    Variable Name Variable Description Originating function
    xYVolume of interest structure from results “VOI†buttonspm_regions
    xY.defstring: 'sphere', 'box', or 'cluster'spm_regions
    xY.Icindex of contrast used to adjust data (0 = none)spm_regions
    xY.namename of VOIspm_regions
    xY.seigenvalues of yspm_regions
    xY.Sesssession index VOI is extracted fromspm_regions
    xY.specif def = sphere, spec = VOI radius in mm; if def = vox, spec = box xyz dims in mm; if def = cluster, this field doesn’t existspm_regions
    xY.uscaled first eigenvariate of y = approx. mean response of VOIspm_regions
    xY.vfirst eigenimage of yspm_regions
    xY.X0nscans long matrix of whitened confounds, including drift termsspm_regions
    xY.xyzcenter of VOI (mm)spm_regions
    xY.XYZmmcoordinates of voxels (mm)spm_regions
    xY.yfiltered/whitened data, voxel-by-voxelspm_regions
    +
    +
    +
    +

    Filtering with regexp

    +
    + +

    +SP on Oct 7th 2010 +The function and dialog for selecting files in SPM - spm_select - uses +regular expression for filtering. So for example when prompted to select + an SPM.mat file, the filter field already contains 'SPM.mat$' otherwise + the default is usually '.*'. This filter function can be pretty handy, +however, the syntax of regexp is not always intuitive. Here is a short +list of regexp features commonly used. +

    + +

    +For the examples let's assume we have the following files in our directory: + +

    +
    con_0001.hdr
+con_0001.img
+T1_my_structural_image.hdr
+T1_my_structural_image.img
+T1_my_structural_image.nii
+wT1_my_structural_image.nii
    +
    + + + + + + + + + + + + + + + + + + + + + +
    Expression Meaning Example Selected Example NOT Selected
    .*
    +    		any character (.) from 0 to infinite times, in short, anythingallnone
    ^T1
    +    		all files starting with 'T1'
    T1_my_structural_image.hdr
+T1_my_structural_image.img
+T1_my_structural_image.nii
    +
    con_0001.hdr
+con_0001.img
+wT1_my_structural_image.nii
    +
    nii$
    +    		all files ending with 'nii'
    T1_my_structural_image.nii
+wT1_my_structural_image.nii
    +
    con_0001.hdr
+con_0001.img
+T1_my_structural_image.hdr
+T1_my_structural_image.img
    +
    ^T1.*nii$
    +    		all files starting (^) with 'T1' and ending ($) with 'nii' with anything (.*) in between
    T1_my_structural_image.nii
    +
    con_0001.hdr
+con_0001.img
+T1_my_structural_image.hdr
+T1_my_structural_image.img
+wT1_my_structural_image.nii
    +
    ^T1.*img$|^T1.*hdr$
    +    		all files starting with 'T1' and ending with 'img' or (|)
    +all files starting with 'T1' and ending with 'hdr'
    T1_my_structural_image.hdr
+T1_my_structural_image.img
    +
    con_0001.hdr
+con_0001.img
+T1_my_structural_image.nii
+wT1_my_structural_image.nii
    +
    ^T1.*(img|hdr)$
    +    		same as above but in a more compact form due to use of parenthesessame as abovesame as above
    +
    +
    +
    +
    + +
    +
    +
    +
    + +
    +
    +

    SPSS

    +
    + +

    + +The Statistical Package for the Social Sciences + has been around long enough to bear its weird name: Apparently the +first versions consisted of packages of punched cards which had to be +fed to the ancestors of our PCs. Some of the program's components +(especially the graphics) seem to have remained unchanged since that +era, but it does almost any statistical analysis you might think of, and + then some more. The same applies to the output of most analysis: People + have reportedly starved to death while searching for a particular +t-value. Some hints and remarks: + +

    +
      +
    • The most frequently used modules in our setting would probably be General Linear Model and Regression, although any statistician will tell you that you should first Explore your data before analysing them.
      +
      • +
    • An interesting but frequently under-used feature of the program is the possibility to Paste + your analysis settings to a syntax file, rather than just executing an +analysis by clicking OK. This way, you can re-run the same analysis +without having to go through a thousand clicks, which is especially +useful if you have lots of factors. Also, the syntax is not very +complex, so sometimes it may be easier to change your analysis settings +in the syntax file rather than via the graphical interface.
      +
      • +
    • Another advantage of syntax files is + that it may be easier to recap previous analysis based on the syntax +than on the output. This is probably why newer versions of the program +paste the syntax into the output window by default.
      +
      • +
    • I will add some course material here soon.
      +
      • +
    + +
    +
    +

    Installation

    +
    + +

    + +Usually, at least the current and one previous version of SPSS are +available on GDL. When downloading one of these, you will also receive +an authorization code on your university e-mail account. Using this, you + can licence your version directly via the internet (although this +sometimes causes problems with version 16). Licences are valid for +around one year. If you're version suddenly stops working and displays a + message about missing licences, go to GDL and check for an SPSS licence + text-file, in which new authorization codes are noted, which you can +then use to re-licence your version (just as you did when you first +installed it). Note that version 16 seems to have been adapted for +Windows Vista, particularly in terms of speed - it is terribly slow. +

    +
      +
    • note further that most of SPSS versions ar not compatible with older ones. That means you need that particular version in wich your old data have been calculated… or at least the viewer SPSS Legacy
      +
        +
      • comment by Karsten: I think this is +only the case for version 16 to earlier ones; 13 through 15 interacted +quite nicely; note that you can have several versions on your computer +at the same time.
        +
        • +
      +
      • +
    + +
    +
    +

    STATISTICA

    +
    +
    Changement du No de code licence
+----------------------------------------------------
+Pour changer ce code, allez  dans
+Help --> About Statistica --> License
+Management --> Enter Code
+
+Tapez : 
+XNVJDFHH6QZXNWLQ8W
+(nouveau code valable jusqu'au 31.10.2009)
+
+Attention !
+Ce code est valable pour la version 8 uniquement.
+Si vous possédez une version antérieure, il vaut mieux
+désinstaller et re-installer la version 8.0.
    + +
    +
    +

    Windows XP

    +
    + +
    +
    +

    Windows addons

    +
    + +

    +Some useful +

    +
    + + + + + + + + + + + + + + + +
    Name Download Description
    Folder Size http://foldersize.sourceforge.net Allows you to display the size of the content of folder in the windows Explorer
    NetDrive http://www.netdrive.net Makes your FTP servers appears as if they were just folders/disks on your PC, for easy copy-paste etc.
    TortoiseSVN http://tortoisesvn.tigris.org Integrates SVN in the right click menu of the Explorer
    Unlocker http://ccollomb.free.fr/unlocker Tell you which program is using the file(s) you want to delete, and let you force the deletion
    + +
    +
    +

    xjview_karim

    +
    + +

    + +It is a Karim-made variant of the xjview toolbox for SPM. + Although the original one already does a very good job, displaying your + results with a cursor that allows you to easily change the p-value +threshold without having to go through the open contrast box again and +again. Plus, it tells you were you are in the brain according to the Brodmann & AAL + atlases. I tweaked it so that you can now also naviguate between +contrasts, and between subjects (if your at the 2nd level). I also added + a feature that can extract betas at a voxels, in a cluster or in +sphere, from each subject of the group. It can also plot correlation +graph in a BOLD-questionnaires study. +

    + +

    +However, although I'm willing to share it, it wasn't meant for public +release: so use it if you want but be aware that it may bug (or show +stupid labels such as “averted gaze†etc. Ask me for the latest version. + Karim +

    + +
    +
    +

    XnView(img batch conversion)

    +
    + +

    + +XnView is THE picture conversion tool, free to use, that let you convert + a bunch of pictures into a very large range of pictures formats +(several 100s). +You can also resize, convert from color to black & white, & +perform several basic operations in one clic. +http://www.xnview.com/fr/index.html + +

    + +
    +
    +

    + Discussion +

    +
    +
    +
    + + , 2009/03/24 10:16 +
    +
    + +

    +Could the Windows addons be moved to Tools & Utilities? + +

    + +
    +
    +
    +
    + + + + + +
    +
    +
    +
    +
    +
    +
    + + , 2009/06/17 00:21 +
    +
    + +

    +Yes, of course! + +

    + +
    +
    +
    +
    + + + + + +
    +
    +
    +
    +
    +
    +
    + + , 2009/03/24 10:16 +
    +
    + +

    +Could xjview_karim be moved to SPM Toolboxes? + +

    + +
    +
    +
    +
    + + + + + +
    +
    +
    +
    +
    +
    +
    + + , 2009/06/17 00:21 +
    +
    + +

    +yes, of course! + +

    + +
    +
    +
    +
    + + + + + +
    +
    +
    +
    +
    +
    +
    + + , 2011/01/08 01:13 +
    +
    + +

    +Could some please updae the licences? + +

    + +
    +
    +
    +
    + + + + + +
    +
    +
    +
    + +
    +
    +
    + + + + + + + + +
    + Enter your comment (wiki syntax is allowed):
    + +
    + + + +
    + +
    +
    +
    +
    +
    + + +
    + +
     
    + + +
    + +
    +
    + Logged in as: Karim N'Diaye (ndiayek)
    +
    + references/software.txt · Last modified: 2012/12/13 11:19 by sinanaj
    +
    + + +
    +
    +
    +
    +
      +
    +
    +
    + +
    + +
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'fieldtrip' -> output FieldTrip structure +% +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-22 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin == 1 + format = 'eeglab'; +end +[format,subformat]=strtok(format, '.'); +switch lower(format) + case 'eeglab' + if exist('eeg_emptyset')==2 + EEG = eeg_emptyset; + else % if no eeglab in the path, use local version... + EEG = emptyset(); + end + [EEG.nbchan EEG.trials EEG.pnts] = size(dh.F); + [EEG.filepath EEG.filename] = fileparts(dh.file.path); + eeg.chanlocs = chanlocs(data) + + if isempty(subformat) || isequal(subformat,'data') + EEG.data = data(dh); + if exist('eeg_checkset')==2 + EEG = eeg_checkset(EEG); + else + warning('Datahandler:Convert:NoEEGLABCheckset', 'EEGLAB''s eeg_checkset function missing.') + end + end + if isempty(subformat) + varargout = {EEG}; + else + varargout = {EEG.(subformat)}; + end + return; +end + +function [EEG] = eeglab_emptyset() +EEG.data = [] ; + +EEG.setname = ''; +EEG.filename = ''; +EEG.filepath = ''; +EEG.trials = NaN; % number of epochs (or trials) in the dataset. +% If data are continuous, this number is 1. +EEG.pnts = NaN; % number of time points (or data frames) per trial (epoch). +% If data are continuous (trials=1), the total number +% of time points (frames) in the dataset +EEG.nbchan = NaN; % number of channels +EEG.srate = NaN; % data sampling rate (in Hz) +EEG.xmin = NaN; % epoch start latency|time (in sec. relative to the +% time-locking event at time 0) +EEG.xmax = NaN; % epoch end latency|time (in seconds) +EEG.times = NaN; % vector of latencies|times in seconds (one per time point) +EEG.ref = NaN; % ['common'|'averef'|integer] reference channel type or number +EEG.history = {}; % cell array of ascii pop-window commands that created +% or modified the dataset +EEG.comments = NaN; % comments about the nature of the dataset (edit this via +% menu selection Edit > About this dataset) +EEG.etc = NaN; % miscellaneous (technical or temporary) dataset information +EEG.saved = 'no'; % ['yes'|'no'] 'no' flags need to save dataset changes before exit +% +% EEG.chanlocs - structure array containing names and locations of the channels on the scalp +% EEG.urchanlocs - original (ur) dataset chanlocs structure containing all channels originally collected with these data (before channel rejection) +% EEG.chaninfo - structure containing additional channel info +% EEG.ref - type of channel reference ('common'|'averef'|+/-int] +% EEG.splinefile - location of the spline file used by headplot() to plot data scalp maps in 3-D + +function eeglab_chanlocs(dh) + +for index = 1:length( eloc ) + eloc(index).X = tmp(1); x(index) = tmp(1); + eloc(index).Y = tmp(2); y(index) = tmp(2); + eloc(index).Z = tmp(3); z(index) = tmp(3); + eloc(index).type = 'EEG'; +end; diff --git a/lena/@datahandler/data.m b/lena/@datahandler/data.m new file mode 100644 index 0000000..7392a4c --- /dev/null +++ b/lena/@datahandler/data.m @@ -0,0 +1,17 @@ +function F = data(dh) +% data (datahandler) - Display/output data +% + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-22 Creation +% +% ----------------------------- Script History --------------------------------- + +F=dh.F; \ No newline at end of file diff --git a/lena/@datahandler/datahandler.m b/lena/@datahandler/datahandler.m new file mode 100644 index 0000000..281aa51 --- /dev/null +++ b/lena/@datahandler/datahandler.m @@ -0,0 +1,86 @@ +function dh = datahandler(varargin) +% datahandler - A class to handle MEEG data +% +% dh = datahandler(varargin) +% +% KND + +% properties +% F = []; +% file = struct('path', '', 'header', []); +% dimensions = [] +% time +% channel +% trial +% marker +% class +% badchannel +% end + +% +DATA_DIMENSIONS = {'supersensors','time','trial'}; + +dh.F = []; +dh.file = struct('path',[],'header',[]); + +% Data dimensions +% DIMENSION_TYPES = {'double','nominal','logical','struct'} +dh.dimensions = struct('names',[],'size',[],'synonyms',[]); +% dh.dimensions.names = {'supersensors','time','trial'}; +dh.supersensor = []; +dh.time = []; +dh.trial = []; + +% Extra info +dh.marker = []; +dh.class = []; +dh.badchannel = []; + +if nargin==0 + + dh = class(dh, 'datahandler'); +else + v = varargin{1}; + if isa(v,'datahandler') + dh = v; + elseif ischar(v) + % if (exist(v, 'filename') || exist(v,'dir')) + dh.file.path = v; + try + dh = import(dh.file.path,varargin{2:end}); + + catch ME + rethrow(ME); + end + dh = class(dh, 'datahandler'); + elseif isnumeric(v) + dh.F = v ; + dh = class(dh, 'datahandler'); + else + error('[datahandler] Bad input argument'); + end +end + +function dh = import(filename,varargin) + +% Import data from file +[dh.file.header,dh.F,dh.time] = read_lena(filename,varargin{:}); +dh.file.path = filename; +% classes = read_lena_classes +% markers = read_lena_events +dh.badchannel = []; + +%% Sensors and supersensors +sensor_range = dh.file.header.description.sensor_range; +sensornames = {sensor_range.sensor_list.sensor.CONTENT}; +n = length(sensor_range.sensor_samples.supersensor); +supersensor = sensor_range.sensor_samples.supersensor; +dh.supersensor = struct([]); +for i=1:n + dh.supersensor(i).name = supersensor(i).sensor; + dh.supersensor(i).idx = strmatch(dh.supersensor(i).name, sensornames); + dh.supersensor(i).unit = supersensor(i).ATTRIBUTE.unit ; + dh.supersensor(i).scale= supersensor(i).ATTRIBUTE.scale; + dh.supersensor(i).bad = ismember(dh.supersensor(i).idx, dh.badchannel); +end + diff --git a/lena/@datahandler/datahandler_classdef.m b/lena/@datahandler/datahandler_classdef.m new file mode 100644 index 0000000..0383ad8 --- /dev/null +++ b/lena/@datahandler/datahandler_classdef.m @@ -0,0 +1,62 @@ +classdef datahandler + % datahandler - A class to handle MEEG data + % + % dh = datahandler(varargin) + % + % KND + + properties + F = []; + file = struct('path', '', 'header', []); + dimensions = [] + time + channels + trials + markers + classes + badchannels + end + + methods + function dh = datahandler(varargin) + if nargin>0 + v = varargin{1}; + if isa(v,'datahandler') + dh = v; + elseif ischar(v) + % if (exist(v, 'file') || exist(v,'dir')) + dh.file.path = v; + try + [dh.file.header,dh.F,dh.time] = read_lena(dh.file.path,varargin{2:end}); + catch ME + rethrow(ME); + end + elseif isnumeric(v) + dh.F = v ; + else + error('[datahandler] Bad input argument'); + end + end + %obj = obj@uint8(data); + %dh = datahandler(data); + + end + + function s = sensornames(dh) + s = [dh.file.header.description.sensor_range.sensor_list.sensor]; + s = {s.CONTENT}; + end + + function plot(td,varargin) + plot(td.Strain,td.Stress,varargin{:}) + title(['Stress/Strain plot for Sample',... + num2str(td.SampleNumber)]) + ylabel('Stress (psi)') + xlabel('Strain %') + end % plot + + + end + + +end \ No newline at end of file diff --git a/lena/@datahandler/file.m b/lena/@datahandler/file.m new file mode 100644 index 0000000..e69de29 diff --git a/lena/@datahandler/get.m b/lena/@datahandler/get.m new file mode 100644 index 0000000..b84958a --- /dev/null +++ b/lena/@datahandler/get.m @@ -0,0 +1,13 @@ +function val = get(dh, propName, options) +% GET - Get property from datahandler object + +% default output data +if nargin<2 + propName = 'data'; +end +switch lower(propName) + case {'data', 'f'} + val = dh.F; + otherwise + error([propName,' is not a datahandler property']) +end \ No newline at end of file diff --git a/lena/@datahandler/sensornames.m b/lena/@datahandler/sensornames.m new file mode 100644 index 0000000..79010c7 --- /dev/null +++ b/lena/@datahandler/sensornames.m @@ -0,0 +1,22 @@ +%SENSORNAMES - Retrieves the name of the sensors in the data +% [] = sensornames(dh) +% +% Example +% >> sensornames +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-22 Creation +% +% ----------------------------- Script History --------------------------------- +function s = sensornames(dh) +s = {dh.supersensor.name}; +end \ No newline at end of file diff --git a/lena/@datahandler/set.m b/lena/@datahandler/set.m new file mode 100644 index 0000000..7768d9f --- /dev/null +++ b/lena/@datahandler/set.m @@ -0,0 +1,9 @@ +function dh = set(dh,varargin) +% SET Set properties and return the updated object +propertyArgIn = varargin; +while length(propertyArgIn) >= 2, + prop = propertyArgIn{1}; + val = propertyArgIn{2}; + propertyArgIn = propertyArgIn(3:end); + dh = set(dh, prop, val); +end \ No newline at end of file diff --git a/lena/@lena/lena.m b/lena/@lena/lena.m new file mode 100644 index 0000000..d29b297 --- /dev/null +++ b/lena/@lena/lena.m @@ -0,0 +1,48 @@ +function obj = lena(varargin) +% LENA - Constructor of the LENA data class +% +% obj = lena(varargin) +% +% KND +if nargin==0 + obj.header = []; + obj.F = []; + obj.Time = []; + obj.filename = ''; + obj.events = []; + obj.trialclass = []; + obj.badchannels = []; + + obj = class(obj,'lena'); +else + v = varargin{1}; + if isa(v,'lena') + obj = v; + elseif ischar(v) + % if (exist(v, 'file') || exist(v,'dir')) + obj.filename = v; + try + [obj.header,obj.F,obj.Time] = read_lena(obj.filename,varargin{2:end}); + catch ME + rethrow(ME); + end + obj = class(obj,'lena'); + elseif isnumeric(v) + obj.F = v ; + obj = class(obj,'lena'); + else + error('[LENA] Bad input argument'); + end + +end + +function [names] = sensornames +names = 1; + +function [pos] = sensorpositions + + +function [F] = data(o) +F = o.F; + + diff --git a/lena/create_events.m b/lena/create_events.m new file mode 100644 index 0000000..a2a3c00 --- /dev/null +++ b/lena/create_events.m @@ -0,0 +1,16 @@ +function events = create_events(onsets,names,trials,durations,offsets) +% create_events() - Create EEGLAB events +% Usage: +% >> events = create_events(onsets,names,trials,durations,offsets) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2010 +% +% See also: read_ptx + +events = struct('type',[],'position',[],'latency',[],'urevent',[0]); +n=length(onsets); +events = repmat(events,n,1); +for i=1:n + events(i) = setfield(events(i),'latency', onsets(i)); + events(i) = setfield(events(i),'type', names{i}); +end \ No newline at end of file diff --git a/lena/ctf_folder.m b/lena/ctf_folder.m new file mode 100644 index 0000000..33c3ee9 --- /dev/null +++ b/lena/ctf_folder.m @@ -0,0 +1,106 @@ +function [ctf] = ctf_folder(folder,ctf); + +% ctf_folder - get and check CTF .ds folder name +% +% [ctf] = ctf_folder( [folder], [ctf] ); +% +% folder: The .ds directory of the dataset. It should be a complete path +% or given relative to the current working directory (given by pwd). The +% returned value will ensure the complete path is identified. If this +% argument is empty or not given, a graphical prompt for the folder +% appears. +% +% eg, +% ctf = ctf_folder; +% +% ctf.folder is returned (as a complete path). +% +% <>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> % +% < > % +% < DISCLAIMER: > % +% < > % +% < THIS PROGRAM IS INTENDED FOR RESEARCH PURPOSES ONLY. > % +% < THIS PROGRAM IS IN NO WAY INTENDED FOR CLINICAL OR > % +% < OFFICIAL USE. > % +% < > % +% <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<> % +% + + +% $Revision: 1.1 $ $Date: 2009-01-30 03:49:27 $ + +% Copyright (C) 2004 Darren L. Weber +% +% This program is free software; you can redistribute it and/or +% modify it under the terms of the GNU General Public License +% as published by the Free Software Foundation; either version 2 +% of the License, or (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + +% Modified: 01/2004, Darren.Weber_at_radiology.ucsf.edu +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + +if ~exist('folder','var'), folder = []; end +if ~exist('ctf','var'), ctf = []; end + +if isempty(folder), + if isfield(ctf,'folder'), + folder = ctf.folder; + else + folder = []; + end +end + +if exist(folder) ~= 7, + fprintf('...folder inputs are invalid\n'); + folder = getfolder; +end + +ctf.folder = folder; + +% ensure we get the folder path +current_dir = pwd; +cd(ctf.folder); +cd .. +folderPath = pwd; +cd(current_dir); + +% check whether the folder path is in the folder already +[path,file] = fileparts(ctf.folder); + +% if findstr(folderPath,ctf.folder), + % OK the path is already in the folder +% else +if isempty(path) + % Add the folderPath + ctf.folder = fullfile(folderPath,ctf.folder); +end + + +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function folder = getfolder, + +% This does not work on linux systems (only windows) +folder = uigetdir(pwd,'locate CTF .ds folder'); + +if ~folder, + % try to get it this way + [filename, folder, filterindex] = uigetfile('*.res4', 'Pick a .res4 file'); + if ~folder, + error('invalid folder'); + end +end + +return diff --git a/lena/ctf_read_classfile.m b/lena/ctf_read_classfile.m new file mode 100644 index 0000000..89261d1 --- /dev/null +++ b/lena/ctf_read_classfile.m @@ -0,0 +1,254 @@ +function class = ctf_read_classfile(ctf,clsFile); + +% class = ctf_read_classfile(ctf,clsFile); +% +% This function reads the ClassFile.cls created by CTF preprocessing +% software. +% +% ctf - a struct returned by ctf_read, it contains ctf.folder, which is a +% .ds path where a ClassFile.cls can be read; eg: +% ctf = ctf_read +% ctf.class = ctf_read_classfile(ctf) +% +% clsFile - this can be used to override the default behavior of reading +% *.ds/ClassFile.cls, it should be a complete path to a .cls file; eg: +% ctf.class = ctf_read_classfile([],clsFile) +% ctf.class = ctf_read_classfile([],'//ClassFile.cls') +% +% It returns a class struct, eg: +% +% class.path: '/data/dnl3/HighN_cuebase/allTrialData/CJ_HiN_alltrials.ds' +% class.number: 4 +% class.data: {[1x1 struct] [1x1 struct] [1x1 struct] [1x1 struct]} +% +% where class.data is a 1xN struct array, eg: +% +% >> class.data(1) +% +% ans = +% +% classgroupid: 3 +% name: 'EYEBLINKa' +% comment: [1x63 char] +% color: '' +% editable: 'Yes' +% classid: 2 +% Ntrials: 67 +% trials: [1x67 double] +% +% To get all the class names, +% [classNames{1:class.number}] = deal(class.data.name); +% classNames = {ctf.class.data(:).name}; +% +% To scan all the class names, use strmatch, eg: +% strmatch('BAD',{ctf.class.data(:).name}); +% +% Note that the class.data(n).trials contains numbers beginning with 1, +% whereas the CTF datafile has values beginning with 0 (this is based on +% differences in array indexing between c/c++ and matlab). +% +% <>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +% < > +% < DISCLAIMER: > +% < > +% < THIS PROGRAM IS INTENDED FOR RESEARCH PURPOSES ONLY. > +% < THIS PROGRAM IS IN NO WAY INTENDED FOR CLINICAL OR > +% < OFFICIAL USE. > +% < > +% <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<> +% + + +% $Revision: 1.1 $ $Date: 2009-01-30 03:49:27 $ + +% Copyright (C) 2005 Darren L. Weber +% +% This program is free software; you can redistribute it and/or +% modify it under the terms of the GNU General Public License +% as published by the Free Software Foundation; either version 2 +% of the License, or (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + +% Created: 12/2005, Darren.Weber_at_radiology.ucsf.edu +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + +if ~exist('clsFile','var'), clsFile = ''; end +if isempty(clsFile), clsFile = ''; end +if clsFile, + fid = fopen(clsFile,'r'); +else + fid = -1; +end + +if fid < 0, + % only use the ctf.folder if the above has failed + if isfield(ctf,'folder'), + if isempty(ctf.folder), + error('ctf.folder is empty and no clsFile specified'); + else + clsFile = fullfile(ctf.folder,'ClassFile.cls'); + fid = fopen(clsFile,'r'); + end + end +end + +if fid < 0, + error('failed to open any ClassFile.cls'); +end + + +% Read the dataset path from the classfile +class.path = []; +while isempty(class.path), + curLine = fgetl(fid); + if strcmp(curLine,'PATH OF DATASET:'), + curLine = fgetl(fid); + class.path = curLine; + end +end +frewind(fid); + +% Find the number of classes to read +class.number = []; +while isempty(class.number), + curLine = fgetl(fid); + if strcmp(curLine,'NUMBER OF CLASSES:'), + curLine = fgetl(fid); + class.number = str2num(curLine); + end +end +frewind(fid) + +if isempty(class.number), + warning('ClassFile.cls is empty of classes'); + fclose(fid); + return +end + + +% read the classes, assuming this format: +% +% CLASSGROUPID: +% 3 +% NAME: +% EYEBLINK +% COMMENT: +% Ampl(MEG)=0T; Deriv(MEG)=0T/s; Ampl(EEG)=80uV; Deriv(EEG)=0V/s. +% COLOR: +% +% EDITABLE: +% Yes +% CLASSID: +% 2 +% NUMBER OF TRIALS: +% 3 +% LIST OF TRIALS: +% TRIAL NUMBER +% +527 +% +612 +% +624 + +% initialize a class.data array of structs +class.data(1:class.number) = struct(... + 'classgroupid', '',... + 'name', '',... + 'comment', '',... + 'color', '',... + 'editable', '',... + 'classid', [],... + 'Ntrials', [],... + 'trials', []); + +classCurrent = 0; +while classCurrent < class.number, + + curLine = fgetl(fid); + if strcmp(curLine,'CLASSGROUPID:'); + % update current class no. here only + classCurrent = classCurrent + 1; + curLine = fgetl(fid); + curLine = str2num(curLine); + class.data(classCurrent).classgroupid = curLine; + curLine = fgetl(fid); + end + + if strcmp(curLine,'NAME:'); + curLine = fgetl(fid); + class.data(classCurrent).name = curLine; + curLine = fgetl(fid); + end + + if strcmp(curLine,'COMMENT:'); + curLine = fgetl(fid); + class.data(classCurrent).comment = curLine; + curLine = fgetl(fid); + end + + if strcmp(curLine,'COLOR:'); + curLine = fgetl(fid); + class.data(classCurrent).color = curLine; + curLine = fgetl(fid); + end + + if strcmp(curLine,'EDITABLE:'); + curLine = fgetl(fid); + class.data(classCurrent).editable = curLine; + curLine = fgetl(fid); + end + + if strcmp(curLine,'CLASSID:'); + curLine = fgetl(fid); + curLine = str2num(curLine); + class.data(classCurrent).classid = curLine; + if curLine ~= classCurrent, + error('curLine ~= classCurrent'); + end + curLine = fgetl(fid); + end + + if strcmp(curLine,'NUMBER OF TRIALS:'); + curLine = fgetl(fid); + Ntrials = str2num(curLine); + class.data(classCurrent).Ntrials = Ntrials; + + % read past "LIST OF TRIALS:" + curLine = fgetl(fid); + if strcmp(curLine,'LIST OF TRIALS:'), + % that's good, we expect it + else + warning('Did not find ''LIST OF TRIALS:'' where expected') + end + + % read past "TRIAL NUMBER" + curLine = fgetl(fid); + if strcmp(curLine,'TRIAL NUMBER'), + % that's good, we expect it + else + warning('Did not find ''TRIAL NUMBER'' where expected') + end + + class.data(classCurrent).trials = []; + if class.data(classCurrent).Ntrials > 0, + class.data(classCurrent).trials = zeros(1,Ntrials); + for n = 1:Ntrials, + curLine = fgetl(fid); + % add 1 to trial numbers for matlab compatibility + class.data(classCurrent).trials(n) = str2num(curLine) + 1; + end + end + + end + +end + +return diff --git a/lena/ctf_read_markerfile.m b/lena/ctf_read_markerfile.m new file mode 100644 index 0000000..df92823 --- /dev/null +++ b/lena/ctf_read_markerfile.m @@ -0,0 +1,188 @@ +function [markers] = ctf_read_markerfile(ctf,mrkFile); + +% ctf_read_markerfile - load data from MarkerFile.mrk in .ds folder +% +% [markers] = ctf_read_markerfile([ctf],[mrkFile]); +% +% ctf.folder is a .ds path, if it is missing or invalid a gui prompts +% for the folder. ctf is a struct generated by this and other +% ctf_read_*.m functions. +% +% mrkFile - this can be used to override the default behavior of reading +% *.ds/MarkerFile.cls, it should be a complete path to a .mrk file; eg: +% ctf = ctf_read_markerfile([],mrkFile) +% ctf = ctf_read_markerfile([],'//MarkerFile.mrk') +% +% Returns the 'markers' struct: +% +% markers.number_markers - scalar +% markers.number_samples - column array, number_markers x 1 +% markers.marker_names - cell array of strings, number_markers x 1 +% markers.trial_times - cell array of matrices, number_markers x 1 each +% containing number_samples x 2 matrix, where column 1 indicates the trial +% number containing the marker and column 2 indicates the offset (in sec). +% +% <>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> +% < > +% < DISCLAIMER: > +% < > +% < THIS PROGRAM IS INTENDED FOR RESEARCH PURPOSES ONLY. > +% < THIS PROGRAM IS IN NO WAY INTENDED FOR CLINICAL OR > +% < OFFICIAL USE. > +% < > +% <<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<> +% + +% $Revision: 1.1 $ $Date: 2009-01-30 03:49:27 $ + +% Copyright (C) 2004 Darren L. Weber +% +% This program is free software; you can redistribute it and/or +% modify it under the terms of the GNU General Public License +% as published by the Free Software Foundation; either version 2 +% of the License, or (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + +% Modified: 12/2003, Darren.Weber_at_radiology.ucsf.edu +% - modified from NIH code readmarkerfile.m +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +ver = '$Revision: 1.1 $'; +fprintf('\nCTF_READ_MARKERFILE [v %s]\n',ver(11:15)); tic; + + + +if ~exist('mrkFile','var'), mrkFile = ''; end +if isempty(mrkFile), mrkFile = ''; end +if isstruct(mrkFile), mrkFile = ''; end +if mrkFile, + fid = fopen(mrkFile,'r'); +else + fid = -1; +end + +if fid < 0, + + % check the ctf.folder + if ~exist('ctf','var'), + ctf = ctf_folder; + else + ctf = ctf_folder([],ctf); + end + %fprintf('...reading from %s\n',ctf.folder); + + % use the ctf.folder to find .mrk file + if isfield(ctf,'folder'), + if isempty(ctf.folder), + error('ctf.folder is empty and no mrkFile specified'); + else + % check for a marker file + mrkFile = findmrkfile( ctf.folder ); + if exist(mrkFile) == 2, + fid = fopen(mrkFile,'r'); + else, + warning('...MarkerFile.mrk does not exist in this .ds folder.'); + ctf.markers = []; + return + end + end + else + error('ctf.folder is not a field of the ctf struct'); + end +end + + + + +% read the marker file, delimited by carriage returns. This new array is +% used below to extract relevant information +fprintf('...reading marker file:\n...%s\n', mrkFile); +fprintf('...reading file text, using ''\\n'' delimiter\n'); +mrkFileText = textread(mrkFile,'%s','delimiter','\n'); + +% extract the number of markers +number_markers_index = strmatch('NUMBER OF MARKERS:',mrkFileText,'exact'); +number_markers = str2num(mrkFileText{number_markers_index + 1}); +fprintf('...found %d marker types:\n',number_markers); + +% extract marker names (this can be an array, if number_markers > 1) +marker_names_index = strmatch('NAME:',mrkFileText,'exact'); +marker_names = mrkFileText(marker_names_index + 1); +for m = 1:length(marker_names), + fprintf(' %40s\n',marker_names{m}); +end + +% replace any '-' with '_' symbols in the marker names +marker_names = strrep(marker_names,'-','_'); +fprintf('...replaced any - with _ symbol in marker names\n'); + +% extract number of marker samples +% (this can be an array, if number_markers > 1) +number_samples_index = strmatch('NUMBER OF SAMPLES:',mrkFileText,'exact'); +number_samples = str2num(char(mrkFileText(number_samples_index + 1))); + +% check that all the marker samples are defined +if ~all(number_samples), + disp('One of the markers has no samples and was ignored.'); +end + + +% extract marker trial number and time (sec), eg, find & read: +% LIST OF SAMPLES: +% TRIAL NUMBER TIME FROM SYNC POINT (in seconds) +% +0 +0 +% +1 +0 +% +2 +0 + +fprintf('...reading trial numbers and offset time (sec)\n'); + +HEADER_LINES = 2; +trial = strmatch('LIST OF SAMPLES:',mrkFileText,'exact') + HEADER_LINES; + +for i = find(number_samples)' + % extract the lines of the samples, where each line contains a trial + % number in the first column and a time offset (sec) in the 2nd column + sample_text_rows = mrkFileText( trial(i):[trial(i) + number_samples(i)] ); + trials{i} = str2num(char(sample_text_rows)); + % add 1 to the trial numbers (which start at 0 for CTF software) + trials{i}(:,1) = trials{i}(:,1) + 1; +end +fprintf('...added 1 to trial numbers for matlab compatibility\n'); + +% allocate marker information into the marker stucture +markers = struct(... + 'file',mrkFile,... + 'number_markers',number_markers,... + 'number_samples',number_samples,... + 'marker_names',marker_names,... + 'trial_times',trials'); + +t = toc; fprintf('...done (%6.2f sec)\n\n',t); + +return + + + +% ------------------------------------------------------- +% find file name if truncated or with uppercase extension +% added by Arnaud Delorme, June 15, 2004 +function mrkname = findmrkfile( folder ) + mrkname = dir([ folder filesep '*.mrk' ]); + if isempty(mrkname) + mrkname = dir([ folder filesep '*.MRK' ]); + end; + if isempty(mrkname) + fprintf('...no file with extension .mrk or .MRK in .ds folder\n'); + mrkname = []; + else + mrkname = [ folder filesep mrkname.name ]; + end; +return diff --git a/lena/extractBINblocksRevised4SensorsBis.m b/lena/extractBINblocksRevised4SensorsBis.m new file mode 100644 index 0000000..497c8ac --- /dev/null +++ b/lena/extractBINblocksRevised4SensorsBis.m @@ -0,0 +1,427 @@ +function echantillons = extractBINblocks(fid,dim_to_read,dim_names,level,data_type,data_size) +% function echantillons = extractBINblocks(fid,mat,data_type,data_size) +% +% Function to read only parts of a bin file ( cf LENA data format ) +% +% Inputs : +% - fid ( integer ) : fid of the bin file +% - mat ( double array ) : matrix of samples to read. Size must be N x 2, +% ie first column for samples to read, second for samples to skip +% - data_type ( string ) : data type and size ( example : int16 ) +% - data_size ( integer ) : data format size +%dim +% Ouputs : +% - echantillons ( cells ) : read datas stored in cells + +size_dim=length(dim_to_read); +trial_dim=[]; +frequency_dim=[]; +sensor_dim=[]; +time_dim=[]; + +first_pos_trial=0; +first_pos_frequency=0; +first_pos_sensor=0; +first_pos_time=0; + +[trial_dim, trial_level,frequency_dim, frequency_level, sensor_dim, sensor_level, time_dim, time_level ]=GetDimensionsValues(dim_to_read, dim_names, level); + +if ~isempty(trial_dim) + trial_dim=cell2mat(trial_dim); + first_pos_trial=Get_First_Pos_Trial(trial_dim, frequency_level, sensor_level,time_level); +end +if ~isempty(sensor_dim) + sensor_dim=cell2mat(sensor_dim); + first_pos_sensor=Get_First_Pos_Sensor(sensor_dim, time_level); +end +if ~isempty(frequency_dim) + if isempty(sensor_dim) + sensor_dim=1; + end + frequency_dim=cell2mat(frequency_dim); + [first_pos_frequency, first_pos_sensor]=Get_First_Pos_Frequency_Sensor(frequency_dim,sensor_dim,frequency_level,sensor_level,time_level, dim_names); +end +if ~isempty(time_dim) + time_dim=cell2mat(time_dim); + first_pos_time=time_dim(1);%-1; +end +first_pos=(first_pos_time+first_pos_sensor+first_pos_frequency+first_pos_trial); +fseek(fid,data_size*first_pos,'bof'); +if ~isempty(trial_dim) + first_trial=trial_dim(1); + last_trial=trial_dim(end); +else + first_trial=1; + last_trial=1; +end +if ~isempty(frequency_dim) + first_frequency=frequency_dim(1); + last_frequency=frequency_dim(end); +else + first_frequency=1; + last_frequency=1; +end +if ~isempty(sensor_dim) + first_sensor=sensor_dim(1); + last_sensor=sensor_dim(end); +else + first_sensor=1; + last_sensor=1; +end +if ~isempty(time_dim) + first_time=time_dim(1); + last_time=time_dim(end); +else + first_time=1; + last_time=1; +end +if exist('time_level') && ~ isempty(time_dim) && (time_level-time_dim(end))>0 + remainder_time=time_level-time_dim(end)-1; +else + remainder_time=0; +end +k=1; +echantillons=[]; + +%% Nouvelle tentative +if (isempty(trial_dim) && isempty(trial_level)) + first_pos_trial=0; + if ~isempty(frequency_level) & ~isempty(sensor_level) & ~isempty(time_level) + [rank_sensor, rank_frequency]=getRankSensorFrequency(dim_names); + if rank_sensor > rank_frequency + [k, echantillon]= Process_Frequency_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_sensor,frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level); % frequence/temps + echantillons= [echantillons echantillon]; + else + [k, echantillon]= Process_Sensor_Frequency(fid,data_size, data_type,first_pos_trial, first_pos_frequency, frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level); % frequence/temps + echantillons= [echantillons echantillon]; + end + else + if ~isempty(sensor_level) & ~isempty(time_level) + first_pos_frequency=0;%1; + [k, echantillon]= Process_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency,sensor_dim, time_dim,sensor_level,time_level,k); + echantillons= [echantillons echantillon]; + else + if ~isempty(frequency_level) & ~isempty(time_level) + [k, echantillon]= Process_Frequency(fid,data_size, data_type,first_pos_trial, frequency_dim,time_dim, k,frequency_level, time_level); % frequence/temps + echantillons= [echantillons echantillon]; + else + if ~isempty(sensor_level) & isempty(frequency_level) & isempty(time_level) + [k, echantillon]= Process_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency,sensor_dim, time_dim,sensor_level,time_level,k); + echantillons= [echantillons echantillon]; + else + if isempty(sensor_level) & ~isempty(frequency_level) & isempty(time_level) + [k, echantillon]= Process_Frequency(fid,data_size, data_type,first_pos_trial, frequency_dim,time_dim, k,frequency_level, time_level); % frequence/temps + echantillons= [echantillons echantillon]; + else + if isempty(sensor_level) & isempty(frequency_level) & ~isempty(time_level) + fseek(fid,data_size*first_pos,'bof'); + echantillons{k}= fread(fid,length(time_dim),data_type); + else + fseek(fid,0,'bof'); + echantillons{k}= fread(fid,1,data_type); + end + end + end + end + end + end +else + if ~isempty(trial_dim) + limit_trial=length(trial_dim); + else + if ~isempty(trial_level) + limit_trial=trial_level; + end + end + for i_dim_trial=1:limit_trial + if ~isempty(frequency_level) & ~isempty(sensor_level) & ~isempty(time_level) + first_pos_trial=(trial_dim(i_dim_trial)-1)*(frequency_level*sensor_level*time_level); + [rank_sensor, rank_frequency]=getRankSensorFrequency(dim_names); + if rank_sensor > rank_frequency + [k, echantillon]= Process_Frequency_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_sensor,frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level); % frequence/temps + echantillons= [echantillons echantillon]; + else + [k, echantillon]= Process_Sensor_Frequency(fid,data_size, data_type,first_pos_trial, first_pos_frequency, frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level); % frequence/temps + echantillons= [echantillons echantillon]; + end + else + if ~isempty(sensor_level) & ~isempty(time_level) + first_pos_trial=(trial_dim(i_dim_trial)-1)*(sensor_level*time_level); + first_pos_frequency=0; + [k, echantillon]= Process_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency,sensor_dim, time_dim,sensor_level,time_level,k); + echantillons= [echantillons echantillon]; + else + if ~isempty(frequency_level) & ~isempty(time_level) + first_pos_trial=(trial_dim(i_dim_trial)-1)*(frequency_level*time_level); + [k, echantillons]= Process_Frequency(fid,data_size, data_type,first_pos_trial, frequency_dim,time_dim, k,frequency_level, time_level); % frequence/temps + else + if ~isempty(sensor_level) & isempty(frequency_level) & isempty(time_level) + [k, echantillons]= Process_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency,sensor_dim, time_dim,sensor_level,time_level,k); + end + end + end + end + end +end +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [trial_dim, trial_level,frequency_dim, frequency_level, sensor_dim, sensor_level, time_dim, time_level ]=GetDimensionsValues(dim_to_read, dim_names, level) + +trial_dim=[]; +frequency_dim=[]; +sensor_dim=[]; +time_dim=[]; + +trial_level=[]; +frequency_level=[]; +sensor_level=[]; +time_level=[]; + +size= length(dim_to_read); +if size==1 + switch dim_names + case 'datablock_range' + trial_dim=dim_to_read; trial_level=level; + case 'frequency_range' + frequency_dim=dim_to_read; frequency_level=level; + case 'sensor_range' + sensor_dim=dim_to_read; sensor_level=level; + case 'time_range' + time_dim=dim_to_read; time_level=level; + end +else + for i=1:length(dim_to_read) + switch dim_names{i} + case 'datablock_range' + trial_dim=dim_to_read(i); trial_level=level(i); + case 'frequency_range' + frequency_dim=dim_to_read(i); frequency_level=level(i); + case 'sensor_range' + sensor_dim=dim_to_read(i); sensor_level=level(i); + case 'time_range' + time_dim=dim_to_read(i); time_level=level(i); + end + end +end +if iscell (dim_names) + for i=1:length(level) + switch dim_names{i} + case 'datablock_range' + if isempty(trial_dim) & isempty(trial_level) + trial_dim=num2cell(level(i)); trial_level=level(i); + end + case 'frequency_range' + if isempty(frequency_dim) & isempty(frequency_level) + frequency_dim=num2cell(level(i)); frequency_level=level(i); + end + case 'sensor_range' + if isempty(sensor_dim) & isempty(sensor_level) + sensor_dim=num2cell(level(i)); sensor_level=level(i); + end + case 'time_range' + if isempty(time_dim) & isempty(time_level) + time_dim=num2cell(level(i)-1); time_level=level(i); + end + end + end +else + if ~ isempty( dim_names) + switch dim_names + case 'datablock_range' + if isempty(trial_dim) & isempty(trial_level) + trial_dim=num2cell(level); trial_level=level; + end + case 'frequency_range' + if isempty(frequency_dim) & isempty(frequency_level) + frequency_dim=num2cell(level); frequency_level=level; + end + case 'sensor_range' + if isempty(sensor_dim) & isempty(sensor_level) + sensor_dim=num2cell(level); sensor_level=level; + end + case 'time_range' + if isempty(time_dim) & isempty(time_level) + time_dim=num2cell(level-1); time_level=level; + end + end + end +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [k, echantillons]= Process_Frequency_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency, frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level) +% frequence/temps +echantillons=[]; +if ~isempty(frequency_dim) + limit_frequency=length(frequency_dim); +else limit_frequency=frequency_level; +end +for i_dim_frequency=1:limit_frequency + first_pos_frequency=(frequency_dim(i_dim_frequency)-1)*(sensor_level*time_level); + [k, echantillon]= Process_Sensor(fid,data_size, data_type,first_pos_trial,first_pos_frequency, sensor_dim, time_dim,sensor_level,time_level,k); + echantillons=[echantillons echantillon]; +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [k, echantillons]= Process_Sensor_Frequency(fid,data_size, data_type,first_pos_trial, first_pos_frequency, frequency_dim,sensor_dim, time_dim, k,frequency_level, time_level, sensor_level); % frequence/temps +echantillons=[]; +if ~isempty(sensor_dim) + limit_sensor=length(sensor_dim); +else limit_sensor=sensor_level; +end +for i_dim_sensor=1:limit_sensor + + first_pos_sensor=(sensor_dim(i_dim_sensor)-1)*(frequency_level*time_level); + [k, echantillon]= Process_Frequency(fid,data_size, data_type,first_pos_trial,first_pos_sensor,frequency_dim,time_dim, k,frequency_level, time_level); + echantillons=[echantillons echantillon]; +end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [k, echantillon]= Process_Frequency(fid,data_size, data_type,first_pos_trial, first_pos_sensor, frequency_dim,time_dim, k,frequency_level, time_level) +% function Process_Frequency(first_pos_trial) +if ( isempty(frequency_dim) & isempty(frequency_level) & isempty(time_dim) & isempty(time_level) ) + fseek(fid,0,'bof'); + echantillons{k}= fread(fid,1,data_type); + %k=1; + %echantillons=[]; + return; +end +if (~ isempty(time_dim) & ~isempty(time_level)) + first_pos_time=time_dim(1);%-1; + if time_level==time_dim(end) + remainder_time=0; + else + remainder_time=time_level-time_dim(end)-1; + end + dim_time=length(time_dim); +else + first_pos_time=0; + remainder_time=0; + time_level=1; + dim_time=1; +end +if ~isempty(frequency_dim) + limit_frequency=length(frequency_dim); +else + limit_frequency=frequency_level; +end +k1=1; +for i_dim_frequency=1:limit_frequency + first_pos=first_pos_trial+first_pos_sensor+ (frequency_dim(i_dim_frequency)-1)*(time_level) + first_pos_time; + %Lecture + fseek(fid,data_size*first_pos,'bof'); + echantillon{k1}= fread(fid,dim_time,data_type); + k1=k1+1; + k=k+1; +end +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%function Process_Sensor(first_pos_trial, first_pos_frequency) +function [k, echantillons]= Process_Sensor(fid,data_size, data_type,first_pos_trial, first_pos_frequency,sensor_dim, time_dim,sensor_level,time_level,k) +if ( isempty(sensor_dim) & isempty(sensor_level) & isempty(time_dim) & isempty(time_level) ) + fseek(fid,0,'bof'); + echantillons{k}= fread(fid,1,data_type); + return; +end +if (~ isempty(time_dim) & ~isempty(time_level)) + first_pos_time=time_dim(1); + if time_level==time_dim(end)+1; + remainder_time=0; + else + remainder_time=time_level-time_dim(end)-1; + end + dim_time=length(time_dim); +else + first_pos_time=0; + remainder_time=0; + time_level=1; + dim_time=1; +end +if ~isempty(sensor_dim) + limit_sensor=length(sensor_dim); +else + limit_sensor=sensor_level; +end +k1=1; +for i_dim_sensor=1:limit_sensor + first_pos_sensor=(sensor_dim(i_dim_sensor)-1)*(time_level); + first_pos=first_pos_trial+first_pos_frequency+ first_pos_sensor + first_pos_time; + %Lecture + fseek(fid,data_size*first_pos,'bof'); + echantillons{k1}= fread(fid,dim_time,data_type); + k1=k1+1; + k=k+1; +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function first_pos_trial=Get_First_Pos_Trial(trial_dim, frequency_level, sensor_level,time_level) +if isempty(frequency_level) + frequency_level=1; +end +if isempty(sensor_level) + sensor_level=1; +end +if isempty(time_level) + time_level=1; +end + +first_pos_trial=(trial_dim(1)-1)*(frequency_level*sensor_level*time_level); + +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [rank_sensor, rank_frequency]=getRankSensorFrequency(dim_names) +rank_sensor=0; +rank_frequency=0; +for i=1:length(dim_names) + if strcmp (dim_names{i}, 'frequency_range') + rank_frequency=i; + else + if strcmp (dim_names{i}, 'sensor_range') + rank_sensor=i; + end + end +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [first_pos_frequency,first_pos_sensor] =Get_First_Pos_Frequency_Sensor(frequency_dim, sensor_dim, frequency_level,sensor_level,time_level, dim_names) +[rank_sensor, rank_frequency]=getRankSensorFrequency(dim_names); +if isempty(time_level) + time_level=1; +end +if isempty(sensor_level) + sensor_level=1; +end +if rank_frequency ~= 0 & rank_frequency > rank_sensor & rank_sensor ~= 0 + % rajouter le cas ou frequency est apres sensors + first_pos_frequency=(frequency_dim(1)-1)*(time_level); + first_pos_sensor=(sensor_dim(1)-1)*(frequency_level*time_level); +else if rank_frequency ~= 0 & rank_sensor > rank_frequency & rank_sensor ~= 0 + first_pos_sensor=(sensor_dim(1)-1)*(time_level); + first_pos_frequency=(frequency_dim(1)-1)*(sensor_level*time_level); + else if rank_frequency == 0 + first_pos_sensor=(sensor_dim(1)-1)*(time_level); + else if rank_sensor == 0 + first_pos_frequency=(frequency_dim(1)-1)*(time_level); + end + end + end +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function first_pos_sensor=Get_First_Pos_Sensor(sensor_dim, time_level) +if isempty(time_level) + time_level=1; +end +first_pos_sensor=(sensor_dim(1)-1)*(time_level); +return diff --git a/lena/lena2brainstorm.m b/lena/lena2brainstorm.m new file mode 100644 index 0000000..ba80402 --- /dev/null +++ b/lena/lena2brainstorm.m @@ -0,0 +1,48 @@ +function [Channel,Time,F,h] = lena2brainstorm(lenafile,varargin) +%LENA2BRAINSTORM - Reads LENA file into brainstorm data format +% [Channel,Time,F,header] = lena2brainstorm(lenafile) +% +% Example +% >> lena2brainstorm +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-02 Creation +% +% ----------------------------- Script History --------------------------------- + +%% Reads .lena file/folder +warning off +if nargout < 3 + % No need to read the full data info + [h] = read_lena(lenafile,varargin{:}); +else + [h,F] = read_lena(lenafile,varargin{:}); +end +warning on +%% Brainstorm's Channel structure +Channel = []; +if nargout < 2 + return +end +%% Time array +Time = [0:(str2num(h.description.time_range.time_samples)-1)]./... + str2num(h.description.time_range.sample_rate) - ... + str2num(h.description.time_range.pre_trigger); +if nargout < 3 + return +end +%% Process data into F +canonical_dimensions = {'sensor_range' 'time_range' 'datablock_range' }; +data_dimensions = fieldnames(h.description); +[ign,candim] = intersect(canonical_dimensions(:), data_dimensions); +icandim(candim)=1:numel(candim); +F = permute(F, icandim); diff --git a/lena/ptx2events.m b/lena/ptx2events.m new file mode 100644 index 0000000..7b1449d --- /dev/null +++ b/lena/ptx2events.m @@ -0,0 +1,27 @@ +function [t,m] = ptx2events(input) +%PTS2EVENTS - One line description goes here. +% [] = ptx2events(input) +% +% Example +% >> ptx2events +% +% See also: eeglab + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-24 Creation +% +% ----------------------------- Script History --------------------------------- + + +[onsets,names,trials,durations,offsets] = read_ptx(input); +e = create_events(onsets,names,trials,durations,offsets); + + + diff --git a/lena/readLENA.m b/lena/readLENA.m new file mode 100644 index 0000000..d997be3 --- /dev/null +++ b/lena/readLENA.m @@ -0,0 +1,150 @@ +% read_lena() - read LENA header & data +% +% Usage: +% >> [header data lena_tree] = read_lena(lenafile) +% +% Required Input: +% lenafile = LENA header file +% Available options: +% device -> 'ALL' (default)|'MEG'|'EEG'|'EEG+MEG'|'DC' +% trials -> Trials to import as list of indices (default: [] = 'all') +% timewindow -> Default: [] = 'all' +% +% Outputs: +% header = header info (from reading the xml heder file) +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READLENA, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [header data lena_tree] = readLENA(lenafile,varargin) + +if nargin < 1 + help(mfilename); + return; +end; +binary_extensions = {'.bin' '.data'}; + +lena_tree = xmltree(lenafile); +warning('off','MATLAB:warn_r14_stucture_assignment') +header = convert(lena_tree); +warning('on','MATLAB:warn_r14_stucture_assignment') + +if nargout<2 + return +end + +if nargin==2 + data_filename = varargin{1}; + if isfield(header, 'data_filename') + warning('Overloading binary data filname from header (%s) to: %s', header.data_filename, data_filename); + end + header.data_filename = data_filename; +end + + +if ~isfield(header, 'data_filename') + header.data_filename =''; + for i=1:length(binary_extensions) + data_filename = [lenafile(1:end-5) binary_extensions{i} ]; + if exist(data_filename, 'file') + header.data_filename = data_filename; + warning('Assumed binary data file not specified in header... Found possible match: %s', data_filename); + break; + end + end +end +if isempty(header.data_filename) + error('No datafile') +end + +fprintf('Importing data from binary file...\n') + +if strcmp(header.data_format,'LittleEndian') + data_fid = fopen(header.data_filename,'r','l'); +elseif strcmp(header.data_format,'BigEndian') + data_fid = fopen(header.data_filename,'r','b'); +else + warning('No data_format provided'); + data_fid = fopen(header.data_filename,'r'); +end + +% Read the offset because this info is not provided in header! +header.data_offset = getData_offset(lena_tree); +fseek(data_fid,header.data_offset,-1); + +% Get data type : +switch(header.data_type) + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +% Get the data size : +header.data_size = getData_size(lena_tree); +data = fread(data_fid,str2num(header.description.time_range.time_samples)*... + length(header.description.sensor_range.sensor_list.sensor),data_type); +data=reshape(data,str2num(header.description.time_range.time_samples), []); +header.Time=[1:str2num(header.description.time_range.time_samples)]... + ./str2num(header.description.time_range.sample_rate) ... + - str2num(header.description.time_range.pre_trigger); + +% first sensor 1, from sample 1 to last (537264) + + +% +% fprintf('Importing channel location information') +% Channel=getfield(load([studyname '_channel']), 'Channel'); +% chanlocs=LENAchannels2chanlocs( Channel ); +% +% i=1; +% %datafilename=sprintf('%s%d.mat', database , i); +% f=dir(sprintf('%s*.mat', database)); +% f=strvcat({f.name}); +% f=f(:,length(database)+1:end); +% trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +% trials=sort(trials); +% +% h = waitbar(0,'Importing Datafiles. Please wait...'); +% for i=1:length(trials) +% waitbar(i/length(trials),h) +% datafilename=sprintf('%s%d.mat', database , trials(i)); +% fprintf('Importing %s\n', datafilename) +% Data(i)=load(datafilename); +% %channelflag=channelflags & Data(i).ChannelFlag; +% channelflag=channelflags; +% Data(i).F=Data(i).F(find(channelflag),:); +% end +%close(h) + +return diff --git a/lena/readLENA.m~ b/lena/readLENA.m~ new file mode 100644 index 0000000..583168e --- /dev/null +++ b/lena/readLENA.m~ @@ -0,0 +1,147 @@ +% read_lena() - read LENA header & data +% +% Usage: +% >> [header data lena_tree] = read_lena(lenafile) +% +% Required Input: +% lenafile = LENA header file +% Available options: +% device -> 'ALL' (default)|'MEG'|'EEG'|'EEG+MEG'|'DC' +% trials -> Trials to import as list of indices (default: [] = 'all') +% timewindow -> Default: [] = 'all' +% +% Outputs: +% header = header info (from reading the xml heder file) +% data = cell array of data (one cell by trial) +% +% Author: Karim N'Diaye, CNRS-UPR640, 01 Jan 2004 +% +% See also: +% POP_READLENA, EEGLAB + +%123456789012345678901234567890123456789012345678901234567890123456789012 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [header data lena_tree] = readLENA(lenafile,varargin) + +if nargin < 1 + help(mfilename); + return; +end; +binary_extensions = {'.bin' '.data'}; + +lena_tree = xmltree(lenafile); +warning('off','MATLAB:warn_r14_stucture_assignment') +header = convert(lena_tree); +warning('on','MATLAB:warn_r14_stucture_assignment') + +if nargout<2 + return +end + +if nargin==2 + data_filename = varargin{1}; + if isfield(header, 'data_filename') + warning('Overloading binary data filname from header (%s) to: %s', header.data_filename, data_filename); + end + header.data_filename = data_filename; +end + + +if ~isfield(header, 'data_filename') + header.data_filename =''; + for i=1:length(binary_extensions) + data_filename = [lenafile(1:end-5) binary_extensions{i} ]; + if exist(data_filename, 'file') + header.data_filename = data_filename; + warning('Assumed binary data file not specified in header... Found possible match: %s', data_filename); + break; + end + end +end +if isempty(header.data_filename) + error('No datafile') +end + +fprintf('Importing data from binary file...\n') + +if strcmp(header.data_format,'LittleEndian') + data_fid = fopen(header.data_filename,'r','l'); +elseif strcmp(header.data_format,'BigEndian') + data_fid = fopen(header.data_filename,'r','b'); +else + warning('No data_format provided'); + data_fid = fopen(header.data_filename,'r'); +end + +% Read the offset because this info is not provided in header! +header.data_offset = getData_offset(lena_tree); +fseek(data_fid,header.data_offset,-1); + +% Get data type : +switch(header.data_type) + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +% Get the data size : +header.data_size = getData_size(lena_tree); +data = fread(data_fid,str2num(header.description.time_range.time_samples)*... + length(header.description.sensor_range.sensor_list.sensor),data_type); +data=reshape(data,str2num(header.description.time_range.time_samples), []); +h.Time= +% first sensor 1, from sample 1 to last (537264) + + +% +% fprintf('Importing channel location information') +% Channel=getfield(load([studyname '_channel']), 'Channel'); +% chanlocs=LENAchannels2chanlocs( Channel ); +% +% i=1; +% %datafilename=sprintf('%s%d.mat', database , i); +% f=dir(sprintf('%s*.mat', database)); +% f=strvcat({f.name}); +% f=f(:,length(database)+1:end); +% trials=str2num(char(strrep(cellstr(f), '.mat', ''))); +% trials=sort(trials); +% +% h = waitbar(0,'Importing Datafiles. Please wait...'); +% for i=1:length(trials) +% waitbar(i/length(trials),h) +% datafilename=sprintf('%s%d.mat', database , trials(i)); +% fprintf('Importing %s\n', datafilename) +% Data(i)=load(datafilename); +% %channelflag=channelflags & Data(i).ChannelFlag; +% channelflag=channelflags; +% Data(i).F=Data(i).F(find(channelflag),:); +% end +%close(h) + +return diff --git a/lena/readLENAHead.m b/lena/readLENAHead.m new file mode 100644 index 0000000..a59e7b6 --- /dev/null +++ b/lena/readLENAHead.m @@ -0,0 +1,568 @@ +function [Header lena_tree] = fastReadLENAHead(lena_file,dim_to_read) + +% This function reads a lena format file. +% +% Parameters : +% Input : +% - lena_file ( String ) : name of LENA file, or lenaTree object if +% file as already been read +% Optional +% - dim_to_read ( cell ) : sample to read indices for each dimension +% +% +% +% Output : +% - Header : a structure containing the header information that can be +% manipulated by the user: Only the dimensions specified inside +% dim_to_read parameter will be found in the Header structure. If dim_to_read is +% not used, all the dimensions will be found in Header structure +% +% Usage : +% H=fastReadLENA('/path/to/file/test.lena'); +% will return a matrix containing all data +% +% H=fastReadLENA('/path/to/file/test.lena',{ 2 , [ ] , [5:12] }); +% will return a matrix containing data for : +% - 2nd element in first dimension +% - all elements in second dimension +% - elements 5 to 12 in third dimension +% +% CNRS LENA UPR 640 + +% Check argument number : + if nargin <3 + smart = 1; + end + +level=[]; + +% First check lena_file argument, and read the header : + +if strcmp(class(lena_file),'xmltree') + lena_tree = lena_file; + lena_file = getfilename(lena_tree); +elseif exist(lena_file)==2 + lena_tree = lenaTree( lena_file ); +else + error(lena_file,'Provided file name doesn t seem to exist, or is not a valid object') + return +end + +% Get the header location : +[lena_path,lena_name]=fileparts(lena_file); + + +% Check present dimensions : + + +history=getHistory(lena_tree); + + + + +dimensions_names = getDimensions_names(lena_tree); +if iscell(dimensions_names) +length_dimensions_names=length(dimensions_names); +else if ischar(dimensions_names) + length_dimensions_names=1; + else if isempty(dimensions_names) + length_dimensions_names=0; + end + end +end + + + +if iscell(dimensions_names) +for i=1:length_dimensions_names + if strcmp(dimensions_names{i},'frequency_range') + frequency_dim=i; + elseif strcmp(dimensions_names{i},'sensor_range') + sensor_dim=i; + elseif strcmp(dimensions_names{i},'time_range') + time_dim=i; + elseif strcmp(dimensions_names{i},'datablock_range') + datablock_dim=i; + else + error(strcat('Found unexpected dimension : ',dimensions_names{i})) + end +end + +else if ischar(dimensions_names) + if strcmp(dimensions_names,'frequency_range') + frequency_dim=1; + elseif strcmp(dimensions_names,'sensor_range') + sensor_dim=1; + elseif strcmp(dimensions_names,'time_range') + time_dim=1; + elseif strcmp(dimensions_names,'datablock_range') + datablock_dim=1; + else + error(strcat('Found unexpected dimension : ',dimensions_names{i})) + end + else +% to do + end + +end + +% If no dimension to read is provided, read all : +if nargin == 1 + for i = 1:length_dimensions_names + dim_to_read{i}=''; + end +else + if length( dim_to_read) dim_to_read{i}(1)&Time1) +% F=convertBlocs2matrix(samples, size_to_read); +% else F=cell2mat (samples); +% end + +fclose (data_fid); +% Search Supersensor scales to apply : + +% if exist('sensor_dim') +% coef = getSupersensor_scale(lena_tree,dim_to_read{sensor_dim}); +% % Apply gains : +% if sensor_dim==1 +% size_to_read(sensor_dim)=1; +% coef_mat = repmat(coef',size_to_read); +% else +% s_t_r_temp=[1,size_to_read(1:sensor_dim-1),size_to_read(sensor_dim+1:end)]; +% test=repmat(coef',s_t_r_temp); +% coef_mat=permute(test,[2:sensor_dim,1,sensor_dim+1:length(size_to_read)]); +% end +% +% if (length(size_to_read)>1) +% F=coef_mat.*F; +% else F=coef.*F; +% end +% end +%if smart + % F=squeeze(F); +%end + +return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +function [leveldim, sensorList, sensorSample]=ProcessSensorDim(lena_tree, sensor_dim,dimensions_names, dim_to_read) + + +sensors_number = getSensors_number(lena_tree); + + + + Supersensors_number = getSensor_sample_number(lena_tree); + leveldim=Supersensors_number; + + + for i=1: sensors_number + list_sensor_name{i} = getSensor_name(lena_tree,i); + end + + + for i=1: Supersensors_number +% list_Supersensor_name{i} = getSupersensor_name(lena_tree,i); +coef{i} = getSupersensor_scale(lena_tree,i); + + end + + +list_Supersensor_name= getSupersensor_list(lena_tree); + +s=[]; + dim=(dim_to_read{sensor_dim}); + if ~ isempty(dim) + s_list= list_sensor_name(dim(1):dim(end)); + + + + for i=1:length(s_list) +% s(i)= rank_sensor(a_listsensor, sensorList(i)); + s1= rank_sensor(list_Supersensor_name, s_list(i)); + s=[s s1]; + + end + + else + + s= [1:length(list_Supersensor_name)]; + + + end + + + + + + +if (~ isempty(list_sensor_name)) + + for i=1:length(list_sensor_name) + sensor_categories{i} = getSensor_category(lena_tree,list_sensor_name{i} ); + sensor_coils{i}= getSensor_coil_geometry(lena_tree,list_sensor_name{i} ); + end + end + + sensorList.name=list_sensor_name; + sensorList.category=sensor_categories; + sensorList.coils=sensor_coils; + + %sensorSample=select_sensors_in(list_sensor_name, lena_tree); + + sensorSample=Supersensors_in(s, list_Supersensor_name ); +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sample_sensors=Supersensors_in(sel_sensor, Supersensor_list ) + +dim=size(Supersensor_list,2); +res=1; +if dim >1 + + for i=1: length(sel_sensor) + for i1=1:dim + rank=sel_sensor(i); + Superlist_sensors{i,i1}=Supersensor_list{rank,i1}; + end + Superlist_unit{i,:}='unknown unit'; %getSupersensor_unit(lenafile,i); + Superlist_scale{i,:}=1;%getSupersensor_scale(lenafile,i); + %res=res+1; + end + +else + + +% + for i=1: length(sel_sensor) + rank=sel_sensor(i); + Superlist_sensors{i,:}=(Supersensor_list{rank,:}); + Superlist_unit{i,:}=''; %getSupersensor_unit(lenafile,i); + Superlist_scale{i,:}=1;%getSupersensor_scale(lenafile,i); + %res=res+1; + end + +end + +if exist('Superlist_sensors') +dim=size(Superlist_sensors,2); +dim1=size(Superlist_sensors,1); +if dim>1 +sample_sensors.list_sensors=reshape (Superlist_sensors,dim1,dim); + + +else +sample_sensors.list_sensors=reshape (Superlist_sensors,length(Superlist_sensors),1); +end +sample_sensors.unit=reshape (Superlist_unit,length(Superlist_unit),1); +sample_sensors.scale=reshape (Superlist_scale,length(Superlist_scale),1); +end + +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [leveldim, time_pretrigger,sample_rate, timesamples_toread]=ProcessTimeDim(lena_tree, time_dim,dimensions_names, dim_to_read) + + +time_samples = getTime_samples(lena_tree); + sample_rate=getSample_rate(lena_tree); + leveldim=time_samples; + time_pretrigger=getPre_trigger(lena_tree); + + + if iscell(dimensions_names) + + for i=1: length( dimensions_names) + if strcmp(dimensions_names{i}, 'time_range') + if isempty(cell2mat(dim_to_read(i))) + timesamples_toread=time_samples; + else + timesamples_toread=cell2mat(dim_to_read(i)); + + end + break; + end + end + else if strcmp(dimensions_names,'time_range') + if isempty(cell2mat(dim_to_read(1))) + timesamples_toread=time_samples; + else + timesamples_toread=cell2mat(dim_to_read(1)); + + end + end + end + +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s= rank_sensor(a_listsensor, sensor) + +found=false; +s=-1; +i=1; +k=1; +while (i< length(a_listsensor)) & ~found + tab=((strmatch(char(sensor),char(a_listsensor{i,:})))); + if ~isempty(tab) + % found =true; + s(k)= i; + k=k+1; + + end + i=i+1; +end +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% diff --git a/lena/read_ClassFile.m b/lena/read_ClassFile.m new file mode 100644 index 0000000..a3c10af --- /dev/null +++ b/lena/read_ClassFile.m @@ -0,0 +1,53 @@ +% readClassFile() - Reads Classes from CTF's ClassFile +% +% [cls]=readClassFile(dsfolder) +% +% Input : +% dsfolder: the folder containing the ClassFile to be read +% or the ClassFile filename itself +% +% Output: +% cls: the classes +% +% Classrs have the following fields: +% .name: their label e.g. 'Tr17' +% .e: the trial in which they occur (indexed from 1) +% + +% Not yet! +% Optional fields: +% .color +% .comment + +function [cls] = readClassFile(dsfolder) + +if exist(dsfolder, 'dir') + [dspath, dsname]=fileparts(dsfolder); + clsfile=fullfile(dsfolder, 'ClassFile.cls'); +elseif exist(dsfolder, 'file') + clsfile=dsfolder; +else + error([mfilename ': .cls file not found!']); +end + +fprintf('Reading File: %s\n', clsfile) +txt=textread(clsfile,'%s','delimiter','\n','whitespace',''); +n=0; + +for i=1:size(txt,1) + if strcmp(txt{i}, 'NAME:') + n=n+1; + cls(n).name=char(txt{i+1}); + end + + if strcmp(txt{i}, 'NUMBER OF TRIALS:') + nb_events(n)=str2num(txt{i+1}); + end + + if strmatch('TRIAL NUMBER', txt{i}) + for j=1:nb_events(n) + [a]= strread(txt{i+j}); + cls(n).e(j)=a+1; + end + end +end diff --git a/lena/read_events.m b/lena/read_events.m new file mode 100755 index 0000000..762f72b --- /dev/null +++ b/lena/read_events.m @@ -0,0 +1,32 @@ + + +error('read_events is deprecated, use: read_lena_events()') + +% function [e,txt] = read_event(eventfile) +% if nargin < 1,help(mfilename);return;end; +% e = struct(... +% 'trial',[],... +% 'time', [],... +% 'name', [],... +% 'duration', [],... +% 'offset', []); +% fprintf('Reading File: %s\n', eventfile) +% txt=textread(eventfile,'%s','delimiter','\n','whitespace',''); +% NL = length(txt); +% i=1; +% % TRIAL TIME NAME DURATION OFFSET +% while(i<=NL && (txt{i}(1) == '#')) +% i=i+1; +% end +% n=0; +% while i<=NL +% n=n+1; +% try +% [e(n).trial,e(n).time,e(n).name,e(n).duration,e(n).offset]=strread(txt{i}, '%d%f%s%f%f'); +% catch +% [e(n).trial,e(n).time,e(n).name]=strread(txt{i}, '%d%f%s'); +% end +% e(n).trial=e(n).trial+1; +% e(n).name = e(n).name{1}; +% i=i+1; +% end diff --git a/lena/read_lena.m b/lena/read_lena.m new file mode 100755 index 0000000..a1ad7c1 --- /dev/null +++ b/lena/read_lena.m @@ -0,0 +1,475 @@ +% read_lena() - read LENA header & data +% +% Usage: +% [header] = read_lena(lenafile) reads only the header found in the LENA folder +% >> [header data] = read_lena(lenafile) also reads the whole data +% >> [header data] = read_lena(lenafile,DataSelection) +% >> [header data] = read_lena(lenafile,OPTIONS) +% >> [header data Time OPTIONS extras] = read_lena(lenafile,...) +% +% Required input: +% lenafile = LENA header file +% Optional inputs: +% The subset of data to read may be (more quickly) specified as a cell array: +% DataSelection = { 1:4 [] -2} to read the first four elemnts of the +% first dimension (e.g. the first 4 channels), all the 2nd dimension, +% excluding the second sample of the third etc. +% +% Alternatively, one may use an OPTIONS structure with any of those fields: +% OPTIONS.DataSelection = (see above) +% OPTIONS.SensorCategory = 'ALL' (default)|'MEG'|'EEG'|'EEG+MEG'|'DC'|'ADC' +% OPTIONS.SensorName = '' (default) or any regexp string or a cell array +% OPTIONS.Trials = Trials to read (default: [] = 'all') +% CAUTION: First Trial is #0 +% OPTIONS.TimeWindow = Start and end time in seconds (todo) +% OPTIONS.XMLDepth -> Depth of the XML parsing (min. 3, default: 5) +% This latter structure (OPTIONS) may also be provided as a list: +% >> [header data] = read_lena(lenafile,'Trials',[1:N],'SensorName','FC'...) +% +% Outputs: +% header = header info (from reading the xml heder file) +% data = cell array of data (one cell by trial) +% Time = Time vector for each sample +% OPTIONS = struct (see above) +% extras = structure with fields: +% * classes +% * events +% * badchannels +% +% Requires: xml_read() +% See also: +% +% Author: Karim N'Diaye, CNRS-UPR640, 21 Apr 2010 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [header data Time options extras] = read_lena(lenafile,varargin) +if nargin < 1 + help(mfilename); + return; +end +header = []; +data=[]; +Time = []; +options = {}; +extras = struct('classes',[] ,'events', [], 'badchannels', []); +if nargin<2 + options.DataSelection = { } ; % reads everything +end +%warning('Oh oh! There is a lot to read! It may take a while...'); +data_selection = {}; +data = []; + +options.XMLDepth = 5; +if nargin>2 + if isstruct(varargin{1}) + fn = fieldnames(varargin{1}); + for i=1:numel(fn) + options = setfield(options,fn{i},getfield(varargin{1},fn{i})); + end + varargin(1)=[]; + end + if iscell(varargin) && numel(varargin) == 1 + options.DataSelection = varargin{1}; + else + if mod(length(varargin),2) ~= 0 + error('Options should be given in pairs: ''Field1'', value1, etc.') + end + for i=1:2:length(varargin) + options = setfield(options,varargin{i}, varargin{i+1}); + end + end +end + +if iscell(lenafile) + header=cell(size(lenafile)); + for i=1:numel(lenafile) + fprintf('Reading: %s\n', lenafile{i}); + switch nargout + case 0; + case 1 + [header{i}] = read_lena(lenafile{i},varargin{:}); + case 2 + data=cell(size(lenafile)); + [header{i} data{i}] = read_lena(lenafile{i},varargin{:}); + case 3 + data=header; + Time=header; + [header{i} data{i} Time{i}] = read_lena(lenafile{i},varargin{:}); + end + end + + return +end +if not(exist(lenafile, 'file')) + error('File/folder does not exist: %s', lenafile); +end + +binary_extensions = {'.bin' '.data'}; + +canonical_dimensions = { + 'Sensor' 'sensor_range' ; + 'Time' 'time_range' ; + 'Trial' 'datablock_range' }; + +if exist(lenafile, 'dir') == 7 + %Folder = 2.0 format and above + header_file = fullfile(lenafile, 'data.header'); +else + [p,r,e]=fileparts(lenafile); + header_file = fullfile(p,[r, '.header']); + if ~exist(header_file, 'file') + header_file = lenafile; + end +end + +% The old version used 'xmltree' which is buggy with +% lena_tree = xmltree(header_file); +% warning('off', 'MATLAB:warn_r14_stucture_assignment') +% header = convert(lena_tree); +% warning('on', 'MATLAB:warn_r14_stucture_assignment') +% +% Indeed sensor info is lost: +% header.description.sensor_range.sensor_list(1).sensor{1}.coil +% is empty! +fprintf('Reading the header: %s...\n', header_file); + +if isfield(options, 'XMLDepth') + fprintf('Reading the XML to depth %d...\n', options.XMLDepth); + header = xml_read(header_file, struct('NumLevels',options.XMLDepth)); +else + header = xml_read(header_file); +end + +%% Exit if enough... +if nargout<2 + return +end +% Otherwise, it means that the user wants the binary data... +%% Read XML +if options.XMLDepth<4 + warning('read_lena:MinimalXMLDepth','The XML header must be read to a depth of at least 4 so as to import data'); + options.XMLDepth = 4; + header = xml_read(header_file, struct('NumLevels',options.XMLDepth)); +end + +%% Time vector +if isfield(header.description, 'time_range') +Time = [1:header.description.time_range.time_samples]... + ./header.description.time_range.sample_rate ... + - header.description.time_range.pre_trigger; +else + warning('read_lena:NoTimeRange', 'Data have no time range.'); + Time = []; +end +%% Data filename +if ~isfield(header, 'data_filename') + header.data_filename =''; + if exist(lenafile, 'dir') + %new format + data_filename = fullfile(lenafile, 'data.data'); + else + for i=1:length(binary_extensions) + [p,fn,ext]=fileparts(lenafile); + fn = fullfile(p,fn); + data_filename = [fn binary_extensions{i} ]; + if exist(data_filename, 'file') + header.data_filename = data_filename; + warning('I had to guess the binary data file since it was not specified in header...\nFound a possible match: %s\n', data_filename); + break; + end + end + end +else + data_filename = header.data_filename; +end +if isempty(fileparts(data_filename)) + % If specified without path, assumed it is in the same folder as the + % lena file + data_filename = fullfile(fileparts(lenafile), data_filename); +end +if ~exist(data_filename, 'file') + error('No binary data file found!') +end +fprintf('Data will be read from binary file: %s ...\n', data_filename) + +%% Data format + +if isfield(header, 'data_format') && strcmp(header.data_format,'LittleEndian') + data_fid = fopen(data_filename,'r','l'); +elseif isfield(header, 'data_format') && strcmp(header.data_format,'BigEndian') + data_fid = fopen(data_filename,'r','b'); +else + warning('No data_format provided'); + data_fid = fopen(data_filename,'r'); +end +if data_fid < 1 + error('Can''t open binary file'); +end +% Read the offset because this info is not provided in header! +if isfield(header, 'data_offset') + data_offset = header.data_offset; +else + data_offset = 0 ; +end +% Get data type : +switch(header.data_type) + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +% Get the data precision size : +data_precision = []; +switch header.data_type + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + if isfield(header, 'data_size') && header.data_size == 4 + data_precision = 'float32'; + end + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +if isempty(data_precision) + error('Unknonw data precision/size/type'); +end + +%% Data dimensions +data_dimensions = fieldnames(header.description); +ndim = length(data_dimensions); +[ign,candim,dimcan] = intersect(canonical_dimensions(:,2), data_dimensions); +if any(dimcan(1:2) == 0) || any((candim-dimcan)~=0) || any(candim == 0) + warning('read_lena:NonBrainstormDimensions',... + ['Dimensions are not "brainstorm/eeglab" like (i.e. Sensor * Time * Epochs) but: ', ... + sprintf('<%s> ',data_dimensions{:})]) +end +% the nth canonical dim is the p-th one in the data +icandim(candim)=dimcan; +data_size=zeros(1,ndim); +for i=1:ndim + switch (data_dimensions{i}) + case 'datablock_range' + data_size(i) = numel(header.description.datablock_range.datablock_samples.trial); + case 'sensor_range' + data_size(i) = numel(header.description.sensor_range.sensor_samples.supersensor); + case 'time_range' + data_size(i) = header.description.time_range.time_samples; + case 'frequency_range' + data_size(i) = numel(header.description.frequency_range.frequency_samples.superfrequency); + otherwise + error('Wrong dimension') + end +end + +%% Data selection +% Expand (if needed) data_selection to the actual size of the data +if numel(data_selection)header.description.time_range.sample_rate) + error('Selection Time window goes by the Time range [%g .. %g] of the data!', Time([1 end])) + end + else + error('Wrong Time selection (should be a 2x1 cell)') + end + + data_selection{icandim(2)} = options.Time; + case 'Trials' + data_selection{icandim(3)} = options.Trials; + end +end +for i_dim = 1:ndim + if islogical(data_selection{i_dim}) + data_selection{i_dim} = find(data_selection{i_dim}); + end +end +if any(cellfun('isempty',data_selection)) + warning('read_lena:EmptySelection','According to options, data selection reduces to nill!') + return +end +for i_dim = 1:ndim + if any(abs(data_selection{i_dim})>data_size(i_dim)) + error('read_lena:SelectionBeyondRange','Selection of <%s> is beyond authorized range [ %g .. %g ]', ... + data_dimensions{i_dim}, 1, data_size(i_dim)) + end +end + +%% Data fread +% the fastest increasing dimension is the first and also the first one in +% the header, that is the 1st one unfolding in the binary data + +h.data.filename = data_filename; +h.data.selection = data_selection; + +[fread_size fread_precision fread_skip fread_offset fread_selection] = fread_options(data_size,data_selection,data_precision); +% Now reads the data +fprintf('... reading %d bytes of data ...\n',prod(fread_size)); +fseek(data_fid,data_offset+fread_offset, 'bof'); +data = fread(data_fid,prod(fread_size),fread_precision,fread_skip); +% Reshape data read into a matrix +data=reshape(data,fread_size); +% Extract the data if needed +for i=1:ndim + data=subarray(data,fread_selection{i},i); +end +% Now permute so as to match the "natural" order of data_dimensions +data=permute(data,ndim:-1:1); + + +%% Read extra info (classes, etc.) +extras.classes = read_lena_classes(lenafile); +extras.events = read_lena_events(lenafile); +%badchannels = read_lena_badchannels(lenafile); + +return + + +function [fread_size fread_precision fread_skip fread_offset fread_selection] = fread_options(data_size,data_selection,data_precision) +% Optimal precision & skip to use in fread based on the shape of data +% The 'quick and dirty' way is to read all the data and select in the matrix afterwards... +fread_size = fliplr(data_size); +fread_precision = data_precision; +fread_skip = 0; +fread_offset = 0; +fread_selection = fliplr(data_selection); +return; +switch(data_precision) + case {'uint8','int8','uchar','schar','char'} + fread_bytes = 2; + case {'uint16','int32','short','ushort'} + fread_bytes = 2; + case {'float32','single', 'float','uint32','int32','int','uint','long'} + fread_bytes = 4; + case {'float64','double','uint64','int64'} + fread_bytes = 8; + otherwise + warning('read_lena:UnknownPrecision','Unknown precision: %s -- Go through the Full monthy', data_precision); + return +end +ndim = numel(fread_size); +% Squeeze successive dimensions (beyond the first one) with only one sample to read +% Find the last squeezable dimension +i = 1; +while i1) + break; + end +end +if i==ndim + skip = 0; +else + +end +return + + +function [i dist] = findclosest(x,y) +x=x(:)'; +y=y(:); +[dist i] = min(abs(repmat(x,length(y),1) - repmat(y,1,length(x)))); + diff --git a/lena/read_lena.m~ b/lena/read_lena.m~ new file mode 100644 index 0000000..fd8e7ea --- /dev/null +++ b/lena/read_lena.m~ @@ -0,0 +1,474 @@ +% read_lena() - read LENA header & data +% +% Usage: +% [header] = read_lena(lenafile) reads only the header found in the LENA folder +% >> [header data] = read_lena(lenafile) also reads the whole data +% >> [header data] = read_lena(lenafile,DataSelection) +% >> [header data] = read_lena(lenafile,OPTIONS) +% >> [header data Time OPTIONS extras] = read_lena(lenafile,...) +% +% Required input: +% lenafile = LENA header file +% Optional inputs: +% The subset of data to read may be (more quickly) specified as a cell array: +% DataSelection = { 1:4 [] -2} to read the first four elemnts of the +% first dimension (e.g. the first 4 channels), all the 2nd dimension, +% excluding the second sample of the third etc. +% +% Alternatively, one may use an OPTIONS structure with any of those fields: +% OPTIONS.DataSelection = (see above) +% OPTIONS.SensorCategory = 'ALL' (default)|'MEG'|'EEG'|'EEG+MEG'|'DC'|'ADC' +% OPTIONS.SensorName = '' (default) or any regexp string or a cell array +% OPTIONS.Trials = Trials to read (default: [] = 'all') +% CAUTION: First Trial is #0 +% OPTIONS.TimeWindow = Start and end time in seconds (todo) +% OPTIONS.XMLDepth -> Depth of the XML parsing (min. 3, default: 5) +% This latter structure (OPTIONS) may also be provided as a list: +% >> [header data] = read_lena(lenafile,'Trials',[1:N],'SensorName','FC'...) +% +% Outputs: +% header = header info (from reading the xml heder file) +% data = cell array of data (one cell by trial) +% Time = Time vector for each sample +% OPTIONS = struct (see above) +% extras = structure with fields: +% * classes +% * events +% * badchannels +% +% Requires: xml_read() +% See also: +% +% Author: Karim N'Diaye, CNRS-UPR640, 21 Apr 2010 + +% Copyright (C) 2004, CNRS - UPR640, N'Diaye Karim, +% karim.ndiaye@chups.jussieu.Fr +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% $Log: readegi.m,v $ +% Revision 0.1 2004/01/01 +% First alpha version for EEGLAB release 4.301 + +function [header data Time options extras] = read_lena(lenafile,varargin) +if nargin < 1 + help(mfilename); + return; +end +header = []; +data=[]; +Time = []; +options = {}; +extras = struct('classes',[] ,'events', [], 'badchannels', []); +if nargin<2 + options.DataSelection = { } ; % reads everything +end +%warning('Oh oh! There is a lot to read! It may take a while...'); +data_selection = {}; +data = []; + +options.XMLDepth = 5; +if nargin>2 + if isstruct(varargin{1}) + fn = fieldnames(varargin{1}); + for i=1:numel(fn) + options = setfield(options,fn{i},getfield(varargin{1},fn{i})); + end + varargin(1)=[]; + end + if iscell(varargin) && numel(varargin) == 1 + options.DataSelection = varargin{1}; + else + if mod(length(varargin),2) ~= 0 + error('Options should be given in pairs: ''Field1'', value1, etc.') + end + for i=1:2:length(varargin) + options = setfield(options,varargin{i}, varargin{i+1}); + end + end +end + +if iscell(lenafile) + header=cell(size(lenafile)); + for i=1:numel(lenafile) + fprintf('Reading: %s\n', lenafile{i}); + switch nargout + case 0; + case 1 + [header{i}] = read_lena(lenafile{i},varargin{:}); + case 2 + data=cell(size(lenafile)); + [header{i} data{i}] = read_lena(lenafile{i},varargin{:}); + case 3 + data=header; + Time=header; + [header{i} data{i} Time{i}] = read_lena(lenafile{i},varargin{:}); + end + end + + return +end +if not(exist(lenafile, 'file')) + error('File/folder does not exist: %s', lenafile); +end + +binary_extensions = {'.bin' '.data'}; + +canonical_dimensions = { + 'Sensor' 'sensor_range' ; + 'Time' 'time_range' ; + 'Trial' 'datablock_range' }; + +if exist(lenafile, 'dir') == 7 + %Folder = 2.0 format and above + header_file = fullfile(lenafile, 'data.header'); +else + [p,r,e]=fileparts(lenafile); + header_file = fullfile(p,[r, '.header']); + if ~exist(header_file, 'file') + header_file = lenafile; + end +end + +% The old version used 'xmltree' which is buggy with +% lena_tree = xmltree(header_file); +% warning('off', 'MATLAB:warn_r14_stucture_assignment') +% header = convert(lena_tree); +% warning('on', 'MATLAB:warn_r14_stucture_assignment') +% +% Indeed sensor info is lost: +% header.description.sensor_range.sensor_list(1).sensor{1}.coil +% is empty! +fprintf('Reading the header: %s...\n', header_file); + +if isfield(options, 'XMLDepth') + fprintf('Reading the XML to depth %d...\n', options.XMLDepth); + header = xml_read(header_file, struct('NumLevels',options.XMLDepth)); +else + header = xml_read(header_file); +end + +%% Exit if enough... +if nargout<2 + return +end +% Otherwise, it means that the user wants the binary data... +%% Read XML +if options.XMLDepth<4 + warning('read_lena:MinimalXMLDepth','The XML header must be read to a depth of at least 4 so as to import data'); + options.XMLDepth = 4; + header = xml_read(header_file, struct('NumLevels',options.XMLDepth)); +end + +%% Time vector +if isfield(header.description, 'time_range') +Time = [1:header.description.time_range.time_samples]... + ./header.description.time_range.sample_rate ... + - header.description.time_range.pre_trigger; +else + warning('read_lena:NoTimeRange', 'Data have no time range.'); + Time = []; +end +%% Data filename +if ~isfield(header, 'data_filename') + header.data_filename =''; + if exist(lenafile, 'dir') + %new format + data_filename = fullfile(lenafile, 'data.data'); + else + for i=1:length(binary_extensions) + [p,fn,ext]=fileparts(lenafile); + fn = fullfile(p,fn); + data_filename = [fn binary_extensions{i} ]; + if exist(data_filename, 'file') + header.data_filename = data_filename; + warning('I had to guess the binary data file since it was not specified in header...\nFound a possible match: %s\n', data_filename); + break; + end + end + end +else + data_filename = header.data_filename; +end +if isempty(fileparts(data_filename)) + % If specified without path, assumed it is in the same folder as the + % lena file + data_filename = fullfile(fileparts(lenafile), data_filename); +end +if ~exist(data_filename, 'file') + error('No binary data file found!') +end +fprintf('Data will be read from binary file: %s ...\n', data_filename) + +%% Data format + +if isfield(header, 'data_format') && strcmp(header.data_format,'LittleEndian') + data_fid = fopen(data_filename,'r','l'); +elseif isfield(header, 'data_format') && strcmp(header.data_format,'BigEndian') + data_fid = fopen(data_filename,'r','b'); +else + warning('No data_format provided'); + data_fid = fopen(data_filename,'r'); +end +if data_fid < 1 + error('Can''t open binary file'); +end +% Read the offset because this info is not provided in header! +if isfield(header, 'data_offset') + data_offset = header.data_offset; +else + data_offset = 0 ; +end +% Get data type : +switch(header.data_type) + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +% Get the data precision size : +data_precision = []; +switch header.data_type + case 'unsigned fixed' + data_type='uint'; + case 'fixed' + data_type='int'; + case 'floating' + data_type='float'; + if isfield(header, 'data_size') && header.data_size == 4 + data_precision = 'float32'; + end + otherwise + error('Error : data_type wasn t found, which is required.') + return +end +if isempty(data_precision) + error('Unknonw data precision/size/type'); +end + +%% Data dimensions +data_dimensions = fieldnames(header.description); +ndim = length(data_dimensions); +[ign,candim,dimcan] = intersect(canonical_dimensions(:,2), data_dimensions); +if any(dimcan(1:2) == 0) || any((candim-dimcan)~=0) || any(candim == 0) + warning('read_lena:NonBrainstormDimensions',... + ['Dimensions are not "brainstorm/eeglab" like (i.e. Sensor * Time * Epochs) but: ', ... + sprintf('<%s> ',data_dimensions{:})]) +end +% the nth canonical dim is the p-th one in the data +icandim(candim)=dimcan; +data_size=zeros(1,ndim); +for i=1:ndim + switch (data_dimensions{i}) + case 'datablock_range' + data_size(i) = numel(header.description.datablock_range.datablock_samples.trial); + case 'sensor_range' + data_size(i) = numel(header.description.sensor_range.sensor_samples.supersensor); + case 'time_range' + data_size(i) = header.description.time_range.time_samples; + case 'frequency_range' + data_size(i) = numel(header.description.frequency_range.frequency_samples.superfrequency); + otherwise + error('Wrong dimension') + end +end + +%% Data selection +% Expand (if needed) data_selection to the actual size of the data +if numel(data_selection)header.description.time_range.sample_rate) + error('Selection Time window goes by the Time range [%g .. %g] of the data!', Time([1 end])) + end + else + error('Wrong Time selection (should be a 2x1 cell)') + end + + data_selection{icandim(2)} = options.Time; + case 'Trials' + data_selection{icandim(3)} = options.Trials; + end +end +for i_dim = 1:ndim + if islogical(data_selection{i_dim}) + data_selection{i_dim} = find(data_selection{i_dim}); + end +end +if any(cellfun('isempty',data_selection)) + warning('read_lena:EmptySelection','According to options, data selection reduces to nill!') + return +end +for i_dim = 1:ndim + if any(abs(data_selection{i_dim})>data_size(i_dim)) + error('read_lena:SelectionBeyondRange','Selection of <%s> is beyond authorized range [ %g .. %g ]', ... + data_dimensions{i_dim}, 1, data_size(i_dim)) + end +end + +%% Data fread +% the fastest increasing dimension is the first and also the first one in +% the header, that is the 1st one unfolding in the binary data + +h.data.filename = data_filename; +h.data.selection = data_selection; + +[fread_size fread_precision fread_skip fread_offset fread_selection] = fread_options(data_size,data_selection,data_precision); +% Now reads the data +fprintf('... reading %d bytes of data ...\n',prod(fread_size)); +fseek(data_fid,data_offset+fread_offset, 'bof'); +data = fread(data_fid,prod(fread_size),fread_precision,fread_skip); +% Reshape data read into a matrix +data=reshape(data,fread_size); +% Extract the data if needed +for i=1:ndim + data=subarray(data,fread_selection{i},i); +end +% Now permute so as to match the "natural" order of data_dimensions +data=permute(data,ndim:-1:1); + + +%% Read extra info (classes, etc.) +c = read_lena_classes(lenafile); + + +return + + +function [fread_size fread_precision fread_skip fread_offset fread_selection] = fread_options(data_size,data_selection,data_precision) +% Optimal precision & skip to use in fread based on the shape of data +% The 'quick and dirty' way is to read all the data and select in the matrix afterwards... +fread_size = fliplr(data_size); +fread_precision = data_precision; +fread_skip = 0; +fread_offset = 0; +fread_selection = fliplr(data_selection); +return; +switch(data_precision) + case {'uint8','int8','uchar','schar','char'} + fread_bytes = 2; + case {'uint16','int32','short','ushort'} + fread_bytes = 2; + case {'float32','single', 'float','uint32','int32','int','uint','long'} + fread_bytes = 4; + case {'float64','double','uint64','int64'} + fread_bytes = 8; + otherwise + warning('read_lena:UnknownPrecision','Unknown precision: %s -- Go through the Full monthy', data_precision); + return +end +ndim = numel(fread_size); +% Squeeze successive dimensions (beyond the first one) with only one sample to read +% Find the last squeezable dimension +i = 1; +while i1) + break; + end +end +if i==ndim + skip = 0; +else + +end +return + + +function [i dist] = findclosest(x,y) +x=x(:)'; +y=y(:); +[dist i] = min(abs(repmat(x,length(y),1) - repmat(y,1,length(x)))); + diff --git a/lena/read_lena_classes.m b/lena/read_lena_classes.m new file mode 100644 index 0000000..8038710 --- /dev/null +++ b/lena/read_lena_classes.m @@ -0,0 +1,37 @@ +function cls = read_lena_class(classfile) +%READ_LENA_CLASS - One line description goes here. +% [cls] = read_lena_class(classfile) +% [cls] = read_lena_class(lenafolder) +% +% Example +% >> read_lena_class +% +% See also: + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-06-08 Creation +% +% ----------------------------- Script History --------------------------------- +cls=repmat(struct('name',[],'trials',[]),0); +if nargin < 1,help(mfilename);return;end; +if exist(classfile,'dir') + classfile = fullfile(classfile,'data.class'); +end +if ~exist(classfile,'file') + error('read_lena_class:BadLenaFolder','File not found: %s',classfile) +end +e = read_lena_events(classfile); +[names i,j] =unique({e.name}); +n=numel(names); +cls=repmat(cls,1,n); +for i=1:n + cls(i).name = names{i}; + cls(i).trials = [e(j==i).trial]; +end diff --git a/lena/read_lena_events.m b/lena/read_lena_events.m new file mode 100644 index 0000000..28f97a2 --- /dev/null +++ b/lena/read_lena_events.m @@ -0,0 +1,79 @@ +function [events,filename] = read_lena_events(filename) +%READ_LENA_EVENTS - Reads events in a LENA file +% [events] = read_lena_events(filename) +% events is a struct array with fields: +% .name +% .comments +% .color +% .epoch +% .time +% .duration +% .offset +% +% Example +% >> read_lena_events('run1.lena') +% >> read_lena_events('data.ptx') +% +% See also: read_ptx + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-10-18 Creation +% +% ----------------------------- Script History --------------------------------- +events = repmat(struct(... + 'name',[],... + 'comment',[],... + 'color',[],... + 'trial',[],... + 'time',[],... + 'duration',[],... + 'offset',[]),0); + +folder = NaN; +if exist(filename, 'dir') + folder = filename; + % Default names for event files + EVENTFILES = { 'data.event' 'data.events' }; + while ~isempty(EVENTFILES) + filename = fullfile(folder,EVENTFILES{1}); + EVENTFILES(1)=[]; + if exist(filename,'file') + break + end + end +end + +if ~exist(filename,'file') + if ~isnan(folder) + return + end + error('File not found: %s must be a LENA folder or a ptx-formatted file',filename); +end + +[onsets,names,epochs,durations,offsets,header] = read_ptx(filename); +if ~isempty(onsets) + events = struct(... + 'name',names,... + 'comment',[],... + 'color',[],... + 'trial',num2cell(epochs),... + 'time',num2cell(onsets),... + 'duration',num2cell(durations),... + 'offset',num2cell(offsets)); +end +if ~isempty(header) + specs = regexp(header(strmatch('#TRIGGER COMMENTS',header)+1:end),... + '#\s+(?\w*)\s+(?.*)\s+#[cC][oO][lL][oO][rR]=(?[#\w]*)','names'); + for i=1:numel(specs) + if ~isempty(specs{i}) + [events(ismember({events.name},specs{i}.name)).color]=deal(specs{i}.color); + end + end +end diff --git a/lena/read_ptx.m b/lena/read_ptx.m new file mode 100644 index 0000000..0a5eb07 --- /dev/null +++ b/lena/read_ptx.m @@ -0,0 +1,45 @@ +function [onsets,names,epochs,durations,offsets,header] = read_ptx(filename) +% read_ptx() - read PTX-formatted file +% Usage: +% [onsets,names,epochs] = read_ptx(filename) reads a PTX formatted file +% [onsets,names,epochs,durations,offsets,header] = ... +% also reads extra info (if provided in PTX file) +% +%Nota bene: +% onsets are in seconds (even for PTX v.1 files) +% epochs start at 1, if not specified in the file, epochs(:) = NaN +% +% See also: read_lena(), read_lena_events() + +% Author: Karim N'Diaye, CRICM, CNRS, 01 Jan 2010 + +if ~exist(filename, 'file') + error('read_ptx:FileNotFound','File not found: %s',filename) +end +% version info: +version = textread(filename,'%s',1); +version = version{1}; +if ~isequal(regexp(version,'#'),1) + version = 'PTX_V1.0 (assumed)'; +end +header = {}; +switch version + case '#PTX_V2.0' + content = textread(filename,'%s','delimiter','\n'); + header = content(strmatch('#',content)); + try + [epochs,onsets,names,durations,offsets]=textread(filename, '%d%f%s%f%f', 'commentstyle', 'shell'); + catch + [onsets,names,durations,offsets]=textread(filename, '%f%s%f%f', 'commentstyle', 'shell'); + epochs = onsets.*NaN; + end + case { '#PTX_V1.0' 'PTX_V1.0 (assumed)' } + [onsets,names]=textread(filename, '%f%s', 'commentstyle', 'shell'); + onsets = onsets/1000; + epochs = onsets.*NaN; + durations = onsets.*NaN; + offsets = onsets.*NaN; + otherwise + error('Unknown PTX version: %s', version); +end +epochs = epochs+1; diff --git a/lena/read_trc.m b/lena/read_trc.m new file mode 100644 index 0000000..7b858b8 --- /dev/null +++ b/lena/read_trc.m @@ -0,0 +1,119 @@ +%TRC import +% after: +% http://neuralensemble.org/trac/OpenElectrophy/browser/trunk/pyssdh/OpenElectrophy/filereader/generic/read_trc.py?rev=77c char string of length 1 + +%Python struct alias read_f format: +% b signed char integer schar +% B unsigned char integer uchar +% h short integer int16 +% H unsigned short integer uint16 +% i int / integer int32 +% I unsigned integer or long uint32 +% http://docs.python.org/library/struct.html + + +clear TRC +TRC.Filename='\\Serveur_meg\datalinks\CONFINUM\intra\micromed\patients\PAT_2\EEG_3.TRC'; +fid=fopen(TRC.Filename); +%% Read Patient info +fseek(fid,64,-1); +TRC.PatientName = deblank(fread(fid, 22, 'int8=>char')'); +TRC.PatientSurname = deblank(fread(fid, 20, 'uint8=>char')'); + +%% Read date +fseek(fid,128,-1); +TRC.Datenum = datenum(fliplr(fread(fid,3,'int8')')+[1900 0 0]); +TRC.Date = datestr(TRC.Datenum); + +%% Header +fseek(fid,175,-1); +TRC.HeaderVersion = fread(fid,1,'int8'); +if TRC.HeaderVersion ~= 4 + error('*.trc file is not Micromed System98 Header type 4') +end + +%% Data description +fseek(fid,138,-1); +TRC.DataStartOffset = fread(fid,1,'uint32') +TRC.NumberOfChannels = fread(fid,1,'uint16') +TRC.Multiplexer = fread(fid,1,'uint16') +TRC.SamplingRate = fread(fid,1,'uint16') +TRC.Bytes = fread(fid,1,'uint16') +TRC.Precision = sprintf('uint%d', 8*TRC.Bytes); +fseek(fid,176+8,-1); +TRC.Code_Area = fread(fid,1,'uint32') +TRC.Code_Area_Length = fread(fid,1,'uint32') +fseek(fid,192+8,-1) +TRC.Electrode_Area = fread(fid,1,'uint32') +TRC.Electrode_Area_Length = fread(fid,1,'uint32') +fseek(fid,400+8,-1) +TRC.Trigger_Area =fread(fid,1,'uint32') +TRC.Trigger_Area_Length=fread(fid,1,'uint32') + +%% Read Code Info +fseek(fid,TRC.Code_Area,-1) +TRC.Code = fread(fid, TRC.NumberOfChannels, 'uint16') +units = { ... + -1 1e-9 + 0 1e-6 + 1 1e-3 + 2 1 + 100 'percent' + 101 'bpm' + 102 'Adim'}; + +%units = {-1:1e-9, 0:1e-6, 1:1e-3, 2:1, 100:'percent', 101:'bpm', 102:'Adim'} +for c=1:TRC.NumberOfChannels + Channel.chan_record = TRC.Code(c) + fseek(fid, TRC.Electrode_Area+TRC.Code(c)*128+2,-1) + Channel.positive_input = sprintf('%02d-%s', c, char(fread(fid, 6, 'uchar'))); + Channel.negative_input = sprintf('%02d-%s', c, char(fread(fid, 6, 'uchar'))); + Channel.logical_min = fread(fid,1,'int32'); + Channel.logical_max = fread(fid,1,'int32'); + Channel.logical_ground = fread(fid,1,'int32'); + Channel.physical_min = fread(fid,1,'int32'); + Channel.physical_max = fread(fid,1,'int32'); + try + Channel.measurement_unit = units{fread(fid,1,'int16')==[units{:,1}],2}; + catch + Channel.measurement_unit = 10e-6; + end + fseek(fid, 8,0); + Channel.rate_coef = fread(fid,1,'uint16'); + Channel + TRC.Channel(c) = Channel; + +end + +%% Read Raw data +fseek(fid,TRC.DataStartOffset,-1); +% Skip 1h40 minutes of data +% + +if 0 % read all channels +%TRC.Data = fread(fid,70000*TRC.NumberOfChannels,'uint16'); +%TRC.Data = reshape(TRC.Data,64, []); +end +% Skip ... min of data +fseek(fid,TRC.Bytes*TRC.NumberOfChannels*TRC.SamplingRate*(0*60),0) +% Skip 24 Channels to read Channel 25 +fseek(fid,TRC.Bytes*24,0) +TRC.Data =fread(fid,Inf,'uint16', 63*TRC.Bytes + TRC.Bytes*TRC.NumberOfChannels*TRC.SamplingRate )'; +plot(TRC.Data) + +%% RAWDATA rescaling matrix +factor = ([TRC.Channel.physical_max]-[TRC.Channel.physical_min])./([TRC.Channel.logical_max]-[TRC.Channel.logical_min]); +if ~all(cell2mat({TRC.Channel.measurement_unit})==units{[units{:,1}]==0,2}) + error('Don''t know how to read multiple measurement units in a single file') +end + +for i=1:size(TRC.Data,1) + TRC.F(i,:) = (TRC.Data(i,:)-TRC.Channel(i).logical_ground)*factor(i); +end + +%% + +TRC + +%% Close fid +%fclose(fid); diff --git a/lena/readds.m b/lena/readds.m new file mode 100644 index 0000000..d8acbea --- /dev/null +++ b/lena/readds.m @@ -0,0 +1,33 @@ +if ~ exist('fic_ds') + fic_ds=input('Fichier DS ?\n ''/pclxserver/home/ndiaye/DAV/rawdata/S7/aud-avTr22.ds'' '); +end + +if ~ exist('F') + [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] = ds2brainstorm(fic_ds,0); +end + +t=textread('ClassFile.cls','%s'); +n=strmatch('BAD',t) +n=strmatch('NUMBER',t(n:end))+n-1 + +nbad=str2num(t{n(1)+3}); +badtrials=[]; +for i=1:nbad + j=i+n(2); +badtrials=[badtrials str2num(t{j})]; +end + +MARQUEURS={'Tr22' 'Tr23' 'Tr24' 'Tr25' 'Tr26'} +for i=1:length(MARQUEURS) + t=textread('MarkerFile.mrk','%s'); + mark(i).name=MARQUEURS{i} + n=strmatch(MARQUEURS{i},t); + n=strmatch('SAMPLES',t(n:end))+n-1; + mark(i).nb=str2num(t{n(1)+1}) + + for j=1:mark(i).nb + k=2*j+n(2)+7; + mark(i).tr(j)=str2num(t{k}); + end + +end diff --git a/lena/xml_read.m b/lena/xml_read.m new file mode 100644 index 0000000..9abd471 --- /dev/null +++ b/lena/xml_read.m @@ -0,0 +1,514 @@ +function [tree, RootName, DOMnode] = xml_read(xmlfile, Pref) +%XML_READ reads xml files and converts them into Matlab's struct tree. +% +% DESCRIPTION +% tree = xml_read(xmlfile) reads 'xmlfile' into data structure 'tree' +% +% tree = xml_read(xmlfile, Pref) reads 'xmlfile' into data structure 'tree' +% according to your preferences +% +% [tree, RootName, DOMnode] = xml_read(xmlfile) get additional information +% about XML file +% +% INPUT: +% xmlfile URL or filename of xml file to read +% Pref Preferences: +% Pref.ItemName - default 'item' - name of a special tag used to itemize +% cell arrays +% Pref.ReadAttr - default true - allow reading attributes +% Pref.ReadSpec - default true - allow reading special nodes +% Pref.Str2Num - default 'smart' - convert strings that look like numbers +% to numbers. Options: "always", "never", and "smart" +% Pref.KeepNS - default true - keep or strip namespace info +% Pref.NoCells - default true - force output to have no cell arrays +% Pref.Debug - default false - show mode specific error messages +% Pref.NumLevels- default infinity - how many recursive levels are +% allowed. Can be used to speed up the function by prunning the tree. +% Pref.RootOnly - default true - output variable 'tree' corresponds to +% xml file root element, otherwise it correspond to the whole file. +% Pref.CellItem - default 'true' - leave 'item' nodes in cell notation. +% OUTPUT: +% tree tree of structs and/or cell arrays corresponding to xml file +% RootName XML tag name used for root (top level) node. +% Optionally it can be a string cell array storing: Name of +% root node, document "Processing Instructions" data and +% document "comment" string +% DOMnode output of xmlread +% +% DETAILS: +% Function xml_read first calls MATLAB's xmlread function and than +% converts its output ('Document Object Model' tree of Java objects) +% to tree of MATLAB struct's. The output is in format of nested structs +% and cells. In the output data structure field names are based on +% XML tags, except in cases when tags produce illegal variable names. +% +% Several special xml node types result in special tags for fields of +% 'tree' nodes: +% - node.CONTENT - stores data section of the node if other fields are +% present. Usually data section is stored directly in 'node'. +% - node.ATTRIBUTE.name - stores node's attribute called 'name'. +% - node.COMMENT - stores node's comment section (string). For global +% comments see "RootName" output variable. +% - node.CDATA_SECTION - stores node's CDATA section (string). +% - node.PROCESSING_INSTRUCTIONS - stores "processing instruction" child +% node. For global "processing instructions" see "RootName" output variable. +% - other special node types like: document fragment nodes, document type +% nodes, entity nodes, notation nodes and processing instruction nodes +% will be treated like regular nodes +% +% EXAMPLES: +% MyTree=[]; +% MyTree.MyNumber = 13; +% MyTree.MyString = 'Hello World'; +% xml_write('test.xml', MyTree); +% [tree treeName] = xml_read ('test.xml'); +% disp(treeName) +% gen_object_display() +% % See also xml_examples.m +% +% See also: +% xml_write, xmlread, xmlwrite +% +% Written by Jarek Tuszynski, SAIC, jaroslaw.w.tuszynski_at_saic.com +% References: +% - Function inspired by Example 3 found in xmlread function. +% - Output data structures inspired by xml_toolbox structures. + +%% default preferences +DPref.ItemName = 'item'; % name of a special tag used to itemize cell arrays +DPref.CellItem = false; % leave 'item' nodes in cell notation +DPref.ReadAttr = true; % allow reading attributes +DPref.ReadSpec = true; % allow reading special nodes: comments, CData, etc. +DPref.KeepNS = true; % Keep or strip namespace info +DPref.Str2Num = 'smart';% convert strings that look like numbers to numbers +DPref.NoCells = true; % force output to have no cell arrays +DPref.NumLevels = 1e10; % number of recurence levels +DPref.PreserveSpace = false; % Preserve or delete spaces at the beggining and the end of stings? +RootOnly = true; % return root node with no top level special nodes +Debug = false; % show specific errors (true) or general (false)? +tree = []; +RootName = []; + +%% Check Matlab Version +v = ver('MATLAB'); +version = str2double(regexp(v.Version, '\d.\d','match','once')); +if (version<7.1) + error('Your MATLAB version is too old. You need version 7.1 or newer.'); +end + +%% read user preferences +if (nargin>1) + if (isfield(Pref, 'ItemName' )), DPref.ItemName = Pref.ItemName; end + if (isfield(Pref, 'CellItem' )), DPref.CellItem = Pref.CellItem; end + if (isfield(Pref, 'Str2Num' )), DPref.Str2Num = Pref.Str2Num ; end + if (isfield(Pref, 'NoCells' )), DPref.NoCells = Pref.NoCells ; end + if (isfield(Pref, 'NumLevels')), DPref.NumLevels = Pref.NumLevels; end + if (isfield(Pref, 'ReadAttr' )), DPref.ReadAttr = Pref.ReadAttr; end + if (isfield(Pref, 'ReadSpec' )), DPref.ReadSpec = Pref.ReadSpec; end + if (isfield(Pref, 'KeepNS' )), DPref.KeepNS = Pref.KeepNS; end + if (isfield(Pref, 'RootOnly' )), RootOnly = Pref.RootOnly; end + if (isfield(Pref, 'Debug' )), Debug = Pref.Debug ; end + if (isfield(Pref, 'PreserveSpace')), DPref.PreserveSpace = Pref.PreserveSpace; end +end +if ischar(DPref.Str2Num), % convert from character description to numbers + DPref.Str2Num = find(strcmpi(DPref.Str2Num, {'never', 'smart', 'always'}))-1; + if isempty(DPref.Str2Num), DPref.Str2Num=1; end % 1-smart by default +end + +%% read xml file using Matlab function +if isa(xmlfile, 'org.apache.xerces.dom.DeferredDocumentImpl'); + % if xmlfile is a DOMnode than skip the call to xmlread + try + try + DOMnode = xmlfile; + catch ME + error('Invalid DOM node: \n%s.', getReport(ME)); + end + catch %#ok catch for mablab versions prior to 7.5 + error('Invalid DOM node. \n'); + end +else % we assume xmlfile is a filename + if (Debug) % in debuging mode crashes are allowed + DOMnode = xmlread(xmlfile); + else % in normal mode crashes are not allowed + try + try + DOMnode = xmlread(xmlfile); + catch ME + error('Failed to read XML file %s: \n%s',xmlfile, getReport(ME)); + end + catch %#ok catch for mablab versions prior to 7.5 + error('Failed to read XML file %s\n',xmlfile); + end + end +end +Node = DOMnode.getFirstChild; + +%% Find the Root node. Also store data from Global Comment and Processing +% Instruction nodes, if any. +GlobalTextNodes = cell(1,3); +GlobalProcInst = []; +GlobalComment = []; +GlobalDocType = []; +while (~isempty(Node)) + if (Node.getNodeType==Node.ELEMENT_NODE) + RootNode=Node; + elseif (Node.getNodeType==Node.PROCESSING_INSTRUCTION_NODE) + data = strtrim(char(Node.getData)); + target = strtrim(char(Node.getTarget)); + GlobalProcInst = [target, ' ', data]; + GlobalTextNodes{2} = GlobalProcInst; + elseif (Node.getNodeType==Node.COMMENT_NODE) + GlobalComment = strtrim(char(Node.getData)); + GlobalTextNodes{3} = GlobalComment; + % elseif (Node.getNodeType==Node.DOCUMENT_TYPE_NODE) + % GlobalTextNodes{4} = GlobalDocType; + end + Node = Node.getNextSibling; +end + +%% parse xml file through calls to recursive DOMnode2struct function +if (Debug) % in debuging mode crashes are allowed + [tree RootName] = DOMnode2struct(RootNode, DPref, 1); +else % in normal mode crashes are not allowed + try + try + [tree RootName] = DOMnode2struct(RootNode, DPref, 1); + catch ME + error('Unable to parse XML file %s: \n %s.',xmlfile, getReport(ME)); + end + catch %#ok catch for mablab versions prior to 7.5 + error('Unable to parse XML file %s.',xmlfile); + end +end + +%% If there were any Global Text nodes than return them +if (~RootOnly) + if (~isempty(GlobalProcInst) && DPref.ReadSpec) + t.PROCESSING_INSTRUCTION = GlobalProcInst; + end + if (~isempty(GlobalComment) && DPref.ReadSpec) + t.COMMENT = GlobalComment; + end + if (~isempty(GlobalDocType) && DPref.ReadSpec) + t.DOCUMENT_TYPE = GlobalDocType; + end + t.(RootName) = tree; + tree=t; +end +if (~isempty(GlobalTextNodes)) + GlobalTextNodes{1} = RootName; + RootName = GlobalTextNodes; +end + + +%% ======================================================================= +% === DOMnode2struct Function =========================================== +% ======================================================================= +function [s TagName LeafNode] = DOMnode2struct(node, Pref, level) + +%% === Step 1: Get node name and check if it is a leaf node ============== +[TagName LeafNode] = NodeName(node, Pref.KeepNS); +s = []; % initialize output structure + +%% === Step 2: Process Leaf Nodes (nodes with no children) =============== +if (LeafNode) + if (LeafNode>1 && ~Pref.ReadSpec), LeafNode=-1; end % tags only so ignore special nodes + if (LeafNode>0) % supported leaf node types + try + try % use try-catch: errors here are often due to VERY large fields (like images) that overflow java memory + s = char(node.getData); + if (isempty(s)), s = ' '; end % make it a string + % for some reason current xmlread 'creates' a lot of empty text + % fields with first chatacter=10 - those will be deleted. + if (~Pref.PreserveSpace || s(1)==10) + if (isspace(s(1)) || isspace(s(end))), s = strtrim(s); end % trim speces is any + end + if (LeafNode==1), s=str2var(s, Pref.Str2Num, 0); end % convert to number(s) if needed + catch ME % catch for mablab versions 7.5 and higher + warning('xml_io_tools:read:LeafRead', ... + 'This leaf node could not be read and was ignored. '); + getReport(ME) + end + catch %#ok catch for mablab versions prior to 7.5 + warning('xml_io_tools:read:LeafRead', ... + 'This leaf node could not be read and was ignored. '); + end + end + if (LeafNode==3) % ProcessingInstructions need special treatment + target = strtrim(char(node.getTarget)); + s = [target, ' ', s]; + end + return % We are done the rest of the function deals with nodes with children +end + +if (level>Pref.NumLevels+1), return; end % if Pref.NumLevels is reached than we are done + +%% === Step 3: Process nodes with children =============================== +if (node.hasChildNodes) % children present + Child = node.getChildNodes; % create array of children nodes + nChild = Child.getLength; % number of children + + % --- pass 1: how many children with each name ----------------------- + f = []; + for iChild = 1:nChild % read in each child + [cname cLeaf] = NodeName(Child.item(iChild-1), Pref.KeepNS); + if (cLeaf<0), continue; end % unsupported leaf node types + if (~isfield(f,cname)), + f.(cname)=0; % initialize first time I see this name + end + f.(cname) = f.(cname)+1; % add to the counter + end % end for iChild + % text_nodes become CONTENT & for some reason current xmlread 'creates' a + % lot of empty text fields so f.CONTENT value should not be trusted + if (isfield(f,'CONTENT') && f.CONTENT>2), f.CONTENT=2; end + + % --- pass 2: store all the children as struct of cell arrays ---------- + for iChild = 1:nChild % read in each child + [c cname cLeaf] = DOMnode2struct(Child.item(iChild-1), Pref, level+1); + if (cLeaf && isempty(c)) % if empty leaf node than skip + continue; % usually empty text node or one of unhandled node types + elseif (nChild==1 && cLeaf==1) + s=c; % shortcut for a common case + else % if normal node + if (level>Pref.NumLevels), continue; end + n = f.(cname); % how many of them in the array so far? + if (~isfield(s,cname)) % encountered this name for the first time + if (n==1) % if there will be only one of them ... + s.(cname) = c; % than save it in format it came in + else % if there will be many of them ... + s.(cname) = cell(1,n); + s.(cname){1} = c; % than save as cell array + end + f.(cname) = 1; % initialize the counter + else % already have seen this name + s.(cname){n+1} = c; % add to the array + f.(cname) = n+1; % add to the array counter + end + end + end % for iChild +end % end if (node.hasChildNodes) + +%% === Step 4: Post-process struct's created for nodes with children ===== +if (isstruct(s)) + fields = fieldnames(s); + nField = length(fields); + + % --- Post-processing: convert 'struct of cell-arrays' to 'array of structs' + % Example: let say s has 3 fields s.a, s.b & s.c and each field is an + % cell-array with more than one cell-element and all 3 have the same length. + % Then change it to array of structs, each with single cell. + % This way element s.a{1} will be now accessed through s(1).a + vec = zeros(size(fields)); + for i=1:nField, vec(i) = f.(fields{i}); end + if (numel(vec)>1 && vec(1)>1 && var(vec)==0) % convert from struct of + s = cell2struct(struct2cell(s), fields, 1); % arrays to array of struct + end % if anyone knows better way to do above conversion please let me know. + +end + +%% === Step 5: Process nodes with attributes ============================= +if (node.hasAttributes && Pref.ReadAttr) + if (~isstruct(s)), % make into struct if is not already + ss.CONTENT=s; + s=ss; + end + Attr = node.getAttributes; % list of all attributes + for iAttr = 1:Attr.getLength % for each attribute + name = char(Attr.item(iAttr-1).getName); % attribute name + name = str2varName(name, Pref.KeepNS); % fix name if needed + value = char(Attr.item(iAttr-1).getValue); % attribute value + value = str2var(value, Pref.Str2Num, 1); % convert to number if possible + s.ATTRIBUTE.(name) = value; % save again + end % end iAttr loop +end % done with attributes +if (~isstruct(s)), return; end %The rest of the code deals with struct's + +%% === Post-processing: fields of "s" +% convert 'cell-array of structs' to 'arrays of structs' +fields = fieldnames(s); % get field names +nField = length(fields); +for iItem=1:length(s) % for each struct in the array - usually one + for iField=1:length(fields) + field = fields{iField}; % get field name + % if this is an 'item' field and user want to leave those as cells + % than skip this one + if (strcmpi(field, Pref.ItemName) && Pref.CellItem), continue; end + x = s(iItem).(field); + if (iscell(x) && all(cellfun(@isstruct,x)) && numel(x)>1) % it's cell-array of structs + % numel(x)>1 check is to keep 1 cell-arrays created when Pref.CellItem=1 + try % this operation fails sometimes + % example: change s(1).a{1}.b='jack'; s(1).a{2}.b='john'; to + % more convinient s(1).a(1).b='jack'; s(1).a(2).b='john'; + s(iItem).(field) = [x{:}]'; % converted to arrays of structs + catch %#ok + % above operation will fail if s(1).a{1} and s(1).a{2} have + % different fields. If desired, function forceCell2Struct can force + % them to the same field structure by adding empty fields. + if (Pref.NoCells) + s(iItem).(field) = forceCell2Struct(x); + end + end % end catch + end + end +end + +%% === Step 4: Post-process struct's created for nodes with children ===== + +% --- Post-processing: remove special 'item' tags --------------------- +% many xml writes (including xml_write) use a special keyword to mark +% arrays of nodes (see xml_write for examples). The code below converts +% s.item to s.CONTENT +ItemContent = false; +if (isfield(s,Pref.ItemName)) + s.CONTENT = s.(Pref.ItemName); + s = rmfield(s,Pref.ItemName); + ItemContent = Pref.CellItem; % if CellItem than keep s.CONTENT as cells +end + +% --- Post-processing: clean up CONTENT tags --------------------- +% if s.CONTENT is a cell-array with empty elements at the end than trim +% the length of this cell-array. Also if s.CONTENT is the only field than +% remove .CONTENT part and store it as s. +if (isfield(s,'CONTENT')) + if (iscell(s.CONTENT)) + x = s.CONTENT; + for i=length(x):-1:1, if ~isempty(x{i}), break; end; end + if (i==1 && ~ItemContent) + s.CONTENT = x{1}; % delete cell structure + else + s.CONTENT = x(1:i); % delete empty cells + end + end + if (nField==1) + if (ItemContent) + ss = s.CONTENT; % only child: remove a level but ensure output is a cell-array + s=[]; s{1}=ss; + else + s = s.CONTENT; % only child: remove a level + end + end +end + + + +%% ======================================================================= +% === forceCell2Struct Function ========================================= +% ======================================================================= +function s = forceCell2Struct(x) +% Convert cell-array of structs, where not all of structs have the same +% fields, to a single array of structs + +%% Convert 1D cell array of structs to 2D cell array, where each row +% represents item in original array and each column corresponds to a unique +% field name. Array "AllFields" store fieldnames for each column +AllFields = fieldnames(x{1}); % get field names of the first struct +CellMat = cell(length(x), length(AllFields)); +for iItem=1:length(x) + fields = fieldnames(x{iItem}); % get field names of the next struct + for iField=1:length(fields) % inspect all fieldnames and find those + field = fields{iField}; % get field name + col = find(strcmp(field,AllFields),1); + if isempty(col) % no column for such fieldname yet + AllFields = [AllFields; field]; + col = length(AllFields); % create a new column for it + end + CellMat{iItem,col} = x{iItem}.(field); % store rearanged data + end +end +%% Convert 2D cell array to array of structs +s = cell2struct(CellMat, AllFields, 2); + +%% ======================================================================= +% === str2var Function ================================================== +% ======================================================================= +function val=str2var(str, option, attribute) +% Can this string 'str' be converted to a number? if so than do it. +val = str; +len = numel(str); +if (len==0 || option==0), return; end % Str2Num="never" of empty string -> do not do enything +if (len>10000 && option==1), return; end % Str2Num="smart" and string is very long -> probably base64 encoded binary +%digits = '[Inf,NaN,pi,\t,\n,\d,\+,\-,\*,\.,e,i, ,E,I,\[,\],\;,\,]'; +digits = '(Inf)|(NaN)|(pi)|[\t\n\d\+\-\*\.ei EI\[\]\;\,]'; +s = regexprep(str, digits, ''); % remove all the digits and other allowed characters +if (~all(~isempty(s))) % if nothing left than this is probably a number + if (~isempty(strfind(str, ' '))), option=2; end %if str has white-spaces assume by default that it is not a date string + if (~isempty(strfind(str, '['))), option=2; end % same with brackets + str(strfind(str, '\n')) = ';';% parse data tables into 2D arrays, if any + if (option==1) % the 'smart' option + try % try to convert to a date, like 2007-12-05 + datenum(str); % if successful than leave it as string + catch %#ok % if this is not a date than ... + option=2; % ... try converting to a number + end + end + if (option==2) + if (attribute) + num = str2double(str); % try converting to a single number using sscanf function + else + num = str2num(str); %#ok % try converting to a single number or array using eval function + end + if(isnumeric(num) && numel(num)>0), val=num; end % if convertion to a single was succesful than save + end +end + +%% ======================================================================= +% === str2varName Function ============================================== +% ======================================================================= +function str = str2varName(str, KeepNS) +% convert a sting to a valid matlab variable name +if(KeepNS) + str = regexprep(str,':','_COLON_', 'once', 'ignorecase'); +else + k = strfind(str,':'); + if (~isempty(k)) + str = str(k+1:end); + end +end +str = regexprep(str,'-','_DASH_' ,'once', 'ignorecase'); +if (~isvarname(str)) + str = genvarname(str); +end + +%% ======================================================================= +% === NodeName Function ================================================= +% ======================================================================= +function [Name LeafNode] = NodeName(node, KeepNS) +% get node name and make sure it is a valid variable name in Matlab. +% also get node type: +% LeafNode=0 - normal element node, +% LeafNode=1 - text node +% LeafNode=2 - supported non-text leaf node, +% LeafNode=3 - supported processing instructions leaf node, +% LeafNode=-1 - unsupported non-text leaf node +switch (node.getNodeType) + case node.ELEMENT_NODE + Name = char(node.getNodeName);% capture name of the node + Name = str2varName(Name, KeepNS); % if Name is not a good variable name - fix it + LeafNode = 0; + case node.TEXT_NODE + Name = 'CONTENT'; + LeafNode = 1; + case node.COMMENT_NODE + Name = 'COMMENT'; + LeafNode = 2; + case node.CDATA_SECTION_NODE + Name = 'CDATA_SECTION'; + LeafNode = 2; + case node.DOCUMENT_TYPE_NODE + Name = 'DOCUMENT_TYPE'; + LeafNode = 2; + case node.PROCESSING_INSTRUCTION_NODE + Name = 'PROCESSING_INSTRUCTION'; + LeafNode = 3; + otherwise + NodeType = {'ELEMENT','ATTRIBUTE','TEXT','CDATA_SECTION', ... + 'ENTITY_REFERENCE', 'ENTITY', 'PROCESSING_INSTRUCTION', 'COMMENT',... + 'DOCUMENT', 'DOCUMENT_TYPE', 'DOCUMENT_FRAGMENT', 'NOTATION'}; + Name = char(node.getNodeName);% capture name of the node + warning('xml_io_tools:read:unkNode', ... + 'Unknown node type encountered: %s_NODE (%s)', NodeType{node.getNodeType}, Name); + LeafNode = -1; +end + + diff --git a/linearfit.m b/linearfit.m new file mode 100644 index 0000000..8ca879c --- /dev/null +++ b/linearfit.m @@ -0,0 +1,67 @@ +function [slope, offset,R2,SCE,P,T] = linearfit(y,x) +%LINEARFIT - One line description goes here. +% [slope,offset,R2,SCE,P,T] = linearfit(Y,X) +% Solves the equation: +% Y = slope * X + offset +% Y: Data to fit. Should be a N-element vector or a 2D matrix with N lines +% X: Fitting data. Should be a N-element vector. If missing: X=1:length(Y) +% R2: Explained variance, also known as the square of the Pearson +% Product-Moment Correlation Coefficient (R=sqrt(R2)) +% SCE: Sum of of the squared distance between Y and the linear fit +% P: Non directional probability assuming normal distribution. +% When a specific hypothesis is made on the direction of the correlation +% (slope > 0 OR slope < 0) you should divide P by 2 to get the +% directional p-value +% T: Approximate T-value corresponding to the R + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-20 Creation +% KND 2008-07-01 Check X, Y order in inputs +% +% ----------------------------- Script History --------------------------------- +if nargin>1 && isvector(y) && ~isvector(x) + warning('X and Y were inverted as inputs!') + tmp=y; + y=x; + x=tmp; + clear tmp; +end +if numel(y)==max(size(y)) + y=y(:); +end +if nargin==1 + x=1:size(y,1); +end +x=x(:); +x=[x ones(size(x))]; +if(size(y,1) ~= size(x,1)) + error('Length of x and y must be the same'); +end +m=(y'/x')'; +slope=m(1,:); +offset=m(2,:); +RES = (x*m-y); +SCE = sum(RES.^2,1); +my=x(:,2)*mean(y,1); +SCY = sum((y-my).^2,1); +SCER= sum((x*m-my).^2); +if SCY>0 + R2 = SCER./SCY; +else + R2=NaN; +end +if nargout>3 + df= length(x)-2; + T = sqrt(R2)./sqrt((1-R2)./(df)); + P = betainc( df ./ (df + T.*T), df/2, 0.5); +end + + +return \ No newline at end of file diff --git a/ll.m b/ll.m new file mode 100644 index 0000000..0be196a --- /dev/null +++ b/ll.m @@ -0,0 +1,88 @@ +function [varargout]=ll(varargin) +% ll - synonym of DIR command (display bytes & date info) +% ll(pat) list file according to pattern and display output +% +% f=ll(pat) ouputs a file structure. +% Note that it uses 'ls' utility in Unix which allow advanced regexp +% e.g. f=ll('~/.c*/*') + +if nargout==0 + if isunix + if ismac && nargin==0 + varargin={pwd}; + end + system(['ls -l ' sprintf('%s ', varargin{:})]); + else + f=dir(varargin{:}); + nf=numel(f); + %sep = repmat(sprintf('\t'), [nf,1]); + %filedates = datevec([f.datenum]); + %if any(strmatch('-t', varargin(:))) + [i,i]=sort([f.datenum]); + %end + f=f(i); + for i=1:numel(f) + mfb = max([f.bytes]); + if isequal(mfb,0) + mfb = 0; + else + mfb = 1+ceil(log10(mfb)); + end + + fprintf(['%s\t%' sprintf(' %d',mfb) 'd\t%s\n'], datestr(f(i).datenum,31), f(i).bytes, f(i).name); + end + % end + % try + % disp([ ... + % datestr(datevec([f.datenum]),31) ... %strvcat({f.date}) ... + % sep ... + % num2str([f.bytes]') ... %strvcat(regexprep(cellstr(num2str([f.bytes]')), '^(\s*)0$','')) + % sep ... + % strvcat({f.name}) ... %names ... + % ]); + % catch + % disp([ ... + % datestr(datevec({f.date}),31) ... %strvcat({f.date}) ... + % sep ... + % num2str([f.bytes]') ... %strvcat(regexprep(cellstr(num2str([f.bytes]')), '^(\s*)0$','')) + % sep ... + % strvcat({f.name}) ... %names ... + % ]); + % end + end +else + if isunix + if ismac + if nargin==0 + varargin={[pwd]}; + end + if isdir(varargin{end}) + varargin{end}=[varargin{end} filesep '*'] + end + [status,s]=system(['\ls -paUogd ' sprintf('%s ', varargin{:})]) + + [attr types bytes days months times names]=strread(s,'%s%d%d%s%s%s%s%*[^\n]'); + dates = [strvcat(days) repmat(' ', numel(days),1) strvcat(months) repmat(' ', numel(days),1) strvcat(times)] + datenums = datenum(dates,31); + else + [status,s]=system(['\ls -paUogd --time-style="long-iso" --block-size=1 ' sprintf('%s ', varargin{:})]); + [attr types bytes days times names] =strread(s,'%s%d%d%s%s%s%*[^\n]'); + dates = [strvcat(days) repmat(' ', numel(days),1) strvcat(times)]; + datenums = datenum(dates,31); + end + if status + varargout={[]}; + return + end + + varargout = {struct(... + 'name', names,... + 'date', cellstr(datestr(datenums)),... + 'bytes',num2cell(bytes),... + 'isdir',num2cell(types==2),... + 'datenum',num2cell(datenums)... + )}; + else + varargout={dir(varargin{:})}; + end +end diff --git a/loadallmat.m b/loadallmat.m new file mode 100644 index 0000000..eba1498 --- /dev/null +++ b/loadallmat.m @@ -0,0 +1,22 @@ +function [varargout]=loadallmat(directory) +%loadallmat - load all MAT files from a directory +% +if nargin<1 + directory=pwd; +end + +f=dir(fullfile(directory,'*.mat')); +for i=1:length(f) + [ignore,vname]=fileparts(f(i).name); + disp(sprintf('Loading %s...', vname)); + eval(sprintf('vars.%s=load(''%s'');',vname,fullfile(directory,f(i).name))); +end +if nargout==1 + varargout={vars}; +else + vnames=fieldnames(vars); + + for i=1:length(vnames) + assignin('base', vnames{i}, getfield(vars, vnames{i})); + end +end diff --git a/loadfield.m b/loadfield.m new file mode 100644 index 0000000..ef987f8 --- /dev/null +++ b/loadfield.m @@ -0,0 +1,25 @@ +function X = loadfield(filename,fieldname) +%LOADFIELD - Load a given variable from a .mat file +% [X] = loadfield(filename,fieldname) +% +% Example +% >> a=loadfield('test.mat', 'a') +% +% See also: load, getfield + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-11 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<2 + error('No field/vraible given!') +end +X=getfield(load(filename, fieldname), fieldname); \ No newline at end of file diff --git a/localmax.m b/localmax.m new file mode 100644 index 0000000..3451024 --- /dev/null +++ b/localmax.m @@ -0,0 +1,84 @@ +function [Y,I] = localmax(X,N,dim) +%LOCALMAX - Finds local maxima +% [Y,I] = localmax(X) +% [Y,I] = localmax(X,N) +% Looks for local maxima in vector X. +% Search window can be enlarged using input N. Default: N=1, ie. +% each local maximum must be greater than or equal to its immediate +% neighbours +% +% Example +% >> localmax +% +% See also: max + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-27 Creation +% KND 2008-09-18 Only the first value of a constant plateau is returned +% KND 2009-03-25 try/catch in case there is no license for the stats toolbox +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + error('No data!') +end +if nargin<2 + N=1; +end +if numel(X)~=max(size(X)) + error('X should be unidimensional') +end + +X=X(:)'; +n=length(X); + +if N>=n + N=n-1; + error(sprintf('Not enough elements in X (of length %d)\nSearch window should be reduced to: N=%d', n, N)); +end +t=1:n; +try + XX=[buffer(X,2*N+1,2*N,repmat(X(1),1,2*N)) ... + fliplr(flipud(buffer(fliplr(X(end-2*N+1:end)),2*N+1,2*N, repmat(X(end),1,2*N))))]; + XX=XX(:,N+1:end-N); +catch + XX=X; + for i=1:N; + XX=[X(1,[repmat(1,1,i) t(1:end-i)]); ... + XX; ... + X(1,[t(i+1:end) repmat(t(end),1,i)])]; + end +end + +YY=repmat(X,[2*N+1 1]); + +I=find(all(YY>=XX)); +dI=diff(I)==1; +I(logical([0 dI])) = []; +Y=X(I); + +return + +Y=reshape(Y,[length(Y)/prod(sX(3:end)) sX(3:end)]); +Y=ipermute(Y,pX); +I=mod(I-1,prod(sX(2)))+1; +I=reshape(I,[length(I)/prod(sX(3:end)) sX(3:end)]); +I=ipermute(I,pX); + +return + + + +N = length(x); % N: Number of elements in time series +x_prev = [x(1) x(1:(N-1))]; % x_prev: Previous element in time series +x_next = [x(2:N) x(N)]; % x_next: Next element in time series +f = ( (x<=x_prev) & (x<=x_next) ); % f: True where x takes on a local +% minimum value + diff --git a/localmin.m b/localmin.m new file mode 100644 index 0000000..f838cd6 --- /dev/null +++ b/localmin.m @@ -0,0 +1,8 @@ +function [values,ix] = localmin(x) +N = length(x); % N: Number of elements in time series +x_prev = [x(1) x(1:(N-1))]; % x_prev: Previous element in time series +x_next = [x(2:N) x(N)]; % x_next: Next element in time series +f = ( (x<=x_prev) & (x<=x_next) ); % f: True where x takes on a local + % minimum value + + diff --git a/locmax.m b/locmax.m new file mode 100644 index 0000000..6be7ee7 --- /dev/null +++ b/locmax.m @@ -0,0 +1,81 @@ +function varargout = localMaximum(x,minDist, exculdeEqualPoints) +% function varargout = localMaximum(x,minDist, exculdeEqualPoints) +% +% This function returns the indexes\subscripts of local maximum in the data x. +% x can be a vector or a matrix of any dimension +% +% minDist is the minimum distance between two peaks (local maxima) +% minDist should be a vector in which each argument corresponds to it's +% relevant dimension OR a number which is the minimum distance for all +% dimensions +% +% exculdeEqualPoints - is a boolean definning either to recognize points with the same value as peaks or not +% x = [1 2 3 4 4 4 4 4 4 3 3 3 2 1]; +% will the program return all the '4' as peaks or not - defined by the 'exculdeEqualPoints' +% localMaximum(x,3) +% ans = +% 4 5 6 7 8 9 11 12 +% +% localMaximum(x,3,true) +% ans = +% 4 7 12 +% +% +% Example: +% a = randn(100,30,10); +% minDist = [10 3 5]; +% peaks = localMaximum(a,minDist); +% +% To recieve the subscript instead of the index use: +% [xIn yIn zIn] = localMaximum(a,minDist); +% +% To find local minimum call the function with minus the variable: +% valleys = localMaximum(-a,minDist); + + if nargin < 3 + exculdeEqualPoints = false; + if nargin < 2 + minDist = size(x)/10; + end + end + + if isempty(minDist) + minDist = size(x)/10; + end + + dimX = length ( size(x) ); + if length(minDist) ~= dimX + % In case minimum distance isn't defined for all of x dimensions + % I use the first value as the default for all of the dimensions + minDist = minDist( ones(dimX,1) ); + end + + % validity checks + minDist = ceil(minDist); + minDist = max( [minDist(:)' ; ones(1,length(minDist))] ); + minDist = min( [minDist ; size(x)] ); + + % --------------------------------------------------------------------- + if exculdeEqualPoints + % this section comes to solve the problem of a plato + % without this code, points with the same hight will be recognized as peaks + y = sort(x(:)); + dY = diff(y); + % finding the minimum step in the data + minimumDiff = min( dY(dY ~= 0) ); + %adding noise which won't affect the peaks + x = x + rand(size(x))*minimumDiff; + end + % --------------------------------------------------------------------- + + + se = ones(minDist); + X = imdilate(x,se); + f = find(x == X); + + + if nargout + [varargout{1:nargout}] = ind2sub( size(x), f ); + else + varargout{1} = f; + end diff --git a/lowerfields.m b/lowerfields.m new file mode 100644 index 0000000..8134359 --- /dev/null +++ b/lowerfields.m @@ -0,0 +1,23 @@ +function [t]=lowerfields(s,force) +% lowerfields - lower case the fields of a struct +if nargin<2 + force=0; +end + +fn=fieldnames(s); +t=[]; +for i=1:length(fn) + if force + t=setfield(t, lower(fn{i}), getfield(s, fn{i})); + else + if length(strmatch(lower(fn{i}), lower(fn)))>1 & ~isequal(lower(fn{i}), fn{i}) + if nargin<2 + warning(sprintf('Field %s is not lower-cased (use option force=1 to override)', fn{i})) + end + t=setfield(t, fn{i}, getfield(s, fn{i})); + else + t=setfield(t, lower(fn{i}), getfield(s, fn{i})); + end + end +end + diff --git a/lowpass.m b/lowpass.m new file mode 100644 index 0000000..afeb19b --- /dev/null +++ b/lowpass.m @@ -0,0 +1,147 @@ +function [xf] = lowpass(x,rf,tdim,df) +% lowpass - easy to use low pass filter (zero phase) +% [xf]=lowpass(x,rf); +% [xf]=lowpass(x,rf,tdim); +% [xf]=lowpass(x,rf,tdim,df); +% lowpass data in x under frequency relative frequency: +% rf=Fc/FS (default: 0.01) +% where Fc is the cutting frequency, and FS is the sampling rate +% Filtering is done along dimension tdim (default: the longest dimension) +% df is the relative width of the attenuation: +% df=(Fc-Fc2)/FS (default: 0.001) +% A causal fft algorithm is applied (i.e. no phase shift). The filter +% functions is constructed from a Hamming window. +% ___________________________ +% :\ +% : \ +% : \ +% : \ +% : \ +% : \________ +% : : +% Fc/FS=rf (rf+df)=Fs/FS +% +% Based on Mario Chavez's LowPassFilter (used as sub-fuction) + +if nargin<2 % Default: ~6Hz/625Hz ~ 100ms sliding window + rf=.01; +end +if nargin<3 % Default: 6Hz/625Hz par défaut ~=~ 100ms sliding window + [ignore,tdim]=max(size(x)); +end +if nargin<4 % Default: ~0.5Hz/625Hz + df=.001; +end + +sx=size(x); +px=[tdim setdiff(1:ndims(x), tdim)]; +if tdim>1 + x=permute(x,px); +end +%Ensure x has an even number of data point +if rem(sx(tdim),2) + x = [x ; zeros([1 sx(px(2:end))])]; +end + + +% Construct the filter function H(f) using frequencies in Nyquist units +N = sx(tdim)+rem(sx(tdim),2); +B = fir2(N-1,[0 rf*2 (rf+df)*2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +H=repmat(H',[ 1 sx(px(2:end))] ); +% Pre-allocate xf +%xf=x*0; +k=1; +xf = real(ifft(fft(x) .* H)); + +xf = reshape(ipermute(xf(1:sx(tdim),:),px),sx); + +return + + +function xf = lowpassFilter(x,Fs,Fp2) +% function XF = lowpassFilter(X,FS,FP2) +% +% Bandpass filter for the signal x. An causal fft algorithm +% is applied (i.e. no phase shift). The filter functions is +% constructed from a Hamming window. +% +% Fs : sampling frequency +% +% The passband (Fp2) and stop band (Fs2) are defined as +% +% --------------------------- +% |\ +% | \ +% | \ +% | \ +% | ----------------- +% | | +% Fp2 Fs2 = Fp2 + 0.5 (Hz) +% +% +% +% If NO OUTPUTS arguments are assigned the filter function H(f) and +% impulse response are plotted. +% +% NOTE: for long data traces the filter is very slow. +% +% EXEMPLE +% x= sin(2*pi*12*[0:1/200:10])+sin(2*pi*30*[0:1/200:10]) +% y=lowpassFilter(x,200,10); lowpass filter between 0 and 10 Hz +%------------------------------------------------------------------------ +% Originally produced by the Helsinki University of Technology, +% Adapted by Mariecito SCHMUCKEN 2001 +%------------------------------------------------------------------------ +Fs2 = Fp2 + 0.5; + +if size(x,1) == 1 + x = x'; +end +% Make x even +Norig = size(x,1); +if rem(Norig,2) + x = [x' zeros(size(x,2),1)]'; +end + +% Normalize frequencies +Ns2 = Fs2/(Fs/2); +Np2 = Fp2/(Fs/2); + +% Construct the filter function H(f) +N = size(x,1); +Nh = N/2; + +% B = fir2(N-1,[0 Ns1 Np1 Np2 Ns2 1],[0 0 1 1 0 0]); +B = fir2(N-1,[0 Np2 Ns2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +IPR = real(ifft(H)); + +% Visual display if off +% if nargout == 0 +% figure, +% subplot(2,1,1) +% f = Fs*(0:Nh-1)/(N); +% plot(f,H(1:Nh)); +% xlim([0 2*Fs2]) +% ylim([0 1]); +% title('Filter function H(f)') +% xlabel('Frequency (Hz)') +% subplot(2,1,2) +% plot((1:Nh)/Fs,IPR(1:Nh)) +% xlim([0 2/Fp2]) +% xlabel('Time (sec)') +% ylim([min(IPR) max(IPR)]) +% title('Impulse response') +% end + + +if size(x,2) > 1 + for k=1:size(x,2) + xf(:,k) = real(ifft(fft(x(:,k)) .* H')); + end + xf = xf(1:Norig,:); +else + xf = real(ifft(fft(x') .* H)); + xf = xf(1:Norig); +end diff --git a/lowpassfilter.m b/lowpassfilter.m new file mode 100644 index 0000000..4fb49a8 --- /dev/null +++ b/lowpassfilter.m @@ -0,0 +1,156 @@ +function [xf] = lowpassfilter(x,rf,tdim,df) +% lowpassfilter - easy to use low pass filter (zero phase) +% [xf]=lowpassfilter(x,rf); +% [xf]=lowpassfilter(x,rf,tdim); +% [xf]=lowpassfilter(x,rf,tdim,df); +% Low-pass filtering of data x below relative frequency: +% rf=Fc/FS (default: 0.01) +% where Fc is the cutting frequency and FS is the sampling rate +% Filtering is done along dimension tdim (default: the longest dimension) +% df is the relative width of the attenuation: +% df=(Fc-Fc2)/FS (default: 0.001) +% ___________________________ +% :\ +% : \ +% : \ +% : \ +% : \ +% : \________ +% : : +% Fc/FS=rf (rf+df)=Fc2/FS +% +% A causal fft algorithm is applied (i.e. no phase shift). The filter +% functions is constructed from a Hamming window. + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Based on Mario Chavez's LowPassFilter & EEGLAB eegfiltfft +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-04-19 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<2 % Default: ~6Hz/625Hz ~ 100ms sliding window + rf=.05; +end +if nargin<3 % Default longest dimension + [ignore,tdim]=max(size(x)); +end +if nargin<4 % Default: ~0.5Hz/625Hz + df=.001; +end + +sx=size(x); +px=[tdim setdiff(1:ndims(x), tdim)]; +if tdim>1 + x=permute(x,px); +end +%Ensure x has an even number of data point +if rem(sx(tdim),2) + x = [x ; zeros([1 sx(px(2:end))])]; +end + +% Construct the filter function H(f) using frequencies in Nyquist units +N = sx(tdim)+rem(sx(tdim),2); +B = fir2(N-1,[0 rf*2 (rf+df)*2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +H=repmat(H',[ 1 sx(px(2:end))] ); +k=1; +xf = real(ifft(fft(x) .* H)); +xf = ipermute(reshape(xf(1:sx(tdim),:),sx(px)),px); + +return + +% This is the original function by Mario: + +function xf = lowpassFilter(x,Fs,Fp2) +% function XF = lowpassFilter(X,FS,FP2) +% +% Bandpass filter for the signal x. An causal fft algorithm +% is applied (i.e. no phase shift). The filter functions is +% constructed from a Hamming window. +% +% Fs : sampling frequency +% +% The passband (Fp2) and stop band (Fs2) are defined as +% +% --------------------------- +% |\ +% | \ +% | \ +% | \ +% | ----------------- +% | | +% Fp2 Fs2 = Fp2 + 0.5 (Hz) +% +% +% +% If NO OUTPUTS arguments are assigned the filter function H(f) and +% impulse response are plotted. +% +% NOTE: for long data traces the filter is very slow. +% +% EXEMPLE +% x= sin(2*pi*12*[0:1/200:10])+sin(2*pi*30*[0:1/200:10]) +% y=lowpassFilter(x,200,10); lowpass filter between 0 and 10 Hz +%------------------------------------------------------------------------ +% Originally produced by the Helsinki University of Technology, +% Adapted by Mariecito SCHMUCKEN 2001 +%------------------------------------------------------------------------ +Fs2 = Fp2 + 0.5; + +if size(x,1) == 1 + x = x'; +end +% Make x even +Norig = size(x,1); +if rem(Norig,2) + x = [x' zeros(size(x,2),1)]'; +end + +% Normalize frequencies +Ns2 = Fs2/(Fs/2); +Np2 = Fp2/(Fs/2); + +% Construct the filter function H(f) +N = size(x,1); +Nh = N/2; + +% B = fir2(N-1,[0 Ns1 Np1 Np2 Ns2 1],[0 0 1 1 0 0]); +B = fir2(N-1,[0 Np2 Ns2 1],[1 1 0 0]); +H = abs(fft(B)); % Make zero-phase filter function +IPR = real(ifft(H)); + +% Visual display if off +% if nargout == 0 +% figure, +% subplot(2,1,1) +% f = Fs*(0:Nh-1)/(N); +% plot(f,H(1:Nh)); +% xlim([0 2*Fs2]) +% ylim([0 1]); +% title('Filter function H(f)') +% xlabel('Frequency (Hz)') +% subplot(2,1,2) +% plot((1:Nh)/Fs,IPR(1:Nh)) +% xlim([0 2/Fp2]) +% xlabel('Time (sec)') +% ylim([min(IPR) max(IPR)]) +% title('Impulse response') +% end + + +if size(x,2) > 1 + for k=1:size(x,2) + xf(:,k) = real(ifft(fft(x(:,k)) .* H')); + end + xf = xf(1:Norig,:); +else + xf = real(ifft(fft(x') .* H)); + xf = xf(1:Norig); +end diff --git a/lpass.m b/lpass.m new file mode 100644 index 0000000..b6634cd --- /dev/null +++ b/lpass.m @@ -0,0 +1,61 @@ +function [z] = lpass(x, f, FS,tdim) +% lpass - easy to use lw pass filter (zero phase) +% [xf]=lpass(x,[f, FS, tdim]) +% Low-passes data in x ... +% with a cutting frequency f [default=5Hz] +% assuming x in sampled at FS Hz [def=625]; +% on the tdim dimension. If not given: +% - x should be a [ 6 conditions x Nchannels x Tsamples ] +% - or: tdim is ssumed to be the longest dimension... don't laugh +% +% Based on Mario Chavez's LowPassFilter +if not(exist('lowpassFilter')) + global HOMEDIR + addpath(fullfile(HOMEDIR, 'matlab', 'mario')) + addpath(fullfile(HOMEDIR, 'matlab', 'mario')) +end + +if nargin<2 % 6Hz par défaut ~=~ 100ms sliding window + f=6; +end + +if nargin < 3 + FS=625; +end + +if nargin > 3 + s1=size(x); + n1=ndims(x); + t=tdim; + s2=[prod(s1(1:t-1)) s1(t) prod(s1(t+1:end))]; + z=reshape(x,s2); + for i=1:size(z,1) + for j=1:size(z,3) + z(i,:,j)=lowpassFilter(squeeze(z(i,:,j)),FS,f); + end + end + + z=reshape(z, s1); + return +end +if ndims(x)==3 & size(x,3)<6 + for i=1:size(x,3); + z(:,:,i)=lowpassFilter(shiftdim(permute(x(:,:,i), [3 2 1])),FS,f)'; + end + if size(z, 2)==1 + z=permute(z, [2 1 3]); + end +else + s1=size(x); + n1=ndims(x); + [ignore,t]=max(s1); + s2=[prod(s1(1:t-1)) s1(t) prod(s1(t+1:end))]; + z=reshape(x,s2); + for i=1:size(z,1) + for j=1:size(z,3) + z(i,:,j)=lowpassFilter(squeeze(z(i,:,j)),FS,f); + end + end + + z=reshape(z, s1); +end \ No newline at end of file diff --git a/match.m b/match.m new file mode 100644 index 0000000..e10d1b1 --- /dev/null +++ b/match.m @@ -0,0 +1,14 @@ +function [I]=match(A,B,varargin) +% match() - find indices of matching items from an array +if iscell(A) && iscell(B) + if all(vertvec(cellfun(@ischar,A))) && ... + all(vertvec(cellfun(@ischar,B))) + I=cellfun2(@strmatch,A,B,'exact'); + v=cellfun(@isempty,I); + if any(v(:)) + warning('match:Nonmatchs','Some values from A are not in B, these indices were set to 0'); + I(v)={0}; + end + I=cell2mat(I); + end +end diff --git a/matlabupdate.m b/matlabupdate.m new file mode 100644 index 0000000..16c8bb7 --- /dev/null +++ b/matlabupdate.m @@ -0,0 +1,35 @@ +function []=matlabupdate(mpath) +% matlabupdate() - Add matlab functions in the path to attempt forward compatibility +% +% matlabupdate(mpath) add the subdirectories found in the specified path +% If a directory matches a date pattern (e.g., 2007-12-31), then it +% is included only if the running version of matlab is older. +% All other subdirectories will be unconditionally added +% +% default: mpath = folder of 'matlabupdate.m'/matlabupdate', +% e.g., g:\ndiayek\matlab\matlabupdate +% +if nargin<1 + mpath=mfilename('fullpath'); +end +dat=0; +try + dat=datenum(version('-date')); +end +f=dir(mpath); +f([f.isdir]==0)=[]; +f(strmatch('.', {f.name}, 'exact'))=[]; +f(strmatch('..', {f.name}, 'exact'))=[]; +f(strmatch('.svn', {f.name}, 'exact'))=[]; + +for dats={f.name} + t=1; %unconditionnlly add "non-calendar" directories + try + t = datenum(dats{1},'yyyy-mm-dd') >= dat; + end + if t + fprintf('Adding to the path: %s\n', fullfile(mpath, dats{1})) + addpath(fullfile(mpath, dats{1})) + end +end + diff --git a/matlabupdate/2000-11-02/strtrim.m b/matlabupdate/2000-11-02/strtrim.m new file mode 100644 index 0000000..faf03d7 --- /dev/null +++ b/matlabupdate/2000-11-02/strtrim.m @@ -0,0 +1,44 @@ +function S=strtrim(A) +%STRTRIM Remove insignificant whitespace on both sides. +% S = STRTRIM(M) removes insignificant whitespace from string M. +if iscell(A) + S=cell(size(A)); + for i=1:numel(A) + S{i}=strtrim(A{i}); + end +else + S=deblank(fliplr(deblank(fliplr(strvcat(A))))); +end +return + + + +%STRTRIM Remove insignificant whitespace. +% S = STRTRIM(M) removes insignificant whitespace from string M. +% +% Whitespace characters are the following: V = char([9 10 11 12 13 32]), which +% return true from ISSPACE(V). Per definition, insignificant leading +% whitespace leads the first non-whitespace character, and insignificant +% trailing whitespace follows the last non-whitespace character in a string. +% +% B = STRTRIM(A) removes insignificant whitespace from the char array. +% +% D = STRTRIM(C), when C is a cell array of strings, removes insignificant +% whitespace from each element of C. +% +% INPUT PARAMETERS: +% M: any one of a char row vector, 2D char array, or an N-D cell array of +% strings. +% +% RETURN PARAMETERS: +% M: any one of a char row vector, 2D char array or an N-D cell array of +% strings. +% +% EXAMPLES: +% M = STRTRIM(M) removes whitespace from the front and rear of M. +% +% See also ISSPACE, CELLSTR, DEBLANK. + +% Copyright 1984-2003 The MathWorks, Inc. +% $Revision: 1.1.6.5 $ $Date: 2004/04/10 23:33:02 $ +%============================================================================== diff --git a/matlabupdate/2004-10-13/isscalar.m b/matlabupdate/2004-10-13/isscalar.m new file mode 100644 index 0000000..c09238c --- /dev/null +++ b/matlabupdate/2004-10-13/isscalar.m @@ -0,0 +1,12 @@ +function t = isscalar(x) +%ISSCALAR True for scalar input. +% +% ISSCALAR(X) returns 1 if it's argument is a scalar and 0 otherwise. +% Note that this function does not consider the empty matrix a scalar. + +% Author: Peter J. Acklam +% Time-stamp: 2002-03-03 13:50:54 +0100 +% E-mail: pjacklam@online.no +% URL: http://home.online.no/~pjacklam +error(nargchk(1, 1, nargin)); +t = all(size(x) == 1); diff --git a/matlabupdate/2004-10-13/isvector.m b/matlabupdate/2004-10-13/isvector.m new file mode 100644 index 0000000..ef7fea7 --- /dev/null +++ b/matlabupdate/2004-10-13/isvector.m @@ -0,0 +1,4 @@ +function [tf]=isvector(X) +%isvector - Test whether X is a vector (i.e. unidimensional) +%NB Returns 1 for empty +tf=isequal(prod(size(X)), max(size(X))); diff --git a/matlabupdate/2006-08-03/cast.m b/matlabupdate/2006-08-03/cast.m new file mode 100644 index 0000000..a2a81fe --- /dev/null +++ b/matlabupdate/2006-08-03/cast.m @@ -0,0 +1,13 @@ +%CAST Cast a variable to a different data type or class. +% B = CAST(A,NEWCLASS) casts A to class NEWCLASS. A must be convertible to +% class NEWCLASS. 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For example, +% +% S = ['1 2' str2num(S) => [1 2;3 4] +% '3 4'] +% +% The numbers in the string matrix S should be ASCII character +% representations of a numeric values. Each number may contain digits, +% a decimal point, a leading + or - sign, an 'e' or 'd' preceding a +% power of 10 scale factor, and an 'i' or 'j' for a complex unit. +% +% If the string S does not represent a valid number or matrix, +% STR2NUM(S) returns the empty matrix. [X,OK]=STR2NUM(S) will +% return OK=0 if the conversion failed. +% +% CAUTION: STR2NUM uses EVAL to convert the input argument, so side +% effects can occur if the string contains calls to functions. Use +% STR2DOUBLE to avoid such side effects or when S contains a single +% number. +% +% Also spaces can be significant. For instance, str2num('1+2i') and +% str2num('1 + 2i') produce x = 1+2i while str2num('1 +2i') produces +% x = [1 2i]. These problems are also avoided when you use STR2DOUBLE. +% +% See also STR2DOUBLE, NUM2STR, HEX2NUM, CHAR. + +% Copyright 1984-2003 The MathWorks, Inc. +% $Revision: 5.31.4.3 $ $Date: 2004/04/10 23:32:52 $ + +if isempty(s) + x = []; + ok=false; + return +end +if ~ischar(s) || ndims(s)>2 + error('Requires string or character array input.') +end +[m,n] = size(s); +if m==1, + % Replace any char(0) characters with spaces + s(s==char(0)) = ' '; + [x,ok] = protected_conversion(['[' s ']']); % Always add brackets +else + semi = ';'; + space = ' '; + if ~any(any(s == '[' | s == ']')), % String does not contain brackets + o = ones(m-1,1); + s = [['[';space(o)] s [semi(o) space(o);' ]']]'; + elseif ~any(any(s(1:m-1,:) == semi)), % No ;'s in non-last rows + s = [s,[semi(ones(m-1,1));space]]'; + else % Put ;'s where appropriate + spost = space(ones(m,1)); + for i = 1:m-1, + last = find(s(i,:) ~= space,1,'last'); + if s(i,n-last+1) ~= semi, + spost(i) = semi; + end + end + s = [s,spost]'; + end + [x,ok] = protected_conversion(s); +end +if isnumeric(x) + return +end +if ischar(x) || iscell(x) + x = []; + ok = false; +end + +function [STR2NUM_VaR,ok] = protected_conversion(STR2NUM_StR) +% Try to convert the string into a number. If this fails, return [] and ok=0 +% Protects variables in STR2NUM from "variables" in s. + +STR2NUM_LaSTeRR = lasterr; +try + STR2NUM_VaR = eval(STR2NUM_StR); + ok = true; +catch + STR2NUM_VaR = []; + ok = false; + lasterr(STR2NUM_LaSTeRR) % Preseve lasterr +end diff --git a/max2.m b/max2.m new file mode 100644 index 0000000..fb25626 --- /dev/null +++ b/max2.m @@ -0,0 +1,40 @@ +function [V,I] = max2(X,ignore,dim) +%MAX2 - Maximum across multiple dimensions +% [V,I] = max2(X,[],dim) +% V is the maximum value across given dimension (dim) +% I is the index in the given dimensions +% (Note that [] must be here for compatibility reasons with max function) +% +% Example +% >> max2(magic(3), [], [1 2]) +% 9 +% Finds the maximum in rows and columns of the magic square +% +% See also: max, imax + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-20 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<2 + [V,I]=max(X); +elseif length(dim)==1 + [V,I]=max(X,[],dim); +else + sX=size(X); + X=nd2array(X,dim); + [V,I]=max(X,[],1); + V=nd2array(V,-dim,sX); + I=ind2sub2(sX(dim),I); + sX(dim)=1; + sX(sX==1)=[]; +% I=reshape(I,[sX,length(dim)]); +end \ No newline at end of file diff --git a/maxabs.m b/maxabs.m new file mode 100644 index 0000000..595643a --- /dev/null +++ b/maxabs.m @@ -0,0 +1,28 @@ +function [Y,I] = maxabs(X,varargin) +%MAXABS - Signed maximum of absolute value +% [Y,I] = maxabs(X,varargin) +% +% Example +% >> maxabs([-3 2 1]) ouputs: -3 +% +% See also: max, max2 + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-26 Creation +% +% ----------------------------- Script History --------------------------------- + +[Y,I]=max(abs(X),varargin{:}); +[Z,J]=max(X,varargin{:}); +if ~isequal(size(Y),size(X)) + Y(I~=J)=-Y(I~=J); +else + Y=X; +end diff --git a/maxnan.m b/maxnan.m new file mode 100644 index 0000000..a9ce407 --- /dev/null +++ b/maxnan.m @@ -0,0 +1,36 @@ +function [y,i,nans]=maxnan(x,dim) +%MAXNAN Find maximum dismissing NaN values +% [y,i,nans]=maxnan(x) +% [y,i,nans]=maxnan(x,dim) +% returns an array +% If dim is negative +% Do not include data if any NaN found along the dimension +% +% Example: +% a = cat(3,magic(5), cumsum(ones(5))); +% a([3 35])=NaN % arbitrarily set some elements to NaN +% maxnan(a,1) +% maxnan(a,-2) +% +% See also: max() + +if nargin==1, + dim = min(find(size(x)~=1)); + if isempty(dim), dim = 1; end +end +nans=isnan(x); +if dim < 0 + dim=-dim; + otherdims = setdiff(1:ndims(x),dim); + permdims = [dim otherdims]; + nans=permute(nans,permdims); + nans(any(nans(:,:),2),:)=1; + nans=ipermute(nans,permdims); +end +x(nans)=-Inf; + +%nans=double(nans); + +[y,i] = max(x,[],dim); +y(all(nans,dim)) = NaN; + \ No newline at end of file diff --git a/mcorr.m b/mcorr.m new file mode 100644 index 0000000..dcf3e57 --- /dev/null +++ b/mcorr.m @@ -0,0 +1,74 @@ +function varargout= mcorr(varargin) +%MCORR Multi-plot of all correlations between columns of a matrix +% MCORR (X) plots correlations between all possible combinations of the +% columns of array X, in a single figure. If the first argument is the +% name of a file present in the current directory, mcorr reads +% it (including variable names in the first row) as X. Otherwise, MCORR assumes +% its first argument is the array to plot, in which case consecutive +% numbers will be used as variable names. If there is a second (numeric) +% argument, mcorr will plot only the columns indicated in the second argument. +% mcorr does not plot self-correlations (each variable with itself). It +% is unpractical to try to plot more than, say, 8 variables, since each +% individual plot becomes too small. +% +% OUTPUT= MCORR (X,'sig') calculates the Pearson correlation coefficient between +% each pair of columns and, if the correlation is sgnificant at the 95% +% level, points are plotted in red and the column numbers, Pearson coefficient +% and p-value are returned in the OUTPUT array. Requires Statistical Toolbox +% +% EXAMPLES: +% mcorr ('myfile') +% mcorr ('myfile',[1:5]) +% mcorr (X,[3:6]) +% output= mcorr (X,'sig') +% +% Last modified: Feb. 2008 + + +if nargin == 0 error ('mcorr needs at least 1 argument: name of file or array'); end +pearson= 0; +color= 'b'; +output= []; + +%Its a file => Read. Else is matrix +if ischar(varargin{1}) & ~isempty(dir(varargin{1})) + [A,varnames] = tblread(varargin{1}); +else + A= varargin{1}; + varnames= num2cell([1:size(A,2)]); +end + +%Select columns +if nargin > 1 & isnumeric(varargin{2}) + A= A(:,varargin{2}); + varnames= varnames(varargin{2}); +end +ncol= size(A,2); + +%Pearson corr. coef. +for j= 1:length(varargin) + if ischar(varargin{j}) & ~isempty(findstr(lower(varargin{j}),'sig')) + pearson= 1 + end +end + +%Function +for j= 2:ncol +for k= 1:j-1 + subplot(ncol-1,ncol-1,(j-2)*(ncol-1)+k); + if pearson [rho,pval]= corr(A(:,k),A(:,j)); + if pval < 0.05 + color= 'r'; + output= [output;k,j,rho,pval]; + else + color= 'b'; + end + end + plot(A(:,k),A(:,j),'.','MarkerSize',5,'MarkerEdgeColor',color); + set (gca,'FontSize',6); + if k == 1 ylabel(varnames(j),'FontSize',7); end + if j == ncol xlabel(varnames(k),'FontSize',7); end +end +end + +varargout{1}= output; diff --git a/meannan.m b/meannan.m new file mode 100644 index 0000000..1ad068c --- /dev/null +++ b/meannan.m @@ -0,0 +1,42 @@ +function [y,nans]=meannan(x,dim,rep) +%MEANNAN Average or mean value once NaN values have been removed +% [y,nans]=meannan(x,dim) +% [y,nans]=meannan(x,dim,rep) +% +% If dim is negative +% Do not include data if any NaN found along the complementary +% dimensions (e.g., -1 will exclude from the averag any row +% containing a NaN) +% +% Example: +% a = cat(3,magic(5), cumsum(ones(5)));a([3 35])=NaN +% meannan(a,1) +% meannan(a,-2) +% see mean() for details + +if nargin==1, + dim = min(find(size(x)~=1)); + if isempty(dim), dim = 1; end +end +nans=isnan(x); +if dim < 0 + dim=-dim; + otherdims = setdiff(1:ndims(x),dim); + permdims = [dim otherdims]; + nans=permute(nans,permdims); + nans(any(nans(:,:),2),:)=1; + nans=ipermute(nans,permdims); +end +if nargin<3 + rep=0; +end +x(nans)=rep; +nans=double(nans); +if isequal(rep,0) + y = sum(x,dim)./(size(x,dim)-sum(nans,dim)); +else + y = sum(x,dim)./size(x,dim); +end +if nargin>1 + nans=logical(nans); +end diff --git a/mediansplit.m b/mediansplit.m new file mode 100644 index 0000000..9285c07 --- /dev/null +++ b/mediansplit.m @@ -0,0 +1,107 @@ +function varargout = mediansplit(X,D,Y) +%MEDIANSPLIT - Split data in two equal groups on each side of the median +% [A,M] = mediansplit(X) +% A are logical arrays such that with M is the median of X +% A=+1 for X(A) > M; A=-1 for X(A) < M, and A=0 for X(A) = M +% +% [A,M] = mediansplit(X,D) works along dimension D in X (default D=1) +% +% [Z,A,M] = mediansplit(X,[],Y) +% [Z,A,M] = mediansplit(X,D ,Y) +% will actually computes the median split of the data in Y according to X +% X must be a vector of length L = size(Y,D) +% Z is a 3-by-... matrix with such that: +% Z(1,...)=mean(Y(A==+1)); Z(2,..)=mean(Y(A==-1)); Z(3,..)=mean(Y(A==0)) +% +% Example +% >> mediansplit(rand(1,10)) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History ---------------------------- +% KND 2008-10-15 Creation +% +% ----------------------------- Script History ---------------------------- + +if nargin<1 + error('No data!') +elseif nargin<2 + D=[]; + Y=[]; +elseif nargin<3 + Y=[]; +elseif nargin>3 + error('%s accepts 1 to 3 inputs',mfilename); +else + if ~isequal(size(X),size(Y)) + if prod(size(X))~=max(size(X)) + error('X should be a vector or of the same size as Y'); + end + X=X(:); + if isempty(D) + if length(X) == size(Y,1) + D=1; + else + error('X should be a vector matching size(Y,1) or you need to specify D'); + end + elseif length(X) ~= size(Y,D) + error('the vector X should be have a same length of size(Y,D)'); + end + rm=[ones(1,D) 1]; + rm(D)=length(X); + X=reshape(X,rm); + end +end + +if isempty(D) + M=median(X); +else + M=median(X,D); +end + +if numel(M)>1 + if isempty(D) + % the median is squeezed along one dimension but we don't know + % which one, so we need to find out. + % We cannot compare directly the sizes of X and M because if D + % happens to be the last dimension of X, the size of M may be + % shorter by one dimension, and the ~= would raise an error... + % Thus this trick: + ndX=ndims(X); + ndM=ndims(M); + nd=max(ndM,ndX); + D = [size(X) zeros(1,nd-ndX)]~=[size(M) zeros(1,nd-ndM)]; + end + rm=[ones(1,D) 1]; + rm(D)=size(X,D); + M=repmat(M,rm); +end +A=(X > M) - (X < M); +if ~isempty(Y) && ~isequal(size(X),size(Y)) + rm=[size(Y)]; + rm(D)=1; + A=repmat(A,rm); +end +sA=sum(A>0,D); +sB=sum(A<0,D); +if(~isequal(sA,sB)) + warning('Distribution(s) above and below median is/are not symmetrical!') +end +varargout={A,M}; +if isempty(Y) + return +end +if isempty(D) + D=1; %It also works if Y is horizontal +end +Z=cat(D,sum(Y.*(A>0),D),sum(Y.*(A<0),D),sum(Y.*(A==0),D)); +Z=Z./cat(D,sA,sB,sum(A==0,D)); +varargout=[Z varargout]; +return diff --git a/mergestructs.m b/mergestructs.m new file mode 100644 index 0000000..fe341c6 --- /dev/null +++ b/mergestructs.m @@ -0,0 +1,59 @@ +function [s1]=mergestructs(s1,s2,ignore) +% mergestructs - merge two structures into one +% [S3]=MERGESTRUCTS(S1,S2) creates a structure s3 whose fields are those +% of structures S1 and S2. +% +% Structures are recursively processed. If some fields (and/or subfields) +% are common to both S1 and S2, values from S1 are replaced by those +% found in S2. +% Common fields/subfields in S1 and S2 MUST be of the same size (or one +% must be of size 1 and will be expanded to match the size of the other). + +% KND + +if isempty(s1) + s1=s2; + return +end +if isempty(s2) + return +end +if nargin<3 + ignore=0; +end + +if ( ~isstruct(s1) || ~isstruct(s2) ) + if ignore && ( ~isstruct(s1) && ~isstruct(s2) ) + % 'ignore == 1' accepts input that aren't structures. + s1=s2; + return; + else + error('KND:MERGESTRUCTS:NotStructures', 'Inputs must be struct arrays!'); + return + end +end + +if ~isequal(size(s1),size(s2)) + if all(size(s1)==1) + s1=repmat(s1, size(s2)); + elseif all(size(s2)==1) + s2=repmat(s2, size(s1)); + else + error('KND:MERGESTRUCTS:NonmatchingSizes', ... + 'Input structures have incompatibles size.'); + end +end +f=fieldnames(s2); +for i=1:length(f) + do_merge = isfield(s1, f{i}); + for j=1:length(s1(:)) + if do_merge + x=mergestructs(getfield(s1(j),f{i}), getfield(s2(j),f{i}),1); + else + x=getfield(s2(j),f{i}); + s1(j).(f{i})=[]; + end + s1(j)=setfield(s1(j), f{i}, x); + end +end +s1=reshape(s1, size(s2)); diff --git a/merror.deprecated.m b/merror.deprecated.m new file mode 100644 index 0000000..48ed399 --- /dev/null +++ b/merror.deprecated.m @@ -0,0 +1,16 @@ +function [varargout]=merror(msg) +% marche pas ! +% on voit 'error in merror' appraitre sur l'écran... +[x,idb]=dbstack +if length(x)>1 + idb=2; +end +a=strread(msg, '%s'); +msg=[]; +for i=1:length(a) + msg=[msg x(idb).name sprintf(': %s\n', a{i})] +end +error(msg) +if nargout>0 +varargout={msg}; +end \ No newline at end of file diff --git a/mesh_smooth_gaussian.m b/mesh_smooth_gaussian.m new file mode 100644 index 0000000..0b79a5b --- /dev/null +++ b/mesh_smooth_gaussian.m @@ -0,0 +1,44 @@ +% Simple Gaussian Smoothing does NOT work on surface manifolds. As +% distance needs to be geodesic not Euclidian +function y=mesh_smooth_gaussian(x,v,vc,sigma,radius) +% mesh_smooth_gaussian - smooth data on a mesh with a Gaussian kernel +% y=mesh_smooth_gaussian(x,v,vc,sigma,radius) +% +% x: data, if empty, the smoothing matrix is returned. +% y: smoothed data / smooting matrix (if x empty) +% v: vertices positions ([X Y Z]) +% vc: vertices connectivity +% sigma: standard deviation of the gaussian kernel +% radius: radius of swelling (in sigma units), default: 4 +% The contribution of any given vertex is set to zero, when it +% lies further than the radius +% +% Note: Full Width at Half Maximum (FWHM) is related to sigma by: +% FWHM = sqrt(8*log(2)) * sigma ~ 2.35*sigma +if (nargin<5) + radius=4; +end +nv=size(v,1); +radius=radius*sigma; +sigma=sigma^2; % +W=sparse(1:nv,1:nv,1./sqrt(2*pi*sigma).*ones(1,nv),nv,nv,ceil(nv*radius/sqrt(sum(median(diff(v)).^2)))); +K=inline('1/sqrt(2*pi*sigma)*exp(-(x.^2/(2*sigma)))','sigma','x'); +for i=1:nv + waitbar(i/nv) + done=[i]; + nb=[vc{i}]; + while ~isempty(nb) + dist=sqrt(sum((v(nb,:)-repmat(v(i,:),length(nb),1)).^2,2)); + j=logical(dist&1` + version=`expr "$CCV" : '.*\([0-9][0-9]*\)\.'` + if [ "$version" = "4" ]; then + echo "SC5.0 or later C++ compiler is required" + fi + CXXFLAGS='-KPIC -dalign -xlibmieee -D__EXTENSIONS__ -D_POSIX_C_SOURCE=199506L -mt' + CXXLIBS="$MLIBS -lm -lCstd -lCrun" + CXXOPTIMFLAGS='-xO3 -xlibmil -DNDEBUG' + CXXDEBUGFLAGS='-g' +# +# f77 -V +# WorkShop Compilers 5.0 99/09/16 FORTRAN 77 5.0 patch 107596-03 + FC='f77' + FFLAGS='-KPIC -dalign -mt' + FLIBS="$MLIBS -lF77 -lM77 -lsunmath -lm -lcx -lc" + FOPTIMFLAGS='-O' + FDEBUGFLAGS='-g' +# + LD="$COMPILER" + LDFLAGS="-G -mt -M$TMW_ROOT/extern/lib/$Arch/$MAPFILE" + LDOPTIMFLAGS='-O' + LDDEBUGFLAGS='-g' +# + POSTLINK_CMDS=':' +#---------------------------------------------------------------------------- + ;; + mac) +#---------------------------------------------------------------------------- + CC='cc' + CFLAGS='-fno-common -traditional-cpp' + + CLIBS="$MLIBS" + + COPTIMFLAGS='-O3 -DNDEBUG' + CDEBUGFLAGS='-g' + + CXX=c++ + CXXFLAGS='-fno-common -traditional-cpp' + CXXLIBS="$MLIBS -lstdc++" + CXXOPTIMFLAGS='-O3 -DNDEBUG' + CXXDEBUGFLAGS='-g' +# + FC='f77' + FFLAGS='-f -N15 -N11 -s -Q51 -W' + ABSOFTLIBDIR=`which $FC | sed -n -e '1s|bin/'$FC'|lib|p'` + FLIBS="-L$ABSOFTLIBDIR -lfio -lf77math" + FOPTIMFLAGS='-O' + FDEBUGFLAGS='-g' +# + LD="$CC" + LDFLAGS="-bundle -Wl,-flat_namespace -undefined suppress" + LDOPTIMFLAGS='-O' + LDDEBUGFLAGS='-g' +# + POSTLINK_CMDS='nmedit -s $TMW_ROOT/extern/lib/$Arch/$MAPFILE $mex_file' +#---------------------------------------------------------------------------- + ;; + esac +############################################################################# +# +# Architecture independent lines: +# +# Set and uncomment any lines which will apply to all architectures. +# +#---------------------------------------------------------------------------- +# CC="$CC" +# CFLAGS="$CFLAGS" +# COPTIMFLAGS="$COPTIMFLAGS" +# CDEBUGFLAGS="$CDEBUGFLAGS" +# CLIBS="$CLIBS" +# +# FC="$FC" +# FFLAGS="$FFLAGS" +# FOPTIMFLAGS="$FOPTIMFLAGS" +# FDEBUGFLAGS="$FDEBUGFLAGS" +# FLIBS="$FLIBS" +# +# LD="$LD" +# LDFLAGS="$LDFLAGS" +# LDOPTIMFLAGS="$LDOPTIMFLAGS" +# LDDEBUGFLAGS="$LDDEBUGFLAGS" +#---------------------------------------------------------------------------- +############################################################################# diff --git a/mfiletemplate.m b/mfiletemplate.m new file mode 100644 index 0000000..a600fd7 --- /dev/null +++ b/mfiletemplate.m @@ -0,0 +1,56 @@ +function outStr = mfiletemplate(option,filename,description) +%MFILETEMPLATE Template for new M-files +% MFILETEMPLATE(OPTION,FILENAME,DESCRIPTION) +% OPTION = { full | description | copyright } + +% Copyright 1984-2003 The MathWorks, Inc. + +if nargin < 1 + option = 'full'; +end + +if nargin < 2 + filename = ''; +end + +if nargin < 3 + description = ''; +end + +if strcmp(option,'description') + s = {[upper(filename) ' ' description]}; + +else + f = textread(which('template.m'),'%s','delimiter','\n','whitespace',''); + s = f; + + copyrightLine = ''; + + for n = 1:length(f) + str = f{n}; + str = strrep(str,'$filename',filename); + str = strrep(str,'$FILENAME',upper(filename)); + str = strrep(str,'$description',description); + if ~isempty(strfind(str,'$date')) + match = regexp(str,'\$date\((.*?)\)','match','once'); + if ~isempty(match) + token = regexp(match,'\((.*?)\)','tokens','once'); + str = strrep(str,match,datestr(now,token{1})); + end + end + if ~isempty(strfind(lower(str),'copyright')) + copyrightLine = str; + end + s{n} = str; + end + + if strcmp(option,'copyright') + s = {copyrightLine}; + end +end + +str = sprintf('%s\n',s{:}); +% Pull off the last \n +str(end) = []; +outStr = str; + diff --git a/minf2struct.m b/minf2struct.m new file mode 100644 index 0000000..337354d --- /dev/null +++ b/minf2struct.m @@ -0,0 +1,64 @@ +function [x]=minf2struct(minf) +% minf2struct - reads .minf file (Brainvisa) and create a structure +% +% [s]=minf2struct(minf) +% +% Input: +% minf: filename to read (e.g. 'toto.tex.minf') +% +% Output: +% s : matlab structure +x=[]; +fid=fopen(minf, 'rt'); +t=[]; +% t=fgetl(fid); % skip 1st line +while not(feof(fid)) + t=fgetl(fid); + t=strrep(t,'attributes = {', ''); + t=strrep(t,'}', ''); + t=rmspaces(t); + [f,v]=strtok(t,':'); + while not(isempty(v)) + [f2,v2]=strtok(v,':'); + sp=findstr('''', f); + f=f(sp(1)+1:sp(2)-1); + sp=findstr('''', f2); + if not(isempty(v2)) + v=v(2:(sp(end-1)-1)); + else + v=v(2:end); + end + x=setfield(x, f, eval([ v ';'])); + v=v2; + if not(isempty(v2)) + f=f2(sp(end-1):end); + else + f=[]; + end + end + + +end +fclose(fid); + + +function [t]=rmspaces(t) +i=1; +if length(t)==0 + return +end +while t(1)==' ' + t(1)=[]; + if length(t)==0 + break + end +end +if length(t)==0 + return +end +while t(end)==' ' + t(end)=[]; + if length(t)==0 + break + end +end diff --git a/misc/biblio/pubmed1.m b/misc/biblio/pubmed1.m new file mode 100644 index 0000000..e000cb3 --- /dev/null +++ b/misc/biblio/pubmed1.m @@ -0,0 +1,30 @@ + +t=urlread('http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=Nature[ta]+brain[TIAB]+"Journal+Article"[PT]&retmax=500'); + +[a]=strread(t,'%s', 'delimiter','\n'); +a=a(strmatch('', a)); +a=strrep(a, '',''); +a=strrep(a, '',''); +%a=strvcat(a); +%a=strrep(vectvec(transpose(a))','', '');a=strrep(a,'', ','); + +au=[]; + +for i=1:length(a) + fprintf('%d/%d\n',i,length(a)) +% q=a{i}(5:end-5); +q=a{i}; +rs{i}=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]); +r=strread(rs{i}, '%s', 'delimiter','\n\n'); +b=strrep(r(strmatch('AU -',r)), 'AU - ',''); +au=[au, {b(:)'} ]; +%r=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]) +% b=findstr(r,char([13 10 13])); +% b=r(b(2)+4:b(3)-2) +% au=[au ', ' b]; +end +o=[au{:}] +[b,i,j]=unique(o) +[m,mm]=histk(j) +b(m(1:10)) +mm(1:10) diff --git a/misc/biblio/pubmed2.m b/misc/biblio/pubmed2.m new file mode 100644 index 0000000..63f4cd3 --- /dev/null +++ b/misc/biblio/pubmed2.m @@ -0,0 +1,45 @@ +f=textread('d:\ndiaye\labo\publis\these\update biblio.txt','%s', 'delimiter', '\n'); +f=f(21:end) + +for i=1:length(f) + f{i} + t=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=' strrep(f{i}, '] "', ']+"')]); + + [a]=strread(t,'%s', 'delimiter','\n'); + a=a(strmatch('', a)); + a=strrep(a, '',''); + a=strrep(a, '',''); + %a=strvcat(a); + %a=strrep(vectvec(transpose(a))','', '');a=strrep(a,'', ','); + au=[]; + if length(a)==1 + for j=1:length(a) + fprintf('%d/%d\n',j,length(a)) + q=a{j}; + rs{j}=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]); + return + end + end + +end + +au=[]; + +for i=1:length(a) + fprintf('%d/%d\n',i,length(a)) + % q=a{i}(5:end-5); + q=a{i}; + rs{i}=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]); + r=strread(rs{i}, '%s', 'delimiter','\n\n'); + b=strrep(r(strmatch('AU -',r)), 'AU - ',''); + au=[au, {b(:)'} ]; + %r=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]) + % b=findstr(r,char([13 10 13])); + % b=r(b(2)+4:b(3)-2) + % au=[au ', ' b]; +end +o=[au{:}] +[b,i,j]=unique(o) +[m,mm]=histk(j) +b(m(1:10)) +mm(1:10) diff --git a/misc/biblio/repairbib.m b/misc/biblio/repairbib.m new file mode 100644 index 0000000..99b8049 --- /dev/null +++ b/misc/biblio/repairbib.m @@ -0,0 +1,42 @@ +% re-fetch biblio data rom medline +t=textread('d:\ndiaye\labo\jabbib.bib', '%s', 'delimiter', '\n'); + +return +fid=fopen('d:\ndiaye\labo\jabbib.bib','rt') +t=textscan(fid, '%s'); +fclose(fid) + + + +return + + +t=urlread('http://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=Nature[ta]+brain[TIAB]+"Journal+Article"[PT]&retmax=500'); + +[a]=strread(t,'%s', 'delimiter','\n'); +a=a(strmatch('', a)); +a=strrep(a, '',''); +a=strrep(a, '',''); +%a=strvcat(a); +%a=strrep(vectvec(transpose(a))','', '');a=strrep(a,'', ','); + +au=[]; + +for i=1:length(a) + fprintf('%d/%d\n',i,length(a)) +% q=a{i}(5:end-5); +q=a{i}; +rs{i}=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]); +r=strread(rs{i}, '%s', 'delimiter','\n\n'); +b=strrep(r(strmatch('AU -',r)), 'AU - ',''); +au=[au, {b(:)'} ]; +%r=urlread(['http://eutils.ncbi.nlm.nih.gov/entrez/eutils/efetch.fcgi?db=pubmed&retmode=text&rettype=medline&id=' q]) +% b=findstr(r,char([13 10 13])); +% b=r(b(2)+4:b(3)-2) +% au=[au ', ' b]; +end +o=[au{:}] +[b,i,j]=unique(o) +[m,mm]=histk(j) +b(m(1:10)) +mm(1:10) diff --git a/misc/cdf.m b/misc/cdf.m new file mode 100644 index 0000000..4f921fa --- /dev/null +++ b/misc/cdf.m @@ -0,0 +1,49 @@ +function [t] = cdf(a) + +% Computes the cumulative distribution function of the histogram of image "a". +% How to use: +% (1) Read the image into the workspace: Ex, a = imread('image.tif'); +% (2) Define the variable to use for the cumm dist function: Ex, s = cdf(a); +% NOTE: The output is normalized to the range [0,1]. + +% Get histogram of image + + h=imhist(a); %This MATLAB function gives a 256X1 histogram if "a" is uint8. + + m=length(h); + +%First normalize the histogram to make sure that its area is unity (i.e., that it is a valid pdf). + + sum=0; + + for k=1:m; + sum=sum + h(k); + end + + coeff=1/sum; + +%Multiply each component of h by coeff + + h = h.*coeff; + +%Now compute the pdf + + for k=1:m; + sum=0; + for j=1:k; + sum=sum + h(j); + end + t(k)=sum; + end + +% Convert to a column vector + + t=t'; + +% End of function + + + + + + \ No newline at end of file diff --git a/misc/compute_ins.m b/misc/compute_ins.m new file mode 100644 index 0000000..e69de29 diff --git a/misc/docinfo.m b/misc/docinfo.m new file mode 100644 index 0000000..7d3919d --- /dev/null +++ b/misc/docinfo.m @@ -0,0 +1,25 @@ +function docinfo; +% Adds a user defined field to a figure that contains +% a text transcript of the m-file that called this command. +% The text will be stored when the figure is stored as a fig file +% and can be recovered using the 'recallfigmfile' command. +% +% To use this function, insert the command 'docinfo' after your plot command. +% The function operates only on the active figure, so if you have more than +% one figure, you will need to insert this command for each one. + +[st,I]=dbstack; % accesses the stack of called functions + +filestring=st(2).name; +% docinfo is first on the stack, so the second file is required. + +[pathstr,name,ext,versn] = fileparts(filestring); +% identifies the mfile + +mfiletext=textread([name,ext],'%s','delimiter','\r'); +%reads the mfile as a text structure. + +atext=char(mfiletext);%convert to a string + +set(gcf,'userdata',atext);%stores as a property of the figure + diff --git a/misc/filelabel.m b/misc/filelabel.m new file mode 100644 index 0000000..6a5c458 --- /dev/null +++ b/misc/filelabel.m @@ -0,0 +1,34 @@ +function filelabel; +% This program labels a figure with the name of the m.file +% which produced the plot as well as the date and time it +% was created. +% +% To use this function, insert the command 'filelabel' after your plot command. +% The function operates only on the active figure, so if you have more than +% one figure, you will need to insert this command for each figure. + +[st,I]=dbstack; % accesses the stack of called functions +filestring=st(2).name; % the first m file is this one - labelfig. +% the second item in the stack would refer to the function +% that called this program + +[pathstr,name,ext,versn] = fileparts(filestring);% allows elimination of the path +% string, since this is assumed to be either extraneous or transient information. +% If the full path name is desired, then the first 'tit' line should be commented out +% and the second one used. + +tit=[name,ext,' ',datestr(now)]; +%tit=[filestring,' ',datestr(now)]; + + +set(gca,'position',[0.1300 0.200 0.775 0.7250]); +% the set command raises the bottom of the axes to allow for labeling + +text(.5,-.2,tit,'interpreter','none','units','normalized','VerticalAlignment','top',... + 'HorizontalAlignment','center','clipping','off'); + + + + + + diff --git a/misc/gmail/gmailclient.m b/misc/gmail/gmailclient.m new file mode 100644 index 0000000..60bfe81 --- /dev/null +++ b/misc/gmail/gmailclient.m @@ -0,0 +1,4 @@ +function [c] = gmailclient(username, password) +url = 'https://www.google.com/accounts/ServiceLoginBoxAuth'; +postdata =sprintf( 'continue=https://gmail.google.com/gmail&service=mail&Email=%s&Passwd=%s&submit=null', username, password) + c = p.read() \ No newline at end of file diff --git a/misc/hex_to_uint64.m b/misc/hex_to_uint64.m new file mode 100644 index 0000000..0162eec --- /dev/null +++ b/misc/hex_to_uint64.m @@ -0,0 +1,56 @@ +function m = hex_to_uint64(h) +%HEX_TO_UINT64 Convert hexadecimal string to uint64 number. +% +% HEX_TO_UINT64(H) converts the hexadecimal string H and returns the +% corresponding uint64 numbers. Each row in H, representing one output +% value, must only contain characters in the set '0123456789abcdefABCDEF'. +% +% For example +% +% hex_to_uint64(['0000000000000000' +% '0000000000000001' +% '0000000000000002' +% '7ffffffffffffffd' +% '7ffffffffffffffe' +% '7fffffffffffffff']) +% +% returns +% +% [ 0 +% 1 +% 2 +% 9223372036854775805 +% 9223372036854775806 +% 9223372036854775807] + +% Author: Peter John Acklam +% Time-stamp: 2004-09-22 18:43:25 +0200 +% E-mail: pjacklam@online.no +% URL: http://home.online.no/~pjacklam + + % Check number of input arguments. + error(nargchk(1, 1, nargin)); + + % Check type and size of input argument. + if ~ischar(h) + error('Argument must be a character array.'); + end + + hs = size(h); + hd = ndims(h); + if (hd > 2) || (hs(2) ~= 16) + error('Input must be a 2D matrix with 16 columns.'); + end + + if any( ( (h(:) < '0') | ('9' < h(:)) ) ... + & ( (h(:) < 'A') | ('F' < h(:)) ) ... + & ( (h(:) < 'a') | ('f' < h(:)) ) ); + error('Invalid hexadecimal string.'); + end + + % Convert to the output data type. + n = uint64(reshape(sscanf(h, '%1x'), hs)) + m = uint64(n(:,1)); + for i = 2:16 + m = bitor(bitshift(m, 4), n(:,i)); + end diff --git a/misc/hypercube.m b/misc/hypercube.m new file mode 100644 index 0000000..ee4a67a --- /dev/null +++ b/misc/hypercube.m @@ -0,0 +1,91 @@ +function hypercube(d,p) +% Draws hypercube projections + +% Ref: +% http://www4.ncsu.edu/unity/lockers/users/f/felder/public/kenny/papers/4dplots.html + + +d = 4 +p = 3 +if p<1|d<1 + error +end +if p>3 + error 'cannot plot beyond 3d' +end + +%vertices +nv = 2^d +v = zeros(nv,d); +for i=1:nv + v(i,:)=bitget(i-1,1:d); +end +colv = rand(nv,3); +%edges +e=[]; +for i=1:nv + for j=i+1:nv + if sum(abs(diff([v(i,:);v(j,:)])))==1 + e=[e; i j]; + end + end +end +ne=size(e,1); +close all +hf = figure; +ha(1) = subplot(2,4,[3]); +ha(2) = subplot(2,4,[4]); +ha(3) = subplot(2,4,[7]); +ha(4) = subplot(2,4,[8]); +ha(5) = subplot(2,4,[1 2 5 6]); +set(ha,'XTick',[],'YTick',[],'Ztick', [], 'XLim',[-1 2], 'Ylim', [-1 2] , 'Zlim', [-1 2] ) +D='XYZU'; + +xy(:,1:p) = nchoosek(1:d,p); +xy(:,p+1:3)=0; +for j=1:d + axes(ha(j)) + xlabel(D(xy(j,1))) + ylabel(D(xy(j,2))) + view(2) + if xy(j,3)>0 + zlabel(D(xy(j,3))); + view(3) + end + axis square + grid on + box on + +end + + +for j=1:d + axes(ha(j)) + hold on + for i=1:nv% randperm(nv) + switch(p) + case 1 + case 2 + hp(j,i)=plot(v(:,xy(j,1)),v(:,xy(j,2)),'.','MarkerSize',12, 'color', colv(i,:)); + case 3 + hp(j,i)=plot3(v(:,xy(j,1)),v(:,xy(j,2)),v(:,xy(j,3)),'.','MarkerSize',12, 'color', colv(i,:)); + end + end + for i=1:ne + switch(p) + case 1 + case 2 + he(j,i)=line(v(e(i,:),xy(j,1)),v(e(i,:),xy(j,2))); + + case 3 + he(j,i)=line(v(e(i,:),xy(j,1)),v(e(i,:),xy(j,2)),v(e(i,:),xy(j,3))); + end + end + hold off +end +set(ha, 'XTick',[], 'YTick',[], 'XLim',[-1 2], 'Ylim', [-1 2] ) + + + +function v=rotate(v,r,a) + diff --git a/misc/ins_c.m b/misc/ins_c.m new file mode 100644 index 0000000..80f03bd --- /dev/null +++ b/misc/ins_c.m @@ -0,0 +1,34 @@ +function [I] = ins_c(prenoms, datedenaissance, nir) +% ins_c - Calcul de l'Identification National de Santé, calculé (INS-C) +if nargin<1 + if 1 + + prenoms = 'PHILIPPE '; + datedenaissance = '610217'; + nir = '1610275754289' + % Hashage: 73ba73767e7a53da3a85fba9929cf62b9e63d01758deb9bf11e14cc40c58ea81 + % Résultat: 0 833 910 461 279 517 589 8 + % Clé: 58 + else + prenoms = 'KARIMBABACARJOSEPH'; + datedenaissance = '790111'; + nir = '1790185191067'; + end +end + +c = [prenoms(1:10) , datedenaissance , nir]; +% SHA-256 hashing: +h=java.security.MessageDigest.getInstance('SHA-256'); +h.update(uint8(c)); +h = typecast(h.digest,'uint8'); + +h = h(1:8); +h = dec2bin(h)'; +b = h(:)'; +uint64(bin2dec(b(13:64))) +b = (uint64(bin2dec(b(1:12)) * 2^(64-12) + bin2dec(b(13:64)))) +%I = sprintf('%.1f',double(b)/10000) +%I = I(1:end-2) +%rem((b),10000) +%sprintf('%d',ans) + diff --git a/misc/isi/isi.bk.htm b/misc/isi/isi.bk.htm new file mode 100644 index 0000000..d0ca4fb --- /dev/null +++ b/misc/isi/isi.bk.htm @@ -0,0 +1,4928 @@ + + +

    Quelques facteurs d'impact (Impact Factor, ISI) + +

    En neurosciences cognitives

    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    Journal

    1992

    1993

    1994

    1995

    1996

    1997

    1998

    1999

    2000

    2001

    2002

    2003

    2004

    ANNU REV NEUROSCI20,42227,62917,95329,08333,62521,95223,02322,6526,67627,15224,09129.08323.143
    BEHAV BRAIN RES1,8541,4441,5631,8621,6132,342,7962,3182,2632,4732,7911.862
    BEHAV BRAIN SCI0,2970,4260,63915,62598,1188,811,27614,2517,3128,73015.6257.125
    BEHAV NEUROSCI2,7292,993,2632,9692,5282,6653,0262,7192,7512,862.7572.969
    BRAIN3,5893,8935,0354,8675,7395,3815,9527,3747,3037,477.1224.8678.201
    BRAIN COGNITION1,51,231,3731,111,0730,5660,5080,7360,630,7911.0931.110
    CEREB CORTEX5.322
    CLIN NEUROPHYSIOL1,6721,9222,120
    CLIN NEUROSCI0,6561,3331,3531,751,0141,7811.333
    COGNITIVE BRAIN RES0,882,2221,731,5762,7552,3332,7332,8842,4042.222
    COGNITIVE NEUROPSYCH2,92,4922,18
    COGN NEUROPSYCHOL3,3973,391
    COGNITIVE PSYCHOL3,7374,1673,4633,7114,059
    CURR OPIN NEUROBIOL5,3457,0797,3568,8549,2879,2779,99510,7185.3457.937
    ELECTROEN CLIN NEURO1,8721,6991,6171,8942,0272,42,452,8613,327N/AN/A1.894
    EUR J NEUROSCI4,824,564,9514,9214,3033,9473,823,8993,8623,9194,1634.921
    EXP BRAIN RES2,3442,4092,2271,9672,0491,8982,0182,2462,1372,362,3001.967
    HUM BRAIN MAPP10,0494,7385,285,1635,6885.076
    INT J NEUROSCI0,5270,6220.579
    J COGNITIVE NEUROSCI3,5714,0634,3833,6794,8445,225,7935,1156,7366.096
    J NEUROSCI7,168,0358,6578,2057,9557,9158,4038,9558,5028,1788.0458.317.907
    NAT NEUROSCI8,86312,63615,66814.85715.1416.980
    NAT REV NEUROSCI014,35324.04727.0121.225
    NEUROIMAGE2,7860,7781,6174,3115,6118,936,8577,8795.624
    NEURON15,58917,25618,34816,61916,95315,82116,50516,78215,08114,15313.84614.1114.439
    NEUROREPORT2,2773,0792,572,4872,2622,5912,6822,6962,3742.265
    NEUROSCI LETT2,4192,6452,7032,3182,091,7681,9342,0852,0912,212.100
    Q J EXP PSYCHOL-A1,9481,5611,4521,281.722
    Q J EXP PSYCHOL-B1,31,1321,2751,1281,3491,4191,221,33311,41.256
    TRENDS COGN SCI11,6608.1297.992
    TRENDS NEUROSCI15,42617,29920,19419,97217,75517,08418,46319,92517,41716,47514.47412.6314.794
    + + +


    +

    DIVERS

    +


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    Quelques facteurs d'impact (Impact Factor, ISI) + +

    En neurosciences cognitives

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    NATURE22,13922,32625,46627,07428,41727,36828,83329,49125,81427,955
    SCIENCE20,96721,07422,06721,91123,60524,67624,38624,59523,87223,329
    P NATL ACAD SCI USA10,4810,32510,66710,5210,2449,049,82110,2610,7891,896
    P ROY SOC LOND B BIO3,0393,1372,792,5892,8672,8733,0332,7553,0373,192
    PHILOS T ROY SOC B2,1151,7682,192,2812,8322,5122,8862,653,5163,66
    ACTA NEUROBIOL EXP0,4130,5050,5510,480,560,7660,50,6310,767
    ACTA NEUROCHIR0,8220,7280,7480,6560,4980,6230,7481,040,8170,957
    ACTA NEUROL BELG0,3880,1630,2290,3330,3290,2530,2260,2750,521
    ACTA NEUROL SCAND1,1220,9771,1331,1421,0680,9021,1081,3251,3041,64
    ACTA NEUROPATHOL2,942,3952,1682,5462,9462,2992,3362,4022,4462,165
    ACTA NEUROPSYCHIATR0,0890,2980,0360,338
    ADV NEUROL0,9681,142
    AKTUEL NEUROL0,2930,1960,3230,2770,2350,240,2750,3140,2960,356
    AM J ELECTRONEUROD T0,0770,0940,0650,53
    AM J NEURORADIOL2,0591,8451,7331,5561,751,7071,8692,3582,1262,24
    ANN NEUROL6,327,0357,6246,6998,7159,5139,4558,3218,488,481
    ANNU REV NEUROSCI20,42227,62917,95329,08333,62521,95223,02322,6526,67627,152
    ARCH CLIN NEUROPSYCH0,750,8421,3950,988
    ARCH NEUROL-CHICAGO3,5173,1643,8514,263,7783,7793,3753,8634,3934,53
    ARQ NEURO-PSIQUIAT0,1410,1730,1970,228
    AUDIOL NEURO-OTOL2,0182,392,532
    AUDIT NEUROSCI2,461,929
    AUTON NEUROSCI-BASIC00,930
    BEHAV NEUROL0,250,2630,2560,333
    BEHAV NEUROSCI2,7292,993,2632,9692,5282,6653,0262,7192,7512,86
    BRIT J NEUROSURG0,9380,5340,5330,5460,5020,5380,5740,5390,563
    CAN J NEUROL SCI1,1811,531,7121,5441,0331,171,0741,2921,5041,317
    CELL MOL NEUROBIOL2,4122,441,6431,3491,6861,9681,961,7522,0932,12
    CESK SLOV NEUROL N0,0290,0650,0590,41
    CHILD NEUROPSYCHOL0,3140,9410,60,565
    CLIN NEUROL NEUROSUR0,3530,3260,4890,5940,6190,6130,4060,5640,6190,595
    CLIN NEUROPATHOL1,0491,3180,840,9350,7470,6360,9060,9681,0120,553
    CLIN NEUROPHARMACOL1,5682,1872,0711,5321,2511,6041,6362,0161,9431,533
    CLIN NEUROPHYSIOL1,6721,922
    CLIN NEUROPSYCHOL0,6740,5610,9480,551
    CLIN NEUROSCI0,6561,3331,3531,751,0141,781
    COGN NEUROPSYCHOL3,397
    COGNITIVE NEUROPSYCH2,92,4922,18
    CRIT REV NEUROBIOL7,7785,750
    CRIT REV NEUROSURG0,0940,2750,2330,227
    CURR OPIN NEUROBIOL5,3457,0797,3568,8549,2879,2779,995
    CURR OPIN NEUROL0,4730,9411,3951,8691,8552,4972,9933,1764,35
    DEV MED CHILD NEUROL1,1021,2081,171,1771,7781,5631,3161,4711,781,988
    DEV NEUROPSYCHOL1,361,0830,8710,914
    DEV NEUROSCI-BASEL0,7271,0380,6130,7561,2211,5961,672,1532,5231,93
    ELECTROEN CLIN NEURO1,8721,6991,6171,8942,0272,42,452,8613,327
    EUR J NEUROL0,6410,6080,670,9521,358
    EUR J NEUROSCI4,824,564,9514,9214,3033,9473,823,8993,8623,919
    EUR NEUROL1,3511,5630,8990,9151,2571,221,051,37911,179
    EUR NEUROPSYCHOPHARM1,9332,3281,6241,8521,7782,3872,0452,437
    EXP NEUROL3,1442,9582,8033,4513,6043,452,8633,263,8583,53
    FOLIA NEUROPATHOL0,2110,3380,2580,471
    FORTSCHR NEUROL PSYC0,430,5240,6170,670,5870,5170,4410,6020,6360,593
    FRONT NEUROENDOCRIN6,2616,0458,2387,875,7787,1117,257,8268,37515
    FUNCT NEUROL0,4120,5310,710,463
    GIORN NEUROPSI EVOL0,0310
    GIORN NEUROPSICOFARM000
    INT J DEV NEUROSCI1,7481,3391,5571,6481,3521,4061,4971,4251,5832,156
    INT J NEUROPSYCHOPH1,8331,3232,779
    INT J NEURORADIOL0,4150,3590,1390,238
    INT J NEUROSCI0,5270,622
    INT REV NEUROBIOL4,86,5881,8282,43,52,9441,78
    INTERV NEURORADIOL0,5850,441
    ITAL J NEUROL SCI0,1880,1980,3390,2160,2610,4180,4210,3490,1620,635
    J CHEM NEUROANAT3,3541,6171,9432,0921,5691,6672,7112,5522,1411,649
    J CHILD NEUROL1,3471,1320,920,9240,8970,9180,9291,0951,1341,393
    J CLIN EXP NEUROPSYC1,8142,8212,1561,5851,2011,3171,3671,2651,0671,14
    J CLIN NEUROPHYSIOL1,5831,5891,4251,1552,1641,4591,5841,9152,1732,538
    J CLIN NEUROSCI0,3850,320,2620,2920,1440,1780,392
    J COGNITIVE NEUROSCI3,5714,0634,3833,6794,8445,225,7935,1156,736
    J COMP NEUROL3,5553,6573,4683,5843,7483,7583,4763,7643,7723,515
    J COMPUT NEUROSCI2,6112,6222,2862,3462,596
    J INT NEUROPSYCH SOC2,3762,340
    J MOL NEUROSCI2,3512,4671,8751,4581,5222,0771,9121,6091,7651,688
    J NEUROBIOL2,8132,4094,1184,5684,8062,8142,8713,333,4653,34
    J NEUROCHEM4,2154,2234,5254,8524,2194,2344,6514,9064,94,834
    J NEUROCYTOL2,4912,3842,562,5362,6791,9732,1541,861,2311,776
    J NEUROENDOCRINOL2,3912,6162,5392,9892,8562,5632,8322,3772,5982,58
    J NEUROGENET1,9092,3642,51,6671,2350,9571,3571,6921,9381,125
    J NEUROIMAGING0,8350,6521,0440,9740,9420,926
    J NEUROIMMUNOL2,9642,9553,1883,6393,0832,8453,2853,2333,3553,342
    J NEUROL1,7361,791,8491,5811,9441,9762,32,8462,0612,653
    J NEUROL NEUROSUR PS2,6962,2612,5342,5042,933,0412,9382,7352,8463,24
    J NEUROL ORTH MED S0,0160,4
    J NEUROL REHABIL0,220,2980,385
    J NEUROL SCI2,3852,1651,7761,8671,7351,4531,8381,6851,6781,986
    J NEUROLINGUIST0,3780,9090,5140,722
    J NEURO-ONCOL1,3411,2771,0960,7771,1111,2321,6411,6551,5811,435
    J NEURO-OPHTHALMOL0,0240,6240,3890,2730,3740,2520,778
    J NEUROPATH EXP NEUR4,9044,2735,3675,8314,7844,2535,3665,595,5655,533
    J NEUROPHYSIOL3,8744,1344,0013,5783,8343,2633,4113,9353,8553,517
    J NEUROPSYCH CLIN N1,7372,0371,5731,7951,6973,2092,141,632
    J NEURORADIOLOGY0,3270,3330,4260,3040,3770,5880,3680,5220,62
    J NEUROSCI7,168,0358,6578,2057,9557,9158,4038,9558,5028,178
    J NEUROSCI METH1,5671,5231,4421,8151,4121,3351,431,3621,4771,659
    J NEUROSCI RES3,1973,0053,6373,3772,8432,4422,8743,1263,2073,378
    J NEUROSURG2,5152,6883,2963,0122,7692,9993,3723,3462,9182,748
    J NEUROSURG ANESTH0,6380,8311,4331,6521,2371,3331,1440,9340,9370,739
    J NEUROTRAUM2,1442,8023,0153,0863,0193,4042,8773,952
    J NEUROVIROL1,8332,4571,7292,0983,3972,71
    J PSYCHIATR NEUROSCI0,9661,6962,0392,516
    JNMS-J NEUROMUSC SYS0,1110,1250,1030,111
    KLIN NEUROPHYSIOL0,3210,2030,156
    MINIM INVAS NEUROSUR0,0770,5250,6490,6920,7440,667
    MOL CELL NEUROSCI3,3072,5293,2596,086,0895,6545,7465,446
    MOL CHEM NEUROPATHOL0,6361,0381,2451,1511,0640,780,881,0941,163
    MOL NEUROBIOL0,8112,2863,2551,62,3853,4834,3885,6234,3822,4
    NAT NEUROSCI8,86312,63615,668
    NAT REV NEUROSCI014,353
    NEUROBIOL AGING3,5273,4343,1012,112,1212,8723,5173,3994,1594,49
    NEUROBIOL DIS2,6114,2254,8695,0235,3334,487
    NEUROBIOL LEARN MEM1,5742,1221,8412,8053,041,83
    NEUROCASE1,0121,2681,8711,312
    NEUROCHEM INT1,8551,5181,4342,2361,9881,7051,7812,1752,6623,4
    NEUROCHEM RES1,4321,591,5761,5771,2921,311,6771,7551,8581,638
    NEUROCHIRURGIE0,4040,4290,5050,2810,2830,3880,3090,3360,390,346
    NEUROCIRUGIA0,0570,1850,1540,13
    NEUROCOMPUTING0,2430,6090,5770,4220,4530,360,6360,534
    NEUROENDOCRINOLOGY2,8412,7022,4222,6842,4452,44133,2142,7442,144
    NEUROEPIDEMIOLOGY0,9490,78611,0471,6541,3971,3531,8031,6541,39
    NEUROGASTROENT MOTIL1,3551,51,7211,6921,9362,0812,5
    NEUROGENETICS1,872,0942,5963,69
    NEUROIMAG CLIN N AM0,6770,831,0950,957
    NEUROIMAGE2,7860,7781,6174,3115,6118,936,8577,879
    NEUROIMMUNOMODULAT0,741,6092,7011,989
    NEUROL CLIN1,1551,0421,7610,8950,9441,331,3751,5660,8961,283
    NEUROL CROATICA0,09400,032
    NEUROL INDIA0,10,0570,0920,173
    NEUROL MED-CHIR0,386
    NEUROL PSYCHIAT BR0,2160,3330,278
    NEUROL RES0,6970,8521,1421,0271,1281,10,8661,176
    NEUROL SCI00,380
    NEUROL SURG TOKYO0,0920,1580,1560,12
    NEUROLOGIST0,3120,3970,2720,22
    NEUROLOGY4,3553,994,3474,6334,6124,5264,9725,2324,7815,212
    NEUROMODULATION2,0951,2161,96
    NEUROMUSCULAR DISORD1,4771,8182,7182,3512,5822,7492,7182,547
    NEURON15,58917,25618,34816,61916,95315,82116,50516,78215,08114,153
    NEURO-OPHTHALMOLOGY0,4570,2980,3720,2890,3740,3680,3610,450,3760,176
    NEURO-ORTHOPEDICS0,2730,222
    NEUROPATH APPL NEURO2,3262,3761,9831,8892,2042,1211,5912,5752,5232,963
    NEUROPATHOLOGY0,6910,4130,4870,575
    NEUROPEDIATRICS0,9261,20,7291,0081,3891,9851,5451,6691,5971,476
    NEUROPEPTIDES1,7972,1642,0261,6010,9640,9051,241,0751,4131,959
    NEUROPHARMACOLOGY2,2461,9972,4243,6344,4583,9093,244,1764,1253,854
    NEUROPHYSIOL CLIN0,4690,350,4330,4220,3690,5320,5161,33
    NEUROPHYSIOLOGY0,1140,1770
    NEUROPHYSIOLOGY+0,0270,870
    NEUROPSY NEUROPSY BE0,9740,6880,7930,6950,50,7580,8961,347
    NEUROPSYCHIATRIE0,1250,2350,3870,135
    NEUROPSYCHOBIOLOGY0,3680,3940,9861,050,8550,8210,8460,9531,561,64
    NEUROPSYCHOL REHABIL0,9470,6090,6670,759
    NEUROPSYCHOL REV0,7271,1821,250,92
    NEUROPSYCHOLOGIA1,8852,0531,9661,8282,0592,2672,9392,6872,7783,32
    NEUROPSYCHOLOGY2,6133,1132,7022,486
    NEUROPSYCHOPHARMACOL3,6612,5212,783,5673,9364,1054,3184,8584,5794,715
    NEURORADIOLOGY1,0510,9350,90,8580,9970,7541,0231,2870,9971,97
    NEUROREHAB NEURAL RE0,190,610
    NEUROREPORT2,2773,0792,572,4872,2622,5912,6822,6962,374
    NEUROSCI BIOBEHAV R2,4962,8573,7932,992,7863,3163,5953,3825,212
    NEUROSCI LETT2,4192,6452,7032,3182,091,7681,9342,0852,0912,21
    NEUROSCI RES1,9782,0592,1412,1652,1021,5231,7751,7261,8071,77
    NEUROSCI RES COMMUN0,9691,1910,9170,871,0740,8740,7420,9890,5380,67
    NEUROSCIENCE4,3244,5824,6264,2883,9083,5943,5913,9243,5633,219
    NEUROSCIENTIST2,1742,2331,9181,42
    NEUROSURG CLIN N AM0,8710,9220,9331,2650,783
    NEUROSURG QUART0,50,7670,50,217
    NEUROSURG REV0,3720,290,2560,1560,20,1610,3270,2860,3580,478
    NEUROSURGERY1,5541,4361,671,0060,7311,1132,42,8212,8992,783
    NEUROTOXICOL TERATOL1,5711,7031,8961,5451,9791,1871,321,8222,288
    NEUROTOXICOLOGY0,8951,3841,511,3631,2841,7281,2051,2821,741,576
    NEUROUROL URODYNAM0,7271,1920,7161,3432,1222,082,4182,4381,9682,266
    PEDIATR NEUROL0,9171,2561,0341,0780,8250,9180,9211,1191,0071,11
    PEDIATR NEUROSURG0,4490,3290,5320,7040,770,6560,7960,7350,8110,787
    PERSPECT DEV NEUROBI2,7231,2622,3171,581
    PROG NEUROBIOL7,8097,48186,1845,88855,6887,099,9339,377
    PROG NEURO-PSYCHOPH0,9460,8811,1410,9140,8870,8191,1141,3891,0781,58
    PSYCHIAT CLIN NEUROS0,1380,1910,3820,3480,4520,548
    PSYCHIAT RES-NEUROIM1,2861,9771,6671,7071,9322,1761,3292,191,9192,354
    PSYCHONEUROENDOCRINO1,5711,4861,4831,6992,2541,9921,8692,0453,0083,369
    RESTOR NEUROL NEUROS2,6091,4350,9150,561,1171,1960,50,9110,678
    REV ECUAT NEUROL0,17200,1060,4
    REV NEUROL0,8130,8820,6550,5140,5351,111,451,0130
    REV NEUROL-FRANCE0,6920,598
    REV NEUROLOGIA0,2650,2560,26
    REV NEUROPSYCHOL0,2110,1750,2860,262
    REV NEUROSCI1,7593,3873,43,794
    RIV NEURORADIOL0,0630,1060,0510,128
    SEMIN NEUROL0,6630,5650,4240,5640,6950,5110,671,3661,6351,49
    SEMIN NEUROSCI1,9892,1722,0833,3253,5962,71,667
    STEREOT FUNCT NEUROS0,2840,4460,6570,672
    SURG NEUROL0,7140,6850,6250,5290,3420,3280,7241,041,0180,936
    TECH NEUROSURG0,2150,290
    TRENDS NEUROSCI15,42617,29920,19419,97217,75517,08418,46319,92517,41716,475
    VISUAL NEUROSCI2,162,2122,2722,1372,491,8872,1862,2042,1492,351
    ZBL NEUROCHIR0,2220,40,9390,688
    ACTA NEUROPSYCHIATR0,0890,2980,0360,338
    ACTA PSYCHIAT SCAND1,31,1421,4951,4181,5951,5881,5541,6191,7742,17
    AM J GERIAT PSYCHIAT2,436
    AM J ORTHOPSYCHIAT0,921,0620,8591,0161,0541,7182,2671,4441,9391,55
    AM J PSYCHIAT4,8244,9544,575,126,0696,5015,9396,3416,5776,913
    ANN MED-PSYCHOL0,1050,0550,1120,1440,1920,210,2080,2380,236
    ANNU REV PSYCHOL5,7255,556,8816,8215,4394,8416,3957,5455,8515,979
    ARCH CLIN NEUROPSYCH0,750,8421,3950,988
    ARCH GEN PSYCHIAT8,2279,50511,41611,15511,50910,7519,39810,95211,77811,981
    AUST NZ J PSYCHIAT0,7840,6240,6350,6450,8570,5740,8471,1971,2650,858
    BIOL PSYCHIAT2,572,6012,1482,3522,4842,2542,4053,3194,2695,55
    BIOL PSYCHOL1,0261,0561,81,4741,51,778
    BRIT J MED PSYCHOL0,6710,4790,4590,5920,9390,6670,7020,8810,5620,674
    BRIT J PSYCHIAT2,3092,3192,862,9513,3933,2653,5034,0934,8274,143
    CAN J PSYCHIAT0,70,5430,5470,7180,8321,1511,0581,4621,6231,624
    CHILD NEUROPSYCHOL0,3140,9410,60,565
    CHILD PSYCHIAT HUM D0,2130,2340,3540,5320,3410,4880,4520,3780,4220,625
    CLIN NEUROPSYCHOL0,6740,5610,9480,551
    COGN NEUROPSYCHOL3,397
    COGNITIVE NEUROPSYCH2,92,4922,18
    COGNITIVE PSYCHOL3,7374,1673,4633,711
    COMPR PSYCHIAT1,4451,0711,2731,6221,521,2461,2341,6881,41,28
    DEV NEUROPSYCHOL1,361,0830,8710,914
    DEV PSYCHOBIOL1,1441,1881,4211,0411,2031,4351,5961,3121,3221,286
    EDUC PSYCHOL MEAS0,3240,2280,3680,3170,3160,4440,6180,6230,6080,789
    EUR NEUROPSYCHOPHARM1,9332,3281,6241,8521,7782,3872,0452,437
    EUR PSYCHIAT0,5440,4970,3940,5910,7481,72
    EXP CLIN PSYCHOPHARM1,511,251,7471,726
    GEN HOSP PSYCHIAT0,7390,921,1161,0281,3371,2981,1441,41,5122,65
    HUM PSYCHOPHARM CLIN0,8180,8540,8690,850,9410,5840,6091,1030,968
    INT CLIN PSYCHOPHARM0,750,8161,3642,2271,6381,9261,5571,0962,0762,295
    INT J GERIATR PSYCH1,5631,4951,778
    INT J NEUROPSYCHOPH1,8331,3232,779
    INT J PSYCHIAT MED0,7970,5520,7410,9181,0820,9440,631,2071,0330,714
    INT J PSYCHOPHYSIOL0,870,6840,8750,5851,0890,7031,1481,8291,4891,747
    INT J SPORT PSYCHOL0,2760,4790,8040,386
    J APPL SPORT PSYCHOL0,970
    J CHILD ADOL PSYCHOP1,3881,9331,6092,11,9821,754
    J CLIN PSYCHIAT2,5542,7693,133,3374,2934,0034,0734,1724,4544,735
    J CLIN PSYCHOPHARM3,6793,3663,4964,9635,35,0945,3385,7385,0524,13
    J COMP PSYCHOL1,2021,4041,5171,4091,6021,5631,7441,571,4771,663
    J EXP PSYCHOL ANIM B1,7752,562,5161,1591,9831,3971,2671,441,3651,95
    J EXP PSYCHOL HUMAN2,4062,3322,2472,498
    J EXP PSYCHOL LEARN2,8383,2052,7532,21
    J GERIATR PSYCH NEUR0,8021,2721,2220,8810,9091,263
    J GERONTOL B-PSYCHOL1,5542,3311,2241,5431,1021,594
    J INT NEUROPSYCH SOC2,3762,340
    J MATH PSYCHOL1,4210,8640,80,7660,780,7920,660,6921,0561,195
    J NEUROPSYCH CLIN N1,7372,0371,5731,7951,6973,2092,141,632
    J PSYCHIAT RES1,4031,0181,0851,5312,1591,6051,3622,1522,332,776
    J PSYCHIATR NEUROSCI0,9661,6962,0392,516
    J PSYCHOPHARMACOL1,3081,8881,4261,3811,4662,8272,3282,642
    J PSYCHOPHYSIOL0,5930,5370,6850,587
    J PSYCHOSOM OBST GYN0,4240,6480,3020,6270,5560,60,6060,7170,5290,67
    J PSYCHOSOM RES1,2220,9741,1021,1611,5841,0061,1291,5731,4461,717
    MOL PSYCHIATR2,1624,7567,9428,9276,25
    NEUROL PSYCHIAT BR0,2160,3330,278
    NEUROPSYCHIATRIE0,1250,2350,3870,135
    NEUROPSYCHOBIOLOGY0,3680,3940,9861,050,8550,8210,8460,9531,561,64
    NEUROPSYCHOL REHABIL0,9470,6090,6670,759
    NEUROPSYCHOL REV0,7271,1821,250,92
    NEUROPSYCHOLOGIA1,8852,0531,9661,8282,0592,2672,9392,6872,7783,32
    NEUROPSYCHOLOGY2,6133,1132,7022,486
    NEUROPSYCHOPHARMACOL3,6612,5212,783,5673,9364,1054,3184,8584,5794,715
    PERCEPT PSYCHOPHYS1,2521,492
    PHARMACOPSYCHIATRY1,1331,41,61,1171,2182,0532,3042,8032,39
    PROG NEURO-PSYCHOPH0,9460,8811,1410,9140,8870,8191,1141,3891,0781,58
    PSYCHIAT CLIN NEUROS0,1380,1910,3820,3480,4520,548
    PSYCHIAT RES1,8751,4741,6921,4731,4891,3271,4241,5511,5571,775
    PSYCHIAT RES-NEUROIM1,2861,9771,6671,7071,9322,1761,3292,191,9192,354
    PSYCHIATR GENET1,862,0162,6091,257
    PSYCHIATR SERV0,9351,4661,571,7471,7951,589
    PSYCHIATRY0,6230,6670,9031,260,7310,7681,2550,9440,8271,2
    PSYCHOBIOLOGY2,0711,7911,5380,9521,2321,0510,8151,2821,1941,652
    PSYCHOL BULL4,9585,1976,6976,9666,5916,0386,3467,796,9136,87
    PSYCHOL MED2,1772,6632,4332,7152,8153,0173,1243,3893,4123,119
    PSYCHOL REV6,4856,57,1875,0585,217,068,2396,8036,0695,756
    PSYCHOMETRIKA0,7870,6360,6230,7680,8330,6560,9330,8240,8980,85
    PSYCHONEUROENDOCRINO1,5711,4861,4831,6992,2541,9921,8692,0453,0083,369
    PSYCHO-ONCOL1,388
    PSYCHOPATHOLOGY0,4330,3270,4460,4510,7070,5750,4740,4250,5470,469
    PSYCHOPHARMACOL BULL1,6711,7291,4391,4311,5711,8162,592,2452,809
    PSYCHOPHARMACOLOGY2,7692,52,5492,8822,5992,9333,0322,9182,8043,145
    PSYCHOPHARMAKOTHERAP0,1970,3010,171
    PSYCHOPHYSIOLOGY2,6382,3492,6592,9482,8272,7742,4323,0063,1063,35
    PSYCHOSOM MED2,6932,3112,8082,9123,0313,0893,0462,6243,2462,815
    PSYCHOSOMATICS1,41,0711,1691,3212,1321,7071,5411,1741,5551,926
    PSYCHOTHER PSYCHOSOM0,3760,7521,0591,0471,5781,8052,1032,2592,3723,429
    Q J EXP PSYCHOL-A1,9481,5611,4521,28
    Q J EXP PSYCHOL-B1,31,1321,2751,1281,3491,4191,221,33311,4
    REV NEUROPSYCHOL0,2110,1750,2860,262
    SPORT PSYCHOL0,8730,9670,6490,76
    Z PSYCHOSOM MED PSYC0,3590,5760,460,4910,440,371,2090,4440,633
    BEHAV BRAIN RES1,8541,4441,5631,8621,6132,342,7962,3182,2632,473
    BEHAV BRAIN SCI0,2970,4260,63915,62598,1188,811,27614,2517,312
    BRAIN3,5893,8935,0354,8675,7395,3815,9527,3747,3037,47
    BRAIN BEHAV EVOLUT1,5491,9591,4171,5771,491,7861,5591,651,3811,635
    BRAIN BEHAV IMMUN2,7592,5242,3191,4841,951,752,1111,6882,1842,23
    BRAIN COGNITION1,51,231,3731,111,0730,5660,5080,7360,630,791
    BRAIN DEV-JPN0,7870,5760,6880,7090,5390,570,7611,3031,1551,49
    BRAIN INJURY0,880,8431,2561,0851,0170,9140,924
    BRAIN LANG1,1970,7130,9761,6581,41,5792,1161,9291,4731,38
    BRAIN PATHOL4,258,5676,4555,6634,8974,1546,4358,654
    BRAIN RES2,8652,8542,8692,6872,5262,1192,152,3022,5262,489
    BRAIN RES BULL1,6921,5991,8111,7941,6411,7081,651,9771,7581,783
    BRAIN RES PROTOC0,2820,7811,0671,284
    BRAIN RES REV9,7429,09410,20713,9627,61911,5536,256,6519,2127,72
    BRAIN TOPOGR0,5771,9061,5961,745
    COGNITIVE BRAIN RES0,882,2221,731,5762,7552,3332,7332,884
    DEV BRAIN DYSFUNCT0,1480,213
    DEV BRAIN RES2,3222,1772,2072,2461,9111,8231,6951,5351,8271,662
    EXP BRAIN RES2,3442,4092,2271,9672,0491,8982,0182,2462,1372,36
    HUM BRAIN MAPP10,0494,7385,285,1635,688
    J BRAIN RES0,3970,6710,2790,182
    METAB BRAIN DIS0,7321,1221,0290,631,751,311,53711,4111,91
    MOL BRAIN RES4,5223,8014,1343,483,4772,7422,4752,5392,6222,538
    PROG BRAIN RES1,8881,2611,4121,6821,4880,7721,951,4252,521,49
    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +

    Journal

    1992

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    2004

    ANNU REV NEUROSCI20,42227,62917,95329,08333,62521,95223,02322,6526,67627,15224,09129.08323.143
    BEHAV BRAIN RES1,8541,4441,5631,8621,6132,342,7962,3182,2632,4732,7911.862
    BEHAV BRAIN SCI0,2970,4260,63915,62598,1188,811,27614,2517,3128,73015.6257.125
    BEHAV NEUROSCI2,7292,993,2632,9692,5282,6653,0262,7192,7512,862.7572.969
    BRAIN3,5893,8935,0354,8675,7395,3815,9527,3747,3037,477.1224.8678.201
    BRAIN COGNITION1,51,231,3731,111,0730,5660,5080,7360,630,7911.0931.110
    CEREB CORTEX5.322
    CLIN NEUROPHYSIOL1,6721,9222,120
    CLIN NEUROSCI0,6561,3331,3531,751,0141,7811.333
    COGNITIVE BRAIN RES0,882,2221,731,5762,7552,3332,7332,8842,4042.222
    COGNITIVE NEUROPSYCH2,92,4922,18
    COGN NEUROPSYCHOL3,3973,391
    COGNITIVE PSYCHOL3,7374,1673,4633,7114,059
    CURR OPIN NEUROBIOL5,3457,0797,3568,8549,2879,2779,99510,7185.3457.937
    ELECTROEN CLIN NEURO1,8721,6991,6171,8942,0272,42,452,8613,327N/AN/A1.894
    EUR J NEUROSCI4,824,564,9514,9214,3033,9473,823,8993,8623,9194,1634.921
    EXP BRAIN RES2,3442,4092,2271,9672,0491,8982,0182,2462,1372,362,3001.967
    HUM BRAIN MAPP10,0494,7385,285,1635,6885.076
    INT J NEUROSCI0,5270,6220.579
    J COGNITIVE NEUROSCI3,5714,0634,3833,6794,8445,225,7935,1156,7366.096
    J NEUROSCI7,168,0358,6578,2057,9557,9158,4038,9558,5028,1788.0458.317.907
    NAT NEUROSCI8,86312,63615,66814.85715.1416.980
    NAT REV NEUROSCI014,35324.04727.0121.225
    NEUROIMAGE2,7860,7781,6174,3115,6118,936,8577,8795.624
    NEURON15,58917,25618,34816,61916,95315,82116,50516,78215,08114,15313.84614.1114.439
    NEUROREPORT2,2773,0792,572,4872,2622,5912,6822,6962,3742.265
    NEUROSCI LETT2,4192,6452,7032,3182,091,7681,9342,0852,0912,212.100
    Q J EXP PSYCHOL-A1,9481,5611,4521,281.722
    Q J EXP PSYCHOL-B1,31,1321,2751,1281,3491,4191,221,33311,41.256
    TRENDS COGN SCI11,6608.1297.992
    TRENDS NEUROSCI15,42617,29920,19419,97217,75517,08418,46319,92517,41716,47514.47412.6314.794
    + + +


    +

    DIVERS

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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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'delimiter', ';'); +address='http://jcr02.isiknowledge.com/JCR/JCR?RQ=IMPACT&rank=1&journal=' +%ic=zeros(length(titles),5)*NaN; +for i=i:length(titles) + titles{i} + [s,b,u] = web([address strrep(titles{i},' ', '+')]); + txt=get(b, 'Htmltext'); + p=findstr('Impact Factor', txt); + p=fliplr(p(4:end-2)); + for j=1:length(p) + z=0; + %z=findstr('Cites to recent articles', txt(p(j)+[1:3000])) + z=z+findstr('dataTable', txt(p(j)+z+[1:2000])); + ic(i,j)=str2num(strrep(strrep(strrep(txt(p(j)+z(6)+[14:19]),'<', ''), '/', ''), 'b', '')); + end + ic(i,:) + + +end + + + +return + + + +ANNU+REV+NEUROSCI \ No newline at end of file diff --git a/misc/isi/isi.mat b/misc/isi/isi.mat new file mode 100644 index 0000000000000000000000000000000000000000..c03300ec4fdd129721aaac7a8bdd8cd87bfe3794 GIT binary patch literal 10464 zcmc(l3yc-z6~|}hKK9A7AY2|=yu4|Z0yPLi=s7^uqJmh7CB~T20#Sm{(yeW+r6EmY zh#|xvwJ)?nmD;qXHG~*rO|fdJZLL~KL8N3^cbCO|vUl%m@9yo)_dnl^osa3_nwFc8 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PSYCHIAT;0006-3223;17553;6.159;0.900;300;5.5; +J CEREBR BLOOD F MET;0271-678X;10182;5.673;0.826;144;6.6; +NEUROBIOL AGING;0197-4580;5501;5.516;1.240;129;5.4; +CEREB CORTEX;1047-3211;7096;5.322;1.097;134;5.0; +J COGNITIVE NEUROSCI;0898-929X;5578;5.275;0.466;148;5.1; +J NEUROPATH EXP NEUR;0022-3069;6612;5.037;0.518;112;6.9; +NEUROPSYCHOPHARMACOL;0893-133X;7448;4.941;0.839;236;4.5; +NEUROIMAGE;1053-8119;11323;4.869;0.601;531;3.5; +HUM BRAIN MAPP;1065-9471;3898;4.815;0.575;73;5.6; +BRAIN RES REV;0165-0173;5439;4.617;0.286;49;6.0; +HIPPOCAMPUS;1050-9631;3766;4.516;0.710;93;5.4; +NEUROBIOL LEARN MEM;1074-7427;1916;4.443;0.644;59;5.2; +CURR OPIN NEUROL;1350-7540;2261;4.017;0.551;78;3.9; +COGNITIVE PSYCHOL;0010-0285;3413;3.977;1.000;21;>10.0; +EUR J NEUROSCI;0953-816X;16736;3.820;0.543;727;4.7; +J NEUROPHYSIOL;0022-3077;34116;3.592;0.885;573;7.7; +NEUROSCIENCE;0306-4522;30136;3.456;0.622;662;7.0; +NEUROSCIENTIST;1073-8584;834;3.175;0.440;50;3.3; +BEHAV BRAIN RES;0166-4328;8530;2.992;0.336;307;6.3; +CLIN NEUROPHYSIOL;1388-2457;3828;2.538;0.370;311;3.6; +J EXP PSYCHOL HUMAN;0096-1523;7203;2.529;0.338;74;>10.0; +CORTEX;0010-9452;2484;2.472;0.905;42;>10.0; +MUSCLE NERVE;0148-639X;6635;2.432;0.319;182;6.9; +BRAIN RES BULL;0361-9230;7189;2.429;0.234;141;7.5; +NEUROREPORT;0959-4965;17280;2.351;0.274;566;5.8; +COGNITIVE BRAIN RES;0926-6410;2166;2.394;0.219;151;4.4; +EXP BRAIN RES;0014-4819;15613;2.304;0.328;344;9.6; +J NEUROSCI METH;0165-0270;5271;1.894;0.383;230;7.7; +NEUROPSYCHOLOGIA;0028-3932;9865;3.668;0.400;175;8.3; +EXP NEUROL;0014-4886;11916;3.369;0.598;249;6.8; +REV NEUROSCI;0334-1763;601;2.860;0.148;27;5.4; +SYNAPSE;0887-4476;4545;2.827;0.474;116;6.3; +BEHAV NEUROSCI;0735-7044;6335;2.819;0.481;154;8.4; +COGN NEUROPSYCHOL;0264-3294;1462;2.746;0.372;43;7.9; +BRAIN RES;0006-8993;58204;2.389;0.302;1037;>10.0; +J PSYCHOPHARMACOL;0269-8811;1454;2.336;0.227;66;5.3; +J PSYCHIATR NEUROSCI;1180-4882;689;2.333;0.467;30;4.8; +PSYCHOPHYSIOLOGY;0048-5772;5530;2.257;0.456;103;9.9; +EUR J NEUROL;1351-5101;1485;2.225;0.234;124;3.8; +J COMPUT NEUROSCI;0929-5313;695;2.200;0.216;37;4.8; +NEUROSCI RES;0168-0102;2988;2.155;0.336;149;6.0; +PROG NEURO-PSYCHOPH;0278-5846;2445;2.149;0.203;158;5.4; +NEUROSCI LETT;0304-3940;25138;2.019;0.248;1101;7.1; +J EXP PSYCHOL LEARN;0278-7393;5821;2.015;0.367;98;9.9; +J NEUROPSYCH CLIN N;0895-0172;1883;1.817;0.133;60;7.5; +VISION RES;0042-6989;12344;1.812;0.290;293;9.3; +BIOL PSYCHOL;0301-0511;1602;1.637;1.029;34;7.5; +BRAIN LANG;0093-934X;3625;1.614;0.431;153;8.5; +HEARING RES;0378-5955;5292;1.578;0.206;160;8.3; +INT J PSYCHOPHYSIOL;0167-8760;1860;1.563;0.333;66;5.9; +VISUAL NEUROSCI;0952-5238;2569;1.554;0.264;91;8.1; +J CLIN NEUROPHYSIOL;0736-0258;1775;1.535;0.188;48;6.9; +J PHYSIOL-PARIS;0928-4257;1079;1.505;0.150;20;7.1; +NEUROL CLIN;0733-8619;1250;1.489;0.057;53;8.5; +PERCEPT PSYCHOPHYS;0031-5117;5622;1.471;0.170;94;>10.0; +Q J EXP PSYCHOL-A;0272-4987;2248;1.426;0.197;61;9.9; +EUR NEUROL;0014-3022;2121;1.312;0.175;120;7.8; +Q J EXP PSYCHOL-B;0272-4995;578;1.289;0.706;17;9.4; +PERCEPTION;0301-0066;2805;1.271;0.155;103;9.8; +EXP AGING RES;0361-073X;516;1.250;0.167;24;9.6; +NETWORK-COMP NEURAL;0954-898X;597;1.227;0.133;15;7.7; +BRAIN RES PROTOC;1385-299X;607;1.224;0.154;39;4.8; +CLIN NEUROPSYCHOL;1385-4046;1100;1.162;0.000;41;7.8; +BRAIN COGNITION;0278-2626;2427;1.148;0.236;144;7.4; +CLIN NEUROSCI RES;1566-2772;167;1.076;0.000;37;3.1; +ACTA NEUROBIOL EXP;0065-1400;482;1.075;0.694;49;7.1; +J NEUROIMAGING;1051-2284;631;1.068;0.385;65;5.1; +NEUROCASE;1355-4794;572;0.978;0.061;49;5.2; +SOMATOSENS MOT RES;0899-0220;669;0.953;0.053;19;9.9; +SPATIAL VISION;0169-1015;644;0.905;0.120;25;7.7; +J CLIN NEUROSCI;0967-5868;671;0.834;0.057;229;3.2; +INT J NEUROSCI;0020-7454;1557;0.654;0.129;116;>10.0; +ENCEPHALE;0013-7006;582;0.413;0.013;79;8.2; +NEW ENGL J MED +LANCET +NAT MED diff --git a/misc/labnic_expe_forms_from_gmail.m b/misc/labnic_expe_forms_from_gmail.m new file mode 100644 index 0000000..e69de29 diff --git a/misc/physique1.m b/misc/physique1.m new file mode 100644 index 0000000..9c5c284 --- /dev/null +++ b/misc/physique1.m @@ -0,0 +1,90 @@ +% Cinématique du solide avec frottements + +% conditions initiales + +% solide +m=5; % Kg +V=0.1; % m^3 +alpha=0; % angle z par rapport à x (degrés) +betha=0; % angle x par rapport à y (degrés) +v0=40000; % Km/h; ratio pour exprimer en m/s= 10/36 +p=[0 0 500000]; % position du solide en metres +pinit=p; + +% environnement + w=[0 0 0]; % vitessse du vent + c=0;%10^-3; % coefficient de frottement de l'air + +% constantes +G=6.670*10^-11; % Gravitation universelle +M=6*10^24; % masse de la Terre (Kg) +R=6378*1000; % rayon de la Terre (m) + +% parametres d'intégration +dt=1; % secondes +Time=100000; % Temps total (secondes) +n_i=Time/dt; % Nombre d'itérations + +alpha=(alpha/360)*(2*pi); +betha=(betha/360)*(2*pi); +r=sqrt((R+p(3))^2+p(1)^2+p(2)^2); +g=G*M/r^2; +v0=sqrt(2*(R+p(3))*g); +v_v=[v0*cos(alpha)*(10/36) v0*sin(betha)*(10/36) v0*sin(alpha)*(10/36)]; +v_v_ref=v_v*Time; +Einit=m*g*(r-R)+0.5*m*sum((v_v+w).^2); % Energie totale du system à t0 + + +figure +[X,Y,Z]=sphere(100);surf(R*X,R*Y,R*Z-R) +shading interp +colormap(1-gray) +axis equal +%axis([-max(pinit) max(pinit) -max(pinit) max(pinit) -max(pinit) max(pinit)]) +%axis([0 v0*2*(10/36) 0 v0*(10/36) -5 v0*(10/36)]) +%view(0,0); +hold on + +for s_i=1:n_i +r=sqrt((R+p(3))^2+p(1)^2+p(2)^2); +% Accélération +% gravitationnelle +g=G*M/r^2; +v_g=[-g*p(1)/r -g*p(2)/r -g*(p(3)+R)/r]; +% frottements de l'air +v_c=-c*(v_v.^2)/m; +% if p(3)<=0 +% v_c(3)=-v_c(3); +% end +% Totale +v_a=v_g+v_c; + +% Energie mécanique +Ep=m*g*(r-R); % energie potentielle +Ec=0.5*m*sum(v_v.^2); % energie cinétique +E=Ep+Ec; % energie mécanique +T=Einit-E; % energie thermique dégagée + +% Vitesse +if r> exit.m +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-02-02 Creation +% +% ----------------------------- Script History --------------------------------- + +if isequal(questdlg('Sure you want to quit Matlab?', 'Exit', 'No'), 'Yes') +a=which('-all','exit'); +cd(fileparts(a{2}((findstr('(',a{2})+1):(findstr(')',a{2})-1)))) +exit +end \ No newline at end of file diff --git a/misc/worldhappiness.dat b/misc/worldhappiness.dat new file mode 100644 index 0000000..70dcf07 --- /dev/null +++ b/misc/worldhappiness.dat @@ -0,0 +1,244 @@ +The World Map of Happiness - http://www.le.ac.uk/pc/aw57/world/sample.html + +This is an interactive map - double click on a country to view in more detail. + +Key: Red = High Levels of Happiness + +Use of this map is subject to the credit line: Adrian White, Analytic Social Psychologist, University of Leicester. + +A high resolution image for downloading in .eps format is available by clicking here: .eps Download . Please feel free to download this map for publication, but use of the map is subject to the credit line: Adrian White, Analytic Social Psychologist, University of Leicester. + +To download a .bmp version click here : .bpm Download + +To download a .pdf version click here : .pdf Download + +To download an .fh11 version click here : .fh11 Download + +1. This is the first map to illustrate international differences in happiness. + +2. UK comes 41st out of 178 countries. + +3. UK doing better than most of our similar neighbours and competitors (France 62nd, Italy 50th, Spain 46th, Japan 90th, Chine 82nd, India 125th). However other counties did do better (Germany 35th, USA 23rd, Ireland 11th). A full copy of the league table is published below. + +4. Health is more important than wealth or education. Further analysis was performed to examine the links between satisfaction with life and measures of life expectancy (health), wealth (GDP per capita) and education (access to secondary level education).It was found that satisfaction with life correlated most closely with health (a correlation of .62), followed by wealth (.52) and then education (.51). (All pearson's r correlations were significant at the p<.001 level) + +5. The map is based on an analysis of the results from over 100 studies. It uses data published by by UNESCO, the CIA, the New Economics Foundation, the WHO, the Veenhoven Database, the Latinbarometer, the Afrobarometer, and the UNHDR. + +6. The map is being published in a psychology journal in September, and will be presented at a Psychology conference later in the year. + + + +Quotes + +Adrian White said “The concept of happiness, or satisfaction with life, is currently a major area of research in economics and psychology, most closely associated with new developments in positive psychology. It has also become a feature in the current political discourse in the UK.” + +"There is increasing political interest in using measures of happiness as a national indicator in conjuntion with measures of wealth. A recent BBC survey found that 81% of the population think the Government should focus on making us happier rather than wealthier." +“It is worth remembering that the UK is doing relatively well in this area, coming 41st out of 178 nations”. + +"Further analysis showed that a nation's level of happiness was most closely associated with health levels (correlation of .62), followed by wealth (.52), and then provision of education (.51)." + +"The three predictor variables of health, wealth and education were also very closely associated with each other, illustrating the interdependence of these factors." + +“There is a belief that capitalism leads to unhappy people. However, when people are asked if they are happy with their lives, people in countries with good healthcare, a higher GDP per captia, and access to education were much more likely to report being happy.” +“The frustrations of modern life, and the anxieties of the age, seem to be much less significant compared to the health, financial and educational needs in other parts of the World. The current concern with happiness levels in the UK may well be a case of the 'worried well'." + + + +World Happiness League Table + +SWL Ranking is each country's position in the international ranking of happiness +Country SWL Ranking (1) SWL Index (2) Life Expectancy (3) GDP per capita (4) Access to education score (5) +Albania 157 153.33 73.8 4.9 75.8 +Algeria 134 173.33 71.1 7.2 66.9 +Angola 149 160 40.8 3.2 NaN +Antigua And Barbuda 16 246.67 73.9 11 NaN +Argentina 56 226.67 74.5 13.1 93.7 +Armenia 172 123.33 71.5 4.5 NaN +Australia 26 243.33 80.3 31.9 NaN +Austria 3 260 79 32.7 99.1 +Azerbaijan 144 163.33 66.9 4.8 80.2 +Bahamas 5 256.67 69.7 20.2 NaN +Bahrain 33 240 74.3 23 102 +Bangladesh 104 190 62.8 2.1 53.7 +Barbados 27 243.33 75 17 101.1 +Belarus 170 133.33 68.1 6.9 94.2 +Belgium 28 243.33 78.9 31.4 145.4 +Belize 48 230 71.9 6.8 71.6 +Benin 122 180 54 1.1 21.8 +Bhutan 8 253.33 62.9 1.4 NaN +Bolivia 117 183.33 64.1 2.9 NaN +Bosnia & Herze 137 170 74.2 6.8 NaN +Botswana 123 180 36.3 10.5 81.8 +Brazil 81 210 70.5 8.4 103.2 +Brunei Darussalam 9 253.33 76.4 23.6 NaN +Bulgaria 164 143.33 72.2 9.6 92 +Burkina Faso 152 156.67 47.5 1.3 10 +Burma 130 176.67 60.2 1.7 NaN +Burundi 178 100 43.6 0.7 NaN +Cambodia 110 186.67 56.2 2.2 17.3 +Cameroon 138 170 45.8 2.4 NaN +Canada 10 253.33 80 34 102.6 +Cape Verdi 100 193.33 70.4 6.2 NaN +Central African Republic 145 163.33 39.3 1.1 NaN +Chad 159 150 43.6 1.5 11.5 +Chile 71 216.67 77.9 11.3 87.5 +China 82 210 71.6 6.8 62.8 +Columbia 34 240 72.4 7.9 70.9 +Comoros 97 196.67 63.2 0.6 NaN +Congo Democratic 176 110 43.1 0.7 18.4 +Congo Republic 105 190 52 1.3 NaN +Costa Rica 13 250 78.2 11.1 50.9 +Croatia 98 196.67 75 11.6 NaN +Cuba 83 210 77.3 3.5 NaN +Cyprus 49 230 78.6 7.14 NaN +Czech Republic 77 213.33 75.6 19.5 87.9 +Denmark 1 273.33 77.2 34.6 NaN +Dijbouti 150 160 52.8 1.3 14.7 +Dominica 29 243.33 75.6 5.5 NaN +Dominican Republic 42 233.33 67.2 7 NaN +Ecuador 111 186.67 74.3 4.3 56.7 +Egypt 151 160 69.8 3.9 NaN +El Salvador 61 220 70.9 4.7 49.8 +Equitorial Guinea 135 173.33 43.3 50.2 NaN +Eritrea 162 146.67 53.8 1 28.2 +Estonia 139 170 71.3 16.7 107 +Ethiopia 153 156.67 47.6 0.9 5.2 +Fiji 57 223.33 67.8 6 NaN +Finland 6 256.67 78.5 30.9 124.5 +France 62 220 79.5 29.9 108.7 +Gabon 88 206.67 54.5 6.8 54.4 +Gambia 106 190 55.7 1.9 27 +Georgia 169 136.67 70.5 3.3 77.7 +Germany 35 240 78.7 30.4 99 +Ghana 89 206.67 56.8 2.5 37.3 +Greece 84 210 78.3 22.2 94.6 +Grenada 72 216.67 65.3 5 NaN +Guatemala 43 233.33 67.3 4.7 32.7 +Guinea 140 170 53.7 2 NaN +Guinea-Bissau 124 180 44.7 0.8 20.4 +Guyana 36 240 63.1 4.6 81 +Haiti 118 183.33 51.6 1.7 NaN +Honduras 37 240 67.8 2.9 NaN +Hong Kong 63 220 81.6 32.9 NaN +Hungary 107 190 72.7 16.3 98.6 +Iceland 4 260 80.7 35.6 108.8 +India 125 180 63.3 3.3 49.9 +Indonesia 64 220 66.8 3.6 NaN +Iran 96 200 70.4 8.3 80 +Ireland 11 253.33 77.7 41 123.1 +Israel 58 223.33 79.7 24.6 93 +Italy 50 230 80.1 29.2 92.8 +Ivory Coast 160 150 45.9 1.6 21.7 +Jamaica 44 233.33 70.8 4.4 83.6 +Japan 90 206.67 82 31.5 102.1 +Jordan 141 170 71.3 4.7 87.7 +Kazakhstan 101 193.33 63.2 8.2 87 +Kenya 112 186.67 47.2 1.1 NaN +Kuwait 38 240 76.9 19.2 55.6 +Kyrgyzstan 65 220 66.8 2.1 83 +Laos 126 180 54.7 1.9 35.6 +Latvia 154 156.67 71.6 13.2 88.9 +Lebanon 113 186.67 72 6.2 78.2 +Lesotho 165 143.33 36.3 2.5 28 +Libya 108 190 73.6 11.4 NaN +Lithuania 155 156.67 72.3 13.7 93.4 +Luxembourg 12 253.33 78.5 55.6 95.3 +Macedonia 146 163.33 73.8 7.8 NaN +Madagascar 103 193.33 55.4 0.9 NaN +Malawi 158 153.33 39.7 0.6 NaN +Malaysia 17 246.67 73.2 12.1 98.8 +Maldives 66 220 66.6 3.9 42.7 +Mali 131 176.67 47.9 1.2 15 +Malta 14 250 78.4 19.9 90.4 +Mauritania 132 176.67 52.7 2.2 NaN +Mauritius 73 216.67 72.2 13.1 107.3 +Mexico 51 230 75.1 10 73.4 +Moldova 175 116.67 67.7 1.8 NaN +Mongolia 59 223.33 64 1.9 64.4 +Morocco 114 186.67 69.7 4.2 39.3 +Mozambique 127 180 41.9 1.3 13.9 +Namibia 74 216.67 48.3 7 59.8 +Nepal 119 183.33 61.6 1.4 53.9 +Netherlands 15 250 78.4 30.5 124.1 +New Zealand 18 246.67 79.1 25.2 112.9 +Nicaragua 85 210 69.7 2.9 NaN +Niger 161 150 44.4 0.9 NaN +Nigeria 120 183.33 43.4 1.4 NaN +Norway 19 246.67 79.4 42.3 117 +Oman 30 243.33 74.1 13.2 67.8 +Pakistan 166 143.33 63 2.4 39 +Palestine 128 180 72.5 5.8 80.7 +Panama 39 240 74.8 7.2 68.7 +Papua New Guinea 86 210 55.3 2.6 21.2 +Paraguay 75 216.67 71 4.9 56.9 +Peru 115 186.67 70 5.9 80.8 +Philippines 78 213.33 70.4 5.1 75.9 +Poland 99 196.67 74.3 13.3 NaN +Portugal 92 203.33 77.2 19.3 112 +Qatar 45 233.33 72.8 27.4 92.4 +Romania 136 173.33 71.3 8.2 80.2 +Russia 167 143.33 65.3 11.1 81.9 +Rwanda 163 146.67 43.9 1.5 12.1 +Samoa Western 52 230 70.2 5.8 76 +Sao Tome And Prinicpe 60 223.33 63 1.2 NaN +Saudi Arabia 31 243.33 71.8 12.8 68.5 +Senegal 116 186.67 55.7 1.8 19.5 +Seychelles 20 246.67 72.7 7.8 NaN +Sierra Leone 143 166.67 40.8 0.8 23.9 +Singapore 53 230 78.7 28.1 NaN +Slovakia 129 180 74 16.1 86.6 +Slovenia 67 220 76.4 21.6 98.8 +Soloman Islands 54 230 62.3 1.7 NaN +South Africa 109 190 48.4 12 90.2 +South Korea 102 193.33 77 20.4 97.4 +Spain 46 233.33 79.5 25.5 112.8 +Sri Lanka 93 203.33 74 4.3 NaN +St Kitts And Nevis 21 246.67 70 8.8 NaN +St Lucia 47 233.33 72.4 5.4 94.3 +St Vincent And The Grenadines 40 240 71.1 2.9 NaN +Sudan 173 120 56.4 2.1 28.8 +Suriname 32 243.33 69.1 4.1 50.7 +Swaziland 168 140 32.5 5 NaN +Sweden 7 256.67 80.2 29.8 152.8 +Switzerland 2 273.33 80.5 32.3 99.9 +Syria 142 170 73.3 3.9 42 +Taiwan 68 220 76.1 27.6 NaN +Tajikistan 94 203.33 63.6 1.2 76 +Tanzania 121 183.33 46 0.7 5.31 +Thailand 76 216.67 70 8.3 79 +Timor-Leste 69 220 65.5 0.4 NaN +Togo 147 163.33 54.3 1.7 NaN +Tonga 70 220 72.2 2.3 NaN +Trinidad And Tobago 55 230 69.9 16.7 78.4 +Tunisia 79 213.33 73.3 8.3 74.6 +Turkey 133 176.67 68.7 8.2 NaN +Turkmenistan 171 133.33 62.4 8 NaN +UAE 22 246.67 78 43.4 74.4 +Uganda 156 156.67 47.3 1.8 NaN +Ukraine 174 120 66.1 7.2 92.8 +United Kingdom 41 236.67 78.4 30.3 157.2 +Uruguay 87 210 75.4 9.6 91.6 +USA 23 246.67 77.4 41.8 94.6 +Uzbekistan 80 213.33 66.5 1.8 NaN +Vanuate 24 246.67 68.6 2.9 28.5 +Venzuela 25 246.67 72.9 6.1 NaN +Vietnam 95 203.33 70.5 2.8 64.6 +Yemen 91 206.67 60.6 0.9 NaN +Zambia 148 163.33 37.5 0.9 25.5 +Zimbabwe 177 110 36.9 2.3 45.3 + +Notes + +1. SWL (satisfaction with life) rating calculated from data published by New Economics Foundation (2006). + +2. SWL (satisfaction with life) index calculated from data published by New Economics Foundation (2006). + +3. Life Expectancy from UN Human Development Report (2003) + +4. GDP per capita from figure published by the CIA (2006), figure in US$. + +5. Access to secondary education rating from UNESCO (2002) + + + +If you are interested in the environment and personality, and live in the UK, please feel free to participate in our online study on the environment by following this link: NEPS diff --git a/misc/worldhappiness.m b/misc/worldhappiness.m new file mode 100644 index 0000000..e69de29 diff --git a/mkdirr.m b/mkdirr.m new file mode 100644 index 0000000..eacd424 --- /dev/null +++ b/mkdirr.m @@ -0,0 +1,28 @@ +function []=mkdirr(p) +% mkdirr - recursive mkdir +% +%Native MKDIR waits a relative path: +% >> mkdir('/usr/bin/newpath1/newpath2') +%will therefore create a usr/bin/newpath1... +%in the CURRENT directory whereas our +% >> mkdirr('/usr/bin/newpath1/newpath2') +%will make newpath1 and newpath2 in /usr/bin +i=0; +while not(exist(p, 'dir')) + i=i+1; + [p,np{i},e]=fileparts(p); + np{i}=[np{i},e]; + if isempty(np{i}) + break + end +end +lcd=pwd; +if isempty(p) + p='.'; +end +for j=i:-1:1 + cd(p) + mkdir(np{j}); + p=fullfile(p,np{j}); +end +cd(lcd) \ No newline at end of file diff --git a/mne.m b/mne.m new file mode 100644 index 0000000000000000000000000000000000000000..d09cd674a28b979f12eed1e834f618a7cc777641 GIT binary patch literal 59 zcmYc*%}XxH%+FI$i1vz4%Pi3;N-fSzDJ_mwuvN&-OVvouNX#wJ$xQ@Fq?hLCjyHPtTcq2NTe1ux+ji)dR{<8~tprZptn-A38$&L*>F*8I`Q zOsLw*LI_e~UE_56Of{%;^q6o z`@P?LzxR8;mk+s2W|EUHt`B@!@=n7jY33t5vu+GaPk6az0&x6;aSCrKC=uF9| ztFM{0S4^#<7PM-$W~ocMYT8xRsH#&hX4OiqsK>(Lz2iHjKMKtJ@S}08<7u!VIzPMq z@y;)7n~ld@KiG(OHrUVAo_1}p@l59@_A^GIB=>rqrjtY|WtejBj!k&64H}8=Qyw6S za3s--elO=zRo9QWbM_?%DW0W8c4Qul&mGxueb4Tci4vXU^>LLbE%Oq8v6Swv@ZwXu z&cB$bT>CERF-t#d@%o1f53)Z``}U|ri!rmPSsGDA=5fHyleSM1+h!{$wy?^ey_ zwkG(Dqi$NOYl(JPX3Tb8|Ks>=^P%=g>l27 za0{~GQ_|0JbG+w5GGvE1{^VRbyZPHT=iHHHhU~*KX+s9O_E0n#YMu{~wco29aBK7C zb~3b(e|espa}I@M$LGcaiv4hNLN-D6UdI~uJEMGE9_hUWJ{1B2AOHd&00JNY0w4ea zAOHd&00Q@cz%8{`Kac1N9x z19jkl00@8p2!H?xfB*=900@8p2!H?x+yeoAZe9K#-Hthd)) +axis image +if NewAxes + colormap(bone) + if slicing==3 + view(2) + else + view(60,30) + end +end + diff --git a/mseq.m b/mseq.m new file mode 100644 index 0000000..5b8cc46 --- /dev/null +++ b/mseq.m @@ -0,0 +1,422 @@ +function ms=mseq(baseVal,powerVal,shift,whichSeq) +% Maximum length sequence assuming 2,3,5 distinct values +% +% [ms]=MSEQ(baseVal,powerVal[,shift,whichSeq]) +% +% OUTPUT: +% ms = generated maximum length sequence, of length basisVal^powerVal-1 +% +% INPUT: +% baseVal -nuber of sequence levels (2,3, or 5 allowed) +% powerVal -power, so that sequence length is baseVal^powerVal-1 +% shift -cyclical shift of the sequence +% whichSeq -sequence istantiation to use +% (numer of sequences varies with powreVal - see the code) + +% (c) Giedrius T. Buracas, SNL-B, Salk Institute +% Register values are taken from: WDT Davies, System Identification +% for self-adaptive control. Wiley-Interscience, 1970 +% When using mseq code for design of FMRI experiments, please, cite: +% G.T.Buracas & G.M.Boynton (2002) Efficient Design of Event-Related fMRI +% Experiments Using M-sequences. NeuroImage, 16, 801-813. + +if nargin<4, whichSeq=1; end +if nargin<3, shift=1; end; + +bitNum=baseVal^powerVal-1; + +register=ones(powerVal,1); + +if baseVal==2, +switch powerVal, +case 2, tap(1).No=[1,2]; +case 3, tap(1).No=[1,3]; + tap(2).No=[2,3]; +case 4, tap(1).No=[1,4]; + tap(2).No=[3,4]; +case 5, tap(1).No=[2,5]; + tap(2).No=[3,5]; + tap(3).No=[1,2,3,5]; + tap(4).No=[2,3,4,5]; + tap(5).No=[1,2,4,5]; + tap(6).No=[1,3,4,5]; +case 6, tap(1).No=[1,6]; + tap(2).No=[5,6]; + tap(3).No=[1,2,5,6]; + tap(4).No=[1,4,5,6]; + tap(5).No=[1,3,4,6]; + tap(6).No=[2,3,5,6]; +case 7, tap(1).No=[1,7]; + tap(2).No=[6,7]; + tap(3).No=[3,7]; + tap(4).No=[4,7]; + tap(5).No=[1,2,3,7]; + tap(6).No=[4,5,6,7]; + tap(7).No=[1,2,5,7]; + tap(8).No=[2,5,6,7]; + tap(9).No=[2,3,4,7]; + tap(10).No=[3,4,5,7]; + tap(11).No=[1,3,5,7]; + tap(12).No=[2,4,6,7]; + tap(13).No=[1,3,6,7]; + tap(14).No=[1,4,6,7]; + tap(15).No=[2,3,4,5,6,7]; + tap(16).No=[1,2,3,4,5,7]; + tap(17).No=[1,2,4,5,6,7]; + tap(18).No=[1,2,3,5,6,7]; +case 8, tap(1).No=[1,2,7,8]; + tap(2).No=[1,6,7,8]; + tap(3).No=[1,3,5,8]; + tap(4).No=[3,5,7,8]; + tap(5).No=[2,3,4,8]; + tap(6).No=[4,5,6,8]; + tap(7).No=[2,3,5,8]; + tap(8).No=[3,5,6,8]; + tap(9).No=[2,3,6,8]; + tap(10).No=[2,5,6,8]; + tap(11).No=[2,3,7,8]; + tap(12).No=[1,5,6,8]; + tap(13).No=[1,2,3,4,6,8]; + tap(14).No=[2,4,5,6,7,8]; + tap(15).No=[1,2,3,6,7,8]; + tap(16).No=[1,2,5,6,7,8]; +case 9, tap(1).No=[4,9]; + tap(2).No=[5,9]; + tap(3).No=[3,4,6,9]; + tap(4).No=[3,5,6,9]; + tap(5).No=[4,5,8,9]; + tap(6).No=[1,4,5,9]; + tap(7).No=[1,4,8,9]; + tap(8).No=[1,5,8,9]; + tap(9).No=[2,3,5,9]; + tap(10).No=[4,6,7,9]; + tap(11).No=[5,6,8,9]; + tap(12).No=[1,3,4,9]; + tap(13).No=[2,7,8,9]; + tap(14).No=[1,2,7,9]; + tap(15).No=[2,4,7,9]; + tap(16).No=[2,5,7,9]; + tap(17).No=[2,4,8,9]; + tap(18).No=[1,5,7,9]; + tap(19).No=[1,2,4,5,6,9]; + tap(20).No=[3,4,5,7,8,9]; + tap(21).No=[1,3,4,6,7,9]; + tap(22).No=[2,3,5,6,8,9]; + tap(23).No=[3,5,6,7,8,9]; + tap(24).No=[1,2,3,4,6,9]; + tap(25).No=[1,5,6,7,8,9]; + tap(26).No=[1,2,3,4,8,9]; + tap(27).No=[1,2,3,7,8,9]; + tap(28).No=[1,2,6,7,8,9]; + tap(29).No=[1,3,5,6,8,9]; + tap(30).No=[1,3,4,6,8,9]; + tap(31).No=[1,2,3,5,6,9]; + tap(32).No=[3,4,6,7,8,9]; + tap(33).No=[2,3,6,7,8,9]; + tap(34).No=[1,2,3,6,7,9]; + tap(35).No=[1,4,5,6,8,9]; + tap(36).No=[1,3,4,5,8,9]; + tap(37).No=[1,3,6,7,8,9]; + tap(38).No=[1,2,3,6,8,9]; + tap(39).No=[2,3,4,5,6,9]; + tap(40).No=[3,4,5,6,7,9]; + tap(41).No=[2,4,6,7,8,9]; + tap(42).No=[1,2,3,5,7,9]; + tap(43).No=[2,3,4,5,7,9]; + tap(44).No=[2,4,5,6,7,9]; + tap(45).No=[1,2,4,5,7,9]; + tap(46).No=[2,4,5,6,7,9]; + tap(47).No=[1,3,4,5,6,7,8,9]; + tap(48).No=[1,2,3,4,5,6,8,9]; +case 10, tap(1).No=[3,10]; + tap(2).No=[7,10]; + tap(3).No=[2,3,8,10]; + tap(4).No=[2,7,8,10]; + tap(5).No=[1,3,4,10]; + tap(6).No=[6,7,9,10]; + tap(7).No=[1,5,8,10]; + tap(8).No=[2,5,9,10]; + tap(9).No=[4,5,8,10]; + tap(10).No=[2,5,6,10]; + tap(11).No=[1,4,9,10]; + tap(12).No=[1,6,9,10]; + tap(13).No=[3,4,8,10]; + tap(14).No=[2,6,7,10]; + tap(15).No=[2,3,5,10]; + tap(16).No=[5,7,8,10]; + tap(17).No=[1,2,5,10]; + tap(18).No=[5,8,9,10]; + tap(19).No=[2,4,9,10]; + tap(20).No=[1,6,8,10]; + tap(21).No=[3,7,9,10]; + tap(22).No=[1,3,7,10]; + tap(23).No=[1,2,3,5,6,10]; + tap(24).No=[4,5,7,8,9,10]; + tap(25).No=[2,3,6,8,9,10]; + tap(26).No=[1,2,4,7,8,10]; + tap(27).No=[1,5,6,8,9,10]; + tap(28).No=[1,2,4,5,9,10]; + tap(29).No=[2,5,6,7,8,10]; + tap(30).No=[2,3,4,5,8,10]; + tap(31).No=[2,4,6,8,9,10]; + tap(32).No=[1,2,4,6,8,10]; + tap(33).No=[1,2,3,7,8,10]; + tap(34).No=[2,3,7,8,9,10]; + tap(35).No=[3,4,5,8,9,10]; + tap(36).No=[1,2,5,6,7,10]; + tap(37).No=[1,4,6,7,9,10]; + tap(38).No=[1,3,4,6,9,10]; + tap(39).No=[1,2,6,8,9,10]; + tap(40).No=[1,2,4,8,9,10]; + tap(41).No=[1,4,7,8,9,10]; + tap(42).No=[1,2,3,6,9,10]; + tap(43).No=[1,2,6,7,8,10]; + tap(44).No=[2,3,4,8,9,10]; + tap(45).No=[1,2,4,6,7,10]; + tap(46).No=[3,4,6,8,9,10]; + tap(47).No=[2,4,5,7,9,10]; + tap(48).No=[1,3,5,6,8,10]; + tap(49).No=[3,4,5,6,9,10]; + tap(50).No=[1,4,5,6,7,10]; + tap(51).No=[1,3,4,5,6,7,8,10]; + tap(52).No=[2,3,4,5,6,7,9,10]; + tap(53).No=[3,4,5,6,7,8,9,10]; + tap(54).No=[1,2,3,4,5,6,7,10]; + tap(55).No=[1,2,3,4,5,6,9,10]; + tap(56).No=[1,4,5,6,7,8,9,10]; + tap(57).No=[2,3,4,5,6,8,9,10]; + tap(58).No=[1,2,4,5,6,7,8,10]; + tap(59).No=[1,2,3,4,6,7,9,10]; + tap(60).No=[1,3,4,6,7,8,9,10]; +case 11, tap(1).No=[9,11]; +case 12, tap(1).No=[6,8,11,12]; +case 13, tap(1).No=[9,10,12,13]; +case 14, tap(1).No=[4,8,13,14]; +case 15, tap(1).No=[14,15]; +case 16, tap(1).No=[4,13,15,16]; +case 17, tap(1).No=[14,17]; +case 18, tap(1).No=[11,18]; +case 19, tap(1).No=[14,17,18,19]; +case 20, tap(1).No=[17,20]; +case 21, tap(1).No=[19,21]; +case 22, tap(1).No=[21,22]; +case 23, tap(1).No=[18,23]; +case 24, tap(1).No=[17,22,23,24]; +case 25, tap(1).No=[22,25]; +case 26, tap(1).No=[20,24,25,26]; +case 27, tap(1).No=[22,25,26,27]; +case 28, tap(1).No=[25,28]; +case 29, tap(1).No=[27,29]; +case 30, tap(1).No=[7,28,29,30]; +otherwise error(sprintf('M-sequence %.0f^%.0f is not defined',baseVal,powerVal)) +end; +elseif baseVal==3, +switch powerVal, +case 2, tap(1).No=[2,1]; + tap(2).No=[1,1]; +case 3, tap(1).No=[0,1,2]; + tap(2).No=[1,0,2]; + tap(3).No=[1,2,2]; + tap(4).No=[2,1,2]; +case 4, tap(1).No=[0,0,2,1]; + tap(2).No=[0,0,1,1]; + tap(3).No=[2,0,0,1]; + tap(4).No=[2,2,1,1]; + tap(5).No=[2,1,1,1]; + tap(6).No=[1,0,0,1]; + tap(7).No=[1,2,2,1]; + tap(8).No=[1,1,2,1]; +case 5, tap(1).No=[0,0,0,1,2]; + tap(2).No=[0,0,0,1,2]; + tap(3).No=[0,0,1,2,2]; + tap(4).No=[0,2,1,0,2]; + tap(5).No=[0,2,1,1,2]; + tap(6).No=[0,1,2,0,2]; + tap(7).No=[0,1,1,2,2]; + tap(8).No=[2,0,0,1,2]; + tap(9).No=[2,0,2,0,2]; + tap(10).No=[2,0,2,2,2]; + tap(11).No=[2,2,0,2,2]; + tap(12).No=[2,2,2,1,2]; + tap(13).No=[2,2,1,2,2]; + tap(14).No=[2,1,2,2,2]; + tap(15).No=[2,1,1,0,2]; + tap(16).No=[1,0,0,0,2]; + tap(17).No=[1,0,0,2,2]; + tap(18).No=[1,0,1,1,2]; + tap(19).No=[1,2,2,2,2]; + tap(20).No=[1,1,0,1,2]; + tap(21).No=[1,1,2,0,2]; +case 6, tap(1).No=[0,0,0,0,2,1]; + tap(2).No=[0,0,0,0,1,1]; + tap(3).No=[0,0,2,0,2,1]; + tap(4).No=[0,0,1,0,1,1]; + tap(5).No=[0,2,0,1,2,1]; + tap(6).No=[0,2,0,1,1,1]; + tap(7).No=[0,2,2,0,1,1]; + tap(8).No=[0,2,2,2,1,1]; + tap(9).No=[2,1,1,1,0,1]; + tap(10).No=[1,0,0,0,0,1]; + tap(11).No=[1,0,2,1,0,1]; + tap(12).No=[1,0,1,0,0,1]; + tap(13).No=[1,0,1,2,1,1]; + tap(14).No=[1,0,1,1,1,1]; + tap(15).No=[1,2,0,2,2,1]; + tap(16).No=[1,2,0,1,0,1]; + tap(17).No=[1,2,2,1,2,1]; + tap(18).No=[1,2,1,0,1,1]; + tap(19).No=[1,2,1,2,1,1]; + tap(20).No=[1,2,1,1,2,1]; + tap(21).No=[1,1,2,1,0,1]; + tap(22).No=[1,1,1,0,1,1]; + tap(23).No=[1,1,1,2,0,1]; + tap(24).No=[1,1,1,1,1,1]; +case 7, tap(1).No=[0,0,0,0,2,1,2]; + tap(2).No=[0,0,0,0,1,0,2]; + tap(3).No=[0,0,0,2,0,2,2]; + tap(4).No=[0,0,0,2,2,2,2]; + tap(5).No=[0,0,0,2,1,0,2]; + tap(6).No=[0,0,0,1,1,2,2]; + tap(7).No=[0,0,0,1,1,1,2]; + tap(8).No=[0,0,2,2,2,0,2]; + tap(9).No=[0,0,2,2,1,2,2]; + tap(10).No=[0,0,2,1,0,0,2]; + tap(11).No=[0,0,2,1,2,2,2]; + tap(12).No=[0,0,1,0,2,1,2]; + tap(13).No=[0,0,1,0,1,1,2]; + tap(14).No=[0,0,1,1,0,1,2]; + tap(15).No=[0,0,1,1,2,0,2]; + tap(16).No=[0,2,0,0,0,2,2]; + tap(17).No=[0,2,0,0,1,0,2]; + tap(18).No=[0,2,0,0,1,1,2]; + tap(19).No=[0,2,0,2,2,0,2]; + tap(20).No=[0,2,0,2,1,2,2]; + tap(21).No=[0,2,0,1,1,0,2]; + tap(22).No=[0,2,2,0,2,0,2]; + tap(23).No=[0,2,2,0,1,2,2]; + tap(24).No=[0,2,2,2,2,1,2]; + tap(25).No=[0,2,2,2,1,0,2]; + tap(26).No=[0,2,2,1,0,1,2]; + tap(27).No=[0,2,2,1,2,2,2]; +otherwise error(sprintf('M-sequence %.0f^%.0f is not defined',baseVal,powerVal)) +end; +elseif baseVal==5, +switch powerVal, +case 2, tap(1).No=[4,3]; + tap(2).No=[3,2]; + tap(3).No=[2,2]; + tap(4).No=[1,3]; +case 3, tap(1).No=[0,2,3]; + tap(2).No=[4,1,2]; + tap(3).No=[3,0,2]; + tap(4).No=[3,4,2]; + tap(5).No=[3,3,3]; + tap(6).No=[3,3,2]; + tap(7).No=[3,1,3]; + tap(8).No=[2,0,3]; + tap(9).No=[2,4,3]; + tap(10).No=[2,3,3]; + tap(11).No=[2,3,2]; + tap(12).No=[2,1,2]; + tap(13).No=[1,0,2]; + tap(14).No=[1,4,3]; + tap(15).No=[1,1,3]; +case 4, tap(1).No=[0,4,3,3]; + tap(2).No=[0,4,3,2]; + tap(3).No=[0,4,2,3]; + tap(4).No=[0,4,2,2]; + tap(5).No=[0,1,4,3]; + tap(6).No=[0,1,4,2]; + tap(7).No=[0,1,1,3]; + tap(8).No=[0,1,1,2]; + tap(9).No=[4,0,4,2]; + tap(10).No=[4,0,3,2]; + tap(11).No=[4,0,2,3]; + tap(12).No=[4,0,1,3]; + tap(13).No=[4,4,4,2]; + tap(14).No=[4,3,0,3]; + tap(15).No=[4,3,4,3]; + tap(16).No=[4,2,0,2]; + tap(17).No=[4,2,1,3]; + tap(18).No=[4,1,1,2]; + tap(19).No=[3,0,4,2]; + tap(20).No=[3,0,3,3]; + tap(21).No=[3,0,2,2]; + tap(22).No=[3,0,1,3]; + tap(23).No=[3,4,3,2]; + tap(24).No=[3,3,0,2]; + tap(25).No=[3,3,3,3]; + tap(26).No=[3,2,0,3]; + tap(27).No=[3,2,2,3]; + tap(28).No=[3,1,2,2]; + tap(29).No=[2,0,4,3]; + tap(30).No=[2,0,3,2]; + tap(31).No=[2,0,2,3]; + tap(32).No=[2,0,1,2]; + tap(33).No=[2,4,2,2]; + tap(34).No=[2,3,0,2]; + tap(35).No=[2,3,2,3]; + tap(36).No=[2,2,0,3]; + tap(37).No=[2,2,3,3]; + tap(38).No=[2,1,3,2]; + tap(39).No=[1,0,4,3]; + tap(40).No=[1,0,3,3]; + tap(41).No=[1,0,2,2]; + tap(42).No=[1,0,1,2]; + tap(43).No=[1,4,1,2]; + tap(44).No=[1,3,0,3]; + tap(45).No=[1,3,1,3]; + tap(46).No=[1,2,0,2]; + tap(47).No=[1,2,4,3]; + tap(48).No=[1,1,4,2]; +otherwise error(sprintf('M-sequence %.0f^%.0f is not defined',baseVal,powerVal)) +end; +end; + +ms=zeros(bitNum,1); +if isempty(whichSeq), whichSeq=ceil(rand(1)*length(tap)); +else, + if whichSeq>length(tap) | whichSeq<1 + disp(sprintf(' wrapping arround!')); + whichSeq=rem(whichSeq,length(tap))+1; + end; +end; + +weights=zeros(1,powerVal); +if baseVal==2, + weights(tap(whichSeq).No)=1; +elseif baseVal>2, + weights=tap(whichSeq).No; +end; + +%weights + +for i=1:bitNum + % calculating next digit with modulo powerVal arithmetic + % register, (tap(1).No) + + %ms(i)=rem(sum(register(tap(whichSeq).No)),baseVal); + ms(i)=rem(weights*register+baseVal,baseVal); + % updating the register + + register=[ms(i);register(1:powerVal-1)]; +end + +ms=ms(:); +if ~isempty(shift), + shift=rem(shift, length(ms)); + ms=[ms(shift+1:end); ms(1:shift)]; +end; + +if baseVal==2, + ms=ms*2-1; +elseif baseVal==3, + ms(ms==2)=-1; +elseif baseVal==5, + ms(ms==4)=-1; + ms(ms==3)=-2; +else + error('wrong baseVal!'); +end; + + diff --git a/myColors.m b/myColors.m new file mode 100644 index 0000000..87918d6 --- /dev/null +++ b/myColors.m @@ -0,0 +1,4 @@ +function [Couleur] = myColors() +% myColors() renvoie un Cell permettant d'automatiser les couleurs des plots pour chaque condition +% e.g. couleur=myColors; plot(x,y, couleur{1}) pour la condition i (où i=1:5) +Couleur={ {'Color', [0 0 0]} , {'Color', [1 0 0]} , {'Color', [0 0 1]} , {'Color', [0 1 0]} , {'Color', [1 0 1]} } diff --git a/mycaxis.m b/mycaxis.m new file mode 100644 index 0000000..8cdfa78 --- /dev/null +++ b/mycaxis.m @@ -0,0 +1,26 @@ +function [] = mycaxis(lims) +%MYCAXIS - One line description goes here. +% [] = mycaxis(lims) +% Works ALSO when there are contours in the plot +% Example +% >> mycaxis +% +% See also: caxis + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-27 Creation +% +% ----------------------------- Script History --------------------------------- + +caxis(lims) +ch=get(gca, 'Children'); +if ~isempty(findobj(ch, 'type', 'hggroup')) + dsip('contours') +end \ No newline at end of file diff --git a/mycolormap.m b/mycolormap.m new file mode 100644 index 0000000..304ce7a --- /dev/null +++ b/mycolormap.m @@ -0,0 +1,21 @@ +function [m]=mycolormap(seuil,varargin) +% mycolormap - custom the jet colormap to display X% of the data +% [m]=mycolormap(X) +% [m]=mycolormap(X,CM) CM is a colormap + +if nargin==1 + + m=ones(100-seuil,3)*[.2 .7 1;0 0 0;0 0 0]; + m= [m ; ones(2*seuil,3)*.5]; + m= [m ; ones(100-seuil,3)*[1 .4 .2;0 0 0;0 0 0]]; + + l=.3; + m=hot(110); + m= [m(1:100,:)*(1-l)+ones(100,3)*l]; + m= [fliplr(flipud(m)) ; ones(2*seuil,3)*l ; m]; + +else + n=varargin{1}; + m=[ n(1:ceil(length(n)/2),:); ones(2*seuil/100*length(n),3)*.5 ; n(ceil(length(n)/2):end,:)]; + +end diff --git a/mymatlabpath.m b/mymatlabpath.m new file mode 100644 index 0000000..749509d --- /dev/null +++ b/mymatlabpath.m @@ -0,0 +1,3 @@ +function [MYMATLABDIR]=MYMATLABPATH() +% MYMATLABPATH - Retrieves the matlab working directory +MYMATLABDIR = fileparts(mfilename('fullpath')); diff --git a/mypath.m b/mypath.m new file mode 100644 index 0000000..80bd3c6 --- /dev/null +++ b/mypath.m @@ -0,0 +1,118 @@ +function [HOMEDIR]=mypath() +% MYPATH - Retrieves home directory on the current OS +HOMEDIR=''; +lcd=cd; +if ispc + [s,m]=system('echo %USERPROFILE%\My Documents & cd "%USERPROFILE%\My Documents"'); + if s + [s,m]=system('echo %USERPROFILE%\Mes Documents & cd "%USERPROFILE%\Mes Documents"'); + end + if s + [s,m]=system([ ... + 'echo "%TEMP%" & regedit /E "%TEMP%\homepath.txt" ' ... + '"HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Explorer\Shell Folders\" & '... + 'type "%TEMP%\homepath.txt"|find "Personal"']); + if ~s + m=m(findstr(lower(deblank(m)), '"personal"="') + 12:end-2); + warning('MYPATH:HomepathFromRegistry','No "My Documents" in the user folder. Use Registry table value.'); + end + else + m=deblank(m); + end + if ~s + lcd=cd; + cd(m); + m=cd; + end +elseif isunix + % [s,m]=system('cd ~'); + % [p,n]=fileparts(cd); + % if isequal('matlab', lower(n)) + % cd(p); + % end + try + s=0; + cd('~'); + m=cd; + catch + s=1; + end +end +cd(lcd); +if s + error('Unable to find your home folder on this OS:\n%s',m); +else + HOMEDIR=m; +end + +return + + +% Set PATH variables: HOMEDIR & USBDIR +% [HOMEDIR,USBDIR]=mypath() + +HOMEDIR=''; +LACIE=''; +WENDY=''; +MAMMAMIA=''; +USBDIR=NaN; + +if nargin>0 + if isunix + testloc={'/mnt'} + elseif ispc + testloc=[ { 'F:' 'G:' 'H:'} cellstr([char(65:90)' repmat(':', 26,1)])' ]; + end + switch upper(NAME) + case 'WENDY' + testname='wendy.txt'; + case 'LACIE' + testname='lacie.txt'; + end + for i=1:length(testloc) + if exist(fullfile(testloc{i}, testname), 'file') + HOMEDIR=testloc{i}; + return + end + end + return +end + +if isunix + if exist('/home/ndiayek') + HOMEDIR='/home/ndiayek'; + elseif exist('/pclxserver2/home/ndiaye') + HOMEDIR='/pclxserver2/home/ndiaye'; + end + +elseif ispc + if exist('f:\matlab') && (exist('g:\lacie.txt') || exist('g:\wendy.txt')) + % USB key is F: + USBDIR='f:\'; + elseif exist('g:\matlab') && (exist('g:\lacie.txt') || exist('g:\wendy.txt') || exist('g:\mammamia.txt')) + % USB key is G: + USBDIR='g:\'; + elseif exist('h:\matlab') && (exist('h:\lacie.txt') || exist('h:\wendy.txt')) + % USB key is H: + USBDIR='h:\'; + % elseif exist('d:\matlab') && (exist('g:\lacie.txt') || exist('g:\wendy.txt')) + % % USB key is D: + % USBDIR='d:\'; + end + + % if D: is a CD drive, hangs the execution !!! + % if exist('d:\ndiaye\') + % HOMEDIR='d:\ndiaye\'; + % elseif exist('d:\ndiayek\') + % HOMEDIR='d:\ndiayek\'; + % elseif exist('e:\ndiaye\') + % HOMEDIR='e:\ndiaye\'; + % elseif exist('g:\ndiayek\') + % HOMEDIR='g:\ndiayek\'; + % end +end + +if nargout==0 + assignin('caller', 'HOMEDIR', HOMEDIR) + assignin('caller', 'USBDIR', USBDIR) +end diff --git a/mypsychtoolbox/ConfidenceDisc.m b/mypsychtoolbox/ConfidenceDisc.m new file mode 100644 index 0000000..64472f8 --- /dev/null +++ b/mypsychtoolbox/ConfidenceDisc.m @@ -0,0 +1,273 @@ +function [c,rt,events,onset_time]=ConfidenceDisc(frame,nlevels,timelimit,keylist,markers,FOV) +% ConfidenceScale - disc for confidence rating +% [c,rt]=ConfidenceDisc(frame,nlevels,timelimit) +% +% markers.onset +% markers.keys +c=NaN; +rt=NaN; +events=[]; +if nargin<1 + DEBUG=1; +else + DEBUG=0; +end +if ~exist('keylist','var') + keylist={}; +end +sendMarkers = 0; +if nargin>4 + sendMarkers = 1; +end + +%% Behaviour & visual aspect of the disc +% +% Shape parameters +% They are all relative top the field of view (fov) which is itself based +% on the frame/window size : +disc.diameter = .25; % height of the disc +disc.contour=1/60; % pen width (relatively to frame size) + +% NaN = starts at a random position; +disc.startlevel = NaN; + +% Number of consecutive key press to go to fast mode +nkey = 10; +repetitiontime = 0.05; % minimum time between consecutive keypresses +keytimebreak = 0.3; + +% To validate, SS press +% Esc = 27 or SPACE = 32 or RETURN = 13 +if isempty(keylist) + keylist = { + [ KbName('LeftArrow') KbName('LeftAlt') KbName('LeftControl') 74 257] + [ KbName('RightArrow') KbName('RightAlt') KbName('RightControl') 75 258] + [ KbName('Return') KbName('Space') 259 ] + [ KbName('Escape') ] }; +end + +listenParPort = 0; +if any([keylist{:}]>256) + if exist('ReadParPort')==2 + listenParPort = 1; + else + error('Listening to Parallel port requires readParPort() function'); + end +end + +if listenParPort || sendMarkers + OpenParPort(1); +end + +keys.less = keylist{1}; +keys.more = keylist{2}; +keys.ok = keylist{3}; +keys.quit = keylist{4}; +keys.resp = [ keys.less keys.more keys.ok keys.quit]; + +%% Processing of inputs +if nargin<1 + frame =[]; +end +WindowWasOpen = 0; +if isempty(frame) + clc + Screen('Preference', 'SkipSyncTests', 1); + frame = OpenDisplay([800,600], [140 140 140]); + WindowWasOpen = 1; +end +w = frame.ptr; + +black = BlackIndex(w); +white = WhiteIndex(w); +red = [white(1) black(1) black(1)]/3; +blue = [black(1) black(1) white(1)]./3; +grey = white/3; +if isfield(frame, 'color') + disc.bgcolor = frame.color; +else + disc.bgcolor = black; +end +disc.fgcolor = 2*grey; +disc.bordercolor = grey; +disc.textcolor = white*.75; + +% "Field of View" +if nargin<6 + fov = min(frame.size); +else + fov = FOV; +end + +if nargin<2 + nlevels=[]; % = 8 including zero! +end +if isempty(nlevels) + nlevels=7; % = 8 including zero! +end +if isnan(disc.startlevel) + c=1+floor(rand*(nlevels-1)); +elseif disc.startlevel<1 + c=round(disc.startlevel*nlevels); +else + c=disc.startlevel; +end +small_inc=1; +big_inc = max(small_inc,nlevels/25); + +if nargin<3 + timelimit = Inf; +end +if nargin<4 + labels={'Totalement incertain' 'Sûr et certain' }; +end + + +%% Drawing of the disc +rect = fov*disc.diameter*[1 1]; +pos = RectAlign(rect,frame.size, 'c'); +penwidth = fov*disc.contour*disc.diameter; +Screen('FrameArc', w, disc.bordercolor, pos, 0, 360, penwidth) + +% Remainder +pos2 = pos + penwidth*[1 1 -1 -1]/2; +Screen('FillArc', w, disc.bgcolor, pos2, 360*(1-(nlevels-c)/nlevels), 360); +% Lines +pos3 = [ (pos(3)-pos(1))/2 , (pos(3)-pos(1))/2 ]; +radius = pos3-penwidth/2; +pos3 = pos3 + pos(1:2); +angle = c/nlevels*2*pi; +Screen('DrawLine', w, disc.bordercolor, pos3(1),pos3(2),pos3(1),pos3(2)-radius(2), penwidth); +Screen('DrawLine', w, disc.bordercolor, pos3(1),pos3(2), ... + pos3(1)+radius(1)*(sin(c/nlevels*2*pi)), ... + pos3(2)-radius(2)*(cos(c/nlevels*2*pi)), ... + penwidth); + +% Filling +Screen('FillArc', w, disc.fgcolor, pos2, 0, 360*(c)/nlevels); +%% User interaction +try + ListenChar(2); +end; + +% Flip screen to show initial position +if exist('c:/documents and Settings/knierim/') + onset_time=Screen('Flip', w, 0); +else + onset_time=Screen('Flip', w, 0,1); +end +if sendMarkers + WriteParPort(markers.onset); +end + +% onset_time will be used to re-compute the response time according to the onset +% time of the display +secs(1:2) = onset_time; +rt=NaN; +btnPress = 0; + +% Log info regarding state of the confidence disc at onset +events(1).c=c; +events(1).dir=nan; +events(1).k=[]; +events(1).press_time=secs(1); +fprintf('c = %d ',c); + +while true + % Is response time over? + if (secs(2)-onset_time) > timelimit + fprintf(' >< time over.\n'); + c=NaN; + break + end + % Reads buttons from parallel port + if listenParPort + [btnPress] = ReadParPort(0); + end + [keyIsDown, secs(2), keyCode] = KbCheck; + keyCode=logical([keyCode bitget(btnPress,1:3)]); + if any(keyCode(keys.resp)); + inc=0; + dir=0; + % Subject pressed Escape (or the like) + if any(keyCode(keys.quit)) + rt=NaN; + c=NaN; + break + elseif any(keyCode(keys.ok)) + % Subject has validated his/her response + if sendMarkers + WriteParPort([c,markers.keys(keyCode),markers.onset]); + WaitSecs(0.0078); + end + % log events + events(end+1).c=c; + events(end).press_time=secs(2); + events(end).dir=nan; + events(end).k=find(keyCode); + fprintf(' = %d ; RT=%0.3fs\n',c,secs(2)-onset_time) + break + elseif any(keyCode(keys.more)) + dir=+1; + elseif any(keyCode(keys.less)) + dir=-1; + end + if (secs(2)-secs(1)) > repetitiontime + if sendMarkers + WriteParPort(markers.keys(keyCode)); + WaitSecs(0.0078); + WriteParPort(markers.onset); + end + % Separated clicks + inc=small_inc; + % Update confidence value + c=c+dir*inc; + c=max(c,0); + c=min(c,nlevels); + % log events + events(end+1).c=c; + events(end).press_time=secs(2); + events(end).dir=dir; + events(end).k=find(keyCode); + % fprintf('RT=%0.3fs [key=%s] %d -> c=%d\n',secs(2)-rt,... + % sprintf('%d ',events(end).k),events(end).dir,c) + if dir>0 + fprintf('%s', '+'); + elseif dir<0 + fprintf('%s', '-'); + end + %fprintf('%d', c); + %d'> c=%d\n',secs(2)-onset_time,... + % sprintf('%d ',events(end).k),events(end).dir,c) + end + secs(1)=secs(2); + + % Update the display + % secs(1:nkey-1) = secs(2:nkey); + Screen('FillArc', w, disc.bgcolor, pos2, 360*(1-(nlevels-c)/nlevels), 360); + Screen('DrawLine', w, disc.bordercolor, pos3(1),pos3(2),pos3(1),pos3(2)-radius(2), penwidth); + Screen('DrawLine', w, disc.bordercolor, pos3(1),pos3(2), ... + pos3(1)+radius(1)*(sin(c/nlevels*2*pi)), ... + pos3(2)-radius(2)*(cos(c/nlevels*2*pi)), ... + penwidth); + Screen('FillArc', w, disc.fgcolor, pos2, 0, 360*(c)/nlevels); + if exist('c:/documents and Settings/knierim/') + secs(2)=Screen('Flip', w, 0); + else + secs(2)=Screen('Flip', w, 0,1); + end + + end +end + +try + ListenChar(0); +end; +if WindowWasOpen + Screen('Close', w); + if doSendMarkers + WriteParPort(0); + end +end +rt=secs(end)-onset_time; + diff --git a/mypsychtoolbox/ConfidenceScale2_mod.m b/mypsychtoolbox/ConfidenceScale2_mod.m new file mode 100644 index 0000000..3e73de9 --- /dev/null +++ b/mypsychtoolbox/ConfidenceScale2_mod.m @@ -0,0 +1,181 @@ +function [c,rt,pos]=ConfidenceScale2_mod(frame,nlevels,labels) +% ConfidenceScale - Scale for confidence rating +if nargin<1 + DEBUG=1; +else + DEBUG=0; +end + +%% Behaviour & visual aspect of the scale +% +% Shape parameters +% They are all relative top the field of view (fov) which is itself based +% on the frame/window size : +scale.orientation = 90; % vertical = 0 ; horizontal = 90 +scale.excentricity = .5; % position of the scale on screen +scale.length = .3; % length of the scale +scale.shape = .25; % width-to-length ratio +scale.contour=1/60; % pen width (relatively to frame size) +scale.ticks = 1; % display ticks on the scale + +% NaN = starts at a random position; 0.5 = starts at the middle position; +scale.startlevel = 0.75; + +% Number of consecutive key press to go to fast mode +nkey = 10; +sluggish = 0.1; % minimum time between consecutive keypresses +keytimebreak = 0.3; +% To validate, SS press +% Esc = 27 or SPACE = 32 or RETURN = 13 +OkKey = [32 13]; +EscKey = 27; + +%% Processing of inputs +if nargin<1 + frame =[]; +end +WindowWasOpen = 0; +if isempty(frame) + clc + Screen('Preference', 'SkipSyncTests', 1); + frame = OpenDisplay([800,600], [0]); + frame.window = frame; + WindowWasOpen = 1; +end +if ~isfield(frame, 'rect') + frame.rect= Screen('Rect', frame.ptr); + frame.size = frame.rect(3:4); +end +w = frame.ptr; + +black = BlackIndex(w); +white = WhiteIndex(w); +red = [white(1) black(1) black(1)]/3; +blue = [black(1) black(1) white(1)]./[3 3 1]; +grey = white/3; + +scale.bgcolor = black; +scale.fgcolor = blue; +scale.bordercolor = grey; +scale.textcolor = white*.75; + +% "Field of View" +fov = min(frame.size); + +if nargin<2 + nlevels=20; +end +if isnan(scale.startlevel) + c=floor(rand*(nlevels+1)); +elseif scale.startlevel<1 + c=round(scale.startlevel*nlevels); +else + c=scale.startlevel; +end +small_inc=1; +big_inc = max(small_inc,nlevels/25); + +if nargin<3 + labels={' ' ' ' }; +% labels={'Totalement incertain','Sur de son choix'}; +end + +%% Drawing of the scale +scale.orientation + +rect = fov*scale.length*[scale.shape 1]; +pos = RectAlign(rect,frame.size, 'c'); +% Bottom label +DrawText(w,labels{1}, [mean(pos([1 3])) ... + frame.size(2)*(1-(1-scale.length)/4)], scale.textcolor); +DrawText(w,labels{2}, [mean(pos([1 3])) ... + frame.size(2)*((1-scale.length)/4)], scale.textcolor) + +penwidth = fov*scale.contour; +Screen('FrameRect',w,scale.bordercolor,pos, penwidth); + +% Upper Black rectangle +pos2 = pos + penwidth/2*[1 1 -1 -1]; +pos2 = pos2([1 2 3 2]) + [0 0 0 +1]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); +Screen('FillRect',w,scale.bgcolor,pos2); + +% Lower Filling Rectangle +pos2 = pos + penwidth/2*[1 1 -1 -1]; +pos2 = pos2([1 2 3 4]) + [0 +1 0 0]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); +Screen('FillRect',w,scale.fgcolor,pos2); + +Screen('Flip', w, 0, 0); + + + +%% User interaction + +ListenChar(2); +[keyIsDown,rt]=KbCheck; +secs(1:nkey) = rt; +prevc=c; +while true + [secs(nkey), keyCode] = KbWait; + if any(keyCode(EscKey)) + rt=NaN; + c=NaN; + break + end + if any(keyCode(OkKey)) + break + end + inc=0; + + if (secs(nkey)-secs(nkey-1)) > sluggish + % slow mode + secs(1:nkey)=secs(nkey); + inc=small_inc; + elseif all(diff(secs)>0) + if all(diff(secs) < sluggish) + % fast mode + inc=big_inc; + else + % wait that nkey have been sampled + inc=0; + end + end + % change cursor only once we are in slow or fast mode + if keyCode(38) + c=min(c+inc,nlevels); + elseif keyCode(40) + c=max(c-inc,0); + end + secs(1:nkey-1) = secs(2:nkey); + + %border + penwidth = fov*scale.contour; + Screen('FrameRect',w,scale.bordercolor,pos, penwidth); + + % Upper Black rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 2]) + [0 0 0 +1]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.bgcolor,pos2); + + % Lower Filling Rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 4]) + [0 +1 0 0]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.fgcolor,pos2); + + + DrawText(w,sprintf('%2.0f%', 100*prevc/nlevels), [mean(pos([1 3])) ... + frame.size(2)*((1.5-scale.length)/4)], scale.bgcolor); + DrawText(w,sprintf('%2.0f%', 100*c/nlevels), [mean(pos([1 3])) ... + frame.size(2)*((1.5-scale.length)/4)], 200); + prevc=c; + Screen('Flip', w, 0, 0); + + +end +try +ListenChar(0); +end; +if WindowWasOpen + Screen('Close', w); +end +rt=secs(nkey)-rt; + diff --git a/mypsychtoolbox/ConfidenceScale3.m b/mypsychtoolbox/ConfidenceScale3.m new file mode 100644 index 0000000..7e87264 --- /dev/null +++ b/mypsychtoolbox/ConfidenceScale3.m @@ -0,0 +1,237 @@ +function [c,rt,pos]=ConfidenceScale(frame,nlevels,labels) %#ok +% ConfidenceScale - Scale for confidence rating +% [] = ConfidenceScale(input) +% +% Example +% >> ConfidenceScale +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-?? Creation +% KND 2009-03-?? Now allows horiz orientation +% +% ----------------------------- Script History --------------------------------- + + +if nargin<1 + DEBUG=1; +else + DEBUG=0; +end + +%% Behaviour & visual aspect of the scale +% +% Shape parameters +% They are all relative top the field of view (fov) which is itself based +% on the frame/window size : +scale.orientation = 00; % vertical = 0 ; horizontal = 90 +scale.excentricity = .5; % position of the scale on screen +scale.length = .3; % length of the scale +scale.shape = .25; % width-to-length ratio +scale.contour=1/60; % pen width (relatively to frame size) +scale.ticks = 1; % display ticks on the scale + +% NaN = starts at a random position; 0.5 = starts at the middle position; +scale.startlevel = 0.75; + +% Number of consecutive key press to go to fast mode +nkey = 10; +sluggish = 0.1; % minimum time between consecutive keypresses +keytimebreak = 0.3; +% To validate, SS press +% Esc = 27 or SPACE = 32 or RETURN = 13 +OkKey = [32 13]; +EscKey = 27; + +%% Processing of inputs +if nargin<1 + frame =[]; +end +WindowWasOpen = 0; +if isempty(frame) + clc + Screen('Preference', 'SkipSyncTests', 1); + frame = OpenDisplay([800,600], [0]); + frame.window = frame; + WindowWasOpen = 1; +end +if ~isfield(frame, 'rect') + frame.rect= Screen('Rect', frame.ptr); + frame.size = frame.rect(3:4); +end +w = frame.ptr; + +black = BlackIndex(w); +white = WhiteIndex(w); +red = [white(1) black(1) black(1)]/3; +blue = [black(1) black(1) white(1)]./[3 3 1]; +grey = white/3; + +scale.bgcolor = black; +scale.fgcolor = blue; +scale.bordercolor = grey; +scale.textcolor = white*.75; + +% "Field of View" +fov = min(frame.size); + +if nargin<2 + nlevels=20; +end +if isnan(scale.startlevel) + c=floor(rand*(nlevels+1)); +elseif scale.startlevel<1 + c=round(scale.startlevel*nlevels); +else + c=scale.startlevel; +end +small_inc=1; +big_inc = max(small_inc,nlevels/25); + +if nargin<3 + labels={' ' ' ' }; +% labels={'Totalement incertain','Sur de son choix'}; +end + +%% Drawing of the scale +if scale.orientation ~= 90 && scale.orientation ~= 0 + error('Can''t deal with this orientation'); +end +if scale.orientation == 90 + rect = fov*scale.length*[1 scale.shape]; + pos = RectAlign(rect,frame.size, 'c'); + % Left label + DrawText(w,labels{1}, [... + mean(pos([1 3])) ... + frame.size(2)*(1-(1-scale.length)/4) ... + ], scale.textcolor); + DrawText(w,labels{2}, [mean(pos([1 3])) ... + frame.size(2)*((1-scale.length)/4)], scale.textcolor) +else + rect = fov*scale.length*[scale.shape 1]; + pos = RectAlign(rect,frame.size, 'c'); + % Bottom label + DrawText(w,labels{1}, [mean(pos([1 3])) ... + frame.size(2)*(1-(1-scale.length)/4)], scale.textcolor); + DrawText(w,labels{2}, [mean(pos([1 3])) ... + frame.size(2)*((1-scale.length)/4)], scale.textcolor) +end + +penwidth = fov*scale.contour; +Screen('FrameRect',w,scale.bordercolor,pos, penwidth); + +if scale.orientation == 90 + % Right Black rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 4]) + [+1 0 0 0]*(c)/(nlevels)*(pos2(3)-pos2(1)); + Screen('FillRect',w,scale.bgcolor,pos2); + % Left Filling Rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 1 4]) + [0 0 +1 0]*(c)/(nlevels)*(pos2(3)-pos2(1)); + Screen('FillRect',w,scale.fgcolor,pos2); +else + % Upper Black rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 2]) + [0 0 0 +1]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.bgcolor,pos2); + % Lower Filling Rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 4]) + [0 +1 0 0]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.fgcolor,pos2); +end + +Screen('Flip', w, 0, 0); + + + +%% User interaction + +ListenChar(2); +[keyIsDown,rt]=KbCheck; +secs(1:nkey) = rt; +prevc=c; +while true + [secs(nkey), keyCode] = KbWait; + if any(keyCode(EscKey)) + rt=NaN; + c=NaN; + break + end + if any(keyCode(OkKey)) + break + end + inc=0; + + if (secs(nkey)-secs(nkey-1)) > sluggish + % slow mode + secs(1:nkey)=secs(nkey); + inc=small_inc; + elseif all(diff(secs)>0) + if all(diff(secs) < sluggish) + % fast mode + inc=big_inc; + else + % wait that nkey have been sampled + inc=0; + end + end + % change cursor only once we are in slow or fast mode + if keyCode(38) || keyCode(39) + c=min(c+inc,nlevels); + elseif keyCode(40) || keyCode(37) + c=max(c-inc,0); + end + secs(1:nkey-1) = secs(2:nkey); + + %border + penwidth = fov*scale.contour; + Screen('FrameRect',w,scale.bordercolor,pos, penwidth); + + if scale.orientation == 90 + % Right Black rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 4]) + [+1 0 0 0]*(c)/(nlevels)*(pos2(3)-pos2(1)); + Screen('FillRect',w,scale.bgcolor,pos2); + + % Left Filling Rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 1 4]) + [0 0 +1 0]*(c)/(nlevels)*(pos2(3)-pos2(1)); + Screen('FillRect',w,scale.fgcolor,pos2); + + else + % Upper Black rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 2]) + [0 0 0 +1]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.bgcolor,pos2); + + % Lower Filling Rectangle + pos2 = pos + penwidth/2*[1 1 -1 -1]; + pos2 = pos2([1 2 3 4]) + [0 +1 0 0]*(nlevels-c)/(nlevels)*(pos2(4)-pos2(2)); + Screen('FillRect',w,scale.fgcolor,pos2); + end + + DrawText(w,sprintf('%2.0f%', 100*prevc/nlevels), [mean(pos([1 3])) ... + frame.size(2)*((1.5-scale.length)/4)], scale.bgcolor); + DrawText(w,sprintf('%2.0f%', 100*c/nlevels), [mean(pos([1 3])) ... + frame.size(2)*((1.5-scale.length)/4)], 200); + prevc=c; + Screen('Flip', w, 0, 0); + + +end +try + ListenChar(0); +end; +if WindowWasOpen + Screen('Close', w); +end +rt=secs(nkey)-rt; + diff --git a/mypsychtoolbox/DrawText.m b/mypsychtoolbox/DrawText.m new file mode 100644 index 0000000..3643a3c --- /dev/null +++ b/mypsychtoolbox/DrawText.m @@ -0,0 +1,189 @@ +function [varargout] = DrawText(wPtr,txt,alignment,fgcol,bgcol) +%DRAWTEXT - One line description goes here. +% [newXY] = DrawText(wPtr, text [,alignment ,fgColor ,bgColor]) +% Easy way to control position of the text on screen +% +% alignment may be any of: 'l' (left), 'c' (horizontally centered), +% 'r' (right), 't' (top), 'm' (vertically middle), 'b' (bottom) +% Any single letter can be used multiple times to: 'llc' position +% the text quite on the left (66% of the half-width), whereas 'rccc' +% puts it almost in the center (25% of the half-width off to the +% right). +% Alignment can also be specified as 2*1 or 4*1 numerical vector +% +% Example +% >> DrawText(w,'bla bla', 'ct') positions the text 'bla bla' at the +% (c)entered at the (t)op +% +% >> DrawText(w,'bla bla', 'ct') positions the text 'bla bla' at the +% (c)entered at the (t)op +% +% Based on: Screen('Drawtext?') +% See also: DrawFormattedtext + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-02-02 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin < 1 + error('DrawText: window handle missing!'); +end + +if nargin < 2 || isempty(txt) + % Empty text string -> Nothing to do. + return; +end +if isempty(wPtr) + clc + frame = OpenDisplay; + wPtr=frame.ptr; +end +if nargin<3 + alignment=''; +end +if nargin<4 + fgcol=[255]; +end +if nargin<5 + bgcol=[]; +end + +% [x,x,x]=intersect(alignment,'lcr'); +% if length(x)>1 +% error('Wrong horizontal alignment!'); +% end +% [y,y,y]=intersect(alignment,'tmb'); +% if length(y)>1 +% error('Wrong vertical alignment!'); +% end + +if ischar(txt) + txt={txt}; +end +wh =[]; +for i=1:numel(txt) + if isempty(txt{i}) + wh = [wh; Screen('TextBounds', wPtr, ' ')]; + wh(end,3)=0; + else + wh = [wh; Screen('TextBounds', wPtr, txt{i})]; + end +end +wh=wh(:,3:4)-wh(:,1:2); +%wh(:,1) = max(wh(:,1)); +%wh(:,2)= cumsum(wh(:,2)); + +xy=zeros(size(wh,1),2); +if isnumeric(alignment) + if numel(alignment) == 2 + x0=alignment(1); + y0=alignment(2); + x=0.*x0; + y=0.*y0; + x(x0==-1)=+1; + x(x0==+1)=-1; + y(y0==-1)=+1; + y(y0==+1)=-1; + + elseif numel(alignment) == 4 + x0=alignment(1); + y0=alignment(2); + x=alignment(3); + y=alignment(4); + else + error('Wrong numeric alignment') + end +else + x0=0; + y0=0; + alignment=lower(alignment); + if isequal(alignment, 'center') + alignment='c'; + end + if isequal(alignment, 'right') + alignment='r'; + x=-1; + end + if isequal(alignment, 'left') + alignment='l'; + x=+1; + end + if isequal(alignment, 'top') + alignment='t'; + y=+1; + end + if isequal(alignment, 'middle') + alignment='m'; + end + if isequal(alignment, 'bottom') + alignment='b'; + y=-1; + end + + [z,z]=ismember(alignment,'lcrtmb'); + if any(z==0) + error('Wrong alignment parameter!'); + end + if any(z<=3) + x0=mean(z(z<=3),2)-2; + else + x0=NaN; + end + x0(isnan(x0))=0; + if any(z>=4) + y0=mean(z(z>=4),2)-5; + else + y0=NaN; + end + y0(isnan(y0))=0; + x=0.*x0; + y=0.*y0; + x(x0==-1)=+1; + x(x0==+1)=-1; + y(y0==-1)=+1; + y(y0==+1)=-1; +end + +%scr = Screen('Resolution',wPtr); +r = [Screen('Rect', wPtr)]; +scr.width = r(3)-r(1); +scr.height = r(4)-r(2); + +if abs(x0)<=1 + x0=(1+x0)*scr.width/2; +end +if abs(y0)<=1 + y0=(1+y0)*scr.height/2; +end + +if x>1 + xy(:,1) = x0 + x; +else + xy(:,1) = x0 + (x-1).*wh(:,1)/2; +end +if y>1 + xy(:,2) = y0 + y; +else + xy(:,2) = y0 + (y-1).*sum(wh(:,2))/2+cumsum([0;wh(1:end-1,2)]); +end +for i=1:numel(txt) + if isempty(txt{i}) + xy2(i,1)=xy(i,1); + xy2(i,2)=xy(i,2); + else + [xy2(i,1) xy2(i,2)]=Screen('DrawText',wPtr,txt{i},xy(i,1),xy(i,2),fgcol,bgcol); + end +end +varargout={}; +if nargout>0 + varargout={xy2,xy,wh}; +end +return diff --git a/mypsychtoolbox/FlipWindow.m b/mypsychtoolbox/FlipWindow.m new file mode 100644 index 0000000..6125f94 --- /dev/null +++ b/mypsychtoolbox/FlipWindow.m @@ -0,0 +1,47 @@ +function [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = FlipWindow(windowPtr,when,dontclear,dontsync,multiflip) +%FLIPWINDOW - Oneliner for Screen('Flip',...) +% [VBLT, OnsetTime, FlipT, Missed Beampos] = +% FlipWindow flips the last window +% FlipWindow(windowPtr) +% +% Example +% >> FlipWindow +% +% See also: Screen('Flip?') + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-02-15 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + windowPtr=[]; +end +if isempty(windowPtr) + windowPtr = Screen('Windows'); + windowPtr = windowPtr(end); +end +if isempty(windowPtr) + warning('FlipWindow:NoWindow', 'No window found'); + return +end +% when,dontclear,dontsync,multiflip) +switch nargin + case {0 1} + [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip',windowPtr); + case 2 + [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip',windowPtr,when); + case 3 + [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip',windowPtr,when,dontclear); + case 4 + [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip',windowPtr,when,dontclear,dontsync); + case 5 + [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip',windowPtr,when,dontclear,dontsync,multiflip); +end \ No newline at end of file diff --git a/mypsychtoolbox/KbNameCell.m b/mypsychtoolbox/KbNameCell.m new file mode 100644 index 0000000..10381b7 --- /dev/null +++ b/mypsychtoolbox/KbNameCell.m @@ -0,0 +1,7 @@ +function [kbNameResult] = KbName(arg); +% KbNameCell - Forec KbName output into cell (for strings) +kbNameResult = KbName(arg); +if isnumeric(arg) && ~iscell(kbNameResult) + kbNameResult = {kbNameResult}; +end + diff --git a/mypsychtoolbox/OpenDisplay.m b/mypsychtoolbox/OpenDisplay.m new file mode 100644 index 0000000..5935196 --- /dev/null +++ b/mypsychtoolbox/OpenDisplay.m @@ -0,0 +1,266 @@ +function [window] = OpenDisplay(subscreen,color,screen_number,debug) +% OpenDisplay - Easy open of the display using Psychtoolbox's Screen +% [window] = OpenDisplay(subscreen,color) +%% INPUTS +if nargin<2 + color=[0 0 0]; +end +if nargin<1 + subscreen = [ 640 480 ]; +end +if nargin<4 + debug = ~isempty(subscreen); +end +%% Invoke PTB OpenGL functions +AssertOpenGL; +scr.Screens = Screen('Screens'); +scr.nScreens = numel(scr.Screens); +if nargin<3 + scr.screenNumber = max(scr.Screens); +else + scr.screenNumber = screen_number; +end +%scr.Resolution = Screen('Resolution',scr.screenNumber); +kPNFOW = []; + +if numel(subscreen)==2 + if isempty(scr.screenNumber) + scr.screenNumber = 0; + end + if scr.nScreens==1 + %do nothing + [wh]=Screen('Rect', scr.screenNumber); + subscreen = RectPosition(subscreen,wh,'ctmr'); + elseif all(Screen('Rect', 0)>=0) && all(Screen('Rect', 2)>=0) + if isempty(scr.screenNumber) + scr.screenNumber = 1; + end + [wh]=Screen('Rect', scr.screenNumber); + % if scr.screenNumber == 2 + % wh(:,1) = wh(:,1) - wh(:,3); + % wh(:,3) = 0; + % end + %subscreen = RectPosition(subscreen,wh,'rrrctttm'); + subscreen = RectPosition(subscreen,wh,'c'); + else + [wh]=Screen('Rect',2); + subscreen = 100+[ wh(1) 0 subscreen+[wh(1) 0] ]; + end +end + +if debug + Screen('Preference', 'SkipSyncTests', 1); +else + % kPsychNeedFastOffscreenWindows + kPNFOW = kPsychNeedFastOffscreenWindows; + Screen('Preference', 'SkipSyncTests', 0); +end +Screen('Preference', 'Verbosity', 1); +Screen('Preference', 'VBLTimeStampingMode', -1); + +window = struct; + +if numel(subscreen)==0 + % Open whole screen display + [window.ptr, window.rect] = Screen('OpenWindow', ... + scr.screenNumber, color, [], [], [], [], [], ... + kPNFOW); + [subscreen]=Screen('Rect', scr.screenNumber); + if scr.screenNumber == 2 + subscreen(:,1) = subscreen(:,1) - subscreen(:,3); + subscreen(:,3) = 0; + end + +else + %Open a smaller graphic window in the screen + [window.ptr, window.rect] = Screen('OpenWindow', ... + scr.screenNumber, color, subscreen, [], [], [], [], ... + kPNFOW); +end +window.screenNumber = scr.screenNumber; + + window.screen_rect = subscreen; +if scr.nScreens > 1 + all(Screen('Rect', 2)>=0) && all(Screen('Rect', 0)>=0) + window.screen_rect([1 3]) = window.screen_rect([1 3]) + Screen('Rect',2)*[-1;0;1;0]; +end + +window.color=color; +[window.size(1), window.size(2)] = Screen('WindowSize', window.ptr); +% Enable alpha blending with proper blend-function. We need it +% for drawing of smoothed points: +try + Screen('BlendFunction', window.ptr, GL_SRC_ALPHA, GL_ONE_MINUS_SRC_ALPHA); +catch +end +Screen('Flip', window.ptr); +window.fps = Screen('FrameRate', window.ptr); +window.ifi = 1./window.fps; + +try + if ~EXPERIMENT.DEBUG + HideCursor; + Priority(MaxPriority(window.ptr)); + % Retrieves flip interval only for fullscreen mode + window.ifi = Screen('GetFlipInterval', window.ptr, 100, 50e-6, 10); + % Retrieves number of frames per second + window.fps = Screen('FrameRate', window.ptr); + if window.fps==0 + window.fps=1/window.ifi; + end; + + % Color calibration + % LoadIdentityClut(window.ptr); + % window.clut = CreateCalibratedClut(screen); + else + fprintf('Debug mode required\n'); + end +catch + fprintf('Debug mode\n'); +end + + + +return + +% % Activate compatibility mode: Try to behave like the old MacOS-9 Psychtoolbox: +% oldEnableFlag=Screen('Preference', 'EmulateOldPTB', [enableFlag]); +% +% % Open or close a window or texture: +% [windowPtr,rect]=Screen('OpenWindow',windowPtrOrScreenNumber [,color] [,rect] [,pixelSize] [,numberOfBuffers] [,stereomode] [,multisample][,imagingmode]); +% [windowPtr,rect]=Screen('OpenOffscreenWindow',windowPtrOrScreenNumber [,color] [,rect] [,pixelSize]); +% textureIndex=Screen('MakeTexture', WindowIndex, imageMatrix [, optimizeForDrawAngle=0] [, enforcepot=0] [, floatprecision=0] [, textureOrientation=0]); +% Screen('Close', windowOrTextureIndex); +% Screen('CloseAll'); +% +% % Draw lines and solids like QuickDraw and DirectX (OS 9 and Windows): +% Screen('SelectStereoDrawBuffer', windowPtr, bufferid); +% Screen('DrawLine', windowPtr [,color], fromH, fromV, toH, toV [,penWidth]); +% Screen('DrawArc',windowPtr,[color],[rect],startAngle,arcAngle) +% Screen('FrameArc',windowPtr,[color],[rect],startAngle,arcAngle[,penWidth] [,penHeight] [,penMode]) +% Screen('FillArc',windowPtr,[color],[rect],startAngle,arcAngle) +% Screen('FillRect', windowPtr [,color] [,rect] ); +% Screen('FrameRect', windowPtr [,color] [,rect] [,penWidth]); +% Screen('FillOval', windowPtr [,color] [,rect]); +% Screen('FrameOval', windowPtr [,color] [,rect] [,penWidth] [,penHeight] [,penMode]); +% Screen('FillPoly', windowPtr [,color], pointList); +% +% % New OpenGL functions for OS X: +% Screen('glPoint', windowPtr, color, x, y [,size]); +% Screen('gluDisk', windowPtr, color, x, y [,size]); +% Screen('DrawDots', windowPtr, xy [,size] [,color] [,center] [,dot_type]); +% Screen('DrawLines', windowPtr, xy [,width] [,colors] [,center] [,smooth]); +% [sourceFactorOld, destinationFactorOld]=('BlendFunction', windowIndex, [sourceFactorNew], [destinationFactorNew]); +% +% % Draw Text in windows +% textModes = Screen('TextModes'); +% oldCopyMode=Screen('TextMode', windowPtr [,textMode]); +% oldTextSize=Screen('TextSize', windowPtr [,textSize]); +% oldStyle=Screen('TextStyle', windowPtr [,style]); +% [oldFontName,oldFontNumber]=Screen(windowPtr,'TextFont' [,fontNameOrNumber]); +% [normBoundsRect, offsetBoundsRect]=Screen('TextBounds', windowPtr, text); +% [newX,newY]=Screen('DrawText', windowPtr, text [,x] [,y] [,color] [,backgroundColor] [,yPositionIsBaseline]); +% oldTextColor=Screen('TextColor', windowPtr [,colorVector]); +% oldTextBackgroundColor=Screen('TextBackgroundColor', windowPtr [,colorVector]); +% +% % Copy an image, very quickly, between textures, offscreen windows and onscreen windows. +% [resident [texidresident]] = Screen('PreloadTextures', windowPtr [, texids]); +% Screen('DrawTexture', windowPointer, texturePointer [,sourceRect] [,destinationRect] [,rotationAngle] [, filterMode] [, globalAlpha]); +% Screen('CopyWindow', srcWindowPtr, dstWindowPtr, [srcRect], [dstRect], [copyMode]) +% +% % Copy an image, slowly, between matrices and windows : +% imageArray=Screen('GetImage', windowPtr [,rect] [,bufferName]); +% Screen('PutImage', windowPtr, imageArray [,rect]); +% +% % Synchronize with the window's screen (on-screen only): +% [VBLTimestamp StimulusOnsetTime FlipTimestamp Missed Beampos] = Screen('Flip', windowPtr [, when] [, dontclear] [, dontsync] [, multiflip]); +% [telapsed] = Screen('DrawingFinished', windowPtr [, dontclear] [, sync]); +% framesSinceLastWait = Screen('WaitBlanking', windowPtr [, waitFrames]); +% +% % Load color lookup table of the window's screen (on-screen only): +% [gammatable, dacbits, reallutsize] = Screen('ReadNormalizedGammaTable', windowPtrOrScreenNumber); +% Screen('LoadNormalizedGammaTable', windowPtrOrScreenNumber, table [, loadOnNextFlip]); +% oldclut = Screen('LoadCLUT', windowPtrOrScreenNumber [, clut] [, startEntry=0] [, bits=8]); +% +% % Get (and set) information about a window or screen: +% screenNumbers=Screen('Screens); +% windowPtrs=Screen('Windows'); +% kind=Screen(windowPtr, 'WindowKind'); +% isOffscreen=Screen(windowPtr,'IsOffscreen'); +% hz=Screen('FrameRate', windowPtrOrScreenNumber [, mode] [, reqFrameRate]); +% hz=Screen('NominalFrameRate', windowPtrOrScreenNumber [, mode] [, reqFrameRate]); +% [ monitorFlipInterval nrValidSamples stddev ]=Screen('GetFlipInterval', windowPtr [, nrSamples] [, stddev] [, timeout]); +% screenNumber=Screen('WindowScreenNumber', windowPtr); +% rect=Screen('Rect', windowPtrOrScreenNumber); +% pixelSize=Screen('PixelSize', windowPtrOrScreenNumber); +% pixelSizes=Screen('PixelSizes', windowPtrOrScreenNumber); +% [width, height]=Screen('WindowSize', windowPointerOrScreenNumber); +% [width, height]=Screen('DisplaySize', ScreenNumber); +% [oldmaximumvalue oldclampcolors] = Screen('ColorRange', windowPtr [, maximumvalue][, clampcolors=1]); +% +% % Get/set details of environment, computer, and video card (i.e. screen): +% struct=Screen('Version'); +% comp=Screen('Computer'); +% oldBool=Screen('Preference', 'IgnoreCase' [,bool]); +% tick0Secs=Screen('Preference', 'Tick0Secs', tick0Secs); +% psychTableVersion=Screen('Preference', 'PsychTableVersion'); +% mexFunctionName=Screen('Preference', 'PsychTableCreator'); +% proc=Screen('Preference', 'Process'); +% oldBool=Screen('Preference','Backgrounding'); +% oldSecondsMultiplier=Screen('Preference', 'SecondsMultiplier'); +% Screen('Preference','SkipSyncTests', skipTest); +% Screen('Preference','VisualDebugLevel', level (valid values between 0 and 5)); +% Screen('Preference', 'ConserveVRAM', mode (valid values between 0 and 3)); +% Screen('Preference', 'Enable3DGraphics', [enableFlag]); +% +% % Helper functions. Don't call these directly, use eponymous wrappers: +% [x, y, buttonVector]= Screen('GetMouseHelper', numButtons); +% Screen('HideCursorHelper', windowPntr); +% Screen('ShowCursorHelper', windowPntr); +% Screen('SetMouseHelper', windowPntrOrScreenNumber, x, y); +% +% % Internal testing of Screen +% timeList= Screen('GetTimelist'); +% Screen('ClearTimelist'); +% Screen('Preference','DebugMakeTexture', enableDebugging); +% +% % Movie and multimedia playback functions: +% [ moviePtr [duration] [fps] [width] [height] [count]]=Screen('OpenMovie', windowPtr, moviefile [, async=0]); +% Screen('CloseMovie', moviePtr); +% [ texturePtr [timeindex]]=Screen('GetMovieImage', windowPtr, moviePtr, [waitForImage], [fortimeindex]); +% [droppedframes] = Screen('PlayMovie', moviePtr, rate, [loop], [soundvolume]); +% timeindex = Screen('GetMovieTimeIndex', moviePtr); +% [oldtimeindex] = Screen('SetMovieTimeIndex', moviePtr, timeindex); +% +% % Video capture functions: +% videoPtr =Screen('OpenVideoCapture', windowPtr [, deviceIndex] [,roirectangle] [, pixeldepth] [, numbuffers] [, allowfallback] [, targetmoviename] [, recordingflags]); +% Screen('CloseVideoCapture', capturePtr); +% [fps starttime] = Screen('StartVideoCapture', capturePtr [, captureRateFPS] [, dropframes=0] [, startAt]); +% droppedframes = Screen('StopVideoCapture', capturePtr); +% [texturePtr [capturetimestamp] [droppedcount] [summed_intensity]]=Screen('GetCapturedImage', windowPtr, capturePtr [, waitForImage=1] [,oldTexture] [,specialmode]); +% oldvalue = Screen('SetVideoCaptureParameter', capturePtr, 'parameterName' [, value]); +% +% % Low level direct access to OpenGL-API functions: +% % Online info for each function available by opening a terminal window +% % and typing 'man Functionname' + Enter. +% +% Screen('glPushMatrix', windowPtr); +% Screen('glPopMatrix', windowPtr); +% Screen('glLoadIdentity', windowPtr); +% Screen('glTranslate', windowPtr, tx, ty [, tz]); +% Screen('glScale', windowPtr, sx, sy [, sz]); +% Screen('glRotate', windowPtr, angle, [rx = 0], [ry = 0] ,[rz = 1]); +% +% % Support for 3D graphics rendering and for interfacing with external OpenGL code: +% Screen('Preference', 'Enable3DGraphics', [enableFlag]); % Enable 3D gfx support. +% Screen('BeginOpenGL', windowPtr [, sharecontext]); % Prepare window for external OpenGL drawing. +% Screen('EndOpenGL', windowPtr); % Finish external OpenGL drawing. +% [textureHandle rect] = Screen('SetOpenGLTextureFromMemPointer', windowPtr, textureHandle, imagePtr, width, height, depth [, upsidedown][, target][, glinternalformat][, gltype][, extdataformat]); +% [textureHandle rect] = Screen('SetOpenGLTexture', windowPtr, textureHandle, glTexid, target [, glWidth] [, glHeight] [, glDepth]); +% [ gltexid gltextarget texcoord_u texcoord_v ] =Screen('GetOpenGLTexture', windowPtr, textureHandle [, x][, y]); +% +% % Support for plugins and for builtin high performance image processing pipeline: +% [ret1, ret2, ...] = Screen('HookFunction', windowPtr, 'Subcommand', 'HookName', arg1, arg2, ...); +% proxyPtr = Screen('OpenProxy', windowPtr [, imagingmode]); +% transtexid = Screen('TransformTexture', sourceTexture, transformProxyPtr +% [, targetTexture]); \ No newline at end of file diff --git a/mypsychtoolbox/RectAlign.m b/mypsychtoolbox/RectAlign.m new file mode 100644 index 0000000..6a65a67 --- /dev/null +++ b/mypsychtoolbox/RectAlign.m @@ -0,0 +1,127 @@ +function [xywh,wh,scr] = RectAlign(wh,scr,varargin) +%RectAlign - Compute coordinates to align rectangular objects +% [xywh] = RectAlign(wh,r,alignment) +% wh = the N-by-2 array of widths and heights of the object to align +% r = the [width height] of the containing rectangle/window +% or a screen number/pointer, or a screen resolution structure, +% as output by Screen('Resolution') +% alignment is a string specifying the style of alignment to use : +% '[C]' for centered (default) | '[L]eft' | '[R]ight' | +% '[T]op' | '[M]iddle' | '[B]ottom' (or any combination of these +% letters, e.g., 'ctm' for horizontally centered but vertically +% at mid-way between the top and the middle of the screen. +% +%OUTPUTS: +% xywh = a N-by-4 array with: +% xywh(:,1) = the horizontal displacement(s) +% xywh(:,2) = the vertical displacement(s) +% xywh(:,3) = right border, i.e. xywh(:,3)-xywh(:,1) = wh(:,1) +% xywh(:,4) = bottom border, i.e. xywh(:,4)-xywh(:,2) = wh(:,2) +% +% Example +% RectAlign([300 200], [640 480]) +% RectAlign([300 NaN], [640 480]) % define a square window +% RectAlign([.3 200], [frame.ptr]) +% +% See also + +% Author: Karim NDiaye +% Created: Jan 2009 +% Copyright 2009 + +if nargin<2 + scr = 0; +end +if numel(scr)==1 + scr = Screen('Rect',scr); +end +if isstruct(scr) + scr = [scr.width scr.height]; +end +if size(scr,2) == 2 + scr = [0 0 scr(1) scr(2)]; +end +if size(wh,2)==4 + wh = [ wh(:,3)-wh(:,1) wh(:,4)-wh(:,2) ]; +end + +[i,j]=find(wh<=1); +k=find(wh<=1); +wh(k(j==1))=wh(k(j==1))*(scr(3)-scr(1)); +wh(k(j==2))=wh(k(j==2))*(scr(4)-scr(2)); + +if nargin<3 + alignment=''; +else + alignment=varargin{1}; +end +if isnumeric(alignment) + if size(alignment,2) == 2 + x=alignment(:,1); + y=alignment(:,2); + else + error('myspychoolbox:RectAlign','Wrong numeric alignment') + end +else + alignment=lower(alignment); + if isequal(alignment, 'center') + alignment='c'; + end + if isequal(alignment, 'right') + alignment='r'; + end + if isequal(alignment, 'left') + alignment='l'; + end + if isequal(alignment, 'top') + alignment='t'; + end + if isequal(alignment, 'middle') + alignment='m'; + end + if isequal(alignment, 'bottom') + alignment='b'; + end + + [z,z]=ismember(alignment,'lcrtmb'); + if any(z==0) + error('myspychoolbox:RectAlign','Wrong alignment parameter!'); + end + if any(z<=3) + x=mean(z(z<=3))-2; + else + x=NaN; + end + if isnan(x) + x=0; + end + if any(z>=4) + y=mean(z(z>=4))-5; + else + y=NaN; + end + if isnan(y) + y=0; + end +end +wnan = isnan(wh(:,1)); +hnan = isnan(wh(:,2)); +if numel(scr)==2 + scr=[0 0 scr ]; +end +wrel = abs(wh(:,1))<1; +hrel = abs(wh(:,2))<1; +wh(wrel,1)=(scr(:,3)-scr(:,1)).*wh(wrel,1); +wh(hrel,2)=(scr(:,4)-scr(:,2)).*wh(hrel,2); + +wh(wnan,1) = wh(wnan,2); +wh(hnan,2) = wh(hnan,1); + +% xywh(:,1) = (1+x) * (scr(1)-wh(:,1))/2; +% xywh(:,2) = (1+y) * (scr(2)-wh(:,2))/2; +xywh(:,1) = scr(:,1) + (1+x) * ((scr(:,3)-scr(:,1))-wh(:,1))/2; +xywh(:,2) = scr(:,2) + (1+y) * ((scr(:,4)-scr(:,2))-wh(:,2))/2; + + +xywh(:,3) = xywh(:,1) + wh(:,1); +xywh(:,4) = xywh(:,2) + wh(:,2); diff --git a/mypsychtoolbox/RectPosition.m b/mypsychtoolbox/RectPosition.m new file mode 100644 index 0000000..604ea6c --- /dev/null +++ b/mypsychtoolbox/RectPosition.m @@ -0,0 +1,4 @@ +function [xywh,wh,scr] = RectPosition(wh,scr,varargin) +% RectPosition - Deprecated see RectAlign +warning('MyPsychtoolbox:RectPositionDeprecated', 'RectPosition is deprecated; use RectAlign() instead'); +[xywh,wh,scr] = RectAlign(wh,scr,varargin{:}); diff --git a/mypsychtoolbox/WaitAnyPress.m b/mypsychtoolbox/WaitAnyPress.m new file mode 100644 index 0000000..3b63302 --- /dev/null +++ b/mypsychtoolbox/WaitAnyPress.m @@ -0,0 +1,102 @@ +function [rt, k, t0, t] = WaitAnyPress(keys, timeout, newOnly) +% WaitAnyPress - Wait for a button or a key press +% +% [rt, k, t0, t] = WaitAnyPress(keys, timeout, newOnly) +% +%INPUTS: +% keys: code of keys to listen to. Keyboard keys are mapped on 8:256. +% By default, mouse clicks (which are mapped on 1=Left, 2=Right, +% 3=??, 4=Middle, 5=Backward, 6=Forward) are not listened. Parallel +% port is read with ReadParPort(), if available. Bits are assigned +% to the keycodes [257:264] so that: +% 1 (bit0) = 257 (left LENA-button) +% 2 (bit1) = 258 (middle LENA-button) +% 4 (bit2) = 259 (right LENA-button) +% ... +% 128 (bit7) = 264 +% timeout: Duration of the timeout in seconds. +% newOnly: Only detect new keypress (not keys that were already pressed from +% the onset), default: true +%OUPUTS: +% rt: reaction time (NaN if no key was pressed before timeout) +% k : array with 1's for the button/key which have been pressed +% t0: start time of the wait +% t : real time of the press, so that rt = t - t0 +% +%See also: WaitAnyRelease, ReadParPort + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-13 Creation +% KND 2009-03-30 Test OpenParPort to set default keys +% KND 2010-11-18 Keys that are pressed on call may now be discarded +% ----------------------------- Script History --------------------------------- + +t0=GetSecs; +t=0; +rt=nan; +if nargin<3 + % wait for a new press (not one that was already down) + newOnly = 1; +end +if nargin<2 + timeout = Inf; +end +btnCode = 256+[1:8]; +if nargin<1 + keys=[]; +end +if isempty(keys) + % Not accepting mouse buttons (from 1 to 7) + keys = [ 8:256 ]; + global PAR_PORT + if ~isempty(PAR_PORT) + keys = [ keys btnCode ]; + end +end +if any(keys<8) + checkMouse = 1; +else + checkMouse = 0; +end +if any(keys>256) + checkParPort = 1; +else + checkParPort = 0; +end +if any(keys<1) + error('Can''t map keys below 1'); +end +k=zeros(1,max(keys)); +k_new = []; +k1=k; +while ~any(k(keys)) && ((t-t0) < timeout) + [keyIsDown,t,k] = KbCheck; + if checkParPort + [btnState] = ReadParPort(0); + k(btnCode) = 0; + k(btnCode(logical(bitget(btnState,1:8)))) = 1; + end + if checkMouse + [mouseState,mouseState,mouseState] = GetMouse; + k(mouseState) = 0; + k(1:3) = mouseState; + end + if newOnly + % Keys that were down from the start, will not trigger a response + if isempty(k_new);k_new=k;end + k1=k; + k(k==k_new)=0; + % Listen to them however if they have been released in the meantime + k_new(k1yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-23 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<2 + timeout = Inf; +end +btnCode = 256+[1:3]; +if nargin<1 + keys=[]; +end +if isempty(keys) + % By default doesn't listen to mouse buttons (from 1 to 7) + keys = [ 8:256 btnCode ]; +end +if any(keys>256) + checkButtons = 1; +else + checkButtons = 0; +end +% At onset, check state of buttons and keys +rt=nan; +t=0; +[keyIsDown,t0,k1] = KbCheck; +if checkButtons + btnPress=0; + [btnPress] = ReadParPort(0); + k1(btnCode) = 0; + k1(btnCode(logical(bitget(btnPress,1:3)))) = 1; +end +k=zeros(1,max(keys)); +while ~any(k(keys)) && ((t-t0) < timeout) + k0 = k1; + [keyIsDown,t,k1] = KbCheck; + if checkButtons + [btnState] = ReadParPort(0); + k1(btnCode) = 0; + k1(btnCode(logical(bitget(btnState,1:3)))) = 1; + end + k = k0 & ~logical(k1); +end +if any(k(keys)) + rt = t-t0; +end diff --git a/mypsychtoolbox/WaitKeyPress.m b/mypsychtoolbox/WaitKeyPress.m new file mode 100644 index 0000000..f75b343 --- /dev/null +++ b/mypsychtoolbox/WaitKeyPress.m @@ -0,0 +1,48 @@ +function [key, t, i] = WaitKeyPress(whichKeys, whichMarkers, timeout) +% WaitKeyPress - Wait for a key press from user and send marker(s) +% [key, t, i] = WaitKeyPress(whichKeys, whichMarkers, timeout) waits for a +% keypress from user and returns the key code and the time of it +% +%INPUTS: +% whichKeys: list of key codes/names. [] (default) listens to any key +% +if nargin < 3 + timeout = 10; +end +if nargin < 2 + whichMarkers = []; +end +if nargin < 1 + whichKeys = {}; +end + +if isempty(whichKeys) + whichKeyCodes = 1:256; +elseif iscell(whichKeys) + whichKeyCodes = KbName(whichKeys); +end +i = []; +t = []; +key = []; +t0 = GetSecs(); +while (GetSecs() - t0) <= timeout + [isKeyDown, keyTime, keyCode] = KbCheck(); + if any(keyCode(whichKeyCodes)) + t = keyTime; + i = find(keyCode(whichKeyCodes), 1); + key = KbName(whichKeyCodes(i)); + if ~isempty(whichMarkers) + WriteMarker(whichMarkers(i)); + end + FlushEvents('keyDown'); +% while true +% [isKeyDown, keyTime, keyCode] = KbCheck(); +% if ~any(keyCode(whichKeyCodes)) && GetSecs() - t > 10e-3 +% break +% end +% end + break + end +end + +end diff --git a/mypsychtoolbox/WaitMouseClick.m b/mypsychtoolbox/WaitMouseClick.m new file mode 100644 index 0000000..29445ca --- /dev/null +++ b/mypsychtoolbox/WaitMouseClick.m @@ -0,0 +1,47 @@ +function [button,t] = WaitMouseClick(timeout,whichButtons, whichMarkers) + +if nargin < 1 || isempty(timeout) + timeout = 10; +end +if nargin < 2 || isempty(whichButtons) + whichButtons = (1:3); +end +if nargin < 3 + whichMarkers = []; +end +if ~isempty(whichMarkers) + wm = whichMarkers; + try % Quick and dirty test to see if buttons & markers match + wm=whichButtons; + wm=whichMarkers; + catch + error('Markers and Buttons do not match'); + end +end +% whichButtons = swap(whichButtons, 2, 3); + +t0 = GetSecs(); +while true + if GetSecs() - t0 > timeout + t = []; + button = []; + break + end + [xMouse, yMouse, mouseButtons] = GetMouse(); + if any(mouseButtons(whichButtons)) + t = GetSecs(); + i = find(mouseButtons(whichButtons), 1); + button = whichButtons(i); + % button = swap(whichButtons(i), 2, 3); + if ~isempty(whichMarkers) + WriteMarker(whichMarkers(i)); + end + while true + [xMouse, yMouse, mouseButtons] = GetMouse(); + if ~any(mouseButtons(whichButtons)) && GetSecs() - t > 10e-3 + break + end + end + break + end +end diff --git a/mypsychtoolox.m b/mypsychtoolox.m new file mode 100644 index 0000000..0b0165b --- /dev/null +++ b/mypsychtoolox.m @@ -0,0 +1,42 @@ +function mypsychtoolox +%MYPSYCHTOOLOX - Add paths to run Psychtoolbox +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-01-17 Creation +% +% ----------------------------- Script History --------------------------------- +lcd=cd; +pwd=fullfile(fileparts(fileparts(mfilename('fullpath'))), 'mtoolbox', 'psychtoolbox'); +cd(pwd) +SetupPsychtoolbox +addpath(fullfile(mymatlabpath,'psychtoolbox')); +cd(lcd) + + +return + +addpath(pwd) +addpath(fullfile(pwd,'PsychBasic')) +addpath(fullfile(pwd,'PsychCal')) +addpath(fullfile(pwd,'PsychFiles')) +addpath(fullfile(pwd,'PsychGamma')) +addpath(fullfile(pwd,'PsychHardware')) +addpath(fullfile(pwd,'PsychInitialize')) +addpath(fullfile(pwd,'PsychJava')) +addpath(fullfile(pwd,'PsychOneliners')) +addpath(fullfile(pwd,'PsychOpenGL')) +addpath(fullfile(pwd,'PsychPriority')) +addpath(fullfile(pwd,'PsychProbability')) +addpath(fullfile(pwd,'PsychRects')) +addpath(fullfile(pwd,'PsychSignal')) +addpath(fullfile(pwd,'PsychOpenGL')) +addpath(fullfile(pwd,'PsychSound')) diff --git a/myspm.m b/myspm.m new file mode 100644 index 0000000..cba242c --- /dev/null +++ b/myspm.m @@ -0,0 +1,117 @@ +function [spmpath] = myspm(varargin) +%MYSPM - Sets SPM path according to the specified version +% [] = myspm('spm2') +% [] = myspm('2') +% Sets the path for SPM2 and runs it. +% +% [] = myspm('ver','spm2','do',action) +% Sets the path for SPM2 and performs the "action" ('run' [default] or 'nothing') +% +% Example +% >> myspm +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-31 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin==1 + options=[{'ver'},varargin]; +else + options=varargin; +end +if nargin>0 + options=struct(options{:}); +else + options=[]; +end +defaults=struct('ver', 'spm5', 'do', 'run', 'mymatlabpath', fileparts(mfilename('fullpath')), 'rmpath', 1); +options = mergestructs(defaults,options); + +[hostname,hostname]=system('hostname'); + +if ~isempty(regexpi(hostname, 'chups.jussieu.fr')) + tbxpath='~/mtoolbox'; + myspmpath=fullfile(options.mymatlabpath,'spm'); +else + switch upper(deblank(hostname)) + case 'D5BDS81J' % LABNIC Office compute + switch options.ver + case {'spm2', '2'} + tbxpath='c:\spm\'; + myspmpath=fullfile(options.mymatabpath,'spm'); + otherwise + error('Unknown version: %s', options.ver); + end + case 'IMAGERIE2-PV' % steph's PC + case 'MONTBLANC' + case 'KARIMND' + options.mymatabpath = 'e:\ndiaye\home\matlab'; + tbxpath='e:\mtoolbox\'; + myspmpath=fullfile(options.mymatabpath,'spm'); + otherwise + tbxpath=fullfile(fileparts(options.mymatabpath),'mtoolbox'); + myspmpath=fullfile(options.mymatabpath,'spm'); + end +end +if isnumeric(options.ver) + options.ver=num2str(options.ver); +end +switch options.ver + case {'spm2', '2'} + options.ver = 'spm2'; + spmpath =fullfile(tbxpath,'spm2'); + myspmpath=fullfile(myspmpath,'spm2'); + case {'spm5', '5'} + options.ver = 'spm5'; + spmpath =fullfile(tbxpath,'spm5'); + myspmpath=fullfile(myspmpath,'spm5'); + case {'spm8', '8'} + options.ver='spm8'; + spmpath =fullfile(tbxpath,'spm8'); + myspmpath=fullfile(myspmpath,'spm8'); + otherwise + error('Unknown version: %s', options.ver); +end + +if options.rmpath + % Find current SPM-directories & subdirectories: + s=lower(fileparts(which('spm'))); + if ~isempty(s) && ~isequal(s,spmpath) + p=lower(path); + if numel(strread(p,'%s', 'delimiter', ';'))==1 + % In later matlab, they use ":" as a delimiter + p=strread(p,'%s', 'delimiter', ':'); + else + p=strread(p,'%s', 'delimiter', ':'); + end + p=p(:); + for d=p(strmatch(s,p))' + rmpath(d{1}); + end + end +end +clear global +clear functions +%clear classes +addpath(spmpath,'-begin') + +% Specific dll for R2007a and later +if ispc && (datenum(version('-date')) > datenum('2007-03-01')) +addpath(fullfile(spmpath,'..', [options.ver '_R2007a_winXP']),'-begin') +end +if exist(myspmpath) + addpath(myspmpath,'-begin') +end + +if isequal(options.do,'run') + spm fmri +end diff --git a/myspm_image.m b/myspm_image.m new file mode 100644 index 0000000..2019bfc --- /dev/null +++ b/myspm_image.m @@ -0,0 +1,466 @@ +function spm_image(op,varargin) +% image and header display +% FORMAT spm_image +%_______________________________________________________________________ +% +% spm_image is an interactive facility that allows orthogonal sections +% from an image volume to be displayed. Clicking the cursor on either +% of the three images moves the point around which the orthogonal +% sections are viewed. The co-ordinates of the cursor are shown both +% in voxel co-ordinates and millimeters within some fixed framework. +% The intensity at that point in the image (sampled using the current +% interpolation scheme) is also given. The position of the crosshairs +% can also be moved by specifying the co-ordinates in millimeters to +% which they should be moved. Clicking on the horizontal bar above +% these boxes will move the cursor back to the origin (analogous to +% setting the crosshair position (in mm) to [0 0 0]). +% +% The images can be re-oriented by entering appropriate translations, +% rotations and zooms into the panel on the left. The transformations +% can then be saved by hitting the ``Reorient images...'' button. The +% transformations that were applied to the image are saved to the +% ``.mat'' files of the selected images. The transformations are +% considered to be relative to any existing transformations that may be +% stored in the ``.mat'' files. Note that the order that the +% transformations are applied in is the same as in ``spm_matrix.m''. +% +% The ``Reset...'' button next to it is for setting the orientation of +% images back to transverse. It retains the current voxel sizes, +% but sets the origin of the images to be the centre of the volumes +% and all rotations back to zero. +% +% The right panel shows miscellaneous information about the image. +% This includes: +% Dimensions - the x, y and z dimensions of the image. +% Datatype - the computer representation of each voxel. +% Intensity - scalefactors and possibly a DC offset. +% Miscellaneous other information about the image. +% Vox size - the distance (in mm) between the centres of +% neighbouring voxels. +% Origin - the voxel at the origin of the co-ordinate system +% DIr Cos - Direction cosines. This is a widely used +% representation of the orientation of an image. +% +% There are also a few options for different resampling modes, zooms +% etc. You can also flip between voxel space (as would be displayed +% by Analyze) or world space (the orientation that SPM considers the +% image to be in). If you are re-orienting the images, make sure that +% world space is specified. Blobs (from activation studies) can be +% superimposed on the images and the intensity windowing can also be +% changed. +% +%_______________________________________________________________________ +% @(#)spm_image.m 2.20 John Ashburner 02/10/29 + +% global st + +% if nargin == 0, +% [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Display',0); +% SPMid = spm('FnBanner',mfilename,'2.20'); +% spm_help('!ContextHelp',[mfilename,'.m']); +% +% % get the image's filename {P} +% %----------------------------------------------------------------------- +% P = spm_get(1,'IMAGE','please select image',[],0); +% myspm_image('init',P); +% return; +% end; + +try + if ~strcmp(op,'init') & ~strcmp(op,'reset') & isempty(st.vols{1}) + my_reset; warning('Lost all the image information'); + return; + end; +end + +if strcmp(op,'repos'), + % The widgets for translation rotation or zooms have been modified. + %----------------------------------------------------------------------- + fg = gcf % spm_figure('Findwin','Graphics'); + set(fg,'Pointer','watch'); + i = varargin{1}; + st.B(i) = eval(get(gco,'String'),num2str(st.B(i))); + set(gco,'String',st.B(i)); + st.vols{1}.premul = spm_matrix(st.B); + % spm_orthviews('MaxBB'); + myspm_image('zoom_in'); + myspm_image('update_info'); + set(fg,'Pointer','arrow'); + return; +end; + +if strcmp(op,'shopos'), + % The position of the crosshairs has been moved. + %----------------------------------------------------------------------- + if isfield(st,'mp'), + fg = gcf % spm_figure('Findwin','Graphics'); + if any(findobj(fg) == st.mp), + set(st.mp,'String',sprintf('%.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',1); + set(st.vp,'String',sprintf('%.1f %.1f %.1f',pos)); + set(st.in,'String',sprintf('%g',spm_sample_vol(st.vols{1},pos(1),pos(2),pos(3),st.hld))); + else, + st.Callback = ';'; + rmfield(st,{'mp','vp','in'}); + end; + else, + st.Callback = ';'; + end; + return; +end; + +if strcmp(op,'setposmm'), + % Move the crosshairs to the specified position + %----------------------------------------------------------------------- + if isfield(st,'mp'), + fg = gcf % spm_figure('Findwin','Graphics'); + if any(findobj(fg) == st.mp), + pos = sscanf(get(st.mp,'String'), '%g %g %g'); + if length(pos)~=3, + pos = spm_orthviews('pos'); + end; + spm_orthviews('Reposition',pos); + end; + end; + return; +end; + +if strcmp(op,'setposvx'), + % Move the crosshairs to the specified position + %----------------------------------------------------------------------- + if isfield(st,'mp'), + fg = gcf % spm_figure('Findwin','Graphics'); + if any(findobj(fg) == st.vp), + pos = sscanf(get(st.vp,'String'), '%g %g %g'); + if length(pos)~=3, + pos = spm_orthviews('pos',1); + end; + tmp = st.vols{1}.premul*st.vols{1}.mat; + pos = tmp(1:3,:)*[pos ; 1]; + spm_orthviews('Reposition',pos); + end; + end; + return; +end; + + +if strcmp(op,'addblobs'), + % Add blobs to the image - in full colour + spm_figure('Clear','Interactive'); + nblobs = spm_input('Number of sets of blobs',1,'1|2|3|4|5|6',[1 2 3 4 5 6],1); + for i=1:nblobs, + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + set(st.blobber,'String','Remove Blobs','Callback','myspm_image(''rmblobs'');'); + end; + spm_orthviews('Redraw'); +end; + +if strcmp(op,'rmblobs'), + % Remove all blobs from the images + spm_orthviews('rmblobs',1); + set(st.blobber,'String','Add Blobs','Callback','myspm_image(''addblobs'');'); +end; + +if strcmp(op,'window'), + op = get(st.win,'Value'); + if op == 1, + spm_orthviews('window',1); + else, + spm_orthviews('window',1,spm_input('Range','+1','e','',2)); + end; +end; + + +if strcmp(op,'reorient'), + % Time to modify the ``.mat'' files for the images. + % I hope that giving people this facility is the right thing to do.... + %----------------------------------------------------------------------- + mat = spm_matrix(st.B); + if det(mat)<=0 + spm('alert!','This will flip the images',mfilename,0,1); + end; + P = spm_get(Inf, 'IMAGE','Images to reorient'); + Mats = zeros(4,4,size(P,1)); + spm_progress_bar('Init',size(P,1),'Reading current orientations',... + 'Images Complete'); + for i=1:size(P,1), + Mats(:,:,i) = spm_get_space(P(i,:)); + spm_progress_bar('Set',i); + end; + spm_progress_bar('Init',size(P,1),'Reorienting images',... + 'Images Complete'); + for i=1:size(P,1), + spm_get_space(P(i,:),mat*Mats(:,:,i)); + spm_progress_bar('Set',i); + end; + spm_progress_bar('Clear'); + tmp = spm_get_space([st.vols{1}.fname ',' num2str(st.vols{1}.n)]); + if sum((tmp(:)-st.vols{1}.mat(:)).^2) > 1e-8, + myspm_image('init',st.vols{1}.fname); + end; + return; +end; + +if strcmp(op,'resetorient'), + % Time to modify the ``.mat'' files for the images. + % I hope that giving people this facility is the right thing to do.... + %----------------------------------------------------------------------- + P = spm_get(Inf, 'IMAGE','Images to reset orientation of'); + V = spm_vol(P); + spm_progress_bar('Init',size(P,1),'Resetting orientations',... + 'Images Complete'); + for i=1:size(P,1), + V = spm_vol(deblank(P(i,:))); + M = V.mat; + vox = sqrt(sum(M(1:3,1:3).^2)); + if det(M(1:3,1:3))<0, vox(1) = -vox(1); end; + orig = (V.dim(1:3)+1)/2; + off = -vox.*orig; + M = [vox(1) 0 0 off(1) + 0 vox(2) 0 off(2) + 0 0 vox(3) off(3) + 0 0 0 1]; + spm_get_space(P(i,:),M); + spm_progress_bar('Set',i); + end; + spm_progress_bar('Clear'); + tmp = spm_get_space([st.vols{1}.fname ',' num2str(st.vols{1}.n)]); + if sum((tmp(:)-st.vols{1}.mat(:)).^2) > 1e-8, + myspm_image('init',st.vols{1}.fname); + end; + return; +end; + +if strcmp(op,'update_info'), + % Modify the positional information in the right hand panel. + %----------------------------------------------------------------------- + mat = st.vols{1}.premul*st.vols{1}.mat; + Z = spm_imatrix(mat); + Z = Z(7:9); + + set(st.posinf.z,'String', sprintf('%.3g x %.3g x %.3g', Z)); + + O = mat\[0 0 0 1]'; O=O(1:3)'; + set(st.posinf.o, 'String', sprintf('%.3g %.3g %.3g', O)); + + R = spm_imatrix(mat); + R = spm_matrix([0 0 0 R(4:6)]); + R = R(1:3,1:3); + + tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(1,1:3)); tmp2(find(tmp2=='+')) = ' '; + set(st.posinf.m1, 'String', tmp2); + tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(2,1:3)); tmp2(find(tmp2=='+')) = ' '; + set(st.posinf.m2, 'String', tmp2); + tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(3,1:3)); tmp2(find(tmp2=='+')) = ' '; + set(st.posinf.m3, 'String', tmp2); + + tmp = [[R zeros(3,1)] ; 0 0 0 1]*diag([Z 1])*spm_matrix(-O) - mat; + + if sum(tmp(:).^2)>1e-8, + set(st.posinf.w, 'String', 'Warning: shears involved'); + else, + set(st.posinf.w, 'String', ''); + end; + + return; +end; + +if strcmp(op,'reset'), + my_reset; +end; + +if strcmp(op,'zoom_in'), + op = get(st.zoomer,'Value'); + if op==1, + spm_orthviews('resolution',1); + spm_orthviews('MaxBB'); + else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 2, st.bb = [pos-80*vx ; pos+80*vx] ; spm_orthviews('resolution',1); + elseif op == 3, st.bb = [pos-40*vx ; pos+40*vx] ; spm_orthviews('resolution',.5); + elseif op == 4, st.bb = [pos-20*vx ; pos+20*vx] ; spm_orthviews('resolution',.25); + elseif op == 5, st.bb = [pos-10*vx ; pos+10*vx] ; spm_orthviews('resolution',.125); + else , st.bb = [pos- 5*vx ; pos+ 5*vx] ; spm_orthviews('resolution',.125); + end; + end; + return; +end; + +if strcmp(op,'init'), +fg = spm_figure('GetWin','Graphics'); +if isempty(fg), error('Can''t create graphics window'); end +spm_figure('Clear','Graphics'); + +P = varargin{1}; +if ischar(P), P = spm_vol(P); end; +P = P(1); + +spm_orthviews('Reset'); +spm_orthviews('Image', P, [0.0 0.45 1 0.55]); +if isempty(st.vols{1}), return; end; + +spm_orthviews('MaxBB'); +st.callback = 'myspm_image(''shopos'');'; + +st.B = [0 0 0 0 0 0 1 1 1 0 0 0]; + +% locate Graphics window and clear it +%----------------------------------------------------------------------- +WS = spm('WinScale'); + +% Widgets for re-orienting images. +%----------------------------------------------------------------------- +uicontrol(fg,'Style','Frame','Position',[60 25 200 325].*WS,'DeleteFcn','myspm_image(''reset'');'); +uicontrol(fg,'Style','Text', 'Position',[75 220 100 016].*WS,'String','right {mm}'); +uicontrol(fg,'Style','Text', 'Position',[75 200 100 016].*WS,'String','foward {mm}'); +uicontrol(fg,'Style','Text', 'Position',[75 180 100 016].*WS,'String','up {mm}'); +uicontrol(fg,'Style','Text', 'Position',[75 160 100 016].*WS,'String','pitch {rad}'); +uicontrol(fg,'Style','Text', 'Position',[75 140 100 016].*WS,'String','roll {rad}'); +uicontrol(fg,'Style','Text', 'Position',[75 120 100 016].*WS,'String','yaw {rad}'); +uicontrol(fg,'Style','Text', 'Position',[75 100 100 016].*WS,'String','resize {x}'); +uicontrol(fg,'Style','Text', 'Position',[75 80 100 016].*WS,'String','resize {y}'); +uicontrol(fg,'Style','Text', 'Position',[75 60 100 016].*WS,'String','resize {z}'); + +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',1)','Position',[175 220 065 020].*WS,'String','0','ToolTipString','translate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',2)','Position',[175 200 065 020].*WS,'String','0','ToolTipString','translate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',3)','Position',[175 180 065 020].*WS,'String','0','ToolTipString','translate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',4)','Position',[175 160 065 020].*WS,'String','0','ToolTipString','rotate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',5)','Position',[175 140 065 020].*WS,'String','0','ToolTipString','rotate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',6)','Position',[175 120 065 020].*WS,'String','0','ToolTipString','rotate'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',7)','Position',[175 100 065 020].*WS,'String','1','ToolTipString','zoom'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',8)','Position',[175 80 065 020].*WS,'String','1','ToolTipString','zoom'); +uicontrol(fg,'Style','edit','Callback','myspm_image(''repos'',9)','Position',[175 60 065 020].*WS,'String','1','ToolTipString','zoom'); + +uicontrol(fg,'Style','Pushbutton','String','Reorient images...','Callback','myspm_image(''reorient'')',... + 'Position',[70 35 125 020].*WS,'ToolTipString','modify position information of selected images'); + +uicontrol(fg,'Style','Pushbutton','String','Reset...','Callback','myspm_image(''resetorient'')',... + 'Position',[195 35 55 020].*WS,'ToolTipString','reset orientations of selected images'); + +% Crosshair position +%----------------------------------------------------------------------- +uicontrol(fg,'Style','Frame','Position',[70 250 180 90].*WS); +uicontrol(fg,'Style','Text', 'Position',[75 320 170 016].*WS,'String','Crosshair Position'); +uicontrol(fg,'Style','PushButton', 'Position',[75 316 170 006].*WS,... + 'Callback','spm_orthviews(''Reposition'',[0 0 0]);','ToolTipString','move crosshairs to origin'); +% uicontrol(fg,'Style','PushButton', 'Position',[75 315 170 020].*WS,'String','Crosshair Position',... +% 'Callback','spm_orthviews(''Reposition'',[0 0 0]);','ToolTipString','move crosshairs to origin'); +uicontrol(fg,'Style','Text', 'Position',[75 295 35 020].*WS,'String','mm:'); +uicontrol(fg,'Style','Text', 'Position',[75 275 35 020].*WS,'String','vx:'); +uicontrol(fg,'Style','Text', 'Position',[75 255 65 020].*WS,'String','Intensity:'); + +st.mp = uicontrol(fg,'Style','edit', 'Position',[110 295 135 020].*WS,'String','','Callback','myspm_image(''setposmm'')','ToolTipString','move crosshairs to mm coordinates'); +st.vp = uicontrol(fg,'Style','edit', 'Position',[110 275 135 020].*WS,'String','','Callback','myspm_image(''setposvx'')','ToolTipString','move crosshairs to voxel coordinates'); +st.in = uicontrol(fg,'Style','Text', 'Position',[140 255 85 020].*WS,'String',''); + +% General information +%----------------------------------------------------------------------- +uicontrol(fg,'Style','Frame','Position',[305 25 280 325].*WS); +uicontrol(fg,'Style','Text','Position' ,[310 330 50 016].*WS,... + 'HorizontalAlignment','right', 'String', 'File:'); +uicontrol(fg,'Style','Text','Position' ,[360 330 210 016].*WS,... + 'HorizontalAlignment','left', 'String', spm_str_manip(st.vols{1}.fname,'k25'),'FontWeight','bold'); +uicontrol(fg,'Style','Text','Position' ,[310 310 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Dimensions:'); +uicontrol(fg,'Style','Text','Position' ,[410 310 160 016].*WS,... + 'HorizontalAlignment','left', 'String', sprintf('%d x %d x %d', st.vols{1}.dim(1:3)),'FontWeight','bold'); +uicontrol(fg,'Style','Text','Position' ,[310 290 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Datatype:'); +uicontrol(fg,'Style','Text','Position' ,[410 290 160 016].*WS,... + 'HorizontalAlignment','left', 'String', spm_type(st.vols{1}.dim(4)),'FontWeight','bold'); +uicontrol(fg,'Style','Text','Position' ,[310 270 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Intensity:'); +str = 'varied'; +if size(st.vols{1}.pinfo,2) == 1, + if st.vols{1}.pinfo(2), + str = sprintf('Y = %g X + %g', st.vols{1}.pinfo(1:2)'); + else, + str = sprintf('Y = %g X', st.vols{1}.pinfo(1)'); + end; +end; +uicontrol(fg,'Style','Text','Position' ,[410 270 160 016].*WS,... + 'HorizontalAlignment','left', 'String', str,'FontWeight','bold'); + +if isfield(st.vols{1}, 'descrip'), + uicontrol(fg,'Style','Text','Position' ,[310 250 260 016].*WS,... + 'HorizontalAlignment','center', 'String', st.vols{1}.descrip,'FontWeight','bold'); +end; + + +% Positional information +%----------------------------------------------------------------------- +mat = st.vols{1}.premul*st.vols{1}.mat; +Z = spm_imatrix(mat); +Z = Z(7:9); +uicontrol(fg,'Style','Text','Position' ,[310 210 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Vox size:'); +st.posinf = struct('z',uicontrol(fg,'Style','Text','Position' ,[410 210 160 016].*WS,... + 'HorizontalAlignment','left', 'String', sprintf('%.3g x %.3g x %.3g', Z),'FontWeight','bold')); + +O = mat\[0 0 0 1]'; O=O(1:3)'; +uicontrol(fg,'Style','Text','Position' ,[310 190 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Origin:'); +st.posinf.o = uicontrol(fg,'Style','Text','Position' ,[410 190 160 016].*WS,... + 'HorizontalAlignment','left', 'String', sprintf('%.3g %.3g %.3g', O),'FontWeight','bold'); + +R = spm_imatrix(mat); +R = spm_matrix([0 0 0 R(4:6)]); +R = R(1:3,1:3); + +uicontrol(fg,'Style','Text','Position' ,[310 170 100 016].*WS,... + 'HorizontalAlignment','right', 'String', 'Dir Cos:'); +tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(1,1:3)); tmp2(find(tmp2=='+')) = ' '; +st.posinf.m1 = uicontrol(fg,'Style','Text','Position' ,[410 170 160 016].*WS,... + 'HorizontalAlignment','left', 'String', tmp2,'FontWeight','bold'); +tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(2,1:3)); tmp2(find(tmp2=='+')) = ' '; +st.posinf.m2 = uicontrol(fg,'Style','Text','Position' ,[410 150 160 016].*WS,... + 'HorizontalAlignment','left', 'String', tmp2,'FontWeight','bold'); +tmp2 = sprintf('%+5.3f %+5.3f %+5.3f', R(3,1:3)); tmp2(find(tmp2=='+')) = ' '; +st.posinf.m3 = uicontrol(fg,'Style','Text','Position' ,[410 130 160 016].*WS,... + 'HorizontalAlignment','left', 'String', tmp2,'FontWeight','bold'); + +tmp = [[R zeros(3,1)] ; 0 0 0 1]*diag([Z 1])*spm_matrix(-O) - mat; +st.posinf.w = uicontrol(fg,'Style','Text','Position' ,[310 110 260 016].*WS,... + 'HorizontalAlignment','center', 'String', '','FontWeight','bold'); +if sum(tmp(:).^2)>1e-8, + set(st.posinf.w, 'String', 'Warning: shears involved'); +end; + +% Assorted other buttons. +%----------------------------------------------------------------------- +uicontrol(fg,'Style','Frame','Position',[310 30 270 70].*WS); +st.zoomer = uicontrol(fg,'Style','popupmenu' ,'Position',[315 75 125 20].*WS,... + 'String',str2mat('Full Volume','160x160x160mm','80x80x80mm','40x40x40mm','20x20x20mm','10x10x10mm'),... + 'Callback','myspm_image(''zoom_in'')','ToolTipString','zoom in by different amounts'); +c = 'if get(gco,''Value'')==1, spm_orthviews(''Space''), else, spm_orthviews(''Space'', 1);end;myspm_image(''zoom_in'')'; +uicontrol(fg,'Style','popupmenu' ,'Position',[315 55 125 20].*WS,... + 'String',str2mat('World Space','Voxel Space'),... + 'Callback',c,'ToolTipString','display in aquired/world orientation'); +c = 'if get(gco,''Value'')==1, spm_orthviews(''Xhairs'',''off''), else, spm_orthviews(''Xhairs'',''on''); end;'; +uicontrol(fg,'Style','togglebutton','Position',[450 75 125 20].*WS,... + 'String','Hide Crosshairs','Callback',c,'ToolTipString','show/hide crosshairs'); +uicontrol(fg,'Style','popupmenu' ,'Position',[450 55 125 20].*WS,... + 'String',str2mat('NN interp','bilin interp','sinc interp'),... + 'Callback','tmp_ = [0 1 -4];spm_orthviews(''Interp'',tmp_(get(gco,''Value'')))',... + 'Value',2,'ToolTipString','interpolation method for displaying images'); +st.win = uicontrol(fg,'Style','popupmenu','Position',[315 35 125 20].*WS,... + 'String',str2mat('Auto Window','Manual Window'),'Callback','myspm_image(''window'');','ToolTipString','range of voxel intensities displayed'); +% uicontrol(fg,'Style','pushbutton','Position',[315 35 125 20].*WS,... +% 'String','Window','Callback','myspm_image(''window'');','ToolTipString','range of voxel intensities % displayed'); +st.blobber = uicontrol(fg,'Style','pushbutton','Position',[450 35 125 20].*WS,... + 'String','Add Blobs','Callback','myspm_image(''addblobs'');','ToolTipString','superimpose activations'); +end; +return; + + +function my_reset +spm_orthviews('reset'); +spm_figure('Clear','Graphics'); +return; diff --git a/myspm_orthviews.m b/myspm_orthviews.m new file mode 100644 index 0000000..15af50e --- /dev/null +++ b/myspm_orthviews.m @@ -0,0 +1,1527 @@ +function varargout = spm_orthviews(action,varargin) +% Display Orthogonal Views of a Normalized Image +% FORMAT H = myspm_orthviews('Image',filename[,position]) +% filename - name of image to display +% area - position of image +% - area(1) - position x +% - area(2) - position y +% - area(3) - size x +% - area(4) - size y +% H - handle for ortho sections +% FORMAT myspm_orthviews('BB',bb) +% bb - bounding box +% [loX loY loZ +% hiX hiY hiZ] +% +% FORMAT myspm_orthviews('Redraw') +% Redraws the images +% +% FORMAT myspm_orthviews('Reposition',centre) +% centre - X, Y & Z coordinates of centre voxel +% +% FORMAT myspm_orthviews('Space'[,handle]) +% handle - the view to define the space by +% with no arguments - puts things into mm space +% +% FORMAT myspm_orthviews('MaxBB') +% sets the bounding box big enough display the whole of all images +% +% FORMAT myspm_orthviews('Resolution',res) +% res - resolution (mm) +% +% FORMAT myspm_orthviews('Delete', handle) +% handle - image number to delete +% +% FORMAT myspm_orthviews('Reset') +% clears the orthogonal views +% +% FORMAT myspm_orthviews('Pos') +% returns the co-ordinate of the crosshairs in millimetres in the +% standard space. +% +% FORMAT myspm_orthviews('Pos', i) +% returns the voxel co-ordinate of the crosshairs in the image in the +% ith orthogonal section. +% +% FORMAT myspm_orthviews('Xhairs','off') OR myspm_orthviews('Xhairs') +% disables the cross-hairs on the display. +% +% FORMAT myspm_orthviews('Xhairs','on') +% enables the cross-hairs. +% +% FORMAT myspm_orthviews('Interp',hld) +% sets the hold value to hld (see spm_slice_vol). +% +% FORMAT myspm_orthviews('AddBlobs',handle,XYZ,Z,mat) +% Adds blobs from a pointlist to the image specified by the handle(s). +% handle - image number to add blobs to +% XYZ - blob voxel locations (currently in millimeters) +% Z - blob voxel intensities +% mat - matrix from millimeters to voxels of blob. +% This method only adds one set of blobs, and displays them using a +% split colour table. +% +% myspm_orthviews('AddColouredBlobs',handle,XYZ,Z,mat,colour) +% Adds blobs from a pointlist to the image specified by the handle(s). +% handle - image number to add blobs to +% XYZ - blob voxel locations (currently in millimeters) +% Z - blob voxel intensities +% mat - matrix from millimeters to voxels of blob. +% colour - the 3 vector containing the colour that the blobs should be +% Several sets of blobs can be added in this way, and it uses full colour. +% Although it may not be particularly attractive on the screen, the colour +% blobs print well. +% +% myspm_orthviews('Register',hReg) +% See spm_XYZreg for more information. +% +% FORMAT myspm_orthviews('RemoveBlobs',handle) +% Removes all blobs from the image specified by the handle(s). +% +% myspm_orthviews('Register',hReg) +% hReg - Handle of HandleGraphics object to build registry in. +% See spm_XYZreg for more information. +% +% myspm_orthviews('AddContext',handle) +% handle - image number to add context menu to +% +% myspm_orthviews('RemoveContext',handle) +% handle - image number to remove context menu from +% +% CONTEXT MENU +% myspm_orthviews offers many of its features in a context menu, which is +% accessible via the right mouse button in each displayed image. +% +% PLUGINS +% The display capabilities of myspm_orthviews can be extended with +% plugins. These are located in the myspm_orthviews subdirectory of the SPM +% distribution. Currently there are 3 plugins available: +% quiver Add Quiver plots to a displayed image +% quiver3d Add 3D Quiver plots to a displayed image +% roi ROI creation and modification +% The functionality of plugins can be accessed via calls to +% myspm_orthviews('plugin_name', plugin_arguments). For detailed descriptions +% of each plugin see help myspm_orthviews/spm_ov_'plugin_name'. +% +%_______________________________________________________________________ +% @(#)myspm_orthviews.m 2.38 John Ashburner, Matthew Brett, Tom Nichols and Volkmar Glauche 03/04/17 + + +% The basic fields of st are: +% n - the number of images currently being displayed +% vols - a cell array containing the data on each of the +% displayed images. +% Space - a mapping between the displayed images and the +% mm space of each image. +% bb - the bounding box of the displayed images. +% centre - the current centre of the orthogonal views +% callback - a callback to be evaluated on a button-click. +% xhairs - crosshairs off/on +% hld - the interpolation method +% fig - the figure that everything is displayed in +% mode - the position/orientation of the sagittal view. +% - currently always 1 +% +% st.registry.hReg \_ See spm_XYZreg for documentation +% st.registry.hMe / +% +% For each of the displayed images, there is a non-empty entry in the +% vols cell array. Handles returned by "myspm_orthviews('Image',.....)" +% indicate the position in the cell array of the newly created ortho-view. +% Operations on each ortho-view require the handle to be passed. +% +% When a new image is displayed, the cell entry contains the information +% returned by spm_vol (type help spm_vol for more info). In addition, +% there are a few other fields, some of which I will document here: +% +% premul - a matrix to premultiply the .mat field by. Useful +% for re-orienting images. +% window - either 'auto' or an intensity range to display the +% image with. +% +% ax - a cell array containing an element for the three +% views. The fields of each element are handles for +% the axis, image and crosshairs. +% +% blobs - optional. Is there for using to superimpose blobs. +% vol - 3D array of image data +% mat - a mapping from vox-to-mm (see spm_vol, or +% help on image formats). +% max - maximum intensity for scaling to. If it +% does not exist, then images are auto-scaled. +% +% There are two colouring modes: full colour, and split +% colour. When using full colour, there should be a +% 'colour' field for each cell element. When using +% split colourscale, there is a handle for the colorbar +% axis. +% +% colour - if it exists it contains the +% red,green,blue that the blobs should be +% displayed in. +% cbar - handle for colorbar (for split colourscale). +% +% PLUGINS +% The plugin concept has been developed to extend the display capabilities +% of myspm_orthviews without the need to rewrite parts of it. Interaction +% between myspm_orthviews and plugins takes place +% a) at startup: The subfunction 'reset_st' looks for files with a name +% spm_ov_PLUGINNAME.m in the directory 'SWD/myspm_orthviews'. +% For each such file, PLUGINNAME will be added to the list +% st.plugins{:}. +% The subfunction 'add_context' calls each plugin with +% feval(['spm_ov_', st.plugins{k}], ... +% 'context_menu', i, parent_menu) +% Each plugin may add its own submenu to the context +% menu. +% b) at redraw: After images and blobs of st.vols{i} are drawn, the +% struct st.vols{i} is checked for field names that occur in +% the plugin list st.plugins{:}. For each matching entry, the +% corresponding plugin is called with the command 'redraw': +% feval(['spm_ov_', st.plugins{k}], ... +% 'redraw', i, TM0, TD, CM0, CD, SM0, SD); +% The values of TM0, TD, CM0, CD, SM0, SD are defined in the +% same way as in the redraw subfunction of myspm_orthviews. +% It is up to the plugin to do all necessary redraw +% operations for its display contents. Each displayed item +% must have set its property 'HitTest' to 'off' to let events +% go through to the underlying axis, which is responsible for +% callback handling. The order in which plugins are called is +% undefined. + +global st; + +if isempty(st), reset_st; end; + +spm('Pointer','watch'); + +if nargin == 0, action = ''; end; +action = lower(action); + +switch lower(action), +case 'image', + H = specify_image(varargin{1}); + if ~isempty(H) + st.vols{H}.area = [0 0 1 1]; + if length(varargin)>=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + redraw(H); + end; + varargout{1} = H; + +case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + +case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + +case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3, st.centre = tmp(:); end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + +case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + +case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + redraw_all; + else, + space(varargin{1}); + redraw_all; + end; + bbox; + +case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + +case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + +case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + +case 'delete', + my_delete(varargin{1}); + +case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + +case 'reset', + my_reset; + +case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + +case 'interp', + st.hld = varargin{1}; + redraw_all; + +case 'xhairs', + xhairs(varargin{1}); + +case 'register', + register(varargin{1}); + +case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + +case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + +case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + +case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + +case 'addtruecolourimage', + % myspm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_get(1, 'IMAGE', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + +case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + +case 'addcontext', + addcontexts(varargin{1}); + +case 'rmcontext', + rmcontexts(varargin{1}); + +case 'context_menu', + c_menu(varargin{:}); + +case 'set_pos2cm', + cm_pos(varargin{:}); + +otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + ax = axes('Parent',st.fig,'Position',[(axpos(1)+axpos(3)+0.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on'); + mx = max([eps max(t)]); + mn = min([0 min(t)]); + image([0 1],[mn mx],[1:64]' + 64,'Parent',ax); + set(ax,'YDir','normal','XTickLabel',[]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'cbar',ax,'max',mx, 'min',mn); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + ax = axes('Parent',st.fig,'Position',[(axpos(1)+axpos(3)+0.05) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on'); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + image([0 1],[mn mx],[1:64]' + 64,'Parent',ax); + set(ax,'YDir','normal','XTickLabel',[]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'cbar',ax,'max',mx); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + % axpos = get(st.vols{i}.ax{2}.ax,'Position'); + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',c); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'myspm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['myspm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),myspm_orthviews(''Reposition'');',... + 'myspm_orthviews(''set_pos2cm'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),myspm_orthviews(''Reposition'');',... + 'myspm_orthviews(''set_pos2cm'');',... + 'myspm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),myspm_orthviews(''Reposition'');',... + 'myspm_orthviews(''set_pos2cm'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),myspm_orthviews(''reposition'');',... + 'myspm_orthviews(''set_pos2cm'');',... + 'myspm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['myspm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(finite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(finite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(finite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(finite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (myspm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (myspm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (myspm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + if strcmp(st.vols{i}.window,'auto'), + mx = -Inf; mn = Inf; + if ~isempty(imgt), + mx = max([mx max(max(imgt))]); + mn = min([mn min(min(imgt))]); + end; + if ~isempty(imgc), + mx = max([mx max(max(imgc))]); + mn = min([mn min(min(imgc))]); + end; + if ~isempty(imgs), + mx = max([mx max(max(imgs))]); + mn = min([mn min(min(imgs))]); + end; + if mx==mn, mx=mn+eps; end; + else, + mx = st.vols{i}.window(2); + mn = st.vols{i}.window(1); + r=min([mn mx]);imgt = max(imgt,r); r=max([mn mx]);imgt = min(imgt,r); + r=min([mn mx]);imgc = max(imgc,r); r=max([mn mx]);imgc = min(imgc,r); + r=min([mn mx]);imgs = max(imgs,r); r=max([mn mx]);imgs = min(imgs,r); + end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(finite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(finite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(finite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + if size(cmap,1)~=128 + figure(st.fig) + spm_figure('Colormap','gray-hot') + end; + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + cmx=10; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,-cmx,cmx,actc,topc); + tmpc = scaletocmap(tmpc,-cmx,cmx,actc,topc); + tmps = scaletocmap(tmps,-cmx,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = (spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'+mn)/(mx-mn); + tmpc = (spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'+mn)/(mx-mn); + tmps = (spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'+mn)/(mx-mn); + tmpt(~finite(tmpt)) = 0; + tmpc(~finite(tmpc)) = 0; + tmps(~finite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + end; + + %cimgt(cimgt<0)=0; cimgt(cimgt>1)=1; + %cimgc(cimgc<0)=0; cimgc(cimgc>1)=1; + %cimgs(cimgs<0)=0; cimgs(cimgs>1)=1; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = [ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'myspm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('myspm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e v] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~finite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item0a = uimenu(item_parent,'UserData','pos_mm'); +item0b = uimenu(item_parent,'UserData','pos_vx'); +item0c = uimenu(item_parent,'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','myspm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','myspm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','myspm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','myspm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','myspm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','myspm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','myspm_orthviews(''context_menu'',''Xhair'',''on'');','Checked','on'); +item2_2 = uimenu(item2, 'Label','off', 'Callback','myspm_orthviews(''context_menu'',''Xhair'',''off'');'); + +%contextsubmenu 3 +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','myspm_orthviews(''context_menu'',''orientation'',2);'); +item3_2 = uimenu(item3, 'Label','Voxel space', 'Callback','myspm_orthviews(''context_menu'',''orientation'',1);','Checked','on'); + +%contextsubmenu 4 +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','myspm_orthviews(''context_menu'',''interpolation'',3);'); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','myspm_orthviews(''context_menu'',''interpolation'',2);','Checked','on'); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','myspm_orthviews(''context_menu'',''interpolation'',1);'); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','myspm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','myspm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','myspm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','myspm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','myspm_orthviews(''context_menu'',''window_gl'',1);'); +item6_2 = uimenu(item6, 'Label','Swap image', 'Callback','myspm_orthviews(''context_menu'',''swap_img'');'); + +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','myspm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','myspm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add colored blobs'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','myspm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','myspm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored image'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','myspm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','myspm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_4 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_5 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_5_1 = uimenu(item7_5, 'Label','local', 'Visible','on'); +item7_5_2 = uimenu(item7_5, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), +case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + +case 'xhair', + myspm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + +case 'orientation', + if varargin{2} == 2, + myspm_orthviews('Space'); + else, + myspm_orthviews('Space',1); + end; + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + +case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + +case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + myspm_orthviews('window',current_handle); + else + myspm_orthviews('window',current_handle,spm_input('Range','+1','e','',2)); + end; + +case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + data = spm_input('Range','+1','e','',2); + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + +case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_get(1,'IMAGE','select new image')); + st.vols{current_handle}.fname = new_info.fname; + st.vols{current_handle}.dim = new_info.dim; + st.vols{current_handle}.mat = new_info.mat; + st.vols{current_handle}.pinfo = new_info.pinfo; + st.vols{current_handle}.descrip = new_info.descrip; + redraw_all; + +case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','myspm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','myspm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + +case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + +case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',c_names{c},'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');myspm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',c_names{c},'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');myspm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + +case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + +case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_get(1,'IMAGE','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',c_names{c},'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');myspm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',c_names{c},'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');myspm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',myspm_orthviews('pos'))); + pos = myspm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = myspm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; diff --git a/mystats/T_pair.m b/mystats/T_pair.m new file mode 100644 index 0000000..a3ebfeb --- /dev/null +++ b/mystats/T_pair.m @@ -0,0 +1,129 @@ +function [] = T_pair(dat,tail,B) +%T_paired(dat,tail,B) produce p-values per la verifica dellipotesi di uguaglianza in +%media di due campioni appaiati. +% +%Parametri in ingresso: +% dat= matrice di dati +% tail direzine delle alternative (vettore 1 X numero di varibili) +% tail = 1, alternativa: "media1 > 0" +% tail = -1, alternativa: "media1 < 0." +% B = Numero permutazioni +% +%ATTENZIONE!!! disporre i dati in modo 'X-Y'; ovvero inserire la matrice delle differenze delle misurazioni tra il +% il tempo 1 e il tempo 2. +% +%By DEFALUT: tail=-1, B=1000; +% +% +%References: Pesarin, F.(2001) Multivariate Permutation Test with Application in Biostatistcs. Wiley, New York. +% +%Livio Finos, Dipartimento di Sci. Statistiche - Università di Padova. +%versione 2.0, 16 Marzo 2003. + + + ora=cputime; +if nargin == 1 + tail=-ones(1,size(dat,2)); + B=1000; +end + +[n n_var]=size(dat); + +% calcolo stat test per dati osservati +Tperm((B+1),:)= mean(dat) ./ (std(dat) ./ sqrt(n)); + + +% calcolo stat test per B permutazioni +for i=1:B + perm=repmat(2.*binornd(1,.5,n,1)-1,1,n_var); + Tperm(i,:)= mean(perm.*dat) ./ (std(perm.*dat) ./ sqrt(n)) ; +end +%Tperm +%cambio segni delle statistiche a seconda della direzione della ipotesi alternativa in modo che a +%valori alti della stat test corrispondano p-value bassi (significativi). + +for i=1:n_var + if tail(i)==0 + Tperm(:,i)=abs(Tperm(:,i)); + else + Tperm(:,i)=Tperm(:,i).*tail(i); + end +end + + + +%[NULL Index]=sort(Tperm,1); +%for j=1:n_var +% rango(Index(:,j),j)=((B+1):-1:1)'; +%end +%clear NULL Index; +% +% +%decommentare le precedenti righe e commentare le successive 5 per ottenere un algoritmo più veloce (e corretto) +%ma meno buono nel caso di valori (nei dati di origine) ripetuti, sempre buono per dati continui +%(o con buona approssimazione al continuo). + +%calcolo del p-value per ogni valore della matrice di statistiche test Tperm (B+1)Xn_var. +for i=1:B+1 + for j=1:n_var + rango(i,j)=sum(Tperm(i,j)<=Tperm(:,j)); + end +end + + +rango=rango/(B+1); + + +%calcolo dei valori delle funzioni di combinazione. + + TpermTipp= max(1-rango,[],2); + TpermFish= -2*(sum(log(rango),2)); + Ninv=norminv(1-rango); + TpermLipt= sum(Ninv,2); + + +%calcolo del p-value dei test combinati +rangoFish=sum(TpermFish(B+1)<=TpermFish)/(B+1); +rangoTipp=sum(TpermTipp(B+1)<=TpermTipp)/(B+1); +rangoLipt=sum(TpermLipt(B+1)<=TpermLipt)/(B+1); + + +%output. + time=cputime-ora; + fprintf('\n Numerosità del campione: %3.0f ', n); + fprintf('\n \n'); + + fprintf(' Direzione delle ipotesi alternative \n \t'); + for var=1:n_var + fprintf('var %3.0f \t',var); + end + fprintf('\n \t'); + for var=1:n_var + fprintf('%3.0f \t \t',tail(var)); + end + fprintf('\n \n'); + + fprintf(' Numero Permutazioni= %3.0f. \t Tempo: %3.2f. \n \n',B,time); + + + fprintf(' p-values parziali \n'); + for var=1:n_var + fprintf('\t var %3.0f ',var); + end + fprintf('\n \t'); + + for var=1:n_var + fprintf(' %3.4f \t',rango(B+1,var)); + end + fprintf('\n'); + + fprintf('\n \n p-value Globale \n'); + + fprintf('\t FISHER \t \t %3.4f \n',rangoFish); + fprintf('\t TIPPETT \t \t %3.4f \n',rangoTipp); + fprintf('\t LIPTAK \t \t %3.4f \n ',rangoLipt); + fprintf('\n \n \n \n'); + + + +%pval=[rango(B+1,:) rangoFish rangoTipp rangoLipt]; \ No newline at end of file diff --git a/mystats/anova-a.m b/mystats/anova-a.m new file mode 100644 index 0000000..46c13de --- /dev/null +++ b/mystats/anova-a.m @@ -0,0 +1,102 @@ +function [pval, f, df_b, df_w] = anova (y, g) +% ANOVA One-way analysis of variance (ANOVA) +% Performs a one-way analysis of variance (ANOVA). The goal is to test +% whether the population means of data taken from k different groups +% are all equal. +% +% anova (y, g) provides all data in a single vector y; g is the vector +% of corresponding group labels (e.g., numbers from 1 to k). This is +% the general form which does not impose any restriction on the number +% of data in each group or the group labels (other than that they must +% be scalars). +% +% anova (y), where y is a matrix, treats each column as a group. This +% form is only appropriate for balanced ANOVA where the numbers of +% samples from each group are all equal. +% +% Under the null of constant means, the statistic f follows an F +% distribution with df_b and df_w degrees of freedom. pval is the +% p-value (1 minus the CDF of this distribution at f) of the test. +% +% If no output argument is given, the standard one-way ANOVA table is +% printed. + + +if ((nargin < 1) | (nargin > 2)) + error('USE anova (y [, g])'); + return +elseif (nargin == 1) + if ndims(y)==1 + error('anova: for anova (y), y must be a matrix'); + return + end + [group_count, k] = size(y); + n = group_count * k; + group_mean = mean(y); +else + if ~isvector(y) % ndims(y) ~= 1 + error('anova: for anova(y, g), y must be a vector'); + end + n = length(y); + if (~isvector(g) | (length(g) ~= n)) % (ndims(g) ~= 1 | (length(g) ~= n)) + error(['anova: for anova (y, g), g must be a vector of the same length y']); + end + group_label = sort(unique(g)); + + if (length(group_label) == 1) + error('anova: there should be at least 2 groups'); + return + end + for i = 1:length(group_label); + v = y(find(g == group_label(i))); + group_count(i) = length(v); + if i>1 + if group_count(i) ~= group_count(i-1) + error('anova: all groups should have the same number of observations'); + end + end + group_mean(i) = mean(v); + end +end +% moyenne de l'échantillon +total_mean = mean(group_mean); % OK car tous les grp ont meme nb d'obs +%total_mean = sum(group_count.*group_mean)/sum(group_count); + +%Variance Expliquée par la partition (inter-groupe) +SSB = sum(group_count .*(group_mean - total_mean) .^ 2); +%VARIANCE TOTALE: +SST = sum((reshape(y, n, 1) - total_mean).^2); +% Variance résiduelle (intra groupe) +SSW = SST - SSB; +%Deg de lib inter, intra +df_b = k - 1; +df_w = n - k; +%Var inter, intra +v_b = SSB / df_b; +v_w = SSW / df_w; + +f = v_b / v_w; + +pval = 1 - cdf('f', f, df_b, df_w); + +if (nargout == 0) + %% This eventually needs to be done more cleanly ... + disp(sprintf('\n')); + disp(sprintf('One-way ANOVA Table:\n')); + disp(sprintf('\n')); + disp(sprintf('Means:')); + disp(sprintf('Group %d: %3.4f (std:%3.4f)\n', [[1:k]; group_mean; std(y)])); + disp(sprintf('Difference of group %d with grandmean: %3.4f\n', [[1:k]; mean(group_mean)-group_mean])); + disp(sprintf('Source of Variation Sum of Squares df Empirical Var\n')); + disp(sprintf('*********************************************************\n')); + disp(sprintf('Between Groups %15.4f %4d %13.4f\n', SSB, df_b, v_b)); + disp(sprintf('Within Groups %15.4f %4d %13.4f\n', SSW, df_w, v_w)); + disp(sprintf('---------------------------------------------------------\n')); + disp(sprintf('Total %15.4f %4d\n', SST, n - 1)); + disp(sprintf('\n')); + disp(sprintf('Test Statistic F(%d,%d)=%15.4f\n', df_b,df_w,f)); + disp(sprintf('p-value p=%15.4f\n', pval)); + disp(sprintf('\n')); +end + + diff --git a/mystats/anova.m b/mystats/anova.m new file mode 100644 index 0000000..0a3249b --- /dev/null +++ b/mystats/anova.m @@ -0,0 +1,626 @@ +function [summary,para,resid] = anova(voie,Y,G,R,int,varargin) +%ANOVA one-way and two-way analysis of variance (ANOVA). +% [summary,para,resid] = anova(voie,Y,G,R,int) +% DO NOT USE FOR WITHIN SUBJECT EFFECTS!!! + +% +% If G isempty (or not specified) columns of Y make each group. No +% repetition is assumed. +% If G is given, Y should be a N*Kvector of length N*R and G a N-by-K matrix +% where the K columns specify the groups. +% R is the repetition factor. + + +% ANOVA calls ANOVA1 in case of one-way and +% ANOVA2 in case of two-way layout. +% +% ANOVA1 and ANOVA2 are from the matlab6 version, to have callbacks +if nargin<3 + G=[]; +end +if nargin<4 + R=1; +end +if nargin<5 + int=1; +end + +if (voie==1) + [p,summary,stats] = anova1(Y',G,'off'); + summary{2,1}='Rows'; + para.mu=mean(mean(Y')); + para.alpha=stats.means-para.mu; +% resid=Y-repmat(stats.means',1,R); +resid=NaN; +else + + if isvector(Y) + [sg,sidx]=sortrows(G); + ng1=length(unique(sg(:,1))); + ng2=length(unique(sg(:,2))); + R=size(G,1)/ng1/ng2; + Y=Y(sidx); + Y=reshape(Y, ng1, ng2*R)'; + n=ng1; + m=ng2*R; + else + if ndims(Y)<=3 + Y=Y(:,:); + else + error('Trop de dim!') + end + [n,m]=size(Y); + end + [p,summary,stats] = anova2(Y',R,'off'); + summary{2,1}='Rows'; + summary{3,1}='Columns'; + para.mu=mean(mean(Y')); + para.alpha=stats.colmeans-para.mu; + para.beta=stats.rowmeans-para.mu; + betainter=repmat(para.beta',1,R)'; + alphaplusbeta=repmat(para.alpha',1,m)+repmat(betainter(:)',n,1); + if ~(int) % no interaction + if (R>1) + % Summation of SC_ab+SC_e + summary{5,2}=summary{5,2}+summary{4,2}; + summary{5,3}=summary{5,3}+summary{4,3}; + summary{5,4}=summary{5,2}/summary{5,3}; + summary{2,5}=summary{2,4}/summary{5,4}; + summary{3,5}=summary{3,4}/summary{5,4}; + summary{2,6}=1-f_cdf(summary{2,5},summary{2,3},summary{5,3}); + summary{3,6}=1-f_cdf(summary{3,5},summary{3,3},summary{5,3}); + summary(4,:)=[]; + end; + resid=Y-alphaplusbeta-para.mu; + else + inter=mean(reshape(Y',R,m*n/R)); + para.alphabeta=reshape(inter,m/R,n)'-repmat(para.alpha',1,m/R) ... + -repmat(para.beta,n,1)-para.mu; + resid=Y-reshape(repmat(inter,R,1),m,n)'; + end; +end; + + +function [p,anovatab,stats] = anova1(x,group,displayopt,extra) +%ANOVA1 One-way analysis of variance (ANOVA). +% ANOVA1 performs a one-way ANOVA for comparing the means of two or more +% groups of data. It returns the p-value for the null hypothesis that the +% means of the groups are equal. +% +% P = ANOVA1(X,GROUP,DISPLAYOPT) +% If X is a matrix, ANOVA1 treats each column as a separate group, and +% determines whether the population means of the columns are equal. +% This form of ANOVA1 is appropriate when each group has the same +% number of elements (balanced ANOVA). GROUP can be a character +% array or a cell array of strings, with one row per column of +% X, containing the group names. Enter an empty array ([]) or +% omit this argument if you do not want to specify group names. +% If X is a vector, GROUP must be a vector of the same length, or a +% string array or cell array of strings with one row for each +% element of X. X values corresponding to the same value of +% GROUP are placed in the same group. +% +% DISPLAYOPT can be 'on' (the default) to display figures +% containing a standard one-way anova table and a boxplot, or +% 'off' to omit these displays. +% +% [P,ANOVATAB] = ANOVA1(...) returns the ANOVA table values as the +% cell array ANOVATAB. +% +% [P,ANOVATAB,STATS] = ANOVA1(...) returns an additional structure +% of statistics useful for performing a multiple comparison of means +% with the MULTCOMPARE function. +% +% See also ANOVA2, ANOVAN, BOXPLOT, MANOVA1, MULTCOMPARE. + +% Reference: Robert V. Hogg, and Johannes Ledolter, Engineering Statistics +% Macmillan 1987 pp. 205-206. +classical = 1; +nargs = nargin; +if (nargin>0 & strcmp(x,'kruskalwallis')) + % Called via kruskalwallis function, adjust inputs + classical = 0; + if (nargin >= 2), x = group; group = []; end + if (nargin >= 3), group = displayopt; displayopt = []; end + if (nargin >= 4), displayopt = extra; end + nargs = nargs-1; +end + +error(nargchk(1,3,nargs)); + +if (nargs < 2), group = []; end +if (nargs < 3), displayopt = 'on'; end +% Note: for backwards compatibility, accept 'nodisplay' for 'off' +willdisplay = ~(strcmp(displayopt,'nodisplay') | strcmp(displayopt,'n') ... + | strcmp(displayopt,'off')); + +% Convert group to cell array from character array, make it a column +if (ischar(group) & ~isempty(group)), group = cellstr(group); end +if (size(group, 1) == 1), group = group'; end + +% If X is a matrix with NaNs, convert to vector form. +if (length(x) < prod(size(x))) + if (any(isnan(x(:)))) + [n,m] = size(x); + x = x(:); + gi = reshape(repmat((1:m), n, 1), n*m, 1); + if (length(group) == 0) % no group names + group = gi; + elseif (size(group,1) == m) + group = group(gi,:); + else + error('X and GROUP must have the same length.'); + end + end +end + +% If X is a matrix and GROUP is strings, use GROUPs as names +if (iscell(group) & (length(x) < prod(size(x))) ... + & (size(x,2) == size(group,1))) + named = 1; + gnames = group; + grouped = 0; +else + named = 0; + gnames = []; + grouped = (length(group) > 0); +end + +if (grouped) + % Single data vector and a separate grouping variable + x = x(:); + lx = length(x); + if (lx ~= prod(size(x))) + error('First argument has to be a vector.') + end + nonan = ~isnan(x); + x = x(nonan); + + % Convert group to indices 1,...,g and separate names + group = group(nonan,:); + [groupnum, gnames] = grp2idx(group); + named = 1; + + % Remove NaN values + nonan = ~isnan(groupnum); + if (~all(nonan)) + groupnum = groupnum(nonan); + x = x(nonan); + end + + lx = length(x); + xorig = x; % use uncentered version to make M + groupnum = groupnum(:); + maxi = size(gnames, 1); + xm = zeros(1,maxi); + countx = xm; + if (willdisplay), M = []; end + if (classical) + mu = mean(x); + x = x - mu; % center to improve accuracy + xr = x; + else + [xr,tieadj] = tiedrank(x); + end + + for j = 1:maxi + % Get group sizes and means + k = find(groupnum == j); + lk = length(k); + countx(j) = lk; + xm(j) = mean(xr(k)); % column means + + if (willdisplay) % create matrix for boxplot + [r, c] = size(M); + if lk > r + tmp = NaN; + M(r+1:lk,:) = tmp(ones(lk - r,c)); + tmp = xorig(k); + M = [M tmp]; + else + tmp = xorig(k); + tmp1 = NaN; + tmp((lk + 1):r,1) = tmp1(ones(r - lk,1)); + M = [M tmp]; + end + end + + end + + gm = mean(xr); % grand mean + df1 = length(xm) - 1; % Column degrees of freedom + df2 = lx - df1 - 1; % Error degrees of freedom + RSS = countx .* (xm - gm)*(xm-gm)'; % Regression Sum of Squares +else + % Data in matrix form, no separate grouping variable + [r,c] = size(x); + lx = r * c; + if (classical) + xr = x; + mu = mean(xr(:)); + xr = xr - mu; % center to improve accuracy + else + [xr,tieadj] = tiedrank(x(:)); + xr = reshape(xr, size(x)); + end + countx = repmat(r, 1, c); + xorig = x; % save uncentered version for boxplot + xm = mean(xr); % column means + gm = mean(xm); % grand mean + df1 = c-1; % Column degrees of freedom + df2 = c*(r-1); % Error degrees of freedom + RSS = r*(xm - gm)*(xm-gm)'; % Regression Sum of Squares +end + +TSS = (xr(:) - gm)'*(xr(:) - gm); % Total Sum of Squares +SSE = TSS - RSS; % Error Sum of Squares + +if (df2 > 0) + mse = SSE/df2; +else + mse = NaN; +end + +if (classical) + if (SSE~=0) + F = (RSS/df1) / mse; + p = 1 - f_cdf(F,df1,df2); % Probability of F given equal means. + elseif (RSS==0) % Constant Matrix case. + F = 0; + p = 1; + else % Perfect fit case. + F = Inf; + p = 0; + end +else + F = (12 * RSS) / (lx * (lx+1)); + if (tieadj > 0) + F = F / (1 - 2 * tieadj/(lx^3-lx)); + end + p = 1 - chi2cdf(F, df1); +end + + +Table=zeros(3,5); %Formatting for ANOVA Table printout +Table(:,1)=[ RSS SSE TSS]'; +Table(:,2)=[df1 df2 df1+df2]'; +Table(:,3)=[ RSS/df1 mse Inf ]'; +Table(:,4)=[ F Inf Inf ]'; +Table(:,5)=[ p Inf Inf ]'; + +colheads = ['Source ';' SS ';' df ';... + ' MS ';' F ';' Prob>F ']; +if (~classical) + colheads(5,:) = ' Chi-sq '; + colheads(6,:) = ' Prob>Chi-sq'; +end +rowheads = ['Columns ';'Error ';'Total ']; +if (grouped) + rowheads(1,:) = 'Groups '; +end + +% Create cell array version of table +atab = num2cell(Table); +for i=1:size(atab,1) + for j=1:size(atab,2) + if (isinf(atab{i,j})) + atab{i,j} = []; + end + end +end +atab = [cellstr(strjust(rowheads, 'left')), atab]; +atab = [cellstr(strjust(colheads, 'left'))'; atab]; +if (nargout > 1) + anovatab = atab; +end + +% Create output stats structure if requested, used by MULTCOMPARE +if (nargout > 2) + if (length(gnames) > 0) + stats.gnames = gnames; + else + stats.gnames = strjust(num2str((1:length(xm))'),'left'); + end + stats.n = countx; + if (classical) + stats.source = 'anova1'; + stats.means = xm + mu; + stats.df = df2; + stats.s = sqrt(mse); + else + stats.source = 'kruskalwallis'; + stats.meanranks = xm; + stats.sumt = 2 * tieadj; + end +end + +if (~willdisplay), return; end + +digits = [-1 -1 0 -1 2 4]; +if (classical) + wtitle = 'One-way ANOVA'; + ttitle = 'ANOVA Table'; +else + wtitle = 'Kruskal-Wallis One-way ANOVA'; + ttitle = 'Kruskal-Wallis ANOVA Table'; +end +statdisptable(atab, wtitle, ttitle, '', digits); + +fig2 = figure('pos',get(gcf,'pos') + [0,-200,0,0]); + +if (~grouped) + boxplot(xorig,1); +else + boxplot(M,1); + h = get(gca,'XLabel'); + set(h,'String','Group Number'); +end + +% If there are group names, use them after removing blanks +if (length(gnames) > 0) + gnames = strrep(gnames, '|', '_'); + gstr = gnames{1}; + for j=2:size(gnames,1) + gstr = [gstr, '|', gnames{j}]; + end + h = get(gca,'XLabel'); + if (named) + set(h,'String',''); + end + set(gca, 'xtick', (1:df1+1), 'xticklabel', gstr); +end + + + +function [p,Table,stats] = anova2(X,reps,displayopt) +%ANOVA2 Two-way analysis of variance. +% ANOVA2(X,REPS,DISPLAYOPT) performs a balanced two-way ANOVA for +% comparing the means of two or more columns and two or more rows of the +% sample in X. The data in different columns represent changes in one +% factor. The data in different rows represent changes in the other +% factor. If there is more than one observation per row-column pair, then +% then the argument REPS indicates the number of observations per "cell". +% A cell contains REPS number of rows. DISPLAYOPT can be 'on' (the +% default) to display the table, or 'off' to skip the display. +% +% For example, if REPS = 3, then each cell contains 3 rows and the total +% number of rows must be a multiple of 3. If X has 12 rows, and REPS = 3, +% then the "row" factor has 4 levels (3*4 = 12). The second level of the +% row factor goes from rows 4 to 6. +% +% [P,TABLE] = ANOVA2(...) returns two items. P is a vector of p-values +% for testing row, column, and if possible interaction effects. TABLE +% is a cell array containing the contents of the anova table. +% +% To perform unbalanced two-way ANOVA, use ANOVAN. +% +% See also ANOVA1, ANOVAN. + +% Reference: Robert V. Hogg, and Johannes Ledolter, Engineering Statistics +% Macmillan 1987 pp. 227-231. + +if (nargin<3), displayopt = 'on'; end +if (nargin < 1), error('At least one input is required.'); end +if (any(isnan(X(:)))) + error('NaN values in input not allowed. Use anovan instead.'); +end +[r,c] = size(X); +if nargin == 1, + reps = 1; + m=r; + Y = X; +elseif reps == 1 + m=r; + Y = X; +else + m = r/reps; + if (floor(m) ~= r/reps), + error('The number of rows must be a multiple of reps.'); + end + Y = zeros(m,c); + for i=1:m, + j = (i-1)*reps; + Y(i,:) = mean(X(j+1:j+reps,:)); + end +end +colmean = mean(Y); % column means +rowmean = mean(Y'); % row means +gm = mean(colmean); % grand mean +df1 = c-1; % Column degrees of freedom +df2 = m-1; % Row degrees of freedom +if reps == 1, + edf = (c-1)*(r-1);% Error degrees of freedom. No replication. This assumes an additive model. +else + edf = (c*m*(reps-1)); % Error degrees of freedom with replicates + idf = (c-1)*(m-1); % Interaction degrees of freedom +end +CSS = m*reps*(colmean - gm)*(colmean-gm)'; % Column Sum of Squares +RSS = c*reps*(rowmean - gm)*(rowmean-gm)'; % Row Sum of Squares +correction = (c*m*reps)*gm^2; +TSS = sum(sum(X .* X)) - correction; % Total Sum of Squares +ISS = reps*sum(sum(Y .* Y)) - correction - CSS - RSS; % Interaction Sum of Squares +if reps == 1, + SSE = ISS; +else + SSE = TSS - CSS - RSS - ISS; % Error Sum of Squares +end + +ip = NaN; +if (SSE~=0) + MSE = SSE/edf; + colf = (CSS/df1) / MSE; + rowf = (RSS/df2) / MSE; + colp = 1 - f_cdf(colf,df1,edf); % Probability of F given equal column means. + rowp = 1 - f_cdf(rowf,df2,edf); % Probability of F given equal row means. + p = [colp rowp]; + + if (reps > 1), + intf = (ISS/idf)/MSE; + ip = 1 - f_cdf(intf,idf,edf); + p = [p ip]; + end + +else % Dealing with special cases around no error. + if (edf > 0) + MSE = 0; + else + MSE = NaN; + end + if CSS==0, % No between column variability. + colf = 0; + colp = 1; + else % Between column variability. + colf = Inf; + colp = 0; + end + + if RSS==0, % No between row variability. + rowf = 0; + rowp = 1; + else % Between row variability. + rowf = Inf; + rowp = 0; + end + + p = [colp rowp]; + + if (reps>1) & (ISS==0) % Replication but no interactions. + intf = 0; + p = [p 1]; + elseif (reps>1) % Replication with interactions. + intf = Inf; + p = [p 0]; + end +end + +if (reps > 1), + Table{6,6} = []; %Formatting for ANOVA Table printout with interactions. + Table(2:6,1)={'Columns';'Rows';'Interaction';'Error';'Total'}; + Table(2:6,2)={CSS; RSS; ISS; SSE; TSS}; + Table(2:6,3)={df1; df2; idf; edf; r*c-1}; + Table(2:5,4)={CSS/df1; RSS/df2; ISS/idf; SSE/edf;}; + Table(2:4,5)={colf; rowf; intf}; +else + Table{5,6} = []; %Formatting for ANOVA Table printout no interactions. + Table(2:5,1)={'Columns';'Rows';'Error';'Total'}; + Table(2:5,2)={CSS; RSS; SSE; TSS}; + Table(2:5,3)={df1; df2; edf; r*c-1}; + Table(2:4,4)={CSS/df1; RSS/df2; SSE/edf;}; + Table(2:3,5)={colf; rowf}; +end + +Table(1,1:6) = {'Source' 'SS' 'df' 'MS' 'F' 'Prob>F'}; +Table(2:(1+length(p)),6) = num2cell(p); + +if (isequal(displayopt, 'on')) + digits = [-1 -1 0 -1 2 4]; + statdisptable(Table, 'Two-way ANOVA', 'ANOVA Table', '', digits); +end + +if (nargout > 2) + stats.source = 'anova2'; + stats.sigmasq = MSE; + stats.colmeans = colmean; % mean of columns + stats.coln = m*reps; % n for estimating column means + stats.rowmeans = rowmean; + stats.rown = c*reps; + stats.inter = (reps>1); % was an interaction term included? + stats.pval = ip; % p-value for interactions + stats.df = edf; +end + + + +return + + +function [g,gn] = grp2idx(s) +% GRP2IDX Create index vector from a grouping variable. +% [G,GN]=GRP2IDX(S) creates an index vector G from the grouping +% variable S. S can be a numeric vector, a character matrix (each +% row representing a group name), or a cell array of strings stored +% as a column vector. The result G is a vector taking integer +% values from 1 up to the number of unique entries in S. GN is a +% cell array of names, so that GN(G) reproduces S (aside from any +% differences in type). + +% Copyright 1993-2002 The MathWorks, Inc. +% $Revision: 1.4 $ $Date: 2002/03/13 23:20:16 $ + +if (ischar(s)) + s = cellstr(s); +end +if (size(s, 1) == 1) + s = s'; +end + +[gn,i,g] = uniquep(s); % b=unique group names + +ii = find(strcmp(gn, '')); +if (length(ii) == 0) + ii = find(strcmp(gn, 'NaN')); +end + +if (length(ii) > 0) + nangrp = ii(1); % this group should really be NaN + gn(nangrp,:) = []; % remove it from the names array + g(g==nangrp) = NaN; % set NaN into the group number array + g = g - (g > nangrp); % re-number remaining groups +end + +% ----------------------------------------------------------- +function [b,i,j] = uniquep(s) +% Same as UNIQUE but orders result: +% if iscell(s), preserve original order +% otherwise use numeric order + +[b,i,j] = unique(s); % b=unique group names + +nb = size(b,1); +i = zeros(nb,1); +if (iscell(s)) + % Restore in original order + for k=1:size(b,1) + ii = find(strcmp(s, b(k))); + i(k) = ii(1); % find first instance of each element of b + end + isort = i; % sort based on this order +else + % If b is a vector, put in numeric order + for k=1:size(b,1) + ii = find(s == b(k)); + if (length(ii) > 0) + i(k) = ii(1); % make sure this is the first instance + end + end + + % Fix up bad treatment of NaN + if (any(isnan(b))) % remove multiple NaNs; put one at the end + nans = isnan(b); + b = [b(~nans); NaN]; + x = find(isnan(s)); + i = [i(~nans); x(1)]; + j(isnan(s)) = length(b); + end + + isort = b; % sort based on numeric values + isort(isnan(isort)) = max(isort) + 1; +end + +[is, f] = sort(isort); % sort according to the right criterion +b = b(f,:); + +[fs, ff] = sort(f); % rearrange j also +j = ff(j); + +if (~iscell(b)) % make sure b is a cell array of strings + b = cellstr(strjust(num2str(b), 'left')); +end +return + + +Y=[ 7.56 9.68 11.65; + 9.98 9.69 10.69; + 7.23 10.49 11.77; + 8.22 8.55 10.72; + 7.59 8.30 12.36]; diff --git a/mystats/kurtosis.m b/mystats/kurtosis.m new file mode 100644 index 0000000..134900b --- /dev/null +++ b/mystats/kurtosis.m @@ -0,0 +1,19 @@ +function [S]=kurtosis(X) +% kurtosis - computes sample kurtosis of a distribution +% [S]=kurtosis(X) computes row-wise kurtosis +% The unbiased Fisher's equation for finite samples, a.k.a, G2 is used. +% Note: +% Positive kurtosis reflects sharp distribution. +% Standard Error of kurtosis for normal distribution is ~ sqrt(24/n) + +if isvector(X) + X=X(:); +end +sz=[size(X) 1 ]; +n=sz(1); +if n<4 + error('Kurtosis needs sample of size > 3') +end +S=sum((X-repmat(mean(X),n,1)).^4); +S=S./(var(X).^2); +S=(n*(n+1)/(n-1)/(n-2)/(n-3)).*S - 3*(n-1).^2/(n-2)/(n-3); diff --git a/mystats/myanova.1.m b/mystats/myanova.1.m new file mode 100644 index 0000000..984c22d --- /dev/null +++ b/mystats/myanova.1.m @@ -0,0 +1,679 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,SStype) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt,peta2]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% epsilon: sphericity correction if applicable +% pomega2: partial omega squared (unbiased estimator of effect size) +% df: degrees of freedom for each effect +% dfe: degrees of freedom of error for each effect +% SS: sum of squares for each effect +% SSe: sum of squares of error for each effect +% SSt: Total sum of squares +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% Default: epsilon=1 +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% See also: myanovaeffects, + +% +% peta2: (biased) percentage of explained variance by each factor +% omega2: (unbiased) percentage of explained variance by each factor + +% Requires: f_cdf() + +SS=[]; +SSb=[]; +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +if nargin<3 + rp=[]; +end +if nargin<4 + epsilon=1; +end +if nargin<5 + SStype=[]; +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Number of groups for each factor +ng=sX(1:nf); +% Number of groups +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +% Number of cells +pnc=prod(ng); +%Number of observations +pno=pnc*nr; +% Dimensions of (pseudo multivariate) dependent variables +svar=[sX(nf+2:end)]; + +% if ~isempty(rp) & ~all(ismember(1:nf,rp)) +% error('Mixed designs (split plot) ANOVA unavailable!') +% end +% if ~isempty(rp) & nf>2 +% error('Repeated measure ANOVA is only available for 2 factor designs!') +% end + +% Sphericity checking +if isnan(epsilon) % | ischar(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% Number of groups in between subjects +pngb=1; +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + pngb=prod(ng(~rp)); + png=png/pngb; + % Factors within first, between next + fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +end +if isempty(SStype) + if isempty(rp) + SStype=3; + error('I dunno which SS type to choose...'); + elseif all(rp) + SStype=2; + else + error('I dunno which SS type to choose...'); + end +end +% Within Group/Error stats +% i.e unmodeled error +mXe=mean(X,nf+1); +SSe=X-repmat(mXe,[ones(1,nf) nr 1]); +SSe=reshape(SSe, [pnc nr svar]).^2; +SSe=sum(sum(SSe)); +if (nr<=1) + error('myanova doesn''t work with 1 subject / group!') +end +dfe=png*(nr-1); +MSe=squeeze(SSe/dfe); +dfe=repmat(dfe, [nfx 1]); + +% Population stats +dft=(pno)-1; +mX=reshape(mXe,pnc,[svar]); +mX=mean(mX,1); + +if any(rp) + % Between-Subject Error (to account for repeated measurements) + mXr=permute(X, [nf+1 fxw nf+2:nX]); + mXr=reshape(mXr,nr,png,pngb,[]); + mXr=mean(mXr,2); + sz=sX; + sz(rp)=1; + mXr=reshape(mXr,sz); + SSr=sum(png*sum((reshape(mXr,[nr pngb svar]) - repmat(mX,[nr pngb 1])).^2)); + dfr=nr*pngb-1; + % + % mXb=permute(X, [nf+1 fxw nf+2:nX]); + % mXb=reshape(mXb,nr*png,pngb,[svar]); + % mXb=mean(mXb,2); + % SSb = sum(pngb*sum((reshape(mXb,[nr png svar]) - repmat(mX,[nr png 1])).^2)); + % + % mXb=permute(X, [nf+1 fxw nf+2:nX]); + % mXb=reshape(mXb,nr*png,pngb,[svar]); + % mXb=mean(mXb); + % SSb = sum(nr*png*sum((reshape(mXb,[pngb svar]) - repmat(mX,[pngb 1])).^2)); + % + % + % mXb=permute(X, [nf+1 fxw nf+2:nX]); + % mXb=reshape(mXb,nr,png,pngb,[]); + % mXr=mean(mXr,2); + % sz=sX; + % sz(rp)=1; + % mXr=reshape(mXr,sz); + + % SSe=SSe- + +end + +% Outputs are: +% [p,F,fx,1:epsilon,2:pomega2,3:df,4:dfe,5:SS,6:SSe,7:SSt,8:peta2]=... +if nargout >= 3+1 + varargout{1}=epsilon; +end +if nargout >= 3+2 + SSt=sum((reshape(X,pno, [])-repmat(mX,[pno 1])).^2); +end + +df=zeros(nfx,1); +SS=zeros([nfx svar]); +F=zeros([nfx svar]); +p=zeros([nfx svar]); +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + df(i)=prod(ng(j)-1); + mXb=permute(mXe, [j setdiff(1:nf,j) nf+1:nX]); + % Number of levels for this factor + nl=prod(ng(j)); + mXb=reshape(mXb,nl,pnc/nl,[svar]); + mXb=mean(mXb,2); + SS(i,:) = pno/nl *sum((reshape(mXb, [nl svar]) - repmat(mX,[nl 1])).^2); +% SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + + + if length(j)>1 + % Interactions: + % we need to x remove single factor variance from the Sum of Squares + for k=1:i-1 + if all(ismember(fx{k}, j)) + SS(i,:)=SS(i,:)-SS(k,:); + end + end + end + MS=SS(i,:)./df(i); + + % Now corrects Error term to account for repeated measurements + if any(rp(j)) + if length(j)==1 + dfe(i)=(nr-1)*df(i); + mXer=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXer=reshape(mXer,nr*nl,png/nl,[svar]); + mXer=mean(mXer,2); + SSe(i,:)=png/nl*sum((reshape(mXer, nr*nl, []) - repmat(mX,[nr*nl pngb 1])).^2); + SSe(i,:)=SSe(i,:)-SSr-SS(i,:); + %SSbe(i,:)=SSe; + else + % Interaction effects residuals + % + % WARNING !!!! + % + % the following does NOT work for more-than-2-factors design! + % + dfe(i)=(png-sum(ng-1)-1)*(nr-1); + mXer=reshape(X,pno,[]); + SSe(i,:)=sum((mXer - repmat(mX,[nr*png 1])).^2); + SSe(i,:)=SSe(i,:)-SSr-sum(SSe(1:nf,:))-sum(SS(1:nfx,:)); + end + MSe=squeeze(SSe(i,:)./dfe(i)); + end + % Apply d.f. correction if needed + df(i)=df(i).*epsilon(i,:); + dfe(i)=dfe(i).*epsilon(i,:); + % Compute F-value and gets the probability + F(i,:)=squeeze(MS)./MSe; + p(i,:)=1-f_cdf(F(i,:),df(i),dfe(i)); + % Outputs (if requested) are: + % [p,F,fx,1:epsilon,2:pomega2,3:df,4:dfe,5:SS,6:SSe,7:SSt,8:peta2]=... + if nargout >= 3+2 %3+6 + % We also need SSe to compute partial omega2 at the end + varargout{6}(i,:)=SSe; + end + +end +% reshape data to match input +if prod(sX)>pno + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end +% Process outputs +if nargout >= 3+2 + % partial omega squared + SSe=varargout{6}; + MSe=SSe./dfe; + varargout{2}=(SS-df.*MSe)./(SSt+(png-df).*MSe); +end +if nargout >= 3+3 + varargout{3}=df; +end +if nargout >= 3+4 + varargout{4}=dfe; +end +if nargout >= 3+5 + varargout{5}=SS; +end +% if nargout >= 3+6 : cf supra +if nargout >= 3+7 + % SSt = SS total + varargout{7}=SSt; +end +if nargout >= 3+8 + % partial eta squared + varargout{8}=SS./(SS+SSe); +end +if nargout >= 3+9 + % omega squared + varargout{9}=(SS-df.*MSe)./(SSt+MSe); +end + + + + +return + + +if nargout>3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + % MS(nfx+3,:)= MSr=squeeze(SSr/dfr);; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 repeated measure ANOVA +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F= 727/57.94 = 12.6 + +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) + + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'COND x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + +%% DATA Eysenck 1974 +% http://web.uccs.edu/lbecker/Psy590/es.htm +% http://homepages.gold.ac.uk/aphome/GLM%20Simple%20Main%20Effects.html +% Counting Rhyming Adjective Imagery Intentional +X=[ + 9 7 11 12 10 + 8 9 13 11 19 + 6 6 8 16 14 + 8 6 6 11 5 + 10 6 14 9 10 + 4 11 11 23 11 + 6 6 13 12 14 + 5 3 13 10 15 + 7 8 10 19 11 + 7 7 11 11 11 + ]; + +% Eysenck 1974 OLD/YOUNG +% +X=urlread('http://forrest.psych.unc.edu/research/vista-frames/help/lecturenotes/lecture10/eysenck.xli'); +X='DATA "Eysenck" :TITLE "Eysenck" :ABOUT "Eysenck study of recall ability of subjects who were young (Y - 18-30 years old) or old (O - 55-65 years old) for recall conditions involving Counting, Rhyming, Adjectives, Imagery or Intentional. From Howell, David C., (Ed. 3) p. 325." :VARIABLES (QUOTE ("Recall" "Age" "Condition")) :TYPES (QUOTE ("Numeric" "Category" "Category")) :LABELS (QUOTE ("Obs0" "Obs1" "Obs2" "Obs3" "Obs4" "Obs5" "Obs6" "Obs7" "Obs8" "Obs9" "Obs10" "Obs11" "Obs12" "Obs13" "Obs14" "Obs15" "Obs16" "Obs17" "Obs18" "Obs19" "Obs20" "Obs21" "Obs22" "Obs23" "Obs24" "Obs25" "Obs26" "Obs27" "Obs28" "Obs29" "Obs30" "Obs31" "Obs32" "Obs33" "Obs34" "Obs35" "Obs36" "Obs37" "Obs38" "Obs39" "Obs40" "Obs41" "Obs42" "Obs43" "Obs44" "Obs45" "Obs46" "Obs47" "Obs48" "Obs49" "Obs50" "Obs51" "Obs52" "Obs53" "Obs54" "Obs55" "Obs56" "Obs57" "Obs58" "Obs59" "Obs60" "Obs61" "Obs62" "Obs63" "Obs64" "Obs65" "Obs66" "Obs67" "Obs68" "Obs69" "Obs70" "Obs71" "Obs72" "Obs73" "Obs74" "Obs75" "Obs76" "Obs77" "Obs78" "Obs79" "Obs80" "Obs81" "Obs82" "Obs83" "Obs84" "Obs85" "Obs86" "Obs87" "Obs88" "Obs89" "Obs90" "Obs91" "Obs92" "Obs93" "Obs94" "Obs95" "Obs96" "Obs97" "Obs98" "Obs99")) :DATA (QUOTE (9 "O" "C" 8 "O" "C" 6 "O" "C" 8 "O" "C" 10 "O" "C" 4 "O" "C" 6 "O" "C" 5 "O" "C" 7 "O" "C" 7 "O" "C" 7 "O" "R" 9 "O" "R" 6 "O" "R" 6 "O" "R" 6 "O" "R" 11 "O" "R" 6 "O" "R" 3 "O" "R" 8 "O" "R" 7 "O" "R" 11 "O" "A" 13 "O" "A" 8 "O" "A" 6 "O" "A" 14 "O" "A" 11 "O" "A" 13 "O" "A" 13 "O" "A" 10 "O" "A" 11 "O" "A" 12 "O" "I" 11 "O" "I" 16 "O" "I" 11 "O" "I" 9 "O" "I" 23 "O" "I" 12 "O" "I" 10 "O" "I" 19 "O" "I" 11 "O" "I" 10 "O" "IN" 19 "O" "IN" 14 "O" "IN" 5 "O" "IN" 10 "O" "IN" 11 "O" "IN" 14 "O" "IN" 15 "O" "IN" 11 "O" "IN" 11 "O" "IN" 8 "Y" "C" 6 "Y" "C" 4 "Y" "C" 6 "Y" "C" 7 "Y" "C" 6 "Y" "C" 5 "Y" "C" 7 "Y" "C" 9 "Y" "C" 7 "Y" "C" 10 "Y" "R" 7 "Y" "R" 8 "Y" "R" 10 "Y" "R" 4 "Y" "R" 7 "Y" "R" 10 "Y" "R" 6 "Y" "R" 7 "Y" "R" 7 "Y" "R" 14 "Y" "A" 11 "Y" "A" 18 "Y" "A" 14 "Y" "A" 13 "Y" "A" 22 "Y" "A" 17 "Y" "A" 16 "Y" "A" 12 "Y" "A" 11 "Y" "A" 20 "Y" "I" 16 "Y" "I" 16 "Y" "I" 15 "Y" "I" 18 "Y" "I" 16 "Y" "I" 20 "Y" "I" 22 "Y" "I" 14 "Y" "I" 19 "Y" "I" 21 "Y" "IN" 19 "Y" "IN" 17 "Y" "IN" 15 "Y" "IN" 22 "Y" "IN" 16 "Y" "IN" 22 "Y" "IN" 22 "Y" "IN" 18 "Y" "IN" 21 "Y" "IN")) :DATASHEET-ARGUMENTS (QUOTE ((420 475) (511 120) 2 8)))'; +X=strread(X, '%s', 'delimiter', ' '); +X=X(160:3:end-8) +X{1}(1)=[]; +X=str2num(strvcat(X)); +X=reshape(X,10,5,2); +X=permute(X,[3 2 1]); % AGE x COND x SUBJ + + +% Migraine Headache +% http://core.ecu.edu/psyc/wuenschk/SPSS/SPSS-Data.htm +X= [ + 21 22 8 6 6 + 20 19 10 4 9 + 7 5 5 4 5 + 25 30 13 12 4 + 30 33 10 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 13 4 8 1 5 + 26 24 14 8 17 + ]; +% Howell Table 14.3 +X= [ + 21 22 8 6 6 + 20 19 10 4 4 + 17 15 5 4 5 + 25 30 13 12 17 + 30 27 13 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 17 18 8 1 5 + 26 24 14 8 9 + ]; + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +X(i)=x(:,1); +X=reshape(X,nl); + + +% +X = [ + 92 + 90 + 92 + 91 + 90 + + 70 + 70 + 71 + 70 + 72 + + 90 + 90 + 92 + 94 + 91 + + 87 + 82 + 81 + 84 + 85 + + 66 + 65 + 67 + 69 + 71 + + 62 + 59 + 58 + 60 + 59 + + 88 + 88 + 83 + 82 + 88 + + 85 + 85 + 82 + 84 + 83 + ]; +X=permute(reshape(X,[5 2 2 2]), [4 3 2 1]); + + +% http://www.ou.edu/faculty/M/Jorge.L.Mendoza-1/psy5013/twoway-repeated.sas +% [Traning] [Males: Pre Post FU6 FU12] [Females: Pre Post FU6 FU12] +X = [ + 1 7 22 13 14 0 6 22 26 + 1 25 10 17 24 0 16 12 15 + 1 50 36 49 23 0 8 0 0 + 1 16 38 34 24 15 14 22 8 + 1 33 25 24 25 27 18 24 37 + 1 10 7 23 26 0 0 0 0 + 1 13 33 27 24 4 27 21 3 + 1 22 20 21 11 26 9 9 12 + 1 4 0 12 0 0 0 14 1 + 1 17 16 20 10 0 0 12 0 + 0 0 0 0 0 15 28 26 15 + 0 69 56 14 36 0 0 0 0 + 0 5 0 0 5 6 0 23 0 + 0 4 24 0 0 0 0 0 0 + 0 35 8 0 0 25 28 0 16 + 0 7 0 9 37 36 22 14 48 + 0 51 53 8 26 19 22 29 2 + 0 25 0 0 15 0 0 5 14 + 0 59 45 11 16 0 0 0 0 + 0 40 2 33 16 0 0 0 0 + ]; +X=reshape(X(:,2:end),[10,2,4 2]); +X=permute(X, [2 3 4 1]); +[p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt,peta2,omega2]=myanova(X,3,2) + + +% http://www.psych.northwestern.edu/help/systat/Syst.facmix.html +% subject Smoking High Stress Low Stress +% 1 light 8 1 +% 2 light 7 1 +% 3 heavy 6 8 +% 4 heavy 5 6 +% 5 light 8 3 +% 6 light 10 1 +% 7 heavy 6 7 +% 8 light 9 2 +% 9 heavy 8 10 +% 10 light 9 2 +x=[ + 1 8 1 + 1 7 1 + 2 6 8 + 2 5 6 + 1 8 3 + 1 10 1 + 2 6 7 + 1 9 2 + 2 8 10 + 1 9 2 + ]; +%X=reshape(X, +[i,nl]=dgrouping([ [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +[i,nl]=dgrouping([ [[1:10]';[1:10]'] [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +X=NaN*zeros(nl); + +%http://www.isogenic.info/html/example_2.html http://www.isogenic.info/html/example_2.html +% Strain EROD Treatm Block +x=[ + 1 18.7 1 1 + 2 17.9 1 1 + 3 19.2 1 1 + 4 26.3 1 1 + 1 7.7 2 1 + 2 8.4 2 1 + 3 9.8 2 1 + 4 9.7 2 1 + 1 16.7 1 2 + 2 14.4 1 2 + 3 12.0 1 2 + 4 19.8 1 2 + 1 6.4 2 2 + 2 6.7 2 2 + 3 8.1 2 2 + 4 6.0 2 2 + ] +[i,nl]=dgrouping(x(:,[1 3 4])) +X=NaN*zeros(nl); +X(i)=x(:,2); +%In this case a three-way ANOVA with strain and treatment being fixed +%effects (determined by the experimentalist) and the block being a random +%factor (i.e. not a specific treatment). +% +% Source DF SS MS F P +% Block 1 47.610 47.610 18.37 0.004 +% Strain 3 32.962 10.988 4.24 0.053 +% Trt 1 422.303 422.303 162.96 0.000 +% Strain*Trt 3 40.343 13.448 5.19 0.034 +% Error 7 18.140 2.591 +% Total 15 561.358 + + +% ABRDATA.TAB from OpenStat +% http://www.statpages.org/miller/openstat/Analyzing%20Data%20with%20Stats4U.pdf +% Row Col C1 C2 C3 C4 +X=[ + 1.00 1.00 18.00 14.00 12.00 6.00 + 1.00 1.00 19.00 12.00 8.00 4.00 + 1.00 1.00 14.00 10.00 6.00 2.00 + 1.00 2.00 16.00 12.00 10.00 4.00 + 1.00 2.00 12.00 8.00 6.00 2.00 + 1.00 2.00 18.00 10.00 5.00 1.00 + 2.00 1.00 16.00 10.00 8.00 4.00 + 2.00 1.00 18.00 8.00 4.00 1.00 + 2.00 1.00 16.00 12.00 6.00 2.00 + 2.00 2.00 19.00 16.00 10.00 8.00 + 2.00 2.00 16.00 14.00 10.00 9.00 + 2.00 2.00 16.00 12.00 8.00 8.00 + ]; +X=reshape(X(:,3:end), [3 2 2 4]); +X=permute(X,[2 3 4 1]); + +% SOURCE DF SS MS F PROB. +% Between Subjects 11 181.000 +% A Effects 1 10.083 10.083 0.978 0.352 +% B Effects 1 8.333 8.333 0.808 0.395 +% AB Effects 1 80.083 80.083 7.766 0.024 +% Error Between 8 82.500 10.312 +% Within Subjects 36 1077.000 +% C Replications 3 991.500 330.500 152.051 0.000 +% AC Effects 3 8.417 2.806 1.291 0.300 +% BC Effects 3 12.167 4.056 1.866 0.162 +% ABC Effects 3 12.750 4.250 1.955 0.148 +% Error Within 24 52.167 2.174 +% Total 47 1258.000 + +function [SS,df]=sumofsquares(X,f1,nf,mX) +sX=size(X); +f2=setdiff(1:nf+1,f1); +mXf = permute(X, [f1 f2 nf+2:ndims(X)]); +mXf = reshape(mXf,prod(sX(f1)),prod(sX(f2)),[]); +mXf = mean(mXf,1); +SS = mXf - repmat(mX,[1 prod(sX(f2)) 1]) +%SS = reshape(SS, prod(sX(f2)), []).^2 +SS = SS.^2 +SS = sum(sum(SS,2),1); +df = prod(sX(f1)) \ No newline at end of file diff --git a/mystats/myanova.2.m b/mystats/myanova.2.m new file mode 100644 index 0000000..b2d9ed2 --- /dev/null +++ b/mystats/myanova.2.m @@ -0,0 +1,516 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,verbose) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% eta: percentage of explained variance by each factor +% epsilon: sphericity correction if applicable +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() + +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +if nr<2 + error('You must have more than one observation per cell/one subject per condition') +end + +if nargin<3 + rp=[]; +end +% if ~isempty(rp) & ~all(ismember(1:nf,rp)) +% error('Mixed designs (split plot) ANOVA unavailable!') +% end +% if ~isempty(rp) & nf>2 +% error('Repeated measure ANOVA is only available for 2 factor designs!') +% end +if nargin<4 + epsilon=1; +end +if nargin<5 || isempty(verbose) + verbose=1; +end +if isempty(epsilon) + epsilon=NaN; +end + +% Within Group/Error stats +% Mean in each cell +mXw=mean(X,nf+1); +% Residual Error of the model +SSe=X-repmat(mXw,[ones(1,nf) nr 1]); +SSe=reshape(SSe, png*nr, []).^2; +SSe=sum(SSe); +dfe=png*(nr-1); +MSe=squeeze(SSe/dfe); +%keeps the full model unexplained variance for later +MSw=MSe; +dfw=dfe; + +% Population stats +dft=(png*nr)-1; +% Grand mean value +mX=reshape(mXw, png, []); +mX=mean(mX,1); +% Correction factor: +% cX=mX.^2./(png*nr); + +% These are not used afterwards +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +% MSt=squeeze(SSt/dft); + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,[]); + mXr=mean(mXr,2); + SSr=png*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); +end + +% Sphericity checking +if isnan(epsilon) % | ischar(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% Number of groups in between subjects +pngb=1; +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + pngb=prod(ng(~rp)); + png=png/pngb; + % Factors within first, between next + fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +end + +% Within Group/Error stats +% i.e unmodeled error +mXe=mean(X,nf+1); +SSe=X-repmat(mXe,[ones(1,nf) nr 1]); +SSe=reshape(SSe, [pnc nr svar]).^2; +SSe=sum(sum(SSe)); +if (nr<=1) + error('myanova doesn''t work with 1 subject / group!') +end +dfe=png*(nr-1); +MSe=squeeze(SSe/dfe); +dfe=repmat(dfe, [nfx 1]); + +% Population stats +dft=(pno)-1; +mX=reshape(mXe,pnc,[svar]); + varargout{1}=epsilon; +end +if nargout > 8 || verbose==1 + varargout{6}=SSt; +end + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + + if length(j)>1 + % Interaction: + % we need to remove the variance from emvbedded effects from the + % Sum of Squares of this effect + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + + if any(ismember(j,rp)) + % Correct Error term to account for repeated measurements + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + for k=1:i-1 + %remove embedded factors effects and error terms + if all(ismember(fx{k}, j)) + SSe=SSe-SS(k,:)-SSbe(k,:); + end + end + end + SSbe(i,:)=SSe; + MSe=squeeze(SSe/dfe); + % % MSr=squeeze(SSr/dfr); + % else + % dfw=png*(nr-1); + % MSw=squeeze(SSw/dfw); + % + % dfe=dfw; + % MSe=MSw; + % end + dfb=dfb.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + % dfb=dfb.*epsilon(i,:); + % dfw=dfw.*epsilon(i,:); + % F(i,:)=squeeze(MSb)./MSw; + % p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + % end + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>4 || verbose==1 + varargout{2}(i,:)=dfb; + end + if nargout>5 || verbose==1 + %if not(isempty(rp)) + varargout{3}(i,:)=dfe; + %else + % varargout{3}(i,:)=dfw; + %end + end + if nargout>6 || verbose==1 + varargout{4}(i,:)=SSb; + end + if nargout>7 || verbose==1 + %if not(isempty(rp)) + varargout{5}(i,:)=SSe; + %else + % varargout{5}(i,:)=SSw; + %end + end +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +if verbose + [ignore,df,dfe,SSb,SSe,SSt]=deal(varargout{:}); + MS=SS./df; + + %Display results + fprintf([repmat('-',1,80) '\n'] ); + fprintf(['%' num2str(max(cellfun('length', fx))*2+15) 's \t| df \t| SS \t| MS \t| F \t| p\n'], 'ANOVA results'); + fprintf([repmat('-',1,80) '\n'] ); + for j=1:min(size(p,2),3) + if size(p,2)>1 + fprintf('MULTIDIMENSIONAL DATA: [%d] ...\n',j) + end + + for i=1:length(fx) + if i<=nf + label=sprintf('Factor #%d',i); + else + label=['Interaction ' sprintf('%d*',fx{i})]; + label=label(1:end-1); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],label); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,df(i),SS(i,j),MS(i,j),F(i,j),p(i,j)); + if ~isempty(rp) || i==nfx + label=sprintf([ '%' num2str(length(label)) 's'],'Error'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\n',... + label,dfe(i),SSe(i,j),SSe(i,j)./dfe(i)); + end + end + + if ~isempty(rp) + MS_r=SSr./dfr; + F_r=squeeze(MS_r)./MSw; + p_r=1-f_cdf(F_r,dfr,dfw); + label=sprintf([ '%' num2str(length(label)) 's'],'Subjects'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,dfr,SSr(j),MS_r(j),F_r(j),p_r(j)); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],'Total'); + fprintf('%s: \t % 3.3g \t% 8.4g\n',... + label,dft,SSt(j)); + if size(p,2)>1 + fprintf([repmat('. ',1,40) '\n']) + end + + end + if j3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 (repeated measure one-way ANOVA) +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F = (1454/2)/(695.3/12) = 727/57.94 = 12.6 + + +% BETWEEN SUBJECT DESIGN WITH 2 REPLICATES +% ======================================== +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F observed = 28.283 12.393 1.973 +% F critique = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) +[p,F]=myanova(X,2,[]) + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'TRIAL x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates + +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +X(i)=x(:,1); +X=reshape(X,nl); + +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% M1 = 11.0 M2 = 13.0 M3 = 14.2 + +% Two-way ANOVA from Cousineau 2007 +X= [ + 550 580 610 + 605 635 655 + 660 690 710 + ]'; + + +% Cousineau ? +X= [ + 150. 44. 71. 59. 132. 74. 1. + 335. 270. 156. 160. 118. 230. 1. + 149. 52. 91. 115. 43. 154. 1. + 159. 31. 127. 212. 71. 224. 1. + 159. 0. 35. 75. 71. 34. 1. + 292. 125. 184. 246. 225. 170. 1. + 297. 187. 66. 96. 209. 74. 1. + 170. 37. 42. 66. 114. 81. 1. + 346. 175. 177. 192. 239. 140. 2. + 426. 329. 236. 76. 102. 232. 2. + 359. 238. 183. 123. 183. 30. 2. + 272. 60. 82. 85. 101. 98. 2. + 200. 271. 263. 216. 241. 227. 2. + 366. 291. 263. 144. 220. 180. 2. + 371. 364. 270. 308. 219. 267. 2. + 497. 402. 294. 216. 284. 255. 2. + 282. 186. 225. 134. 189. 169. 3. + 317. 31. 85. 120. 131. 205. 3. + 362. 104. 144. 114. 115. 127. 3. + 338. 132. 91. 77. 108. 169. 3. + 263. 94. 141. 142. 120. 195. 3. + 138. 38. 16. 95. 39. 55. 3. + 329. 62. 62. 6. 93. 67. 3. + 292. 139. 104. 184. 193. 122. 3. + ]; +X=reshape(X(:,1:6),[8,3,6]); +X=permute(X,[1 3 2]); + + +% Cousineau TQPM +X=str2num(urlread('http://www.tqmp.org/doc/vol1-1/p42.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +myanova(X,2,1:2) + +% Loftus & Masson 1994 +X= [ + 1 450 462 12 460 482 22 460 497 37 480 507 27 + 2 510 492 -18 515 530 15 520 534 14 504 550 46 + 3 492 508 16 512 522 10 503 553 50 520 539 19 + 4 524 532 8 530 543 13 517 546 29 503 553 50 + 5 420 409 -11 424 452 28 431 468 37 446 472 26 + 6 540 550 10 538 528 -10 552 575 23 562 598 36 + ]; +X=reshape(X(:,2:end),6,3,4); +X=permute(X(:,1:2,:),[2 3 1]); +% X : R vs U | SOA 50/100/200/400 | SUBJ(6) diff --git a/mystats/myanova.6.m b/mystats/myanova.6.m new file mode 100644 index 0000000..8b99077 --- /dev/null +++ b/mystats/myanova.6.m @@ -0,0 +1,737 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,SStype) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt]=... +% myanova(X,nf,rp,epsilon,SStype) +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% epsilon: sphericity correction if applicable +% pomega2: partial omega squared (unbiased estimator of effect size) +% df: degrees of freedom for each effect +% dfe: degrees of freedom of error for each effect +% SS: sum of squares for each effect +% SSe: sum of squares of error for each effect +% SSt: Total sum of squares +% peta2: partial eta-squared, (biased) percentage of explained variance by each factor +% omega2: (unbiased) percentage of explained variance by each factor +% eta2: cf infra +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() +% +% See also: myanovaeffects, factorlabels, dgrouping + + +% References: +% On effect sizes: http://epm.sagepub.com/cgi/content/abstract/64/6/916 +% http://psyphz.psych.wisc.edu/~shackman/olejnik_PsychMeth2003.pdf +% http://www.psy.jhu.edu/~ashelton/courses/stats315/week5.pdf +% + +% peta2: (biased) percentage of explained variance by each factor +% omega2: (unbiased) percentage of explained variance by each factor + +SS=[]; +SSb=[]; +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +% Number of cells +pnc=prod(ng); +%Number of observations +pno=pnc*nr; +% Dimensions of (pseudo multivariate) dependent variables +svar=[sX(nf+2:end)]; +if nr<2 + error('MYANOVA:NoReplicates''You must have more than one observation per cell/one subject per condition') +end +if nargin<3 + rp=[]; +end +if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('MYANOVA:MixedDesign','Mixed designs (split plot) ANOVA unavailable!\nAll factors must be either within or between.') +end +if nargin<4 + epsilon=1; +end +if nargin<5 + SStype=[]; +end +% Number of groups in between subjects +pngb=1; +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + pngb=prod(ng(~rp)); + png=png/pngb; + % Factors within first, between next + fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +end +if isempty(SStype) + SSStype=3; +% if isempty(rp) +% SStype=3; +% % error('I dunno which SS type to choose...'); +% elseif all(rp) +% SStype=2; +% else +% error('I dunno which SS type to choose...'); +% end +end + +% Within Group/Error stats +% Mean in each cell +mXw=mean(X,nf+1); +% Residual Error of the model +SSe=X-repmat(mXw,[ones(1,nf) nr 1]); +SSe=reshape(SSe, png*nr, []).^2; +SSe=sum(SSe); +dfe=png*(nr-1); +dfe=repmat(dfe, [nfx 1]); +MSe=squeeze(SSe/dfe); +%Keeps the full model unexplained variance for later +MSw=MSe; +dfw=dfe; + +% Population stats +dft=(png*nr)-1; +% Grand mean value +mX=reshape(mXw, png, []); +mX=mean(mX,1); + + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,[]); + mXr=mean(mXr,2); + SSr=png*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Sphericity checking +if isnan(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... +if nargout > 3 || nargout==0 + varargout{1}=epsilon; +end + +df=zeros(nfx,1); +SS=zeros([nfx svar]); +F=zeros([nfx svar]); +p=zeros([nfx svar]); + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + df=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Interaction: + % we need to remove the variance from emvbedded effects from the + % Sum of Squares of this effect + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./df; + + if any(ismember(j,rp)) + % Correct Error term to account for repeated measurements + dfe=(nr-1)*df; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + for k=1:i-1 + %remove embedded factors effects and error terms + if all(ismember(fx{k}, j)) + SSe=SSe-SS(k,:)-SSbe(k,:); + end + end + end + SSbe(i,:)=SSe; + MSe=squeeze(SSe/dfe); + % Non-sphericity correction of degrees of liberty + df=df.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + % F-ratio & p-value + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),df,dfe); + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>=6 || nargout==0 + varargout{3}(i,:)=df; + end + if nargout>=7 || nargout==0 + varargout{4}(i,:)=dfe; + end +end + +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +SSe=SSbe; +% Process outputs +if nargout >= 5 || nargout==0 + % partial omega squared + MSe=SSe./dfe; + varargout{2}=(SS-df.*MSe)./(SSt+(png-df).*MSe); +end + +if nargout>=8 || nargout==0 + varargout{5}=SSbe; +end +if nargout>=9 || nargout==0 + varargout{6}=SSbe; +end +if nargout >=10 || nargout == 0 + varargout{7}=SSt; +end +if nargout >= 11 + % partial eta squared + varargout{8}=SS./(SS+SSe); +end +if nargout >= 12 + % omega squared + varargout{9}=(SS-df.*MSe)./(SSt+MSe); +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +%% Process output for display +if nargout==0 + %Display results + %Retrieves numerical results + [pomega2,df,dfe,SS,SSe,SSt,peta2]=deal(varargout{:}); + MS=SS./df; + + fprintf([repmat('-',1,80) '\n'] ); + fprintf(['%' num2str(max(cellfun('length', fx))*2+15) 's \t| df \t| SS \t| MS \t| F \t| p\n'], 'ANOVA results'); + fprintf([repmat('-',1,80) '\n'] ); + for j=1:min(size(p,2),3) + if size(p,2)>1 + fprintf('MULTIDIMENSIONAL DATA: [%d] ...\n',j) + end + + for i=1:length(fx) + if i<=nf + label=sprintf('Factor #%d',i); + else + label=['Interaction ' sprintf('%d*',fx{i})]; + label=label(1:end-1); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],label); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,df(i),SS(i,j),MS(i,j),F(i,j),p(i,j)); + if ~isempty(rp) || i==nfx + label=sprintf([ '%' num2str(length(label)) 's'],'Error'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\n',... + label,dfe(i),SSe(i,j),SSe(i,j)./dfe(i)); + end + end + + if ~isempty(rp) + MS_r=SSr./dfr; + F_r=squeeze(MS_r)./MSw; + p_r=1-f_cdf(F_r,dfr,dfw); + label=sprintf([ '%' num2str(length(label)) 's'],'Subjects'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,dfr,SSr(j),MS_r(j),F_r(j),p_r(j)); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],'Total'); + fprintf('%s: \t % 3.3g \t% 8.4g\n',... + label,dft,SSt(j)); + if size(p,2)>1 + fprintf([repmat('. ',1,40) '\n']) + end + + end + if j3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 (repeated measure one-way ANOVA) +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F = (1454/2)/(695.3/12) = 727/57.94 = 12.6 + + +% BETWEEN SUBJECT DESIGN WITH 2 REPLICATES +% ======================================== +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F observed = 28.283 12.393 1.973 +% F critique = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) +[p,F]=myanova(X,2,[]) + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'TRIAL x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +clear X +X(i)=x(:,1); +X=reshape(X,nl); + + + +% Two-way ANOVA from Cousineau 2007 +X= [ + 550 580 610 + 605 635 655 + 660 690 710 + ]'; + + +% Cousineau ? +X= [ + 150. 44. 71. 59. 132. 74. 1. + 335. 270. 156. 160. 118. 230. 1. + 149. 52. 91. 115. 43. 154. 1. + 159. 31. 127. 212. 71. 224. 1. + 159. 0. 35. 75. 71. 34. 1. + 292. 125. 184. 246. 225. 170. 1. + 297. 187. 66. 96. 209. 74. 1. + 170. 37. 42. 66. 114. 81. 1. + 346. 175. 177. 192. 239. 140. 2. + 426. 329. 236. 76. 102. 232. 2. + 359. 238. 183. 123. 183. 30. 2. + 272. 60. 82. 85. 101. 98. 2. + 200. 271. 263. 216. 241. 227. 2. + 366. 291. 263. 144. 220. 180. 2. + 371. 364. 270. 308. 219. 267. 2. + 497. 402. 294. 216. 284. 255. 2. + 282. 186. 225. 134. 189. 169. 3. + 317. 31. 85. 120. 131. 205. 3. + 362. 104. 144. 114. 115. 127. 3. + 338. 132. 91. 77. 108. 169. 3. + 263. 94. 141. 142. 120. 195. 3. + 138. 38. 16. 95. 39. 55. 3. + 329. 62. 62. 6. 93. 67. 3. + 292. 139. 104. 184. 193. 122. 3. + ]; +X=reshape(X(:,1:6),[8,3,6]); +X=permute(X,[1 3 2]); + +% Cousineau TQPM +X=str2num(urlread('http://www.tqmp.org/doc/vol1-1/p42.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +myanova(X,2,1:2) + +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% M1 = 11.0 M2 = 13.0 M3 = 14.2 + + +% Loftus & Masson 1994 +X= [ + 1 450 462 12 460 482 22 460 497 37 480 507 27 + 2 510 492 -18 515 530 15 520 534 14 504 550 46 + 3 492 508 16 512 522 10 503 553 50 520 539 19 + 4 524 532 8 530 543 13 517 546 29 503 553 50 + 5 420 409 -11 424 452 28 431 468 37 446 472 26 + 6 540 550 10 538 528 -10 552 575 23 562 598 36 + ]; +X=reshape(X(:,2:end),6,3,4); +X=permute(X(:,1:2,:),[2 3 1]); +% X : R vs U | SOA 50/100/200/400 | SUBJ(6) + + +%% DATA Eysenck 1974 +% http://web.uccs.edu/lbecker/Psy590/es.htm +% http://homepages.gold.ac.uk/aphome/GLM%20Simple%20Main%20Effects.html +% Counting Rhyming Adjective Imagery Intentional +X=[ + 9 7 11 12 10 + 8 9 13 11 19 + 6 6 8 16 14 + 8 6 6 11 5 + 10 6 14 9 10 + 4 11 11 23 11 + 6 6 13 12 14 + 5 3 13 10 15 + 7 8 10 19 11 + 7 7 11 11 11 + ]; + +% Eysenck 1974 OLD/YOUNG +% +X=urlread('http://forrest.psych.unc.edu/research/vista-frames/help/lecturenotes/lecture10/eysenck.xli'); +X='DATA "Eysenck" :TITLE "Eysenck" :ABOUT "Eysenck study of recall ability of subjects who were young (Y - 18-30 years old) or old (O - 55-65 years old) for recall conditions involving Counting, Rhyming, Adjectives, Imagery or Intentional. From Howell, David C., (Ed. 3) p. 325." :VARIABLES (QUOTE ("Recall" "Age" "Condition")) :TYPES (QUOTE ("Numeric" "Category" "Category")) :LABELS (QUOTE ("Obs0" "Obs1" "Obs2" "Obs3" "Obs4" "Obs5" "Obs6" "Obs7" "Obs8" "Obs9" "Obs10" "Obs11" "Obs12" "Obs13" "Obs14" "Obs15" "Obs16" "Obs17" "Obs18" "Obs19" "Obs20" "Obs21" "Obs22" "Obs23" "Obs24" "Obs25" "Obs26" "Obs27" "Obs28" "Obs29" "Obs30" "Obs31" "Obs32" "Obs33" "Obs34" "Obs35" "Obs36" "Obs37" "Obs38" "Obs39" "Obs40" "Obs41" "Obs42" "Obs43" "Obs44" "Obs45" "Obs46" "Obs47" "Obs48" "Obs49" "Obs50" "Obs51" "Obs52" "Obs53" "Obs54" "Obs55" "Obs56" "Obs57" "Obs58" "Obs59" "Obs60" "Obs61" "Obs62" "Obs63" "Obs64" "Obs65" "Obs66" "Obs67" "Obs68" "Obs69" "Obs70" "Obs71" "Obs72" "Obs73" "Obs74" "Obs75" "Obs76" "Obs77" "Obs78" "Obs79" "Obs80" "Obs81" "Obs82" "Obs83" "Obs84" "Obs85" "Obs86" "Obs87" "Obs88" "Obs89" "Obs90" "Obs91" "Obs92" "Obs93" "Obs94" "Obs95" "Obs96" "Obs97" "Obs98" "Obs99")) :DATA (QUOTE (9 "O" "C" 8 "O" "C" 6 "O" "C" 8 "O" "C" 10 "O" "C" 4 "O" "C" 6 "O" "C" 5 "O" "C" 7 "O" "C" 7 "O" "C" 7 "O" "R" 9 "O" "R" 6 "O" "R" 6 "O" "R" 6 "O" "R" 11 "O" "R" 6 "O" "R" 3 "O" "R" 8 "O" "R" 7 "O" "R" 11 "O" "A" 13 "O" "A" 8 "O" "A" 6 "O" "A" 14 "O" "A" 11 "O" "A" 13 "O" "A" 13 "O" "A" 10 "O" "A" 11 "O" "A" 12 "O" "I" 11 "O" "I" 16 "O" "I" 11 "O" "I" 9 "O" "I" 23 "O" "I" 12 "O" "I" 10 "O" "I" 19 "O" "I" 11 "O" "I" 10 "O" "IN" 19 "O" "IN" 14 "O" "IN" 5 "O" "IN" 10 "O" "IN" 11 "O" "IN" 14 "O" "IN" 15 "O" "IN" 11 "O" "IN" 11 "O" "IN" 8 "Y" "C" 6 "Y" "C" 4 "Y" "C" 6 "Y" "C" 7 "Y" "C" 6 "Y" "C" 5 "Y" "C" 7 "Y" "C" 9 "Y" "C" 7 "Y" "C" 10 "Y" "R" 7 "Y" "R" 8 "Y" "R" 10 "Y" "R" 4 "Y" "R" 7 "Y" "R" 10 "Y" "R" 6 "Y" "R" 7 "Y" "R" 7 "Y" "R" 14 "Y" "A" 11 "Y" "A" 18 "Y" "A" 14 "Y" "A" 13 "Y" "A" 22 "Y" "A" 17 "Y" "A" 16 "Y" "A" 12 "Y" "A" 11 "Y" "A" 20 "Y" "I" 16 "Y" "I" 16 "Y" "I" 15 "Y" "I" 18 "Y" "I" 16 "Y" "I" 20 "Y" "I" 22 "Y" "I" 14 "Y" "I" 19 "Y" "I" 21 "Y" "IN" 19 "Y" "IN" 17 "Y" "IN" 15 "Y" "IN" 22 "Y" "IN" 16 "Y" "IN" 22 "Y" "IN" 22 "Y" "IN" 18 "Y" "IN" 21 "Y" "IN")) :DATASHEET-ARGUMENTS (QUOTE ((420 475) (511 120) 2 8)))'; +X=strread(X, '%s', 'delimiter', ' '); +X=X(160:3:end-8) +X{1}(1)=[]; +X=str2num(strvcat(X)); +X=reshape(X,10,5,2); +X=permute(X,[3 2 1]); % AGE x COND x SUBJ + + +% Migraine Headache +% http://core.ecu.edu/psyc/wuenschk/SPSS/SPSS-Data.htm +X= [ + 21 22 8 6 6 + 20 19 10 4 9 + 7 5 5 4 5 + 25 30 13 12 4 + 30 33 10 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 13 4 8 1 5 + 26 24 14 8 17 + ]; +% Howell Table 14.3 +X= [ + 21 22 8 6 6 + 20 19 10 4 4 + 17 15 5 4 5 + 25 30 13 12 17 + 30 27 13 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 17 18 8 1 5 + 26 24 14 8 9 + ]; + + +% http://www.ou.edu/faculty/M/Jorge.L.Mendoza-1/psy5013/twoway-repeated.sas +% [Traning] [Males: Pre Post FU6 FU12] [Females: Pre Post FU6 FU12] +X = [ + 1 7 22 13 14 0 6 22 26 + 1 25 10 17 24 0 16 12 15 + 1 50 36 49 23 0 8 0 0 + 1 16 38 34 24 15 14 22 8 + 1 33 25 24 25 27 18 24 37 + 1 10 7 23 26 0 0 0 0 + 1 13 33 27 24 4 27 21 3 + 1 22 20 21 11 26 9 9 12 + 1 4 0 12 0 0 0 14 1 + 1 17 16 20 10 0 0 12 0 + 0 0 0 0 0 15 28 26 15 + 0 69 56 14 36 0 0 0 0 + 0 5 0 0 5 6 0 23 0 + 0 4 24 0 0 0 0 0 0 + 0 35 8 0 0 25 28 0 16 + 0 7 0 9 37 36 22 14 48 + 0 51 53 8 26 19 22 29 2 + 0 25 0 0 15 0 0 5 14 + 0 59 45 11 16 0 0 0 0 + 0 40 2 33 16 0 0 0 0 + ]; +X=reshape(X(:,2:end),[10,2,4 2]); +X=permute(X, [2 3 4 1]); +[p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt,peta2,omega2]=myanova(X,3,2) + + +% http://www.psych.northwestern.edu/help/systat/Syst.facmix.html +% subject Smoking High Stress Low Stress +% 1 light 8 1 +% 2 light 7 1 +% 3 heavy 6 8 +% 4 heavy 5 6 +% 5 light 8 3 +% 6 light 10 1 +% 7 heavy 6 7 +% 8 light 9 2 +% 9 heavy 8 10 +% 10 light 9 2 +x=[ + 1 8 1 + 1 7 1 + 2 6 8 + 2 5 6 + 1 8 3 + 1 10 1 + 2 6 7 + 1 9 2 + 2 8 10 + 1 9 2 + ]; +%X=reshape(X, +[i,nl]=dgrouping([ [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +[i,nl]=dgrouping([ [[1:10]';[1:10]'] [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +X=NaN*zeros(nl); + +%http://www.isogenic.info/html/example_2.html http://www.isogenic.info/html/example_2.html +% Strain EROD Treatm Block +x=[ + 1 18.7 1 1 + 2 17.9 1 1 + 3 19.2 1 1 + 4 26.3 1 1 + 1 7.7 2 1 + 2 8.4 2 1 + 3 9.8 2 1 + 4 9.7 2 1 + 1 16.7 1 2 + 2 14.4 1 2 + 3 12.0 1 2 + 4 19.8 1 2 + 1 6.4 2 2 + 2 6.7 2 2 + 3 8.1 2 2 + 4 6.0 2 2 + ] +[i,nl]=dgrouping(x(:,[1 3 4])) +X=NaN*zeros(nl); +X(i)=x(:,2); +%In this case a three-way ANOVA with strain and treatment being fixed +%effects (determined by the experimentalist) and the block being a random +%factor (i.e. not a specific treatment). +% +% Source DF SS MS F P +% Block 1 47.610 47.610 18.37 0.004 +% Strain 3 32.962 10.988 4.24 0.053 +% Trt 1 422.303 422.303 162.96 0.000 +% Strain*Trt 3 40.343 13.448 5.19 0.034 +% Error 7 18.140 2.591 +% Total 15 561.358 + + +% ABRDATA.TAB from OpenStat +% http://www.statpages.org/miller/openstat/Analyzing%20Data%20with%20Stats4U.pdf +% Row Col C1 C2 C3 C4 +X=[ + 1.00 1.00 18.00 14.00 12.00 6.00 + 1.00 1.00 19.00 12.00 8.00 4.00 + 1.00 1.00 14.00 10.00 6.00 2.00 + 1.00 2.00 16.00 12.00 10.00 4.00 + 1.00 2.00 12.00 8.00 6.00 2.00 + 1.00 2.00 18.00 10.00 5.00 1.00 + 2.00 1.00 16.00 10.00 8.00 4.00 + 2.00 1.00 18.00 8.00 4.00 1.00 + 2.00 1.00 16.00 12.00 6.00 2.00 + 2.00 2.00 19.00 16.00 10.00 8.00 + 2.00 2.00 16.00 14.00 10.00 9.00 + 2.00 2.00 16.00 12.00 8.00 8.00 + ]; +X=reshape(X(:,3:end), [3 2 2 4]); +X=permute(X,[2 3 4 1]); + +% SOURCE DF SS MS F PROB. +% Between Subjects 11 181.000 +% A Effects 1 10.083 10.083 0.978 0.352 +% B Effects 1 8.333 8.333 0.808 0.395 +% AB Effects 1 80.083 80.083 7.766 0.024 +% Error Between 8 82.500 10.312 +% Within Subjects 36 1077.000 +% C Replications 3 991.500 330.500 152.051 0.000 +% AC Effects 3 8.417 2.806 1.291 0.300 +% BC Effects 3 12.167 4.056 1.866 0.162 +% ABC Effects 3 12.750 4.250 1.955 0.148 +% Error Within 24 52.167 2.174 +% Total 47 1258.000 + +function [SS,df]=sumofsquares(X,f1,nf,mX) +sX=size(X); +f2=setdiff(1:nf+1,f1); +mXf = permute(X, [f1 f2 nf+2:ndims(X)]); +mXf = reshape(mXf,prod(sX(f1)),prod(sX(f2)),[]); +mXf = mean(mXf,1); +SS = mXf - repmat(mX,[1 prod(sX(f2)) 1]) +%SS = reshape(SS, prod(sX(f2)), []).^2 +SS = SS.^2 +SS = sum(sum(SS,2),1); +df = prod(sX(f1)) \ No newline at end of file diff --git a/mystats/myanova.m b/mystats/myanova.m new file mode 100644 index 0000000..b9ecad8 --- /dev/null +++ b/mystats/myanova.m @@ -0,0 +1,737 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,SStype) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt]=... +% myanova(X,nf,rp,epsilon,SStype) +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% epsilon: sphericity correction if applicable +% pomega2: partial omega squared (unbiased estimator of effect size) +% df: degrees of freedom for each effect +% dfe: degrees of freedom of error for each effect +% SS: sum of squares for each effect +% SSe: sum of squares of error for each effect +% SSt: Total sum of squares +% peta2: partial eta-squared, (biased) percentage of explained variance by each factor +% omega2: (unbiased) percentage of explained variance by each factor +% eta2: cf infra +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() +% +% See also: myanovaeffects, factorlabels, dgrouping + + +% References: +% On effect sizes: http://epm.sagepub.com/cgi/content/abstract/64/6/916 +% http://psyphz.psych.wisc.edu/~shackman/olejnik_PsychMeth2003.pdf +% http://www.psy.jhu.edu/~ashelton/courses/stats315/week5.pdf +% + +% peta2: (biased) percentage of explained variance by each factor +% omega2: (unbiased) percentage of explained variance by each factor + +SS=[]; +SSb=[]; +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +% Number of cells +pnc=prod(ng); +%Number of observations +pno=pnc*nr; +% Dimensions of (pseudo multivariate) dependent variables +svar=[sX(nf+2:end)]; +if nr<2 + error('MYANOVA:NoReplicates''You must have more than one observation per cell/one subject per condition') +end +if nargin<3 + rp=[]; +end +if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('MYANOVA:MixedDesign','Mixed designs (split plot) ANOVA unavailable!\nAll factors must be either within or between.') +end +if nargin<4 + epsilon=1; +end +if nargin<5 + SStype=[]; +end +% Number of groups in between subjects +pngb=1; +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + pngb=prod(ng(~rp)); + png=png/pngb; + % Factors within first, between next + fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +end +if isempty(SStype) + SSStype=3; +% if isempty(rp) +% SStype=3; +% % error('I dunno which SS type to choose...'); +% elseif all(rp) +% SStype=2; +% else +% error('I dunno which SS type to choose...'); +% end +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Within Group/Error stats +% Mean in each cell +mXw=mean(X,nf+1); +% Residual Error of the model +SSe=X-repmat(mXw,[ones(1,nf) nr 1]); +SSe=reshape(SSe, png*nr, []).^2; +SSe=sum(SSe); +dfe=png*(nr-1); +dfe=repmat(dfe, [nfx 1]); +MSe=squeeze(SSe/dfe); +%Keeps the full model unexplained variance for later +MSw=MSe; +dfw=dfe; + +% Population stats +dft=(png*nr)-1; +% Grand mean value +mX=reshape(mXw, png, []); +mX=mean(mX,1); + + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,[]); + mXr=mean(mXr,2); + SSr=png*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); +end + +% Sphericity checking +if isnan(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... +if nargout > 3 || nargout==0 + varargout{1}=epsilon; +end + +df=zeros(nfx,1); +SS=zeros([nfx svar]); +F=zeros([nfx svar]); +p=zeros([nfx svar]); + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + df=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Interaction: + % we need to remove the variance from emvbedded effects from the + % Sum of Squares of this effect + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./df; + + if any(ismember(j,rp)) + % Correct Error term to account for repeated measurements + dfe=(nr-1)*df; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + for k=1:i-1 + %remove embedded factors effects and error terms + if all(ismember(fx{k}, j)) + SSe=SSe-SS(k,:)-SSbe(k,:); + end + end + end + SSbe(i,:)=SSe; + MSe=squeeze(SSe/dfe); + % Non-sphericity correction of degrees of liberty + df=df.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + % F-ratio & p-value + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),df,dfe); + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>=6 || nargout==0 + varargout{3}(i,:)=df; + end + if nargout>=7 || nargout==0 + varargout{4}(i,:)=dfe; + end +end + +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +SSe=SSbe; +% Process outputs +if nargout >= 5 || nargout==0 + % partial omega squared + MSe=SSe./dfe; + varargout{2}=(SS-df.*MSe)./(SSt+(png-df).*MSe); +end + +if nargout>=8 || nargout==0 + varargout{5}=SSbe; +end +if nargout>=9 || nargout==0 + varargout{6}=SSbe; +end +if nargout >=10 || nargout == 0 + varargout{7}=SSt; +end +if nargout >= 11 + % partial eta squared + varargout{8}=SS./(SS+SSe); +end +if nargout >= 12 + % omega squared + varargout{9}=(SS-df.*MSe)./(SSt+MSe); +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +%% Process output for display +if nargout==0 + %Display results + %Retrieves numerical results + [pomega2,df,dfe,SS,SSe,SSt,peta2]=deal(varargout{:}); + MS=SS./df; + + fprintf([repmat('-',1,80) '\n'] ); + fprintf(['%' num2str(max(cellfun('length', fx))*2+15) 's \t| df \t| SS \t| MS \t| F \t| p\n'], 'ANOVA results'); + fprintf([repmat('-',1,80) '\n'] ); + for j=1:min(size(p,2),3) + if size(p,2)>1 + fprintf('MULTIDIMENSIONAL DATA: [%d] ...\n',j) + end + + for i=1:length(fx) + if i<=nf + label=sprintf('Factor #%d',i); + else + label=['Interaction ' sprintf('%d*',fx{i})]; + label=label(1:end-1); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],label); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,df(i),SS(i,j),MS(i,j),F(i,j),p(i,j)); + if ~isempty(rp) || i==nfx + label=sprintf([ '%' num2str(length(label)) 's'],'Error'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\n',... + label,dfe(i),SSe(i,j),SSe(i,j)./dfe(i)); + end + end + + if ~isempty(rp) + MS_r=SSr./dfr; + F_r=squeeze(MS_r)./MSw; + p_r=1-f_cdf(F_r,dfr,dfw); + label=sprintf([ '%' num2str(length(label)) 's'],'Subjects'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,dfr,SSr(j),MS_r(j),F_r(j),p_r(j)); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],'Total'); + fprintf('%s: \t % 3.3g \t% 8.4g\n',... + label,dft,SSt(j)); + if size(p,2)>1 + fprintf([repmat('. ',1,40) '\n']) + end + + end + if j3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 (repeated measure one-way ANOVA) +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F = (1454/2)/(695.3/12) = 727/57.94 = 12.6 + + +% BETWEEN SUBJECT DESIGN WITH 2 REPLICATES +% ======================================== +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F observed = 28.283 12.393 1.973 +% F critique = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) +[p,F]=myanova(X,2,[]) + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'TRIAL x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +clear X +X(i)=x(:,1); +X=reshape(X,nl); + + + +% Two-way ANOVA from Cousineau 2007 +X= [ + 550 580 610 + 605 635 655 + 660 690 710 + ]'; + + +% Cousineau ? +X= [ + 150. 44. 71. 59. 132. 74. 1. + 335. 270. 156. 160. 118. 230. 1. + 149. 52. 91. 115. 43. 154. 1. + 159. 31. 127. 212. 71. 224. 1. + 159. 0. 35. 75. 71. 34. 1. + 292. 125. 184. 246. 225. 170. 1. + 297. 187. 66. 96. 209. 74. 1. + 170. 37. 42. 66. 114. 81. 1. + 346. 175. 177. 192. 239. 140. 2. + 426. 329. 236. 76. 102. 232. 2. + 359. 238. 183. 123. 183. 30. 2. + 272. 60. 82. 85. 101. 98. 2. + 200. 271. 263. 216. 241. 227. 2. + 366. 291. 263. 144. 220. 180. 2. + 371. 364. 270. 308. 219. 267. 2. + 497. 402. 294. 216. 284. 255. 2. + 282. 186. 225. 134. 189. 169. 3. + 317. 31. 85. 120. 131. 205. 3. + 362. 104. 144. 114. 115. 127. 3. + 338. 132. 91. 77. 108. 169. 3. + 263. 94. 141. 142. 120. 195. 3. + 138. 38. 16. 95. 39. 55. 3. + 329. 62. 62. 6. 93. 67. 3. + 292. 139. 104. 184. 193. 122. 3. + ]; +X=reshape(X(:,1:6),[8,3,6]); +X=permute(X,[1 3 2]); + +% Cousineau TQPM +X=str2num(urlread('http://www.tqmp.org/doc/vol1-1/p42.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +myanova(X,2,1:2) + +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% M1 = 11.0 M2 = 13.0 M3 = 14.2 + + +% Loftus & Masson 1994 +X= [ + 1 450 462 12 460 482 22 460 497 37 480 507 27 + 2 510 492 -18 515 530 15 520 534 14 504 550 46 + 3 492 508 16 512 522 10 503 553 50 520 539 19 + 4 524 532 8 530 543 13 517 546 29 503 553 50 + 5 420 409 -11 424 452 28 431 468 37 446 472 26 + 6 540 550 10 538 528 -10 552 575 23 562 598 36 + ]; +X=reshape(X(:,2:end),6,3,4); +X=permute(X(:,1:2,:),[2 3 1]); +% X : R vs U | SOA 50/100/200/400 | SUBJ(6) + + +%% DATA Eysenck 1974 +% http://web.uccs.edu/lbecker/Psy590/es.htm +% http://homepages.gold.ac.uk/aphome/GLM%20Simple%20Main%20Effects.html +% Counting Rhyming Adjective Imagery Intentional +X=[ + 9 7 11 12 10 + 8 9 13 11 19 + 6 6 8 16 14 + 8 6 6 11 5 + 10 6 14 9 10 + 4 11 11 23 11 + 6 6 13 12 14 + 5 3 13 10 15 + 7 8 10 19 11 + 7 7 11 11 11 + ]; + +% Eysenck 1974 OLD/YOUNG +% +X=urlread('http://forrest.psych.unc.edu/research/vista-frames/help/lecturenotes/lecture10/eysenck.xli'); +X='DATA "Eysenck" :TITLE "Eysenck" :ABOUT "Eysenck study of recall ability of subjects who were young (Y - 18-30 years old) or old (O - 55-65 years old) for recall conditions involving Counting, Rhyming, Adjectives, Imagery or Intentional. From Howell, David C., (Ed. 3) p. 325." :VARIABLES (QUOTE ("Recall" "Age" "Condition")) :TYPES (QUOTE ("Numeric" "Category" "Category")) :LABELS (QUOTE ("Obs0" "Obs1" "Obs2" "Obs3" "Obs4" "Obs5" "Obs6" "Obs7" "Obs8" "Obs9" "Obs10" "Obs11" "Obs12" "Obs13" "Obs14" "Obs15" "Obs16" "Obs17" "Obs18" "Obs19" "Obs20" "Obs21" "Obs22" "Obs23" "Obs24" "Obs25" "Obs26" "Obs27" "Obs28" "Obs29" "Obs30" "Obs31" "Obs32" "Obs33" "Obs34" "Obs35" "Obs36" "Obs37" "Obs38" "Obs39" "Obs40" "Obs41" "Obs42" "Obs43" "Obs44" "Obs45" "Obs46" "Obs47" "Obs48" "Obs49" "Obs50" "Obs51" "Obs52" "Obs53" "Obs54" "Obs55" "Obs56" "Obs57" "Obs58" "Obs59" "Obs60" "Obs61" "Obs62" "Obs63" "Obs64" "Obs65" "Obs66" "Obs67" "Obs68" "Obs69" "Obs70" "Obs71" "Obs72" "Obs73" "Obs74" "Obs75" "Obs76" "Obs77" "Obs78" "Obs79" "Obs80" "Obs81" "Obs82" "Obs83" "Obs84" "Obs85" "Obs86" "Obs87" "Obs88" "Obs89" "Obs90" "Obs91" "Obs92" "Obs93" "Obs94" "Obs95" "Obs96" "Obs97" "Obs98" "Obs99")) :DATA (QUOTE (9 "O" "C" 8 "O" "C" 6 "O" "C" 8 "O" "C" 10 "O" "C" 4 "O" "C" 6 "O" "C" 5 "O" "C" 7 "O" "C" 7 "O" "C" 7 "O" "R" 9 "O" "R" 6 "O" "R" 6 "O" "R" 6 "O" "R" 11 "O" "R" 6 "O" "R" 3 "O" "R" 8 "O" "R" 7 "O" "R" 11 "O" "A" 13 "O" "A" 8 "O" "A" 6 "O" "A" 14 "O" "A" 11 "O" "A" 13 "O" "A" 13 "O" "A" 10 "O" "A" 11 "O" "A" 12 "O" "I" 11 "O" "I" 16 "O" "I" 11 "O" "I" 9 "O" "I" 23 "O" "I" 12 "O" "I" 10 "O" "I" 19 "O" "I" 11 "O" "I" 10 "O" "IN" 19 "O" "IN" 14 "O" "IN" 5 "O" "IN" 10 "O" "IN" 11 "O" "IN" 14 "O" "IN" 15 "O" "IN" 11 "O" "IN" 11 "O" "IN" 8 "Y" "C" 6 "Y" "C" 4 "Y" "C" 6 "Y" "C" 7 "Y" "C" 6 "Y" "C" 5 "Y" "C" 7 "Y" "C" 9 "Y" "C" 7 "Y" "C" 10 "Y" "R" 7 "Y" "R" 8 "Y" "R" 10 "Y" "R" 4 "Y" "R" 7 "Y" "R" 10 "Y" "R" 6 "Y" "R" 7 "Y" "R" 7 "Y" "R" 14 "Y" "A" 11 "Y" "A" 18 "Y" "A" 14 "Y" "A" 13 "Y" "A" 22 "Y" "A" 17 "Y" "A" 16 "Y" "A" 12 "Y" "A" 11 "Y" "A" 20 "Y" "I" 16 "Y" "I" 16 "Y" "I" 15 "Y" "I" 18 "Y" "I" 16 "Y" "I" 20 "Y" "I" 22 "Y" "I" 14 "Y" "I" 19 "Y" "I" 21 "Y" "IN" 19 "Y" "IN" 17 "Y" "IN" 15 "Y" "IN" 22 "Y" "IN" 16 "Y" "IN" 22 "Y" "IN" 22 "Y" "IN" 18 "Y" "IN" 21 "Y" "IN")) :DATASHEET-ARGUMENTS (QUOTE ((420 475) (511 120) 2 8)))'; +X=strread(X, '%s', 'delimiter', ' '); +X=X(160:3:end-8) +X{1}(1)=[]; +X=str2num(strvcat(X)); +X=reshape(X,10,5,2); +X=permute(X,[3 2 1]); % AGE x COND x SUBJ + + +% Migraine Headache +% http://core.ecu.edu/psyc/wuenschk/SPSS/SPSS-Data.htm +X= [ + 21 22 8 6 6 + 20 19 10 4 9 + 7 5 5 4 5 + 25 30 13 12 4 + 30 33 10 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 13 4 8 1 5 + 26 24 14 8 17 + ]; +% Howell Table 14.3 +X= [ + 21 22 8 6 6 + 20 19 10 4 4 + 17 15 5 4 5 + 25 30 13 12 17 + 30 27 13 8 6 + 19 27 8 7 4 + 26 16 5 2 5 + 17 18 8 1 5 + 26 24 14 8 9 + ]; + + +% http://www.ou.edu/faculty/M/Jorge.L.Mendoza-1/psy5013/twoway-repeated.sas +% [Traning] [Males: Pre Post FU6 FU12] [Females: Pre Post FU6 FU12] +X = [ + 1 7 22 13 14 0 6 22 26 + 1 25 10 17 24 0 16 12 15 + 1 50 36 49 23 0 8 0 0 + 1 16 38 34 24 15 14 22 8 + 1 33 25 24 25 27 18 24 37 + 1 10 7 23 26 0 0 0 0 + 1 13 33 27 24 4 27 21 3 + 1 22 20 21 11 26 9 9 12 + 1 4 0 12 0 0 0 14 1 + 1 17 16 20 10 0 0 12 0 + 0 0 0 0 0 15 28 26 15 + 0 69 56 14 36 0 0 0 0 + 0 5 0 0 5 6 0 23 0 + 0 4 24 0 0 0 0 0 0 + 0 35 8 0 0 25 28 0 16 + 0 7 0 9 37 36 22 14 48 + 0 51 53 8 26 19 22 29 2 + 0 25 0 0 15 0 0 5 14 + 0 59 45 11 16 0 0 0 0 + 0 40 2 33 16 0 0 0 0 + ]; +X=reshape(X(:,2:end),[10,2,4 2]); +X=permute(X, [2 3 4 1]); +[p,F,fx,epsilon,pomega2,df,dfe,SS,SSe,SSt,peta2,omega2]=myanova(X,3,2) + + +% http://www.psych.northwestern.edu/help/systat/Syst.facmix.html +% subject Smoking High Stress Low Stress +% 1 light 8 1 +% 2 light 7 1 +% 3 heavy 6 8 +% 4 heavy 5 6 +% 5 light 8 3 +% 6 light 10 1 +% 7 heavy 6 7 +% 8 light 9 2 +% 9 heavy 8 10 +% 10 light 9 2 +x=[ + 1 8 1 + 1 7 1 + 2 6 8 + 2 5 6 + 1 8 3 + 1 10 1 + 2 6 7 + 1 9 2 + 2 8 10 + 1 9 2 + ]; +%X=reshape(X, +[i,nl]=dgrouping([ [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +[i,nl]=dgrouping([ [[1:10]';[1:10]'] [x(:,1);x(:,1)],[repmat(1,10,1);repmat(2,10,1)]]); +X=NaN*zeros(nl); + +%http://www.isogenic.info/html/example_2.html http://www.isogenic.info/html/example_2.html +% Strain EROD Treatm Block +x=[ + 1 18.7 1 1 + 2 17.9 1 1 + 3 19.2 1 1 + 4 26.3 1 1 + 1 7.7 2 1 + 2 8.4 2 1 + 3 9.8 2 1 + 4 9.7 2 1 + 1 16.7 1 2 + 2 14.4 1 2 + 3 12.0 1 2 + 4 19.8 1 2 + 1 6.4 2 2 + 2 6.7 2 2 + 3 8.1 2 2 + 4 6.0 2 2 + ] +[i,nl]=dgrouping(x(:,[1 3 4])) +X=NaN*zeros(nl); +X(i)=x(:,2); +%In this case a three-way ANOVA with strain and treatment being fixed +%effects (determined by the experimentalist) and the block being a random +%factor (i.e. not a specific treatment). +% +% Source DF SS MS F P +% Block 1 47.610 47.610 18.37 0.004 +% Strain 3 32.962 10.988 4.24 0.053 +% Trt 1 422.303 422.303 162.96 0.000 +% Strain*Trt 3 40.343 13.448 5.19 0.034 +% Error 7 18.140 2.591 +% Total 15 561.358 + + +% ABRDATA.TAB from OpenStat +% http://www.statpages.org/miller/openstat/Analyzing%20Data%20with%20Stats4U.pdf +% Row Col C1 C2 C3 C4 +X=[ + 1.00 1.00 18.00 14.00 12.00 6.00 + 1.00 1.00 19.00 12.00 8.00 4.00 + 1.00 1.00 14.00 10.00 6.00 2.00 + 1.00 2.00 16.00 12.00 10.00 4.00 + 1.00 2.00 12.00 8.00 6.00 2.00 + 1.00 2.00 18.00 10.00 5.00 1.00 + 2.00 1.00 16.00 10.00 8.00 4.00 + 2.00 1.00 18.00 8.00 4.00 1.00 + 2.00 1.00 16.00 12.00 6.00 2.00 + 2.00 2.00 19.00 16.00 10.00 8.00 + 2.00 2.00 16.00 14.00 10.00 9.00 + 2.00 2.00 16.00 12.00 8.00 8.00 + ]; +X=reshape(X(:,3:end), [3 2 2 4]); +X=permute(X,[2 3 4 1]); + +% SOURCE DF SS MS F PROB. +% Between Subjects 11 181.000 +% A Effects 1 10.083 10.083 0.978 0.352 +% B Effects 1 8.333 8.333 0.808 0.395 +% AB Effects 1 80.083 80.083 7.766 0.024 +% Error Between 8 82.500 10.312 +% Within Subjects 36 1077.000 +% C Replications 3 991.500 330.500 152.051 0.000 +% AC Effects 3 8.417 2.806 1.291 0.300 +% BC Effects 3 12.167 4.056 1.866 0.162 +% ABC Effects 3 12.750 4.250 1.955 0.148 +% Error Within 24 52.167 2.174 +% Total 47 1258.000 + +function [SS,df]=sumofsquares(X,f1,nf,mX) +sX=size(X); +f2=setdiff(1:nf+1,f1); +mXf = permute(X, [f1 f2 nf+2:ndims(X)]); +mXf = reshape(mXf,prod(sX(f1)),prod(sX(f2)),[]); +mXf = mean(mXf,1); +SS = mXf - repmat(mX,[1 prod(sX(f2)) 1]) +%SS = reshape(SS, prod(sX(f2)), []).^2 +SS = SS.^2 +SS = sum(sum(SS,2),1); +df = prod(sX(f1)) \ No newline at end of file diff --git a/mystats/myanova.old.2.m b/mystats/myanova.old.2.m new file mode 100644 index 0000000..f2d17b0 --- /dev/null +++ b/mystats/myanova.old.2.m @@ -0,0 +1,186 @@ +function [p,F,fx,SS,df,MS]=myanova(X,nf,rp) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf,rp) +% Performs a N-way anova on X: +% nf: number of factors +% rp: an array listing the repeated factors +% OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% Input data should be as follows: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% +% Ex: +% 2 tasks by 3 condition for 10 subjects, within subject design: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() function + +sX=size(X); +nX=ndims(X); + +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); + +if nargin<3 + rp=[]; +end +if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('Mixed designs (split plot) ANOVA unavailable!') +end +if ~isempty(rp) & nf>2 + error('Repeated measure ANOVA is only available for 2 factor designs!') +end + +% Within group stats +dfw=png*(nr-1); +mXw=mean(X,nf+1); +SSw=X-repmat(mXw,[ones(1,nf) nr 1]); +SSw=reshape(SSw, png*nr, []).^2; +SSw=sum(SSw); +MSw=squeeze(SSw/dfw); + +% Population stats +dft=(png*nr)-1; +mX=reshape(mXw, png, []); +mX=mean(mX,1); +% These are not used afterwards +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +MSt=squeeze(SSt/dft); + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,[]); + mXr=mean(mXr,2); + SSr=png*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); + SSw=SSt-SSr; +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Interaction: + % we need to remove single factor variance from the Sum of Squares + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + + if not(isempty(rp)) + % Correct Error term to account for repeated measurements + if length(j)==1 + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + SSbe(i,:)=SSe; + else + % Interaction effects residuals + % + % WARNING !!!! + % + % the following does NOT work for higher than 2 factor design! + % + dfe=(png-sum(ng-1)-1)*(nr-1) + mXe=reshape(X,png*nr,[]); + SSe=sum((mXe - repmat(mX,[nr*png 1])).^2) + SSe=SSe-SSr-sum(SSbe(1:nf,:))-sum(SS(1:nf,:)) + end + MSe=squeeze(SSe/dfe); + MSr=squeeze(SSr/dfr); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + else + F(i,:)=squeeze(MSb)./MSw; + p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + end + if nargout>4 + df(i,:)=dfb; + end + if nargout>5 + MS(i,:)=MSb; + end +end + + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +return + + +if nargout>3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + +return + + +% Examples from ZAR, pp. 250 sqq. +% +% Ex. 12.5 repeated measure ANOVA +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 +]'; + + +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) diff --git a/mystats/myanova.old.m b/mystats/myanova.old.m new file mode 100644 index 0000000..6f6dfb9 --- /dev/null +++ b/mystats/myanova.old.m @@ -0,0 +1,186 @@ +function [p,fx,F]=myanova(X,factors,repls) +% myanva - computes N-way ANOVA +% [p,fx,F]=myanova(X,factors,repls) +% factors : dimensions of factors. default: [1 2] +% repls : replications. Default [3] +% repts : repeated measures. Default [] +% +% +% If X is typically a N1 x N2 x NS matrix of a given measure for +% 2 factors across NS subjects (or replications) +% >> myanova(X) +% will say if any of the 2 factor or their interaction has a significnt +% effect on X +% +% For p factors: +% >> myanova(X,[1 2 ... p]) +% (The replications is supposed to be the p+1 dimension) +% +% The function is vectorized so that for X a N1 x N2 x NS x M measures +% >> myanova(X) +% will return a [3 by M] matrix of p values +% Idem for p factors, and X a N1 x N2 x ... Np x NS x NM matrix + +sX=size(X); + +if nargin<2 + if ndims(X)==2 + factors=1; + elseif ndims(X)==3 + factors=[1 2]; + end +end + +if nargin<3 + repls=max(factors)+1; +end + +% Number of modalities for each factor +% i.e. degrees of freedom +df=sX(factors); +% Number of replications for each factor +Nrepls=sX(repls); + +% +% % Number of observations +% N=prod([df, Nrepls]) +% dftot=N-1; + +% List of effects/interactions +nf=length(factors); +fx={}; +for i=1:nf + fx=[fx ;num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% % Reshape X for latter easier use +% if prod(sX)>prod([df Nrepls]) +% X= +% end + +N=prod([df Nrepls]); +SSw=N-prod(df(1:nf)); + +for i=1:nfx + j=fx{i}; + + if length(j)==1 + x=reshape(permute(X, [j 1:j-1 j+1:nf nf+1 nf+2]), df(j),prod(df)*Nrepls/df(j),[]); + [p(i,:),F(i,:)]=anova1(x); + else + end +end + +% +% for i=1:length(factors) +% +% mY{i}=mean(reshape(permute(X, [factors(i) 1:factors(i)-1 factors(i)+1:length(sX)]), df(i), N/df(i), []) ,2); +% sY=[ df Nrepls ]; +% sY(factors(i))=1; +% nY=prod(sY); +% +% sY=size(X); +% sY(factors(i))=[]; +% sY=[1 sY]; +% ssY=repmat(mY{i},sY) +% ssY=permute(ssY, [2:factors(i) 1 factor(i)+1:ndims(ssY)]); +% ssY=(X-ssY).^2 +% SSwithin= SSwithin + sum(reshape(ssY,N,[]),1) +% +% ssY=(squeeze(mY{i})-repmat(mX, df(i) ,1 )).^2 * nY +% SSbetween= SSbetween + sum(ssY) +% +% dfb=prod(df-1) +% Vbetween=SSbetween/dfb +% dfw=N-prod(df) +% Vwithin=SSwithin/dfw +% +% % Test whether F [ dfbetween , dfwithin ] < x +% F=Vbetween./Vwithin +% p=1-f_cdf(F,dfb,dfw) +% +% end +% +% nfx=2; + + +% Reshape output to match input format +if length(sX)>repls+1 + p=reshape(p, [ nfx sX(repls+1:end) ]); + F=reshape(F, [ nfx sX(repls+1:end) ]); +end + + + +function [p,F]=anova1(X,) +% Row-by-row One-way ANOVA +% X = [groups x replicates x ...] + +% Number of groups +ng=size(X,1); +% Number of replicates, ie. samples in each group +nr=size(X,2); + +% Between group stats +dfb=ng-1; +mXb=mean(X,2); +SSb=sum(sum((X-repmat(mXb,[1 nr 1])).^2,2),1); +MSb=SSb/dfb; + +% Population stats +dft=ng*nr-1; +mX=mean(mXb,2); +SSt=sum(sum((X-repmat(mX,[ng nr 1])).^2)); +MSt=SSt/dft; + +% Within group stats +dfw=ng*(nr-1); +mXw=mean(X,2); +SSw=sum(sum((X-repmat(mXw,[1 nr 1])).^2,2),1); +MSw=SSw/dfw; + +% SSb=SSt-SSw; +% MSb=SSb/dfb; + +% Test whether F [ dfbetween , dfwithin ] < x +F=MSb./MSw; +p=1-f_cdf(F,dfb,dfw); + +return + +function [p,F]=anova1_ok(X) +% Row-by-row One-way ANOVA +% X = [groups x replicates x ...] + +% Number of groups +ng=size(X,1); +% Number of replicates, ie. samples in each group +nr=size(X,2); + +% Between group stats +dfb=ng-1; +mXb=mean(X,2); +SSb=sum(sum((X-repmat(mXb,[1 nr 1])).^2,2),1); +MSb=SSb/dfb; + +% Population stats +dft=ng*nr-1; +mX=mean(mXb,2); +SSt=sum(sum((X-repmat(mX,[ng nr 1])).^2)); +MSt=SSt/dft; + +% Within group stats +dfw=ng*(nr-1); +mXw=mean(X,2); +SSw=sum(sum((X-repmat(mXw,[1 nr 1])).^2,2),1); +MSw=SSw/dfw; + +% SSb=SSt-SSw; +% MSb=SSb/dfb; + +% Test whether F [ dfbetween , dfwithin ] < x +F=MSb./MSw; +p=1-f_cdf(F,dfb,dfw); + +return \ No newline at end of file diff --git a/mystats/myanova1.m b/mystats/myanova1.m new file mode 100644 index 0000000..836e33f --- /dev/null +++ b/mystats/myanova1.m @@ -0,0 +1,36 @@ +function [p,F]=anova1(X) +% Row-by-row One-way ANOVA +% X = [groups x replicates x ...] + +sX=size(X); +% Number of groups +ng=sX(1); +% Number of replicates, ie. samples in each group +nr=sX(2); + +% Within group stats +dfw=ng*(nr-1); +mXw=mean(X,2); +SSw=sum(sum((X-repmat(mXw,[1 nr])).^2,2),1); +MSw=SSw/dfw; + +% Population stats +dft=ng*nr-1; +mX=mean(mXw,1); +SSt=sum(sum((X-repmat(mX,[ng nr])).^2)); +MSt=SSt/dft; + +% Between group stats +dfb=ng-1; +mXb=mean(X,1); +SSb=nr*sum(sum((mXw-repmat(mX,[ng 1])).^2,2),1); +MSb=SSb/dfb; + +% SSb=SSt-SSw; +% MSb=SSb/dfb; + +% Test whether F [ dfbetween , dfwithin ] < x +F=MSb./MSw; +p=1-f_cdf(F,dfb,dfw); + +return \ No newline at end of file diff --git a/mystats/myanova2.m b/mystats/myanova2.m new file mode 100644 index 0000000..80b93b7 --- /dev/null +++ b/mystats/myanova2.m @@ -0,0 +1,89 @@ +function [p,F,fx,SS,df,MS]=myanova(X,nf) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% Performs a N-way anova (nf is the number of factors) on X +% Ouputs p is the Null hypothesis probability, F is the F-value +% where: +% X = [group1 x group2 x ... x groupN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' dimension. + +sX=size(X); +nX=ndims(X); + +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); + +% Within group stats +dfw=prod(ng)*(nr-1); +mXw=mean(X,nf+1); +SSw=X-repmat(mXw,[ones(1,nf) nr 1]); +SSw=reshape(SSw, png*nr, []).^2; +SSw=sum(SSw); +MSw=squeeze(SSw/dfw); + +% Population stats +dft=prod(ng)*nr-1; +mX=reshape(mXw, png, []); +mX=mean(mX,1); +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +MSt=squeeze(SSt/dft); + +fx={}; +for i=1:nf + fx=[fx ;num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Multiple factors + % Subtract crossed terms from the Sum of squares + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + if nargout>4 + df(i,:)=dfb; + end + if nargout>5 + MS(i,:)=MSb; + end + + F(i,:)=squeeze(MSb)./MSw; + p(i,:)=1-f_cdf(F(i,:),dfb,dfw); +end + + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end +if nargout>3 + SS(nfx+1,:)=SSw; + SS(nfx+2,:)=SSt; +end +if nargout>4 + df(nfx+1,:)=dfw; + df(nfx+2,:)=dft; +end +if nargout>5 + MS(nfx+1,:)=MSw; + MS(nfx+2,:)=MSt; +end + +return diff --git a/mystats/myanova3.m b/mystats/myanova3.m new file mode 100644 index 0000000..36ed703 --- /dev/null +++ b/mystats/myanova3.m @@ -0,0 +1,301 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% eta: percentage of explained variance by each factor +% epsilon: sphericity correction if applicable +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated factors in a within-subject design +% rp: an array listing the repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser or Huynh-Feldt (if eGG>.7) +% +% Ex: +% 2 tasks by 3 condition for 10 subjects, within subject design: +% >> [p,F,fx]=myanova(X(1:2,1:3,1:10),2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() + +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +% Nb of cells +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +%Size of dependent variables (DV) +szd=[size(X) ones(1,nf)]; +szd=szd(nf+2:end); +% Number of DV +pszd=prod(szd); + +if nargin<3 + rp=[]; +end +if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('Mixed designs (split plot) ANOVA unavailable!') +end +if ~isempty(rp) & nf>3 + error('Repeated measure ANOVA is only available for 2 factor designs!') +end +if nargin<4 + epsilon=1; +end + +% Within Group/Error stats +mXw=sum(X,nf+1)./sX(nf+1); +SSw=X-repmat(mXw,[ones(1,nf) nr 1]); +SSw=reshape(SSw, [png*nr, szd]); +SSw=sum(SSw.^2); +if (nr>1) + dfw=png*(nr-1); + MSw=squeeze(SSw/dfw); +else + error('(my)anova doesn''t work with 1 subject / group!') +end + +% Population stats +%Total number of freedom +dft=(png*nr)-1; +mX=reshape(mXw, [png, szd]); +% Mean value of DV per subject +mX=sum(mX,1)./png; + +% Useful value: +sX2=sum(reshape(X, [png*nr, szd]),1).^2./(png*nr); + +% These are not used afterwards +SSt=sum(reshape(X, [png*nr, szd]).^2,1); +SSt=SSt-sX2; +MSt=squeeze(SSt/dft); + +error +unterminated program!!! + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,pszd); + mXr=mean(mXr,2); + % SSr=png*sum((reshape(mXr, nr, szd) - repmat(mX,[nr 1])).^2); + SSr=png*(sum(reshape(mXr, nr, szd).^2,1) - mX2); + SSw=SSt-SSr; +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Sphericity checking +if isnan(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... +if nargout > 3 + varargout{1}=epsilon; +end +if nargout > 8 + varargout{6}=SSt; +end + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Interaction: + % we need to remove single factor variance from the Sum of Squares + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + + if not(isempty(rp)) + % Correct Error term to account for repeated measurements + if length(j)==1 + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + SSbe(i,:)=SSe; + else + % Interaction effects residuals + % + % WARNING !!!! + % + % the following does NOT work for more-than-2-factors design! + % + dfe=(png-sum(ng-1)-1)*(nr-1); + mXe=reshape(X,png*nr,[]); + SSe=sum((mXe - repmat(mX,[nr*png 1])).^2); + SSe=SSe-SSr-sum(SSbe(1:nf,:))-sum(SS(1:nfx,:)); + end + MSe=squeeze(SSe/dfe); + MSr=squeeze(SSr/dfr); + dfb=dfb.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + else + dfb=dfb.*epsilon(i,:); + dfw=dfw.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSw; + p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + end + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>4 + varargout{2}(i,:)=dfb; + end + if nargout>5 + if not(isempty(rp)) + varargout{3}(i,:)=dfe; + else + varargout{3}(i,:)=dfw; + end + end + if nargout>6 + varargout{4}(i,:)=SSb; + end + if nargout>7 + if not(isempty(rp)) + varargout{5}(i,:)=SSe; + else + varargout{5}(i,:)=SSw; + end + end +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + + + +return + + +if nargout>3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 repeated measure ANOVA +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F= 727/57.94 = 12.6 + +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) + + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +% X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +% X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +% X=permute(X,[3 2 1]); +% +% [p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'COND x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + \ No newline at end of file diff --git a/mystats/myanova4.m b/mystats/myanova4.m new file mode 100644 index 0000000..3f393aa --- /dev/null +++ b/mystats/myanova4.m @@ -0,0 +1,57 @@ +function [p,F,fx,pomega2,peta2]=myanova4(X,varargin) +% Effect sizes for anova +%cf. http://psyphz.psych.wisc.edu/~shackman/olejnik_PsychMeth2003.pdf +% http://www.psy.ohio-state.edu/visionlab/lore/827/lab5_07.pdf + + +[p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(X,varargin{:}); + +eta2=SS./SSt +peta2=SS./(SSe+SS) +MSe=(SSe./dfe); +N=prod(size(X))./(df+1); +%omega2= +pomega2=(SS-df.*MSe)./(SSe+(N-dfe).*MSe) + +% MS=SS./df +% theta2=dfe*(MS-MSe)./prod(size(X)) +% theta2/(theta2+MSe) + +return + +% http://www.ats.ucla.edu/stat/stata/faq/crf24 +% http://www.ats.ucla.edu/stat/stata/faq/omega2.htm +y=[ + 3 1 1 +4 1 2 +7 1 3 +7 1 4 +1 2 1 +2 2 2 +5 2 3 +10 2 4 +6 1 1 +5 1 2 +8 1 3 +8 1 4 +2 2 1 +3 2 2 +6 2 3 +10 2 4 +3 1 1 +4 1 2 +7 1 3 +9 1 4 +2 2 1 +4 2 2 +5 2 3 +9 2 4 +3 1 1 +3 1 2 +6 1 3 +8 1 4 +2 2 1 +3 2 2 +6 2 3 +11 2 4]; +y=reshape(y(:,1),4,2,4) \ No newline at end of file diff --git a/mystats/myanova5.m b/mystats/myanova5.m new file mode 100644 index 0000000..b2d9ed2 --- /dev/null +++ b/mystats/myanova5.m @@ -0,0 +1,516 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,verbose) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% eta: percentage of explained variance by each factor +% epsilon: sphericity correction if applicable +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() + +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +if nr<2 + error('You must have more than one observation per cell/one subject per condition') +end + +if nargin<3 + rp=[]; +end +% if ~isempty(rp) & ~all(ismember(1:nf,rp)) +% error('Mixed designs (split plot) ANOVA unavailable!') +% end +% if ~isempty(rp) & nf>2 +% error('Repeated measure ANOVA is only available for 2 factor designs!') +% end +if nargin<4 + epsilon=1; +end +if nargin<5 || isempty(verbose) + verbose=1; +end +if isempty(epsilon) + epsilon=NaN; +end + +% Within Group/Error stats +% Mean in each cell +mXw=mean(X,nf+1); +% Residual Error of the model +SSe=X-repmat(mXw,[ones(1,nf) nr 1]); +SSe=reshape(SSe, png*nr, []).^2; +SSe=sum(SSe); +dfe=png*(nr-1); +MSe=squeeze(SSe/dfe); +%keeps the full model unexplained variance for later +MSw=MSe; +dfw=dfe; + +% Population stats +dft=(png*nr)-1; +% Grand mean value +mX=reshape(mXw, png, []); +mX=mean(mX,1); +% Correction factor: +% cX=mX.^2./(png*nr); + +% These are not used afterwards +SSt=sum((reshape(X, png*nr, [])-repmat(mX,[png*nr 1])).^2); +% MSt=squeeze(SSt/dft); + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,[]); + mXr=mean(mXr,2); + SSr=png*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); +end + +% Sphericity checking +if isnan(epsilon) % | ischar(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% Number of groups in between subjects +pngb=1; +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + pngb=prod(ng(~rp)); + png=png/pngb; + % Factors within first, between next + fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +end + +% Within Group/Error stats +% i.e unmodeled error +mXe=mean(X,nf+1); +SSe=X-repmat(mXe,[ones(1,nf) nr 1]); +SSe=reshape(SSe, [pnc nr svar]).^2; +SSe=sum(sum(SSe)); +if (nr<=1) + error('myanova doesn''t work with 1 subject / group!') +end +dfe=png*(nr-1); +MSe=squeeze(SSe/dfe); +dfe=repmat(dfe, [nfx 1]); + +% Population stats +dft=(pno)-1; +mX=reshape(mXe,pnc,[svar]); + varargout{1}=epsilon; +end +if nargout > 8 || verbose==1 + varargout{6}=SSt; +end + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + + if length(j)>1 + % Interaction: + % we need to remove the variance from emvbedded effects from the + % Sum of Squares of this effect + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + + if any(ismember(j,rp)) + % Correct Error term to account for repeated measurements + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + for k=1:i-1 + %remove embedded factors effects and error terms + if all(ismember(fx{k}, j)) + SSe=SSe-SS(k,:)-SSbe(k,:); + end + end + end + SSbe(i,:)=SSe; + MSe=squeeze(SSe/dfe); + % % MSr=squeeze(SSr/dfr); + % else + % dfw=png*(nr-1); + % MSw=squeeze(SSw/dfw); + % + % dfe=dfw; + % MSe=MSw; + % end + dfb=dfb.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + % dfb=dfb.*epsilon(i,:); + % dfw=dfw.*epsilon(i,:); + % F(i,:)=squeeze(MSb)./MSw; + % p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + % end + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>4 || verbose==1 + varargout{2}(i,:)=dfb; + end + if nargout>5 || verbose==1 + %if not(isempty(rp)) + varargout{3}(i,:)=dfe; + %else + % varargout{3}(i,:)=dfw; + %end + end + if nargout>6 || verbose==1 + varargout{4}(i,:)=SSb; + end + if nargout>7 || verbose==1 + %if not(isempty(rp)) + varargout{5}(i,:)=SSe; + %else + % varargout{5}(i,:)=SSw; + %end + end +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +if verbose + [ignore,df,dfe,SSb,SSe,SSt]=deal(varargout{:}); + MS=SS./df; + + %Display results + fprintf([repmat('-',1,80) '\n'] ); + fprintf(['%' num2str(max(cellfun('length', fx))*2+15) 's \t| df \t| SS \t| MS \t| F \t| p\n'], 'ANOVA results'); + fprintf([repmat('-',1,80) '\n'] ); + for j=1:min(size(p,2),3) + if size(p,2)>1 + fprintf('MULTIDIMENSIONAL DATA: [%d] ...\n',j) + end + + for i=1:length(fx) + if i<=nf + label=sprintf('Factor #%d',i); + else + label=['Interaction ' sprintf('%d*',fx{i})]; + label=label(1:end-1); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],label); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,df(i),SS(i,j),MS(i,j),F(i,j),p(i,j)); + if ~isempty(rp) || i==nfx + label=sprintf([ '%' num2str(length(label)) 's'],'Error'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\n',... + label,dfe(i),SSe(i,j),SSe(i,j)./dfe(i)); + end + end + + if ~isempty(rp) + MS_r=SSr./dfr; + F_r=squeeze(MS_r)./MSw; + p_r=1-f_cdf(F_r,dfr,dfw); + label=sprintf([ '%' num2str(length(label)) 's'],'Subjects'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,dfr,SSr(j),MS_r(j),F_r(j),p_r(j)); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],'Total'); + fprintf('%s: \t % 3.3g \t% 8.4g\n',... + label,dft,SSt(j)); + if size(p,2)>1 + fprintf([repmat('. ',1,40) '\n']) + end + + end + if j3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 (repeated measure one-way ANOVA) +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F = (1454/2)/(695.3/12) = 727/57.94 = 12.6 + + +% BETWEEN SUBJECT DESIGN WITH 2 REPLICATES +% ======================================== +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F observed = 28.283 12.393 1.973 +% F critique = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) +[p,F]=myanova(X,2,[]) + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'TRIAL x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates + +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +X(i)=x(:,1); +X=reshape(X,nl); + +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% M1 = 11.0 M2 = 13.0 M3 = 14.2 + +% Two-way ANOVA from Cousineau 2007 +X= [ + 550 580 610 + 605 635 655 + 660 690 710 + ]'; + + +% Cousineau ? +X= [ + 150. 44. 71. 59. 132. 74. 1. + 335. 270. 156. 160. 118. 230. 1. + 149. 52. 91. 115. 43. 154. 1. + 159. 31. 127. 212. 71. 224. 1. + 159. 0. 35. 75. 71. 34. 1. + 292. 125. 184. 246. 225. 170. 1. + 297. 187. 66. 96. 209. 74. 1. + 170. 37. 42. 66. 114. 81. 1. + 346. 175. 177. 192. 239. 140. 2. + 426. 329. 236. 76. 102. 232. 2. + 359. 238. 183. 123. 183. 30. 2. + 272. 60. 82. 85. 101. 98. 2. + 200. 271. 263. 216. 241. 227. 2. + 366. 291. 263. 144. 220. 180. 2. + 371. 364. 270. 308. 219. 267. 2. + 497. 402. 294. 216. 284. 255. 2. + 282. 186. 225. 134. 189. 169. 3. + 317. 31. 85. 120. 131. 205. 3. + 362. 104. 144. 114. 115. 127. 3. + 338. 132. 91. 77. 108. 169. 3. + 263. 94. 141. 142. 120. 195. 3. + 138. 38. 16. 95. 39. 55. 3. + 329. 62. 62. 6. 93. 67. 3. + 292. 139. 104. 184. 193. 122. 3. + ]; +X=reshape(X(:,1:6),[8,3,6]); +X=permute(X,[1 3 2]); + + +% Cousineau TQPM +X=str2num(urlread('http://www.tqmp.org/doc/vol1-1/p42.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +myanova(X,2,1:2) + +% Loftus & Masson 1994 +X= [ + 1 450 462 12 460 482 22 460 497 37 480 507 27 + 2 510 492 -18 515 530 15 520 534 14 504 550 46 + 3 492 508 16 512 522 10 503 553 50 520 539 19 + 4 524 532 8 530 543 13 517 546 29 503 553 50 + 5 420 409 -11 424 452 28 431 468 37 446 472 26 + 6 540 550 10 538 528 -10 552 575 23 562 598 36 + ]; +X=reshape(X(:,2:end),6,3,4); +X=permute(X(:,1:2,:),[2 3 1]); +% X : R vs U | SOA 50/100/200/400 | SUBJ(6) diff --git a/mystats/myanovaeffects.m b/mystats/myanovaeffects.m new file mode 100644 index 0000000..fd76895 --- /dev/null +++ b/mystats/myanovaeffects.m @@ -0,0 +1,27 @@ +function [fx]=myanovaeffects(nf,factornames) +% myanovaeffects - List effects and their interaction in a factorial design +% [fx]=myanovaeffects(nf) +% List main effects and interaction(s) in factorial design with [nf] factors +% [fx] is a N-by-1 cell array +% +% [fx]=myanovaeffects(nf,factornames) +% Makes up a cell list of char listing instead of the factor index, +% their names according to factornames. +% Example: +% >> myanovaeffects(2, {'FACTOR1','FACTOR2'}) +% outputs: { 'FACTOR1' 'FACTOR2' 'FACTOR1*FACTOR2' } +% +% See also: myanova +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +if nargin>1 + for i=1:length(fx) + fxn{i,1}=factornames{fx{i}(1)}; + for j=2:length(fx{i}) + fxn{i,1}=[ fxn{i} '*' factornames{fx{i}(j)}]; + end + end + fx=fxn; +end \ No newline at end of file diff --git a/mystats/myanovan.m b/mystats/myanovan.m new file mode 100644 index 0000000..964b59c --- /dev/null +++ b/mystats/myanovan.m @@ -0,0 +1,372 @@ +% Perform a multi-way analysis of variance (ANOVA). The goal is to test +% whether the population means of data taken from {k} different +% groups are all equal. +% +% Data is a single vector {data} with groups specified by +% a corresponding matrix of group labels {grps}, where {grps} +% has the same number of rows as {data}. For example, if +% {data} = [1.1;1.2]; {grps}= [1,2,1; 1,5,2]; +% then data point 1.1 was measured under conditions 1,2,1 and +% data point 1.2 was measured under conditions 1,5,2. +% Note that groups do not need to be sequentially numbered. +% +% By default, a 'linear' model is used, computing the N main effects +% with no interactions. this may be modified by param 'model' +% +% p= anovan(data,groups, 'model', modeltype) +% - modeltype = 'linear': compute N main effects +% - modeltype = 'interaction': compute N effects and +% N*(N-1) two-factor interactions +% - modeltype = 'full': compute interactions at all levels +% +% Under the null of constant means, the statistic {f} follows an F +% distribution with {df_b} and {df_e} degrees of freedom. +% +% The p-value (1 minus the CDF of this distribution at {f}) is +% returned in {pval}. +% +% If no output argument is given, the standard one-way ANOVA table is +% printed. +% +% BUG: DFE is incorrect for modeltypes != full +% @end deftypefn + +% Copyright (C) 2003-2005 Andy Adler +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2, or (at your option) +% any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place - Suite 330, Boston, MA +% 02111-1307, USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {[{pval}, {f}, {df_b}, {df_e}] =} anovan ({data}, {grps}) +% @deftypefnx {Function File} {[{pval}, {f}, {df_b}, {df_e}] =} anovan ({data}, {grps}, 'param1', {value1}) +% + +% Author: Andy Adler +% Based on code by: KH +% $Id: anovan.m,v 1.10 2005/05/30 13:04:41 adb014 Exp $ +% +% TESTING RESULTS: +% 1. ANOVA ACCURACY: www.itl.nist.gov/div898/strd/anova/anova.html +% Passes 'easy' test. Comes close on 'Average'. Fails 'Higher'. +% This could be fixed with higher precision arithmetic +% 2. Matlab anova2 test +% www.mathworks.com/access/helpdesk/help/toolbox/stats/anova2.html +% % From web site: +% popcorn= [ 5.5 4.5 3.5; 5.5 4.5 4.0; 6.0 4.0 3.0; +% 6.5 5.0 4.0; 7.0 5.5 5.0; 7.0 5.0 4.5]; +% % Define groups so reps = 3 +% groups = [ 1 1;1 2;1 3;1 1;1 2;1 3;1 1;1 2;1 3; +% 2 1;2 2;2 3;2 1;2 2;2 3;2 1;2 2;2 3 ]; +% anovan( vec(popcorn'), groups, 'model', 'full') +% % Results same as Matlab output +% 3. Matlab anovan test +% www.mathworks.com/access/helpdesk/help/toolbox/stats/anovan.html +% % From web site +% y = [52.7 57.5 45.9 44.5 53.0 57.0 45.9 44.0]'; +% g1 = [1 2 1 2 1 2 1 2]; +% g2 = {'hi';'hi';'lo';'lo';'hi';'hi';'lo';'lo'}; +% g3 = {'may'; 'may'; 'may'; 'may'; 'june'; 'june'; 'june'; 'june'}; +% anovan( y', [g1',g2',g3']) +% % Fails because we always do interactions + + +function [PVAL, FSTAT, DF_B, DFE] = anovan (data, grps, varargin) + +% if nargin <= 1 +% usage ('anovan (data, grps)'); +% end + +% test supplied parameters +modeltype= 'linear'; +for idx= 3:2:nargin + param= varargin{idx-2}; + value= varargin{idx-1}; + if strcmp(param, 'model') + modeltype= value; + % elseif strcmp(param % add other parameters here + else + error(sprintf('parameter %s is not supported', param)); + end +end + +if ~isvector (data) + error ('anova: for `anova (data, grps) data must be a vector'); +end + +nd = size (grps,1); % number of data points +nw = size (grps,2); % number of anova 'ways' +if (~ isvector (data) || (length(data) ~= nd)) + % error ('anova: grps must be a matrix of the same number of rows as data'); +end + +[g,grp_map] = relabel_groups (grps); +if strcmp(modeltype, 'linear') + max_interact = 1; +elseif strcmp(modeltype,'interaction') + max_interact = 2; +elseif strcmp(modeltype,'full') + max_interact = size(grps,1); +else + error(sprintf('modeltype %s is not supported', modeltype)); +end +ng = length(grp_map); +int_tbl = interact_tbl (nw, ng, max_interact ); +[gn, gs, gss] = raw_sums(data, g, ng, int_tbl); + +stats_tbl = int_tbl(2:size(int_tbl,1),:)>0; +nstats= size(stats_tbl,1); +stats= zeros( nstats+1, 5); % SS, DF, MS, F, p +for i= 1:nstats + [SS, DF, MS]= factor_sums( gn, gs, gss, stats_tbl(i,:), ng, nw); + stats(i,1:3)= [SS, DF, MS]; +end + +% The Mean squared error is the data - avg for each possible measurement +% This calculation doesn't work unless there is replication for all grps +% SSE= sum( gss(sel) ) - sum( gs(sel).^2 ./ gn(sel) ); +SST= gss(1) - gs(1)^2/gn(1); +SSE= SST - sum(stats(:,1)); + +% KND: Error with the following! +sel = select_pat( ones(1,nw), ng, nw); %incorrect for modeltypes != full +DFE= sum( (gn(sel)-1).*(gn(sel)>0) ); +MSE= SSE/DFE; +stats(nstats+1,1:3)= [SSE, DFE, MSE]; + +for i= 1:nstats + MS= stats(i,3); + DF= stats(i,2); + F= MS/MSE; + pval = 1 - f_cdf (F, DF, DFE); + stats(i,4:5)= [F, pval]; +end + +if nargout==0; + printout( stats, stats_tbl ); +else + PVAL= stats(1:nstats,5); + FSTAT=stats(1:nstats,4); + DF_B= stats(1:nstats,2); + DF_E= DFE; +end +return + + +% relabel groups to a mapping from 1 to ng +% Input +% grps input grouping +% Output +% g relabelled grouping +% grp_map map from output to input grouping +function [g,grp_map] = relabel_groups(grps) +grp_vec= vec(grps); +s= sort (grp_vec); +uniq = 1+[0;find(diff(s))]; +% mapping from new grps to old groups +grp_map = s(uniq); +% create new group g +ngroups= length(uniq); +g= zeros(size(grp_vec)); +for i = 1:ngroups + g( find( grp_vec== grp_map(i) ) ) = i; +end +g= reshape(g, size(grps)); +return + +% Create interaction table +% +% Input: +% nw number of 'ways' +% ng number of ANOVA groups +% max_interact maximum number of interactions to consider +% default is nw +function int_tbl =interact_tbl(nw, ng, max_interact) +combin= 2^nw; +inter_tbl= zeros( combin, nw); +idx= (0:combin-1)'; +for i=1:nw; + inter_tbl(:,i) = ( rem(idx,2^i) >= 2^(i-1) ); +end + +% find elements with more than max_interact 1's +idx = ( sum(inter_tbl',1) > max_interact ); +inter_tbl(idx,:) =[]; +combin= size(inter_tbl,1); % update value + +%scale inter_tbl +% use ng+1 to map combinations of groups to integers +% this would be lots easier with a hash data structure +int_tbl = inter_tbl .* (ones(combin,1) * (ng+1).^(0:nw-1) ); +return + +% Calculate sums for each combination +% +% Input: +% g relabelled grouping matrix +% ng number of ANOVA groups +% max_interact +% +% Output (virtual (ng+1)x(nw) matrices): +% gn number of data sums in each group +% gs sum of data in each group +% gss sumsqr of data in each group +function [gn, gs, gss] = raw_sums(data, g, ng, int_tbl); +nw= size(g,2); +ndata= size(g,1); +gn=zeros((ng+1)^nw, 1); +gs=zeros((ng+1)^nw, 1); +gss=zeros((ng+1)^nw, 1); +for i=1:ndata + % need offset by one for indexing + datapt= data(i); + idx = 1+ int_tbl*g(i,:)'; + gn(idx)=gn(idx)+1; + gs(idx)=gs(idx)+datapt; + gss(idx)=gss(idx)+datapt^2; +end +return + +% Calcualte the various factor sums +% Input: +% gn number of data sums in each group +% gs sum of data in each group +% gss sumsqr of data in each group +% select binary vector of factor for this 'way'? +% ng number of ANOVA groups +% nw number of ways + +function [SS,DF]= raw_factor_sums( gn, gs, gss, select, ng, nw); +sel= select_pat( select, ng, nw); +ss_raw= gs(sel).^2 ./ gn(sel); +SS= sum( ss_raw( ~isnan(ss_raw) )); +if length(find(select>0))==1 + DF= sum(gn(sel)>0)-1; +else + DF= 1; %this isn't the real DF, but needed to multiply +end +return + +function [SS, DF, MS]= factor_sums( gn, gs, gss, select, ng, nw); +SS=0; +DF=1; + +ff = find(select); +lff= length(ff); +% zero terms added, one term subtracted, two added, etc +for i= 0:2^lff-1 + remove= find( rem( floor( i * 2.^(-lff+1:0) ), 2) ); + sel1= select; + if ~isempty(remove) + sel1( ff( remove ) )=0; + end + [raw_sum,raw_df]= raw_factor_sums(gn,gs,gss,sel1,ng,nw); + + add_sub= (-1)^length(remove); + SS = SS + add_sub*raw_sum; + DF = DF*raw_df; +end + +MS= SS/DF; +return + +% Calcualte the various factor sums +% Input: +% select binary vector of factor for this 'way'? +% ng number of ANOVA groups +% nw number of ways +function sel= select_pat( select, ng, nw); +% if select(i) is zero, remove nonzeros +% if select(i) is zero, remove zero terms for i + +persistent field +%field=[]; + +if length(select) ~= nw; + error('length of select must be = nw'); +end +ng1= ng+1; + +if isempty(field) + % expand 0:(ng+1)^nw in base ng+1 + field= (0:(ng1)^nw-1)'* ng1.^(-nw+1:0); + field= rem( floor( field), ng1); + % select zero or non-zero elements + + %knd + field= (field>0); +end +%disp('selection pattern') %debug +sel= find( all( field == ones(ng1^nw,1)*select(:)', 2) ); + +return + + +function printout( stats, stats_tbl ); +nw= size( stats_tbl,2); +[jnk,order]= sort( sum(stats_tbl,2) ); + +fprintf('\n%d-way ANOVA Table (Factors A%s):\n\n', nw, ... + sprintf(',%c',('A')+(1:nw-1)) ); +fprintf('Source of Variation Sum Sqr df MeanSS Fval p-value\n'); +fprintf('*********************************************************************\n'); +fprintf('Error %10.2f %4d %10.2f\n', stats( size(stats,1),1:3)); + +for i= order(:)' + str= sprintf(' %c x',('A')+find(stats_tbl(i,:)>0)-1 ); + str= str(1:length(str)-2); % remove x + fprintf('Factor %15s %10.2f %4d %10.2f %7.3f %7.6f\n', ... + str, stats(i,:) ); +end +fprintf('\n'); +return + +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/14.shtml +data=[7 9 9 8 12 10 ... + 9 8 10 11 13 13 ... + 9 10 10 12 10 12]'; +grp = [1,1; 1,1; 1,2; 1,2; 1,3; 1,3; + 2,1; 2,1; 2,2; 2,2; 2,3; 2,3; + 3,1; 3,1; 3,2; 3,2; 3,3; 3,3]; +data=[7 9 9 8 12 10 9 8 ... + 9 8 10 11 13 13 10 11 ... + 9 10 10 12 10 12 10 12]'; +grp = [1,4; 1,4; 1,5; 1,5; 1,6; 1,6; 1,7; 1,7; + 2,4; 2,4; 2,5; 2,5; 2,6; 2,6; 2,7; 2,7; + 3,4; 3,4; 3,5; 3,5; 3,6; 3,6; 3,7; 3,7]; +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/9.shtml +data=[9.5 11.1 11.9 12.8 ... + 10.9 10.0 11.0 11.9 ... + 11.2 10.4 10.8 13.4]'; +grp= [1:4,1:4,1:4]'; +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/13.shtml +data=[7.56 9.68 11.65 ... + 9.98 9.69 10.69 ... + 7.23 10.49 11.77 ... + 8.22 8.55 10.72 ... + 7.59 8.30 12.36]'; +grp = [1,1;1,2;1,3; + 2,1;2,2;2,3; + 3,1;3,2;3,3; + 4,1;4,2;4,3; + 5,1;5,2;5,3]; +% Test Data from www.mathworks.com/ +% access/helpdesk/help/toolbox/stats/linear10.shtml +data=[23 27 43 41 15 17 3 9 20 63 55 90]; +grp= [ 1 1 1 1 2 2 2 2 3 3 3 3; + 1 1 2 2 1 1 2 2 1 1 2 2]'; + + + + diff --git a/mystats/permfriedman.m b/mystats/permfriedman.m new file mode 100644 index 0000000..0d6290c --- /dev/null +++ b/mystats/permfriedman.m @@ -0,0 +1,148 @@ +function [p,S0,fx,P] = permfriedman(X,nf,dim_m,NP,rp) +%PERMFRIEDMAN - Permutation test based on Friedman's ANOVA +% [pv,F,fx,P] = permfriedman(X,nf,dimM,NP,rp) +% +% Performs permutation test based on Friedman's non-parametric N-wy ANOVA +% +%INPUTS: +% X: Data matrix should be as follows: +% X = [ factor1 x factor2 x ... x factorN x Subjects x ...] +% nf: number of factors. +% dimM: Dimensions of data over which the maximum T-value is to be found. +% Default: all dimensions +% NP: Number of permutations (may lead to exhaustive permutation, +% for example if NP <= 2^N-1 using paired data) +% rp: an array listing the repeated factors +% Default: full within subject design, ie rp=1:nf +% +%OUPUTS: +% pv: p-values of the observed data, computed from the permutations +% F: the F-values of the observed data +% fx: a cell array listing the tested effects +% P: List of permutations used +% +% Example +% permfriedmann(X,2) +% +% See also; permtest2 + +% Author: Karim N'Diaye +% Created: Sep 2005 +% Copyright 2005 + + +NPERMS=1000; %Max. number of permutations + +%initialize parameters +if nf>ndims(X)-1 + error('Error Number of factors and dimensions of X don''t match!') +end +if nargin<3 + dim_m=[]; +end +if nargin<4 + NP=[]; +end +if nargin<5 + rp=[1:nf]; +end +rp=rp(:)'; +if not(isempty(rp)) & ~all(ismember(1:nf, rp)) + error('Cannot deal with spli-plot (ie. mixed) designs') +end + +sX=size(X); +ng=sX(1:nf); % nb of groups in each factor +png=prod(ng); % nb of cells +nr=sX(nf+1); % nb of subjects/repeated measures +nsX=[sX(nf+2:end) 1 1]; % shape of the data +ndX=ndims(X); + +% Default is to compute the maximum F value across all dimensions +if isempty(dim_m) + dim_m=1:ndX-nf-1; +end + +within=0; +% Now compute the number of exhaustive permutations +Nexh=inf; % I don't want to think on how to compute the perms... + +if isequal(rp,[1:nf]) + within=1; +end +exhaustive=0; +if isempty(NP) + NP=NPERMS; +end + +if NP>Nexh + warning(sprintf('Cannot do %d permutations. For this dataset, the maximum is: %d.\nThis latter value will be used.',NP, Nexh)); + NP=Nexh; + exhaustive=1; +end + +if NP>NPERMS + warning(sprintf('Too many permutations! Only %d will be performed.',NPERMS)); + NP = NPERMS; + exhaustive=0; +end + +% DEBUG: +% NP = min(500,NP); + + +% PERMUTATION LOOP +for i=0:NP + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=reshape(X,[png*nr,nsX]); + if within + [ignore,P] = sort(rand(png,nr)); + P=P+repmat([0:png:png*(nr-1)],png,1); + else + P=randperm(png*nr); + end + Y=Y(P(:),:); + Y=reshape(X,[ng,nr,nsX]); + end + + [p,Z,fx]=friedmantest(Y,nf,rp); + + + if i==0 + nfx=length(fx); + Z=reshape(Z,[nfx nsX]); + S0=Z; + sz=size(S0); + % preallocate memory + S=zeros(sz); + else + Z=reshape(Z,[nfx nsX]); + if dim_m==0 + % keep Z as it is + elseif ~isequal(dim_m,1:(ndX-nf-1)) + Z=submax(Z,dim_m+1); + else + Z=max(Z(:,:),[],2); + Z=repmat(Z,[1 sz(2:end) 1]); + end + S=S+(Z>=S0); + end +end +% Compute p-values +pv=(S+1)/(NP+1); + +return + +function [Z]=submax(Z,dims) +sZ=size(Z); +odims=setdiff(1:length(sZ),dims); +pdims=prod(sZ(dims)); +Z=permute(Z, [dims odims]); +Z=reshape(Z,[pdims, sZ(odims) 1]); +Z=max(Z,[],1); +Z=repmat(Z,[pdims 1]); +Z=reshape(Z,[sZ(dims) sZ(odims) 1]); +Z=ipermute(Z, [dims odims]); diff --git a/mystats/permtest.m b/mystats/permtest.m new file mode 100644 index 0000000..8de9204 --- /dev/null +++ b/mystats/permtest.m @@ -0,0 +1,604 @@ +function [pv,S0,NP,PS,P]=permtest(X,X2,testoptions,dim_p,dim_m,NP,TimeBar,tails,verbose,varargin) +% permtest - Generic permutation/randomization test +% +% [pv,S0,NP,PS,P] = permtest(X1,X2,{testname testparams},dim_p,dim_m,NP,TimeBar,tails) +% +% Performs a permutation test with the data +% +%MANDATORY INPUTS: +% X1,X2: [N1 x Ma x Mb...] and [ N2 x Ma x Mb x...] Multidimensional matrices +% of Ni samples/subjects for each group, eg. [ Subjects x Channel x Time ] +% Alternative input formats: +% [pv ... ] = permtest(X,D,{testname},...) +% X is a single data matrix. The two conditions are specified by +% dimension D in the matrix. +% size(X,D)=2 & X1=X(...,1,...) & X2=X(...,2,...) +% [pv ... ] = permtest(X,-N1,{...},...) +% X can be a single data matrix. But the number of samples (ie subjects) +% in the first group should be set using 'N1' (which is input as a +% negative value) +% I.e. X = [ X1 ; X2 ] & N1=size(X1,1)=nb of subjects in group 1 +% +% { testname testparams } : Name of the test statistic to use (and its +% parameters). Must be a cell or a char: +% 'ttest': Student's t-value +% 'difftest': difference of the means +% 'pseudottest': t-value with smoothed variance +% 'signtest': sign of the differences +% 'wilcoxon': signed ranks (used for paired data) +% 'edist': euclidian distance, along given dimension(s) +% Test parameters (if needed) should be given in the right order +% following testname: +% 'ttest': No parameters needed +% 'mann-whitney': No parameters needed +% 'wilcoxon': No parameters needed +% 'signtest': No parameters needed +% 'pseudottest': Needs the smooting kernel +% 'edist': Specify the dimension(s) on which distance is computed + +% You can add post-processing on a 2nd line of the cell (if none: enter []) +% 'vertconn_min': Uses the minimal statistic value of the +% neighourhoud. Vertices must be the first dimension +% of dependent variables. +% Vertex connectivity must be provided. +% +% And on a 3rd line, the post-hoc correction for multiple comparison +% across dimension(s) specified in dim_m (skipped if dim_m==0) +% 'max': (default) uses the maximal statistic value +% 'vertconn_max',vc: uses the maximum statistic across neighbours +% only (not the whole brain). It needs the vertex +% connectivity: vc +% 'quantile',p: uses the p-th quantile of data +% 'wyrm': Westfall-Young Randomization Method for multiple +% comparisons +% +% Example: +% >> permtest(x1,x2,{'ttest' [];'vertconn_min', vertconn}) +% Note that the [] is needed by matlab but is not used. +% +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : paired permutations (default) +% Use negative dim_p for unpaired samples/subjects +% dimM: Dimensions of data across which the maximum (or whatever post +% processing ) of T-value is computed. +% For multidimensional data, eg. [ Subject x Channel x Time ], +% control of Family-wise Error Rate requires to compute T-value +% across all dimensions (starting after the permuted one. +% Default is: all dimensions besides the "permuted" dimensions +% (typically: [2 3 ... ndims(X)]) +% NP: Number of permutations (may be reduced if bigger than the number of permutations, +% for example if NP > 2^N-1 using paired data) +% If not specify, permttest uses 10000 (at most). +% Set NP=inf so to enforce exhaustive permutations, ie. all possible permutations +% (this may lead to HUGE numbers of permutations, avoid with unpaired tests) +% TimeBar: 1 (default) or 0. To display a progress bar. +% tails: 1- (one: X1>X2) or 2- (two: X1X2) tailed test (default: 2) +% +%OUTPUTS: +% pv: p-values of the observed data, computed from the permutations +% (dimensions subjects and dim_m are squeezed). This is a fairly good +% approximation of the parametric test when data are normally +% distributed. But it is still valid when they are not! +% S0: [Ma x Mb...] Observed values of the statistic +% NP: Number of permutations actually performed +% PS: [P x Ma x Mb... ] Matrix of permutation statistics (may be quite big!) +% P: [NP x (N1+N2)] List of permutations used +% +% References: +% On pseudo T-value (smoothed variance): Nichols, NeuroImage, 2003[?] +% On euclidian distance: Greenblatt, Brain Topography, 2004 +% +% Authors: +% K² Team, aka. K. N'Diaye (kndiaye01yahoo.fr> & K. Jerbi (jerbichups.jussieu.fr) +% CNRS UPR640, Lab. d'imagerie cérébrale et neurosciences cognitives +% Hopital de la Salpetriere, Paris, France +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% K² 2006-02-02 Creation +% KND 2006-02-14 Added euclidian distance test ('edist') +% KND 2006-10-12 Corrected bug due to missing reshape following global stat +% ----------------------------- Script History --------------------------------- + +NMAX_UNPAIRED=15; % maximum number of observations for exhaustive search for unpaired samples +NMAX_PAIRED=30; % maximum number of observations for exhaustive search in paired samples +NMAX_SUBJECTS=1000; % Max number of subjects +NPERMS=10000; % Default number of permutations +TESTS={'ttest','difftest','pseudottest','signtest','wilcoxon','edist','cluttest', 'pairedttest'}; +PAIREDTESTS={'wilcoxon', 'mann-whitney', 'signtest', 'plusminus', 'pairedttest'}; +%Note for authors: +% 'mann-whitney' : check code below before making it available to user +% 'plusminus' : should be ok +% 'plusminus' (sum of X1>X2 along dim_m) + +%initialize parameters +if nargin<3 + error('Test Statistic need to be specified!') +end +if ischar(testoptions) + testoptions={testoptions}; +end +if ~iscell(testoptions) + error('The test to be used should be specified as char or cell!') +end +if not(ismember(testoptions{1}, TESTS)) + error('Wrong type of test! Possible test statistics are:\n%s\n', sprintf('%s ', TESTS{:})) +end +if nargin<4 + dim_p=[]; +end +if nargin<5 + dim_m=[]; +end +if nargin<6 + NP=[]; +end +if nargin<7 + TimeBar=1; % KJ, default is off now... +end +if nargin<8 + tails=2; +end +if nargin<9 + verbose=1; +end +if ~isequal(tails,1) && ~isequal(tails,2) + error('Tails can be 1 or 2') +end + +%__________________________________________________________________________ +% +%% Checking dimensions +% +if isempty(dim_p) + dim=find(size(X)>1); + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + dim=dim(1); + dim_p=dim; +end +dim=abs(dim_p); +if dim_p<0 && ~isempty(strmatch(testoptions{1}, PAIREDTESTS)) + error('Unpaired data not supported for %s statistics, are you still a Student? LOL',testoptions{1}) +end + + +%__________________________________________________________________________ +% +%% RESHAPING ORIGINAL DATA +% +% Data in X (and possibly in X2) will be concatenated (if needed) and +% reshaped so that following computations are made easier. +% Resulting size of X will be: [ (N1+N2) "dim_m"(1) "dim_m"(2) (...) ] +% i.e - subjects are put in the first dimension, group 1 above group 2 +% - data from the dimension(s) dim_m are put as the second, third... dimension of X +% - additional dimensions (tested separately, ie univariately) follow +% +ndX=ndims(X); +sX1=[size(X) 1 1]; +if numel(X2)==1 && X2>0 % X2 is the dimension of the "group factor" + X=permute(X, [ setdiff(1:dim-1,X2) dim X2 setdiff(dim+1:ndX,X2) ]); + X=reshape(X, [ sX1(setdiff(1:dim-1,X2)) sX1(dim)*2 sX1(setdiff(dim+1:ndX,X2)) 1 ]); + sX1(X2)=[]; + dim=dim-(X21 % X2 is a matrix + X2=permute(X2, [dim dX1]); + sX2=[size(X2) ones(1,ndX)]; + if ~isequal(sX(2:end), sX2(2:end)) + error('X1 and X2 should be of the same size in the non-permuted dimensions!') + end + X=cat(1,X,X2); + N=[sX(1) sX2(1)]; + clear sX2; +elseif numel(X2)==1 && X2<0 % X2 is the number of samples in the first group + X2=-X2; + N=[X2 sX(1)-X2]; +elseif numel(X2)==1 && X2>0 +else + error('Check inputs!') +end +clear X2; +X=double(X); +NS=sum(N); +if NS>NMAX_SUBJECTS + error('Too many subjects!') +end +if dim_p>0 && N(1) ~= N(2) + error('Paired data should have the same number of samples!') +end +nsX=[size(X) 1 1]; +Options.Test.InputSize=nsX; +Options.Test.OuputSize=Options.Test.InputSize; +nsX(1)=[]; +Options.Test.OuputSize(1)=[]; + + +%__________________________________________________________________________ +% +%% PREPARE DATA FOR SPECIFIC TESTS +% +Options.Test.Name=testoptions{1}; +switch(Options.Test.Name) + case {'ttest' 'pairedttest' 'difftest' 'pseudottest' 'signtest' 'wilcoxon'} + % Nothing to do + if verbose, fprintf('The %s statistic will be used\n', Options.Test.Name); end + case 'edist' + d={}; + if size(testoptions,2)>1 + d=testoptions{1,2}; + end + if isempty(d) + error('You must specify one or many dimension(s) to compute Euclidan Distance'); + elseif ismember(d, dim_m) + error('Euclidan Distance cannot use the same dimension as dim_m'); + end + d=d-(dim1 + Options.Local.Function=testoptions{2,1}; + Options.Local.Apply=1; +end +if isempty(Options.Local.Function) + Options.Local.Apply=0; +end +if Options.Local.Apply + switch Options.Local.Function + % This apply a correction factor on the statistisc by replacing + % each value by the minimum found over a neigbourhood of connected + % nodes on a mesh + case 'vertconn_min' + Options.Local.Dims=1; + Options.Local.Permute=[1:max(ndX-1,2)]; + Options.Local.Repmat=[1]; + if verbose, fprintf('Local correction using minimal statistic\n'); end + + otherwise + error('Unknown processing options: %s', Options.Local.Function) + end +end +%__________________________________________________________________________ +% +%% PROCESSING OF THE GLOBAL STATISTICS +% +if isequal(dim_m,0) + Options.Global.Apply=0; +else + %SETTING dim_m VARIABLE & SHAPE OF X ALONG IT + % Default is to compute the maximum T value across all dimensions of the + % measurement data (dim_m). + dim_m0=dim_m; + if isempty(dim_m) + dim_m=setdiff(1:ndX,dim); + end + dim_m=unique(dim_m(:))'; + if max(dim_m)>ndX + error('Wrong dim_m dimensions!') + end + if ismember(dim_p,dim_m) + error(sprintf('Wrong dim_m dimensions: [%d] is already set as the permuted dimension!\n' , dim)) + end + dim_m1=dim_m; + dim_m=dim_m-(dim_m>dim); + + Options.Global.Apply=1; + % Default: uses the global maximum + Options.Global.Function='max'; + if size(testoptions, 1)>=3 + Options.Global.Function=testoptions{3,1}; + end + if isempty(Options.Global.Function) + Options.Global.Apply=0; + end + +end +if Options.Global.Apply + switch Options.Global.Function + case {'max', 'quantile'} + switch Options.Global.Function + case 'max' + Options.Global.FunctionName='Maximum'; + case 'quantile' + Options.Global.FunctionName='Quantile'; + end + if verbose, fprintf('The %s statistic will be computed over dimensions: %s\n', Options.Global.FunctionName, sprintf('%d ', dim_m)); end + Options.Global.Dims=dim_m; + Options.Global.Permute=[dim_m setdiff([1:max(ndX-1,2)],dim_m)]; + Options.Global.Reshape=[prod(sX1(dim_m1)) nsX(setdiff(1:ndX-1, dim_m)) 1]; + Options.Global.Repmat=[ prod(sX1(dim_m1)) 1]; + case 'vertconn_max' + if verbose, fprintf('Maximum Statistic will be computed over a neighbouring vertex in dimension: %d\n', dim_m(1)); end + Options.Global.Dims=dim_m(1); + Options.Global.Permute=[dim_m setdiff([1:max(ndX-1,2)],dim_m)]; + Options.Global.Reshape=[prod(sX1(dim_m1)) nsX(setdiff(1:ndX-1, dim_m)) 1]; + Options.Global.Repmat=[ 1 1]; + case 'wyrm' + if verbose, fprintf('Westfall-Young Randomization Method for multiple comparisons will be used in dimension: %d\n', dim_m(1)); end + Options.Global.Dims=dim_m(1); + Options.Global.Permute=[dim_m setdiff([1:max(ndX-1,2)],dim_m)]; + Options.Global.Reshape=[prod(sX1(dim_m1)) nsX(setdiff(1:ndX-1, dim_m)) 1]; + Options.Global.Repmat=[ 1 1]; + otherwise + error('Unknown processing options: %s', Options.Global.Function) + end +else + if verbose, fprintf('No correction for multiple comparisons will be applied.\n'); end +end + + + + +%__________________________________________________________________________ +% +%% NUMBER OF PERMUTATIONS +% +% Now compute the number of exhaustive permutations +if dim_p>0 + if tails==2 + % We compute only one half of the permutations for paired samples + Nexh=2^(N(1)-1)-1; + else + Nexh=2^(N(1))-1; + end +else + Nexh=factorial(N(1)+N(2))/(factorial(N(1))*factorial(N(2)))-1; +end + +exhaustive=0; +if isempty(NP) + if (dim_p>0 && (N(1)+N(2))0 + msg=[ msg ' paired']; + end + msg=sprintf([ 'You are under-sampling (with %d permutations)!\nFor this dataset (with %s subjects),'... + 'the possible number of permutations is: %d.'],NP,msg,Nexh); + + warning(msg); + clear msg + end + elseif isequal(NP, inf) + if TimeBar + if verbose, disp(sprintf('You have requested exhaustive permutations: %d.',Nexh)); end + end + NP=Nexh; + exhaustive=1; + elseif NP>Nexh + if TimeBar + msg=sprintf('%d', N(1)); + if dim_p>0 + msg=[ msg ' paired']; + end + warning(sprintf([ 'You are over-sampling (with %d permutations)!\nFor this dataset (with %s subjects),'... + 'the maximum number of permutations is: %d.'],NP,msg,Nexh)); + end + elseif NP==Nexh; + exhaustive=1; + else + if NP>NPERMS + if TimeBar + warning(sprintf('So many permutations to be done (%d) may take a long time!',NP)); + end + end + end +end + + +%__________________________________________________________________________ +% +%% LIST OF PERMUTATIONS +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + P=49==(dec2bin(1:NP,N(1))); + else + % non exhaustive + P=round(rand(NP,N(1))); + end + P=[P 1-P].*N(1)+repmat(1:N(1), [NP,2]); +else + % non-paired perms + if exhaustive % do all possible perms + p=nchoosek(1:(N(1)+N(2)),N(1)); + p(1,:)=[]; % the 1st is not a permutation + for i=1:NP + P(i,:)=[p(i,:) setdiff(1:(N(1)+N(2)),p(i,:))]; + end + clear p + else % non exhaustive + [ignore,P]=sort(rand(NP,N(1)+N(2)),2); + end +end + +%__________________________________________________________________________ +% +%% DISPLAY TIMEBAR +if TimeBar + try + htimer = timebar('Permutation Statistics','Progress...'); + catch + warning('Function timebar.m missing. waitbar.m is used instead') + htimer = waitbar(0,'Permutation Statistics'); + end +else + htimer = NaN; +end + +%__________________________________________________________________________ +% +%% PERMUTATION LOOP +for i=0:NP + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:); + end + Y=reshape(Y,[Options.Test.InputSize]); + switch(testoptions{1}) + case 'ttest' + Z=tvalue(Y(1:N(1),:),Y(N(1)+(1:N(2)),:)); + case 'pairedttest' + Z=tvalue_paired(Y(1:N(1),:),Y(N(1)+(1:N(2)),:)); + case 'difftest' + Z=sum(Y(1:N(1),:),1)./N(1)-sum(Y(N(1)+(1:N(2)),:),1)./N(2); %this is to use difference of mean instead of T-statistic (KJ) + case 'pseudottest' + Z=pseudotvalue(Y(1:N(1),:),Y(N(1)+(1:N(2)),:),testoptions{1,2}); + case 'signtest' + Z=sign(Y(1:N(1),:)-Y(N(1)+(1:N(2)),:)); + Z=sum(Z,1).^2./sum(abs(Z),1); + case 'wilcoxon' + %This is the signed ranks (not sum of ranks!) + %Or almost: we don't correct by the denominator because it is + %the same for all permutations. But it should be when there is + %no ties: + % Z=sum(Z(:,:),1)./sqrt(n*(n+1)*(2*n+1)/6) + %otherwise: + % Z=sum(Z(:,:),1)./sum(abs(Z).^2,1) + Z=Y(1:N(1),:)-Y(N(1)+(1:N(2)),:); + Z=sign(Z).*tiedrank(abs(Z),1); + Z=sum(Z(:,:),1); + case 'edist' + Y=reshape(Y,Options.Test.InputSize); + Y=permute(Y,Options.Test.Permute); + Z=sqrt(sum((sum(Y(1:N(1),:,:),1)./N(1)-sum(Y(N(1)+(1:N(2)),:,:),1)./N(2)).^2,2)); + otherwise + error('No statistic comput''d!!! Check da f*** m code') + % case 'mann-whitney' + % Z=tiedrank(Y(:,:),1); + % Z=sum(Z(1:N(1),:),1); + % case 'plusminus' + % Z=sum(Y(1:N(1),:)>Y(N(1)+(1:N(2)),:),1); + end + Z=reshape(Z,[Options.Test.OuputSize]); + if i==0 + S0=Z; + end + if tails==2 + Z=abs(Z); + end + if Options.Local.Apply + switch Options.Local.Function + case 'vertconn_min' + Z=permute(Z,Options.Local.Permute); + Z=vertconn_min(Z(:,:),testoptions{2,2}); + Z=ipermute(Z,Options.Local.Permute); + Z=repmat(Z,Options.Local.Repmat); + end + Z=reshape(Z,[Options.Test.OuputSize]); %Z=reshape(Z,nsX); + end + if i==0 + if tails==2 + S0=abs(Z).*sign(S0); + else + S0=Z;%abs(Z).*sign(S0); + end + sz=size(S0); + S=zeros(sz); + if nargout>3 + try; + PS=zeros([NP sz 1],'single'); + catch + pack; + PS=zeros([NP sz 1],'single'); + end + end + else + if Options.Global.Apply + Z=permute(Z,Options.Global.Permute); + Z=reshape(Z,Options.Global.Reshape); + switch Options.Global.Function + case 'max' + [Z]=max(Z,[],1); + case 'vertconn_max' + Z=vertconn_max(Z(:,:),testoptions{3,2}); + case 'quantile' + Z=quantile(Z(:,:),testoptions{3,2}); + end + Z=repmat(Z,Options.Global.Repmat); + Z=ipermute(Z,Options.Global.Permute); + Z=reshape(Z,[Options.Test.OuputSize]); + end + + if tails==2 + S=S+(Z>=abs(S0)); + %S=S+(repmat(Z,[nsX(1) 1])>=abs(S0)); + else + S=S+(Z>=S0); + end + % If (and only if) requested, PS is output + if nargout>3 + PS(i,:)=Z(:)'; + end + if ishandle(htimer),try,if isequal(get(htimer, 'tag'), 'timebar'), timebar(htimer,i/NP),else,waitbar(i/NP,htimer);end;catch,end,end + end +end + +%% COMPUTE RESULTING P-VALUES +pv=(S+1)./(NP+1); + +%% PROCESSING OUTPUTS + +% Put back the dim_m dimension at their original place +% sX1(dim)=[]; +% pv=reshape(pv, Options.Test.OutputSize); +% S0=reshape(S0, Options.Test.OutputSize); + +if nargout>3 + PS=reshape(PS, [NP nsX]); +end +if ishandle(htimer),try,close(htimer),end,drawnow;end +return + + +%% Validation: +X1=randn(100,1); +X=X1+0.2+randn(size(X1)); +% Paired case: +[p,K,P,PS]=permttest(X1,X,1,[],999,0);p +myttest(X1,X,1,'pttest') +% Unpaired (unequal variance) +[p,K,P,PS]=permttest(X1,X,-1,[],999,0);p +myttest(X1,X,1,'uttest') \ No newline at end of file diff --git a/mystats/permtest2.m b/mystats/permtest2.m new file mode 100644 index 0000000..1d42b08 --- /dev/null +++ b/mystats/permtest2.m @@ -0,0 +1,129 @@ +function [Thd,S0,S]=mypermtest(X,X2,dimS,dimT,pS,pT,NP) +% permtest2 - BrainStorm data permutation test +% [thd,obs]=mypermtest(F1,F2,dimS,dimT,pS,pT) +% +%Inputs: +% F1,F2: data matrices. +% dimS: subject dimension (negative: unpaired test) +% dimT: Time dimension +% pS: threshold for subject-wise pemutation on temporal extent [0.05] +% pT: threshold for sample-by-sample significance [0.05] +% +%Outputs: +% thd: thresholds at the given p-values, computed from the permutations +% obs: observed value in the original data +% stt: statistics +%initialize parameters + +if nargin<5 + p1=.05; +end +if nargin<6 + pT=.05; +end +if nargin<7 + NP = 500; % max number of permutations +end +Nmax=12; % maximum number of observations for Fisher statistic + +if dimS<0 + error('Unpaired testing not implemented yet!') +end + +% ORIGINAL OBSERVATIONS +sX=size(X); +nX=length(sX); +X=permute(X, [dimS dimT setdiff(1:nX,[dimS dimT])]); +X2=permute(X2, [dimS dimT setdiff(1:nX,[dimS dimT])]); +X=cat(1,X,X2); +N= [sX(dimS) ; size(X2,dimS) ]; +clear X2; +% the shape of the measurement data +nsX=[size(X) 1]; +nsX(1)=[]; +np=size(X,1); +nt=sX(dimT); + +if max(N(:,1))Thd; + +if 0 % look in previous permutations +V=S1>repmat(Thd, [NP,1]); +for i=1:NP + p=max(piecemeal(V(i,:))); + if isempty(p),p=0;end + S2(i)=p; +end +end + +if 1 +for i=1:NP + p=max(piecemeal(V0(randperm(nt)))); + if isempty(p),p=0;end + S2(i)=p; +end +end + + + + + + return + + +function [Z]=tmax(Y1,Y2) +% default function: max of pseudo-t +% sqrt((std_PA_orig.*std_PA_orig/JA)+(std_PB_orig.*std_PB_orig/JB)); +Z=(mean(Y1)-mean(Y2)) ./ sqrt( std(Y1).*std(Y1)/size(Y1,1) + std(Y2).*std(Y2)/size(Y2,1) ); + +function [Z]=abstmax(Y1,Y2,dims) +[Z]=tmax(Y1,Y2); +Z=shiftdim(Z,2); +Z=abs(Z); +sZ=size(Z); +Z=reshape(Z,[prod(sZ(dims)), sZ(setdiff(1:length(sZ),dims))]); +Z=max(Z,[],1); + + + +% EX: +% X=rand(3,5)+cumsum(ones(3,5)) +% [th,o,ss]=mypermtest(X,1,2,[.05],500,'myanova', {1}) \ No newline at end of file diff --git a/mystats/permtest2b.m b/mystats/permtest2b.m new file mode 100644 index 0000000..1d42b08 --- /dev/null +++ b/mystats/permtest2b.m @@ -0,0 +1,129 @@ +function [Thd,S0,S]=mypermtest(X,X2,dimS,dimT,pS,pT,NP) +% permtest2 - BrainStorm data permutation test +% [thd,obs]=mypermtest(F1,F2,dimS,dimT,pS,pT) +% +%Inputs: +% F1,F2: data matrices. +% dimS: subject dimension (negative: unpaired test) +% dimT: Time dimension +% pS: threshold for subject-wise pemutation on temporal extent [0.05] +% pT: threshold for sample-by-sample significance [0.05] +% +%Outputs: +% thd: thresholds at the given p-values, computed from the permutations +% obs: observed value in the original data +% stt: statistics +%initialize parameters + +if nargin<5 + p1=.05; +end +if nargin<6 + pT=.05; +end +if nargin<7 + NP = 500; % max number of permutations +end +Nmax=12; % maximum number of observations for Fisher statistic + +if dimS<0 + error('Unpaired testing not implemented yet!') +end + +% ORIGINAL OBSERVATIONS +sX=size(X); +nX=length(sX); +X=permute(X, [dimS dimT setdiff(1:nX,[dimS dimT])]); +X2=permute(X2, [dimS dimT setdiff(1:nX,[dimS dimT])]); +X=cat(1,X,X2); +N= [sX(dimS) ; size(X2,dimS) ]; +clear X2; +% the shape of the measurement data +nsX=[size(X) 1]; +nsX(1)=[]; +np=size(X,1); +nt=sX(dimT); + +if max(N(:,1))Thd; + +if 0 % look in previous permutations +V=S1>repmat(Thd, [NP,1]); +for i=1:NP + p=max(piecemeal(V(i,:))); + if isempty(p),p=0;end + S2(i)=p; +end +end + +if 1 +for i=1:NP + p=max(piecemeal(V0(randperm(nt)))); + if isempty(p),p=0;end + S2(i)=p; +end +end + + + + + + return + + +function [Z]=tmax(Y1,Y2) +% default function: max of pseudo-t +% sqrt((std_PA_orig.*std_PA_orig/JA)+(std_PB_orig.*std_PB_orig/JB)); +Z=(mean(Y1)-mean(Y2)) ./ sqrt( std(Y1).*std(Y1)/size(Y1,1) + std(Y2).*std(Y2)/size(Y2,1) ); + +function [Z]=abstmax(Y1,Y2,dims) +[Z]=tmax(Y1,Y2); +Z=shiftdim(Z,2); +Z=abs(Z); +sZ=size(Z); +Z=reshape(Z,[prod(sZ(dims)), sZ(setdiff(1:length(sZ),dims))]); +Z=max(Z,[],1); + + + +% EX: +% X=rand(3,5)+cumsum(ones(3,5)) +% [th,o,ss]=mypermtest(X,1,2,[.05],500,'myanova', {1}) \ No newline at end of file diff --git a/mystats/skewness.m b/mystats/skewness.m new file mode 100644 index 0000000..43e2ec3 --- /dev/null +++ b/mystats/skewness.m @@ -0,0 +1,23 @@ +function [S]=skewness(X) +% skewness - computes skewness of a distribution +% [S]=skewness(X) computes row-wise skewness +% The unbiased Fisher's skewness for finite samples, a.k.a. G1, is used. +% skewness = n/(n-1)/(n-2) * sum( ((X-mean)/std)^3 ) +% Note: +% Positive skewness reflects an asymmetrical distribution with tail in positive values. +% Standard Error of skewness for normal distribution is: SES ~ sqrt(6/n) +% i.e. if abs(skew) > 2*SES, your data are significantly skewed (2 is the +% T value à.05) +% +if isvector(X) + X=X(:); +end +sz=[size(X) 1 ]; +n=sz(1); +if n<3 + error('Skewness needs sample of size > 2') +end +S=sum((X-repmat(mean(X),n,1)).^3); +S=S./(var(X).^1.5); +S=S.*(n/(n-1)/(n-2)); + \ No newline at end of file diff --git a/mystats/trimmean.m b/mystats/trimmean.m new file mode 100644 index 0000000..e77c9a0 --- /dev/null +++ b/mystats/trimmean.m @@ -0,0 +1,3 @@ +function [ output_args ] = Untitled1( input_args ) +%UNTITLED1 Summary of this function goes here +% Detailed explanation goes here diff --git a/mystats/wyrm.m b/mystats/wyrm.m new file mode 100644 index 0000000..5385c99 --- /dev/null +++ b/mystats/wyrm.m @@ -0,0 +1,50 @@ +function r = wyrm(X,Y,alpha,NP) +%WYRM - Westfall-Young Randomization Method for multiple comparisons tests +% [] = wyrm(X,alpha,N) +% +% Example +% >> wyrm +% +% See also: + +% Ref: +% Pointwise Testing with Functional Data Using the Westfall-Young Randomization Method +% http://cohesion.rice.edu/engineering/Statistics/emplibrary/lee_cox_070119.pdf + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-11-05 Creation +% +% ----------------------------- Script History --------------------------------- + +X=X(:,:); +Y=Y(:,:); + +alpha=0.05; +NP=100; + +t=tvalue(X,Y); +[to,it]=sort(-(t)); +sX=size(X); +N(1)=size(X,1); +N(2)=size(Y,1); +X=cat(1,X,Y); +[ignore,P]=sort(rand(NP,N(1)+N(2)),2); +pp=zeros([NP sX(2:end),1]); +n=prod(sX(2:end)); +for i=1:NP + t(i,:)=tvalue(X(P(i,1:N(1)),:),X(P(i,N(1)+1:end),:)); + for j=1:n + q(i,j)=max(t(i,it(j:end))); + end +end +r=sum(q<=repmat(to, [NP,1]))/NP; +j=find(r>alpha); +if ~isempty(j);j=j(1); + diff --git a/mytriplot.m b/mytriplot.m new file mode 100644 index 0000000..6e63970 --- /dev/null +++ b/mytriplot.m @@ -0,0 +1,324 @@ +function [hs, hc, contour] = triplot(pnt, dhk, val, mode, levels) + +% TRIPLOT make 2D or 3D plot of a triangulated surface and interpolated values +% the surface can be displayed with linear interpolated values or with +% linear interpolated contours of a potential distribution +% +% Use as +% triplot(pnt, dhk, value, mode, levels) +% This will make a plot of value on the surface described by triangles +% dhk with vertices pnt. The matrix dhk can be [], in which case a +% it will be computed using a delaunay triangulation. +% +% The visualization mode can be +% 'faces' plot white triangles only (value can be []) +% 'faces_skin' plot skin-colored triangles only (value can be []) +% 'face_index' plot index of each triangle (value can be []) +% 'nodes' plot black vertices only (value can be []) +% 'node_index' plot index of each vertex (value can be []) +% 'node_label' plot label of each vertex (value should be cell array) +% 'edges' plot black edges only (value can be []) +% 'surface' make interpolated plot of value on surface +% 'contour' make interpolated contour plot of value on surface +% 'contour_bw' make interpolated black-white contour plot +% 'contour_rb' make interpolated contour plot with red-blue +% +% With the optional levels, you can specify the levels at which contours will +% be plotted +% +% See also PATCH, COLORMAP, VIEW (general Matlab commands) + +% updated on Mon Jul 23 12:41:44 MET DST 2001 +% updated on Fri Jan 31 11:47:28 CET 2003 + +% Copyright (C) 2001, Robert Oostenveld +% +% $Log: triplot.m,v $ +% Revision 1.3 2004/06/28 07:51:39 roberto +% improved documentation, added faces_skin +% +% Revision 1.2 2003/03/17 10:37:29 roberto +% improved general help comments and added copyrights +% + +% start with empty return values +hs = []; +hc = []; +contour = []; + +% everything is added to the current figure +holdflag = ishold; +hold on + +% check the input variables +if ~isempty(val) + val = val(:); +end + +if nargin<4 + mode = 'surface'; +end + +if isempty(dhk) & ~strcmp(mode, 'nodes') + % no triangulation was specified but a triangulation is needed + mpnt=mean(pnt); + pnt=pnt-repmat(mpnt,size(pnt,1),1) + + if size(pnt,2)==2 + % make a 2d triangulation of the points using delaunay + dhk = delaunay(pnt(:,1), pnt(:,2)); + else + % make a 2d triangulation of the projected points using delaunay + prj = elproj(pnt); + dhk = delaunay(prj(:,1), prj(:,2)); + end + pnt=pnt+repmat(mpnt,size(pnt,1),1) + +end + +if nargin<3 + warning('only displaying triangle edges') + mode='edges'; + val = []; +elseif nargin<4 + % warning('default displaying surface') + mode='surface'; +elseif nargin<5 + % determine contour levels + if ~isempty(val) & ~iscell(val) + absmax = max(abs([min(val) max(val)])); + levels = linspace(-absmax,absmax,21); + else + levels = []; + end +end + +if isequal(mode, 'contour') | isequal(mode, 'contour_bw') | isequal(mode, 'contour_rb') + % compute contours for 2D or 3D triangulation + triangle_val = val(dhk); + triangle_min = min(triangle_val, [], 2); + triangle_max = max(triangle_val, [], 2); + + for cnt_indx=1:length(levels) + cnt = levels(cnt_indx); + use = cnt>=triangle_min & cnt<=triangle_max; + counter = 0; + intersect1 = []; + intersect2 = []; + + for tri_indx=find(use)' + pos = pnt(dhk(tri_indx,:), :); + v(1) = triangle_val(tri_indx,1); + v(2) = triangle_val(tri_indx,2); + v(3) = triangle_val(tri_indx,3); + la(1) = (cnt-v(1)) / (v(2)-v(1)); % abcissa between vertex 1 and 2 + la(2) = (cnt-v(2)) / (v(3)-v(2)); % abcissa between vertex 2 and 3 + la(3) = (cnt-v(3)) / (v(1)-v(3)); % abcissa between vertex 1 and 2 + abc(1,:) = pos(1,:) + la(1) * (pos(2,:) - pos(1,:)); + abc(2,:) = pos(2,:) + la(2) * (pos(3,:) - pos(2,:)); + abc(3,:) = pos(3,:) + la(3) * (pos(1,:) - pos(3,:)); + counter = counter + 1; + sel = find(la>=0 & la<=1); + intersect1(counter, :) = abc(sel(1),:); + intersect2(counter, :) = abc(sel(2),:); + end + + % remember the details for external reference + contour(cnt_indx).level = cnt; + contour(cnt_indx).n = counter; + contour(cnt_indx).intersect1 = intersect1; + contour(cnt_indx).intersect2 = intersect2; + end + + % collect all different contourlevels for plotting + intersect1 = []; + intersect2 = []; + cntlevel = []; + for cnt_indx=1:length(levels) + intersect1 = [intersect1; contour(cnt_indx).intersect1]; + intersect2 = [intersect2; contour(cnt_indx).intersect2]; + cntlevel = [cntlevel; ones(contour(cnt_indx).n,1) * levels(cnt_indx)]; + end + + X = [intersect1(:,1) intersect2(:,1)]'; + Y = [intersect1(:,2) intersect2(:,2)]'; + C = [cntlevel(:) cntlevel(:)]'; + + if size(pnt,2)>2 + Z = [intersect1(:,3) intersect2(:,3)]'; + else + Z = zeros(2, length(cntlevel)); + end +end + + +switch lower(mode) + +case 'faces' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the faces of the 2D or 3D triangulation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + hs = patch('Vertices', pnt, 'Faces', dhk); + set(hs, 'FaceColor', 'white'); + set(hs, 'EdgeColor', 'none'); + +case 'faces_skin' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the faces of the 2D or 3D triangulation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + skin = [255 213 119]/255; + brain = [202 100 100]/255; + cortex = [255 213 119]/255; + hs = patch('Vertices', pnt, 'Faces', dhk); + set(hs, 'FaceColor', skin); + set(hs, 'EdgeColor', 'none'); + lighting gouraud + material shiny + camlight + +case 'face_index' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the triangle indices (numbers) at each face +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + for face_indx=1:size(dhk,1) + str = sprintf('%d', face_indx); + tri_x = (pnt(dhk(face_indx,1), 1) + pnt(dhk(face_indx,2), 1) + pnt(dhk(face_indx,3), 1))/3; + tri_y = (pnt(dhk(face_indx,1), 2) + pnt(dhk(face_indx,2), 2) + pnt(dhk(face_indx,3), 2))/3; + tri_z = (pnt(dhk(face_indx,1), 3) + pnt(dhk(face_indx,2), 3) + pnt(dhk(face_indx,3), 3))/3; + h = text(tri_x, tri_y, tri_z, str, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle'); + hs = [hs; h]; + end + +case 'edges' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the edges of the 2D or 3D triangulation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + hs = patch('Vertices', pnt, 'Faces', dhk); + set(hs, 'FaceColor', 'none'); + set(hs, 'EdgeColor', 'black'); + +case 'nodes' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the nodes (vertices) only as points +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if size(pnt, 2)==2 + plot(pnt(:,1), pnt(:,2), 'k.'); + else + plot3(pnt(:,1), pnt(:,2), pnt(:,3), 'k.'); + end + +case 'node_index' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the vertex indices (numbers) at each node +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + for node_indx=1:size(pnt,1) + str = sprintf('%d', node_indx); + if size(pnt, 2)==2 + h = text(pnt(node_indx, 1), pnt(node_indx, 2), str, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle'); + else + h = text(pnt(node_indx, 1), pnt(node_indx, 2), pnt(node_indx, 3), str, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle'); + end + hs = [hs; h]; + end + +case 'node_label' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot the vertex indices (numbers) at each node +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + for node_indx=1:size(pnt,1) + str = val{node_indx}; + if ~isempty(str) + if size(pnt, 2)==2 + h = text(pnt(node_indx, 1), pnt(node_indx, 2), str, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle'); + else + h = text(pnt(node_indx, 1), pnt(node_indx, 2), pnt(node_indx, 3), str, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'middle'); + end + else + h = -1; + end + hs = [hs; h]; + end + +case 'surface' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% plot a 2D or 3D triangulated surface with linear interpolation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if length(val)==size(pnt,1) + hs = patch('Vertices', pnt, 'Faces', dhk, 'FaceVertexCData', val, 'FaceColor', 'interp'); +else + hs = patch('Vertices', pnt, 'Faces', dhk, 'CData', val, 'FaceColor', 'flat'); +end +set(hs, 'EdgeColor', 'none'); + +case 'contour_bw' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% make black-white contours +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + hc = []; + for i=1:length(cntlevel) + if cntlevel(i)>0 + linestyle = '-'; + linewidth = 1; + elseif cntlevel(i)<0 + linestyle = '--'; + linewidth = 1; + else + linestyle = '-'; + linewidth = 2; + end + h1 = patch('XData', X(:,i), 'Ydata', Y(:,i), ... + 'ZData', Z(:,i), 'CData', C(:,i), ... + 'facecolor','none','edgecolor','black', ... + 'linestyle', linestyle, 'linewidth', linewidth, ... + 'userdata',cntlevel(i)); + hc = [hc; h1]; + end + +case 'contour_rb' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% make red-blue contours +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + hc = []; + for i=1:length(cntlevel) + if cntlevel(i)>0 + edgecolor = 'red'; + elseif cntlevel(i)<0 + edgecolor = 'blue'; + else + edgecolor = 'black'; + end + h1 = patch('XData', X(:,i), 'Ydata', Y(:,i), ... + 'ZData', Z(:,i), 'CData', C(:,i), ... + 'facecolor','none','edgecolor',edgecolor, ... + 'linestyle', '-', 'linewidth', 1, ... + 'userdata',cntlevel(i)); + hc = [hc; h1]; + end + +case 'contour' +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% make full-color contours +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + hc = []; + for i=1:length(cntlevel) + h1 = patch('XData', X(:,i), 'Ydata', Y(:,i), ... + 'ZData', Z(:,i), 'CData', C(:,i), ... + 'facecolor','none','edgecolor','flat',... + 'userdata',cntlevel(i)); + hc = [hc; h1]; + end + +end % switch + +axis off +axis vis3d +axis equal + +if nargout==0 + clear contour hc hs +end + +if ~holdflag + hold off +end + diff --git a/myview_surface.m b/myview_surface.m new file mode 100644 index 0000000..54e70a8 --- /dev/null +++ b/myview_surface.m @@ -0,0 +1,47 @@ +function [hf,hs,hl] = view_surface(figname,faces,verts,cdata); +% VIEW_SURFACE Convenient function to consistently plot surfaces +% function [hf,hs,hl] = view_surface(figname,faces,verts,cdata); +% figname is the name of the figure window +% faces is the triangle listing +% verts are the corresponding vertices +% cdata is the colordata to use. If not given, uses norms of verts + +% John C. Mosher, Ph.D. See Copyright.m for information +% $Revision: 1 $ $Date: 1/24/01 5:50p $ +% ---> Karim NDIAYEs version <---- + +if(size(verts,2) > 3), % assume transposed + verts = verts'; % if the assumption is wrong, will crash below anyway +end + +if(~exist('cdata','var')), + cdata = rownorm(verts); +end + +cla +hs = patch('faces',faces,'vertices',verts,... + 'facevertexcdata',cdata(:),'facecolor','interp','edgecolor','none'); +view(2) +axis image +axis off +lighting phong + + + +material dull; +lighting phong +set(gcf, 'Color', [1 1 1 ]) +rotate3d on + +hl(1) = camlight(-20,30); +hl(2) = camlight(20,30); +hl(3) = camlight(-20,-30); +%for i = 1:length(hl), +% set(hl(i),'color',[.8 1 1]/length(hl)/1.2); % mute the intensity of the lights +%end + +if(nargout>0), + hf = h; % only if the user has output argument +end + +return diff --git a/nappe.m b/nappe.m new file mode 100644 index 0000000..8fc944d --- /dev/null +++ b/nappe.m @@ -0,0 +1,28 @@ +function h = nappe(data) +%NAPPE - One line description goes here. +% [] = nappe(input) +% +% Example +% >> nappe +% +% See also: + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2011 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2011-05-23 Creation +% +% ----------------------------- Script History --------------------------------- +s=size(data); +if sum(s>1)==2 + data=squeeze(data); +end + h = pcolor(data); +set(h, 'EdgeColor', 'none'); + +% time,1:12,nd2array(normalize(mean(data(ok,:,:,:)),'baseline',4,128:256),4)') diff --git a/nd2array.m b/nd2array.m new file mode 100644 index 0000000..93c0de5 --- /dev/null +++ b/nd2array.m @@ -0,0 +1,71 @@ +function [y]=nd2array(x,dim,sx) +% nd2array - Reshape & permute N-dimensional data to (2 dimensional) array +% +% [y]=nd2array(x,dim [,sx]) +% Permutes dimensions so that dim will be the first dimension (i.e. rows) +% of the to-be-created 2-d array. +%INPUTS: +% X: a N-dimensional matrix +% dim: dimension(s) to be put as rows. Default is to use the first non +% singleton dimension. dim can be a vector [dim1 ... dimN], in that +% case, all these dimensions will be append to form the 1st +% dimension of the output Y. +% sx: if set to [], the shape of remaining dimensions in the output will +% be preserved (i.e., equivalent to a permute) +% +% To return back to original shape, use negative dim: +% nd2array(y,-dim,size(x)); +% If dim is a scalar or if size(y,1)==1, size(x,dim) will be ignored, +% otherwise you must have: prod(size(x,dim)) == size(y,1) + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-16 Updated help +% +% ----------------------------- Script History --------------------------------- + + +if nargin<2 + dim = min(find(size(x)>1)); + if isempty(dim), dim = 1; end +end +if dim==0 + error('Dimension can''t be 0') +end +if all(dim>0) + reshape2d=1; + if nargin>2 && isempty(sx) + reshape2d=0; + end + odim=setdiff(1:max(ndims(x),dim),dim); + pd=[dim, odim]; + sx=[size(x) pd.*0+1]; + x=permute(x,pd); + if reshape2d + s2=[prod(sx(dim)) prod(sx(odim))]; + else + s2=[prod(sx(dim)) sx(odim)]; + end + y=reshape(x,s2); +elseif all(dim<0) + if nargin<3 + error('Size of the original array is needed!') + end + dim=-dim; + ndim=length(sx); + if length(dim)==1 || size(x,1)==1 + sx(dim)=size(x,1); + end + odim=setdiff(1:ndim,dim); + y=reshape(x,[sx(dim) sx(odim)]); + y=ipermute(y,[dim odim]); +else + error('You can''t mix positive and negative dim!') +end + diff --git a/ndcat.m b/ndcat.m new file mode 100644 index 0000000..95e0e85 --- /dev/null +++ b/ndcat.m @@ -0,0 +1,140 @@ +function M = ndcat(d,varargin) +%NDCAT - Assemble matrices as blocks +% [M] = ndcat(d,A,B,C,...) constructs the matrix M which is the +% concatenation of matrices A, B, C,... along dimension(s) given in d. +% NDCAT fills with zeros. +% A,B,C,... are matrices to be assembled +% d: Specify along which dimensions the concatenation should proceed +% Examples: +% d=[1 1] would place matrices in the diagonal, ie growing +% both dimension 1 (rows) and dimension 2 (columns). +% d=[0 1] would place matrices horizontally, that is without +% increasing the 1st dimension (rows) +% If d=[], default is to concatenate along the diagonal. +% If d has multiple rows, each row corresponds to the +% concatenations with the corresponding matrix in the list: +% d(1,:) specifies how B should be concatenated with A; +% d(2,:) specifies how C should then be concatenated with the +% outcome of the previous concatenation (of A and B), etc. +% d can also be provided as a cell array: d={[dB], [dC], etc} +% +% Presently, NDCAT works only with 2-D matrices +% +% Example +% >> ndcat([1 1], ones(2,3), 2*eye +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-10-30 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin==2 + M=varargin{1}; + return +end + + +%% Check input d +nm=nargin-1; +nd=0; +% sz=[]; +for i=1:nm + nd(i)=ndims(varargin{i}); + % sz(i,1:nd(i))=size(varargin{i}); +end +if iscell(d) + dd=[]; + for i=1:length(d) + dd(i,1:length(d{i}))=d{i}; + end + d=dd; +end +if isempty(d) + % where to put matrices relatively to the others + d=ones(1,max(nd)); +end +if size(d,1)==1 + d=repmat(d, [nm-1,1]); +end +if size(d,1)~=(nm-1) + error('Number of matrices and specifier ''d'' don''t match') +end +if size(d,2)==1 + d=[d ones(nm-1,max(nd)-1)]; +end + +%% recursive call +N=ndcat(d(1:end-1,:), varargin{1:end-1}); +d=d(end,:); +nn=numel(N); +sn=size(N); +dn=ndims(N); +Z=varargin{end}; +sz=size(Z); +dz=ndims(Z); +if isequal(d, [1 1]) + M=[N zeros(sn(1),sz(2)) ; zeros(sz(1),sn(2)) Z]; +elseif isequal(d, [0 1]) + M=[ [N;zeros(max(0,sz(1)-sn(1)),sn(2))] [Z;zeros(max(0,sn(1)-sz(1)),sz(2))] ] ; +elseif isequal(d, [1 0]) + M=[ [N zeros(sn(1),max(0,sz(2)-sn(2)))];[Z zeros(sz(1),max(0,sn(2)-sz(2)))] ] ; +else + error('Can''t process multidim arrays yet') + + +end + +return +if nz1 + r=r+[0:sz(j)-1]'*ones(1,sz/(sz(j)-1)); + end + idx=idx+r(:); +end +M(idx)=varargin{end}; + +return + +% nd(2)=ndims(varargin{end}); +% sz(2,1:nd(2))=size(varargin{end}); +% ne=numel(N); +%% ndx = ndx + (v-1)*k(i); +% +% for i=1:nm +% idx=[]; +% for j=1:nd(i)-1 +% z=idx +% if i==1 && j==1 +% z=1; +% end +% ne=prod(msz(1:j)) +% for k=1:sz(i,j) +% idx=[idx, z+ne*(k-1)] +% end +% end +% +% +% M(idx)=varargin{i} +% end +% +% idx \ No newline at end of file diff --git a/ndiags.m b/ndiags.m new file mode 100644 index 0000000..c9093cb --- /dev/null +++ b/ndiags.m @@ -0,0 +1,29 @@ +function [X]=ndiags(A,d) +s=[size(A)]; +if any(s~=s(1)) + error('Non square matrix') +end +n=1+prod(s(1:end-1))+sum(s(1:end-2)) +X=A(1:n:end); +return + +error('NDIAGS: Not implemented yet') +if length(d)~=2 + error('d has to be a 2 value vector') +end +if not(size(A,d(1))==size(A,d(2))) + error('Diagonalized dimensions of A have to form a square, same ') +end; + +if ndims(A)==4 + A=permute(A,[2 3 1 4]); + for i=1:size(A,d(1)) + i + a=squeeze(A(i, i, :,:)); + d(i,:,:)=a; + end + d=permute([2 1 3]); +end + + + \ No newline at end of file diff --git a/ndmultiply.m b/ndmultiply.m new file mode 100644 index 0000000..31e0c56 --- /dev/null +++ b/ndmultiply.m @@ -0,0 +1,50 @@ +function Z = ndmultiply(X,Y,dim) +%NDMULTIPLY Multiply two (matching) dimensions of N-dimension matrices +% Z = ndmultiply(X,Y,dimY) +% Computes Z = X*W(:,:) where W is a permutation of Y placing dimY in +% first position so that it match X second dimension +% i.e. size(X,2) == size(Y,dim) +% The result Z is then permuted to match Y dimensions -- except dimY, +% the one which has been multiplied and now equals to size(X,1) +% +% If Y is an array and dim > 2 and X is a N-d array, N>=2, then the +% multiplication is done "on the right side" of dimension dim of X +% i.e. size(X,dim) == size(Y,1) +% +% Example: +% X=rand(3,4);Y=rand(2,4,7); +% Z=ndmultiply(X,Y,2) +% Z will be of size 2-by-3-by-7 +% Conversely, with: +% X=rand(2,5); Y=rand(2,4,7); +% ndmultiply(Y,X,1) is of size [5,4,7] +% +% See also: nd2array + +% Author: KND +% Created: Sep 2005 +% Copyright 2005 + +if nargin<3 + dim=1; +end +if ndims(X)>=dim && ndims(Y)==2 + Z=X; + X=Y'; + Y=Z; +end +if ndims(X) == 2 + if dim > ndims(Y) + error('Cannot perform multiplication on dimension dim=%d of Y',dim) + end +else + error('Wrong inputs, check dimensions!') +end +sY=size(Y); +try + Z=X*nd2array(Y,dim); +catch + warning('Data put in double format') + Z=double(X)*double(nd2array(Y,dim)); +end +Z=nd2array(Z, -dim, sY); diff --git a/nearest.c b/nearest.c new file mode 100644 index 0000000..6beaeed --- /dev/null +++ b/nearest.c @@ -0,0 +1,84 @@ +//------------------------------------------------------------------------ +// file: nearest.c - Find nearest points according to euclidian distance +// [I,D,DD] = nearest(A,B) +// INPUTS: +// A - mxd matrix (m=number of points, d=number of dimensions) +// B - kxd matrix (k=number of points, d=number of dimensions) +// OUTPUTS: +// I - mx1 vector of matching points in B +// D - mx1 vector of distances +// D - mxk matrix of all-to-all euclidian distances +//------------------------------------------------------------------------ +#include +#include "mex.h" + +//-------------------------------------------------------------- +// function: mexFunction - Entry point from Matlab environment +// INPUTS: +// nlhs - number of left hand side arguments (outputs) +// plhs[] - pointer to table where created matrix pointers are +// to be placed +// nrhs - number of right hand side arguments (inputs) +// prhs[] - pointer to table of input matrices +//-------------------------------------------------------------- +void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray +*prhs[] ) +{ + int M,N,K; // Sizes + int m,n,k; // Loop variables + double *pA, *pB, *pI, *pD, *pDD; + + + if (nrhs < 2) + mexErrMsgTxt("Not enough input arguments."); + if (nrhs > 2) + mexErrMsgTxt("Too many input arguments."); + if (!mxIsDouble(prhs[0]) || !mxIsDouble(prhs[1])) + mexErrMsgTxt("Arguments must be type double."); + if (mxGetN(prhs[0]) != mxGetN(prhs[1])) + mexErrMsgTxt("matrix dimensions (number of columns) must agree."); + if (mxIsComplex(prhs[0]) || mxIsComplex(prhs[1])) + mexWarnMsgTxt("Complex parts ignored."); + + // edist(MxK,NxK) => MxN + M = mxGetM(prhs[0]); // Number of rows in input A + N = mxGetM(prhs[1]); // Number of rows in input B + K = mxGetN(prhs[0]); // Number of dimensions (columns of A) + + + plhs[0] = mxCreateDoubleMatrix(M,1,mxREAL); + pI = mxGetPr(plhs[0]); + plhs[1] = mxCreateDoubleMatrix(M,1,mxREAL); + pD = mxGetPr(plhs[1]); + + if (nlhs >2) + { + plhs[2] = mxCreateDoubleMatrix(M,N,mxREAL); + pDD = mxGetPr(plhs[2]); + } + + // Now the distance computation + pA = mxGetPr(prhs[0]); + pB = mxGetPr(prhs[1]); + for (m=0; m 2) + pDD[m+M*n] = sum ; + if (n==0 || (sum < pD[m])) + { + pD[m]=sum; + pI[m]=n+1; // Matab indexing + } + } + } + +} // end mexFunction() diff --git a/nearest.dll b/nearest.dll new file mode 100644 index 0000000000000000000000000000000000000000..272607acc0184c1b7b9ed9b952e3db45c7f4b2fa GIT binary patch literal 12288 zcmeHNeQ;FQbw6*l;1w*eU>Rdf@B=SKB(T+f=mRX`71DxaOG1?vLtM$rO8cZ;*bim* zEf!<1hpDE2C~IQerW2=WTDwkLPfJ=mrc=_msT`OHyS4|nZfX~>sY^ZUqM=MoY}wIh z`#bl&w|Xl%ojQ}r)Dy1e+;{HpoO|xMpYOc8>bUP1RS=OCR4fvm#FLX>w?i(MjlS5hSK4LJP=MMQ>xsr$mwiSjwR)m-92(56;WJEmMn7W zrn>?}?b1Su{I{od<;_Hcz%Pnqup6JRP7KQFaL4LL_No;lE&qk#lE| zxL=|Y*W(J}sXz7;busKmA2dZS%}-D|%cx8goG<-_5tpirsHnZqh75j*r|!4BlFe@7 zCilD2k+2%p+Xf(fSjzI*B%>EDO^qfQt|9FSyXNF48h6DsMbT#f;<>`Cg+^H~t;ACU zdf&VB=jL)fnaJW&G<#4H6~)svPtRYDTrd598G)0$flj%{{rPsM^}{CXLKM|y`4*=w zA9Om#EGKzyoa(uEFCa(Pftlz+Y`sXami>>6ZQutaa(OIY@HyM%*CLND;98@n?V(rjH|Ag^92j~DrABX8;)>de| zfv69{vB|zu(@+?lw6RXU&z=w1KJ*J8vx%|5R6gJs3rrskOpP^9=QH;FgEsb{|ET@Y z=tGZMN!@nuo}&jH#o(jXzWY(Ta$Kz*aYL)8@H@p~arCqm(tCRfYem6^YI*CU`DQyR z*r3H_-=mk0yT>oz!gdZ6dkXK*a6S8h#f8flDOfQ4)cP@+vrE|ph4tLOoSnda2W&Bm zZrRbZC$Tdf#k1(zi$AoJ=$U;ly8b~S3~T5R_@5T`2!0y;wL+WVuSM5##q3mJ3(8N~ zP>8M($aLXWMy#{QwL&G3(bF|g*#YLav#7GDE7BZ(yRn^dz^2kwf{6C<}w4e3HwjNOa`%wKsD!gZaSBk(cd*n3OjY)93oG zy_uNF2d=%S>r7T*8YcqR&=3{wLFKViV|`aIuRGHCIfk~Y6~(}{vA5mhAKmiePyXt| zH;*>Wj7{u1y5>$@fwKRS&t2PfwDIp*eJnRw%uW{WVkaeD7U>Vs!dqE!_2gB#l-v!|1--{WJqZNmD`}Aap3hYo{+}?* z#!emi8L79j_yKF-8}mfjn_+!P^!M55@0q25mzs>;X_k#mh2bnJ8QL!D#C?O3Ol60n^JSmdm0x@CasTWPd}Rl&TbdBcny}-* z@b;lICTtuS-aK^Pg#8;ZylH-E=^@zq8t9KePlLV-8V4EaRq$__%2&WogI2;1BdurO zL0<&5g1SMypg~X)Gy*yTGSaWQ&9jskX-+F)RcR3`yF+XgqIxMYvP)4rh_-25C;ZpA zt~B+7Ys=_+jfO-?tB>8t`*CkLo$SaA1#!Q$mCJ#2S}#(Z0wXcCE1eopG8y_0LMwsf zp;$VVcH( z$|#6$q(nF_Zj8JX8c@&*){)^K`^ayn*N{7DSryR+x&!$g z)Qfy0rIA*z`34fF!?t#l6g zcKR6k7pV#n$z60i@+R^kZ>C1%E!2v9Cmlk*i;fE9Tgcn!1>|?rOUUn`caXP}g!|=A zT8?}-$;f|`oXDG~0eLqyBEO5ekO#>%7{lu39um#qR(yzz`&Awnj)f{DAM*K0T;Uoz z6w0WPSds{LD591{AgQcMxJ5A`N;*xrchM2HiY^mwG)%~CKyY(lLNK1>EJHA1RIMZU zu14Ao+FXY80;wt0a`odN;3VTR7mo_8g}KSNtLC-A;tDAU<8ql=C=uq4iuJ=fY>Uq$ zq9b}OTr(j(40=LGG@WBWHsW@lYiT-9gIiUGj03s740!{HzYMtognuQNZG8sFg94Ft ze;g1l$F++@GHK&;JCJAz355pL6b_&kfp9Oh`*Noj6@-ln$q%dLN!O|C@)O~@2;(DG zL79?qk3Z66=mg8;TrgIh3%po$70ugvySjJp>Tc?gceb?$dU`vWg6&N^>T7(xJzwhS zZEtSw?Fj7SXHRg?4p*~g(pamwcM_}R6X*0(%sXO4F{%}kU29-Y?!y>rIy}xsFZg5; 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M(i,j) +% is 1 if variable i is nested in variable j. +% +% Example +% >> nestingmatrix +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-02-08 Creation +% +% ----------------------------- Script History --------------------------------- +M=zeros(nf+1); +M(rp,nf+1)=1; + + diff --git a/newdeal.m b/newdeal.m new file mode 100644 index 0000000..a544df5 --- /dev/null +++ b/newdeal.m @@ -0,0 +1,28 @@ +function varargout = newdeal(func,X,dim,varargin) +%NEWDEAL - Deal a given dimension of X as arguments to a function +% varargout = newdeal(func,X,dim,params) +% For 2-D matrix, default is to deal columns (ie. dim = 2) +% Otherwise (vectors, and N-D array, N>2) dim = first non singleton +% +% Example of use: +% PLOT3 wants coordinates as 3 separate arrays: XYZ(:,1) XYZ(:,2) XYZ(:,3) +% newdeal(@plot3,XYZ)) does it in one go + +if nargin<3 + dim = []; +end +if isempty(dim) + if ndims(X) == 2 && size(X,2)>1 + dim = 2; + else + [dim] = max([1 find(size(X)>1,1)]); + end +end +X = num2cell(X,setdiff(1:ndims(X),dim)); + +if nargout == 0 + feval(func,X{:},varargin{:}); +else + [varargout{1:nargout}] = feval(func,X{:},varargin{:}); +end +return diff --git a/noaccents.m b/noaccents.m new file mode 100644 index 0000000..19d01dd --- /dev/null +++ b/noaccents.m @@ -0,0 +1,63 @@ +function s = noaccents(s) +%NOACCENTS - Convert LATIN-1 string to ASCII (remove accents) +% [S] = noaccents(str) +% +% Example +% >> noaccents +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-08 Creation +% +% ----------------------------- Script History --------------------------------- +if iscell(s) + for i=1:numel(s) + s{i}=noaccents(s{i}); + end + return +end +if ~ischar(s) + return +end + +j=find(double(s)>127); + +LATIN1=[ + 'ÀÁÂÃÄÅÆÇÈÉÊËÌÍÎÏ'... + 'ÐÑÒÓÔÕÖ×ØÙÚÛÜÝÞß'... + 'àáâãäåæçèéêëìíîï'... + 'ðñòóôõö÷øùúûüýþÿ'... + 131 ... + 135 ... + 141 ... + 142 143 144 145 ... + 148 149 ... %î ï + 150 ... %ñ + 151 153 ... %?o ô + ]; + +ASCII=[ + 'AAAAAAACEEEEIIII'... + 'DNOOOOO*OUUUUY_S'... + 'aaaaaaaceeeeiiii'... + 'dnooooo:ouuuuy_y'... + 'E' ... + 'a' ... + 'c' ... + 'eeee' ... + 'ii' ... + 'n' ... + 'oo' ... + ]; + +[i,i]=ismember(s(j),LATIN1); +s(j(i==0))='_'; +s(j(i>0))=ASCII(i(i>0)); \ No newline at end of file diff --git a/nonempty.m b/nonempty.m new file mode 100644 index 0000000..8025412 --- /dev/null +++ b/nonempty.m @@ -0,0 +1,25 @@ +function [S,loc] = nonempty(S); +%nonempty - Non empty cells from a cell array +% nonempty(S) is a full column vector of the non-empty cells of S. +% This gives the s, but not the i and j, from [i,j,s] = find(isempty(S)). +% Warning! Even if S is a multidimensional cell array, nonempty() outputs +% a single column vector of cells. +% Example +% >> nonempty({ [] , 'a' , 3 , '' , {} , 'last' }) +% +% See also: NONZEROS + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% -------------------------- Script History ------------------------------- +% KND 2007-10-04 Creation +% +% -------------------------- Script History ------------------------------- +loc = find(~cellfun('isempty',S)); +S=S(loc); + diff --git a/nonnans.m b/nonnans.m new file mode 100644 index 0000000..9e0fd4c --- /dev/null +++ b/nonnans.m @@ -0,0 +1,45 @@ +function [S,loc,i] = nonnans(S,dim) +%nonnans - Non-NaN matrix elements. +% +% V=nonnans(S) is a full column vector of the non-nans elements of S. +% This gives the s, but not the i and j, from [i,j,s] = find(isnan(S)). +% Be aware that if S is a matrix, it outputs a single column vector. +% [V,L]=nonanas(S) also outputs indices of non-NaN values +% +% B = nonnans(A,dim) will return a matrix without the NaN's removing the +% whole rows/columns in each dimension specified in the vector [dim] +% +% Example +% >> histk +% +% See also: NONZEROS, NUMREP + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-07 Creation +% +% ----------------------------- Script History --------------------------------- +loc=find(~isnan(S)); +if nargin<2 + S=S(loc); +else + s=size(S); + i=[]; + i=find(isnan(S)); + e= ['[' sprintf('i(:,%d),',1:ndims(S)) ']=ind2sub(size(S),i);']; + eval(e) + i(:,size(i,2)+1:max(dim))=1; + for d=dim(:)' + e = ['S(' ... + repmat(':,',1,d-1) sprintf('i(:,%d)',d) repmat(',:',1,ndims(S)-d) ... + ')=[];']; + eval(e) + + end +end diff --git a/nonunique.m b/nonunique.m new file mode 100644 index 0000000..d9cb5dd --- /dev/null +++ b/nonunique.m @@ -0,0 +1,47 @@ +function [B,I] = nonunique(A,varargin) +%NONUNIQUE - Retrieves non-unique elements +% [B,I] = nonunique(A) +% [B,I] = nonunique(A, 'rows') +% +% Example +% >> nonunique +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-03 Creation +% +% ----------------------------- Script History --------------------------------- + +% Example data: +% A=flipud([0 0 1:3 3 3 4:10 13]') +% size(A), +% [b,i]=nonunique(A) +% i{:},A(cat(1,i{:})) + +[C,J,K] = unique(A,varargin{:}); +% Now find indices of nonunique elements +% First sort the indices listed in K +[k,i]=sort(K); +% 1) those where two successive location in K point to the same value of C +j=[(diff(k)==0)]; +% 2) you want only one item of each duplicate, keep the first of each +% series of repeated values +j = j & [1;[diff(diff(k))~=0]]; +% Retrieves the values they correspond to in A +B = C(K(i(j)),:); +if nargout<2 + return +end +% if requested by the user, output the indices of these duplicates +k=i(j); +for i=1:length(k) + I{i,1} = find(K==K(k(i))); +end diff --git a/normalize.m b/normalize.m new file mode 100644 index 0000000..82fb1c4 --- /dev/null +++ b/normalize.m @@ -0,0 +1,198 @@ +function [X,nX,cX] = normalize(X,P,D,varargin) +% normalize() - normalize a vector or a matrix +%[Y,nX,cX]=NORMALIZE(X,P,D) +% Vector-byvector normalization of data X +% X: vector or 2D matrix of data +% P: norm to be used, is a number [default: 2] of -inf or +inf or: +% - 'center'/'centered' set the mean to 0 +% - 'unity' range of data is linearly mapped to [0:1] +% (the signed maximum is set to 1; the signed minimum is set to 0) +% - 'rms' normalize by the rootmeansquare +% - 'z' z-transform +% - 'baseline' e.g. NORMALIZE(X,'baseline',1,[1:50]) to compute the +% baseline on the first 50 samples +% - 'baseline', dim, [samples], function, options... +% to compute baseline using a specific norm. E.g. +% normalize(X,'baseline',2,'median',[1:100]) normalize according to +% median of the 100 first samples +% +% See: norm() +% D: dimension(s) along which to normalize (default: first non singleton) +% Y: normalized data +% nX: value(s) of the norm(s) +% cX: centering value + +% if ndims(X)>2 +% error('Normalize apply only to vector or 2D-matrices') +% end +% +sX=[size(X)]; + +if nargin<3 + if max(sX)==prod(sX) + % it is a vector + [ignore, D]=max(size(X)); + else + % it is a matrix + D=1; + end +end +sX=[sX ones(1,1+length(D))]; +if nargin<2 + P=[]; +end +if isempty(P) + P=2; +end + +pX=[]; +if length(D)>1 + pX=[D setdiff(1:length(sX),D)]; + X=permute(X,pX); + X=reshape(X, prod(sX(D)), []); + D=1; +end + +[cX,nX] = normalize2(X,P,D,varargin{:}); + +nsX=size(X); +nsX(~ismember(1:length(sX),D))=1; +if ~isequal(cX,0) + if numel(cX)>1 + cX=repmat(cX,nsX); + end + X=X-cX; +end +if ~isequal(nX,1) + if numel(nX)>1 + nX=repmat(nX,nsX); + end + X=X./nX; +end +if ~isempty(pX) + X=reshape(X,sX(pX)); + X=ipermute(X,pX); +end + +return + +function [cX,nX] = normalize2(X,P,D,varargin) +sX=[size(X)]; +cX=0; +if isnumeric(P) + switch P + case inf + nX=max(abs(X),[],D); + case -inf + nX=min(abs(X),[],D); + otherwise + nX=sum(abs(X).^P,D).^(1/P); + end +else + if ischar(P) + P=lower(P); + switch P + case {'center', 'centered'} + cX=mean(X,D); + nX=.0*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'rms' + nX=sqrt(mean(abs(X).^2,D)); + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'unity' % rescale between 0 and 1 + cX=min(X,[],D); + nX=max(X,[],D)-cX; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case {'z', 'zscore', 'z-score'} + cX=mean(X,D); + nX=std(X,[],D); + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'baseline' + if nargin<4 + error('# of samples for baseline not specified!'); + end + b = varargin{1}; + if isempty(b) + b=1:sX(D); + elseif numel(b)==1 && sX(D)>100 + warning('Baseline on one sample ??? If it''s what you want...'); + end + if nargin<5 % default baseline correction is centering on mean + [cX,nX] = normalize2(subarray(X,b,D),'center',D); + else + [cX,nX] = normalize2(subarray(X,b,D),varargin{2},D,varargin{3:end}); + end + case {'(x-a)/b'} + if nargin<5 + error('a and b factors required!'); + end + cX = varargin{1}; + nX = varargin{2}; + case {'ax+b'} + if nargin<5 + error('a and b factors required!'); + end + a = varargin{1}; + b = varargin{2}; + nX=1./a; + cX=-b./a; + case 'max' % rescale between 0 and 1 + cX=max(X,[],D); + nX=0.*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'min' % rescale between 0 and 1 + cX=min(X,[],D); + nX=0.*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + + otherwise + if strcmp(P,'mean') + error('Didn''t you mean ''center'' instead of ''mean''?'); + else + error('Unknown norm: ''%s''', P); + end + end + else + % {'translation' 'scaling'} format + % e.f. ['mean' 'std'} for z-score + if length(P)<2 + error('Missing info in norm: {''translation'' ''scaling''}'); + end + if isnumeric(P{1}) + cX=X(1,:).*0+P{1}; + else + if nargin>3 + cX=feval(P{1},X,varargin{1}{1}{1:end}); + else + cX=feval(P{1},X); + end + end + if isnumeric(P{2}) + if numel(P{2})==1 + nX=cX.*0+P{2}; + else + nX=cX; + nX(:)=P{2}(:); + end + else + if nargin>3 && numel(varargin{1})>1 + nX=feval(P{2},X,varargin{1}{2}{1:end}); + else + nX=feval(P{2},X); + end + end + end +end +return \ No newline at end of file diff --git a/normalize.m~ b/normalize.m~ new file mode 100644 index 0000000..9894ea5 --- /dev/null +++ b/normalize.m~ @@ -0,0 +1,198 @@ +function [X,nX,cX] = normalize(X,P,D,varargin) +% normalize() - normalize a vector or a matrix +%[Y,nX,cX]=NORMALIZE(X,P,D) +% Vector-byvector normalization of data X +% X: vector or 2D matrix of data +% P: norm to be used, is a number [default: 2] of -inf or +inf or: +% - 'center'/'centered' set the mean to 0 +% - 'unity' range of data is linearly mapped to [0:1] +% (the signed maximum is set to 1; the signed minimum is set to 0) +% - 'rms' normalize by the rootmeansquare +% - 'z' z-transform +% - 'baseline' e.g. NORMALIZE(X,'baseline',1,[1:50]) to compute the +% baseline on the first 50 samples +% - 'baseline', dim, [samples], function, options... +% to compute baseline using a specific norm. E.g. +% normalize(X,'baseline',2,'median',[1:100]) normalize according to +% median of the 100 first samples +% +% See: norm() +% D: dimension(s) along which to normalize (default: first non singleton) +% Y: normalized data +% nX: value(s) of the norm(s) +% cX: centering value + +% if ndims(X)>2 +% error('Normalize apply only to vector or 2D-matrices') +% end +% +sX=[size(X)]; + +if nargin<3 + if max(sX)==prod(sX) + % it is a vector + [ignore, D]=max(size(X)); + else + % it is a matrix + D=1; + end +end +sX=[sX ones(1,1+length(D))]; +if nargin<2 + P=[]; +end +if isempty(P) + P=2; +end + +pX=[]; +if length(D)>1 + pX=[D setdiff(1:length(sX),D)]; + X=permute(X,pX); + X=reshape(X, prod(sX(D)), []); + D=1; +end + +[cX,nX] = normalize2(X,P,D,varargin{:}); + +nsX=size(X); +nsX(~ismember(1:length(sX),D))=1; +if ~isequal(cX,0) + if numel(cX)>1 + cX=repmat(cX,nsX); + end + X=X-cX; +end +if ~isequal(nX,1) + if numel(nX)>1 + nX=repmat(nX,nsX); + end + X=X./nX; +end +if ~isempty(pX) + X=reshape(X,sX(pX)); + X=ipermute(X,pX); +end + +return + +function [cX,nX] = normalize2(X,P,D,varargin) +sX=[size(X)]; +cX=0; +if isnumeric(P) + switch P + case inf + nX=max(abs(X),[],D); + case -inf + nX=min(abs(X),[],D); + otherwise + nX=sum(abs(X).^P,D).^(1/P); + end +else + if ischar(P) + P=lower(P); + switch P + case {'center', 'centered', 'mean'} + cX=mean(X,D); + nX=.0*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'rms' + nX=sqrt(mean(abs(X).^2,D)); + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'unity' % rescale between 0 and 1 + cX=min(X,[],D); + nX=max(X,[],D)-cX; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case {'z', 'zscore', 'z-score'} + cX=mean(X,D); + nX=std(X,[],D); + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'baseline' + if nargin<4 + error('# of samples for baseline not specified!'); + end + b = varargin{1}; + if isempty(b) + b=1:sX(D); + elseif numel(b)==1 && sX(D)>100 + warning('Baseline on one sample ??? If it''s what you want...'); + end + if nargin<5 % default baseline correction is centering on mean + [cX,nX] = normalize2(subarray(X,b,D),'center',D); + else + [cX,nX] = normalize2(subarray(X,b,D),varargin{2},D,varargin{3:end}); + end + case {'(x-a)/b'} + if nargin<5 + error('a and b factors required!'); + end + cX = varargin{1}; + nX = varargin{2}; + case {'ax+b'} + if nargin<5 + error('a and b factors required!'); + end + a = varargin{1}; + b = varargin{2}; + nX=1./a; + cX=-b./a; + case 'max' % rescale between 0 and 1 + cX=max(X,[],D); + nX=0.*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + case 'min' % rescale between 0 and 1 + cX=min(X,[],D); + nX=0.*cX+1; + if nargin>3 + error('There should be no extra argument for norm ''%s''',P); + end + + otherwise + if strcmp(P,'mean') + error('Didn''t you mean ''center'' instead of ''mean''?'); + else + error('Unknown norm: ''%s''', P); + end + end + else + % {'translation' 'scaling'} format + % e.f. ['mean' 'std'} for z-score + if length(P)<2 + error('Missing info in norm: {''translation'' ''scaling''}'); + end + if isnumeric(P{1}) + cX=X(1,:).*0+P{1}; + else + if nargin>3 + cX=feval(P{1},X,varargin{1}{1}{1:end}); + else + cX=feval(P{1},X); + end + end + if isnumeric(P{2}) + if numel(P{2})==1 + nX=cX.*0+P{2}; + else + nX=cX; + nX(:)=P{2}(:); + end + else + if nargin>3 && numel(varargin{1})>1 + nX=feval(P{2},X,varargin{1}{2}{1:end}); + else + nX=feval(P{2},X); + end + end + end +end +return \ No newline at end of file diff --git a/normalsOutFaces.m b/normalsOutFaces.m new file mode 100644 index 0000000..916b16e --- /dev/null +++ b/normalsOutFaces.m @@ -0,0 +1,35 @@ +function [normals, centroid]=normalsOutFaces(vertices, faces) +% [normals, centroid]=normalsfaces(vertices, faces) +% Normals of the (triangular) faces defined by vertices and faces % + +v=vertices(faces,:); +v=reshape(v, [size(faces, 1) 3 3]); +v1=squeeze(v(:,1,:)); +v2=squeeze(v(:,2,:)); +v3=squeeze(v(:,3,:)); + +% Position of the barycentre of each triangle +centroid = squeeze(mean(v,2)); + +% The normals to the surface of the triangle +normals=cross(v2-v1, v3-v1,2); +%surfaces = rownorm(normals)/2; % area of each triangle + +% is the orientation of the triangle in or out? +inout = sign(sum(centroid .* normals ,2)); +% Make the normals out going +normals=normals.*repmat(inout,1,3); +return + +if 0 +figure(1) +clf +plot3(vertices(faces(1,[1 2 3 1]),1),vertices(faces(1,[1 2 3 1]),2), vertices(faces(1,[1 2 3 1]),3)) +hold on +v=[centroid(1,:) ; centroid(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'rx') +v=[centroid(1,:) ; centroid(1,:) + normals(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'g') +grid on +axis equal +end \ No newline at end of file diff --git a/normalsOutVertices.m b/normalsOutVertices.m new file mode 100644 index 0000000..83c5d02 --- /dev/null +++ b/normalsOutVertices.m @@ -0,0 +1,40 @@ +function [normals, centroid]=normalsOutVertices(vertices, faces) +% [normals, centroid]=normalsOutVertices(vertices, faces) +% Normals going out of the patch, at each vertex +% + + normals=normalsvertices(vertices, faces); + + +% is the orientation of the triangle in or out? +inout = sign(sum(vertices .* normals ,2)); +% Make the normals out going +normals=normals.*repmat(inout,1,3); +return + +%v=vertices(faces,:); +%v=reshape(v, [size(faces, 1) 3 3]); +%v1=squeeze(v(:,1,:)); +%v2=squeeze(v(:,2,:)); +%v3=squeeze(v(:,3,:)); + +% Position of the barycentre of each triangle +% centroid = squeeze(mean(v,2)); + +% The normals to the surface of the triangle +% normals=cross(v2-v1, v3-v1,2); +%surfaces = rownorm(normals)/2; % area of each triangle + + +if 0 +figure(1) +clf +plot3(vertices(faces(1,[1 2 3 1]),1),vertices(faces(1,[1 2 3 1]),2), vertices(faces(1,[1 2 3 1]),3)) +hold on +v=[centroid(1,:) ; centroid(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'rx') +v=[centroid(1,:) ; centroid(1,:) + normals(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'g') +grid on +axis equal +end \ No newline at end of file diff --git a/normalsfaces.m b/normalsfaces.m new file mode 100644 index 0000000..4f8494c --- /dev/null +++ b/normalsfaces.m @@ -0,0 +1,35 @@ +function [normals, centroid]=normalsfaces(vertices, faces) +% [normals, centroid]=normalsfaces(vertices, faces) +% Normals of the (triangular) faces defined by vertices and faces % + +v=vertices(faces,:); +v=reshape(v, [size(faces, 1) 3 3]); +v1=squeeze(v(:,1,:)); +v2=squeeze(v(:,2,:)); +v3=squeeze(v(:,3,:)); + +% Position of the barycentre of each triangle +centroid = squeeze(mean(v,2)); + +% The normals to the surface of the triangle +normals=cross(v2-v1, v3-v1,2); +%surfaces = rownorm(normals)/2; % area of each triangle + +% is the orientation of the triangle in or out? +inout = sign(sum(centroid .* normals ,2)); +% Make the normals out going +% normals=normals.*repmat(inout,1,3); +return + +if 0 +figure(1) +clf +plot3(vertices(faces(1,[1 2 3 1]),1),vertices(faces(1,[1 2 3 1]),2), vertices(faces(1,[1 2 3 1]),3)) +hold on +v=[centroid(1,:) ; centroid(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'rx') +v=[centroid(1,:) ; centroid(1,:) + normals(1,:)]; +plot3(v(:,1), v(:,2), v(:,3), 'g') +grid on +axis equal +end \ No newline at end of file diff --git a/normalspatch.m b/normalspatch.m new file mode 100644 index 0000000..2c0665d --- /dev/null +++ b/normalspatch.m @@ -0,0 +1,11 @@ +function [normals]=normalspatch(vertices, faces) +% Normals at the vertices od the (triangular) faces defined by vertices and faces + +h=patch('vertices',vertices, 'faces', faces); +normals=get(h, 'VertexNormals'); +delete(h); +%normals=normals./repmat(rownorm(normals),1,3); +%inout=-sign(sum(vertices .* normals ,2)); +%normals=repmat(inout, 1,3).*normals; +return + diff --git a/normalsvertices.m b/normalsvertices.m new file mode 100644 index 0000000..28e69e7 --- /dev/null +++ b/normalsvertices.m @@ -0,0 +1,11 @@ +function [normals]=normalsvertices(vertices, faces) +% Normals at the vertices od the (triangular) faces defined by vertices and faces + +h=patch('vertices',vertices, 'faces', faces); +normals=get(h, 'VertexNormals'); +delete(h); +%normals=normals./repmat(rownorm(normals),1,3); +%inout=-sign(sum(vertices .* normals ,2)); +%normals=repmat(inout, 1,3).*normals; +return + diff --git a/normalz.m b/normalz.m new file mode 100644 index 0000000..379f852 --- /dev/null +++ b/normalz.m @@ -0,0 +1,7 @@ +function z = normalz(p, mu, sigma) +% NORMALZ Normal z-score +% >> z = normalz(p, [mu], [sigma]) +if nargin < 3, sigma = 1; end +if nargin < 2, mu = 0; end +if nargin < 1, error('Not enough input parameters.'); end +z = mu+sqrt(2)*sigma*erfinv(2*p-1); diff --git a/norminv.m b/norminv.m new file mode 100644 index 0000000..48309f3 --- /dev/null +++ b/norminv.m @@ -0,0 +1,28 @@ +function z = norminv(p,mu,sigma) +%NORMINV - Inverse Normal Law +% [z] = norminv(p,mu,sigma) +% +% Example +% >> norminv() +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-06-01 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin < 3 + sigma = 1; + if nargin < 2 + mu = 0; + end +end +z=-sqrt(2)*sigma.*erfcinv(2*p) + mu; +%z=-sqrt(2)*erfcinv(2*p); diff --git a/normminmax.m b/normminmax.m new file mode 100644 index 0000000..8a11d49 --- /dev/null +++ b/normminmax.m @@ -0,0 +1,20 @@ +function [X,mn,mx]=normminmax(X,dims) +% normminmax() - normalize a vector or a matrix to the [0 1] range +%[Y,nY]=NORMMINMAX(X) does a column-by-column normalization of data X +% Y: normalized data +if nargin<2 | isempty(dims) + dims=1; +end +if ~isequal(dims,1) + sX=[ size(X) 1 ]; + npX = setdiff(1:ndims(X), dims); + pX=[dims npX]; + X=permute(X, pX); + X=reshape(X, [ prod(sX(dims)) sX(npX) 1] ); +end +X=X-repmat(min(X), [size(X,1) 1]); +X=X./repmat(max(X), [size(X,1) 1]); +if ~isequal(dims,1) + X=reshape(X, [ sX(dims) sX(npX) 1] ); + X=ipermute(X, pX); +end \ No newline at end of file diff --git a/nth.m b/nth.m new file mode 100644 index 0000000..a16ae42 --- /dev/null +++ b/nth.m @@ -0,0 +1,16 @@ +function [x]=nth(a,varargin) +%Nth : N-th element in an array +% +% [x]=nth(a,varargin) +% +% Useful for 'pipeing' i.e. input-output redirection. +% e.g. fun1() returns an array, but you want fun2() to use the k-th value +% returned by fun1() : disp(fun2(nth(fun1(x), k))) +if nargin<2 + error(('no')) +end +if all(cellfun('isreal',varargin)) + x=a(varargin{:}); +else + x=eval(['a(' varargin{:} ')']); +end \ No newline at end of file diff --git a/numrep.m b/numrep.m new file mode 100644 index 0000000..3c8d6bb --- /dev/null +++ b/numrep.m @@ -0,0 +1,45 @@ +function Y = numrep(X,varargin) +%numrep() - Replace numerical value with another +% [Y] = numrep(X,p,q) replaces p's in X with q's +% Works with p=NaN (as well as p=+Inf, and p=-Inf) +% p may be an array so that all of these values will be replaced by q +% [Y] = numrep(X,[p1 p2],q1 , p3,q3) works also +% +% See also: strrep + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-12 Creation +% KND 2006-10-23 Added possibility to replace multiple p values at once +% KND 2009-10-22 Logical array are converted to double if needed (+warning) +% ----------------------------- Script History --------------------------------- + +Y=X; +p=varargin(1:2:end); +q=varargin(2:2:end); +for i=1:length(p) + while ~isempty(p{i}) + if isnan(p{i}(1)) + Y(isnan(X))=q{i}; + else + try + Y(X==p{i}(1))=q{i}; + catch ME + if isequal(ME.identifier, 'MATLAB:nologicalnan') + warning('numrep:NAnintoLogical','numrep:Logical array is converted to double to incoporate NaN''s.'); + Y=double(Y); + Y(X==p{i}(1))=q{i}; + else + rethrow(ME) + end + end + end + p{i}(1)=[]; + end +end \ No newline at end of file diff --git a/octave/fminunc.m b/octave/fminunc.m new file mode 100644 index 0000000..79d09ba --- /dev/null +++ b/octave/fminunc.m @@ -0,0 +1,426 @@ +% [x,v,flag,out,df,d2f] = fminunc (f,x,opt,...) - M*tlab-like optimization +% +% Imitation of m*tlab's fminunc(). The optional 'opt' argument is a struct, +% e.g. produced by 'optimset()'. +% +% Supported options +% ----------------- +% Diagnostics, [off|on] : Be verbose +% Display , [off|iter|notify|final] +% : Be verbose unless value is "off" +% GradObj , [off|on] : Function's 2nd return value is derivatives +% Hessian , [off|on] : Function's 2nd and 3rd return value are +% derivatives and Hessian. +% TolFun , scalar : Termination criterion (see 'ftol' in minimize()) +% TolX , scalar : Termination criterion (see 'utol' in minimize()) +% MaxFunEvals, int : Max. number of function evaluations +% MaxIter , int : Max. number of algorithm iterations +% +% These non-m*tlab are provided to facilitate porting code to octave: +% ----------------------- +% "MinEquiv" , [off|on] : Don't minimize 'fun', but instead return the +% option passed to minimize(). +% +% "Backend" , [off|on] : Don't minimize 'fun', but instead return +% [backend, opt], the name of the backend +% optimization function that is used and the +% optional arguments that will be passed to it. See +% the 'backend' option of minimize(). +% +% This function is a front-end to minimize(). + + +% Copyright (C) 2008, 2009 VZLU Prague, a.s. +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 3 of the License, or (at +% your option) any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, see +% . +% +% Author: Jaroslav Hajek + +% -*- texinfo -*- +% @deftypefn{Function File} {} fminunc (@var{fcn}, @var{x0}, @var{options}) +% @deftypefnx{Function File} {[@var{x}, @var{fvec}, @var{info}, @var{output}, @var{grad}, @var{hess}]} = fminunc (@var{fcn}, @dots{}) +% Solve a unconstrained optimization problem defined by the function @var{fcn}. +% @var{fcn} should accepts a vector (array) defining the unknown variables, +% and return the objective function value, optionally with gradient. +% In other words, this function attempts to determine a vector @var{x} such +% +% that @code{@var{fcn} (@var{x})} is a local minimum. +% @var{x0} determines a starting guess. The shape of @var{x0} is preserved +% in all calls to @var{fcn}, but otherwise it is treated as a column vector. +% @var{options} is a structure specifying additional options. +% Currently, @code{fminunc} recognizes these options: +% @code{'FunValCheck'}, @code{'OutputFcn'}, @code{'TolX'}, +% @code{'TolFun'}, @code{'MaxIter'}, @code{'MaxFunEvals'}, +% @code{'GradObj'}, @code{'FinDiffType'}. +% +% If @code{'GradObj'} is @code{'on'}, it specifies that @var{fcn}, +% called with 2 output arguments, also returns the Jacobian matrix +% of right-hand sides at the requested point. @code{'TolX'} specifies +% the termination tolerance in the unknown variables, while +% @code{'TolFun'} is a tolerance for equations. Default is @code{1e-7} +% for both @code{'TolX'} and @code{'TolFun'}. +% +% For description of the other options, see @code{optimset}. +% +% On return, @var{fval} contains the value of the function @var{fcn} +% evaluated at @var{x}, and @var{info} may be one of the following values: +% +% @table @asis +% @item 1 +% Converged to a solution point. Relative gradient error is less than specified +% by TolFun. +% @item 2 +% Last relative step size was less that TolX. +% @item 3 +% Last relative decrease in func value was less than TolF. +% @item 0 +% Iteration limit exceeded. +% @item -3 +% The trust region radius became excessively small. +% @end table +% +% Optionally, fminunc can also yield a structure with convergence statistics +% (@var{output}), the output gradient (@var{grad}) and approximate hessian +% (@var{hess}). +% +% Note: If you only have a single nonlinear equation of one variable, using +% @code{fminbnd} is usually a much better idea. +% @seealso{fminbnd, optimset} +% @end deftypefn + +% PKG_ADD: all_opts ('fminunc'); + +function [x, fval, info, output, grad, hess] = fminunc (fcn, x0, options) +if nargin<3 + options = struct (); +end +% Get default options if requested. +if (nargin == 1 && ischar (fcn) && strcmp (fcn, 'defaults')) + x = optimset ('MaxIter', 400, 'MaxFunEvals', Inf, ... + 'GradObj', 'off', 'TolX', 1.5e-8, 'TolFun', 1.5e-8, ... + 'OutputFcn', [], 'FunValCheck', 'off', ... + 'FinDiffType', 'central'); + return; +end + +if (nargin < 2 || nargin > 3 || ~ ismatrix (x0)) + print_usage (); +end + +if (ischar (fcn)) + fcn = str2func (fcn, 'global'); +end + +xsiz = size (x0); +n = numel (x0); + +has_grad = strcmpi (optimget (options, 'GradObj', 'off'), 'on'); +cdif = strcmpi (optimget (options, 'FinDiffType', 'central'), 'central'); +maxiter = optimget (options, 'MaxIter', 400); +maxfev = optimget (options, 'MaxFunEvals', Inf); +outfcn = optimget (options, 'OutputFcn'); + +funvalchk = strcmpi (optimget (options, 'FunValCheck', 'off'), 'on'); + +if (funvalchk) + % Replace fcn with a guarded version. + fcn = @(x) guarded_eval (fcn, x); +end + +% These defaults are rather stringent. I think that normally, user +% prefers accuracy to performance. + +macheps = eps (class (x0)); + +tolx = optimget (options, 'TolX', sqrt (macheps)); +tolf = optimget (options, 'TolFun', sqrt (macheps)); + +factor = 0.1; +% FIXME: TypicalX corresponds to user scaling (???) +autodg = true; + +niter = 1; +nfev = 0; + +x = x0(:); +info = 0; + +% Initial evaluation. +fval = fcn (reshape (x, xsiz)); +n = length (x); + +if (~isempty (outfcn)) + optimvalues.iter = niter; + optimvalues.funccount = nfev; + optimvalues.fval = fval; + optimvalues.searchdirection = zeros (n, 1); + state = 'init'; + stop = outfcn (x, optimvalues, state); + if (stop) + info = -1; + break; + end +end + +nsuciter = 0; +lastratio = 0; + +grad = []; + +% Outer loop. +while (niter < maxiter && nfev < maxfev && ~ info) + + grad0 = grad; + + % Calculate function value and gradient (possibly via FD). + if (has_grad) + [fval, grad] = fcn (reshape (x, xsiz)); + grad = grad(:); + nfev =nfev + 1; + else + grad = fdjac (fcn, reshape (x, xsiz), fval, cdif)(:); + nfev = nfev + (1 + cdif) * length (x); + end + + if (niter == 1) + % Initialize by identity matrix. + hesr = eye (n); + else + % Use the damped BFGS formula. + y = grad - grad0; + sBs = sumsq (w); + Bs = hesr'*w; + sy = y'*s; + theta = 0.8 / max (1 - sy / sBs, 0.8); + r = theta * y + (1-theta) * Bs; + hesr = cholupdate (hesr, r / sqrt (s'*r), '+'); + [hesr, info] = cholupdate (hesr, Bs / sqrt (sBs), '-'); + if (info) + hesr = eye (n); + end + end + + % Second derivatives approximate the hessian. + d2f = norm (hesr, 'columns').'; + if (niter == 1) + dg = d2f; + xn = norm (dg .* x); + % FIXME: something better? + delta = factor * max (xn, 1); + end + + % FIXME: maybe fixed lower and upper bounds? + dg = max (0.1*dg, d2f); + + % FIXME -- why tolf*n*xn? If abs (e) ~ abs(x) * eps is a vector + % of perturbations of x, then norm (hesr*e) <= eps*xn, i.e. by + % tolf ~ eps we demand as much accuracy as we can expect. + if (norm (grad) <= tolf*n*xn) + info = 1; + break; + end + + suc = false; + decfac = 0.5; + + % Inner loop. + while (~ suc && niter <= maxiter && nfev < maxfev && ~ info) + + s = - doglegm (hesr, grad, dg, delta); + + sn = norm (dg .* s); + if (niter == 1) + delta = min (delta, sn); + end + + fval1 = fcn (reshape (x + s, xsiz)) (:); + nfev =nfev+1; + + if (fval1 < fval) + % Scaled actual reduction. + actred = (fval - fval1) / (abs (fval1) + abs (fval)); + else + actred = -1; + end + + w = hesr*s; + % Scaled predicted reduction, and ratio. + t = 1/2 * sumsq (w) + grad'*s; + if (t < 0) + prered = -t/(abs (fval) + abs (fval + t)); + ratio = actred / prered; + else + prered = 0; + ratio = 0; + end + + % Update delta. + if (ratio < min(max(0.1, 0.8*lastratio), 0.9)) + delta *= decfac; + decfac ^= 1.4142; + if (delta <= 1e1*macheps*xn) + % Trust region became uselessly small. + info = -3; + break; + end + else + lastratio = ratio; + decfac = 0.5; + if (abs (1-ratio) <= 0.1) + delta = 1.4142*sn; + elseif (ratio >= 0.5) + delta = max (delta, 1.4142*sn); + end + end + + if (ratio >= 1e-4) + % Successful iteration. + x = x+s; + xn = norm (dg .* x); + fval = fval1; + nsuciter =nsuciter +1; + suc = true; + end + + niter =niter +1; + + % FIXME: should outputfcn be only called after a successful iteration? + if (~ isempty (outfcn)) + optimvalues.iter = niter; + optimvalues.funccount = nfev; + optimvalues.fval = fval; + optimvalues.searchdirection = s; + state = 'iter'; + stop = outfcn (x, optimvalues, state); + if (stop) + info = -1; + break; + end + end + + % Tests for termination conditions. A mysterious place, anything + % can happen if you change something here... + + % The rule of thumb (which I'm not sure M*b is quite following) + % is that for a tolerance that depends on scaling, only 0 makes + % sense as a default value. But 0 usually means uselessly long + % iterations, so we need scaling-independent tolerances wherever + % possible. + + % The following tests done only after successful step. + if (ratio >= 1e-4) + % This one is classic. Note that we use scaled variables again, + % but compare to scaled step, so nothing bad. + if (sn <= tolx*xn) + info = 2; + % Again a classic one. + elseif (actred < tolf) + info = 3; + end + end + + end +end + +% Restore original shapes. +x = reshape (x, xsiz); + +output.iterations = niter; +output.successful = nsuciter; +output.funcCount = nfev; + +if (nargout > 5) + hess = hesr'*hesr; +end + +return + +% An assistant function that evaluates a function handle and checks for +% bad results. +function [fx, gx] = guarded_eval (fun, x) +if (nargout > 1) + [fx, gx] = fun (x); +else + fx = fun (x); + gx = []; +end + +if (~ (isreal (fx) && isreal (jx))) + error ('fminunc:notreal', 'fminunc: non-real value encountered'); +elseif (complexeqn && ~ (isnumeric (fx) && isnumeric(jx))) + error ('fminunc:notnum', 'fminunc: non-numeric value encountered'); +elseif (any (isnan (fx(:)))) + error ('fminunc:isnan', 'fminunc: NaN value encountered'); +end +return + +%~function f = rosenb (x) +%~ n = length (x); +%~ f = sumsq (1 - x(1:n-1)) + 100 * sumsq (x(2:n) - x(1:n-1).^2); +%~test +%~ [x, fval, info, out] = fminunc (@rosenb, [5, -5]); +%~ tol = 2e-5; +%~ assert (info > 0); +%~ assert (x, ones (1, 2), tol); +%~ assert (fval, 0, tol); +%~test +%~ [x, fval, info, out] = fminunc (@rosenb, zeros (1, 4)); +%~ tol = 2e-5; +%~ assert (info > 0); +%~ assert (x, ones (1, 4), tol); +%~ assert (fval, 0, tol); + +% Solve the double dogleg trust-region minimization problem: +% Minimize 1/2*norm(r*x)^2 subject to the constraint norm(d.*x) <= delta, +% x being a convex combination of the gauss-newton and scaled gradient. + +% TODO: error checks +% TODO: handle singularity, or leave it up to mldivide? + +function x = doglegm (r, g, d, delta) +% Get Gauss-Newton direction. +b = r' \ g; +x = r \ b; +xn = norm (d .* x); +if (xn > delta) + % GN is too big, get scaled gradient. + s = g ./ d; + sn = norm (s); + if (sn > 0) + % Normalize and rescale. + s = (s / sn) ./ d; + % Get the line minimizer in s direction. + tn = norm (r*s); + snm = (sn / tn) / tn; + if (snm < delta) + % Get the dogleg path minimizer. + bn = norm (b); + dxn = delta/xn; snmd = snm/delta; + t = (bn/sn) * (bn/xn) * snmd; + t -= dxn * snmd^2 - sqrt ((t-dxn)^2 + (1-dxn^2)*(1-snmd^2)); + alpha = dxn*(1-snmd^2) / t; + else + alpha = 0; + end + else + alpha = delta / xn; + snm = 0; + end + % Form the appropriate convex combination. + x = alpha * x + ((1-alpha) * min (snm, delta)) * s; +end + diff --git a/oddsratio.m b/oddsratio.m new file mode 100644 index 0000000..ef94540 --- /dev/null +++ b/oddsratio.m @@ -0,0 +1,22 @@ +function r = oddsratio(p,q) +%ODDSRATIO - Computes the odds ratio +% [r] = oddsratio(p,q) +% +% Example +% >> oddsratio( 1/23 , 5/100 ) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-04-30 Creation +% +% ----------------------------- Script History --------------------------------- + +r=p.*(1-q)./q./(1-p); diff --git a/openpdf.m b/openpdf.m new file mode 100644 index 0000000..f241773 --- /dev/null +++ b/openpdf.m @@ -0,0 +1,2 @@ +function [] = openpdf(f) +dir('c:\program Files\Adobe\Acrobat *') \ No newline at end of file diff --git a/overlap.m b/overlap.m new file mode 100644 index 0000000..e1ebee4 --- /dev/null +++ b/overlap.m @@ -0,0 +1,44 @@ +function [x]=overlap(S,s2) +% overlap - return the overlap between two segments +% +% [x]=overlap(s1,s2) +% Computes the overlap x=[a b] between the two (closed) segments. +% s1 and s2 MUST be real numbers. +% +% [x]=overlap(S) +% If S is a N-by-2 matrix, computes the global overlap of these N +% segments. +% +% x may be empty if s1 and s2 have no overlap, equals to [a a] if their +% overlap is a single point, or equals to the smaller of s1 and s2 if one +% includes the other. +% +%INPUTS: +% s1=[a1 b1], s2=[a2 b2] are two numerical segment (of real numbers) +% +if nargin<2 + s2=[]; +end +if any(~isreal([S(:) ; s2(:)])) + error('s1 and s2 must be real numbers') +end +if nargin>1 & isempty(s2) + x=[]; + return +end +if isempty(S) + x=[]; + return +end +S=[S;s2]; + +if size(S,1)>2 + x=overlap(S(1,:), overlap(S(2:end,:))); +else + if S(1)>S(4) | S(3)2 % VARARGIN can be used to pass standard arguments to DEPFUN + % Concatentate the VARARGIN into a string that can be used with DEPFUN + input=[]; + for n=1:length(varargin) + input=[input,'''',varargin{n},'''']; + if n~=length(varargin), input=[input,',']; end + end +else % Default input argument to DEPFUN +% input=['''','-quiet','''',',','''','-toponly','''']; % This restricts tracing to first level + input=['''','-quiet','''']; +end + +try +T=eval(['depfun(fname,',input,');']); +catch + T=depfun(fname); +end + +G=[]; m=1; +for k=1:length(T) + f=strfind(T{k},keyword); + if ~isempty(f), + G{m}=T{k}; + m=m+1; + end +end + +G=G'; + +return + + +% % DEPFUN2 finds the M-file dependencies of an m-file whos +% % path also contains a keyword. It relies upon the use of the +% % DEPFUN function. DEPFUN2 accepts a keyword to 'grep' for allowing +% % the return of m-files that are only found on a specific path (a users +% % path for example). The keyword (or part of a word) is used to find +% % matches in the full pathname of all files that the m-file depends on. +% % +% % SYNTAX: G=depfun2(fname,keyword,varargin); +% % +% % fname - The name of the m-file for which to determine dependencies +% % keyword - The keyword used to retain m-files whose pathname contains 'keyword' +% % DEFAULT keyword is unix('whoami') +% % varargin - Any of the various arguments that DEPFUN usually accepts. +% % +% % Example: G=depfun2('bench','graphics','-quiet','-toponly'); % Returns FEWER results than... +% % G=depfun2('bench','graphics','-quiet'); % Because this includes indirectly called m-files +% % +% % DBE 02/07/03 +% % DBE 04/10/26 Modified to support full range of DEPFUN inputs. +% % +% % To Do: Figure out a good way to include functions that sub-functions +% % depend upon etc. +% +% function G=depfun2(fname,keyword,varargin); +% if nargin <2 & isunix +% [status,keyword]=unix('whoami'); +% keyword=deblank(keyword); +% if status +% error('UNIX WHOAMI call failed.'); +% end +% elseif nargin<2 & ~isunix +% error('PACKAGE.M requires two user inputs on the PC platform'); +% elseif nargin==2 +% else +% error('depfun2.M requires two user inputs'); +% end +% +% if nargin>2 % Concatentate the VARARGIN into a string that can be used with DEPFUN +% input=[]; +% for n=1:length(varargin) +% input=[input,'''',varargin{n},'''']; +% if n~=length(varargin), input=[input,',']; end +% end +% else % Default input string to DEPFUN +% input=['''','-quiet','''',',','''','-toponly','''']; +% % input=['''','-quiet',''''] +% end +% +% T=eval(['depfun(fname,',input,');']); +% +% G=[]; m=1; +% for k=1:length(T) +% f=strfind(T{k},keyword); +% if ~isempty(f), +% G{m}=T{k}; +% m=m+1; +% end +% end +% +% G=G'; +% +% return + diff --git a/paren_parse.m b/paren_parse.m new file mode 100644 index 0000000..dd9edc2 --- /dev/null +++ b/paren_parse.m @@ -0,0 +1,2 @@ +function [tree]=paren_parse(txt) +error('paren_parse parse no more! See paren_parser') \ No newline at end of file diff --git a/paren_parser.m b/paren_parser.m new file mode 100644 index 0000000..1b5b686 --- /dev/null +++ b/paren_parser.m @@ -0,0 +1,28 @@ +function [paren_tree]=paren_parser(txt) +% Parsing an expression with parentheses +% [paren_tree]=paren_parser(txt) + +paren_op={'(' ')'; '[' ']'}; +opens=findstr(paren_op{1,1}, txt); %opening paren +closes=findstr(paren_op{1,2}, txt); %closing paren + +error('not working yet!') + +if not(isempty(opens)) + pairs=[]; + open = 1; + while open opens(nbopen) + nbopen=nbopen+1; + end + open=open+1; + end + pairs=[pairs idx_op{i,1}] + nbpar=nbpar+1; +end +return +end +paren_tree=struct('op', '', 'e', {txt}); diff --git a/pascualmarqui.m b/pascualmarqui.m new file mode 100644 index 0000000..17eb547 --- /dev/null +++ b/pascualmarqui.m @@ -0,0 +1,41 @@ +function L = loreta_laplacian(varargin) +%loreta_laplacian - Laplacian operator for a mesh according to Pascual-Marqui +% [L] = loreta_laplacian(D) +% Computes LORETA's laplacian L for a distance matrix (D) of a mesh +% +% [L] = loreta_laplacian(vertices,faces) +% Computes laplacian L for a mesh defined by its vertices and faces +% +% [L] = loreta_laplacian(vertices,vertconn) +% Computes laplacian L for a mesh where vertex connectivity cell list has +% already been computed using: vertices_connectivity +% +% See also: bst_laplacian, mesh_laplacian + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-03 Creation (thanks to Jean Daunizeau scripts) +% +% ----------------------------- Script History --------------------------------- +if nargin>1 + if ~iscell(varargin{2}) + vertices_distances + else + D=vertices_distances(vararagin{1},vararagin{2},1); + end +else + D=varargin{1}; +end +L=-bst_smooth_fun([],D,1,0,'1./r'); +nv=size(L,1); +L(1:(nv+1):end)=0; +L(1:(nv+1):end)=-mean(sum(L,2)); + +return + diff --git a/patch_swell.m b/patch_swell.m new file mode 100644 index 0000000..e6702e4 --- /dev/null +++ b/patch_swell.m @@ -0,0 +1,55 @@ +function newverts = patch_swell(iverts, vconn) +% PATCH_SWELL: Enlarge a patch by appending the next set of adjacent vertices. +% +% USAGE: newverts = patch_swell(iverts, vconn); +% +% INPUT: +% - iverts : index list of vertex numbers +% - vconn : sparse matrix of vertex connectivity +% OUTPUT: +% - newverts: row vec list of NEW vertex numbers adjacent the patch + +% @============================================================================= +% This software is part of The Brainstorm Toolbox +% http://neuroimage.usc.edu/brainstorm +% +% Copyright (c)2008 Brainstorm by the University of Southern California +% This software is distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html. +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% +% For more information type "brainstorm licence" at command prompt. +% =============================================================================@ +% +% Authors: ? +% ----------------------------- Script History --------------------------------- +% +% ------------------------------------------------------------------------------ + +if (size(iverts,1) ~= 1) + iverts = iverts(:)'; % ensure row vector +end + +%%%%%%% BUG WORKAROUND FOR MATLAB R2009a: 7.8.0 %%%%%% +% Get version name +vername = version; +% If bugged version: need to convert matrice to a FULL one +if strcmpi(vername(1:5), '7.8.0') + % Concatenate all vertex connections for all verts + newverts = find(max(full(vconn(iverts, :)), [], 1)); +else + % Concatenate all vertex connections for all verts + newverts = find(max(vconn(iverts, :), [], 1)); +end + +% Extract unique set of indices, remove existing vertices +newverts = setdiff(newverts, iverts); + + + diff --git a/patchify.m b/patchify.m new file mode 100644 index 0000000..e995c9c --- /dev/null +++ b/patchify.m @@ -0,0 +1,34 @@ +function FV = patchify(S,varargin) +%PATCHIFY - Remove subfields from a struct to make it a FV patch +% FV = patchify(S) remove fields from S other than .vertices and .faces +% If needed, those fields will be lower-cased. +% See also: patch + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-08 Creation +% +% ----------------------------- Script History --------------------------------- +FV=struct('vertices', [], 'faces', []); +if isfield(S,'vertices') + FV=setfield(FV,'vertices',getfield(S, 'vertices')); +elseif isfield(S,'Vertices') + FV=setfield(FV,'vertices',getfield(S, 'Vertices')); +end +if isfield(S,'faces') + FV=setfield(FV,'faces',getfield(S, 'faces')); +elseif isfield(S,'Faces') + FV=setfield(FV,'faces',getfield(S, 'Faces')); +end +if isfield(S,'facevertexcdata') + FV=setfield(FV,'facevertexcdata',getfield(S, 'facevertexcdata')); +elseif isfield(S,'FaceVertexCData') + FV=setfield(FV,'facevertexcdata',getfield(S, 'FaceVertexCData')); +end + \ No newline at end of file diff --git a/patchplot.m b/patchplot.m new file mode 100644 index 0000000..39e74ec --- /dev/null +++ b/patchplot.m @@ -0,0 +1,66 @@ +function h = patchplot(X,Y,varargin) +%PATCHPLOT - One line description goes here. +% [h] = patchplot(Y) +% [h] = patchplot(X,Y) +% [h] = patchplot(X,Y,varargin) +% +% Example +% >> patchplot +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-06 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin==1 + Y=X; + X=[]; +end +if numel(Y)==max(size(Y)) + Y=Y(:); +end +Y=Y(:,:); +if isempty(X) + X=1:size(Y,1); +end +bl=0; +if nargin>1 + try + i = strmatch('baseline', lower(varargin(1:2:end)), 'exact'); + if ~isempty(i) + bl=varargin{2*i}; + varargin((2*i-1):(2*i))=[]; + else + bl=0; + end + end +end + +minY = zeros(1,size(Y,2))+bl; +% minY(all(Y>=0,1),:)=min(Y,[],1); +% minY(all(Y<=0,1),:)=min(Y,[],1); +X=X([1 1:end end]); +Y = [minY;Y;minY]; + +%Y(end+1,:) = Y(1,:); + +for i=1:size(Y,2) + if size(Y,2)>1 + C=rand(1,3); + else + C=[.87 .87 .87]; + end + h(i)=patch(X,Y,C,varargin{:}); +end +% Move it to the back layer +hh = get(gca, 'children'); +set(gca, 'children',[ hh(hh~=h);h]); \ No newline at end of file diff --git a/pca.m b/pca.m new file mode 100644 index 0000000..bca4269 --- /dev/null +++ b/pca.m @@ -0,0 +1,118 @@ +function [Y, lbd, cos2, CC] = pca(X, P, labels) +%PCA Principal Components Analysis +% +% Y = PCA(X, P) returns the first P principal components of X. +% X must be a NxL matrix of N vectors in L dimensions. +% +% Y = PCA(X, P, LABELS) displays several plots related to the PCA: +% . projection of data on the first two principal axes, +% . correlation circle, +% . % inertia of the principal components, +% . angles of the data w.r.t. the PC subspace. +% If LABELS is a matrix containing N rows of text, each row is used +% to label the corresponding data point, otherwise data go unlabelled. +% +% Additional outputs: [Y, LBD, C2, CC] = PCA(X, P [, LABELS]), where +% Y is the projection of X on the first P principal components, +% LBD contains the % inertia of the required P components, +% C2 is the squared cosine between projected data and original data, +% CC is the correlation between the input features and the first P P.C. +% +% See also: . +if (nargin < 2) or (nargin > 4) + error('PCANA: wrong number of arguments.') +end + +[N, L] = size(X) ; +if (P < 1) + error('PCANA: must return at least 1 principal component.') +end +if (P > L) + error('PCANA: can''t get more principal components than dimensions.') +end + +if (nargin == 2) + verbose = 0 ; +end + +%%%%%%%%%% + +R = corrcoef(X) ; +% XM= ones(N,1) * mean(X') ; +% Xc = X' - XM ; +% [U, S, V] = svd(Xc, 0) ; +[V, S] = eig(R) ; +[l, idx] = sort(diag(S)') ; +l = fliplr(l) ; +idx = fliplr(idx) ; + +% Coordonees centrees reduites. +XCR = (X - ones(N,1)*mean(X)) / diag(std(X)) ; +%PC = (Xc * V(:,idx)' + XM)' ; +PC = (XCR * V(:,idx) ) ; + +% P first principal components: +Y = PC(:, 1:P) ; + +% P first portions of inertia: +lbd = l(1:P) / sum(l) ; + +% Squared cosines of projection vs. original data: +cos2 = sum((Y.^2)') ./ sum((XCR.^2)') ; + +% Correlations of features with PCs: +CC = V(:,idx) * diag(sqrt(l)) ; + +if (nargin == 3) + figure + subplot(2,2,1) ; + plot(PC(:,1), PC(:,2), '+') ; + if (size(labels, 1) == N) + for i = 1:N + text(PC(i,1), PC(i,2), [' ', labels(i,:)]) ; + end + end + xlabel('First principal axis') ; + ylabel('Second principal axis') ; + title('Data projection on the first two principal axes') + subplot(2,2,2) ; + plot(cos(2*pi*(0:100)/100), sin(2*pi*(0:100)/100)) ; + hold on, plot([-1, 1], [0, 0]), plot([0, 0], [-1, 1]) ; + plot(CC(:,1), CC(:,2), 'x') ; + for k = 1:L + text(CC(k,1)+.03, CC(k,2)+.03, num2str(k)) ; + end + xlabel('First PC') ; + ylabel('Second PC') ; + title('Correlation of features with first 2 PCs') + subplot(2,2,3) ; + hh = plot(l/sum(l), '--') ; + set(hh, 'LineWidth', 3) ; + hold on, hh = plot(cumsum(l)/sum(l)) ; + set(hh, 'LineWidth', 3) ; + axis([1 L 0 1]) ; + plot([2 2], [0 1]) ; + xlabel('PC no.') ; + ylabel('Inertia') ; + legend('PC inertia', 'Cumulated inertia') ; + title('Repartition of inertia on the PCs') ; + subplot(2,2,4) ; + hold on + hh = plot(acos(sqrt(cos2))/pi*180, 1:N, '+') ; + set(hh, 'LineWidth', 3) ; + hold on + for i = 1:N + hh = plot([0, acos(sqrt(cos2(i)))/pi*180], [i, i], '-') ; + set(hh, 'LineWidth', 3) ; + end + set(gca, 'Box', 'on') ; + set(gca, 'YLim', [1 N]) ; + if (size(labels, 1) == N) + set(gca, 'YTick', 1:N) ; + set(gca, 'YTickLabels', labels) ; + end + xlabel('Angle (deg)') + title('Angle of data with the PC plan') +end + +CC = CC(:,1:P) ; diff --git a/permarray.m b/permarray.m new file mode 100644 index 0000000..e05b420 --- /dev/null +++ b/permarray.m @@ -0,0 +1,4 @@ +function [y]=permarray(x,pv,dim) +% not aailable !!! (Can't even remember what it is suppose to do) +error('bla bla') +return \ No newline at end of file diff --git a/permprep.m b/permprep.m new file mode 100644 index 0000000..a375028 --- /dev/null +++ b/permprep.m @@ -0,0 +1,31 @@ +% function prep=permprep(X,Y,paired,tails) +for i=1:10000 + n=subarray(randperm(30),1:15); + y(i)=mean(z{1}(n)); + n=subarray(randperm(30),1:15); + y(i)=y(i)-mean(z{2}(n)); +end + +% doesn't work + + +% % +% % Z=sum(Y(1:ceil(N(1)/2),:),1)./ceil(N(1)/2)-sum(Y(N(1)+(1:ceil(N(2)/2)),:),1)./ceil(N(2)/2); +% % if i==0 +% +% Randomization methods avoid assumptions of normality, are useful for +% small-n experiments, and are robust against heteroscedasticity. To employ +% them: +% +% * Bootstrap populations for the experimental and control samples +% independently, generating subsamples of half the size of the original +% samples, using software such as Resampling Stats©(Bruce, 2003). This +% half-sizing provides the sqrt(2) increase in the standard +% deviation intrinsic to calculation of prep. +% * Generate an empirical sampling distribution of the difference of +% the means of the subsamples, or of the mean of the differences for a +% matched-sample design. +% * The proportion of the means that are positive gives prep. +% +% This robust approach does not take into account ??2, and so is accurate +% only for exact replications. \ No newline at end of file diff --git a/permute2.m b/permute2.m new file mode 100644 index 0000000..a87dcf3 --- /dev/null +++ b/permute2.m @@ -0,0 +1,31 @@ +function Y = permute2(X,p) +%PERMUTE2 - Easi(er) to use than permute +% [Y] = permute2(X,p) +% +% Example +% >> permute2(rand(3,2,4), 3) will put 3rd dimension first followed +% by the other ones +% +% See also: permute, nd2array + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-03-13 Creation +% +% ----------------------------- Script History --------------------------------- + +ndx=ndims(X); +if all(p(:)>0) +Y=permute(X,[p(:)' setdiff(1:ndx,p(:))]); +elseif all(p(:)<0) +Y=ipermute(X,[p(:)' setdiff(1:ndx,p(:))]); +else + error('Can''t handle negative and positive dimensions!'); +end + diff --git a/perso/predictors.m b/perso/predictors.m new file mode 100644 index 0000000..a0f084b --- /dev/null +++ b/perso/predictors.m @@ -0,0 +1,18 @@ +function []=p() +g(1,1:2)=0; +k=2; +for i=2:1000 + p1=ceil(rand*6); + sum(k-3.5)/i + [p2]=round(3.5-mean(k-3.5)) + k(i)=ceil(rand*6); + k + p2 + + g(i,1)=g(i-1,1)+(p1(i)==k(i)); + g(i,2)=g(i-1,2)+(p2(i)==k(i)); + +end + + plot(cumsum(g)) + drawnow diff --git a/perso/prerdictors.m b/perso/prerdictors.m new file mode 100644 index 0000000..276701b --- /dev/null +++ b/perso/prerdictors.m @@ -0,0 +1,12 @@ +function []=p() +g(1:2,1)=0; +for i=2:1000 + p1=ceil(rand*6); + [v,p2]=min(sum(k-3.5)); + k + p2 + k(i)=ceil(rand*6); + g(i,1)=g(i-1,1)+(p1(i)==k(i)); + g(i,2)=g(i-1,2)+(p2(i)==k(i)); + + plot(cumsum([g1;g2])) \ No newline at end of file diff --git a/piecemeal.m b/piecemeal.m new file mode 100644 index 0000000..3732297 --- /dev/null +++ b/piecemeal.m @@ -0,0 +1,42 @@ +function [sz,idx]=piecemeal(p) % ,dim,minsize) +% piecemeal - find continuous segments of true in a logical array +% +% [sz,idx]=piecemeal(p) +%INPUT: +% p: logical vector +%OUPUTS: +% sz: size of the chunks/clusters/segment... +% idx: position of the first element of each chunk + +dim=1; +p=p(:); +p=logical(p); +np=size(p,dim); +dip=diff(cumsum(p),2); +dp1=find(dip==1)+2; +dp2=find(dip==-1)+2; +if isequal(p(1),[1]) + dp1=[1; dp1]; + if isequal(p(2),[0]) + dp2=[2; dp2]; + end +elseif isequal(p(2),[1]) + dp1=[2; dp1]; +end +if isequal(p(end),[1]) + dp2=[dp2; np+1]; +end +sz=dp2-dp1; +idx=dp1; + +return + +% one patch per col +dp=diff(p); +fdp=find(dp) +pfdp=p(fdp) + +fx=[fdp; fdp]; +fx=[1 fx(:)' length(p)] +fy=[[p(fdp) p(end)]; [p(fdp) p(end)]]; +fy=[fy(:)']; diff --git a/plot2d.m b/plot2d.m new file mode 100644 index 0000000..25b86c3 --- /dev/null +++ b/plot2d.m @@ -0,0 +1,21 @@ +function h = plot2d(XY, varargin) +%PLOT2D - Plot 2 data X,Y +% [h] = plot2d(XY) +% +% Example +% >> plot2d(randn(1000,2),'.') +% +% See also: plot, plot3d, plotnd() + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-03 Creation +% +% ----------------------------- Script History --------------------------------- +h=plot(XY(:,1), XY(:,2), varargin{:}); diff --git a/plot3d.m b/plot3d.m new file mode 100644 index 0000000..4a620f1 --- /dev/null +++ b/plot3d.m @@ -0,0 +1,18 @@ +function [p]=plot3d(xyz, varargin); +% plot in 3 dimension +% [p]=plot3d(xyz, varargin); +if size(xyz, 2) ~= 3 && size(xyz, 1) == 3 + xyz=xyz'; +end +if nargin<2 + varargin={'.'}; +end +if size(xyz,2)==2 + xyz(:,3)=0.*xyz(:,1); +end +% varargin{1}=['.' varargin{1}]; +% , 'LineStyle', 'None', 'Marker', '.' +p=plot3(xyz(:,1),xyz(:,2),xyz(:,3),varargin{:} ); +if all(xyz(:,3)==0) + view(2) +end \ No newline at end of file diff --git a/plot4.m b/plot4.m new file mode 100644 index 0000000..72b7ee5 --- /dev/null +++ b/plot4.m @@ -0,0 +1,51 @@ +function varargout=plot4(x,y,z,c,varargin); + +% PLOT4 Plot colored lines and points in 3-D space +% +% PLOT3(x,y,z,c), where x, y, z and c are four vectors of the same length N, +% plots a line in 3-space through the points whose coordinates are the +% elements of x, y and z, colored occording to the values in c. The line +% consists of N-1 line segments. +% +% Various line types, plot symbols and colors may be obtained with +% PLOT3(X,Y,Z,s) where s is a 1, 2 or 3 character string made from +% the characters listed under the PLOT command. +% +% Example: A helix: +% +% t = 0:pi/50:4*pi; +% plot4(sin(t),cos(t),t.^2,t,'.-'); +% +% PLOT4 returns a column vector of handles to lineseries objects, one +% handle per line segment. +% +% See also plot, plot3, line, axis, view, mesh, surf. + +% author: Christophe Lauwerys +% contact: christophe.lauwerys@gmail.com +% date: 22/03/2006 + +error(nargchk(4,inf,nargin)) +error(nargoutchk(0,1,nargout)) + +x=x(:); +y=y(:); +z=z(:); +c=c(:); + +% For all c that are NaN, set x to NaN to overcome plotting +idx = find(isnan(c)); +x(idx) = NaN; +c(idx) = min(c); + +% Interpolate colormap +cmap=colormap; % get current colormap +yy=linspace(min(c),max(c),size(cmap,1)); % Generate range of color indices that map to cmap +cm = interp1(yy,cmap,c,'linear')'; + +% Plot data +storeNextPlot = get(gca,'NextPlot'); +set(gca,'ColorOrder',cm','NextPlot','ReplaceChildren') +h=plot3([x(1:end-1) x(2:end)]',[y(1:end-1) y(2:end)]',[z(1:end-1) z(2:end)]',varargin{:}); +set(gca,'NextPlot',storeNextPlot); +if nargout==1, varargout{1}=h; end \ No newline at end of file diff --git a/plotSDV.m b/plotSDV.m new file mode 100644 index 0000000..0edc43e --- /dev/null +++ b/plotSDV.m @@ -0,0 +1,10 @@ +function [p] = plotSDV(x, y, sdv, varargin) +%PLOTSDV : [plots()] = plotSDV(x,y, sdv, varargin) +% Plot standard deviation around a value 'moustache' like +for k=1:length(x) + z=y(k) + [-sdv(k) sdv(k)]; + p(k)=plot([x(k) x(k)], z, varargin{:}) + set(p(k), 'Marker', '+') +end + + diff --git a/plotdata.m b/plotdata.m new file mode 100644 index 0000000..8dceb6c --- /dev/null +++ b/plotdata.m @@ -0,0 +1,308 @@ +function [varargout]=plotdata(action,varargin); +% plotdata - plots multiple data typically [ Channels x Time x Trials ] +% +% Example +% >> plotdata(F) +% >> plotdata('plot',F,Options) +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2004 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2004-12-15 Creation +% KND 2005-12-15 Now links between many plotdata axes +% ----------------------------- Script History --------------------------------- +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='plot'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_plot(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'TimeDim',imax(size(data)),... + 'Fields', {{'Channel', 'Trial' , 'Condition', 'Field4', 'Field5'}} ,... + 'Time', [] ,... + 'TimeWindow', [], ... + 'Values', [], ... + 'Interactive', 1, ... + 'LinkedAxes', [] ... % Link to other plots + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2);% struct(varargin{:}); + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- + +z=permute(data, [OPTIONS.TimeDim 1:(OPTIONS.TimeDim-1) (OPTIONS.TimeDim+1):ndims(data)]); +if isempty(OPTIONS.Time) + Time=1:size(z,1); +else + Time=OPTIONS.Time; +end +nf=ndims(data)-1; +if length(OPTIONS.Fields) < nf + OPTIONS.Fields(end+1:nf)={[]}; +end +for i=1:nf + if isempty( OPTIONS.Fields{i} ) + OPTIONS.Fields{i}=sprintf('Field %d',i); + end +end +cla +if isempty(OPTIONS.TimeWindow) + hp=plot(Time,z(:,:)); +else + hold on + for i=1:size(z(:,:),2); + hp(i)=plot(Time(1:OPTIONS.TimeWindow(i)), z(1:OPTIONS.TimeWindow(i),i), 'Color',subarray(get(gca, 'ColorOrder'), mod(i-1,size(get(gca, 'ColorOrder'),1))+1)); + end + hold off +end +ha=get(hp(1), 'Parent'); +sz=[size(z)]; +x=OPTIONS; +x.Axes=ha; +x.DataSize=sz; +% x.Data=data; +x.Time=OPTIONS.Time; +sz(1)=[]; +sz=[sz 1]; +hp=reshape(hp,sz); +x.Traces=hp; +x.Selected=[]; +setappdata(ha,mfilename,x) +for i=1:length(x.LinkedAxes) + y=getappdata(x.LinkedAxes(i),mfilename); + y.LinkedAxes=[y.LinkedAxes x.Axes]; + setappdata(y.Axes, mfilename, y); +end +if OPTIONS.Interactive + set(hp, 'ButtonDownFcn', sprintf('%s(''click_trace'', gcbo)', mfilename)); + title('Click on a trace') + h=uicontextmenu; + + uimenu('Label', 'Unselect all' , 'Parent', h, 'Callback', sprintf('%s(''select_rmv'',overobj(''axes''))', mfilename)); + uimenu('Label', 'Unselect visible ones' , 'Parent', h, 'Callback', sprintf('%s(''select_rmv'',overobj(''axes''), ''Visible'', ''on'')', mfilename)); + uimenu('Label', 'Hide selected traces' , 'Parent', h, 'Callback', sprintf('%s(''hide_add'',overobj(''axes''))', mfilename)); + % 'set(getappdata(get(gcbo, ''UserData''), ''SelectedHandle''), ''Visible'', ''off'')'); + uimenu('Label', 'Un-hide last selected trace', 'Parent', h, 'Callback', sprintf('%s(''hide_rmv'',overobj(''axes''),1)', mfilename)); + % 'set(getappdata(get(gcbo, ''UserData''), ''SelectedHandle''), ''Visible'', ''on'')'); + uimenu('Label', 'Un-hide all traces', 'Parent', h, 'Callback', sprintf('%s(''hide_rmv'',overobj(''axes''))', mfilename)); + %'set(getappdata(get(gcbo, ''UserData''), ''Traces''), ''Visible'', ''on'')'); + uimenu('Label', 'List hidden traces', 'parent', h, 'Callback', sprintf('%s(''hide_list'',gca)', mfilename)); + + % + % uimenu('Label', 'Display single channel traces', 'Parent', h, 'Separator', 'on', 'Callback', [ ... + % 'figure(''Name'', sprintf(''Channel #%d'', subarray(getappdata(get(gcbo, ''UserData''), ''Selected''), 1)));'... + % 'plotdata(permute(cell2mat(get(subarray(getappdata(get(gcbo, ''UserData''), ''Traces''),'... + % 'subarray(getappdata(get(gcbo, ''UserData''), ''Selected''), 1), 1),''YData'')),[3 2 1]));'... + % ]); + if prod(sz)>1 + for i=1:length(sz) + h2=uimenu('Label', sprintf('Display single (%s) traces', OPTIONS.Fields{i}), 'Parent', h, 'Callback', [ ... + 'figure(''Name'', [ get(gcbf, ''Name'') '', '' sprintf(''' sprintf('%s', OPTIONS.Fields{i}) ' #%d'', subarray(getappdata(get(gcbo, ''UserData''), ''Selected''), ' sprintf('%d',i) '))]);' ... + 'plotdata(reshape(shiftdim(cell2mat(x2cell(get(subarray(getappdata(get(gcbo, ''UserData''), ''Traces''),'... + 'subarray(getappdata(get(gcbo, ''UserData''), ''Selected''), ' sprintf('%d',i) '), ' sprintf('%d',i) '),''YData''))),1),'... + '[subarray(getappdata(get(gcbo, ''UserData''),''DataSize''),' sprintf('%d',i+1) ', -2) 1])' ... + ', ''TimeDim'',1, ''Time'', getappdata(get(gcbo, ''UserData''),''Time''), ' ... + ' ''Fields'', {subarray(getappdata(get(gcbo, ''UserData''),''Fields''),' sprintf('%d',i) ', -2)} );'... + ]); + if i==1 + set(h2, 'separator', 'on') + end + + end + + uimenu('separator', 'on', 'Label', 'Select one trace', 'Parent', h, 'Callback', 'set(getappdata(get(gcbo, ''UserData''), ''Traces''), ''Visible'', ''on'')'); + + end + set(get(h, 'Children'),'UserData', ha); + set(hp, 'uicontextmenu', h); + set(ha, 'uicontextmenu', h); + +end + +function sel=handles2ind(x,ho) +if ~isstruct(x) + x=getappdata(x, mfilename); +end +sel=ind2sub2(size(x.Traces), idxmember(ho,x.Traces)); + +function b=ind2logical(traces,sel) +b=logical(zeros(size(traces))); +sel=num2cell(sel); +for i=1:size(sel,1) + b(sel{i,:})=1; +end +return + +function []=action_click_trace(ho) +ha=get(ho(1), 'Parent'); +hf=get(ha, 'Parent'); +if ismember(get(hf, 'SelectionType'), {'normal', 'extend'}) + action_select_toggle(ha,handles2ind(ha,ho)); +end + +function action_select_toggle(x, sel) +% Toggle selected/not-selected style +if ~isstruct(x) + x=getappdata(x, mfilename); +end +for i=1:size(sel,1) + if ismember(sel,x.Selected, 'rows') + action_select_rmv(x, sel(i,:)) + else + action_select_add(x, sel(i,:)) + end +end + + +function action_select_add(x, sel,link) +% Put back non-selected style +if nargin<2 + error('No selection') +end +if ~isstruct(x) + x=getappdata(x, mfilename); +end +x.Selected=[x.Selected;sel]; +set(x.Traces(ind2logical(x.Traces,sel)), 'LineWidth', 2); +setappdata(x.Axes, mfilename, x); +set(get(x.Axes,'Title'), 'String', [ 'Selection: [ ' sprintf('%d ', sel) ']']); +if nargin<3 + link=[]; +end +if all(link)>0 + link=[link x.Axes]; + ToBeLinked=setdiff(x.LinkedAxes,link); + for i=1:length(ToBeLinked) + action_select_add(ToBeLinked(i),sel,link) + end +end +return + +function action_select_rmv(x, sel,link) +% Put back to non-selected style +if ~isstruct(x) + x=getappdata(x, mfilename); +end +if nargin<2 + % If unspecified act on the previously selected traces + sel=x.Selected; +end +if nargin>1 + if ischar(sel) + sel=findobj(x.Traces(ind2logical(x.Traces,x.Selected)), sel, link); + sel=handles2ind(x, sel); + link=[]; + end +end +x.Selected=x.Selected(~ismember(x.Selected, sel, 'rows'),:); +set(x.Traces(ind2logical(x.Traces,sel)), 'LineWidth', .5); +setappdata(x.Axes, mfilename, x); +if nargin<3 + link=[]; +end +if all(link)>0 + link=[link x.Axes]; + ToBeLinked=setdiff(x.LinkedAxes,link); + for i=1:length(ToBeLinked) + action_select_rmv(ToBeLinked(i), sel,link) + end +end +return + +function action_hide_toggle(x, sel) +% Toggle selected/not-selected style +if ~isstruct(x) + x=getappdata(x, mfilename); +end +for i=1:size(sel,1) + if ismember(sel,x.Selected, 'rows') + action_hide_rmv(x, sel(i,:)) + else + action_hide_add(x, sel(i,:)) + end +end + + +function action_hide_add(x, sel) +% Hide selection +if ~isstruct(x) + x=getappdata(x, mfilename); +end +if nargin<2 + sel=x.Selected; +elseif isscalar(sel) + if sel<=0 + error('wrong input') + end + sel=x.Selected(end:-1:(end-abs(sel)+1)); +end +set(x.Traces(ind2logical(x.Traces,sel)), 'Visible', 'off'); +return + +function action_hide_rmv(x, sel) +% Put back non-selected style +if ~isstruct(x) + x=getappdata(x, mfilename); +end +if nargin<2 + % If unspecified act on the previously selected traces + sel=x.Selected; +elseif isscalar(sel) + if sel<=0 + error('wrong input') + end + if isequal(get(x.Traces(ind2logical(x.Traces,x.Selected(end,:))), 'Visible'), 'on') + % If we are being selecting a trace, we unselect it and go one step + % further in the selected list. + action_select_rmv(x,x.Selected(end,:)) + x=getappdata(x.Axes, mfilename); + end + sel=x.Selected(end:-1:(end-abs(sel)+1),:); +end +set(x.Traces(ind2logical(x.Traces,sel)), 'Visible', 'on'); +return + +function action_hide_list(x) +% List (in command window) the hidden traces +if ~isstruct(x) + x=getappdata(x, mfilename); +end +disp(handles2ind(x ,findobj(x.Traces, 'Visible','off'))) + +% [ '[ cell2mat(x2cell(argouts('... +% ' ''ind2sub( size(getappdata(gca, ''''Traces'''')),nonzeros(idxmember(findobj(gca, ''''Visible'''', ''''off'''') , getappdata(gca,''''Traces''''))))'' ,'... +% ' ndims(getappdata(gca,''Traces''))))) ]' ]); diff --git a/ploterr.m b/ploterr.m new file mode 100644 index 0000000..c5de3ae --- /dev/null +++ b/ploterr.m @@ -0,0 +1,82 @@ +function [h,Options]=ploterr(x,y,s,varargin) +% ploterr - plot with a patch representing dispersion/error around the value +% [h]=ploterr(x,y,s) +% [h]=ploterr(x,y,s, 'Color', [r g b], 'PatchColor', [r g b]) +% [h]=ploterr(y,s) +% [h]=ploterr(y) +% +% Plots data y with their dispersion s, given abscissa x. +%INPUTS: +% x: T-long vector, abscissa for data point (if not given: x=[1:length(y)]) +% y: T-by-N matrix of mean data points (N may be 1) +% s: T-by-N matrix of dispersion around mean for each data point +%OUTPUT: +% h is N-by-2 array of handles: h(:,1) are the lines, h(:,2) the patches +% +% If no s is provided. Default is to plot the STANDARD ERROR around the +% mean: +% s=std(y)/sqrt(n); +% y=mean(y); +% ie. y is assumed to be a [ K x T x N ] matrix (of K observations/subjects) + +if nargin<2 + y=x; + x=[]; +end +if nargin<3 + s=[]; +end +if ~isempty(s) && ischar(s) + varargin=[{s} varargin]; + s=[]; +end +Options.Color=get(gca, 'ColorOrder'); +Options.Color([1 2 3],:)=Options.Color([1 3 2],:); +Options.PatchColor=brighten(Options.Color,.97); +if nargin>3 + Options=mergestructs(Options,struct(varargin{:})); +end +if isempty(s) + s=shiftdim(std(y),1)./sqrt(size(y,1)); + y=shiftdim(mean(y),1); +end +if isempty(x) + x=[1:size(y,1)]'; +end + +if prod(size(y))~=max(size(y)) + Ys=y; + holdstate=ishold; + y=y(:,:); + s=s(:,:); + for i=1:size(y,2) + o=Options; + o.Color=circshift(Options.Color,1-i); + o.PatchColor=circshift(Options.PatchColor,1-i); + [h(i,:)]=ploterr(x,y(:,i),s(:,i),o); + hold on + end + if ~holdstate + hold off + end + return +end + +px=[x(:); flipud(x(:))]; % use px=[x1;x2(end:-1:1)]; if row vecs +py=[ y(:)-s(:) ; flipud(y(:)+s(:)) ]; % use ... + +holdstate=ishold; +if ~holdstate + delete(get(gca, 'Children')) +end +h=patch(px, py, Options.PatchColor(1,:)); +% set(h, 'FaceAlpha', .5) +hold on +h=[plot(x,y, 'LineWidth', 2,'Color', Options.Color(1,:)) h]; +set([h(:,2)], 'FaceAlpha', .35); +if ~holdstate + hold off; +end + +return + diff --git a/ploterrw.m b/ploterrw.m new file mode 100644 index 0000000..2b0a6b7 --- /dev/null +++ b/ploterrw.m @@ -0,0 +1,103 @@ +function [h,Options]=ploterrw(x,y,s,varargin) +% ploterr - plot with a patch representing dispersion/error around the value +% [h]=ploterrw(x,y,s) +% [h]=ploterrw(x,y,s, 'Color', [r g b], 'PatchColor', [r g b]) +% [h]=ploterrw(y,s) +% [h]=ploterrw(y) +% [h]=ploterrw(y,dim) +% +% +% Plots data y with their dispersion s, given abscissa x. +% +%INPUTS: +% x: T-long vector, abscissa for data point (if not given: x=[1:length(y)]) +% y: T-by-N matrix of mean data points (N may be 1) +% s: T-by-N matrix of dispersion around mean for each data point +%OUTPUT: +% h is N-by-2 array of handles: h(:,1) are the lines, h(:,2) the patches +% +% If no s is provided. Default is to plot the STANDARD ERROR around the +% mean OF THE DIFFERENCE: (cf. ploterr()) +% s=std(y)/sqrt(n); +% y=mean(y); +% ie. y is assumed to be a [ K x T x N ] matrix (of K observations/subjects) +% +% See also: ploterr +if nargin<2 + y=x; + x=[]; +end +if nargin<3 + s=[]; + if isscalar(y) + y=permute(x,[y setdiff(1:ndims(x),y)]); + x=[]; + end +end + +if ~isempty(s) + if ischar(s) + varargin=[{s} varargin]; + s=[]; + elseif isscalar(s) + y=permute(y,[s setdiff(1:ndims(y),s)]); + s=[]; + end +end +Options.Color=get(gca, 'ColorOrder'); +if Options.Color(2)~=1 + Options.Color([1 2 3],:)=Options.Color([1 3 2],:); + set(gca, 'ColorOrder',Options.Color); +end + +Options.PatchColor=brighten(Options.Color,.97); +if nargin>3 + Options=mergestructs(Options,struct(varargin{:})); +end + +if isempty(s) + y=squeeze(y); + s=shiftdim(std(diff(y,[],3)),1)./sqrt(size(y,1)); % New... + s=repmat(s,1,size(y,3)); + y=shiftdim(mean(y),1); +end +if isempty(x) + x=[1:size(y,1)]'; +end + +if prod(size(y))~=max(size(y)) + Ys=y; + holdstate=ishold; + y=y(:,:); + s=s(:,:); + for i=1:size(y,2) + o=Options; + o.Color=circshift(Options.Color,1-i); + o.PatchColor=circshift(Options.PatchColor,1-i); + [h(i,:)]=ploterr(x,y(:,i),s(:,i),o); + hold on + end + if ~holdstate + hold off + end + return +end + +px=[x(:); flipud(x(:))]; % use px=[x1;x2(end:-1:1)]; if row vecs +py=[ y(:)-s(:) ; flipud(y(:)+s(:)) ]; % use ... + +holdstate=ishold; +if ~holdstate + delete(get(gca, 'Children')) +end +h=patch(px, py, Options.PatchColor(1,:)); +% set(h, 'FaceAlpha', .5) +hold on +h=[plot(x,y, 'LineWidth', 2,'Color', Options.Color(1,:)) h]; +set([h(:,2)], 'FaceAlpha', .35); +if ~holdstate + hold off; +end + +return + diff --git a/ploterrw1.m b/ploterrw1.m new file mode 100644 index 0000000..0601697 --- /dev/null +++ b/ploterrw1.m @@ -0,0 +1,86 @@ +function [h,Options]=ploterrw1(x,y,s,varargin) +% ploterr - plot with a patch representing dispersion/error around the value +% [h]=ploterrw(x,y,s) +% [h]=ploterrw(x,y,s, 'Color', [r g b], 'PatchColor', [r g b]) +% [h]=ploterrw(y,s) +% [h]=ploterrw(y) +% +% +% Plots data y with their dispersion s, given abscissa x. +% +%INPUTS: +% x: T-long vector, abscissa for data point (if not given: x=[1:length(y)]) +% y: T-by-N matrix of mean data points (N may be 1) +% s: T-by-N matrix of dispersion around mean for each data point +%OUTPUT: +% h is N-by-2 array of handles: h(:,1) are the lines, h(:,2) the patches +% +% If no s is provided. Default is to plot the STANDARD ERROR around the +% mean OF THE DIFFERENCE: (cf. ploterr()) +% s=std(y)/sqrt(n); +% y=mean(y); +% ie. y is assumed to be a [ K x T x N ] matrix (of K observations/subjects) +% +% See also: ploterr +if nargin<2 + y=x; + x=[]; +end +if nargin<3 + s=[]; +end +if ~isempty(s) && ischar(s) + varargin=[{s} varargin]; + s=[]; +end +Options.Color=get(gca, 'ColorOrder'); +Options.PatchColor=brighten(Options.Color,.97); +if nargin>3 + Options=mergestructs(Options,struct(varargin{:})); +end +if isempty(s) + s=shiftdim(std(diff(y,[],3)),1)./sqrt(size(y,1)); % New... + s=repmat(s,1,size(y,3)); + s=s/2; % divide Standard errot by 2 to represent 1-tail type statistical inference (well u know...) + y=shiftdim(mean(y),1); +end +if isempty(x) + x=[1:size(y,1)]'; +end + +if prod(size(y))~=max(size(y)) + Ys=y; + holdstate=ishold; + y=y(:,:); + s=s(:,:); + for i=1:size(y,2) + o=Options; + o.Color=circshift(Options.Color,1-i); + o.PatchColor=circshift(Options.PatchColor,1-i); + [h(i,:)]=ploterr(x,y(:,i),s(:,i),o); + hold on + end + if ~holdstate + hold off + end + return +end + +px=[x(:); flipud(x(:))]; % use px=[x1;x2(end:-1:1)]; if row vecs +py=[ y(:)-s(:) ; flipud(y(:)+s(:)) ]; % use ... + +holdstate=ishold; +if ~holdstate + delete(get(gca, 'Children')) +end +h=patch(px, py, Options.PatchColor(1,:)); +% set(h, 'FaceAlpha', .5) +hold on +h=[plot(x,y, 'LineWidth', 2,'Color', Options.Color(1,:)) h]; +set([h(:,2)], 'FaceAlpha', .35); +if ~holdstate + hold off; +end + +return + diff --git a/plotlabel.m b/plotlabel.m new file mode 100644 index 0000000..e5fb1a3 --- /dev/null +++ b/plotlabel.m @@ -0,0 +1,60 @@ +function [] = plotlabel(h,t) +%PLOTLABEL - Add text label near each plot +% [] = plotlabel(h) add a label near each point of the plot (default: +% current plot) +% [] = plotlabel(ax) add a label near each child of the axes + +% Example +% >> plotlabel +% +% See also: text + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-01-28 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + h=gco; + t=[]; +end +if ~ishandle(h) & iscell(h) + if nargin==2 + o=t; + else + o=gco; + end + t=h; + h=o; +end + +x=get(h,'XData'); +y=get(h,'YData'); +z=get(h,'ZData'); +n=length(x); +if n>100 + error(); +end +for i=1:n + if isempty(z) + if ~isempty(t) + ht(i)=text(x(i),y(i),t{i}); + else + ht(i)=text(x(i),y(i),sprintf('%d [ %.2g ; %.2g ]', i, x(i),y(i))); + end + else + if ~isempty(t) + ht(i)=text(x(i),y(i),z(i),t{i}); + else + ht(i)=text(x(i),y(i),z(i),sprintf('%d [ %.2g ; %.2g ; %.2g ]', i, x(i),y(i),z(i))); + end + end +end +set(ht, 'ButtonDownFcn', 'set(gcbo, ''Visible'', ''off'')'); \ No newline at end of file diff --git a/plotlinearfit.m b/plotlinearfit.m new file mode 100644 index 0000000..df549cf --- /dev/null +++ b/plotlinearfit.m @@ -0,0 +1,67 @@ +function [h,slope,offset,R2,SCE,P,T] = plotlinearfit(Y,X,varargin) +%PLOTLINEARFIT - One line description goes here. +% [h,slope,offset,R2,SCE,P,T] = plotlinearfit(Y,X) +% +% Example +% >> plotlinearfit(Y,X) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-07-01 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + error('No data!') +end +switch nargin + case 0 + error('No input!') + case 1 + [slope,offset,R2,SCE,P,T] = linearfit(Y); + X=1:size(Y,1); + otherwise + [slope,offset,R2,SCE,P,T] = linearfit(Y,X); +end +% [s,o,r2,sce,p]=linearfit(roi.allcons,roi.allregressors); +% text(median(roi.allregressors), quantile(roi.allcons,.90), {'Correlation: ' sprintf('r2 = %g\np = %g', r2,p)}) +% xlabel(xSPM.SPM.xX.name(find(xSPM.SPM.xCon(Icc).c))) +% ylabel(xSPM.SPM.xY.VY(1).descrip) +if size(X,2) == 1 + h=plot(X, Y,'.', varargin{:}); +elseif size(X,2) == 2 + for i=1:size(Y,2) + h(i)=stem(X(:,1),X(:,2),Y(:,i),'.', varargin{:}); + end +else +end +hold on; +h=h(:); +set(h, 'linestyle', 'none') +[xx]=axis; +for i=1:size(Y,2) + h(i,2)=plot(xx(1:2)', xx(1:2)'*slope(i)+(xx(1:2)'.*0+1)*offset(i), ... + '--', 'Color', get(h(i), 'Color'), 'Marker', 'none'); + hold on +end +set(h(P<.05,2),'LineStyle', '-'); +hold off +if nargout==0 + set(h(P>0.05,2),'LineStyle',':'); + fprintf('Slope....: %s\n',sprintf('% 5.2g\t',slope)); + fprintf('Offset...: %s\n',sprintf('% 5.2g\t',offset)); + fprintf('r2.......: %s ; r = %s\n',sprintf('% 5.2g\t',R2),sprintf('% 5.2g\t',sqrt(R2))); + fprintf('p-value..: %s\n',sprintf('% 5.2g\t',P)); + fprintf('SCE......: %s\n',sprintf('% 5.2g\t',SCE)); + fprintf('T........: %s\n',sprintf('% 5.2g\t',T)); +end + + diff --git a/plotnd.m b/plotnd.m new file mode 100644 index 0000000..7bcbf85 --- /dev/null +++ b/plotnd.m @@ -0,0 +1,472 @@ +function [varargout]=plotnd(action,varargin) +% plotnd - plots multidimensional data typically [ Channels x Time x Trials ] +% +% +%OPTIONS: +% 'XDim': abscissa dimension. Default: imax(size(data)),... +% 'DimensionNames', {{'Channel', 'Trial' , 'Condition', 'Field4', 'Field5'}} +% 'X': +% 'XLim' +% 'Values' +% 'Interactive', 1 +% 'LinkedAxes': Plotting axes that should be linked +% +% Example +% >> plotnd(F) +% >> plotnd('plot',F,Options) +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2004 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2004-12-15 Creation +% KND 2005-12-15 Now links between many plotdata axes +% KND 2007-04-03 Renamed plotnd (because 'plotdata' is an eeglab function) +% KND 2009-09-09 Added zoom ability +% ----------------------------- Script History --------------------------------- +if nargin<1 + error('No data!') + +elseif all(ishandle(action(:))) && (nargin==2) + if isstruct(varargin{1}) && isfield(varargin{1},'VerticalScrollAmount') + hf=action; + action = 'wheelzoom'; + varargin=[ {hf} varargin(:) ]; + end +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='plot'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_plot(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'DimensionNames', {{'Channel','Time','Trial','Condition', 'Field4', 'Field5'}} ,... + 'X', [] ,... + 'XDim', [] ,... + 'XLim', [], ... + 'Values', [], ... + 'Interactive', 1, ... + 'LinkedAxes', [], ... % Link to other plots + 'ColorDim', NaN , ... + 'LineStyleDim', NaN ... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2);% struct(varargin{:}); + elseif isnumeric(varargin{1}) + OPTIONS.X=varargin{1}; + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- + +if ~isfield(OPTIONS, 'XDim') || isempty(OPTIONS.XDim) + if isfield(OPTIONS, 'X') && ~isempty(OPTIONS.X) + OPTIONS.XDim=find(size(data) == numel(OPTIONS.X)); + if numel(OPTIONS.XDim)>1 + warning('Multiple dimensions match the size of X... I take the 1st one'); + end + else + OPTIONS.XDim=imax(size(data)); + end +end + +%% Reshape data & update dimension names +nf=ndims(data); +sz0 = size(data); +permdim = [OPTIONS.XDim setdiff(1:nf,OPTIONS.XDim)]; +ipermdim(permdim) = 1:numel(permdim); +z = permute(data,permdim); +sz=[size(z) 1]; +if isempty(OPTIONS.X) + X=1:size(z,1); +else + X=OPTIONS.X; +end +if length(OPTIONS.DimensionNames) < nf + OPTIONS.DimensionNames(end+1:nf)=regexprep(cellstr(num2str([length(OPTIONS.DimensionNames)+1:nf]')), '(.*)', 'dim_$1'); +end +for i=1:nf + if isempty( OPTIONS.DimensionNames{i} ) + OPTIONS.DimensionNames{i}=sprintf('Dim #%d',i); + if i==OPTIONS.XDim + OPTIONS.DimensionNames{i}=[ OPTIONS.DimensionNames{i} ' (X-axis)']; + end + end +end +%% Plot options +cla +sz=[size(z)]; +if numel(sz)<3 +sz=[sz 1]; +end +ncurves = prod(sz(2:end)); +if isnan(OPTIONS.ColorDim) + try + OPTIONS.ColorDim = subarray(setdiff(find(sz0>1),OPTIONS.XDim),1); + catch + OPTIONS.ColorDim = []; + end +end +if isnan(OPTIONS.LineStyleDim) + try + OPTIONS.LineStyleDim = subarray(setdiff(find(sz0>1),OPTIONS.XDim),2); + catch + OPTIONS.LineStyleDim = []; + end +end +if ~isfield(OPTIONS, 'ColorOrder') + co = get(gca, 'ColorOrder'); + d=ipermdim(OPTIONS.ColorDim); + if size(co,1)>=sz(d) + % Enough colors in the ColorOrder + OPTIONS.ColorOrder = co(1:sz(d),:); + else + OPTIONS.ColorOrder=co; + OPTIONS.ColorOrder(end+[1:ncurves-length(co)],:) = rand(ncurves-length(co),3); + end +end +if ~isfield(OPTIONS, 'LineStyleOrder') + lso = get(gca, 'LineStyleOrder'); + if ischar(lso) + lso=strread(lso, '%s', 'delimiter', '|'); + end + OPTIONS.LineStyleOrder = lso; + d=ipermdim(OPTIONS.LineStyleDim); + if length(lso)

    Journal

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    1998

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    2001

    2002

    NATURE22,13922,32625,46627,07428,41727,36828,83329,49125,81427,955
    SCIENCE20,96721,07422,06721,91123,60524,67624,38624,59523,87223,329
    P NATL ACAD SCI USA10,4810,32510,66710,5210,2449,049,82110,2610,7891,896
    P ROY SOC LOND B BIO3,0393,1372,792,5892,8672,8733,0332,7553,0373,192
    PHILOS T ROY SOC B2,1151,7682,192,2812,8322,5122,8862,653,5163,66
    ACTA NEUROBIOL EXP0,4130,5050,5510,480,560,7660,50,6310,767
    ACTA NEUROCHIR0,8220,7280,7480,6560,4980,6230,7481,040,8170,957
    ACTA NEUROL BELG0,3880,1630,2290,3330,3290,2530,2260,2750,521
    ACTA NEUROL SCAND1,1220,9771,1331,1421,0680,9021,1081,3251,3041,64
    ACTA NEUROPATHOL2,942,3952,1682,5462,9462,2992,3362,4022,4462,165
    ACTA NEUROPSYCHIATR0,0890,2980,0360,338
    ADV NEUROL0,9681,142
    AKTUEL NEUROL0,2930,1960,3230,2770,2350,240,2750,3140,2960,356
    AM J ELECTRONEUROD T0,0770,0940,0650,53
    AM J NEURORADIOL2,0591,8451,7331,5561,751,7071,8692,3582,1262,24
    ANN NEUROL6,327,0357,6246,6998,7159,5139,4558,3218,488,481
    ANNU REV NEUROSCI20,42227,62917,95329,08333,62521,95223,02322,6526,67627,152
    ARCH CLIN NEUROPSYCH0,750,8421,3950,988
    ARCH NEUROL-CHICAGO3,5173,1643,8514,263,7783,7793,3753,8634,3934,53
    ARQ NEURO-PSIQUIAT0,1410,1730,1970,228
    AUDIOL NEURO-OTOL2,0182,392,532
    AUDIT NEUROSCI2,461,929
    AUTON NEUROSCI-BASIC00,930
    BEHAV NEUROL0,250,2630,2560,333
    BEHAV NEUROSCI2,7292,993,2632,9692,5282,6653,0262,7192,7512,86
    BRIT J NEUROSURG0,9380,5340,5330,5460,5020,5380,5740,5390,563
    CAN J NEUROL SCI1,1811,531,7121,5441,0331,171,0741,2921,5041,317
    CELL MOL NEUROBIOL2,4122,441,6431,3491,6861,9681,961,7522,0932,12
    CESK SLOV NEUROL N0,0290,0650,0590,41
    CHILD NEUROPSYCHOL0,3140,9410,60,565
    CLIN NEUROL NEUROSUR0,3530,3260,4890,5940,6190,6130,4060,5640,6190,595
    CLIN NEUROPATHOL1,0491,3180,840,9350,7470,6360,9060,9681,0120,553
    CLIN NEUROPHARMACOL1,5682,1872,0711,5321,2511,6041,6362,0161,9431,533
    CLIN NEUROPHYSIOL1,6721,922
    CLIN NEUROPSYCHOL0,6740,5610,9480,551
    CLIN NEUROSCI0,6561,3331,3531,751,0141,781
    COGN NEUROPSYCHOL3,397
    COGNITIVE NEUROPSYCH2,92,4922,18
    CRIT REV NEUROBIOL7,7785,750
    CRIT REV NEUROSURG0,0940,2750,2330,227
    CURR OPIN NEUROBIOL5,3457,0797,3568,8549,2879,2779,995
    CURR OPIN NEUROL0,4730,9411,3951,8691,8552,4972,9933,1764,35
    DEV MED CHILD NEUROL1,1021,2081,171,1771,7781,5631,3161,4711,781,988
    DEV NEUROPSYCHOL1,361,0830,8710,914
    DEV NEUROSCI-BASEL0,7271,0380,6130,7561,2211,5961,672,1532,5231,93
    ELECTROEN CLIN NEURO1,8721,6991,6171,8942,0272,42,452,8613,327
    EUR J NEUROL0,6410,6080,670,9521,358
    EUR J NEUROSCI4,824,564,9514,9214,3033,9473,823,8993,8623,919
    EUR NEUROL1,3511,5630,8990,9151,2571,221,051,37911,179
    EUR NEUROPSYCHOPHARM1,9332,3281,6241,8521,7782,3872,0452,437
    EXP NEUROL3,1442,9582,8033,4513,6043,452,8633,263,8583,53
    FOLIA NEUROPATHOL0,2110,3380,2580,471
    FORTSCHR NEUROL PSYC0,430,5240,6170,670,5870,5170,4410,6020,6360,593
    FRONT NEUROENDOCRIN6,2616,0458,2387,875,7787,1117,257,8268,37515
    FUNCT NEUROL0,4120,5310,710,463
    GIORN NEUROPSI EVOL0,0310
    GIORN NEUROPSICOFARM000
    INT J DEV NEUROSCI1,7481,3391,5571,6481,3521,4061,4971,4251,5832,156
    INT J NEUROPSYCHOPH1,8331,3232,779
    INT J NEURORADIOL0,4150,3590,1390,238
    INT J NEUROSCI0,5270,622
    INT REV NEUROBIOL4,86,5881,8282,43,52,9441,78
    INTERV NEURORADIOL0,5850,441
    ITAL J NEUROL SCI0,1880,1980,3390,2160,2610,4180,4210,3490,1620,635
    J CHEM NEUROANAT3,3541,6171,9432,0921,5691,6672,7112,5522,1411,649
    J CHILD NEUROL1,3471,1320,920,9240,8970,9180,9291,0951,1341,393
    J CLIN EXP NEUROPSYC1,8142,8212,1561,5851,2011,3171,3671,2651,0671,14
    J CLIN NEUROPHYSIOL1,5831,5891,4251,1552,1641,4591,5841,9152,1732,538
    J CLIN NEUROSCI0,3850,320,2620,2920,1440,1780,392
    J COGNITIVE NEUROSCI3,5714,0634,3833,6794,8445,225,7935,1156,736
    J COMP NEUROL3,5553,6573,4683,5843,7483,7583,4763,7643,7723,515
    J COMPUT NEUROSCI2,6112,6222,2862,3462,596
    J INT NEUROPSYCH SOC2,3762,340
    J MOL NEUROSCI2,3512,4671,8751,4581,5222,0771,9121,6091,7651,688
    J NEUROBIOL2,8132,4094,1184,5684,8062,8142,8713,333,4653,34
    J NEUROCHEM4,2154,2234,5254,8524,2194,2344,6514,9064,94,834
    J NEUROCYTOL2,4912,3842,562,5362,6791,9732,1541,861,2311,776
    J NEUROENDOCRINOL2,3912,6162,5392,9892,8562,5632,8322,3772,5982,58
    J NEUROGENET1,9092,3642,51,6671,2350,9571,3571,6921,9381,125
    J NEUROIMAGING0,8350,6521,0440,9740,9420,926
    J NEUROIMMUNOL2,9642,9553,1883,6393,0832,8453,2853,2333,3553,342
    J NEUROL1,7361,791,8491,5811,9441,9762,32,8462,0612,653
    J NEUROL NEUROSUR PS2,6962,2612,5342,5042,933,0412,9382,7352,8463,24
    J NEUROL ORTH MED S0,0160,4
    J NEUROL REHABIL0,220,2980,385
    J NEUROL SCI2,3852,1651,7761,8671,7351,4531,8381,6851,6781,986
    J NEUROLINGUIST0,3780,9090,5140,722
    J NEURO-ONCOL1,3411,2771,0960,7771,1111,2321,6411,6551,5811,435
    J NEURO-OPHTHALMOL0,0240,6240,3890,2730,3740,2520,778
    J NEUROPATH EXP NEUR4,9044,2735,3675,8314,7844,2535,3665,595,5655,533
    J NEUROPHYSIOL3,8744,1344,0013,5783,8343,2633,4113,9353,8553,517
    J NEUROPSYCH CLIN N1,7372,0371,5731,7951,6973,2092,141,632
    J NEURORADIOLOGY0,3270,3330,4260,3040,3770,5880,3680,5220,62
    J NEUROSCI7,168,0358,6578,2057,9557,9158,4038,9558,5028,178
    J NEUROSCI METH1,5671,5231,4421,8151,4121,3351,431,3621,4771,659
    J NEUROSCI RES3,1973,0053,6373,3772,8432,4422,8743,1263,2073,378
    J NEUROSURG2,5152,6883,2963,0122,7692,9993,3723,3462,9182,748
    J NEUROSURG ANESTH0,6380,8311,4331,6521,2371,3331,1440,9340,9370,739
    J NEUROTRAUM2,1442,8023,0153,0863,0193,4042,8773,952
    J NEUROVIROL1,8332,4571,7292,0983,3972,71
    J PSYCHIATR NEUROSCI0,9661,6962,0392,516
    JNMS-J NEUROMUSC SYS0,1110,1250,1030,111
    KLIN NEUROPHYSIOL0,3210,2030,156
    MINIM INVAS NEUROSUR0,0770,5250,6490,6920,7440,667
    MOL CELL NEUROSCI3,3072,5293,2596,086,0895,6545,7465,446
    MOL CHEM NEUROPATHOL0,6361,0381,2451,1511,0640,780,881,0941,163
    MOL NEUROBIOL0,8112,2863,2551,62,3853,4834,3885,6234,3822,4
    NAT NEUROSCI8,86312,63615,668
    NAT REV NEUROSCI014,353
    NEUROBIOL AGING3,5273,4343,1012,112,1212,8723,5173,3994,1594,49
    NEUROBIOL DIS2,6114,2254,8695,0235,3334,487
    NEUROBIOL LEARN MEM1,5742,1221,8412,8053,041,83
    NEUROCASE1,0121,2681,8711,312
    NEUROCHEM INT1,8551,5181,4342,2361,9881,7051,7812,1752,6623,4
    NEUROCHEM RES1,4321,591,5761,5771,2921,311,6771,7551,8581,638
    NEUROCHIRURGIE0,4040,4290,5050,2810,2830,3880,3090,3360,390,346
    NEUROCIRUGIA0,0570,1850,1540,13
    NEUROCOMPUTING0,2430,6090,5770,4220,4530,360,6360,534
    NEUROENDOCRINOLOGY2,8412,7022,4222,6842,4452,44133,2142,7442,144
    NEUROEPIDEMIOLOGY0,9490,78611,0471,6541,3971,3531,8031,6541,39
    NEUROGASTROENT MOTIL1,3551,51,7211,6921,9362,0812,5
    NEUROGENETICS1,872,0942,5963,69
    NEUROIMAG CLIN N AM0,6770,831,0950,957
    NEUROIMAGE2,7860,7781,6174,3115,6118,936,8577,879
    NEUROIMMUNOMODULAT0,741,6092,7011,989
    NEUROL CLIN1,1551,0421,7610,8950,9441,331,3751,5660,8961,283
    NEUROL CROATICA0,09400,032
    NEUROL INDIA0,10,0570,0920,173
    NEUROL MED-CHIR0,386
    NEUROL PSYCHIAT BR0,2160,3330,278
    NEUROL RES0,6970,8521,1421,0271,1281,10,8661,176
    NEUROL SCI00,380
    NEUROL SURG TOKYO0,0920,1580,1560,12
    NEUROLOGIST0,3120,3970,2720,22
    NEUROLOGY4,3553,994,3474,6334,6124,5264,9725,2324,7815,212
    NEUROMODULATION2,0951,2161,96
    NEUROMUSCULAR DISORD1,4771,8182,7182,3512,5822,7492,7182,547
    NEURON15,58917,25618,34816,61916,95315,82116,50516,78215,08114,153
    NEURO-OPHTHALMOLOGY0,4570,2980,3720,2890,3740,3680,3610,450,3760,176
    NEURO-ORTHOPEDICS0,2730,222
    NEUROPATH APPL NEURO2,3262,3761,9831,8892,2042,1211,5912,5752,5232,963
    NEUROPATHOLOGY0,6910,4130,4870,575
    NEUROPEDIATRICS0,9261,20,7291,0081,3891,9851,5451,6691,5971,476
    NEUROPEPTIDES1,7972,1642,0261,6010,9640,9051,241,0751,4131,959
    NEUROPHARMACOLOGY2,2461,9972,4243,6344,4583,9093,244,1764,1253,854
    NEUROPHYSIOL CLIN0,4690,350,4330,4220,3690,5320,5161,33
    NEUROPHYSIOLOGY0,1140,1770
    NEUROPHYSIOLOGY+0,0270,870
    NEUROPSY NEUROPSY BE0,9740,6880,7930,6950,50,7580,8961,347
    NEUROPSYCHIATRIE0,1250,2350,3870,135
    NEUROPSYCHOBIOLOGY0,3680,3940,9861,050,8550,8210,8460,9531,561,64
    NEUROPSYCHOL REHABIL0,9470,6090,6670,759
    NEUROPSYCHOL REV0,7271,1821,250,92
    NEUROPSYCHOLOGIA1,8852,0531,9661,8282,0592,2672,9392,6872,7783,32
    NEUROPSYCHOLOGY2,6133,1132,7022,486
    NEUROPSYCHOPHARMACOL3,6612,5212,783,5673,9364,1054,3184,8584,5794,715
    NEURORADIOLOGY1,0510,9350,90,8580,9970,7541,0231,2870,9971,97
    NEUROREHAB NEURAL RE0,190,610
    NEUROREPORT2,2773,0792,572,4872,2622,5912,6822,6962,374
    NEUROSCI BIOBEHAV R2,4962,8573,7932,992,7863,3163,5953,3825,212
    NEUROSCI LETT2,4192,6452,7032,3182,091,7681,9342,0852,0912,21
    NEUROSCI RES1,9782,0592,1412,1652,1021,5231,7751,7261,8071,77
    NEUROSCI RES COMMUN0,9691,1910,9170,871,0740,8740,7420,9890,5380,67
    NEUROSCIENCE4,3244,5824,6264,2883,9083,5943,5913,9243,5633,219
    NEUROSCIENTIST2,1742,2331,9181,42
    NEUROSURG CLIN N AM0,8710,9220,9331,2650,783
    NEUROSURG QUART0,50,7670,50,217
    NEUROSURG REV0,3720,290,2560,1560,20,1610,3270,2860,3580,478
    NEUROSURGERY1,5541,4361,671,0060,7311,1132,42,8212,8992,783
    NEUROTOXICOL TERATOL1,5711,7031,8961,5451,9791,1871,321,8222,288
    NEUROTOXICOLOGY0,8951,3841,511,3631,2841,7281,2051,2821,741,576
    NEUROUROL URODYNAM0,7271,1920,7161,3432,1222,082,4182,4381,9682,266
    PEDIATR NEUROL0,9171,2561,0341,0780,8250,9180,9211,1191,0071,11
    PEDIATR NEUROSURG0,4490,3290,5320,7040,770,6560,7960,7350,8110,787
    PERSPECT DEV NEUROBI2,7231,2622,3171,581
    PROG NEUROBIOL7,8097,48186,1845,88855,6887,099,9339,377
    PROG NEURO-PSYCHOPH0,9460,8811,1410,9140,8870,8191,1141,3891,0781,58
    PSYCHIAT CLIN NEUROS0,1380,1910,3820,3480,4520,548
    PSYCHIAT RES-NEUROIM1,2861,9771,6671,7071,9322,1761,3292,191,9192,354
    PSYCHONEUROENDOCRINO1,5711,4861,4831,6992,2541,9921,8692,0453,0083,369
    RESTOR NEUROL NEUROS2,6091,4350,9150,561,1171,1960,50,9110,678
    REV ECUAT NEUROL0,17200,1060,4
    REV NEUROL0,8130,8820,6550,5140,5351,111,451,0130
    REV NEUROL-FRANCE0,6920,598
    REV NEUROLOGIA0,2650,2560,26
    REV NEUROPSYCHOL0,2110,1750,2860,262
    REV NEUROSCI1,7593,3873,43,794
    RIV NEURORADIOL0,0630,1060,0510,128
    SEMIN NEUROL0,6630,5650,4240,5640,6950,5110,671,3661,6351,49
    SEMIN NEUROSCI1,9892,1722,0833,3253,5962,71,667
    STEREOT FUNCT NEUROS0,2840,4460,6570,672
    SURG NEUROL0,7140,6850,6250,5290,3420,3280,7241,041,0180,936
    TECH NEUROSURG0,2150,290
    TRENDS NEUROSCI15,42617,29920,19419,97217,75517,08418,46319,92517,41716,475
    VISUAL NEUROSCI2,162,2122,2722,1372,491,8872,1862,2042,1492,351
    ZBL NEUROCHIR0,2220,40,9390,688
    ACTA NEUROPSYCHIATR0,0890,2980,0360,338
    ACTA PSYCHIAT SCAND1,31,1421,4951,4181,5951,5881,5541,6191,7742,17
    AM J GERIAT PSYCHIAT2,436
    AM J ORTHOPSYCHIAT0,921,0620,8591,0161,0541,7182,2671,4441,9391,55
    AM J PSYCHIAT4,8244,9544,575,126,0696,5015,9396,3416,5776,913
    ANN MED-PSYCHOL0,1050,0550,1120,1440,1920,210,2080,2380,236
    ANNU REV PSYCHOL5,7255,556,8816,8215,4394,8416,3957,5455,8515,979
    ARCH CLIN NEUROPSYCH0,750,8421,3950,988
    ARCH GEN PSYCHIAT8,2279,50511,41611,15511,50910,7519,39810,95211,77811,981
    AUST NZ J PSYCHIAT0,7840,6240,6350,6450,8570,5740,8471,1971,2650,858
    BIOL PSYCHIAT2,572,6012,1482,3522,4842,2542,4053,3194,2695,55
    BIOL PSYCHOL1,0261,0561,81,4741,51,778
    BRIT J MED PSYCHOL0,6710,4790,4590,5920,9390,6670,7020,8810,5620,674
    BRIT J PSYCHIAT2,3092,3192,862,9513,3933,2653,5034,0934,8274,143
    CAN J PSYCHIAT0,70,5430,5470,7180,8321,1511,0581,4621,6231,624
    CHILD NEUROPSYCHOL0,3140,9410,60,565
    CHILD PSYCHIAT HUM D0,2130,2340,3540,5320,3410,4880,4520,3780,4220,625
    CLIN NEUROPSYCHOL0,6740,5610,9480,551
    COGN NEUROPSYCHOL3,397
    COGNITIVE NEUROPSYCH2,92,4922,18
    COGNITIVE PSYCHOL3,7374,1673,4633,711
    COMPR PSYCHIAT1,4451,0711,2731,6221,521,2461,2341,6881,41,28
    DEV NEUROPSYCHOL1,361,0830,8710,914
    DEV PSYCHOBIOL1,1441,1881,4211,0411,2031,4351,5961,3121,3221,286
    EDUC PSYCHOL MEAS0,3240,2280,3680,3170,3160,4440,6180,6230,6080,789
    EUR NEUROPSYCHOPHARM1,9332,3281,6241,8521,7782,3872,0452,437
    EUR PSYCHIAT0,5440,4970,3940,5910,7481,72
    EXP CLIN PSYCHOPHARM1,511,251,7471,726
    GEN HOSP PSYCHIAT0,7390,921,1161,0281,3371,2981,1441,41,5122,65
    HUM PSYCHOPHARM CLIN0,8180,8540,8690,850,9410,5840,6091,1030,968
    INT CLIN PSYCHOPHARM0,750,8161,3642,2271,6381,9261,5571,0962,0762,295
    INT J GERIATR PSYCH1,5631,4951,778
    INT J NEUROPSYCHOPH1,8331,3232,779
    INT J PSYCHIAT MED0,7970,5520,7410,9181,0820,9440,631,2071,0330,714
    INT J PSYCHOPHYSIOL0,870,6840,8750,5851,0890,7031,1481,8291,4891,747
    INT J SPORT PSYCHOL0,2760,4790,8040,386
    J APPL SPORT PSYCHOL0,970
    J CHILD ADOL PSYCHOP1,3881,9331,6092,11,9821,754
    J CLIN PSYCHIAT2,5542,7693,133,3374,2934,0034,0734,1724,4544,735
    J CLIN PSYCHOPHARM3,6793,3663,4964,9635,35,0945,3385,7385,0524,13
    J COMP PSYCHOL1,2021,4041,5171,4091,6021,5631,7441,571,4771,663
    J EXP PSYCHOL ANIM B1,7752,562,5161,1591,9831,3971,2671,441,3651,95
    J EXP PSYCHOL HUMAN2,4062,3322,2472,498
    J EXP PSYCHOL LEARN2,8383,2052,7532,21
    J GERIATR PSYCH NEUR0,8021,2721,2220,8810,9091,263
    J GERONTOL B-PSYCHOL1,5542,3311,2241,5431,1021,594
    J INT NEUROPSYCH SOC2,3762,340
    J MATH PSYCHOL1,4210,8640,80,7660,780,7920,660,6921,0561,195
    J NEUROPSYCH CLIN N1,7372,0371,5731,7951,6973,2092,141,632
    J PSYCHIAT RES1,4031,0181,0851,5312,1591,6051,3622,1522,332,776
    J PSYCHIATR NEUROSCI0,9661,6962,0392,516
    J PSYCHOPHARMACOL1,3081,8881,4261,3811,4662,8272,3282,642
    J PSYCHOPHYSIOL0,5930,5370,6850,587
    J PSYCHOSOM OBST GYN0,4240,6480,3020,6270,5560,60,6060,7170,5290,67
    J PSYCHOSOM RES1,2220,9741,1021,1611,5841,0061,1291,5731,4461,717
    MOL PSYCHIATR2,1624,7567,9428,9276,25
    NEUROL PSYCHIAT BR0,2160,3330,278
    NEUROPSYCHIATRIE0,1250,2350,3870,135
    NEUROPSYCHOBIOLOGY0,3680,3940,9861,050,8550,8210,8460,9531,561,64
    NEUROPSYCHOL REHABIL0,9470,6090,6670,759
    NEUROPSYCHOL REV0,7271,1821,250,92
    NEUROPSYCHOLOGIA1,8852,0531,9661,8282,0592,2672,9392,6872,7783,32
    NEUROPSYCHOLOGY2,6133,1132,7022,486
    NEUROPSYCHOPHARMACOL3,6612,5212,783,5673,9364,1054,3184,8584,5794,715
    PERCEPT PSYCHOPHYS1,2521,492
    PHARMACOPSYCHIATRY1,1331,41,61,1171,2182,0532,3042,8032,39
    PROG NEURO-PSYCHOPH0,9460,8811,1410,9140,8870,8191,1141,3891,0781,58
    PSYCHIAT CLIN NEUROS0,1380,1910,3820,3480,4520,548
    PSYCHIAT RES1,8751,4741,6921,4731,4891,3271,4241,5511,5571,775
    PSYCHIAT RES-NEUROIM1,2861,9771,6671,7071,9322,1761,3292,191,9192,354
    PSYCHIATR GENET1,862,0162,6091,257
    PSYCHIATR SERV0,9351,4661,571,7471,7951,589
    PSYCHIATRY0,6230,6670,9031,260,7310,7681,2550,9440,8271,2
    PSYCHOBIOLOGY2,0711,7911,5380,9521,2321,0510,8151,2821,1941,652
    PSYCHOL BULL4,9585,1976,6976,9666,5916,0386,3467,796,9136,87
    PSYCHOL MED2,1772,6632,4332,7152,8153,0173,1243,3893,4123,119
    PSYCHOL REV6,4856,57,1875,0585,217,068,2396,8036,0695,756
    PSYCHOMETRIKA0,7870,6360,6230,7680,8330,6560,9330,8240,8980,85
    PSYCHONEUROENDOCRINO1,5711,4861,4831,6992,2541,9921,8692,0453,0083,369
    PSYCHO-ONCOL1,388
    PSYCHOPATHOLOGY0,4330,3270,4460,4510,7070,5750,4740,4250,5470,469
    PSYCHOPHARMACOL BULL1,6711,7291,4391,4311,5711,8162,592,2452,809
    PSYCHOPHARMACOLOGY2,7692,52,5492,8822,5992,9333,0322,9182,8043,145
    PSYCHOPHARMAKOTHERAP0,1970,3010,171
    PSYCHOPHYSIOLOGY2,6382,3492,6592,9482,8272,7742,4323,0063,1063,35
    PSYCHOSOM MED2,6932,3112,8082,9123,0313,0893,0462,6243,2462,815
    PSYCHOSOMATICS1,41,0711,1691,3212,1321,7071,5411,1741,5551,926
    PSYCHOTHER PSYCHOSOM0,3760,7521,0591,0471,5781,8052,1032,2592,3723,429
    Q J EXP PSYCHOL-A1,9481,5611,4521,28
    Q J EXP PSYCHOL-B1,31,1321,2751,1281,3491,4191,221,33311,4
    REV NEUROPSYCHOL0,2110,1750,2860,262
    SPORT PSYCHOL0,8730,9670,6490,76
    Z PSYCHOSOM MED PSYC0,3590,5760,460,4910,440,371,2090,4440,633
    BEHAV BRAIN RES1,8541,4441,5631,8621,6132,342,7962,3182,2632,473
    BEHAV BRAIN SCI0,2970,4260,63915,62598,1188,811,27614,2517,312
    BRAIN3,5893,8935,0354,8675,7395,3815,9527,3747,3037,47
    BRAIN BEHAV EVOLUT1,5491,9591,4171,5771,491,7861,5591,651,3811,635
    BRAIN BEHAV IMMUN2,7592,5242,3191,4841,951,752,1111,6882,1842,23
    BRAIN COGNITION1,51,231,3731,111,0730,5660,5080,7360,630,791
    BRAIN DEV-JPN0,7870,5760,6880,7090,5390,570,7611,3031,1551,49
    BRAIN INJURY0,880,8431,2561,0851,0170,9140,924
    BRAIN LANG1,1970,7130,9761,6581,41,5792,1161,9291,4731,38
    BRAIN PATHOL4,258,5676,4555,6634,8974,1546,4358,654
    BRAIN RES2,8652,8542,8692,6872,5262,1192,152,3022,5262,489
    BRAIN RES BULL1,6921,5991,8111,7941,6411,7081,651,9771,7581,783
    BRAIN RES PROTOC0,2820,7811,0671,284
    BRAIN RES REV9,7429,09410,20713,9627,61911,5536,256,6519,2127,72
    BRAIN TOPOGR0,5771,9061,5961,745
    COGNITIVE BRAIN RES0,882,2221,731,5762,7552,3332,7332,884
    DEV BRAIN DYSFUNCT0,1480,213
    DEV BRAIN RES2,3222,1772,2072,2461,9111,8231,6951,5351,8271,662
    EXP BRAIN RES2,3442,4092,2271,9672,0491,8982,0182,2462,1372,36
    HUM BRAIN MAPP10,0494,7385,285,1635,688
    J BRAIN RES0,3970,6710,2790,182
    METAB BRAIN DIS0,7321,1221,0290,631,751,311,53711,4111,91
    MOL BRAIN RES4,5223,8014,1343,483,4772,7422,4752,5392,6222,538
    PROG BRAIN RES1,8881,2611,4121,6821,4880,7721,951,4252,521,49
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    + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/scalpface.m b/scalpface.m new file mode 100644 index 0000000..a0582e2 --- /dev/null +++ b/scalpface.m @@ -0,0 +1,63 @@ +function [face_t]=scalpface(scalp) +% Convert scalp (a patch structure) to head.mat to be used in EEGLAB +% cf. headplot() + +if 0 %s4head + %Vertices in the face + face_v=find(scalp.vertices(:,3)<-.01 & scalp.vertices(:,1)>.025 ); + % remove also the basal part + x1=-0.0960; + y1=0.0533; + x2=0.0264; + y2=-0.0308; + face_v=[face_v ; find(scalp.vertices(:,3) <= (y2-y1)/(x2-x1)*(scalp.vertices(:,1)-x1)+y1)]; + % Which triangles encompass these vertices + face_t=[]; + for v=face_v' + face_t=[face_t; find(scalp.faces(:,1)==v | scalp.faces(:,2)==v |scalp.faces(:,3)==v )]; + end + face_t=unique(scalp.faces(face_t,:), 'rows'); + %[ign,face_t]=intersect(scalp.faces(:),face_v); + %[face_t, ign]=ind2sub([length(scalp.faces), 3] , face_t); + %face_t=scalp.faces(face_t,:); + scalp_t=setdiff(scalp.faces, face_t, 'rows'); +end + +% ------------------------- +% Head1 or nicehead +% ------------------------- + nv=size(scalp.vertices,1); +% Distance au centre 1 +d1=sqrt(sum((scalp.vertices(:,[1 3])-repmat([70 230],nv,1)).^2, 2)); +% Distance au centre 2 +d2=sqrt(sum((scalp.vertices(:,[1 3])-repmat([105 -75],nv,1)).^2, 2)); +scalp_v=find((d1 < 265 & d2 > 95 & scalp.vertices(:,[3])> -30)); + +% nicehead: +% scalp_v=find((d1 < 255 & d2 > 95 & scalp.vertices(:,[3])> -30) | (scalp.vertices(:,[3]) > -30 & scalp.vertices(:,[2]) < -69)); + +scalp_t=find(ismember(scalp.faces(:,1), scalp_v) | ismember(scalp.faces(:,2), scalp_v) | ismember(scalp.faces(:,3), scalp_v)); +scalp_t=scalp.faces(scalp_t,:); + +% For NiceHead, add the following line: +% scalp_t=scalp_t([1:629 632:end],:); + +face_t=setdiff(scalp.faces, scalp_t, 'rows'); + + +POS=scalp.vertices; +TRI1=scalp_t; +index1=unique(scalp_t(:)); +TRI2=face_t; +HeadCenter=[0 0 0]; +save head1.mat POS TRI1 TRI2 HeadCenter index1 + +return +% in mhead.mat +% POS 2678x3 64272 double array : vertices +% TRI1 2697x3 64728 double array : scalp +% TRI2 2305x3 55320 double array : face +% center 1x3 24 double array : center shouldn't it be HeadCenter ? +% index1 1612x1 12896 double array : vertices of the scalp + + diff --git a/scrollaxes.m b/scrollaxes.m new file mode 100644 index 0000000..5928d38 --- /dev/null +++ b/scrollaxes.m @@ -0,0 +1,421 @@ +function scrollaxes(arg,arg2) +%scrollaxes Interactively scrollte the view of a 3-D plot. +% scrollaxes ON turns on mouse-based scroll +% scrollaxes OFF turns if off. +% scrollaxes by itself toggles the state. +% +% scrollaxes(FIG,...) works on the figure FIG. +% scrollaxes(AXIS,...) works on the axis AXIS. +% In this latter case, ONLY this axis will be scrollted. +% +% See also ZOOM. + +% scrollaxes on enables text feedback +% scrollaxes ON disables text feedback. + +% Revised by Rick Paxson 10-25-96 +% Clay M. Thompson 5-3-94 +% Copyright 1984-2002 The MathWorks, Inc. +% $Revision: 1.46 $ $Date: 2002/06/14 18:45:51 $ +% KND : 2005-07-06 : Rotate ONLY pre-specified axis, if any. + +if(nargin == 0) + setState(gcf,'toggle'); +elseif nargin==1 + if ishandle(arg) + setState(arg,'toggle') + else + switch(lower(arg)) % how much performance hit here + case 'motion' + scrollMotionFcn + case 'down' + scrollButtonDownFcn + case 'up' + scrollButtonUpFcn + case 'on' + setState(gcf,arg); + case 'off' + setState(gcf,arg); + otherwise + error('Unknown action string.'); + end + end +elseif nargin==2 + if ~ishandle(arg), error('Unknown figure.'); end + switch(lower(arg2)) % how much performance hit here + case 'on' + setState(arg,arg2) + case 'off' + setState(arg,arg2); + otherwise + error('Unknown action string.'); + end +end + +%-------------------------------- +% Set activation state. Options on, ON, off +function setState(target,state) + +% if the target is an axis, restrict to that +if strcmp(get(target,'Type'),'axes') + axis = target; + fig = get(axis,'Parent'); +else % otherwise, allow any axis in this figure + axis = []; + fig = target; +end +scrollObj = findobj(allchild(fig),'Tag','scrollObj'); + +% %KND : Add Button Rotate3DAxes in figure's toolbar +% h=findall(fig,'Tag','figToolRotate3DAxes'); +% if isempty(h) +% %disp('Creating Rotate3DAxes button'); +% h=findall(fig,'Tag','figToolRotate3D'); +% h=copyobj(h, get(h, 'Parent')); +% set(h, 'Tag','figToolRotate3DAxes'); +% set(h, 'ClickedCallback', 'scrollaxes(gca), putdowntext(''scrollaxes'',gcbo)'); +% c=get(h, 'CData'); +% c(6:12,6:12,:)=1; +% c(11,6:12,:)=0; +% c(6:12,7,:)=0; +% set(h, 'CData', c); +% end + +if(strcmp(state,'toggle')) + if(~isempty(scrollObj)) + setState(target,'off'); + else + setState(target,'on'); + end + return; +elseif(strcmp(lower(state),'on')) + if(isempty(scrollObj)) + plotedit(fig,'locktoolbarvisibility'); + scrollObj = makeRotaObj(fig); + if isempty(axis) +% set(findall(fig,'Tag','figToolRotate3D'),'State','on'); + set(findall(fig,'Tag','figToolScrollAxes'),'State','off'); + else +% set(findall(fig,'Tag','figToolRotate3D'),'State','off'); + set(findall(fig,'Tag','figToolScrollAxes'),'State','on'); + end + end + + rdata = getappdata(scrollObj,'ScrollData'); + rdata.destAxis = axis; + + + % Handle toggle of text feedback. ON means no feedback on means feedback. + if(strcmp(state,'on')) + rdata.textState = 1; + else + rdata.textState = 0; + end + setappdata(scrollObj,'ScrollData',rdata); + % set this so we can know if Rotate3d is on + % for now there is only one on state + % and this app data will not exist if it is off + setappdata(fig,'ScrollAxesOnState','on'); + scribefiglisten(fig,'on'); +elseif(strcmp(lower(state),'off')) + scribefiglisten(fig,'off'); +% set(findall(fig,'Tag','figToolScroll'),'State','off'); +% set(findall(fig,'Tag','figToolRotate3DAxes'),'State','off'); + if(~isempty(scrollObj)) + destroyRotaObj(scrollObj); + end + % get rid of on state appdata + % if it exists. + % if isappdata(fig,'Rotate3dOnState') + % rmappdata(fig,'Rotate3dOnState'); + % end + + scribefiglisten(fig,'off'); + state = getappdata(fig,'ScrollAxesFigureState'); + if ~isempty(state) + % since we didn't set the pointer, + % make sure it does not get reset + ptr = get(fig,'pointer'); + % restore figure and non-uicontrol children + % don't restore uicontrols because they were restored + % already when scroll was turned on + uirestore(state,'nouicontrols'); + set(fig,'pointer',ptr) + if isappdata(fig,'ScrollAxesFigureState') + rmappdata(fig,'ScrollAxesFigureState'); + end + end + if isappdata(fig,'ScrollAxesOnState') + rmappdata(fig,'ScrollAxesOnState'); + end +end + +%--------------------------- +% Button down callback +function scrollButtonDownFcn +scrollObj = findobj(allchild(gcbf),'Tag','scrollObj'); +if(isempty(scrollObj)) + return; +else + rdata = getappdata(scrollObj,'ScrollData'); + + %KND: Rotate ONLY the axes which were + if ~isempty(rdata.destAxis) & ~isequal(gca, rdata.destAxis) + return + end + + % Activate axis that is clicked in + allAxes = findobj(datachildren(gcbf),'flat','type','axes'); + axes_found = 0; + funits = get(gcbf,'units'); + set(gcbf,'units','pixels'); + for i=1:length(allAxes), + ax=allAxes(i); + cp = get(gcbf,'CurrentPoint'); + aunits = get(ax,'units'); + set(ax,'units','pixels') + pos = get(ax,'position'); + set(ax,'units',aunits) + if cp(1) >= pos(1) & cp(1) <= pos(1)+pos(3) & ... + cp(2) >= pos(2) & cp(2) <= pos(2)+pos(4) + axes_found = 1; + set(gcbf,'currentaxes',ax); + break + end % if + end % for + set(gcbf,'units',funits) + if axes_found==0, return, end + + if (not(isempty(rdata.destAxis)) & rdata.destAxis ~= ax) + return + end + + rdata.targetAxis = ax; + rdata.XLim = get(ax,'XLim'); + + % store the state on the zlabel: that way if the user + % plots over this axis, this state will be cleared and + % we get to start over. +% viewData = getappdata(get(ax,'ZLabel'),'ROTATEAxesView'); +% if isempty(viewData) +% setappdata(get(ax,'ZLabel'),'ROTATEAxesView', get(ax, 'View')); +% end + + selection_type = get(gcbf,'SelectionType'); + if strcmp(selection_type,'open') + % this assumes that we will be getting a button up + % callback after the open button down + lims = getappdata(get(ax,'ZLabel'),'ROTATEAxesView'); + if(rdata.textState) + set(rdata.textBoxText,'String',... + sprintf('X: %4.0f %4.0f',lims)); + end + set(scrollObj, 'XLim', lims); + return + end + + rdata.oldFigureUnits = get(gcbf,'Units'); + set(gcbf,'Units','pixels'); + rdata.oldPt = get(gcbf,'CurrentPoint'); + rdata.oldLims = [ get(rdata.targetAxis,'XLim') ; get(rdata.targetAxis,'YLim')]; + + setappdata(scrollObj,'ScrollData',rdata); + setOutlineObjToFitAxes(scrollObj); + copyAxisProps(rdata.targetAxis, scrollObj); + + rdata = getappdata(scrollObj,'ScrollData'); + setappdata(scrollObj,'ScrollData',rdata); + + if(rdata.textState) + fig_color = get(gcbf,'Color'); + % if the figure color is 'none', setting the uicontrol + % backgroundcolor to white and the foreground accordingly. + if strcmp(fig_color, 'none') + fig_color = [1 1 1]; + end + c = sum([.3 .6 .1].*fig_color); + set(rdata.textBoxText,'BackgroundColor',fig_color); + if(c > .5) + set(rdata.textBoxText,'ForegroundColor',[0 0 0]); + else + set(rdata.textBoxText,'ForegroundColor',[1 1 1]); + end + set(rdata.textBoxText,'Visible','on'); + end + set(rdata.outlineObj,'Visible','on'); + set(gcbf,'WindowButtonMotionFcn','scrollaxes(''motion'')'); +end + +%------------------------------- +% Button up callback +function scrollButtonUpFcn +scrollObj = findobj(allchild(gcbf),'Tag','scrollObj'); +if isempty(scrollObj) | ... + ~strcmp(get(gcbf,'WindowButtonMotionFcn'),'scrollaxes(''motion'')') + return; +else + set(gcbf,'WindowButtonMotionFcn',''); + rdata = getappdata(scrollObj,'ScrollData'); + set([rdata.outlineObj rdata.textBoxText],'Visible','off'); + rdata.XLim = get(scrollObj,'XLim'); + set(rdata.targetAxis,'XLim',rdata.XLim); +% set(gcbf,'Units',rdata.oldFigureUnits); + setappdata(scrollObj,'ScrollData',rdata) +end + +%----------------------------- +% Mouse motion callback +function scrollMotionFcn +scrollObj = findobj(allchild(gcbf),'Tag','scrollObj'); +rdata = getappdata(scrollObj,'ScrollData'); +switch get(get(rdata.targetAxis, 'Parent'), 'selectiontype') + case {'extend'} + new_pt = get(gcbf,'CurrentPoint'); + old_pt = rdata.oldPt; + dx = new_pt(1) - old_pt(1); + dy = new_pt(2) - old_pt(2); + lims = mappingFunction(rdata, dx, dy); + set(scrollObj,'XLim',lims); + + otherwise + return + plims=get(rdata.targetAxis,'XLim'); + axis(rdata.targetAxis, 'normal'); + axis(rdata.targetAxis, 'tight'); + lims=get(rdata.targetAxis,'XLim'); + set(rdata.targetAxis,'XLim',plims); + set(scrollObj,'XLim',lims); + +end + +% if(new_azel(2) < 0 & rdata.crossPos == 0) +% set(rdata.outlineObj,'ZData',rdata.scaledData(4,:)); +% rdata.crossPos = 1; +% setappdata(scrollObj,'ScrollData',rdata); +% end +% if(new_azel(2) > 0 & rdata.crossPos == 1) +% set(rdata.outlineObj,'ZData',rdata.scaledData(3,:)); +% rdata.crossPos = 0; +% setappdata(scrollObj,'ScrollData',rdata); +% end +setappdata(scrollObj,'ScrollData',rdata); +if(rdata.textState) + set(rdata.textBoxText,'String',sprintf('X: %4.0f %4.0f',lims)); +end + +%---------------------------- +% Map a dx dy to a zoomed window on data +function lims = mappingFunction(rdata, dx, dy) +lims = rdata.XLim; +ctr = (lims(1)+lims(2))/2; +width = (lims(2)-lims(1))/2; +lims = ctr+[-width width]*exp(dy/rdata.GAIN(2)); +lims= lims + width*rdata.GAIN(1)*(-dx); + +%----------------------------- +% Scale data to fit target axes limits +function setOutlineObjToFitAxes(scrollObj) +rdata = getappdata(scrollObj,'ScrollData'); +ax = rdata.targetAxis; +x_extent = get(ax,'XLim'); +y_extent = get(ax,'YLim'); +z_extent = get(ax,'ZLim'); +X = rdata.outlineData; +X(1,:) = X(1,:)*diff(x_extent) + x_extent(1); +X(2,:) = X(2,:)*diff(y_extent) + y_extent(1); +X(3,:) = X(3,:)*diff(z_extent) + z_extent(1); +X(4,:) = X(4,:)*diff(z_extent) + z_extent(1); +set(rdata.outlineObj,'XData',X(1,:),'YData',X(2,:),'ZData',X(3,:)); +rdata.scaledData = X; +setappdata(scrollObj,'ScrollData',rdata); + +%------------------------------- +% Copy properties from one axes to another. +function copyAxisProps(original, dest) +props = { + 'DataAspectRatio' + 'DataAspectRatioMode' + 'CameraViewAngle' + 'CameraViewAngleMode' + 'XLim' + 'YLim' + 'ZLim' + 'PlotBoxAspectRatio' + 'PlotBoxAspectRatioMode' + 'Units' + 'Position' + 'View' + 'Projection' +}; +values = get(original,props); +set(dest,props,values); + +%------------------------------------------- +% Constructor for the Rotate object. +function scrollObj = makeRotaObj(fig) + +% save the previous state of the figure window +% rdata.uistate = uiclearmode(fig,'scroll',fig,'off'); + +rdata.targetAxis = []; % Axis that is being scrollted (target axis) +rdata.destAxis = []; % the axis the caller specified (may be []) +rdata.GAIN = [ 1e-2 40 ] ; % Motion gain +rdata.oldPt = []; % Point where the button down happened +rdata.oldLims = []; +curax = get(fig,'currentaxes'); +scrollObj = axes('Parent',fig,'Visible','off','HandleVisibility','off','Drawmode','fast'); +nondataobj = []; +setappdata(scrollObj,'NonDataObject',nondataobj); +% Data points for the outline box. +rdata.outlineData = [0 0 1 0;0 1 1 0;1 1 1 0;1 1 0 1;0 0 0 1;0 0 1 0; ... + 1 0 1 0;1 0 0 1;0 0 0 1;0 1 0 1;1 1 0 1;1 0 0 1;0 1 0 1;0 1 1 0; ... + NaN NaN NaN NaN;1 1 1 0;1 0 1 0]'; +rdata.outlineObj = line(rdata.outlineData(1,:),rdata.outlineData(2,:),rdata.outlineData(3,:), ... + 'Parent',scrollObj,'Erasemode','xor','Visible','off','HandleVisibility','off', ... + 'Clipping','off'); + +% Make text box. +fig_color = get(fig, 'Color'); + +% if the figure color is 'none', setting the uicontrol +% backgroundcolor to white and the foreground accordingly. +if strcmp(fig_color, 'none') + fig_color = [1 1 1]; +end +rdata.textBoxText = uicontrol('parent',fig,'Units','Pixels','Position',[2 2 130 20],'Visible','off', ... + 'Style','text','BackgroundColor', fig_color,'HandleVisibility','off'); + +rdata.textState = []; +rdata.oldFigureUnits = ''; +rdata.crossPos = 0; % where do we put the X at zmin or zmax? 0 means zmin 1 means zmax +rdata.scaledData = rdata.outlineData; + + +state = getappdata(fig,'Rotate3dFigureState'); +if isempty(state) + % turn off all other interactive modes + state = uiclearmode(fig,'docontext','scrollaxes',fig,'off'); + % restore button down functions for uicontrol children of the figure + uirestore(state,'uicontrols'); + setappdata(fig,'Rotate3dFigureState',state); +end + + +set(fig,'WindowButtonDownFcn','scrollaxes(''down'')'); +set(fig,'WindowButtonUpFcn' ,'scrollaxes(''up'')'); +set(fig,'WindowButtonMotionFcn',''); +set(fig,'ButtonDownFcn',''); + +set(scrollObj,'Tag','scrollObj'); +setappdata(scrollObj,'ScrollData',rdata); +set(fig,'currentaxes',curax) + +%---------------------------------- +% Deactivate scrollte object +function destroyRotaObj(scrollObj) +rdata = getappdata(scrollObj,'ScrollData'); + +% uirestore(rdata.uistate); + +delete(rdata.textBoxText); +delete(scrollObj); diff --git a/sdt.m b/sdt.m new file mode 100644 index 0000000..b6060e6 --- /dev/null +++ b/sdt.m @@ -0,0 +1,57 @@ +function [dprime,logbeta,c] = sdt(varargin) +%SDT - Signal detection théory computations (d-prime, beta, criterion) +% [dprime,logb,c] = sdt(s,r) where s and r are two vectors of 0's and 1's +% +% Example +% >> +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-24 Creation +% +% ----------------------------- Script History --------------------------------- + +s=logical(varargin{1}(:)); +r=logical(varargin{2}(:)); +%Hit rate: +hr = sum(r(s))/sum(s); +fa = sum(r(~s))/sum(~s); +if hr==1 + hr = 1-1/(2*sum(s)); + warning(sprintf('Hit rate is approximated to: %g%%', 100*hr)); +elseif hr==0 + hr = 1/(2*sum(s)); + warning(sprintf('Hit rate is approximated to: %g%%', 100*hr)); +end +if fa==0 + fa = 1/(2*sum(~s)); + warning(sprintf('False alarm rate is approximated to: %g%%', 100*fa)); +elseif fa==1 + fa = 1-1/(2*sum(~s)); + warning(sprintf('False alarm rate is approximated to: %g%%', 100*fa)); +end + + +% Discrimination index (d') +dprime = normalz(hr)-normalz(fa); +% Response bias (or criterion) +c = -(normalz(hr)+normalz(fa))/2; +% Log-likelihood ratio +logbeta = dprime * c; +return + +function z = normalz(p, mu, sigma) +% NORMALZ Normal z-score +% >> z = normalz(p, [mu], [sigma]) +if nargin < 3, sigma = 1; end +if nargin < 2, mu = 0; end +if nargin < 1, error('Not enough input parameters.'); end +z = mu+sqrt(2)*sigma*erfinv(2*p-1); diff --git a/select3d.m b/select3d.m new file mode 100644 index 0000000..0b87699 --- /dev/null +++ b/select3d.m @@ -0,0 +1,381 @@ +function [pout, vout, viout, facevout, faceiout] = select3d(obj) +%SELECT3D(H) Determines the selected point in 3-D data space. +% P = SELECT3D determines the point, P, in data space corresponding +% to the current selection position. P is a point on the first +% patch or surface face intersected along the selection ray. If no +% face is encountered along the selection ray, P returns empty. +% +% P = SELECT3D(H) constrains selection to graphics handle H and, +% if applicable, any of its children. H can be a figure, axes, +% patch, or surface object. +% +% [P V] = SELECT3D(...), V is the closest face or line vertex +% selected based on the figure's current object. +% +% [P V VI] = SELECT3D(...), VI is the index into the object's +% x,y,zdata properties corresponding to V, the closest face vertex +% selected. +% +% [P V VI FACEV] = SELECT3D(...), FACE is an array of vertices +% corresponding to the face polygon containing P and V. +% +% [P V VI FACEV FACEI] = SELECT3D(...), FACEI is the row index into +% the object's face array corresponding to FACE. For patch +% objects, the face array can be obtained by doing +% get(mypatch,'faces'). For surface objects, the face array +% can be obtained from the output of SURF2PATCH (see +% SURF2PATCH for more information). +% +% RESTRICTIONS: +% SELECT3D supports surface, patch, or line object primitives. For surface +% and patches, the algorithm assumes non-self-intersecting planar faces. +% For line objects, the algorithm always returns P as empty, and V will +% be the closest vertex relative to the selection point. +% +% Example: +% +% h = surf(peaks); +% zoom(10); +% disp('Click anywhere on the surface, then hit return') +% pause +% [p v vi face facei] = select3d; +% marker1 = line('xdata',p(1),'ydata',p(2),'zdata',p(3),'marker','o',... +% 'erasemode','xor','markerfacecolor','k'); +% marker2 = line('xdata',v(1),'ydata',v(2),'zdata',v(3),'marker','o',... +% 'erasemode','xor','markerfacecolor','k'); +% marker2 = line('erasemode','xor','xdata',face(1,:),'ydata',face(2,:),... +% 'zdata',face(3,:),'linewidth',10); +% disp(sprintf('\nYou clicked at\nX: %.2f\nY: %.2f\nZ: %.2f',p(1),p(2),p(3)')) +% disp(sprintf('\nThe nearest vertex is\nX: %.2f\nY: %.2f\nZ: %.2f',v(1),v(2),v(3)')) +% +% Version 1.2 2-15-02 +% Copyright Joe Conti 2002 +% Send comments to jconti@mathworks.com +% +% See also GINPUT, GCO. + +% Output variables +pout = []; +vout = []; +viout = []; +facevout = []; +faceiout = []; + +% other variables +ERRMSG = 'Input argument must be a valid graphics handle'; +isline = logical(0); +isperspective = logical(0); + +% Parse input arguments +if nargin<1 + obj = gco; +end + +if isempty(obj) | ~ishandle(obj) | length(obj)~=1 + error(ERRMSG); +end + +% if obj is a figure +if strcmp(get(obj,'type'),'figure') + fig = obj; + ax = get(fig,'currentobject'); + currobj = get(fig,'currentobject'); + + % bail out if not a child of the axes + if ~strcmp(get(get(currobj,'parent'),'type'),'axes') + return; + end + +% if obj is an axes +elseif strcmp(get(obj,'type'),'axes') + ax = obj; + fig = get(ax,'parent'); + currobj = get(fig,'currentobject'); + currax = get(currobj,'parent'); + + % Bail out if current object is under an unspecified axes + if ~isequal(ax,currax) + return; + end + +% if obj is child of axes +elseif strcmp(get(get(obj,'parent'),'type'),'axes') + currobj = obj; + ax = get(obj,'parent'); + fig = get(ax,'parent'); + +% Bail out +else + return +end + +axchild = currobj; +obj_type = get(axchild,'type'); +is_perspective = strcmp(get(ax,'projection'),'perspective'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Get projection transformation %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% syntax not supported in old versions of MATLAB +[a b] = view(ax); +xform = viewmtx(a,b); +if is_perspective + warning(sprintf('%s does not support perspective axes projection.',mfilename)); + d = norm(camtarget(ax)-campos(ax)) + P = [1 0 0 0; + 0 1 0 0; + 0 0 1 0; + 0 0 -1/d 1]; + xform = P*xform; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Get vertex, face, and current point data %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +cp = get(ax,'currentpoint')'; + +% If surface object +if strcmp(obj_type,'surface') + % Get surface face and vertices + fv = surf2patch(axchild); + vert = fv.vertices; + faces = fv.faces; + +% If patch object +elseif strcmp(obj_type,'patch') + vert = get(axchild,'vertices'); + faces = get(axchild,'faces'); + vzb = get(axchild,'FaceVertexAlphaData'); + vert(vzb==0)=NaN; + if isequal('interp', get(axchild,'FaceVertexAlphaData')) + [ignore,tmp]=ismember(faces(:),vzb); + faces(tmp)=NaN; + clear tmp; + end +% If line object +elseif strcmp(obj_type,'line') + xdata = get(axchild,'xdata'); + ydata = get(axchild,'ydata'); + zdata = get(axchild,'zdata'); + vert = [xdata', ydata',zdata']; + faces = []; + isline = logical(1); + +% Ignore all other objects +else + return; +end + +% Add z if empty +if size(vert,2)==2 + vert(:,3) = zeros(size(vert(:,2))); + if isline + zdata = vert(:,3); + end +end + +% NaN and Inf check +nan_inf_test1 = isnan(faces) | isinf(faces); +nan_inf_test2 = isnan(vert) | isinf(vert); +if any(nan_inf_test1(:)) | any(nan_inf_test2(:)) + warning(sprintf('%s does not support NaNs or Infs in face/vertex data.',mfilename)); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Normalize for data aspect ratio %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +dar = get(ax,'DataAspectRatio'); + +ncp(1,:) = cp(1,:)./dar(1); +ncp(2,:) = cp(2,:)./dar(2); +ncp(3,:) = cp(3,:)./dar(3); +ncp(4,:) = ones(size(ncp(3,:))); + +nvert(:,1) = vert(:,1)./dar(1); +nvert(:,2) = vert(:,2)./dar(2); +nvert(:,3) = vert(:,3)./dar(3); +nvert(:,4) = ones(size(nvert(:,3))); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Transform data to view space %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +xvert = xform*nvert'; +xcp = xform*ncp; + +if is_perspective % normalize 4th dimension + xcp(1,:) = xcp(1,:)./xcp(4,:); + xcp(2,:) = xcp(2,:)./xcp(4,:); + xcp(3,:) = xcp(3,:)./xcp(4,:); + xcp(4,:) = xcp(4,:)./xcp(4,:); + + xvert(1,:) = xvert(1,:)./xvert(4,:); + xvert(2,:) = xvert(2,:)./xvert(4,:); + xvert(3,:) = xvert(3,:)./xvert(4,:); + xvert(4,:) = xvert(4,:)./xvert(4,:); +end + +% Ignore 3rd & 4th dimensions for crossing test +xvert(4,:) = []; +xvert(3,:) = []; +xcp(4,:) = []; +xcp(3,:) = []; + +% For debugging +% if 0 +% ax1 = getappdata(ax,'testselect3d'); +% if isempty(ax1) | ~ishandle(ax1) +% fig = figure; +% ax1 = axes; +% axis(ax1,'equal'); +% setappdata(ax,'testselect3d',ax1); +% end +% cla(ax1); +% patch('parent',ax1,'faces',faces,'vertices',xvert','facecolor','none','edgecolor','k'); +% line('parent',ax1,'xdata',xcp(1,2),'ydata',xcp(2,2),'zdata',0,'marker','o','markerfacecolor','r','erasemode','xor'); +% end + +% Translate vertices so that the selection point is at the origin. +xvert(1,:) = xvert(1,:) - xcp(1,2); +xvert(2,:) = xvert(2,:) - xcp(2,2); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% simple algorithm (almost naive algorithm!) for line objects %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if isline + + % Ignoring line width and marker attributes, find closest + % vertex in 2-D view space. + d = xvert(1,:).*xvert(1,:) + xvert(2,:).*xvert(2,:); + [val i] = min(d); + i = i(1); % enforce only one output + + % Assign output + vout = [ xdata(i) ydata(i) zdata(i)]; + viout = i; + + return % Bail out early +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Perform 2-D crossing test (Jordan Curve Theorem) %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% Find all vertices that have y components less than zero +vert_with_negative_y = zeros(size(faces)); +face_y_vert = xvert(2,faces); +ind_vert_with_negative_y = find(face_y_vert<0); +vert_with_negative_y(ind_vert_with_negative_y) = logical(1); + +% Find all the line segments that span the x axis +is_line_segment_spanning_x = abs(diff([vert_with_negative_y, vert_with_negative_y(:,1)],1,2)); + +% Find all the faces that have line segments that span the x axis +ind_is_face_spanning_x = find(any(is_line_segment_spanning_x,2)); + +% Ignore data that doesn't span the x axis +candidate_faces = faces(ind_is_face_spanning_x,:); +vert_with_negative_y = vert_with_negative_y(ind_is_face_spanning_x,:); +is_line_segment_spanning_x = is_line_segment_spanning_x(ind_is_face_spanning_x,:); + +% Create line segment arrays +pt1 = candidate_faces; +pt2 = [candidate_faces(:,2:end), candidate_faces(:,1)]; + +% Point 1 +x1 = reshape(xvert(1,pt1),size(pt1)); +y1 = reshape(xvert(2,pt1),size(pt1)); + +% Point 2 +x2 = reshape(xvert(1,pt2),size(pt2)); +y2 = reshape(xvert(2,pt2),size(pt2)); + +% Cross product of vector to origin with line segment +cross_product_test = -x1.*(y2-y1) > -y1.*(x2-x1); + +% Find all line segments that cross the positive x axis +crossing_test = (cross_product_test==vert_with_negative_y) & is_line_segment_spanning_x; + +% If the number of line segments is odd, then we intersected the polygon +s = sum(crossing_test,2); +s = mod(s,2); +ind_intersection_test = find(s~=0); + +% Bail out early if no faces were hit +if isempty(ind_intersection_test) + return; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Plane/ray intersection test %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Perform plane/ray intersection with the faces that passed +% the polygon intersection tests. Grab the only the first +% three vertices since that is all we need to define a plane). +% assuming planar polygons. +candidate_faces = candidate_faces(ind_intersection_test,1:3); +candidate_faces = reshape(candidate_faces',1,prod(size(candidate_faces))); +vert = vert'; +candidate_facev = vert(:,candidate_faces); +candidate_facev = reshape(candidate_facev,3,3,length(ind_intersection_test)); + +% Get three contiguous vertices along polygon +v1 = squeeze(candidate_facev(:,1,:)); +v2 = squeeze(candidate_facev(:,2,:)); +v3 = squeeze(candidate_facev(:,3,:)); + +% Get normal to face plane +vec1 = [v2-v1]; +vec2 = [v3-v2]; +crs = cross(vec1,vec2); +mag = sqrt(sum(crs.*crs)); +nplane(1,:) = crs(1,:)./mag; +nplane(2,:) = crs(2,:)./mag; +nplane(3,:) = crs(3,:)./mag; + +% Compute intersection between plane and ray +cp1 = cp(:,1); +cp2 = cp(:,2); +d = cp2-cp1; +dp = dot(-nplane,v1); + +%A = dot(nplane,d); +A(1,:) = nplane(1,:).*d(1); +A(2,:) = nplane(2,:).*d(2); +A(3,:) = nplane(3,:).*d(3); +A = sum(A,1); + +%B = dot(nplane,pt1) +B(1,:) = nplane(1,:).*cp1(1); +B(2,:) = nplane(2,:).*cp1(2); +B(3,:) = nplane(3,:).*cp1(3); +B = sum(B,1); + +% Distance to intersection point +t = (-dp-B)./A; + +% Find "best" distance (smallest) +[tbest ind_best] = min(t); + +% Determine intersection point +pout = cp1 + tbest .* d; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%% Assign additional output variables %% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if nargout>1 + + % Get face index and vertices + faceiout = ind_is_face_spanning_x(ind_intersection_test(ind_best)); + facevout = vert(:,faces(faceiout,:)); + + % Determine index of closest face vertex intersected + facexv = xvert(:,faces(faceiout,:)); + dist = sqrt(facexv(1,:).*facexv(1,:) + facexv(2,:).*facexv(2,:)); + min_dist = min(dist); + min_index = find(dist==min_dist); + + % Get closest vertex index and vertex + viout = faces(faceiout,min_index); + vout = vert(:,viout); +end diff --git a/selectscout.m b/selectscout.m new file mode 100644 index 0000000..579cfb7 --- /dev/null +++ b/selectscout.m @@ -0,0 +1,17 @@ +function [vi,p,fi,v,f]=selectscout(ctx) +% selectscout - Select scout on the cortical surface +% [vi,p,fi,v,f]=selectscout(ctx) selects a vertex on the patch surface ctx +% If ctx not given, find the tessellation. +% If ctx=[] the surface used is the one one which the user click. +if nargin<1 + ctx=findTessellationHandles; +end +if ~isempty(ctx) + axes(get(ctx, 'Parent')); +end + +ginput(1); +if isempty(ctx) + ctx=gco; +end +[p v vi f fi]=select3d(ctx); diff --git a/setAllText.m b/setAllText.m new file mode 100644 index 0000000..999d4bf --- /dev/null +++ b/setAllText.m @@ -0,0 +1,29 @@ +function ht = setAll(p,v,h) +%SETALLTEXT - Set properties of all text objects (in a given figure/plot/...) +% ht = setAllText(Property,Value,[Handles]) +% ht are the handles to text object found + +% Author: KND +% Created: Sep 2005 +if nargin<3 + h=gca; +end + + +ht=findobj(h, 'type', 'text'); +set(ht, p, v) +ha=findobj(h,'type', 'axes') +if ~isempty(ha) + for i=1:length(ha) + if isfield(get(ha(i)), p) + set(ha(i),p,v) + else + warning(sprintf('No property %s for object Axes', p)) + end + for hah=get(ha(i),'Children')' + if isfield(get(hah), p) + %set(hah + end + end + end +end diff --git a/setall.m b/setall.m new file mode 100644 index 0000000..f80e83e --- /dev/null +++ b/setall.m @@ -0,0 +1,26 @@ +function varargout = setAll(p,v,h) +%SETALL - Set a given property for all objects that have it +% ht = setall(Property,Value,[ParentHandles]) +% ht are the modified handles + +% Author: KND +% Created: Sep 2005 +if nargin<3 + h=gca; +end +if ~ishandle(h) + return +end +h=findall(h); +ht=[]; +for i=1:length(h) + try%if isfield(get(h(i)), p) + set(h(i),p,v); + ht=[ht h(i)]; + end +end +if nargout + varargout={ht}; +end +return + diff --git a/setdiff.m b/setdiff.m new file mode 100644 index 0000000..1ac5ec8 --- /dev/null +++ b/setdiff.m @@ -0,0 +1,199 @@ +function [c,ia] = setdiff(a,b,flag) +%SETDIFF Set difference. +% SETDIFF(A,B) when A and B are vectors returns the values +% in A that are not in B. The result will be sorted. A and B +% can be cell arrays of strings. +% +% SETDIFF(A,B,'rows') when A are B are matrices with the same +% number of columns returns the rows from A that are not in B. +% +% [C,I] = SETDIFF(...) also returns an index vector I such that +% C = A(I) (or C = A(I,:)). +% +% See also UNIQUE, UNION, INTERSECT, SETXOR, ISMEMBER. + +% Copyright 1984-2003 The MathWorks, Inc. +% $Revision: 1.22.4.3 $ $Date: 2004/12/06 16:35:41 $ + +% Cell array implementation in @cell/setdiff.m + +nIn = nargin; + +if nIn < 2 + error('MATLAB:SETDIFF:NotEnoughInputs', 'Not enough input arguments.'); +elseif nIn > 3 + error('MATLAB:SETDIFF:TooManyInputs', 'Too many input arguments.'); +end + +if nIn == 2 + flag = []; +end + +isrows = strcmpi(flag,'rows'); + +rowsA = size(a,1); +colsA = size(a,2); +rowsB = size(b,1); +colsB = size(b,2); + +rowvec = ~((rowsA > 1 && colsB <= 1) || (rowsB > 1 && colsA <= 1) || isrows); + +nOut = nargout; + +if isempty(flag) + + numelA = length(a); + numelB = length(b); + + if numel(a)~=numelA || numel(b)~=numelB + error('MATLAB:SETDIFF:AandBvectorsOrRowsFlag', ... + 'A and B must be vectors or ''rows'' must be specified.'); + end + + % Handle empty arrays. + + if (numelA == 0) + % Predefine outputs to be of the correct type. + c = a([]); + ia = []; + % Ambiguous if no way to determine whether to return a row or column. + ambiguous = (rowsA==0 && colsA==0) && ... + ((rowsB==0 && colsB==0) || numelB == 1); + if ~ambiguous + c = reshape(c,0,1); + ia = reshape(ia,0,1); + end + elseif (numelB == 0) + % If B is empty, invoke UNIQUE to remove duplicates from A. + if nOut <= 1 + c = unique(a); + else + [c,ia] = unique(a); + end + return + + % Handle scalar: one element. Scalar A done only. + % Scalar B handled within ISMEMBER and general implementation. + + elseif (numelA == 1) + if ~ismember(a,b,flag) + c = a; + ia = 1; + else + c = []; + ia = []; + end + return + + % General handling. + + else + + % Convert to columns. + a = a(:); + b = b(:); + + % Convert to double arrays, which sort faster than other types. + + whichclass = class(a); + isdouble = strcmp(whichclass,'double'); + + if ~isdouble + a = double(a); + end + + if ~strcmp(class(b),'double') + b = double(b); + end + + % Call ISMEMBER to determine list of non-matching elements of A. + tf = ~(ismember(a,b)); + c = a(tf); + + % Call UNIQUE to remove duplicates from list of non-matches. + if nargout <= 1 + c = unique(c); + else + [c,ndx] = unique(c); + + % Find indices by using TF and NDX. + where = find(tf); + ia = where(ndx); + end + + % Re-convert to correct output data type using FEVAL. + if ~isdouble + c = feval(whichclass,c); + end + end + + % If row vector, return as row vector. + if rowvec + c = c.'; + if nOut > 1 + ia = ia.'; + end + end + +else % 'rows' case + if ~isrows + error('MATLAB:SETDIFF:UnknownFlag', 'Unknown flag.'); + end + + % Automatically pad strings with spaces + if ischar(a) && ischar(b) + if colsA > colsB + b = [b repmat(' ',rowsB,colsA-colsB)]; + elseif colsA < colsB + a = [a repmat(' ',rowsA,colsB-colsA)]; + colsA = colsB; + end + elseif colsA ~= colsB + error('MATLAB:SETDIFF:AandBColnumAgree',... + 'A and B must have the same number of columns.'); + end + + % Handle empty arrays + if rowsA == 0 + c = zeros(rowsA,colsA); + ia = []; + elseif colsA == 0 && rowsA > 0 + c = zeros(1,0); + ia = rowsA; + % General handling + else + % Remove duplicates from A; get indices only if needed + if nOut > 1 + [a,ia] = unique(a,flag); + else + a = unique(a,flag); + end + + % Create sorted list of unique A and B; want non-matching entries + [c,ndx] = sortrows([a;b]); + [rowsC,colsC] = size(c); + if rowsC > 1 && colsC ~= 0 + % d indicates the location of non-matching entries + d = c(1:rowsC-1,:) ~= c(2:rowsC,:); + else + d = zeros(rowsC-1,0); + end + d = any(d,2); + d(rowsC,1) = 1; % Final entry always included. + + % d = 1 now for any unmatched entry of A or of B. + n = size(a,1); + d = d & ndx <= n; % Now find only the ones in A. + + c = c(d,:); + + if nOut > 1 + ia = ia(ndx(d)); + end + end +end + +% Automatically deblank strings +if ischar(a) + c = deblank(c); +end diff --git a/setdiff2.m b/setdiff2.m new file mode 100644 index 0000000..1ac5ec8 --- /dev/null +++ b/setdiff2.m @@ -0,0 +1,199 @@ +function [c,ia] = setdiff(a,b,flag) +%SETDIFF Set difference. +% SETDIFF(A,B) when A and B are vectors returns the values +% in A that are not in B. The result will be sorted. A and B +% can be cell arrays of strings. +% +% SETDIFF(A,B,'rows') when A are B are matrices with the same +% number of columns returns the rows from A that are not in B. +% +% [C,I] = SETDIFF(...) also returns an index vector I such that +% C = A(I) (or C = A(I,:)). +% +% See also UNIQUE, UNION, INTERSECT, SETXOR, ISMEMBER. + +% Copyright 1984-2003 The MathWorks, Inc. +% $Revision: 1.22.4.3 $ $Date: 2004/12/06 16:35:41 $ + +% Cell array implementation in @cell/setdiff.m + +nIn = nargin; + +if nIn < 2 + error('MATLAB:SETDIFF:NotEnoughInputs', 'Not enough input arguments.'); +elseif nIn > 3 + error('MATLAB:SETDIFF:TooManyInputs', 'Too many input arguments.'); +end + +if nIn == 2 + flag = []; +end + +isrows = strcmpi(flag,'rows'); + +rowsA = size(a,1); +colsA = size(a,2); +rowsB = size(b,1); +colsB = size(b,2); + +rowvec = ~((rowsA > 1 && colsB <= 1) || (rowsB > 1 && colsA <= 1) || isrows); + +nOut = nargout; + +if isempty(flag) + + numelA = length(a); + numelB = length(b); + + if numel(a)~=numelA || numel(b)~=numelB + error('MATLAB:SETDIFF:AandBvectorsOrRowsFlag', ... + 'A and B must be vectors or ''rows'' must be specified.'); + end + + % Handle empty arrays. + + if (numelA == 0) + % Predefine outputs to be of the correct type. + c = a([]); + ia = []; + % Ambiguous if no way to determine whether to return a row or column. + ambiguous = (rowsA==0 && colsA==0) && ... + ((rowsB==0 && colsB==0) || numelB == 1); + if ~ambiguous + c = reshape(c,0,1); + ia = reshape(ia,0,1); + end + elseif (numelB == 0) + % If B is empty, invoke UNIQUE to remove duplicates from A. + if nOut <= 1 + c = unique(a); + else + [c,ia] = unique(a); + end + return + + % Handle scalar: one element. Scalar A done only. + % Scalar B handled within ISMEMBER and general implementation. + + elseif (numelA == 1) + if ~ismember(a,b,flag) + c = a; + ia = 1; + else + c = []; + ia = []; + end + return + + % General handling. + + else + + % Convert to columns. + a = a(:); + b = b(:); + + % Convert to double arrays, which sort faster than other types. + + whichclass = class(a); + isdouble = strcmp(whichclass,'double'); + + if ~isdouble + a = double(a); + end + + if ~strcmp(class(b),'double') + b = double(b); + end + + % Call ISMEMBER to determine list of non-matching elements of A. + tf = ~(ismember(a,b)); + c = a(tf); + + % Call UNIQUE to remove duplicates from list of non-matches. + if nargout <= 1 + c = unique(c); + else + [c,ndx] = unique(c); + + % Find indices by using TF and NDX. + where = find(tf); + ia = where(ndx); + end + + % Re-convert to correct output data type using FEVAL. + if ~isdouble + c = feval(whichclass,c); + end + end + + % If row vector, return as row vector. + if rowvec + c = c.'; + if nOut > 1 + ia = ia.'; + end + end + +else % 'rows' case + if ~isrows + error('MATLAB:SETDIFF:UnknownFlag', 'Unknown flag.'); + end + + % Automatically pad strings with spaces + if ischar(a) && ischar(b) + if colsA > colsB + b = [b repmat(' ',rowsB,colsA-colsB)]; + elseif colsA < colsB + a = [a repmat(' ',rowsA,colsB-colsA)]; + colsA = colsB; + end + elseif colsA ~= colsB + error('MATLAB:SETDIFF:AandBColnumAgree',... + 'A and B must have the same number of columns.'); + end + + % Handle empty arrays + if rowsA == 0 + c = zeros(rowsA,colsA); + ia = []; + elseif colsA == 0 && rowsA > 0 + c = zeros(1,0); + ia = rowsA; + % General handling + else + % Remove duplicates from A; get indices only if needed + if nOut > 1 + [a,ia] = unique(a,flag); + else + a = unique(a,flag); + end + + % Create sorted list of unique A and B; want non-matching entries + [c,ndx] = sortrows([a;b]); + [rowsC,colsC] = size(c); + if rowsC > 1 && colsC ~= 0 + % d indicates the location of non-matching entries + d = c(1:rowsC-1,:) ~= c(2:rowsC,:); + else + d = zeros(rowsC-1,0); + end + d = any(d,2); + d(rowsC,1) = 1; % Final entry always included. + + % d = 1 now for any unmatched entry of A or of B. + n = size(a,1); + d = d & ndx <= n; % Now find only the ones in A. + + c = c(d,:); + + if nOut > 1 + ia = ia(ndx(d)); + end + end +end + +% Automatically deblank strings +if ischar(a) + c = deblank(c); +end diff --git a/setfield2.m b/setfield2.m new file mode 100644 index 0000000..0c62d64 --- /dev/null +++ b/setfield2.m @@ -0,0 +1,14 @@ +function B = setfield2(A,F,V) +%SETFIELD2 - Set structure field contents (even for arrays) +% S = SETFIELD(S,F,V) sets the contents of the specified +% field(s) F to the value(s) V. Structure S, fields F and values V may +% be array of the same size or expandable scalar. +% +% S = SETFIELD(S,{i,j},'field',{k},V) is equivalent to the syntax +% S(i,j).field(k) = V; +% +% +% ----------------------------- Script History --------------------------------- +% KND 2011-06-08 Creation +% +% ----------------------------- Script History --------------------------------- diff --git a/setfocus.m b/setfocus.m new file mode 100644 index 0000000..daafa2c --- /dev/null +++ b/setfocus.m @@ -0,0 +1,75 @@ +function setfocus(h); +% +% +% sample of a simple apporch to the set a focus to a uicontrol: +% setfocus forces a mouseclick in the upper left corner of the +% object with the handle h. +% + +% $Revision: 1.3 $ +% $Date: 2002/06/27 12:41:01 $ +% $Author: weber $ + +if nargin<1 + error('No input handle defined!') +end + +if ~ishandle(h) + error('Input must be a handle!'); +end + + +callback=''; + +% When the object is a 'uicontrol' the function of the object would be +% executed. Therefore I have to set it to '', and set it back after the mouseclick + +if strcmp(get(h, 'Type'), 'uicontrol') + callback=get(h, 'Callback'); + set(h, 'Callback', ''); + drawnow; % Update the figure data +end + + +figh=get(h, 'Parent'); +unit_root=get(0, 'Unit'); +unit_fig=get(figh, 'Unit'); +unit_obj=get(h, 'Unit'); +set(0, 'Units', 'pixels'); +set(figh, 'Units', 'pixels'); +set(h, 'Units', 'pixels'); +drawnow; + +% get the current mouse pointer coordinates +mouse_coord=get(0, 'PointerLocation'); +fig_pos=get(figh, 'Position'); +obj_pos=get(h, 'Position'); + +act_pos=fig_pos+obj_pos; +act_pos=act_pos(1:2); +act_pos(1)=act_pos(1)+3; +act_pos(2)=act_pos(2)+obj_pos(4)-7; + +% set the mouse pointer to the upper left corner of the object +% (I did this for listboxes, to highlight the first entry) + +set(0, 'PointerLocation', act_pos); + +mouseclick; %simulate the mouseclick + + +%----------------------------------------------------------------------------- +% set all parameters that were changed back to the starting values + +set(0, 'PointerLocation', mouse_coord); + +if strcmp(get(h, 'Type'), 'uicontrol') + drawnow; % When there is no 'drawnow', the original Callback- String + % will be executed, even the Callback String is set to ''; + set(h, 'Callback', callback); +end + +set(0, 'Unit', unit_root); +set(figh, 'Unit', unit_fig); +set(h, 'Unit', unit_obj); +drawnow; diff --git a/setmycolormap.m b/setmycolormap.m new file mode 100644 index 0000000..5a15423 --- /dev/null +++ b/setmycolormap.m @@ -0,0 +1,19 @@ +function [varargout]=setmycolormap(seuil,varargin) + +m=mycolormap(seuil, varargin{:}); +colormap(m); +material dull; +%h=light; +%set(h, 'position', [0 -1 0]) +%set(h, 'color', [0.5 .5 0.5]) +%h=light; +%set(h, 'position', [0 1 0]) +%set(h, 'color', [0.5 .5 0.5]) +% caxis([-mean(abs(caxis)) mean(abs(caxis))]) + +colorbar +set(gcf, 'Color', [1 1 1 ]) +rotate3d on +if nargout > 0 +varargout=m; +end diff --git a/sf_estrrep.m b/sf_estrrep.m new file mode 100644 index 0000000..77d332e --- /dev/null +++ b/sf_estrrep.m @@ -0,0 +1,9 @@ +function str = sf_estrrep(str,srstr) +%sf_estrrep - Replaces multiples strings +% str = sf_estrrep(str,srstr) replaces srstr multiple times in str. +% srstr is a n-by-2 cell array of strings +% +% (from SPM2 toolbox) +for i = 1:size(srstr,1) + str = strrep(str,srstr{i,1},srstr{i,2}); +end \ No newline at end of file diff --git a/sfieldnames.m b/sfieldnames.m new file mode 100644 index 0000000..5fbeb04 --- /dev/null +++ b/sfieldnames.m @@ -0,0 +1,22 @@ +function [f]=sfieldnames(s) +%SFIELDNAMES Get structure field names. +% NAMES = SFIELDNAMES(S) returns a cell array of strings containing +% the structure field and subfields names (under the form: +% 'field.subfield') associated with the structure s +% +% See also SISFIELD, SSETFIELD + +f=fieldnames(s); +f=f(:); +i=0; +while iyahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-12 Also process struct arrays +% +% ----------------------------- Script History --------------------------------- + +% Check for sufficient inputs +if (isempty(varargin)) + error('MATLAB:sgetfield:InsufficientInputs',... + 'Not enough input arguments.') +end + +sz = size(s) + +% The most common case +strField = varargin{1}; +if (length(varargin)==1 && ischar(strField)) + [strField, subField]=strtok(strField, '.'); + f = [s.(deblank(strField))]; % deblank field name + if numel(f)==numel(s) + f=reshape(f,size(s)); + end + if isempty(subField) + return + end + % recursive call to process subfields + f = sgetfield(f,subField); + if numel(f)==numel(s) + f=reshape(f,size(s)); + else + warning('MATLAB:sgetfield:EmptySubields','Incomplete array of (sub)fields, some are empty') + end +end + +return + + +f = s; +for i = 1:length(varargin) + index = varargin{i}; + if (isa(index, 'cell')) + f = f(index{:}); + elseif ischar(index) + + % Return the first element, if a comma separated list is generated + try + f = f.(deblank(index)); % deblank field name + catch + tmp = cell(1,length(f)); + [tmp{:}] = deal(f.(deblank(index))); + f = tmp{1}; + end + else + error('MATLAB:getfield:InvalidType', 'Inputs must be either cell arrays or strings.'); + end +end + diff --git a/showpercent.m b/showpercent.m new file mode 100644 index 0000000..06ebb7c --- /dev/null +++ b/showpercent.m @@ -0,0 +1,138 @@ +function [keep,c,clim]=showpercent(p,hpatch,basecolor,cmap,asym) +%showpercent - Set the colormap to display some percentage of active sources +% +%[keep,c,clim]=showpercent(p,hpatch,basecolor,cmap,asym) +% Set the colormap to display some percentage of the most active sources +% of the cortical surface (according to FaceVertexCData). +%INPUTS: +% p: the percentage to keep (if p<0, the actual number, i.e. -p==keep) +%OPTIONAL INPUTS: +% hpatch: handle to the patch surface. If missing, find it... If array, +% If this is not a handle but an array of numbers, showpercent +% compute the colormap that would display p% of those values. +% basecolor: color to be used for unactive sources [.6 .6 .6] +% cmap: colormap to use, if missing use the colormap of the figure +% asym: 0:symmetical colormap (to display +/- values), +% 1: positive; -1:negative values only +%OUTPUT: +% keep: number of sources; +% c: the new colormap +% clim: the new limits for the colormap +% +% If FaceVertexCData is >=0 the CLim properties are changed to display only +% the p% most active sources and the lowest color is set to the basecolor. +% Otherwise (some FVCData<0), the ColorMap is symmetrized, with basecolor +% inserted in the middle to "mute" low-amplitude sources. + +if p==0 + return +end +if nargin<2 + hpatch=findTessellationHandles; +end +if nargin<3 || isempty(basecolor) + basecolor=[.6 .6 .6]; +end +if nargin<4 || isempty(cmap) + cmap=get(get(get(hpatch, 'Parent'), 'Parent'), 'Colormap'); + cmap=cmap(~all((cmap==repmat(basecolor, size(cmap,1), 1))'),:); +end +if nargin<5 + asym=NaN; +end +if ishandle(hpatch) +cdata=get(hpatch, 'FaceVertexCData'); +else + cdata=hpatch; +end +cdata=cdata(:); +if p>0 + % Number of vertices to keep so that it make only X% + keep=round(p/100*size(cdata,1)); +else + keep=-p; +end +if p==100 | keep == length(cdata) + top=max(abs(cdata)); + bot=-top; + c=cmap; +elseif (isnan(asym) && any(cdata>0) & any(cdata<0)) || ~asym + f=-sort(-abs(cdata)); + bot=-f(1); + top=f(1); + noff=size(cmap,1)/2*f(keep)/(f(1) - f(keep)); + c=[cmap(1:end/2,:) ; repmat(basecolor, ceil(2*noff), 1) ; cmap(end/2+1:end,:)]; + %bot=cdata(f(keep)) + %neg=find(cdata<0); + %pos=find(cdata>0); + %nmap=length(colormap); + %c=[fliplr(flipud(cmap)); repmat(basecolor,nmap*100/p,1) ; cmap]; + % top=-bot; + % if top < 0 + % top=-top;bot=-bot; + % end +elseif (isnan(asym) & all(cdata>=0)) || asym>0 + f=-sort(-(cdata)); + top=f(1); + % Alt. version: Colormap show also lower bound + % bot=0; + % noff=size(cmap,1)*f(keep)/(f(1) - f(keep)); + % c=[repmat(basecolor, ceil(2*noff), 1) ; cmap(1:end,:)]; + bot = f(keep+1); + c=([basecolor; cmap]); +elseif (isnan(asym) & all(cdata<=0)) || asym<0 + f=-sort(-(cdata)); + top=-f(keep+1); + % Alt. version: Colormap show also lower bound + % bot=0; + % noff=size(cmap,1)*f(keep)/(f(1) - f(keep)); + % c=[repmat(basecolor, ceil(2*noff), 1) ; cmap(1:end,:)]; + bot = -f(1); + c=([cmap;basecolor]); + +end +if ishandle(hpatch) + set(get(hpatch, 'Parent'), 'CLim', [bot top]); + colormap(get(hpatch, 'Parent'),c); +end +return + + +% ==================================================== + + +% Previous version +cmap=hot(100).*(1-flipud(cumsum(ones(100,3))/100)*.6)+ ... + (flipud(cumsum(ones(100,3))/100)*.6) + + + +if any(cdata>0) & any(cdata<0) + bot=cdata(f(keep)) +else + bot=cdata(f(keep)); + top=cdata(f(1)); + if all(cdata<0) + % All negative sign + bot=-bot; + top=-top; + end + set(gca, 'CLim', [bot top]); + if nargin < 4 + [ign, ci]=unique(colormap, 'rows'); + c=colormap; + c=c(ci,:); + if size(c,1) < size(colormap,1) + disp('Changing previous ColorMap') + c=([basecolor; c(2:end,:)]); + else + disp('Adding gray to previous ColorMap') + c=([basecolor; c]); + end + else + c=([basecolor; cmap]); + end + +end +colormap(c); +colorbar diff --git a/sigproc/__zp2ssg2__.m b/sigproc/__zp2ssg2__.m new file mode 100644 index 0000000..39132eb --- /dev/null +++ b/sigproc/__zp2ssg2__.m @@ -0,0 +1,68 @@ +## Copyright (C) 1996, 1998 Auburn University. All rights reserved. +## +## This file is part of Octave. +## +## Octave is free software; you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by the +## Free Software Foundation; either version 2, or (at your option) any +## later version. +## +## Octave is distributed in the hope that it will be useful, but WITHOUT +## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or +## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License +## for more details. +## +## You should have received a copy of the GNU General Public License +## along with Octave; see the file COPYING. If not, write to the Free +## Software Foundation, 59 Temple Place, Suite 330, Boston, MA 02111 USA. + +## -*- texinfo -*- +## @deftypefn {Function File} {[@var{poly}, @var{rvals}] =} __zp2ssg2__ (@var{rvals}) +## Used internally in @code{zp2ss} +## Extract 2 values from @var{rvals} (if possible) and construct +## a polynomial with those roots. +## @end deftypefn + +## Author: A. S. Hodel +## Created: August 1996 + +function [poly, rvals] = __zp2ssg2__ (rvals) + + ## locate imaginary roots (if any) + cidx = find(imag(rvals)); + + if(!isempty(cidx)) + ## select first complex root, omit from cidx + r1i = cidx(1); r1 = rvals(r1i); cidx = complement(r1i,cidx); + + ## locate conjugate root (must be in cidx list, just in case there's + ## roundoff) + err = abs(rvals(cidx) - r1'); + minerr = min(err); + c2i = min(find(err == minerr)); + r2i = cidx(c2i); + r2 = rvals(r2i); + cidx = complement(r2i,cidx); + + ## don't check for divide by zero, since 0 is not complex. + if(abs(r2 - r1')/abs(r1) > 1e-12) + error(sprintf("r1=(%f,%f); r2=(%f,%f), not conjugates.", ... + real(r1),imag(r1),real(r2),imag(r2))); + endif + + ## complex conjugate pair + poly = [1, -2*real(r1), real(r1)^2+imag(r1)^2]; + else + ## select two roots (they're all real) + r1 = rvals(1); + r2 = rvals(2); + poly = [1, -(r1+r2), (r1*r2)]; + r1i = 1; r2i = 2; + endif + + ## remove roots used + idx = complement([r1i, r2i],1:length(rvals)); + rvals = rvals(idx); + +endfunction + diff --git a/sigproc/bilinear.m b/sigproc/bilinear.m new file mode 100644 index 0000000..adf2cc0 --- /dev/null +++ b/sigproc/bilinear.m @@ -0,0 +1,103 @@ +% Copyright (C) 1999 Paul Kienzle +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% usage: [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T) +% [Zb, Za] = bilinear(Sb, Sa, T) +% +% Transform a s-plane filter specification into a z-plane +% specification. Filters can be specified in either zero-pole-gain or +% transfer function form. The input form does not have to match the +% output form. T is the sampling frequency represented in the z plane. +% +% Theory: Given a piecewise flat filter design, you can transform it +% from the s-plane to the z-plane while maintaining the band edges by +% means of the bilinear transform. This maps the left hand side of the +% s-plane into the interior of the unit circle. The mapping is highly +% non-linear, so you must design your filter with band edges in the +% s-plane positioned at 2/T tan(w*T/2) so that they will be positioned +% at w after the bilinear transform is complete. +% +% The following table summarizes the transformation: +% +% Transform Zero at x Pole at x +% ---------------- ------------------------- ------------------------ +% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT) +% 2 z-1 pole: -1 zero: -1 +% S -> - --- gain: (2-xT)/T gain: (2-xT)/T +% T z+1 +% ---------------- ------------------------- ------------------------ +% +% With tedious algebra, you can derive the above formulae yourself by +% substituting the transform for S into H(S)=S-x for a zero at x or +% H(S)=1/(S-x) for a pole at x, and converting the result into the +% form: +% +% H(Z)=g prod(Z-Xi)/prod(Z-Xj) +% +% Please note that a pole and a zero at the same place exactly cancel. +% This is significant since the bilinear transform creates numerous +% extra poles and zeros, most of which cancel. Those which do not +% cancel have a 'fill-in' effect, extending the shorter of the sets to +% have the same number of as the longer of the sets of poles and zeros +% (or at least split the difference in the case of the band pass +% filter). There may be other opportunistic cancellations but I will +% not check for them. +% +% Also note that any pole on the unit circle or beyond will result in +% an unstable filter. Because of cancellation, this will only happen +% if the number of poles is smaller than the number of zeros. The +% analytic design methods all yield more poles than zeros, so this will +% not be a problem. +% +% References: +% +% Proakis & Manolakis (1992). Digital Signal Processing. New York: +% Macmillan Publishing Company. + +% Author: pkienzle@cs.indiana.edu + +function [Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T) + +if nargin==3 + T = Sg; + [Sz, Sp, Sg] = tf2zp(Sz, Sp); +elseif nargin ~= 4 + usage('[Zz, Zp, Zg]=bilinear(Sz,Sp,Sg,T) or [Zb, Za]=blinear(Sb,Sa,T)'); +end; + +p = length(Sp); +z = length(Sz); +if z > p || p==0 + error('bilinear: must have at least as many poles as zeros in s-plane'); +end + +% ---------------- ------------------------- ------------------------ +% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT) +% 2 z-1 pole: -1 zero: -1 +% S -> - --- gain: (2-xT)/T gain: (2-xT)/T +% T z+1 +% ---------------- ------------------------- ------------------------ +Zg = real(Sg * prod((2-Sz*T)/T) / prod((2-Sp*T)/T)); +Zp = (2+Sp*T)./(2-Sp*T); +if isempty(Sz) + Zz = -ones(size(Zp)); +else + Zz = [(2+Sz*T)./(2-Sz*T)]; + Zz = postpad(Zz, p, -1); +end + +if nargout==2, [Zz, Zp] = zp2tf(Zz, Zp, Zg); end +end diff --git a/sigproc/cheby1.m b/sigproc/cheby1.m new file mode 100644 index 0000000..3c7a4dc --- /dev/null +++ b/sigproc/cheby1.m @@ -0,0 +1,99 @@ +function [Zz, Zp, Zg] = cheby1(n, Rp, W, stype) +% Generate an Chebyshev type I filter with Rp dB of pass band ripple. +% +% [b, a] = cheby1(n, Rp, Wc) +% low pass filter with cutoff pi*Wc radians +% +% [b, a] = cheby1(n, Rp, Wc, 'high') +% high pass filter with cutoff pi*Wc radians +% +% [b, a] = cheby1(n, Rp, [Wl, Wh]) +% band pass filter with edges pi*Wl and pi*Wh radians +% +% [b, a] = cheby1(n, Rp, [Wl, Wh], 'stop') +% band reject filter with edges pi*Wl and pi*Wh radians +% +% [z, p, g] = cheby1(...) +% return filter as zero-pole-gain rather than coefficients of the +% numerator and denominator polynomials. +% +% References: +% +% Parks & Burrus (1987). Digital Filter Design. New York: +% John Wiley & Sons, Inc. + +% Author: pkienzle@cs.indiana.edu + +% Copyright (C) 1999 Paul Kienzle +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + + + +if (nargin>4 || nargin<3) || (nargout>3 || nargout<2) + disp('[b, a] or [z, p, g] = cheby1 (n, Rp, W, [, ''ftype''])'); +end + +stop = nargin==4; +if stop && ~(strcmp(stype, 'high') || strcmp(stype, 'stop')) + error ('cheby1: ftype must be ''high'' or ''stop'''); +end + +[r, c]=size(W); +if (~(length(W)<=2 && (r==1 || c==1))) + error('cheby1: frequency must be given as w0 or [w0, w1]'); +elseif (~all(W >= 0 & W <= 1)) + error('cheby1: critical frequencies must be in (0, 1)'); +elseif (~(length(W)==1 || length(W) == 2)) + error('cheby1: only one filter band allowed'); +elseif (length(W)==2 && ~(W(1) < W(2))) + error('cheby1: first band edge must be smaller than second'); +end + +if (Rp < 0) + error('cheby1: passband ripple must be positive decibels'); +end + +% Prewarp to the band edges to s plane +T = 2; % sampling frequency of 2 Hz +Ws = 2/T*tan(pi*W/T); + +% Generate splane poles and zeros for the chebyshev type 1 filter +C = 1; % default cutoff frequency +epsilon = sqrt(10^(Rp/10) - 1); +beta = ((sqrt(1+epsilon^2)+1)/epsilon)^(1/n); +r = C*(beta^2-1)/(2*beta); +R = C*(beta^2+1)/(2*beta); +Sz = []; +Sp = exp(1i*pi*(2*[1:n] + n - 1)/(2*n)); +Sp = r*real(Sp) + 1i*R*imag(Sp); + +% compensate for amplitude at s=0 +Sg = prod(-Sp); +% if n is even, the ripple starts low, but if n is odd the ripple +% starts high. We must adjust the s=0 amplitude to compensate. +if (rem(n,2)==0) + Sg = Sg/10^(Rp/20); +end + +% splane frequency transform +[Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, Ws, stop); + +% Use bilinear transform to convert poles to the z plane +[Zz, Zp, Zg] = bilinear(Sz, Sp, Sg, T); + +if nargout==2, [Zz, Zp] = zp2tf(Zz, Zp, Zg); end + +end \ No newline at end of file diff --git a/sigproc/complement.m b/sigproc/complement.m new file mode 100644 index 0000000..00945d5 --- /dev/null +++ b/sigproc/complement.m @@ -0,0 +1,61 @@ +% Copyright (C) 1996, 1997 John W. Eaton +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2, or (at your option) +% any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place - Suite 330, Boston, MA +% 02111-1307, USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {} complement (@var{x}, @var{y}) +% Return the elements of set @var{y} that are not in set @var{x}. For +% example, +% +% @example +% @group +% complement ([ 1, 2, 3 ], [ 2, 3, 5 ]) +% @result{} 5 +% @end group +% @end example +% @end deftypefn +% +% @seealso{create_set, union, and intersection} + +% Author: jwe + +function y = complement (a, b) + +if (nargin ~= 2) + usage ('complement(a,b)'); +end + +if (isempty (a)) + y = create_set(b); +elseif (isempty (b)) + y = []; +else + a = create_set (a); + b = create_set (b); + yindex = 1; + y = zeros (1, length (b)); + for index = 1:length (b) + if (all (a ~= b (index))) + y(yindex) = b(index); + yindex=yindex+1; + end + end + y = y(1:(yindex-1)); +end + +end diff --git a/sigproc/create_set.m b/sigproc/create_set.m new file mode 100644 index 0000000..0fbea09 --- /dev/null +++ b/sigproc/create_set.m @@ -0,0 +1,56 @@ +% Copyright (C) 1996, 1997 John W. Eaton +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2, or (at your option) +% any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place - Suite 330, Boston, MA +% 02111-1307, USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {} create_set (@var{x}) +% Return a row vector containing the unique values in @var{x}, sorted in +% ascending order. For example, +% +% @example +% @group +% create_set ([ 1, 2; 3, 4; 4, 2 ]) +% @result{} [ 1, 2, 3, 4 ] +% @end group +% @end example +% @end deftypefn +% +% @seealso{union, intersection, and complement} + +% Author: jwe + +function y = create_set(x) + +if (nargin ~= 1) + usage ('create_set(x)'); +end + +if (isempty(x)) + y = []; +else + nel = numel (x); + y = sort (reshape (x, 1, nel)); + els = find (y(1:nel-1) ~= y(2:nel)); + if (isempty (els)); + y = y(1); + else + y = y([1, els+1]); + end +end + +end diff --git a/sigproc/decimate.m b/sigproc/decimate.m new file mode 100644 index 0000000..b474753 --- /dev/null +++ b/sigproc/decimate.m @@ -0,0 +1,82 @@ +function y = decimate(x, q, n, ftype) +% usage: y = decimate(x, q [, n] [, ftype]) +% +% Downsample the signal x by a factor of q, using an order n filter +% of ftype 'fir' or 'iir'. By default, an order 8 Chebyshev type I +% filter is used or a 30 point FIR filter if ftype is 'fir'. Note +% that q must be an integer for this rate change method. +% +% Example +% % Generate a signal that starts away from zero, is slowly varying +% % at the start and quickly varying at the end, decimate and plot. +% % Since it starts away from zero, you will see the boundary +% % effects of the antialiasing filter clearly. Next you will see +% % how it follows the curve nicely in the slowly varying early +% % part of the signal, but averages the curve in the quickly +% % varying late part of the signal. +% t=0:0.01:2; x=chirp(t,2,.5,10,'quadratic')+sin(2*pi*t*0.4); +% y = decimate(x,4); # factor of 4 decimation +% stem(t(1:121)*1000,x(1:121),"-g;Original;"); hold on; # plot original +% stem(t(1:4:121)*1000,y(1:31),"-r;Decimated;"); hold off; # decimated + +% Copyright (C) 2000 Paul Kienzle +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +if nargin < 1 || nargin > 4, + disp('y=decimate(x, q [, n] [, ftype])'); +end +if q ~= fix(q), error('decimate only works with integer q.'); end + +if nargin<3 + ftype='iir'; + n=[]; +elseif nargin==3 + if isstr(n) + ftype=n; + n=[]; + else + ftype='iir'; + end +end + +fir = strcmp(ftype, 'fir'); +if isempty(n) + if fir, n=30; else n=8; end +end + +if fir + b = fir1(n, 1/q); + y=fftfilt(b, x); +else + [b, a] = cheby1(n, 0.05, 1/q); + y=filtfilt(b,a,x); +end +y = y(1:q:length(x)); +end + +%!demo +%! t=0:0.01:2; x=chirp(t,2,.5,10,'quadratic')+sin(2*pi*t*0.4); +%! y = decimate(x,4); # factor of 4 decimation +%! stem(t(1:121)*1000,x(1:121),"-g;Original;"); hold on; # plot original +%! stem(t(1:4:121)*1000,y(1:31),"-r;Decimated;"); hold off; # decimated +%! %------------------------------------------------------------------ +%! % The signal to decimate starts away from zero, is slowly varying +%! % at the start and quickly varying at the end, decimate and plot. +%! % Since it starts away from zero, you will see the boundary +%! % effects of the antialiasing filter clearly. You will also see +%! % how it follows the curve nicely in the slowly varying early +%! % part of the signal, but averages the curve in the quickly +%! % varying late part of the signal. diff --git a/sigproc/filtfilt.m b/sigproc/filtfilt.m new file mode 100644 index 0000000..806403e --- /dev/null +++ b/sigproc/filtfilt.m @@ -0,0 +1,72 @@ +% Copyright (C) 1999 Paul Kienzle +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +% usage: y = filtfilt(b, a, x) +% +% Forward and reverse filter the signal. This corrects for phase +% distortion introduced by a one-pass filter, though it does square the +% magnitude response in the process. That's the theory at least. In +% practice the phase correction is not perfect, and magnitude response +% is distorted, particularly in the stop band. +% +% In this version, I zero-pad the end of the signal to give the reverse +% filter time to ramp up to the level at the end of the signal. +% Unfortunately, the degree of padding required is dependent on the +% nature of the filter and not just its order, so this function needs +% some work yet. +% +% Example +% [b, a]=butter(3, 0.1); % 10 Hz low-pass filter +% t = 0:0.01:1.0; % 1 second sample +% x=sin(2*pi*t*2.3)+0.25*randn(size(t)); % 2.3 Hz sinusoid+noise +% y = filtfilt(b,a,x); z = filter(b,a,x); % apply filter +% plot(t,x,';data;',t,y,';filtfilt;',t,z,';filter;') + +% Changelog: +% 2000 02 pkienzle@kienzle.powernet.co.uk +% - pad with zeros to load up the state vector on filter reverse. +% - add example + +% TODO: In Matlab filtfilt `reduces filter startup transients by carefully +% TODO: choosing initial conditions, and by prepending onto the input +% TODO: sequence a short, reflected piece of the input sequence'. +% TODO: Once filtic is written, use that here. +% TODO: My version seems to have similar quality to matlab, but both are +% TODO: pretty bad. They do remove gross lag errors, though. +% TODO: Note that if x is really long, it might be worth doing +% TODO: the zero padding as a separate call to filter so that the +% TODO: vector never has to be copied. E.g., +% TODO: [y, state] = filter(b,a,x); +% TODO: tail = filter(b,a,zeros(1,max(length(b),length(a))),state); +% TODO: [tail, state] = filter(b,a,flipXX(tail)); +% TODO: y = flipXX(filter(b,a,flipXX(y), state)); +% TODO: Don't know for what n this would be faster, if any, but the +% TODO: memory saving might be nice. + +function y = filtfilt(b, a, x) +if (nargin ~= 3) + usage('y=filtfilt(b,a,x)'); +end + +if (size(x,1) == 1) + y = filter(b,a,[x, zeros(1,2*max(length(a),length(b)))]); + y = fliplr(filter(b,a,fliplr(y))); +else + y = filter(b,a,[x ; zeros(2*max(length(a),length(b)), 1)]); + y = flipud(filter(b,a,flipud(y))); +end +y = y(1:length(x)); +end diff --git a/sigproc/firls.m b/sigproc/firls.m new file mode 100644 index 0000000..31a75bb --- /dev/null +++ b/sigproc/firls.m @@ -0,0 +1,116 @@ +% Copyright (C) 2006 Quentin Spencer +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; If not, see . + +% b = firls(N, F, A); +% b = firls(N, F, A, W); +% +% FIR filter design using least squares method. Returns a length N+1 +% linear phase filter such that the integral of the weighted mean +% squared error in the specified bands is minimized. +% +% F specifies the frequencies of the band edges, normalized so that +% half the sample frequency is equal to 1. Each band is specified by +% two frequencies, to the vector must have an even length. +% +% A specifies the amplitude of the desired response at each band edge. +% +% W is an optional weighting function that contains one value for each +% band that weights the mean squared error in that band. A must be the +% same length as F, and W must be half the length of F. + +% The least squares optimization algorithm for computing FIR filter +% coefficients is derived in detail in: +% +% I. Selesnick, 'Linear-Phase FIR Filter Design by Least Squares,' +% http://cnx.org/content/m10577 + +function coef = firls(N, frequencies, pass, weight, str); + + +if nargin<3 | nargin>6 + usage(''); +end +if nargin==3 + weight = ones(1, length(pass)/2); + str = []; +end +if nargin==4 + if ischar(weight) + str = weight; + weight = ones (size (pass)); + else + str = []; + end +end +if length (frequencies) ~= length (pass) + error('F and A must have equal lengths.'); +end +if 2 * length (weight) ~= length (pass) + error('W must contain one weight per band.'); +end + +if ischar(str) + error('This feature is implemented yet'); +else + + M = N/2; + w = kron(weight(:), [-1; 1]); + omega = frequencies * pi; + i1 = 1:2:length(omega); + i2 = 2:2:length(omega); + + % Generate the matrix Q + % As illustrated in the above-cited reference, the matrix can be + % expressed as the sum of a Hankel and Toeplitz matrix. A factor of + % 1/2 has been dropped and the final filter coefficients multiplied + % by 2 to compensate. + cos_ints = [omega; sin((1:N)' * omega)]; + q = [1, 1./(1:N)]' .* (cos_ints * w); + Q = toeplitz (q(1:M+1)) + hankel (q(1:M+1), q(M+1:end)); + + % The vector b is derived from solving the integral: + % + % _ w + % / 2 + % b = / W(w) D(w) cos(kw) dw + % k / w + % - 1 + % + % Since we assume that W(w) is constant over each band (if not, the + % computation of Q above would be considerably more complex), but + % D(w) is allowed to be a linear function, in general the function + % W(w) D(w) is linear. The computations below are derived from the + % fact that: + % _ + % / a ax + b + % / (ax + b) cos(nx) dx = --- cos (nx) + ------ sin(nx) + % / 2 n + % - n + % + cos_ints2 = [omega(i1).^2 - omega(i2).^2; ... + cos((1:M)' * omega(i2)) - cos((1:M)' * omega(i1))] ./ ... + ([2, 1:M]' * (omega(i2) - omega(i1))); + d = [-weight .* pass(i1); weight .* pass(i2)] ; + d = d(:); + b = [1, 1./(1:M)]' .* ((kron (cos_ints2, [1, 1]) + cos_ints(1:M+1,:)) * d); + + % Having computed the components Q and b of the matrix equation, + % solve for the filter coefficients. + a = Q \ b; + coef = [ a(end:-1:2); 2 * a(1); a(2:end) ]; + +end + +end diff --git a/sigproc/hann.m b/sigproc/hann.m new file mode 100644 index 0000000..c7145e0 --- /dev/null +++ b/sigproc/hann.m @@ -0,0 +1,48 @@ +% Copyright (C) 1995, 1996, 1997 Andreas Weingessel +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2, or (at your option) +% any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place - Suite 330, Boston, MA +% 02111-1307, USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {} hanning (@var{m}) +% Return the filter coefficients of a Hanning window of length @var{m}. +% +% For a definition of this window type, see e.g. A. V. Oppenheim & +% R. W. Schafer, 'Discrete-Time Signal Processing'. +% @end deftypefn + +% Author: AW +% Description: Coefficients of the Hanning window + +function c = hann(m) + + if (nargin ~= 1) + usage ('hanning (m)'); + end + + if (~ (isscalar (m) && (m == round (m)) && (m > 0))) + error ('hanning: m has to be an integer > 0'); + end + + if (m == 1) + c = 1; + else + m = m - 1; + c = 0.5 - 0.5 * cos (2 * pi * (0 : m)' / m); + end + +end diff --git a/sigproc/hanning.m b/sigproc/hanning.m new file mode 100644 index 0000000..a1eff29 --- /dev/null +++ b/sigproc/hanning.m @@ -0,0 +1,48 @@ +## Copyright (C) 1995, 1996, 1997 Andreas Weingessel +## +## This file is part of Octave. +## +## Octave is free software; you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by +## the Free Software Foundation; either version 2, or (at your option) +## any later version. +## +## Octave is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +## General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with Octave; see the file COPYING. If not, write to the Free +## Software Foundation, 59 Temple Place - Suite 330, Boston, MA +## 02111-1307, USA. + +## -*- texinfo -*- +## @deftypefn {Function File} {} hanning (@var{m}) +## Return the filter coefficients of a Hanning window of length @var{m}. +## +## For a definition of this window type, see e.g. A. V. Oppenheim & +## R. W. Schafer, "Discrete-Time Signal Processing". +## @end deftypefn + +## Author: AW +## Description: Coefficients of the Hanning window + +function c = hanning (m) + + if (nargin != 1) + usage ("hanning (m)"); + endif + + if (! (isscalar (m) && (m == round (m)) && (m > 0))) + error ("hanning: m has to be an integer > 0"); + endif + + if (m == 1) + c = 1; + else + m = m - 1; + c = 0.5 - 0.5 * cos (2 * pi * (0 : m)' / m); + endif + +endfunction diff --git a/sigproc/sftrans.m b/sigproc/sftrans.m new file mode 100644 index 0000000..ef5b3a9 --- /dev/null +++ b/sigproc/sftrans.m @@ -0,0 +1,185 @@ +% usage: [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop) +% +% Transform band edges of a generic lowpass filter (cutoff at W=1) +% represented in splane zero-pole-gain form. W is the edge of the +% target filter (or edges if band pass or band stop). Stop is true for +% high pass and band stop filters or false for low pass and band pass +% filters. Filter edges are specified in radians, from 0 to pi (the +% nyquist frequency). Warning: gain Sg is returned as a complex value +% which may have some residual imaginary component. This matters for +% poles at extreme values in the s-plane, such as those created by odd +% order chebyshev type II low pass filters. +% +% Theory: Given a low pass filter represented by poles and zeros in the +% splane, you can convert it to a low pass, high pass, band pass or +% band stop by transforming each of the poles and zeros individually. +% The following table summarizes the transformation: +% +% Transform Zero at x Pole at x +% ---------------- ------------------------- ------------------------ +% Low Pass zero: Fc x/C pole: Fc x/C +% S -> C S/Fc gain: C/Fc gain: Fc/C +% ---------------- ------------------------- ------------------------ +% High Pass zero: Fc C/x pole: Fc C/x +% S -> C Fc/S pole: 0 zero: 0 +% gain: -x gain: -1/x +% ---------------- ------------------------- ------------------------ +% Band Pass zero: b ± sqrt(b^2-FhFl) pole: b ± sqrt(b^2-FhFl) +% S^2+FhFl pole: 0 zero: 0 +% S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C +% S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2 +% ---------------- ------------------------- ------------------------ +% Band Stop zero: b ± sqrt(b^2-FhFl) pole: b ± sqrt(b^2-FhFl) +% S(Fh-Fl) pole: ±sqrt(-FhFl) zero: ±sqrt(-FhFl) +% S -> C -------- gain: -x gain: -1/x +% S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2 +% ---------------- ------------------------- ------------------------ +% Bilinear zero: (2+xT)/(2-xT) pole: (2+xT)/(2-xT) +% 2 z-1 pole: -1 zero: -1 +% S -> - --- gain: (2-xT)/T gain: (2-xT)/T +% T z+1 +% ---------------- ------------------------- ------------------------ +% +% where C is the cutoff frequency of the initial lowpass filter, Fc is +% the edge of the target low/high pass filter and [Fl,Fh] are the edges +% of the target band pass/stop filter. With abundant tedious algebra, +% you can derive the above formulae yourself by substituting the +% transform for S into H(S)=S-x for a zero at x or H(S)=1/(S-x) for a +% pole at x, and converting the result into the form: +% +% H(S)=g prod(S-Xi)/prod(S-Xj) +% +% The transforms are from the references. The actual pole-zero-gain +% changes I derived myself. +% +% Please note that a pole and a zero at the same place exactly cancel. +% This is significant for High Pass, Band Pass and Band Stop filters +% which create numerous extra poles and zeros, most of which cancel. +% Those which do not cancel have a "fill-in" effect, extending the +% shorter of the sets to have the same number of as the longer of the +% sets of poles and zeros (or at least split the difference in the case +% of the band pass filter). There may be other opportunistic +% cancellations but I will not check for them. +% +% Also note that any pole on the unit circle or beyond will result in +% an unstable filter. Because of cancellation, this will only happen +% if the number of poles is smaller than the number of zeros and the +% filter is high pass or band pass. The analytic design methods all +% yield more poles than zeros, so this will not be a problem. +% +% References: +% +% Proakis & Manolakis (1992). Digital Signal Processing. New York: +% Macmillan Publishing Company. + +% Author: pkienzle@cs.indiana.edu + +% 2000-03 pkienzle@kienzle.powernet.co.uk +% leave transformed Sg as a complex value since cheby2 blows up +% otherwise (but only for odd-order low-pass filters). bilinear +% will return Zg as real, so there is no visible change to the +% user of the IIR filter design functions. + +% TODO: Shoul return real(Sg) rather than complex. Must fix cheby2 to be +% TODO: more stable first + +% Copyright (C) 1999 Paul Kienzle +% +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% This program is distributed in the hope that it will be useful, +% but WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +% GNU General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with this program; if not, write to the Free Software +% Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA + +function [Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop) +if (nargin ~= 5) + disp('[Sz, Sp, Sg] = sftrans(Sz, Sp, Sg, W, stop)'); +end; + +C = 1; +p = length(Sp); +z = length(Sz); +if z > p || p == 0 + error('sftrans: must have at least as many poles as zeros in s-plane'); +end + +if length(W)==2 + Fl = W(1); + Fh = W(2); + if stop + % ---------------- ------------------------- ------------------------ + % Band Stop zero: b ± sqrt(b^2-FhFl) pole: b ± sqrt(b^2-FhFl) + % S(Fh-Fl) pole: ±sqrt(-FhFl) zero: ±sqrt(-FhFl) + % S -> C -------- gain: -x gain: -1/x + % S^2+FhFl b=C/x (Fh-Fl)/2 b=C/x (Fh-Fl)/2 + % ---------------- ------------------------- ------------------------ + Sg = Sg * prod(-Sz)/prod(-Sp); + b = (C*(Fh-Fl)/2)./Sp; + Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)]; + extend = [sqrt(-Fh*Fl), -sqrt(-Fh*Fl)]; + if isempty(Sz) + Sz = [extend(1+rem([1:2*p],2))]; + else + b = (C*(Fh-Fl)/2)./Sz; + Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)]; + if (p > z) + Sz = [Sz, extend(1+rem([1:2*(p-z)],2))]; + end + end + else + % ---------------- ------------------------- ------------------------ + % Band Pass zero: b ± sqrt(b^2-FhFl) pole: b ± sqrt(b^2-FhFl) + % S^2+FhFl pole: 0 zero: 0 + % S -> C -------- gain: C/(Fh-Fl) gain: (Fh-Fl)/C + % S(Fh-Fl) b=x/C (Fh-Fl)/2 b=x/C (Fh-Fl)/2 + % ---------------- ------------------------- ------------------------ + Sg = Sg * (C/(Fh-Fl))^(z-p); + b = Sp*((Fh-Fl)/(2*C)); + Sp = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)]; + if isempty(Sz) + Sz = zeros(1,p); + else + b = Sz*((Fh-Fl)/(2*C)); + Sz = [b+sqrt(b.^2-Fh*Fl), b-sqrt(b.^2-Fh*Fl)]; + if (p>z) + Sz = [Sz, zeros(1, (p-z))]; + end + end + end +else + Fc = W; + if stop + % ---------------- ------------------------- ------------------------ + % High Pass zero: Fc C/x pole: Fc C/x + % S -> C Fc/S pole: 0 zero: 0 + % gain: -x gain: -1/x + % ---------------- ------------------------- ------------------------ + Sg = Sg * prod(-Sz)/prod(-Sp); + Sp = C * Fc ./ Sp; + if isempty(Sz) + Sz = zeros(1,p); + else + Sz = [C * Fc ./ Sz]; + if (p > z) + Sz = [Sz, zeros(1,p-z)]; + end + end + else + % ---------------- ------------------------- ------------------------ + % Low Pass zero: Fc x/C pole: Fc x/C + % S -> C S/Fc gain: C/Fc gain: Fc/C + % ---------------- ------------------------- ------------------------ + Sg = Sg * (C/Fc)^(z-p); + Sp = Fc * Sp / C; + Sz = Fc * Sz / C; + end +end +end diff --git a/sigproc/zp2ssg2.m b/sigproc/zp2ssg2.m new file mode 100644 index 0000000..7cd4afe --- /dev/null +++ b/sigproc/zp2ssg2.m @@ -0,0 +1,68 @@ +% Copyright (C) 1996, 1998 Auburn University. All rights reserved. +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2, or (at your option) any +% later version. +% +% Octave is distributed in the hope that it will be useful, but WITHOUT +% ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or +% FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License +% for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place, Suite 330, Boston, MA 02111 USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {[@var{poly}, @var{rvals}] =} __zp2ssg2__ (@var{rvals}) +% Used internally in @code{zp2ss} +% Extract 2 values from @var{rvals} (if possible) and construct +% a polynomial with those roots. +% @end deftypefn + +% Author: A. S. Hodel +% Created: August 1996 + +function [poly, rvals] = zp2ssg2(rvals) + +% locate imaginary roots (if any) +cidx = find(imag(rvals)); + +if(~isempty(cidx)) + % select first complex root, omit from cidx + r1i = cidx(1); r1 = rvals(r1i); cidx = complement(r1i,cidx); + + % locate conjugate root (must be in cidx list, just in case there's + % roundoff) + err = abs(rvals(cidx) - r1'); + minerr = min(err); + c2i = min(find(err == minerr)); + r2i = cidx(c2i); + r2 = rvals(r2i); + cidx = complement(r2i,cidx); + + % don't check for divide by zero, since 0 is not complex. + if(abs(r2 - r1')/abs(r1) > 1e-12) + error(sprintf('r1=(%f,%f); r2=(%f,%f), not conjugates.', ... + real(r1),imag(r1),real(r2),imag(r2))); + end + + % complex conjugate pair + poly = [1, -2*real(r1), real(r1)^2+imag(r1)^2]; +else + % select two roots (they're all real) + r1 = rvals(1); + r2 = rvals(2); + poly = [1, -(r1+r2), (r1*r2)]; + r1i = 1; r2i = 2; +end + +% remove roots used +idx = complement([r1i, r2i],1:length(rvals)); +rvals = rvals(idx); + +end + diff --git a/sigproc/zp2tf.m b/sigproc/zp2tf.m new file mode 100644 index 0000000..7848ac4 --- /dev/null +++ b/sigproc/zp2tf.m @@ -0,0 +1,74 @@ +% Copyright (C) 1996, 1998 Auburn University. All rights reserved. +% +% This file is part of Octave. +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2, or (at your option) any +% later version. +% +% Octave is distributed in the hope that it will be useful, but WITHOUT +% ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or +% FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License +% for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place, Suite 330, Boston, MA 02111 USA. + +% -*- texinfo -*- +% @deftypefn {Function File} {[@var{num}, @var{den}] =} zp2tf (@var{zer}, @var{pol}, @var{k}) +% Converts zeros / poles to a transfer function. +% +% @strong{Inputs} +% @table @var +% @item zer +% @itemx pol +% Vectors of (possibly complex) poles and zeros of a transfer +% function. Complex values must appear in conjugate pairs. +% @item k +% Real scalar (leading coefficient). +% @end table +% @end deftypefn + +% Author: A. S. Hodel +% (With help from students Ingram, McGowan.) + +function [num, den] = zp2tf (zer, pol, k) + +% Find out whether data was entered as a row or a column vector and +% convert to a column vector if necessary. + +[rp,cp] = size(pol); +[rz,cz] = size(zer); + +if(~(isvector(zer) | isempty(zer)) ) + error(sprintf('zer(%dx%d) must be a vector',rz,cz)); +elseif(~(isvector(pol) | isempty(pol)) ) + error(sprintf('pol(%dx%d) must be a vector',rp,cp)); +elseif(length(zer) > length(pol)) + error(sprintf('zer(%dx%d) longer than pol(%dx%d)',rz,cz,rp,cp)); +end + +% initialize converted polynomials + +num = k; den = 1; + +% call __zp2ssg2__ if there are complex conjugate pairs left, otherwise +% construct real zeros one by one. Repeat for poles. + +while(~isempty(zer)) + if( max(abs(imag(zer))) ) [poly, zer] = zp2ssg2(zer); + else poly = [1, -zer(1)]; + zer = zer(2:length(zer)); end + num = conv(num,poly); +end + +while(~isempty(pol)) + if( max(abs(imag(pol))) ) [poly, pol] = zp2ssg2(pol); + else poly = [1, -pol(1)]; + pol = pol(2:length(pol)); end + den = conv(den,poly); +end + +end diff --git a/simsort.m b/simsort.m new file mode 100644 index 0000000..d4a227f --- /dev/null +++ b/simsort.m @@ -0,0 +1,49 @@ +function [r,cc,M,YY] = simsort(X,simfun,M) +% simsort() - Sort data based on their similarity with a model + +% try +% D=evalin('base', 'D'); +% catch +% evalin('base', 'load mri'); +% end +% j=[1 20 30 31 60 61 62 63 64 65 66 70 75 80 85 110 120] +% X=double(D(j,40:80,1,13)); +% dbstop in simsort + +if nargin<3 +M=meannan(X); +end +if nargin<2 +simfun = 'corrcoef2'; +end +Y=M; +if nargout>4 + YY=repmat(M,size(X,1)-1,1); +end +ii=1:size(X,1); +r=NaN.*ii; +for i=1:size(X,1); + if nargout>4 + YY(i,:)=Y; + end + Z=X(ii,:); + [cc(i) tmp]=max(abs(feval(simfun,Y,Z'))); + r(i) = ii(tmp) + ii(tmp)=[]; + se(i)=0; + Y=meannan(X(r(1:i),:),1); + subplot(2,1,1); cla + hold on; + plot(X(r(1:i),:)') + plot(Y(:),'linewidth',3); + subplot(2,1,2) + plot(Z(:,:)'); + pause(.1) +end +%r(end)=ii; +size(Z) +abs(feval(simfun,Y,Z')) +cc(end+1)=abs(feval(simfun,Y,Z')); + + +%if exist('j','var');disp(j(r));end diff --git a/slidingwindow.m b/slidingwindow.m new file mode 100644 index 0000000..0bf4a84 --- /dev/null +++ b/slidingwindow.m @@ -0,0 +1,209 @@ +function [Y,W] = slidingwindow(X,N,dim,W,Wnorm,padval,fun,direction,varargin) +% SLIDINGWINDOW - Sliding window filter +% Y = slidingwindow(X,N) +% Y = slidingwindow(X,N,dim) +% Computes a sliding window filtering of width N along a given dimension +% of X (default: use the first non-singleton dimension) +% Note: The floor(N/2) first and last samples are computed with NaN padding +% Contrary to BUFFER, SLIDINGWINDOW works on matrices +% See also: BUFFER +% +% [Y,w] = slidingwindow(X,N,dim,W,Wnorm) +% Computes with a given windowing. +% W can be: +% - A vector of values (e.g. [0:10 9:-1:0] for a triangular windowing) +% - A function name (e.g. 'hanning') +% - A cell { funname arguments }, e.g. {'gausswin',5} (see: GAUSSWIN) +% N is not used (i.e. N is forced to the length of the windowing vector.) +% The W vector can be normalized so that norm(W,Wnorm)=1 (See NORM) +% Use Wnorm=[] to prevent normalizing W (default). +% +% [Y,w] = slidingwindow(X,N,dim,W,Wnorm,padval) +% padval: padding value on both sides +% +% Y = slidingwindow(X,N,dim,window,wnorm,fun,direction,funoptions) +% Instead of computing the sum of windowed values, it will uses +% 'fun' (a function handle/name) using additional options, if any. +% E.g. +% >> slidingwindow(X,10,1,[],[],0,'var') will compute local variance + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-15 Creation +% 2007-04-03 Updated, now allows specific padding +% KND 2009-04-15 Updated: remove borders +% +% ----------------------------- Script History --------------------------------- + +% Author: KND +% Created: Dec 2005 +% Copyright 2005 +if nargin<3 || isempty(dim) + dim = min(find(size(X)>1)); + if isempty(dim), dim = 1; end +end +if dim>1 + ndX=ndims(X); + X=permute(X,[dim 1:dim-1 dim+1:ndX]); +end +sX=[size(X) 1]; +X=X(:,:); +Y=zeros(size(X)); +if numel(N)>1 || numel(dim) > 1 + error('N and dim should be a single value'); +end +if nargin<4 + W=[]; +elseif ~isempty(W) + N=length(W); +elseif isempty(N) + error('N and W cannot be both []!') +end +if nargin<5 + Wnorm=[]; +end +if nargin<6 || isempty(padval) + padval=NaN; +end +if nargin<7 || isempty(fun) + fun=''; +end +if nargin<8 || isempty(direction) + direction = 0; +end + +if isempty(W) + if ~isempty(fun) + W=ones(N,1); + else + W=ones(N,1)/N; + end +elseif iscell(W) + W=feval(W{1},N,W{2:end}); +elseif ischar(W) + W=feval(W,N); +elseif isnumeric(W) + W=W; +end +W=W(:); +if ~isempty(Wnorm) + W=W./norm(W,Wnorm); +end + +padding = repmat(padval,floor(N/2),size(X,2)); +%padval=2*padval; +switch fun + case {'', 'sum'} + %for i=1:size(X,2) + %ya= filter(flipud(W),1,[padval+zeros(floor(N/2),1); X(:,i) ;padval+zeros(floor(N/2),1)]); + %yb=flipud(filter(W ,1,[padval+zeros(floor(N/2),1);flipud(X(:,i));padval+zeros(floor(N/2),1)])); + %ya=ya(N:end-1+mod(N,2)); + %yb=yb(2-mod(N,2):end-N+1); + %Y(:,i)=(ya+yb)/2; + %Y(:,i)=filter(W,1, + %end + + Y=filter(W,1,[ padding; X ;padding]); + Y(1:(N-mod(N,2)),:)=[]; + + case 'std' + warning('Uncjhecked result!!!') + W=diag(W); + for i=1:size(X,2) + ya=W*buffer([X(:,i);padval+zeros(floor(N/2),1)],N,N-1); + yb=fliplr(W*buffer([flipud(X(:,i));padval+zeros(floor(N/2),1)],N,N-1)); + ya=std(ya(:,floor(N/2)+1:end)); + yb=std(yb(:,1:end-floor(N/2))); + + ya=W*buffer([padval+zeros(floor(N/2),1);X(:,i);padval+zeros(floor(N/2),1)],N,N-1); + yb=fliplr(flipud(fliplr(W))*buffer([padval+zeros(floor(N/2),1);flipud(X(:,i));padval+zeros(floor(N/2),1)],N,N-1)); + ya=std(ya(:,N:end-1+mod(N,2))); + yb=std(yb(:,2-mod(N,2):end-N+1)); + + Y(:,i)=(ya+yb)'/2; +% Y(:,i)=std(W*buffer(X(:,i),N,N-1),[],1)+fliplr(std(W*buffer(flipud(X(:,i)),N,N-1),[],1))'; +% Y(:,i)=Y(:,i)/2; + end + W=diag(W); + otherwise + W=diag(W); + if exist('buffer', 'builtin') + error('unverified') + if direction>=0 + for i=1:size(X,2) + Y(:,i)=Y(:,i)+feval(fun,W*buffer(X(:,i),N,N-1),varargin{:}) + end + elseif direction <= 0 + for i=1:size(X,2) + Y(:,i)=Y(:,i)+fliplr(feval(fun,W*buffer(flipud(X(:,i)),N,N-1),varargin{:})); + end + else + error('Wrong direction'); + end + else % No buffer function + N2 = floor(N/2); + L = size(X,1); + if direction>=0 + for i=1:size(X,2) + for j=1:L % ceil(N/2):size(X,1)-floor(N/2) + Y(j,i)=feval(fun,W*[... + padding(end+((N2-(N-j)+1):0),i); ... + X(max(1,j-N2):min(L,j+N2),i); ... + padding(1:(N2-(L-j)),i)]); + end + end + elseif direction <= 0 + for i=1:size(X,2) + for j=1:L % ceil(N/2):size(X,1)-floor(N/2) + Y(j,i)=feval(fun,W*[... + padding(end+((N2-(N-j)+1):0),i); ... + X(max(1,j-N2):min(L,j+N2),i); ... + padding(1:(N2-(L-j)),i)]); + end + end + else + error('Wrong direction'); + end + end + if direction==0 + Y=Y./2; + end + W=diag(W); +end +Y=reshape(Y, [sX(1), sX(2:end)]); +if dim>1 + Y=ipermute(Y,[dim 1:dim-1 dim+1:ndX]); + %Y=permute(Y, [2:dim 1 dim+1:ndX]); +end + +return +% use FILTER instead of BUFFER (which requires the signal processing toolbox) +% Y(:,i)=[mean(w'*buffer(X(:,i),N,N-1),1)+fliplr(mean(w'*buffer(flipud(X(:,i)),N,N-1),1))]'; +% Y(:,i)=filter(w,1,X(:,i),[],1);%+flipud(filter(w,1,flipud(X(:,i)),[],1)); +% Y(:,i)=Y(:,i)/2; + +% Y(:,i)=(W'*buffer(X(:,i),N,N-1)+fliplr(W'*buffer(flipud(X(:,i)),N,N-1)))'/2; + +% FILTER is a causal filter!! +% ya=[filter(W,1,X(:,i),[],1);zeros(floor(N/2),1)]; +% ya=ya(floor(N/2)+1:end); +% yb=flipud([ filter(W,1,flipud(X(:,i)),[],1) ; zeros(floor(N/2),1)]); +% yb=yb(1:end-floor(N/2)); +% Y(:,i)=(ya+yb)/2; + + +% OUT OF MEMORY error with buffer +% for i=1:size(X,2) +% ya=W'*buffer([X(:,i);padval+zeros(floor(N/2),1)],N,N-1); +% yb=fliplr(W'*buffer([flipud(X(:,i));padval+zeros(floor(N/2),1)],N,N-1)); +% ya=ya(floor(N/2)+1:end); +% yb=yb(1:end-floor(N/2)); +% Y(:,i)=(ya+yb)'/2; +% end + diff --git a/sources_menu.m b/sources_menu.m new file mode 100644 index 0000000..674839a --- /dev/null +++ b/sources_menu.m @@ -0,0 +1,60 @@ +function [] = meeg_menu( varargin ) +%SOURCES_MENU - Add a MEEG Source related menue +return + +[hp,ha,hf]=findTessellationHandles(varargin{:}); +uhp=get(hp, 'UserData'); + +% Remove previous instances +t0=findobj(hf, 'Type', 'uimenu', 'Label', 'MEEG'); +delete(t0); + +t0=uimenu('Label', 'MEEG', 'Parent', hf) +t1 = uimenu('Parent',t0,... + 'Label','Surface processing'); + +cback='uhp=get(findTessellationHandles, ''UserData'');'; +t11 = uimenu('Parent',t1,... + 'Label','Smooth surface ',... + 'CallBack',[ ... + 'uhp=get(findTessellationHandles, ''UserData'');'... + 'p=handle2struct(uhp.h);p=lowerfields(p.properties);'... + '[fv]=smooth_cortex(p,uhp.vertconn,.3,10);' ... + 'set(uhp.h, ''Vertices'', fv.vertices)']); +t12 = uimenu('Parent',t1,... + 'Label','Adv. Smooth surface',... + 'CallBack',[ ... + 'uhp=get(findTessellationHandles, ''UserData'');'... + 'p=handle2struct(uhp.h);p=lowerfields(p.properties);'... + 'vals=inputdlg({''Smoothing factor'',''Iterations''}, ''Smooting parameters'', 1 , {''.3'', ''10''});'... + '[fv]=smooth_cortex(p,uhp.vertconn,str2num(vals{1}),str2num(vals{2}));' ... + 'set(uhp.h, ''Vertices'', fv.vertices)']); +if ~isfield(uhp, 'vertconn') + set([t11 t12], 'Enable', 'off') +end + + +t2 = uimenu('Parent',t1,... + 'Label','Back to original surface',... + 'CallBack',[ ... + 'uhp=get(findTessellationHandles, ''UserData'');'... + 'set(uhp.h, ''Vertices'', uhp.vertices)']); + +t2 = uimenu('Parent',t1,... + 'Label','Vertex Connectivity',... + 'CallBack','disp(''smoothing'');'); + +return +% Context menu +t0 = uicontextmenu('Visible', 'on'); +cback= ['u=get(gcbf, ''UserData'');' ... + '[p v vi f fi]=select3d(gcbo);'... + 'figure(''Name'', sprintf(''Scout: Vert#%d [%0.2g %0.2g %0.2g]'', vi, v)); plot(u.time, 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new file mode 100644 index 0000000..af149a4 --- /dev/null +++ b/spatfreq/filtimg1.m @@ -0,0 +1,137 @@ +% This Matlab (version 4) program demonstrates how gif-images can be filtered. +% Two of Matlab's toolboxes are required: +% - the Signal Processing Toolbox +% - the Image Processing Toolbox +% A one-dimensional Finite Impulse Response filter ('fir1') is +% transformed to a two-dimensional FIR filter using the 'ftrans2' function. +% GIF-image 'original.gif' is filtered and saved as 'lowpass.gif', +% 'bandpass.gif' and 'highpass.gif' +% +% Author: Paul van Diepen - Matlab Filter Program for Full Color Images +% Scene Perception Research, October 1992 - April 1999 +% Laboratory for Experimental Psychology +% University of Leuven, Belgium +% http://psy.van-diepen.com/pvdmatl.html + +% FILTER PARAMETERS +f1 = 1; % lowpass cut-off (cycl/deg) +f2 = 3; % highpass cut-off (cycl/deg) +fnyquist = 23; % Nyquist frequency (pixels/deg) (half the sample frequency) +n = 50; % Filter order + +% LOAD ORIGINAL IMAGE +[X, map] = gifread('original.gif'); + +% SEPARATE Red, Green, AND Blue CHANNELS +[R, G, B] = ind2rgb(X,map); + +% TWO-DIMENSIONAL FOURIER TRANSFORM +FFTr = fft2(R); +FFTg = fft2(G); +FFTb = fft2(B); + +% STORE DC-COMPONENT (THE AVERAGE COLOUR VALUE) +DCr = FFTr(1,1); +DCg = FFTg(1,1); +DCb = FFTb(1,1); + +% REARRANGE QUADRANTS (THE DC-COMPONENT IS MOVED TO THE CENTRE OF THE SPECTRUM) +FFTr = fftshift(FFTr); +FFTg = fftshift(FFTg); +FFTb = fftshift(FFTb); + +% LOWPASS FILTER +% RED +lowFFTr = freqz2( ftrans2(fir1(n, f1/fnyquist)), size(FFTr)) .* FFTr; +lowFFTr = rot90(fftshift(rot90(lowFFTr,2)),2); % restore quadrant positions +lowFFTr(1,1) = DCr; % restore dc-component +lowR = real(ifft2(lowFFTr)); % inverse Fourier transform +d = find(lowR < 0); lowR(d) = zeros(size(d)); % remove negative intensities +d = find(lowR > 1); lowR(d) = ones(size(d)); % remove intensities above 1 + +% GREEN +lowFFTg = freqz2( ftrans2(fir1(n, f1/fnyquist)), size(FFTg)) .* FFTg; +lowFFTg = rot90(fftshift(rot90(lowFFTg,2)),2); % restore quadrant positions +lowFFTg(1,1) = DCg; % restore dc-component +lowG = real(ifft2(lowFFTg)); % inverse Fourier transform +d = find(lowG < 0); lowG(d) = zeros(size(d)); % remove negative intensities +d = find(lowG > 1); lowG(d) = ones(size(d)); % remove intensities above 1 + +% BLUE +lowFFTb = freqz2( ftrans2(fir1(n, f1/fnyquist)), size(FFTb)) .* FFTb; +lowFFTb = rot90(fftshift(rot90(lowFFTb,2)),2); % restore quadrant positions +lowFFTb(1,1) = DCb; % restore dc-component +lowB = real(ifft2(lowFFTb)); % inverse Fourier transform +d = find(lowB < 0); lowB(d) = zeros(size(d)); % remove negative intensities +d = find(lowB > 1); lowB(d) = ones(size(d)); % remove intensities above 1 + +% COMBINE COLOURS TO INDEXED IMAGE +[X, map] = rgb2ind(lowR, lowG, lowB, 256); + +% STORE IMAGE +gifwrite(X, map, 'lowpass.gif'); + + +% BANDPASS FILTER +% RED +midFFTr = freqz2( ftrans2(fir1(n, [f1,f2]/fnyquist)), size(FFTr)) .* FFTr; +midFFTr = rot90(fftshift(rot90(midFFTr,2)),2); % restore quadrant positions +midFFTr(1,1) = DCr; % restore dc-component +midR = real(ifft2(midFFTr)); % inverse Fourier transform +d = find(midR < 0); midR(d) = zeros(size(d)); % remove negative intensities +d = find(midR > 1); midR(d) = ones(size(d)); % remove intensities above 1 + +% GREEN +midFFTg = freqz2( ftrans2(fir1(n, [f1,f2]/fnyquist)), size(FFTg)) .* FFTg; +midFFTg = rot90(fftshift(rot90(midFFTg,2)),2); % restore quadrant positions +midFFTg(1,1) = DCg; % restore dc-component +midG = real(ifft2(midFFTg)); % inverse Fourier transform +d = find(midG < 0); midG(d) = zeros(size(d)); % remove negative intensities +d = find(midG > 1); midG(d) = ones(size(d)); % remove intensities above 1 + +% BLUE +midFFTb = freqz2( ftrans2(fir1(n, [f1,f2]/fnyquist)), size(FFTb)) .* FFTb; +midFFTb = rot90(fftshift(rot90(midFFTb,2)),2); % restore quadrant positions +midFFTb(1,1) = DCb; % restore dc-component +midB = real(ifft2(midFFTb)); % inverse Fourier transform +d = find(midB < 0); midB(d) = zeros(size(d)); % remove negative intensities +d = find(midB > 1); midB(d) = ones(size(d)); % remove intensities above 1 + +% COMBINE COLOURS TO INDEXED IMAGE +[X, map] = rgb2ind(midR, midG, midB, 256); + +% STORE IMAGE +gifwrite(X, map, 'bandpass.gif'); + +% HIGHPASS FILTER +% RED +highFFTr = freqz2( ftrans2(fir1(n, f2/fnyquist, 'high')), size(FFTr)) .* FFTr; +highFFTr = rot90(fftshift(rot90(highFFTr,2)),2); % restore quadrant positions +highFFTr(1,1) = DCr; % restore dc-component +highR = real(ifft2(highFFTr)); % inverse Fourier transform +d = find(highR < 0); highR(d) = zeros(size(d)); % remove negative intensities +d = find(highR > 1); highR(d) = ones(size(d)); % remove intensities above 1 + +% GREEN +highFFTg = freqz2( ftrans2(fir1(n, f2/fnyquist, 'high')), size(FFTg)) .* FFTg; +highFFTg = rot90(fftshift(rot90(highFFTg,2)),2); % restore quadrant positions +highFFTg(1,1) = DCg; % restore dc-component +highG = real(ifft2(highFFTg)); % inverse Fourier transform +d = find(highG < 0); highG(d) = zeros(size(d)); % remove negative intensities +d = find(highG > 1); highG(d) = ones(size(d)); % remove intensities above 1 + +% BLUE +highFFTb = freqz2( ftrans2(fir1(n, f2/fnyquist, 'high')), size(FFTb)) .* FFTb; +highFFTb = rot90(fftshift(rot90(highFFTb,2)),2); % restore quadrant positions +highFFTb(1,1) = DCb; % restore dc-component +highB = real(ifft2(highFFTb)); % inverse Fourier transform +d = find(highB < 0); highB(d) = zeros(size(d)); % remove negative intensities +d = find(highB > 1); highB(d) = ones(size(d)); % remove intensities above 1 + +% COMBINE COLOURS TO INDEXED IMAGE +[X, map] = rgb2ind(highR, highG, highB, 256); + +% STORE IMAGE +gifwrite(X, map, 'highpass.gif'); + +% (p) 1996, Paul van Diepen, Laboratory of Experimental Psychology, Leuven, Belgium \ No newline at end of file diff --git a/spatfreq/lena_bw.bmp b/spatfreq/lena_bw.bmp new file mode 100644 index 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FORMAT N = spm_ecat2nifti(fname) +% fname - name of ECAT file +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner & Roger Gunn +% $Id: spm_ecat2nifti.m 112 2005-05-04 18:20:52Z john $ + + +if nargin==1, + opts = struct('ext','.nii'); +end; + +fp = fopen(fname,'r','ieee-be'); +if fp == -1, + error(['Can''t open "' fname '".']); + return; +end + +mh = ECAT7_mheader(fp); +if ~strcmp(mh.MAGIC_NUMBER,'MATRIX70v') &&... + ~strcmp(mh.MAGIC_NUMBER,'MATRIX71v') &&... + ~strcmp(mh.MAGIC_NUMBER,'MATRIX72v'), + error(['"' fname '" does not appear to be ECAT 7 format.']); + fclose(fp); + return; +end + +if mh.FILE_TYPE ~= 7, + error(['"' fname '" does not appear to be an image file.']); + fclose(fp); + return; +end + +list = s7_matlist(fp); +matches = find((list(:,4) == 1) | (list(:,4) == 2)); +llist = list(matches,:); + +for i=1:size(llist,1), + sh(i) = ECAT7_sheader(fp,llist(i,2)); +end; +fclose(fp); + +for i=1:size(llist,1), + dim = [sh(i).X_DIMENSION sh(i).Y_DIMENSION sh(i).Z_DIMENSION]; + dtype = [4 1]; + off = 512*llist(i,2); + scale = sh(i).SCALE_FACTOR*mh.ECAT_CALIBRATION_FACTOR; + inter = 0; + dati = file_array(fname,dim,dtype,off,scale,inter); + + dircos = diag([-1 -1 -1]); + step = ([sh(i).X_PIXEL_SIZE sh(i).Y_PIXEL_SIZE sh(i).Z_PIXEL_SIZE]*10); + start = -(dim(1:3)'/2).*step'; + mat = [[dircos*diag(step) dircos*start] ; [0 0 0 1]]; + + matnum = sprintf('%.8x',list(i,1)); + [pth,nam,ext] = fileparts(fname); + fnameo = fullfile(pwd,[nam '_' matnum opts.ext]); + dato = file_array(fnameo,dim,[4 spm_platform('bigend')],0,scale,inter); + + N = nifti; + N.dat = dato; + N.mat = mat; + N.mat0 = mat; + N.mat_intent = 'aligned'; + N.mat0_intent = 'scanner'; + N.descrip = sh(i).ANNOTATION; + N.timing = struct('toffset',sh(i).FRAME_START_TIME/1000,'tspace',sh(i).FRAME_DURATION/1000); + create(N); + for j=1:dim(3), + N.dat(:,:,j) = dati(:,:,j); + end; + N.extras = struct('mh',mh,'sh',sh(i)); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +%S7_MATLIST List the available matrixes in an ECAT 7 file. +% LIST = S7_MATLIST(FP) lists the available matrixes +% in the file specified by FP. +% +% Columns in LIST: +% 1 - Matrix identifier. +% 2 - Matrix subheader record number +% 3 - Last record number of matrix data block. +% 4 - Matrix status: +% 1 - exists - rw +% 2 - exists - ro +% 3 - matrix deleted +% +function list = s7_matlist(fp) + +% I believe fp should be opened with: +% fp = fopen(filename,'r','ieee-be'); + +fseek(fp,512,'bof'); +block = fread(fp,128,'int'); +if size(block,1) ~= 128 + list = []; + return; +end; +block = reshape(block,4,32); +list = []; +while block(2,1) ~= 2, + if block(1,1)+block(4,1) ~= 31, + list = []; return; + end; + list = [list block(:,2:32)]; + + fseek(fp,512*(block(2,1)-1),'bof'); + block = fread(fp,128,'int'); + if size(block,1) ~= 128, list = []; return; end; + block = reshape(block,4,32); +end +list = [list block(:,2:(block(4,1)+1))]; +list = list'; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function SHEADER=ECAT7_sheader(fid,record) +% +% Sub header read routine for ECAT 7 image files +% +% Roger Gunn, 260298 +off = (record-1)*512; +status = fseek(fid, off,'bof'); +data_type = fread(fid,1,'uint16',0); +num_dimensions = fread(fid,1,'uint16',0); +x_dimension = fread(fid,1,'uint16',0); +y_dimension = fread(fid,1,'uint16',0); +z_dimension = fread(fid,1,'uint16',0); +x_offset = fread(fid,1,'float32',0); +y_offset = fread(fid,1,'float32',0); +z_offset = fread(fid,1,'float32',0); +recon_zoom = fread(fid,1,'float32',0); +scale_factor = fread(fid,1,'float32',0); +image_min = fread(fid,1,'int16',0); +image_max = fread(fid,1,'int16',0); +x_pixel_size = fread(fid,1,'float32',0); +y_pixel_size = fread(fid,1,'float32',0); +z_pixel_size = fread(fid,1,'float32',0); +frame_duration = fread(fid,1,'uint32',0); +frame_start_time = fread(fid,1,'uint32',0); +filter_code = fread(fid,1,'uint16',0); +x_resolution = fread(fid,1,'float32',0); +y_resolution = fread(fid,1,'float32',0); +z_resolution = fread(fid,1,'float32',0); +num_r_elements = fread(fid,1,'float32',0); +num_angles = fread(fid,1,'float32',0); +z_rotation_angle = fread(fid,1,'float32',0); +decay_corr_fctr = fread(fid,1,'float32',0); +corrections_applied = fread(fid,1,'uint32',0); +gate_duration = fread(fid,1,'uint32',0); +r_wave_offset = fread(fid,1,'uint32',0); +num_accepted_beats = fread(fid,1,'uint32',0); +filter_cutoff_frequency = fread(fid,1,'float32',0); +filter_resolution = fread(fid,1,'float32',0); +filter_ramp_slope = fread(fid,1,'float32',0); +filter_order = fread(fid,1,'uint16',0); +filter_scatter_fraction = fread(fid,1,'float32',0); +filter_scatter_slope = fread(fid,1,'float32',0); +annotation = fread(fid,40,'char',0); +mt_1_1 = fread(fid,1,'float32',0); +mt_1_2 = fread(fid,1,'float32',0); +mt_1_3 = fread(fid,1,'float32',0); +mt_2_1 = fread(fid,1,'float32',0); +mt_2_2 = fread(fid,1,'float32',0); +mt_2_3 = fread(fid,1,'float32',0); +mt_3_1 = fread(fid,1,'float32',0); +mt_3_2 = fread(fid,1,'float32',0); +mt_3_3 = fread(fid,1,'float32',0); +rfilter_cutoff = fread(fid,1,'float32',0); +rfilter_resolution = fread(fid,1,'float32',0); +rfilter_code = fread(fid,1,'uint16',0); +rfilter_order = fread(fid,1,'uint16',0); +zfilter_cutoff = fread(fid,1,'float32',0); +zfilter_resolution = fread(fid,1,'float32',0); +zfilter_code = fread(fid,1,'uint16',0); +zfilter_order = fread(fid,1,'uint16',0); +mt_4_1 = fread(fid,1,'float32',0); +mt_4_2 = fread(fid,1,'float32',0); +mt_4_3 = fread(fid,1,'float32',0); +scatter_type = fread(fid,1,'uint16',0); +recon_type = fread(fid,1,'uint16',0); +recon_views = fread(fid,1,'uint16',0); +fill = fread(fid,1,'uint16',0); +annotation = deblank(char(annotation.*(annotation>0))'); + +SHEADER = struct('DATA_TYPE', data_type, ... + 'NUM_DIMENSIONS', num_dimensions, ... + 'X_DIMENSION', x_dimension, ... + 'Y_DIMENSION', y_dimension, ... + 'Z_DIMENSION', z_dimension, ... + 'X_OFFSET', x_offset, ... + 'Y_OFFSET', y_offset, ... + 'Z_OFFSET', z_offset, ... + 'RECON_ZOOM', recon_zoom, ... + 'SCALE_FACTOR', scale_factor, ... + 'IMAGE_MIN', image_min, ... + 'IMAGE_MAX', image_max, ... + 'X_PIXEL_SIZE', x_pixel_size, ... + 'Y_PIXEL_SIZE', y_pixel_size, ... + 'Z_PIXEL_SIZE', z_pixel_size, ... + 'FRAME_DURATION', frame_duration, ... + 'FRAME_START_TIME', frame_start_time, ... + 'FILTER_CODE', filter_code, ... + 'X_RESOLUTION', x_resolution, ... + 'Y_RESOLUTION', y_resolution, ... + 'Z_RESOLUTION', z_resolution, ... + 'NUM_R_ELEMENTS', num_r_elements, ... + 'NUM_ANGLES', num_angles, ... + 'Z_ROTATION_ANGLE', z_rotation_angle, ... + 'DECAY_CORR_FCTR', decay_corr_fctr, ... + 'CORRECTIONS_APPLIED', corrections_applied, ... + 'GATE_DURATION', gate_duration, ... + 'R_WAVE_OFFSET', r_wave_offset, ... + 'NUM_ACCEPTED_BEATS', num_accepted_beats, ... + 'FILTER_CUTOFF_FREQUENCY', filter_cutoff_frequency, ... + 'FILTER_RESOLUTION', filter_resolution, ... + 'FILTER_RAMP_SLOPE', filter_ramp_slope, ... + 'FILTER_ORDER', filter_order, ... + 'FILTER_SCATTER_CORRECTION', filter_scatter_fraction, ... + 'FILTER_SCATTER_SLOPE', filter_scatter_slope, ... + 'ANNOTATION', annotation, ... + 'MT_1_1', mt_1_1, ... + 'MT_1_2', mt_1_2, ... + 'MT_1_3', mt_1_3, ... + 'MT_2_1', mt_2_1, ... + 'MT_2_2', mt_2_2, ... + 'MT_2_3', mt_2_3, ... + 'MT_3_1', mt_3_1, ... + 'MT_3_2', mt_3_2, ... + 'MT_3_3', mt_3_3, ... + 'RFILTER_CUTOFF', rfilter_cutoff, ... + 'RFILTER_RESOLUTION', rfilter_resolution, ... + 'RFILTER_CODE', rfilter_code, ... + 'RFILTER_ORDER', rfilter_order, ... + 'ZFILTER_CUTOFF', zfilter_cutoff, ... + 'ZFILTER_RESOLUTION', zfilter_resolution, ... + 'ZFILTER_CODE', zfilter_code, ... + 'ZFILTER_ORDER', zfilter_order, ... + 'MT_4_1', mt_4_1, ... + 'MT_4_2', mt_4_2, ... + 'MT_4_3', mt_4_3, ... + 'SCATTER_TYPE', scatter_type, ... + 'RECON_TYPE', recon_type, ... + 'RECON_VIEWS', recon_views, ... + 'FILL', fill); +return; +%_______________________________________________________________________ +function [MHEADER]=ECAT7_mheader(fid) +% +% Main header read routine for ECAT 7 image files +% +% Roger Gunn, 260298 + +status = fseek(fid, 0,'bof'); +magic_number = fread(fid,14,'char',0); +original_file_name = fread(fid,32,'char',0); +sw_version = fread(fid,1,'uint16',0); +system_type = fread(fid,1,'uint16',0); +file_type = fread(fid,1,'uint16',0); +serial_number = fread(fid,10,'char',0); +scan_start_time = fread(fid,1,'uint32',0); +isotope_name = fread(fid,8,'char',0); +isotope_halflife = fread(fid,1,'float32',0); +radiopharmaceutical = fread(fid,32,'char',0); +gantry_tilt = fread(fid,1,'float32',0); +gantry_rotation = fread(fid,1,'float32',0); +bed_elevation = fread(fid,1,'float32',0); +intrinsic_tilt = fread(fid,1,'float32',0); +wobble_speed = fread(fid,1,'uint16',0); +transm_source_type = fread(fid,1,'uint16',0); +distance_scanned = fread(fid,1,'float32',0); +transaxial_fov = fread(fid,1,'float32',0); +angular_compression = fread(fid,1,'uint16',0); +coin_samp_mode = fread(fid,1,'uint16',0); +axial_samp_mode = fread(fid,1,'uint16',0); +ecat_calibration_factor = fread(fid,1,'float32',0); +calibration_units = fread(fid,1,'uint16',0); +calibration_units_type = fread(fid,1,'uint16',0); +compression_code = fread(fid,1,'uint16',0); +study_type = fread(fid,12,'char',0); +patient_id = fread(fid,16,'char',0); +patient_name = fread(fid,32,'char',0); +patient_sex = fread(fid,1,'char',0); +patient_dexterity = fread(fid,1,'char',0); +patient_age = fread(fid,1,'float32',0); +patient_height = fread(fid,1,'float32',0); +patient_weight = fread(fid,1,'float32',0); +patient_birth_date = fread(fid,1,'uint32',0); +physician_name = fread(fid,32,'char',0); +operator_name = fread(fid,32,'char',0); +study_description = fread(fid,32,'char',0); +acquisition_type = fread(fid,1,'uint16',0); +patient_orientation = fread(fid,1,'uint16',0); +facility_name = fread(fid,20,'char',0); +num_planes = fread(fid,1,'uint16',0); +num_frames = fread(fid,1,'uint16',0); +num_gates = fread(fid,1,'uint16',0); +num_bed_pos = fread(fid,1,'uint16',0); +init_bed_position = fread(fid,1,'float32',0); +bed_position = zeros(15,1); +for bed=1:15, + tmp = fread(fid,1,'float32',0); + if ~isempty(tmp), bed_position(bed) = tmp; end; +end; +plane_separation = fread(fid,1,'float32',0); +lwr_sctr_thres = fread(fid,1,'uint16',0); +lwr_true_thres = fread(fid,1,'uint16',0); +upr_true_thres = fread(fid,1,'uint16',0); +user_process_code = fread(fid,10,'char',0); +acquisition_mode = fread(fid,1,'uint16',0); +bin_size = fread(fid,1,'float32',0); +branching_fraction = fread(fid,1,'float32',0); +dose_start_time = fread(fid,1,'uint32',0); +dosage = fread(fid,1,'float32',0); +well_counter_corr_factor = fread(fid,1,'float32',0); +data_units = fread(fid,32,'char',0); +septa_state = fread(fid,1,'uint16',0); +fill = fread(fid,1,'uint16',0); + +magic_number = deblank(char(magic_number.*(magic_number>32))'); +original_file_name = deblank(char(original_file_name.*(original_file_name>0))'); +serial_number = deblank(char(serial_number.*(serial_number>0))'); +isotope_name = deblank(char(isotope_name.*(isotope_name>0))'); +radiopharmaceutical = deblank(char(radiopharmaceutical.*(radiopharmaceutical>0))'); +study_type = deblank(char(study_type.*(study_type>0))'); +patient_id = deblank(char(patient_id.*(patient_id>0))'); +patient_name = deblank(char(patient_name.*(patient_name>0))'); +patient_sex = deblank(char(patient_sex.*(patient_sex>0))'); +patient_dexterity = deblank(char(patient_dexterity.*(patient_dexterity>0))'); +physician_name = deblank(char(physician_name.*(physician_name>0))'); +operator_name = deblank(char(operator_name.*(operator_name>0))'); +study_description = deblank(char(study_description.*(study_description>0))'); +facility_name = deblank(char(facility_name.*(facility_name>0))'); +user_process_code = deblank(char(user_process_code.*(user_process_code>0))'); +data_units = deblank(char(data_units.*(data_units>0))'); + +MHEADER = struct('MAGIC_NUMBER', magic_number, ... + 'ORIGINAL_FILE_NAME', original_file_name, ... + 'SW_VERSION', sw_version, ... + 'SYSTEM_TYPE', system_type, ... + 'FILE_TYPE', file_type, ... + 'SERIAL_NUMBER', serial_number, ... + 'SCAN_START_TIME', scan_start_time, ... + 'ISOTOPE_NAME', isotope_name, ... + 'ISOTOPE_HALFLIFE', isotope_halflife, ... + 'RADIOPHARMACEUTICAL', radiopharmaceutical, ... + 'GANTRY_TILT', gantry_tilt, ... + 'GANTRY_ROTATION', gantry_rotation, ... + 'BED_ELEVATION', bed_elevation, ... + 'INTRINSIC_TILT', intrinsic_tilt, ... + 'WOBBLE_SPEED', wobble_speed, ... + 'TRANSM_SOURCE_TYPE', transm_source_type, ... + 'DISTANCE_SCANNED', distance_scanned, ... + 'TRANSAXIAL_FOV', transaxial_fov, ... + 'ANGULAR_COMPRESSION', angular_compression, ... + 'COIN_SAMP_MODE', coin_samp_mode, ... + 'AXIAL_SAMP_MODE', axial_samp_mode, ... + 'ECAT_CALIBRATION_FACTOR', ecat_calibration_factor, ... + 'CALIBRATION_UNITS', calibration_units, ... + 'CALIBRATION_UNITS_TYPE', calibration_units_type, ... + 'COMPRESSION_CODE', compression_code, ... + 'STUDY_TYPE', study_type, ... + 'PATIENT_ID', patient_id, ... + 'PATIENT_NAME', patient_name, ... + 'PATIENT_SEX', patient_sex, ... + 'PATIENT_DEXTERITY', patient_dexterity, ... + 'PATIENT_AGE', patient_age, ... + 'PATIENT_HEIGHT', patient_height, ... + 'PATIENT_WEIGHT', patient_weight, ... + 'PATIENT_BIRTH_DATE', patient_birth_date, ... + 'PHYSICIAN_NAME', physician_name, ... + 'OPERATOR_NAME', operator_name, ... + 'STUDY_DESCRIPTION', study_description, ... + 'ACQUISITION_TYPE', acquisition_type, ... + 'PATIENT_ORIENTATION', patient_orientation, ... + 'FACILITY_NAME', facility_name, ... + 'NUM_PLANES', num_planes, ... + 'NUM_FRAMES', num_frames, ... + 'NUM_GATES', num_gates, ... + 'NUM_BED_POS', num_bed_pos, ... + 'INIT_BED_POSITION', init_bed_position, ... + 'BED_POSITION', bed_position, ... + 'PLANE_SEPARATION', plane_separation, ... + 'LWR_SCTR_THRES', lwr_sctr_thres, ... + 'LWR_TRUE_THRES', lwr_true_thres, ... + 'UPR_TRUE_THRES', upr_true_thres, ... + 'USER_PROCESS_CODE', user_process_code, ... + 'ACQUISITION_MODE', acquisition_mode, ... + 'BIN_SIZE', bin_size, ... + 'BRANCHING_FRACTION', branching_fraction, ... + 'DOSE_START_TIME', dose_start_time, ... + 'DOSAGE', dosage, ... + 'WELL_COUNTER_CORR_FACTOR', well_counter_corr_factor, ... + 'DATA_UNITS', data_units, ... + 'SEPTA_STATE', septa_state, ... + 'FILL', fill); +return; +%_______________________________________________________________________ diff --git a/spm/nii_for_spm2/spm_eeg_marry_scalp_head_quick.m b/spm/nii_for_spm2/spm_eeg_marry_scalp_head_quick.m new file mode 100755 index 0000000..30860a2 --- /dev/null +++ b/spm/nii_for_spm2/spm_eeg_marry_scalp_head_quick.m @@ -0,0 +1,16 @@ +function [col_scalp]=marry_scalp_head_quick(V,C,V3,elec_verts,dv,id); +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% James Kilner +% $Id: spm_eeg_marry_scalp_head_quick.m 112 2005-05-04 18:20:52Z john $ + +col_scalp=zeros(length(dv),1); +P = fullfile(spm('dir'), 'EEGtemplates'); +load(fullfile(P, 'params2.mat')); +col_scalp(col_scalp==0)=NaN; +allid(allid(:,1)==0,:)=''; +alltds(alltds(:,1)==0,:)=''; +alli(alli(:,1)==0,:)=''; + +col_scalp(allid)=sum((alltds(:,:).*C(alli(:,1:10))),2); diff --git a/spm/nii_for_spm2/spm_fileparts.m b/spm/nii_for_spm2/spm_fileparts.m new file mode 100755 index 0000000..2866b59 --- /dev/null +++ b/spm/nii_for_spm2/spm_fileparts.m @@ -0,0 +1,24 @@ +function [pth,nam,ext,num] = spm_fileparts(fname) +% Like fileparts, but separates off a comma separated list at the end +% FORMAT [pth,nam,ext,num] = spm_fileparts(fname) +% fname - original filename +% pth - path +% nam - filename +% ext - extension +% num - comma separated list of values +% +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_fileparts.m 112 2005-05-04 18:20:52Z john $ + + +num = ''; +[pth,nam,ext] = fileparts(fname); +ind = find(ext==','); +if ~isempty(ind), + num = ext(ind(1):end); + ext = ext(1:(ind(1)-1)); +end; + diff --git a/spm/nii_for_spm2/spm_mnc2nifti.m b/spm/nii_for_spm2/spm_mnc2nifti.m new file mode 100644 index 0000000..f188bde --- /dev/null +++ b/spm/nii_for_spm2/spm_mnc2nifti.m @@ -0,0 +1,213 @@ +function [N,cdf] = spm_mnc2nifti(fname,opts) +% Get header information etc. for MINC images. +% FORMAT spm_mnc2nifti(fname) +% fname - a MINC filename. +% +% The MINC file format was developed by Peter Neelin at the Montréal +% Neurological Institute, and is based upon the NetCDF libraries. +% The NetCDF documentation specifically recommends that people do not +% write their own libraries for accessing the data. This suggestion +% was ignored. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_mnc2nifti.m 946 2007-10-15 16:36:06Z john $ + + +if nargin==1, + opts = struct('dtype',4,'ext','.img'); +end; + +cdf = spm_read_netcdf(fname); +if isempty(cdf), warning(['"' fname '" does not appear to be MINC.']); return; end; + +idat = file_array; + +d_types = [2 2 512 768 16 64 ; 256 256 4 8 16 64]; +dsizes = [1 1 2 4 4 8 ]; +mxs = [255 255 65535 2^32-1 Inf Inf; 127 127 32767 2^31-1 Inf Inf]; +mns = [0 0 0 0 -Inf -Inf;-128 -128 -32768 -2^31 -Inf -Inf]; +space_names = {'xspace','yspace','zspace'}; +img = findvar(cdf.var_array,'image'); +nd = length(img.dimid); +idat.fname = fname; +idat.dim = fliplr(cat(2,cdf.dim_array(:).dim_length)); +signed = findvar(img.vatt_array,'signtype'); +signed = strcmp(signed.val,'signed__'); +idat.dtype = [d_types(signed+1,img.nc_type) 1]; +range = [mns(signed+1,img.nc_type) mxs(signed+1,img.nc_type)]; +idat.offset = img.begin; + + +if img.nc_type <=4, + tmp = findvar(img.vatt_array,'valid_range'); + if isempty(tmp), + disp(['Can''t get valid_range for "' fname '" - having to guess']); + else + range = tmp.val; + end; + + fp = fopen(fname,'r','ieee-be'); + imax = get_imax(fp, cdf, 'image-max', fname, 1, idat.dim); + imin = get_imax(fp, cdf, 'image-min', fname, 0, idat.dim); + fclose(fp); + + scale = (imax-imin)/(range(2)-range(1)); + dcoff = imin-range(1)*scale; +else + scale = 1; + dcoff = 0; +end; + + +% Extract affine transformation from voxel to world co-ordinates +%----------------------------------------------------------------------- +step = [1 1 1]; +start = [0 0 0]'; +dircos = eye(3); +for j=1:3, + nam = cdf.dim_array(img.dimid(nd+1-j)).name; + space = findvar(cdf.var_array,nam); + tmp = findvar(space.vatt_array,'step'); + if ~isempty(tmp), step(j) = tmp.val; end; + tmp = findvar(space.vatt_array,'start'); + if ~isempty(tmp), start(j) = tmp.val; else start(j) = -dim(j)/2*step(j); end; + tmp = findvar(space.vatt_array,'direction_cosines'); + if ~isempty(tmp), dircos(:,j) = tmp.val; end; +end; +shiftm = [1 0 0 -1; 0 1 0 -1; 0 0 1 -1; 0 0 0 1]; +mat = [[dircos*diag(step) dircos*start] ; [0 0 0 1]] * shiftm; + +N = nifti; +dat = file_array; +[pth,nam,ext] = fileparts(fname); +dat.fname = fullfile(pwd,[nam opts.ext]); +dat.dim = idat.dim; +dat.dtype = [opts.dtype spm_platform('bigend')]; +dat.offset = 0; + +if ~spm_type(opts.dtype,'intt'), + dat.scl_slope = 1; + dat.scl_inter = 0; +else + mn = Inf; + mx = -Inf; + for i6=1:size(idat,6), + for i5=1:size(idat,5), + for i4=1:size(idat,4), + for i3=1:size(idat,3), + if size(scale,3)==1, + scale1 = scale(:,:,1,i4,i5,i6); + dcoff1 = dcoff(:,:,1,i4,i5,i6); + else + scale1 = scale(:,:,i3,i4,i5,i6); + dcoff1 = dcoff(:,:,i3,i4,i5,i6); + end + if numel(scale1)==1, + img = double(idat(:,:,i3,i4,i5,i6))*scale1 + dcoff1; + elseif size(scale1,1)>1 && size(scale1,2)>1, + img = double(idat(:,:,i3,i4,i5,i6)).*scale1 + dcoff1; + elseif size(scale1,1)==1, + img = double(idat(:,:,i3,i4,i5,i6)).*repmat(scale1,[size(idat,1) 1]) +... + repmat(dcoff1,[size(idat,1) 1]); + else + img = double(idat(:,:,i3,i4,i5,i6)).*repmat(scale1,[1 size(idat,2)]) +... + repmat(dcoff1,[1 size(idat,2)]); + end; + img = img(isfinite(img)); + if ~isempty(img), + mx = max(mx,max(img)); + mn = min(mn,min(img)); + end; + end; + end; + end; + end; + dat.scl_slope = mx/spm_type(opts.dtype,'maxval'); + if spm_type(opts.dtype,'minval')~=0, + dat.scl_slope = max(dat.scl_slope,mn/spm_type(opts.dtype,'minval')); + end; + dat.scl_inter = 0; +end; + +N.dat = dat; +flp = false; +if det(mat)>0, + flp = true; + mat = mat*[diag([-1 1 1]) [size(dat,1)+1 0 0]' ; 0 0 0 1]; +end; +N.mat = mat; +N.mat0 = mat; +create(N); +for i6=1:size(idat,6), + for i5=1:size(idat,5), + for i4=1:size(idat,4), + for i3=1:size(idat,3), + if size(scale,3)==1, + scale1 = scale(:,:,1,i4,i5,i6); + dcoff1 = dcoff(:,:,1,i5,i5,i6); + else + scale1 = scale(:,:,i3,i4,i5,i6); + dcoff1 = dcoff(:,:,i3,i4,i5,i6); + end + if numel(scale1)==1, + slice = double(idat(:,:,i3,i4,i5,i6))*scale1 + dcoff1; + elseif size(scale1,1)>1 && size(scale1,2)>1, + slice = double(idat(:,:,i3,i4,i5,i6)).*scale1 + dcoff1; + elseif size(scale1,1)==1, + slice = double(idat(:,:,i3,i4,i5,i6)).*repmat(scale1,[size(idat,1) 1]) +... + repmat(dcoff1,[size(idat,1) 1]); + else + slice = double(idat(:,:,i3,i4,i5,i6)).*repmat(scale1,[1 size(idat,2)]) +... + repmat(dcoff1,[1 size(idat,2)]); + end; + if flp, slice = flipud(slice); end; + N.dat(:,:,i3,i4,i5,i6) = slice; + end; + end; + end; +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function var = findvar(varlist, name) +% Finds the structure in a list of structures that has a name element +% matching the second argument. +for i=1:numel(varlist) + if strcmp(varlist(i).name,name) + var = varlist(i); + return; + end; +end; +var = []; +%error(['Can''t find "' name '".']); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function str = dtypestr(i) +% Returns a string appropriate for reading or writing the CDF data-type. +types = char('uint8','uint8','int16','int32','float32','float64'); +str = deblank(types(i,:)); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function imax = get_imax(fp, cdf, strng, fname, def, dim) +dim = fliplr(dim); +str = findvar(cdf.var_array,strng); + +if ~isempty(str) && str.nc_type == 6, + fseek(fp,str.begin,'bof'); + nel = str.vsize/(spm_type(dtypestr(str.nc_type),'bits')/8); + imax = fread(fp,nel,dtypestr(str.nc_type))'; + resh = ones(1,numel(dim)); + resh(numel(dim)+1-str.dimid) = dim(str.dimid); + imax = reshape(imax,resh); +else + imax = def; +end; +return; + diff --git a/spm/nii_for_spm2/spm_read_hdr.m b/spm/nii_for_spm2/spm_read_hdr.m new file mode 100755 index 0000000..11bb8b1 --- /dev/null +++ b/spm/nii_for_spm2/spm_read_hdr.m @@ -0,0 +1,141 @@ +function [hdr,otherendian] = spm_read_hdr(fname) +% Read (SPM customised) Analyze header +% FORMAT [hdr,otherendian] = spm_read_hdr(fname) +% fname - .hdr filename +% hdr - structure containing Analyze header +% otherendian - byte swapping necessary flag +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_read_hdr.m 112 2005-05-04 18:20:52Z john $ + + +fid = fopen(fname,'r','native'); +otherendian = 0; +if (fid > 0) + dime = read_dime(fid); + if dime.dim(1)<0 | dime.dim(1)>15, % Appears to be other-endian + % Re-open other-endian + fclose(fid); + if spm_platform('bigend'), fid = fopen(fname,'r','ieee-le'); + else, fid = fopen(fname,'r','ieee-be'); end; + otherendian = 1; + dime = read_dime(fid); + end; + hk = read_hk(fid); + hist = read_hist(fid); + hdr.hk = hk; + hdr.dime = dime; + hdr.hist = hist; + + % SPM specific bit - unused + %if hdr.hk.sizeof_hdr > 348, + % spmf = read_spmf(fid,dime.dim(5)); + % if ~isempty(spmf), + % hdr.spmf = spmf; + % end; + %end; + + fclose(fid); +else, + hdr = []; + otherendian = NaN; + %error(['Problem opening header file (' fopen(fid) ').']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hk = read_hk(fid) +% read (struct) header_key +%----------------------------------------------------------------------- +fseek(fid,0,'bof'); +hk.sizeof_hdr = fread(fid,1,'int32'); +hk.data_type = mysetstr(fread(fid,10,'uchar'))'; +hk.db_name = mysetstr(fread(fid,18,'uchar'))'; +hk.extents = fread(fid,1,'int32'); +hk.session_error = fread(fid,1,'int16'); +hk.regular = mysetstr(fread(fid,1,'uchar'))'; +hk.hkey_un0 = mysetstr(fread(fid,1,'uchar'))'; +if isempty(hk.hkey_un0), error(['Problem reading "hk" of header file (' fopen(fid) ').']); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function dime = read_dime(fid) +% read (struct) image_dimension +%----------------------------------------------------------------------- +fseek(fid,40,'bof'); +dime.dim = fread(fid,8,'int16')'; +dime.vox_units = mysetstr(fread(fid,4,'uchar'))'; +dime.cal_units = mysetstr(fread(fid,8,'uchar'))'; +dime.unused1 = fread(fid,1,'int16'); +dime.datatype = fread(fid,1,'int16'); +dime.bitpix = fread(fid,1,'int16'); +dime.dim_un0 = fread(fid,1,'int16'); +dime.pixdim = fread(fid,8,'float')'; +dime.vox_offset = fread(fid,1,'float'); +dime.funused1 = fread(fid,1,'float'); +dime.funused2 = fread(fid,1,'float'); +dime.funused3 = fread(fid,1,'float'); +dime.cal_max = fread(fid,1,'float'); +dime.cal_min = fread(fid,1,'float'); +dime.compressed = fread(fid,1,'int32'); +dime.verified = fread(fid,1,'int32'); +dime.glmax = fread(fid,1,'int32'); +dime.glmin = fread(fid,1,'int32'); +if isempty(dime.glmin), error(['Problem reading "dime" of header file (' fopen(fid) ').']); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hist = read_hist(fid) +% read (struct) data_history +%----------------------------------------------------------------------- +fseek(fid,148,'bof'); +hist.descrip = mysetstr(fread(fid,80,'uchar'))'; +hist.aux_file = mysetstr(fread(fid,24,'uchar'))'; +hist.orient = fread(fid,1,'uchar'); +hist.origin = fread(fid,5,'int16')'; +hist.generated = mysetstr(fread(fid,10,'uchar'))'; +hist.scannum = mysetstr(fread(fid,10,'uchar'))'; +hist.patient_id = mysetstr(fread(fid,10,'uchar'))'; +hist.exp_date = mysetstr(fread(fid,10,'uchar'))'; +hist.exp_time = mysetstr(fread(fid,10,'uchar'))'; +hist.hist_un0 = mysetstr(fread(fid,3,'uchar'))'; +hist.views = fread(fid,1,'int32'); +hist.vols_added = fread(fid,1,'int32'); +hist.start_field= fread(fid,1,'int32'); +hist.field_skip = fread(fid,1,'int32'); +hist.omax = fread(fid,1,'int32'); +hist.omin = fread(fid,1,'int32'); +hist.smax = fread(fid,1,'int32'); +hist.smin = fread(fid,1,'int32'); +if isempty(hist.smin), error(['Problem reading "hist" of header file (' fopen(fid) ').']); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function spmf = read_spmf(fid,n) +% Read SPM specific fields +% This bit may be used in the future for extending the Analyze header. + +fseek(fid,348,'bof'); +mgc = fread(fid,1,'int32'); % Magic number +if mgc ~= 20020417, spmf = []; return; end; + +for j=1:n, + spmf(j).mat = fread(fid,16,'double'); % Orientation information + spmf(j).unused = fread(fid,384,'uchar'); % Extra unused stuff + if length(spmf(j).unused)<384, + error(['Problem reading "spmf" of header file (' fopen(fid) ').']); + end; + spmf(j).mat = reshape(spmf(j).mat,[4 4]); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function out = mysetstr(in) +tmp = find(in == 0); +tmp = min([min(tmp) length(in)]); +out = setstr([in(1:tmp)' zeros(1,length(in)-(tmp))])'; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ diff --git a/spm/nii_for_spm2/spm_read_vols.m b/spm/nii_for_spm2/spm_read_vols.m new file mode 100644 index 0000000..e37ad8f --- /dev/null +++ b/spm/nii_for_spm2/spm_read_vols.m @@ -0,0 +1,59 @@ +function [Y,XYZ] = spm_read_vols(V,mask) +% Read in entire image volumes +% FORMAT [Y,XYZ] = spm_read_vols(V,mask) +% V - vector of mapped image volumes to read in (from spm_vol) +% mask - implicit zero mask? +% Y - 4D matrix of image data, fourth dimension indexes images +% XYZ - 3xn matrix of XYZ locations returned +%_______________________________________________________________________ +% +% For image data types without a representation of NaN (see spm_type), +% implicit zero masking can be used. If mask is set, then zeros are +% treated as masked, and returned as NaN. +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% Andrew Holmes +% $Id: spm_read_vols.m 1096 2008-01-16 12:12:57Z john $ + + + +%-Argument checks +%----------------------------------------------------------------------- +if nargin<2, mask = 0; end +if nargin<1, error('insufficient arguments'), end + +spm_check_orientations(V); + +%-Read in image data +%----------------------------------------------------------------------- +n = prod(size(V)); %-#images +Y = zeros([V(1).dim(1:3),n]); %-image data matrix + +for i=1:n, for p=1:V(1).dim(3) + Y(:,:,p,i) = spm_slice_vol(V(i),spm_matrix([0 0 p]),V(i).dim(1:2),0); +end, end + +%-Apply implicit zero mask for image datatypes without a NaNrep +%----------------------------------------------------------------------- +if mask + %-Work out images without NaNrep + im = logical(zeros(n,1)); + for i=1:n, im(i)=~spm_type(V(i).dt(1),'NaNrep'); end + %-Mask + Y(Y(:,:,:,im)==0)=NaN; +end + +%-Return as 3D matrix if single image +%----------------------------------------------------------------------- +if n==1; Y=Y(:,:,:,1); end + +%-Compute XYZ co-ordinates (if required) +%----------------------------------------------------------------------- +if nargout>1 + [R,C,P]=ndgrid(1:V(1).dim(1),1:V(1).dim(2),1:V(1).dim(3)); + RCP = [R(:)';C(:)';P(:)']; + clear R C P + RCP(4,:)=1; + XYZ = V(1).mat(1:3,:)*RCP; +end diff --git a/spm/nii_for_spm2/spm_render_vol.mexa64 b/spm/nii_for_spm2/spm_render_vol.mexa64 new file mode 100644 index 0000000000000000000000000000000000000000..1a37da6539f65dad71dd5f82a650ea00922a409b GIT binary patch literal 260719 zcmeFa4SZC^)jz&THV`d%H=1ZvsHrS%h=_?|O$0RyyKombfC8G>D8T@t1xdpOqk;xD zt6Z0h)I!VCM_SryOP|VvwxU*{gx3Hf22cc1h>Chwd_in6ppyUhd*?;ZId7LMSCCjnC;SfB=?5O}A#mrtz%5Z%?kIg8gWI{ew7Fa0{%#&p`n$#|+A@YrwFx-M5X;_QM`@H^8^OMYodk<$@A3%~9* 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zEbc<_8?BUuUh#3L1Ky06&^U^Z-Dt}}^osXFBk*RNgT_C&Z)O||sWa$-%Hh4>-+$DW zO89PY$0z9{_)2i=U0gqx`hc<60L2BLrtRnzuYp4FL2&4AICF*{20OZlQ-SXUm)uR9 z7QA_OuV?y?{H-m=(JLN-(&y1GFm?v7*nJ=K7`s}U4s$)c zdA6%(ybnT$&?`O<4Z@FtyZ@PSfv*IUpTNf#Fc#oH9${X=o9CwHIjo+?&VPy+L#|N_ zK{vuHev5O`PI&XIQ_oKSWdK{~74>{nE=oA#oYXv+!P z^}w6wgyuPBBtBrLvftJvffo6U4@0x<8i@gPFC#QNmtNj5^0{k3owMAq@6I$=s zaX#RqnB}e95ULBcdGv&7O~HY>#^uWjJbK8qreJ%l28*xUz=_m`D|`i>>tl9TE%q*6 z;a%wk3-qP2dW6x`yuP`*wl2h*etDhgnu4kZ|H=|Rw*6Zs*_l6 literal 0 HcmV?d00001 diff --git a/spm/nii_for_spm2/spm_vol.m b/spm/nii_for_spm2/spm_vol.m new file mode 100644 index 0000000..c85c0b1 --- /dev/null +++ b/spm/nii_for_spm2/spm_vol.m @@ -0,0 +1,179 @@ +function V = spm_vol(P) +% Get header information etc for images. +% FORMAT V = spm_vol(P) +% P - a matrix of filenames. +% V - a vector of structures containing image volume information. +% The elements of the structures are: +% V.fname - the filename of the image. +% V.dim - the x, y and z dimensions of the volume +% V.dt - A 1x2 array. First element is datatype (see spm_type). +% The second is 1 or 0 depending on the endian-ness. +% V.mat - a 4x4 affine transformation matrix mapping from +% voxel coordinates to real world coordinates. +% V.pinfo - plane info for each plane of the volume. +% V.pinfo(1,:) - scale for each plane +% V.pinfo(2,:) - offset for each plane +% The true voxel intensities of the jth image are given +% by: val*V.pinfo(1,j) + V.pinfo(2,j) +% V.pinfo(3,:) - offset into image (in bytes). +% If the size of pinfo is 3x1, then the volume is assumed +% to be contiguous and each plane has the same scalefactor +% and offset. +%____________________________________________________________________________ +% +% The fields listed above are essential for the mex routines, but other +% fields can also be incorporated into the structure. +% +% The images are not memory mapped at this step, but are mapped when +% the mex routines using the volume information are called. +% +% Note that spm_vol can also be applied to the filename(s) of 4-dim +% volumes. In that case, the elements of V will point to a series of 3-dim +% images. +% +% This is a replacement for the spm_map_vol and spm_unmap_vol stuff of +% MatLab4 SPMs (SPM94-97), which is now obsolete. +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_vol.m 982 2007-10-26 14:01:54Z john $ + +if nargin==0, + V = struct('fname', {},... + 'dim', {},... + 'dt', {},... + 'pinfo', {},... + 'mat', {},... + 'n', {},... + 'descrip', {},... + 'private',{}); + return; +end; + +% If is already a vol structure then just return; +if isstruct(P), V = P; return; end; + +V = subfunc2(P); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function V = subfunc2(P) +if iscell(P), + V = cell(size(P)); + for j=1:numel(P), + if iscell(P{j}), + V{j} = subfunc2(P{j}); + else + V{j} = subfunc1(P{j}); + end; + end; +else + V = subfunc1(P); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function V = subfunc1(P) +if isempty(P), + V = []; + return; +end; + +counter = 0; +for i=1:size(P,1), + v = subfunc(P(i,:)); + [V(counter+1:counter+size(v, 2),1).fname] = deal(''); + [V(counter+1:counter+size(v, 2),1).mat] = deal([0 0 0 0]); + [V(counter+1:counter+size(v, 2),1).mat] = deal(eye(4)); + [V(counter+1:counter+size(v, 2),1).mat] = deal([1 0 0]'); + if isempty(v), + hread_error_message(P(i,:)); + error(['Can''t get volume information for ''' P(i,:) '''']); + end + + f = fieldnames(v); + for j=1:size(f,1) + eval(['[V(counter+1:counter+size(v,2),1).' f{j} '] = deal(v.' f{j} ');']); + end + counter = counter + size(v,2); +end + +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function V = subfunc(p) +[pth,nam,ext,n1] = spm_fileparts(deblank(p)); +p = fullfile(pth,[nam ext]); +n = str2num(n1); +if ~exist(p,'file'), + existance_error_message(p); + error('File "%s" does not exist.', p); +end +switch ext, + case {'.nii','.NII'}, + % Do nothing + + case {'.img','.IMG'}, + if ~exist(fullfile(pth,[nam '.hdr']),'file') && ~exist(fullfile(pth,[nam '.HDR']),'file'), + existance_error_message(fullfile(pth,[nam '.hdr'])), + error('File "%s" does not exist.', fullfile(pth,[nam '.hdr'])); + end + + case {'.hdr','.HDR'}, + ext = '.img'; + p = fullfile(pth,[nam ext]); + if ~exist(p,'file'), + existance_error_message(p), + error('File "%s" does not exist.', p); + end + + otherwise, + error('File "%s" is not of a recognised type.', p); +end + +if isempty(n), + V = spm_vol_nifti(p); +else + V = spm_vol_nifti(p,n); +end; + + +if isempty(n) && length(V.private.dat.dim) > 3 + V0(1) = V; + for i = 2:V.private.dat.dim(4) + V0(i) = spm_vol_nifti(p, i); + end + V = V0; +end +%KND : SPM2 wants a 4th dim +for i=1:numel(V) + V(i).dim(4)=4; % +end + +if ~isempty(V), return; end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function hread_error_message(q) +str = {... + 'Error reading information on:',... + [' ',spm_str_manip(q,'k40d')],... + ' ',... + 'Please check that it is in the correct format.'}; +spm('alert*',str,mfilename,sqrt(-1)); +return; +%_______________________________________________________________________ +function existance_error_message(q) +str = {... + 'Unable to find file:',... + [' ',spm_str_manip(q,'k40d')],... + ' ',... + 'Please check that it exists.'}; +spm('alert*',str,mfilename,sqrt(-1)); +return; + diff --git a/spm/nii_for_spm2/spm_vol_check.m b/spm/nii_for_spm2/spm_vol_check.m new file mode 100755 index 0000000..d25175f --- /dev/null +++ b/spm/nii_for_spm2/spm_vol_check.m @@ -0,0 +1,72 @@ +function [samef, msg, chgf] = spm_vol_check(varargin) +% FORMAT [samef, msg, chgf] = spm_vol_check(V1, V2, ...) +% checks spm_vol structs are in same space +% +% V1, V2, etc - arrays of spm_vol structs +% +% samef - true if images have same dims, mats +% msg - cell array containing helpful message if not +% chgf - logical Nx2 array of difference flags +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% Matthew Brett +% $Id: spm_vol_check.m 184 2005-05-31 13:23:32Z john $ + + +[fnames samef msg] = deal({},1,{}); + +if nargin < 1, + return; +end; + +for i = 1:numel(varargin), + vols = varargin{i}; + if ~isempty(vols), + if i == 1, + dims = cat(3,vols(:).dim); + mats = cat(3,vols(:).mat); + else, + dims = cat(3,dims,vols(:).dim); + mats = cat(3,mats,vols(:).mat); + end; + fnames = {fnames{:}, vols(:).fname}; + end; +end; + +nimgs = size(dims, 3); +if nimgs < 2, + return; +end; + +labs = {'dimensions', 'orientation & voxel size'}; + +dimf = any(diff(dims(:,1:3,:),1,3)); +matf = any(any(diff(mats,1,3))); +chgf = logical([dimf(:) matf(:)]); +chgi = find(any(chgf, 2)); +if ~isempty(chgi), + samef = 0; + e1 = chgi(1); + msg = {['Images don''t all have the same ' ... + sepcat(labs(chgf(e1,:)),', ')],... + 'First difference between image pair:',... + fnames{e1},... + fnames{e1+1}}; +end; +return; + +function s = sepcat(strs, sep) +% returns cell array of strings as one char string, separated by sep +if nargin < 2, + sep = ';'; +end +if isempty(strs), + s = ''; + return; +end +strs = strs(:)'; +strs = [strs; repmat({sep}, 1, length(strs))]; +s = [strs{1:end-1}]; +return; + diff --git a/spm/nii_for_spm2/spm_vol_nifti.m b/spm/nii_for_spm2/spm_vol_nifti.m new file mode 100755 index 0000000..8290a66 --- /dev/null +++ b/spm/nii_for_spm2/spm_vol_nifti.m @@ -0,0 +1,39 @@ +function V = spm_vol_nifti(fname,n) +% Get header information for a NIFTI-1 image. +% FORMAT V = spm_vol_nifti(P) +% P - filename. +% n - volume id (a 1x2 array, e.g. [3,1]) +% V - a structure containing the image volume information. +%____________________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_vol_nifti.m 112 2005-05-04 18:20:52Z john $ + + +if nargin<2, n = [1 1]; end; +if ischar(n), n = str2num(n); end; +N = nifti(fname); +n = [n 1 1]; +n = n(1:2); +dm = [N.dat.dim 1 1 1 1]; +if any(n>dm(4:5)), V = []; return; end; + +dt = struct(N.dat); +dt = double([dt.dtype dt.be]); + +if isfield(N.extras,'mat') && size(N.extras.mat,3)>=n(1) && sum(sum(N.extras.mat(:,:,n(1))))~=0, + mat = N.extras.mat(:,:,n(1)); +else + mat = N.mat; +end; + +off = (n(1)-1+dm(4)*(n(2)-1))*ceil(spm_type(dt(1),'bits')*dm(1)*dm(2)/8)*dm(3) + N.dat.offset; +V = struct('fname', N.dat.fname,... + 'dim', dm(1:3),... + 'dt', dt,... + 'pinfo', [N.dat.scl_slope N.dat.scl_inter off]',... + 'mat', mat,... + 'n', n,... + 'descrip', N.descrip,... + 'private',N); diff --git a/spm/spm2/myspm_get_data_xyz.m b/spm/spm2/myspm_get_data_xyz.m new file mode 100644 index 0000000..caff5a7 --- /dev/null +++ b/spm/spm2/myspm_get_data_xyz.m @@ -0,0 +1,90 @@ +function [K,XYZvox,rXYZmm] = myspm_get_data_xyz(V,XYZmm,approx) +%MYSPM_GET_DATA_XYZ - gets data from image files at locations given in mm +% FORMAT [K,XYZvox,rXYZmm] = myspm_get_data(V,XYZmm,approx); +% +%INPUTS +% V: (cell) array of M filenames or volume structures from sspm_vol +% XYZmm: 3-by-N voxels locations to read in millimeters +% approx: Approximation mode. if approx==NaN (default) returns NaN for +% voxels out of the image else approximates see spm_sample_vol() +% +%OUPUTS +% K: M-by-N values read in the files +% XYZvox: 3-by-M-by-N matrix of voxels locations read in voxel space +% rXYZmm: 3-by-M-by-N matrix of actual coordinates of the voxels read +% +% Example +% >> spm_get_data_xyz(P,[45 -50 +50]) retrieves voxel intensity in +% the VMPFC of the MNI template... +% +% See also: spm_get_data + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-22 Creation +% +% ----------------------------- Script History --------------------------------- + +if ~isstruct(V) + V = spm_vol(V); + try + V = cat(2,V{:}); + end +end +if ~isequal(size(XYZmm,1),3) + error('XYZ input should be 3-by-N') +end +if nargin<3 + approx=NaN; +end +if isempty(approx) + approx=NaN; +end +if ~ischar(XYZmm) + + % number of voxels to retrieve + %--------------------------------------------------------------- + n=size(XYZmm,2); + % preallocate outputs + %--------------------------------------------------------------- + K = zeros( length(V),n); + XYZvox= zeros(3,length(V),n); + rXYZmm= zeros(3,length(V),n); + % expand approximation mode to match size of inputs + %--------------------------------------------------------------- + if prod(size(approx))==1 + approx=repmat(approx,length(V),1); + end + xyz = [XYZmm; ones(1,n)]; + xyz(isinf(xyz)) = 1e10*sign(xyz(isinf(xyz))); +else + switch (XYZmm) + case 'roi' + % To do: retrieve a region from a given atlas: + % aal:sup front gyrus:Right; + % brodmannn:4:Left etc. + end +end +for i = 1:length(V) + % trick from spm_XYZreg + vox = round(inv(V(i).mat)*xyz); + j = all(vox(1:3,:)<=repmat(V(i).dim(1:3)',1,n)) & all(vox(1:3,:)>zeros(3,n)); + if any(j) + %-Load mask image within current mask & update mask + %------------------------------------------------------- + K(i,j) = spm_sample_vol(V(i),vox(1,j),vox(2,j),vox(3,j),0); + end + if isnan(approx(i)) + K(i,~j)=NaN; + else + K(i,~j) = spm_sample_vol(V(i),vox(1,~j),vox(2,~j),vox(3,~j),approx(i)); + end + XYZvox(1:3,i,1:n) = vox(1:3,:); + rXYZmm(1:3,i,1:n) = V(i).mat(1:3,:)*xyz; +end diff --git a/spm/spm2/spm_P_RF.m b/spm/spm2/spm_P_RF.m new file mode 100644 index 0000000..289fc5c --- /dev/null +++ b/spm/spm2/spm_P_RF.m @@ -0,0 +1,188 @@ +function [P,p,Em,En,EN] = spm_P_RF(c,k,Z,df,STAT,R,n) +% Returns the [un]corrected P value using unifed EC theory +% FORMAT [P p Em En EN] = spm_P_RF(c,k,Z,df,STAT,R,n) +% +% c - cluster number +% k - extent {RESELS} +% Z - height {minimum over n values} +% df - [df{interest} df{error}] +% STAT - Statisical feild +% 'Z' - Gaussian feild +% 'T' - T - feild +% 'X' - Chi squared feild +% 'F' - F - feild +% R - RESEL Count {defining search volume} +% n - number of component SPMs in conjunction +% +% P - corrected P value - P(n > kmax} +% p - uncorrected P value - P(n > k} +% Em - expected total number of maxima {m} +% En - expected total number of resels per cluster {n} +% EN - expected total number of voxels {N} +% +%___________________________________________________________________________ +% +% spm_P_RF returns the probability of c or more clusters with more than +% k voxels in volume process of R RESELS thresholded at u. All p values +% can be considered special cases: +% +% spm_P_RF(1,0,Z,df,STAT,1,n) = uncorrected p value +% spm_P_RF(1,0,Z,df,STAT,R,n) = corrected p value {based on height Z) +% spm_P_RF(1,k,u,df,STAT,R,n) = corrected p value {based on extent k at u) +% spm_P_RF(c,k,u,df,STAT,R,n) = corrected p value {based on number c at k and u) +% spm_P_RF(c,0,u,df,STAT,R,n) = omnibus p value {based on number c at u) +% +% If n > 1 a conjunction probility over the n values of the statistic +% is returned +% +% Ref: Hasofer AM (1978) Upcrossings of random fields +% Suppl Adv Appl Prob 10:14-21 +% Ref: Friston et al (1993) Comparing functional images: Assessing +% the spatial extent of activation foci +% Ref: Worsley KJ et al 1996, Hum Brain Mapp. 4:58-73 +%___________________________________________________________________________ +% @(#)spm_P_RF.m 2.12 Karl Friston 02/10/16 + + +% get expectations +%=========================================================================== + +% get EC densities +%--------------------------------------------------------------------------- +D = max(find(R)); +R = R(1:D); +G = sqrt(pi)./gamma(([1:D])/2); +EC = spm_ECdensity(STAT,Z,df); +EC = EC([1:D]) + eps; + +% corrected p value +%--------------------------------------------------------------------------- +P = triu(toeplitz(EC'.*G))^n; +P = P(1,:); +EM = (R./G).*P; % over D dimensions +Em = sum(EM); % +EN = P(1)*R(D); % +En = EN/EM(D); % En = EN/EM(D); + +% get P{n > k} +%=========================================================================== + +% assume a Gaussian form for P{n > k} ~ exp(-beta*k^(2/D)) +% Appropriate for SPM{Z} and high d.f. SPM{T} +%--------------------------------------------------------------------------- +D = D - 1; +if isnan(k) || isnan(D) || ~k | ~D + + p = 1; + +elseif STAT == 'Z' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'T' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'X' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'F' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +end + +% Poisson clumping heuristic {for multiple clusters} +%=========================================================================== +P = 1 - spm_Pcdf(c - 1,(Em + eps)*p); + + +% set P and p = [] for non-implemented cases +%+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +if k > 0 & n > 1 + P = []; p = []; +end +if k > 0 & (STAT == 'X' | STAT == 'F') + P = []; p = []; +end +%+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + + + + +% spm_ECdensity +%=========================================================================== + +function [EC] = spm_ECdensity(STAT,t,df) +% Returns the EC density +%___________________________________________________________________________ +% +% Reference : Worsley KJ et al 1996, Hum Brain Mapp. 4:58-73 +% +%--------------------------------------------------------------------------- + +% EC densities (EC} +%--------------------------------------------------------------------------- +t = t(:)'; +if STAT == 'Z' + + % Gaussian Field + %------------------------------------------------------------------- + a = 4*log(2); + b = exp(-t.^2/2); + + EC(1,:) = 1 - spm_Ncdf(t); + EC(2,:) = a^(1/2)/(2*pi)*b; + EC(3,:) = a/((2*pi)^(3/2))*b.*t; + EC(4,:) = a^(3/2)/((2*pi)^2)*b.*(t.^2 - 1); + +elseif STAT == 'T' + + % T - Field + %------------------------------------------------------------------- + v = df(2); + a = 4*log(2); + b = exp(gammaln((v+1)/2) - gammaln(v/2)); + c = (1+t.^2/v).^((1-v)/2); + + EC(1,:) = 1 - spm_Tcdf(t,v); + EC(2,:) = a^(1/2)/(2*pi)*c; + EC(3,:) = a/((2*pi)^(3/2))*c.*t/((v/2)^(1/2))*b; + EC(4,:) = a^(3/2)/((2*pi)^2)*c.*((v-1)*(t.^2)/v - 1); + +elseif STAT == 'X' + + % X - Field + %------------------------------------------------------------------- + v = df(2); + a = (4*log(2))/(2*pi); + b = t.^(1/2*(v - 1)).*exp(-t/2-gammaln(v/2))/2^((v-2)/2); + + EC(1,:) = 1 - spm_Xcdf(t,v); + EC(2,:) = a^(1/2)*b; + EC(3,:) = a*b.*(t-(v-1)); + EC(4,:) = a^(3/2)*b.*(t.^2-(2*v-1)*t+(v-1)*(v-2)); + +elseif STAT == 'F' + + % F Field + %------------------------------------------------------------------- + k = df(1); + v = df(2); + a = (4*log(2))/(2*pi); + b = gammaln(v/2) + gammaln(k/2); + + EC(1,:) = 1 - spm_Fcdf(t,df); + EC(2,:) = a^(1/2)*exp(gammaln((v+k-1)/2)-b)*2^(1/2)... + *(k*t/v).^(1/2*(k-1)).*(1+k*t/v).^(-1/2*(v+k-2)); + EC(3,:) = a*exp(gammaln((v+k-2)/2)-b)*(k*t/v).^(1/2*(k-2))... + .*(1+k*t/v).^(-1/2*(v+k-2)).*((v-1)*k*t/v-(k-1)); + EC(4,:) = a^(3/2)*exp(gammaln((v+k-3)/2)-b)... + *2^(-1/2)*(k*t/v).^(1/2*(k-3)).*(1+k*t/v).^(-1/2*(v+k-2))... + .*((v-1)*(v-2)*(k*t/v).^2-(2*v*k-v-k-1)*(k*t/v)+(k-1)*(k-2)); +end diff --git a/spm/spm2/spm_create_vol.m b/spm/spm2/spm_create_vol.m new file mode 100644 index 0000000..8b960a9 --- /dev/null +++ b/spm/spm2/spm_create_vol.m @@ -0,0 +1,363 @@ +function V = spm_create_vol(V,varargin) +% Create an image file. +% FORMAT Vo = spm_create_vol(Vi,['noopen']) +% Vi - data structure containing image information. +% - see spm_vol for a description. +% 'noopen' - optional flag to say "don't open/create the image file". +% Vo - data structure after modification for writing. +%_______________________________________________________________________ +% @(#)spm_create_vol.m 2.14 John Ashburner 03/07/31 +for i=1:prod(size(V)), + if nargin>1, + v = create_vol(V(i),varargin{:}); + else, + v = create_vol(V(i)); + end; + f = fieldnames(v); + for j=1:size(f,1), + %eval(['V(i).' f{j} ' = v.' f{j} ';']); + V = setfield(V,{i},f{j},getfield(v,f{j})); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function V = create_vol(V,varargin) +if ~isfield(V,'n') | isempty(V.n), V.n = 1; end; +if ~isfield(V,'descrip') | isempty(V.descrip), V.descrip = 'SPM2 compatible'; end; +V.private = struct('hdr',[]); + +% Orientation etc... +M = V.mat; +if spm_flip_analyze_images, M = diag([-1 1 1 1])*M; end; +vx = sqrt(sum(M(1:3,1:3).^2)); +if det(M(1:3,1:3))<0, vx(1) = -vx(1); end; +origin = M\[0 0 0 1]'; +origin = round(origin(1:3)); + +[pth,nam,ext] = fileparts(V.fname); +fname = fullfile(pth,[nam, '.hdr']); +try, + [hdr,swapped] = spm_read_hdr(fname); +catch, + warning(['Could not read "' fname '"']); + swapped = 0; + hdr = []; +end; + +if ~isempty(hdr) & (hdr.dime.dim(5)>1 | V.n>1), + % cannot simply overwrite the header + + hdr.dime.dim(5) = max(V.n,hdr.dime.dim(5)); + if any(V.dim(1:3) ~= hdr.dime.dim(2:4)) + error('Incompatible image dimensions'); + end; + + if sum((vx-hdr.dime.pixdim(2:4)).^2)>1e-6, + error('Incompatible voxel sizes'); + end; + + V.dim(4) = spm_type(spm_type(hdr.dime.datatype)); + mach = 'native'; + if swapped, + V.dim(4) = V.dim(4)*256; + if spm_platform('bigend'), + mach = 'ieee-le'; + else, + mach = 'ieee-be'; + end; + end; + + if finite(hdr.dime.funused1) & hdr.dime.funused1, + scal = hdr.dime.funused1; + if finite(hdr.dime.funused2), + dcoff = hdr.dime.funused2; + else, + dcoff = 0; + end; + else + if hdr.dime.glmax-hdr.dime.glmin & hdr.dime.cal_max-hdr.dime.cal_min, + scal = (hdr.dime.cal_max-hdr.dime.cal_min)/(hdr.dime.glmax-hdr.dime.glmin); + dcoff = hdr.dime.cal_min - scal*hdr.dime.glmin; + else, + scal = 1; + dcoff = 0; + warning(['Assuming a scalefactor of 1 for "' V.fname '".']); + end; + end; + V.pinfo(1:2) = [scal dcoff]'; + V.private.hdr = hdr; +else, + + V.private.hdr = create_defaults; + + swapped = spm_type(V.dim(4),'swapped'); + dt = spm_type(spm_type(V.dim(4))); + if any(dt == [128+2 128+4 128+8]), + % Convert to a form that Analyze will support + dt = dt - 128; + end; + V.dim(4) = dt; + mach = 'native'; + if isnan(swapped) + warning('Big/Little endian issue unsolved!'); + elseif swapped, + V.dim(4) = V.dim(4)*256; + if spm_platform('bigend'), + mach = 'ieee-le'; + else, + mach = 'ieee-be'; + end; + end; + V.private.hdr.dime.datatype = dt; + V.private.hdr.dime.bitpix = spm_type(dt,'bits'); + + if spm_type(dt,'intt'), + + V.private.hdr.dime.glmax = spm_type(dt,'maxval'); + V.private.hdr.dime.glmin = spm_type(dt,'minval'); + + if 0, % Allow DC offset + V.private.hdr.dime.cal_max = max(V.private.hdr.dime.glmax*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.cal_min = min(V.private.hdr.dime.glmin*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.funused1 = 0; + scal = (V.private.hdr.dime.cal_max - V.private.hdr.dime.cal_min)/... + (V.private.hdr.dime.glmax - V.private.hdr.dime.glmin); + dcoff = V.private.hdr.dime.cal_min - V.private.hdr.dime.glmin*scal; + V.pinfo = [scal dcoff 0]'; + else, % Don't allow DC offset + cal_max = max(V.private.hdr.dime.glmax*V.pinfo(1,:) + V.pinfo(2,:)); + cal_min = min(V.private.hdr.dime.glmin*V.pinfo(1,:) + V.pinfo(2,:)); + V.private.hdr.dime.funused1 = cal_max/V.private.hdr.dime.glmax; + if V.private.hdr.dime.glmin, + V.private.hdr.dime.funused1 = max(V.private.hdr.dime.funused1,... + cal_min/V.private.hdr.dime.glmin); + end; + V.private.hdr.dime.cal_max = V.private.hdr.dime.glmax*V.private.hdr.dime.funused1; + V.private.hdr.dime.cal_min = V.private.hdr.dime.glmin*V.private.hdr.dime.funused1; + V.pinfo = [V.private.hdr.dime.funused1 0 0]'; + end; + else, + V.private.hdr.dime.glmax = 1; + V.private.hdr.dime.glmin = 0; + V.private.hdr.dime.cal_max = 1; + V.private.hdr.dime.cal_min = 0; + V.private.hdr.dime.funused1 = 1; + end; + + V.private.hdr.dime.pixdim(2:4) = vx; + V.private.hdr.dime.dim(2:4) = V.dim(1:3); + V.private.hdr.dime.dim(5) = V.n; + V.private.hdr.hist.origin(1:3) = origin; + + d = 1:min([length(V.descrip) 79]); + V.private.hdr.hist.descrip = char(zeros(1,80)); + V.private.hdr.hist.descrip(d) = V.descrip(d); + V.private.hdr.hk.db_name = char(zeros(1,18)); + [pth,nam,ext] = fileparts(V.fname); + d = 1:min([length(nam) 17]); + V.private.hdr.hk.db_name(d) = nam(d); +end; + +V.pinfo(3) = prod(V.private.hdr.dime.dim(2:4))*V.private.hdr.dime.bitpix/8*(V.n-1); + +fid = fopen(fname,'w',mach); +if (fid == -1), + error(['Error opening ' fname '. Check that you have write permission.']); +end; + +write_hk(fid,V.private.hdr.hk); +write_dime(fid,V.private.hdr.dime); +write_hist(fid,V.private.hdr.hist); +fclose(fid); + +fname = fullfile(pth,[nam, '.mat']); +off = -vx'.*origin; +mt = [vx(1) 0 0 off(1) ; 0 vx(2) 0 off(2) ; 0 0 vx(3) off(3) ; 0 0 0 1]; +if spm_flip_analyze_images, mt = diag([-1 1 1 1])*mt; end; + +if sum((V.mat(:) - mt(:)).*(V.mat(:) - mt(:))) > eps*eps*12 | exist(fname)==2, + if exist(fname)==2, + clear mat + str = load(fname); + if isfield(str,'mat'), + mat = str.mat; + elseif isfield(str,'M'), + mat = str.M; + if spm_flip_analyze_images, + for i=1:size(mat,3), + mat(:,:,i) = diag([-1 1 1 1])*mat(:,:,i); + end; + end; + end; + mat(:,:,V.n) = V.mat; + mat = fill_empty(mat,mt); + M = mat(:,:,1); if spm_flip_analyze_images, M = diag([-1 1 1 1])*M; end; + try, + save(fname,'mat','M','-append'); + catch, % Mat-file was probably Matlab 4 + save(fname,'mat','M'); + end; + else, + clear mat + mat(:,:,V.n) = V.mat; + mat = fill_empty(mat,mt); + M = mat(:,:,1); if spm_flip_analyze_images, M = diag([-1 1 1 1])*M; end; + save(fname,'mat','M'); + end; +end; + +if nargin==1 | ~strcmp(varargin{1},'noopen'), + fname = fullfile(pth,[nam, '.img']); + V.private.fid = fopen(fname,'r+',mach); + if (V.private.fid == -1), + V.private.fid = fopen(fname,'w',mach); + if (V.private.fid == -1), + error(['Error opening ' fname '. Check that you have write permission.']); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function Mo = fill_empty(Mo,Mfill) +todo = []; +for i=1:size(Mo,3), + if ~any(any(Mo(:,:,i))), + todo = [todo i]; + end; +end; +if ~isempty(todo), + for i=1:length(todo), + Mo(:,:,todo(i)) = Mfill; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function write_hk(fid,hk) +% write (struct) header_key +%----------------------------------------------------------------------- +fseek(fid,0,'bof'); +fwrite(fid,hk.sizeof_hdr, 'int32'); +fwrite(fid,hk.data_type, 'char' ); +fwrite(fid,hk.db_name, 'char' ); +fwrite(fid,hk.extents, 'int32'); +fwrite(fid,hk.session_error,'int16'); +fwrite(fid,hk.regular, 'char' ); +if fwrite(fid,hk.hkey_un0, 'char' )~= 1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function write_dime(fid,dime) +% write (struct) image_dimension +%----------------------------------------------------------------------- +fseek(fid,40,'bof'); +fwrite(fid,dime.dim, 'int16'); +fwrite(fid,dime.vox_units, 'uchar' ); +fwrite(fid,dime.cal_units, 'uchar' ); +fwrite(fid,dime.unused1, 'int16' ); +fwrite(fid,dime.datatype, 'int16'); +fwrite(fid,dime.bitpix, 'int16'); +fwrite(fid,dime.dim_un0, 'int16'); +fwrite(fid,dime.pixdim, 'float'); +fwrite(fid,dime.vox_offset, 'float'); +fwrite(fid,dime.funused1, 'float'); +fwrite(fid,dime.funused2, 'float'); +fwrite(fid,dime.funused2, 'float'); +fwrite(fid,dime.cal_max, 'float'); +fwrite(fid,dime.cal_min, 'float'); +fwrite(fid,dime.compressed, 'int32'); +fwrite(fid,dime.verified, 'int32'); +fwrite(fid,dime.glmax, 'int32'); +if fwrite(fid,dime.glmin, 'int32')~=1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function write_hist(fid,hist) +% write (struct) data_history +%----------------------------------------------------------------------- +fseek(fid,148,'bof'); +fwrite(fid,hist.descrip, 'uchar'); +fwrite(fid,hist.aux_file, 'uchar'); +fwrite(fid,hist.orient, 'uchar'); +fwrite(fid,hist.origin, 'int16'); +fwrite(fid,hist.generated, 'uchar'); +fwrite(fid,hist.scannum, 'uchar'); +fwrite(fid,hist.patient_id, 'uchar'); +fwrite(fid,hist.exp_date, 'uchar'); +fwrite(fid,hist.exp_time, 'uchar'); +fwrite(fid,hist.hist_un0, 'uchar'); +fwrite(fid,hist.views, 'int32'); +fwrite(fid,hist.vols_added, 'int32'); +fwrite(fid,hist.start_field,'int32'); +fwrite(fid,hist.field_skip, 'int32'); +fwrite(fid,hist.omax, 'int32'); +fwrite(fid,hist.omin, 'int32'); +fwrite(fid,hist.smax, 'int32'); +if fwrite(fid,hist.smin, 'int32')~=1, + error(['Error writing ' fopen(fid) '. Check your disk space.']); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function hdr = create_defaults +hk.sizeof_hdr = 348; +hk.data_type = ['dsr ' 0]; +hk.db_name = char(zeros(1,18)); +hk.extents = 0; +hk.session_error= 0; +hk.regular = 'r'; +hk.hkey_un0 = 0; + +dime.dim = [4 0 0 0 1 0 0 0]; +dime.vox_units = ['mm ' 0]; +dime.cal_units = char(zeros(1,8)); +dime.unused1 = 0; +dime.datatype = -1; +dime.bitpix = 0; +dime.dim_un0 = 0; +dime.pixdim = [0 1 1 1 1 0 0 0]; +dime.vox_offset = 0; +dime.funused1 = 1; +dime.funused2 = 0; +dime.funused3 = 0; +dime.cal_max = 1; +dime.cal_min = 0; +dime.compressed = 0; +dime.verified = 0; +dime.glmax = 1; +dime.glmin = 0; + +hist.descrip = char(zeros(1,80)); +hist.descrip(1:length('SPM2 compatible')) = 'SPM2 compatible'; +hist.aux_file = char(zeros(1,24)); +hist.orient = char(0); +hist.origin = [0 0 0 0 0]; +hist.generated = char(zeros(1,10)); +hist.scannum = char(zeros(1,10)); +hist.patient_id = char(zeros(1,10)); +hist.exp_date = char(zeros(1,10)); +hist.exp_time = char(zeros(1,10)); +hist.hist_un0 = char(zeros(1,3)); +hist.generated(1:5) = 'today'; +hist.views = 0; +hist.vols_added = 0; +hist.start_field= 0; +hist.field_skip = 0; +hist.omax = 0; +hist.omin = 0; +hist.smax = 0; +hist.smin = 0; + +hdr.hk = hk; +hdr.dime = dime; +hdr.hist = hist; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ + diff --git a/spm/spm2/spm_dcm_display.m b/spm/spm2/spm_dcm_display.m new file mode 100644 index 0000000..52ecd5e --- /dev/null +++ b/spm/spm2/spm_dcm_display.m @@ -0,0 +1,266 @@ +function spm_dcm_display(varargin) +% region and anatomical graph display +% FORMAT spm_dcm_display(xY,a,c,u,M,U,img) +% xY - cell of region structures (see spm_regions) +% a - connections of directed graph a(i,j,1) = p value +% c - node-specific inputs +% u - (3 x 2) projection matrix [default = [] ] +% M - margin (mm) [default = 24 ] +% U - theshold for plotting connections [default = 0.9] +% beta - image contrast ( 0 < beta < 1 ) +% img - image to plot on +% markerstyle - Marker size +% markerstyle2 - Marker style +%___________________________________________________________________________ +% @(#)spm_dcm_display.m 2.5 Karl Friston 02/10/29 + + +% null input arguments +%--------------------------------------------------------------------------- +% Fgraph = spm_figure('GetWin','Graphics'); +n = length(varargin); + +if n < 1; xY = []; else, xY = varargin{1}; end +if n < 2; a = []; else, a = varargin{2}; end +if n < 3; c = []; else, c = varargin{3}; end +if n < 4; u = []; else, u = varargin{4}; end +if n < 5; M = 16; else, M = varargin{5}; end +if n < 6; U = .9; else, U = varargin{6}; end +if n < 7; beta=.24; else, beta = varargin{7}; end +if n < 8; img = []; else, img=varargin{8}; end +if isempty(img) + fullfile(spm('Dir'),'canonical','single_subj_T1.mnc'); +end +markerstyle = {'MarkerSize',64,'Marker', '.'}; +if n >= 9; markerstyle=[markerstyle varargin{9}]; end +markerstyle2 = {'MarkerSize',4,'Marker', '.'}; +if n >= 10; markerstyle2=[markerstyle2 varargin{10}]; end +if n < 11; imgori='sa'; else imgori=varargin{11}; end + +col = [0 0 0]; +rad = 6; +w = 2; + +% enforce orientation for 1 or 2 regions +%--------------------------------------------------------------------------- +if length(xY) < 3 + switch imgori + case 'ax' + u = [[1 0 0];[0 1 0]]'; + case 'sa' + u = [[0 1 0];[0 0 1]]'; + case 'co' + u = [[1 0 0];[0 0 1]]'; + end +end + +% get dimensions +%--------------------------------------------------------------------------- +m = size(xY,2); +L = []; +for i = 1:m + L = [L xY(i).xyz]; + name{i} = xY(i).name; +end +L = [L; ones(1,m)]; +o = mean(L,2); +M1 = spm_matrix(-o(1:3)'); + +% compute projection matrix for 'principal' plane +%--------------------------------------------------------------------------- +if ~length(u) + [u s v] = svd(M1*L); + u = u(:,[2 1]); + [i j] = max(abs(u)); + u = u*diag(sign([u(j(1),1) u(j(2),2)])); +end +M2 = u'; +M2(4,4) = 1; +L = M2*M1*L; + +% coordinates +%--------------------------------------------------------------------------- +i = (min(L(1,:)) - M):(max(L(1,:)) + M); +j = (min(L(2,:)) - M):(max(L(2,:)) + M); +x = kron(ones(size(j)),i); +y = kron(j,ones(size(i))); +xyz = [x; y; zeros(1,length(x)); ones(1,length(x))]; +xyz = pinv(M1)*pinv(M2)*xyz; +M3 = [1 0 0 -min(i); 0 -1 0 -min(j); 0 0 0 0; 0 0 0 1]; +L = M3*L; + + +% get T1 background +%--------------------------------------------------------------------------- +if ~exist(img, 'file') + img = fullfile(spm('Dir'),'canonical','single_subj_T1.mnc'); +end +try + V = spm_vol(img); +catch + V = spm_vol('mask.img'); +end +ijk = inv(V.mat)*xyz; +t1 = spm_sample_vol(V,ijk(1,:),ijk(2,:),ijk(3,:),2); +t1 = size(colormap,1)*((1 - beta) + beta*t1/max(t1(:))); + + +% Watermark and regions +%--------------------------------------------------------------------------- +str = get(get(gca,'Title'),'String'); +image(rot90(reshape(t1,length(i),length(j)))) +axis image off +title(str) + + +% Connections +%--------------------------------------------------------------------------- +Q = [-pi:pi/32:pi]; +Q = rad*[sin(Q); cos(Q)]; +x = mean(L(1,:)); +y = mean(L(2,:)); +q = 1/3; +for i = 1:length(a) + for j = 1:length(a) + if ~isnan(a(i,j,1)) + + % show connection + %----------------------------------------------------------- + if i ~= j + + % line + %--------------------------------------------------- + h = line(L(1,[i j]),L(2,[i j]),... + 'Color',col,... + 'LineStyle',':',... + 'LineWidth',w); + + % if significant + %--------------------------------------------------- + if a(i,j,1) > U + set(h,'LineStyle','-','LineWidth',w) + + % text + %------------------------------------------- + u = q*(L(1,j) - L(1,i)) + L(1,i); + v = q*(L(2,j) - L(2,i)) + L(2,i);; + str = {}; + for k = 1:size(a,3) + str{k} = sprintf('%0.2f ',a(i,j,k)); + end + h = text(u,v,1,str(:),'FontSize',10,... + 'HorizontalAlignment','Center'); + if a(i,j,2) < 0 + set(h, 'Color','r') + end + end + + % self connection + %----------------------------------------------------------- + else + + % line + %--------------------------------------------------- + u = (L(1,i) - x); + v = (L(2,i) - y); + l = sqrt(u^2 + v^2); + l = (l + rad)/l; + u = Q(1,:) + x + l*u; + v = Q(2,:) + y + l*v; + h = line(u,v,... + 'Color',col,... + 'LineStyle',':',... + 'LineWidth',w); + + % if significant + %--------------------------------------------------- + if a(i,j,1) > U + set(h,'LineStyle','-','LineWidth',w) + + % text + %------------------------------------------- + u = u(48); + v = v(48); + str = {}; + for k = 1:size(a,3) + str{k} = sprintf('%0.2f ',a(i,j,k)); + end + h = text(u,v,1,str(:),'FontSize',10,... + 'HorizontalAlignment','Center'); + if a(i,j,2) < 0 + set(h, 'Color','r') + end + end + end + end + end +end + +% Extrinsic influences +%--------------------------------------------------------------------------- +for i = 1:size(c,1) + if ~isnan(c(i,1)) + + % line + %----------------------------------------------------------- + u = (L(1,i) - x); + v = (L(2,i) - y); + l = sqrt(u^2 + v^2); + l = (l + rad)/l; + u = [u l*u] + x; + v = [v l*v] + y; + h = line(u,v,... + 'Color',col,... + 'LineStyle',':',... + 'LineWidth',w); + + % if significant + %---------------------------------------------------------- + if c(i,1) > U + set(h,'LineStyle','-','LineWidth',w) + + % patch + %-------------------------------------------------- + u = u(2); + v = v(2); + + % text + %-------------------------------------------------- + str = {}; + for k = 1:size(c,2) + str{k} = sprintf('%0.2f ',c(i,k)); + end + h = text(u,v,str(:),'FontSize',10,... + 'HorizontalAlignment','Center'); + if c(i,2) < 0 + set(h, 'Color','r') + end + + end + end +end + + +% projected coordinates of voxels within region[s] +%--------------------------------------------------------------------------- +hold on +for i = 1:m + l = xY(i).XYZmm; + n = size(l,2); + l = [l; ones(1,n)]; + l = M3*M2*M1*l; + plot(l(1,:),l(2,:),'.r',markerstyle2{:}) +end + +line(L(1,:),L(2,:),... + 'Color',[0 0 0],... + 'Marker','.',... + 'LineStyle','none',... + markerstyle{:}); + +text(L(1,:),L(2,:),name,'FontSize',8,... + 'FontWeight','Bold',... + 'Color','w',... + 'HorizontalAlignment','center',... + 'FontAngle','italic') +hold off diff --git a/spm/spm2/spm_defaults.m b/spm/spm2/spm_defaults.m new file mode 100644 index 0000000..0b3b75d --- /dev/null +++ b/spm/spm2/spm_defaults.m @@ -0,0 +1,126 @@ + +% Sets the defaults which are used by SPM +% +% FORMAT spm_defaults +%_______________________________________________________________________ +% +% This file is intended to be customised for the site. +% Individual users can make copies which can be stored in their own +% matlab subdirectories. If ~/matlab is ahead of the SPM directory +% in the MATLABPATH, then the users own personal defaults are used. +% +% Care must be taken when modifying this file +%_______________________________________________________________________ +% @(#)spm_defaults.m 2.23 John Ashburner, Andrew Holmes 03/04/16 + +global defaults + +% Misc +%======================================================================= +defaults.grid = 0.4; +defaults.cmdline = 0; +defaults.logfile = ''; +defaults.printstr = [];%spm_figure('DefPrintCmd'),'spm2.ps']; + +% File format specific +%======================================================================= +defaults.analyze.multivol = 0; +defaults.analyze.flip = 1; % <<= Very important. Relates to L/R +% Changed by KND: +% defaults.analyze.flip = 0; % <<= Very important. Relates to L/R +% but now in the CMU it's 1... + +% Stats defaults +%======================================================================= +defaults.stats.maxmem = 2^20; +defaults.stats.maxres = 64; +defaults.stats.fmri.ufp = 0.001; +defaults.stats.fmri.t = 16; +defaults.stats.fmri.t0 = 8; +defaults.stats.pet.ufp = 0.05; + +defaults.stats.fmri.t0 = 1; + +defaults.modality = 'FMRI'; + + +% Mask defaults +%======================================================================= +defaults.mask.thresh = 0.8; + +% Realignment defaults +%======================================================================= +defaults.realign.estimate.quality = 0.75; +defaults.realign.estimate.weight = 0; +defaults.realign.estimate.interp = 2; +defaults.realign.estimate.wrap = [0 0 0]; +defaults.realign.write.mask = 1; +defaults.realign.write.interp = 4; +defaults.realign.write.wrap = [0 0 0]; + +% Unwarp defaults +%======================================================================= +defaults.unwarp.estimate.fwhm = 4; +defaults.unwarp.estimate.basfcn = [10 10]; +defaults.unwarp.estimate.regorder= 1; +defaults.unwarp.estimate.regwgt = 1e5; +defaults.unwarp.estimate.soe = 1; +defaults.unwarp.estimate.rem = 1; +defaults.unwarp.estimate.jm = 0; +defaults.unwarp.estimate.noi = 5; +defaults.unwarp.estimate.expround= 'Average'; +% +% Unwarp uses defaults.realign.write +% defaults for writing. +% + +% Coregistration defaults +%======================================================================= +defaults.coreg.estimate.cost_fun = 'nmi'; +defaults.coreg.estimate.sep = [4 2]; +defaults.coreg.estimate.tol = [0.02 0.02 0.02 0.001 0.001 0.001 0.01 0.01 0.01 0.001 0.001 0.001]; +defaults.coreg.estimate.fwhm = [7 7]; +defaults.coreg.write.interp = 1; +defaults.coreg.write.wrap = [0 0 0]; +defaults.coreg.write.mask = 0; + +% Spatial Normalisation defaults +%======================================================================= +defaults.normalise.estimate.smosrc = 8; +defaults.normalise.estimate.smoref = 0; +defaults.normalise.estimate.regtype = 'mni'; +defaults.normalise.estimate.weight = ''; +defaults.normalise.estimate.cutoff = 25; +defaults.normalise.estimate.nits = 16; +defaults.normalise.estimate.reg = 1; +defaults.normalise.estimate.wtsrc = 0; +defaults.normalise.write.preserve = 0; +defaults.normalise.write.bb = [[-78 -112 -50];[78 76 85]]; +%defaults.normalise.write.vox = [2 2 2]; +defaults.normalise.write.vox = [3 3 3]; +defaults.normalise.write.interp = 1; +defaults.normalise.write.wrap = [0 0 0]; + +% Segmentation defaults +%======================================================================= +defaults.segment.estimate.priors = str2mat(... + fullfile(spm('Dir'),'apriori','gray.mnc'),... + fullfile(spm('Dir'),'apriori','white.mnc'),... + fullfile(spm('Dir'),'apriori','csf.mnc')); +defaults.segment.estimate.reg = 0.01; +defaults.segment.estimate.cutoff = 30; +defaults.segment.estimate.samp = 3; +defaults.segment.estimate.bb = [[-88 88]' [-122 86]' [-60 95]']; +defaults.segment.estimate.affreg.smosrc = 8; +defaults.segment.estimate.affreg.regtype = 'mni'; +%defaults.segment.estimate.affreg.weight = fullfile(spm('Dir'),'apriori','brainmask.mnc'); +defaults.segment.estimate.affreg.weight = ''; +defaults.segment.write.cleanup = 1; +defaults.segment.write.wrt_cor = 1; + +% Bias field estimation defaults +%======================================================================= +defaults.bias.nbins = 256; % Number of histogram bins +defaults.bias.reg = 0.01; % Regularisation +defaults.bias.cutoff = 30; % DCT frequency cutoff (mm) + diff --git a/spm/spm2/spm_figure.m b/spm/spm2/spm_figure.m new file mode 100644 index 0000000..34753b4 --- /dev/null +++ b/spm/spm2/spm_figure.m @@ -0,0 +1,875 @@ +function varargout=spm_figure(varargin) +% Setup and callback functions for Graphics window +% FORMAT varargout=spm_figure(varargin) +% - An embedded callback, multi-function function +% - For detailed programmers comments, see format specifications +% in main body of code +%_______________________________________________________________________ +% +% spm_figure creates and manages the 'Graphics' window. This window and +% these facilities may be used independently of SPM, and any number of +% Graphics windows my be used within the same MatLab session. (Though +% only one SPM 'Graphics' 'Tag'ed window is permitted. +% +% The Graphics window is provided with a menu bar at the top that +% facilitates editing and printing of the current graphic display, +% enabling interactive editing of graphic output prior to printing +% (e.g. selection of color maps, deleting, moving and editing graphics +% objects or adding text). (This menu is also provided as a figure +% background "ContextMenu" - right-clicking on the figure background +% should bring up the menu.) +% +% Print: Creates a footnote (detailing the SPM version, user & date) +% and evaluates defaults.printstr (see spm_defaults.m). Graphics windows with +% multi-page axes are printed page by page. +% +% Clear: Clears the Graphics window. If in SPM usage (figure 'Tag'ed as +% 'Graphics') then all SPM windows are cleared and reset. +% +% Colormap options: +% * gray, hot, pink: Sets the colormap to its default values and loads +% either a grayscale, 'hot metal' or color map. +% * gray-hot, etc: Creates a 'split' colormap {128 x 3 matrix}. +% The lower half is a gray scale and the upper half +% is 'hot metal' or 'pink'. This color map is used for +% viewing 'rendered' SPMs on a PET, MRI or other background images +% +% Colormap effects: +% * Invert: Inverts (flips) the current color map. +% * Brighten and Darken: Brighten and Darken the current colourmap +% using the MatLab BRIGHTEN command, with beta's of +0.2 and -0.2 +% respectively. +% +% Editing: Right button ('alt' button) cancels operations +% * Cut : Deletes the graphics object next selected (if deletable) +% Select with middle mouse button to delete blocks of text, +% or to delete individual elements from a plot. +% * Move : To re-position a text, uicontrol or axis object using a +% 'drag and drop' implementation (i.e. depress - move - release) +% Using the middle 'extend' mouse button on a text object moves +% the axes containing the text - i.e. blocks of text. +% * Size : Re-sizes the text, uicontrol or axis object next selected +% {left button - decrease, middle button - increase} by a factor +% of 1.24 (or increase/decrease FontSize by 2 dpi) +% * Text : Creates an editable text widget that produces a text object as +% its CallBack. +% The text object is provided with a ContextMenu, obtained by +% right-clicking ('alt') on the text, allowing text attributes +% to be changed. Alternatively, the edit facilities on the window +% menu bar or ContextMenu can be used. +% * Edit : To edit text, select a text object with the circle cursor, +% and edit the text in the editable text widget that appears. +% A middle 'extend' mouse click places a context menu on the text +% object, facilitating easy modification of text atributes. +% +% For SPM usage, the figure should be 'Tag'ed as 'Graphics'. +% +% For SPM power users, and programmers, spm_figure provides utility +% routines for using the SPM graphics interface. Of particular use are +% the GetWin, FindWin and Clear functions See the embedded callback +% reference in the main body of spm_figure, below the help text. +% +% See also: spm_print, spm_clf +% +%_______________________________________________________________________ +% @(#)spm_figure.m 2.39 Andrew Holmes 03/05/16 + +%======================================================================= +% - FORMAT specifications for embedded CallBack functions +%======================================================================= +%( This is a multi function function, the first argument is an action ) +%( string, specifying the particular action function to take. Recall ) +%( MatLab's command-function duality: `spm_figure Create` is ) +%( equivalent to `spm_figure('Create')`. ) +% +% FORMAT F = spm_figure +% [ShortCut] Defaults to Action 'Create' +% +% FORMAT F = spm_figure(F) - numeric F +% [ShortCut] Defaults to spm_figure('CreateBar',F) +% +% FORMAT F = spm_figure('Create',Tag,Name,Visible) +% Create a full length WhiteBg figure 'Tag'ed Tag (if specified), +% with a ToolBar and background context menu. +% Equivalent to spm_figure('CreateWin','Tag') and spm_figure('CreateBar') +% Tag - 'Tag' string for figure. +% Name - Name for window +% Visible - 'on' or 'off' +% F - Figure used +% +% FORMAT F = spm_figure('FindWin',F) +% Finds window with 'Tag' or figure numnber F - returns empty F if not found +% F - (Input) Figure to use [Optional] - 'Tag' string or figure number. +% - Defaults to 'Graphics' +% F - (Output) Figure number (if found) or empty (if not). +% +% FORMAT F = spm_figure('GetWin',Tag) +% Like spm_figure('FindWin',Tag), except that if 'Tag' is 'Graphics' or +% 'Interactive' and no such 'Tag'ged figure is found, one is created. Further, +% the "got" window is made current. +% Tag - Figure 'Tag' to get, defaults to 'Graphics' +% F - Figure number (if found/created) or empty (if not). +% +% FORMAT F = spm_figure('ParentFig',h) +% Finds window containing the object whose handle is specified +% h - Handle of object whose parent figure is required +% - If a vector, then first object handle is used +% F - Number or parent figure +% +% FORMAT spm_figure('Clear',F,Tags) +% Clears figure, leaving ToolBar (& other objects with invisible handles) +% Optional third argument specifies 'Tag's of objects to delete. +% If figure F is 'Tag'ged 'Interactive' (SPM usage), then the window +% name and pointer are reset. +% F - 'Tag' string or figure number of figure to clear, defaults to gcf +% Tags - 'Tag's (string matrix or cell array of strings) of objects to delete +% *regardless* of 'HandleVisibility'. Only these objects are deleted. +% '!all' denotes all objects +% +% FORMAT str = spm_figure('DefPrintCmd') +% Returns default print command for SPM, as a string +% +% FORMAT spm_figure('Print',F) +% SPM print function: Appends footnote & executes PRINTSTR +% F - [Optional] Figure to print. ('Tag' or figure number) +% Defaults to figure 'Tag'ed as 'Graphics'. +% If none found, uses CurrentFigure if avaliable. +% defaults.printstr - global variable holding print command to be evaluated +% Defaults to 'print -dps2 fig.ps' +% If objects 'Tag'ed 'NextPage' and 'PrevPage' are found, then the +% pages are shown and printed in order. In breif, pages are held as +% seperate axes, with ony one 'Visible' at any one time. The handles of +% the "page" axes are stored in the 'UserData' of the 'NextPage' +% object, while the 'PrevPage' object holds the current page number. +% See spm_help('!Disp') for details on setting up paging axes. +% +% FORMAT [hNextPage, hPrevPage, hPageNo] = spm_figure('NewPage',hPage) +% SPM pagination function: Makes objects with handles hPage paginated +% Creates pagination buttons if necessary. +% hPage - Handles of objects to stick to this page +% hNextPage, hPrevPage, hPageNo - Handles of pagination controls +% +% FORMAT spm_figure('TurnPage',move,F) +% SPM pagination function: Turn to specified page +% +% FORMAT spm_figure('DeletePageControls',F) +% SPM pagination function: Deletes page controls +% F - [Optional] Figure in which to attempt to turn the page +% Defaults to 'Graphics' 'Tag'ged window +% +% FORMAT n = spm_figure('#page') +% Returns the current page number. +% +% FORMAT spm_figure('WaterMark',F,str,Tag,Angle,Perm) +% Adds watermark to figure windows. +% F - Figure for watermark. Defaults to gcf +% str - Watermark string. Defaults (missing or empty) to SPM +% Tag - Tag for watermark axes. Defaults to '' +% Angle - Angle for watermark. Defaults to -45 +% Perm - If specified, then watermark is permanent (HandleVisibility 'off') +% +% FORMAT F = spm_figure('CreateWin',Tag,Name,Visible) +% Creates a full length WhiteBg figure 'Tag'ged Tag (if specified). +% F - Figure created +% Tag - Tag for window +% Name - Name for window +% Visible - 'on' or 'off' +% +% FORMAT WS = spm_figure('GetWinScale') +% Returns ratios of current display dimensions to that of a 1152 x 900 +% Sun display. WS=[Xratio,Yratio,Xratio,Yratio]. Used for scaling other +% GUI elements. +% (Function duplicated in spm.m, repeated to reduce inter-dependencies.) +% +% FORMAT FS = spm_figure('FontSizes',FS) +% Returns fontsizes FS scaled for the current display. +% FS - (vector of) Font sizes to scale +% [default [08,09,11,13,14,6:36]] +% +% FORMAT spm_figure('CreateBar',F) +% Creates toolbar in figure F (defaults to gcf). F can be a 'Tag' +% If the figure is 'Tag'ed as 'Graphics' (SPM usage), then the Print button +% callback is set to attempt to clear an 'Interactive' figure too. +% +% FORMAT spm_figure('ColorMap') +% Callback for "ColorMap" buttons +% +% FORMAT h = spm_figure('GraphicsHandle',F) +% GUI choose object for handle identification. LeftMouse 'normal' returns +% handle, MiddleMouse 'extend' returns parents handle, RightMouse 'alt' cancels. +% F - figure to do a GUI "handle ID" in [Default gcbf] +%_______________________________________________________________________ + + +%-Condition arguments +%----------------------------------------------------------------------- +if (nargin==0), Action = 'Create'; else, Action = varargin{1}; end + +switch lower(Action), case 'create' +%======================================================================= +% F = spm_figure('Create',Tag,Name,Visible) +%-Condition arguments +if nargin<4, Visible='on'; else, Visible=varargin{4}; end +if nargin<3, Name=''; else, Name=varargin{3}; end +if nargin<2, Tag=''; else, Tag=varargin{2}; end + +F = spm_figure('CreateWin',Tag,Name,Visible); +spm_figure('CreateBar',F); +spm_figure('FigContextMenu',F); +varargout = {F}; + + +case 'findwin' +%======================================================================= +% F=spm_figure('FindWin',F) +% F=spm_figure('FindWin',Tag) +%-Find window: Find window with FigureNumber# / 'Tag' attribute +%-Returns empty if window cannot be found - deletes multiple tagged figs. + +if nargin<2, F='Graphics'; else, F=varargin{2}; end + +if isempty(F) + % Leave F empty +elseif ischar(F) + % Finds Graphics window with 'Tag' string - delete multiples + Tag=F; + F = findobj(get(0,'Children'),'Flat','Tag',Tag); + if length(F) > 1 + % Multiple Graphics windows - close all but most recent + close(F(2:end)) + F = F(1); + end +else + % F is supposed to be a figure number - check it + if ~any(F==get(0,'Children')), F=[]; end +end +varargout = {F}; + +case 'getwin' +%======================================================================= +% F=spm_figure('GetWin',Tag) + +if nargin<2, Tag='Graphics'; else, Tag=varargin{2}; end +F = spm_figure('FindWin',Tag); + +if isempty(F) + if ischar(Tag) + switch Tag, case 'Graphics' + F = spm_figure('Create','Graphics','Graphics'); + case 'Interactive' + F = spm('CreateIntWin'); + end + end +else + set(0,'CurrentFigure',F); +end +varargout = {F}; + +case 'parentfig' +%======================================================================= +% F=spm_figure('ParentFig',h) +if nargin<2, error('No object specified'), else, h=varargin{2}; end +F = get(h(1),'Parent'); +while ~strcmp(get(F,'Type'),'figure'), F=get(F,'Parent'); end +varargout = {F}; + + +case 'clear' +%======================================================================= +% spm_figure('Clear',F,Tags) + +%-Sort out arguments +%----------------------------------------------------------------------- +if nargin<3, Tags=[]; else, Tags=varargin{3}; end +if nargin<2, F=get(0,'CurrentFigure'); else, F=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), return, end + +%-Clear figure +%----------------------------------------------------------------------- +if isempty(Tags) + %-Clear figure of objects with 'HandleVisibility' 'on' + pos = get(F,'Position'); + delete(findobj(get(F,'Children'),'flat','HandleVisibility','on')); + drawnow + set(F,'Position',pos); + + %-Reset figures callback functions + set(F,'KeyPressFcn','',... + 'WindowButtonDownFcn','',... + 'WindowButtonMotionFcn','',... + 'WindowButtonUpFcn','') + %-If this is the 'Interactive' window, reset name & UserData + if strcmp(get(F,'Tag'),'Interactive') + set(F,'Name','','UserData',[]), end +else + %-Clear specified objects from figure + cSHH = get(0,'ShowHiddenHandles'); + set(0,'ShowHiddenHandles','on') + if ischar(Tags); Tags=cellstr(Tags); end + if any(strcmp(Tags(:),'!all')) + delete(get(F,'Children')) + else + for tag = Tags(:)' + delete(findobj(get(F,'Children'),'flat','Tag',tag{:})); + end + end + set(0,'ShowHiddenHandles',cSHH) +end +set(F,'Pointer','Arrow') + + +case 'defprintcmd' +%======================================================================= +% spm_figure('DefPrintCmd') +varargout = {'print -dpsc2 -painters -append -noui '}; + + +case 'print' +%======================================================================= +% spm_figure('Print',F) + +%-Arguments & defaults +if nargin<2, F='Graphics'; else, F=varargin{2}; end + +%-Find window to print, default to gcf if specified figure not found +% Return if no figures +F=spm_figure('FindWin',F); +if isempty(F), F = get(0,'CurrentFigure'); end +if isempty(F), return, end + +%-Note current figure, & switch to figure to print +cF = get(0,'CurrentFigure'); +set(0,'CurrentFigure',F) + +%-See if window has paging controls +hNextPage = findobj(F,'Tag','NextPage'); +hPrevPage = findobj(F,'Tag','PrevPage'); +hPageNo = findobj(F,'Tag','PageNo'); +iPaged = ~isempty(hNextPage); + +%-Construct print command +%----------------------------------------------------------------------- +global defaults +if ~isempty(defaults), + PRINTSTR = defaults.printstr; +else, + PRINTSTR = [spm_figure('DefPrintCmd'),'spm2.ps']; +end + +%-Create footnote with SPM version, username, date and time. +%----------------------------------------------------------------------- +FNote = sprintf('%s%s: %s',spm('ver'),spm('GetUser',' (%s)'),spm('time')); +%-Delete old tag lines, and print new one +delete(findobj(F,'Tag','SPMprintFootnote')); +axes('Position',[0.005,0.005,0.1,0.1],... + 'Visible','off',... + 'Tag','SPMprintFootnote') +text(0,0,FNote,'FontSize',6); + +%-Temporarily change all units to normalized prior to printing +% (Fixes bizzarre problem with stuff jumping around!) +%----------------------------------------------------------------------- +H = findobj(get(F,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +set(H,'Units','normalized') + + +%-Print +%----------------------------------------------------------------------- +err = 0; +if ~iPaged + printstr = clean_PRINTSTR(PRINTSTR); + try, eval(printstr), catch, err=1; end +else + hPg = get(hNextPage,'UserData'); + Cpage = get(hPageNo, 'UserData'); + nPages = size(hPg,1); + + set([hNextPage,hPrevPage,hPageNo],'Visible','off') + if Cpage~=1 + set(hPg{Cpage,1},'Visible','off'), end + for p = 1:nPages + set(hPg{p,1},'Visible','on'); + printstr = clean_PRINTSTR(PRINTSTR); + try, eval(printstr), catch, err=1; end + set(hPg{p,1},'Visible','off') + end + set(hPg{Cpage,1},'Visible','on') + set([hNextPage,hPrevPage,hPageNo],'Visible','on') +end + +if err + errstr = lasterr; + tmp = [find(abs(errstr)==10),length(errstr)+1]; + str = {errstr(1:tmp(1)-1)}; + for i = 1:length(tmp)-1 + if tmp(i)+1 < tmp(i+1) + str = [str, {errstr(tmp(i)+1:tmp(i+1)-1)}]; + end + end + str = {str{:}, '','- print command is:',[' ',printstr],... + '','- current directory is:',[' ',pwd],... + '',' * nothing has been printed *'}; + spm('alert!',str,'printing problem...',sqrt(-1)); +end + +set(H,{'Units'},un) +set(0,'CurrentFigure',cF) + + +case 'newpage' +%======================================================================= +% [hNextPage, hPrevPage, hPageNo] = spm_figure('NewPage',h) +if nargin<2 | isempty(varargin{2}), error('No handles to paginate') + else, h=varargin{2}(:)'; end + +%-Work out which figure we're in +F = spm_figure('ParentFig',h(1)); + +hNextPage = findobj(F,'Tag','NextPage'); +hPrevPage = findobj(F,'Tag','PrevPage'); +hPageNo = findobj(F,'Tag','PageNo'); + +%-Create pagination widgets if required +%----------------------------------------------------------------------- +if isempty(hNextPage) + WS = spm('WinScale'); + FS = spm('FontSizes'); + SatFig = findobj('Tag','Satellite'); + if ~isempty(SatFig) + SatFigPos = get(SatFig,'Position'); + hNextPagePos = [SatFigPos(3)-25 15 15 15]; + hPrevPagePos = [SatFigPos(3)-40 15 15 15]; + hPageNo = [SatFigPos(3)-40 5 30 10]; + else + hNextPagePos = [580 022 015 015].*WS; + hPrevPagePos = [565 022 015 015].*WS; + hPageNo = [550 005 060 015].*WS; + end + + hNextPage = uicontrol(F,'Style','Pushbutton',... + 'HandleVisibility','on',... + 'String','>','FontSize',FS(10),... + 'ToolTipString','next page',... + 'Callback','spm_figure(''TurnPage'',''+1'',gcbf)',... + 'Position',hNextPagePos,... + 'ForegroundColor',[0 0 0],... + 'Tag','NextPage','UserData',[]); + hPrevPage = uicontrol(F,'Style','Pushbutton',... + 'HandleVisibility','on',... + 'String','<','FontSize',FS(10),... + 'ToolTipString','previous page',... + 'Callback','spm_figure(''TurnPage'',''-1'',gcbf)',... + 'Position',hPrevPagePos,... + 'Visible','on',... + 'Enable','off',... + 'Tag','PrevPage'); + hPageNo = uicontrol(F,'Style','Text',... + 'HandleVisibility','on',... + 'String','1',... + 'FontSize',FS(6),... + 'HorizontalAlignment','center',... + 'BackgroundColor','w',... + 'Position',hPageNo,... + 'Visible','on',... + 'UserData',1,... + 'Tag','PageNo','UserData',1); +end + +%-Add handles for this page to UserData of hNextPage +%-Make handles for this page invisible if PageNo>1 +%----------------------------------------------------------------------- +mVis = strcmp('on',get(h,'Visible')); +hPg = get(hNextPage,'UserData'); +if isempty(hPg) + hPg = {h(mVis), h(~mVis)}; +else + hPg = [hPg; {h(mVis), h(~mVis)}]; + set(h(mVis),'Visible','off') +end +set(hNextPage,'UserData',hPg) + +%-Return handles to pagination controls if requested +if nargout>0, varargout = {[hNextPage, hPrevPage, hPageNo]}; end + + +case 'turnpage' +%======================================================================= +% spm_figure('TurnPage',move,F) +if nargin<3, F='Graphics'; else, F=varargin{3}; end +if nargin<2, move=1; else, move=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), error('No Graphics window'), end + +hNextPage = findobj(F,'Tag','NextPage'); +hPrevPage = findobj(F,'Tag','PrevPage'); +hPageNo = findobj(F,'Tag','PageNo'); +if isempty(hNextPage), return, end +hPg = get(hNextPage,'UserData'); +Cpage = get(hPageNo, 'UserData'); +nPages = size(hPg,1); + +%-Sort out new page number +if ischar(move), Npage = Cpage+eval(move); else, Npage = move; end +Npage = max(min(Npage,nPages),1); + +%-Make current page invisible, new page visible, set page number string +set(hPg{Cpage,1},'Visible','off') +set(hPg{Npage,1},'Visible','on') +set(hPageNo,'UserData',Npage,'String',sprintf('%d / %d',Npage,nPages)) + +%-Disable appropriate page turning control if on first/last page (for neatness) +if Npage==1, set(hPrevPage,'Enable','off') +else, set(hPrevPage,'Enable','on'), end +if Npage==nPages, set(hNextPage,'Enable','off') +else, set(hNextPage,'Enable','on'), end + + + +case 'deletepagecontrols' +%======================================================================= +% spm_figure('DeletePageControls',F) +if nargin<2, F='Graphics'; else, F=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), error('No Graphics window'), end + +hNextPage = findobj(F,'Tag','NextPage'); +hPrevPage = findobj(F,'Tag','PrevPage'); +hPageNo = findobj(F,'Tag','PageNo'); + +delete([hNextPage hPrevPage hPageNo]) + + +case '#page' +%======================================================================= +% n = spm_figure('#Page',F) +if nargin<2, F='Graphics'; else, F=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), error('No Graphics window'), end + +hNextPage = findobj(F,'Tag','NextPage'); +if isempty(hNextPage) + n = 1; +else + n = size(get(hNextPage,'UserData'),1)+1; +end +varargout = {n}; + + +case 'watermark' +%======================================================================= +% spm_figure('WaterMark',F,str,Tag,Angle,Perm) +if nargin<6, HVis='on'; else, HVis='off'; end +if nargin<5, Angle=-45; else, Angle=varargin{5}; end +if nargin<4 | isempty(varargin{4}), Tag = 'WaterMark'; else, Tag=varargin{4}; end +if nargin<3 | isempty(varargin{3}), str = 'SPM'; else, str=varargin{3}; end +if nargin<2, if any(get(0,'Children')), F=gcf; else, F=''; end + else, F=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), return, end + +%-Specify watermark color from background colour +%----------------------------------------------------------------------- +Colour = get(F,'Color'); +%-Only mess with grayscale backgrounds +if ~all(Colour==Colour(1)), return, end +%-Work out colour - lighter unless grey value > 0.9 +Colour = Colour+(2*(Colour(1)<0.9)-1)*0.02; + +cF = get(0,'CurrentFigure'); +set(0,'CurrentFigure',F) +Units=get(F,'Units'); +set(F,'Units','normalized'); +h = axes('Position',[0.45,0.5,0.1,0.1],... + 'Units','normalized',... + 'Visible','off',... + 'Tag',Tag); +set(F,'Units',Units) +text(0.5,0.5,str,... + 'FontSize',spm('FontSize',80),... + 'FontWeight','Bold',... + 'FontName',spm_platform('Font','times'),... + 'Rotation',Angle,... + 'HorizontalAlignment','Center',... + 'VerticalAlignment','middle',... + 'EraseMode','normal',... + 'Color',Colour,... + 'ButtonDownFcn',[... + 'if strcmp(get(gcbf,''SelectionType''),''open''),',... + 'delete(get(gcbo,''Parent'')),',... + 'end']) +set(h,'HandleVisibility',HVis) +set(0,'CurrentFigure',cF) + + +case 'createwin' +%======================================================================= +% F=spm_figure('CreateWin',Tag,Name,Visible) + +%-Condition arguments +%----------------------------------------------------------------------- +if nargin<4 | isempty(varargin{4}), Visible='on'; else, Visible=varargin{4}; end +if nargin<3, Name=''; else, Name = varargin{3}; end +if nargin<2, Tag=''; else, Tag = varargin{2}; end + +WS = spm('WinScale'); %-Window scaling factors +FS = spm('FontSizes'); %-Scaled font sizes +PF = spm_platform('fonts'); %-Font names (for this platform) +Rect = spm('WinSize','Graphics','raw').*WS; %-Graphics window rectangle + +F = figure(... + 'Tag',Tag,... + 'Position',Rect,... + 'Resize','off',... + 'Color','w',... + 'ColorMap',gray(64),... + 'DefaultTextColor','k',... + 'DefaultTextInterpreter','none',... + 'DefaultTextFontName',PF.helvetica,... + 'DefaultTextFontSize',FS(10),... + 'DefaultAxesColor','w',... + 'DefaultAxesXColor','k',... + 'DefaultAxesYColor','k',... + 'DefaultAxesZColor','k',... + 'DefaultAxesFontName',PF.helvetica,... + 'DefaultPatchFaceColor','k',... + 'DefaultPatchEdgeColor','k',... + 'DefaultSurfaceEdgeColor','k',... + 'DefaultLineColor','k',... + 'DefaultUicontrolFontName',PF.helvetica,... + 'DefaultUicontrolFontSize',FS(10),... + 'DefaultUicontrolInterruptible','on',... + 'PaperType','A4',... + 'PaperUnits','normalized',... + 'PaperPosition',[.0726 .0644 .854 .870],... + 'InvertHardcopy','off',... + 'Renderer','zbuffer',... + 'Visible','off'); +if ~isempty(Name) + set(F,'Name',sprintf('%s%s: %s',spm('ver'),... + spm('GetUser',' (%s)'),Name),'NumberTitle','off') +end +set(F,'Visible',Visible) +varargout = {F}; + + +case 'getwinscale' +%======================================================================= +% WS = spm_figure('GetWinScale') +warning('spm_figure(''GetWinScale''... is Grandfathered: use spm(''WinScale''') +varargout = {spm('WinScale')}; + + +case 'fontsizes' +%======================================================================= +% FS = spm_figure('FontSizes',FS) +warning('spm_figure(''FontSizes''... is Grandfathered: use spm(''FontSizes''') +if nargin<2, FS=[08,09,11,13,14,6:36]; else, FS=varargin{2}; end +varargout = {round(FS*min(spm('WinScale')))}; + + +%======================================================================= + case 'createbar' +%======================================================================= +% spm_figure('CreateBar',F) +if nargin<2, if any(get(0,'Children')), F=gcf; else, F=''; end + else, F=varargin{2}; end +F = spm_figure('FindWin',F); +if isempty(F), return, end + +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') + +t0 = findobj(get(F,'Children'),'Flat','Label','&Help'); +if isempty(t0), t0 = uimenu( F,'Label','&Help'); end; + +set(findobj(t0,'Position',1),'Separator','on'); +t1 = uimenu(t0,'Position',1,... + 'Label','SPM web',... + 'CallBack','web(''http://www.fil.ion.ucl.ac.uk/spm'');'); +t1 = uimenu(t0,'Position',1,... + 'Label','SPM help','ForegroundColor',[0 1 0],... + 'CallBack','spm_help'); + +t0=uimenu( F,'Label','Colours','HandleVisibility','off'); +t1=uimenu(t0,'Label','ColorMap'); +t2=uimenu(t1,'Label','Gray','CallBack','spm_figure(''ColorMap'',''gray'')'); +t2=uimenu(t1,'Label','Hot','CallBack','spm_figure(''ColorMap'',''hot'')'); +t2=uimenu(t1,'Label','Pink','CallBack','spm_figure(''ColorMap'',''pink'')'); +t2=uimenu(t1,'Label','Gray-Hot','CallBack','spm_figure(''ColorMap'',''gray-hot'')'); +t2=uimenu(t1,'Label','Gray-Pink','CallBack','spm_figure(''ColorMap'',''gray-pink'')'); +t1=uimenu(t0,'Label','Effects'); +t2=uimenu(t1,'Label','Invert','CallBack','spm_figure(''ColorMap'',''invert'')'); +t2=uimenu(t1,'Label','Brighten','CallBack','spm_figure(''ColorMap'',''brighten'')'); +t2=uimenu(t1,'Label','Darken','CallBack','spm_figure(''ColorMap'',''darken'')'); +t0=uimenu( F,'Label','Clear','HandleVisibility','off','CallBack','if ~isequal(questdlg(''Sure you want to clear ?'', ''...'', ''Yes'', ''No'', ''No''), ''Yes'');return;end;spm_figure(''Clear'',gcbf)'); +t0=uimenu('Parent', F,'Label','PRINT-OK','HandleVisibility','off','CallBack','print -painters -dwin'); %SOSART +% ### CODE FOR SATELLITE FIGURE ### +% Code checks if there is a satellite window and if results are currently displayed +% It assumes that if hReg is invalid then there are no results currently displayed +% Modified by DRG to display a satellite figure 02/14/01. +cb = ['global SatWindow,',... + 'try,',... + 'tmp = get(hReg);,',... + 'ResFlag = 1;',... + 'catch,',... + 'ResFlag = 0;',... + 'end,',... + 'if SatWindow,',... + 'figure(SatWindow),',... + 'else,',... + 'if ResFlag,',... + 'spm_setup_satfig,',... + 'end,',... + 'end']; +t0=uimenu( F,'Label','Results-Fig','HandleVisibility','off','Callback',cb); +% ### END NEW CODE ### + + +set(0,'ShowHiddenHandles',cSHH) +%======================================================================= + + +case 'figcontextmenu' +%======================================================================= +% h = spm_figure('FigContextMenu',F) +if nargin<2 + F = get(0,'CurrentFigure'); + if isempty(F), error('no figure'), end +else + F = spm_figure('FindWin',varargin{2}); + if isempty(F), error('no such figure'), end +end +h = uicontextmenu('Parent',F,'HandleVisibility','CallBack'); +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +copy_menu(F,h); +set(0,'ShowHiddenHandles',cSHH) +set(F,'UIContextMenu',h) +varargout = {h}; + + +case 'colormap' +%======================================================================= +% spm_figure('ColorMap',ColAction,h) +if nargin<3, h=[]; else, h=varargin{3}; end +if nargin<2, ColAction='gray'; else, ColAction=varargin{2}; end + +switch lower(ColAction), case 'gray' + colormap(gray(64)) +case 'hot' + colormap(hot(64)) +case 'pink' + colormap(pink(64)) +case 'gray-hot' + tmp = hot(64 + 16); tmp = tmp([1:64] + 16,:); + colormap([gray(64); tmp]) +case 'gray-pink' + tmp = pink(64 + 16); tmp = tmp([1:64] + 16,:); + colormap([gray(64); tmp]) +case 'invert' + colormap(flipud(colormap)) +case 'brighten' + colormap(brighten(colormap, 0.2)) +case 'darken' + colormap(brighten(colormap, -0.2)) +otherwise + error('Illegal ColAction specification') +end + +case 'graphicshandle' +%======================================================================= +% h = spm_figure('GraphicsHandle',F) +if nargin<2, F=gcbf; else, F=spm_figure('FindWin',varargin{2}); end +if isempty(F), return, end + +tmp = get(F,'Name'); +set(F,'Name',... + 'Handle: Select item to identify, MiddleMouse=parent, RightMouse=cancel...'); +set(F,'Pointer','CrossHair') +waitforbuttonpress; +h = gco(F); +hType = get(h,'Type'); +SelnType = get(gcf,'SelectionType'); +set(F,'Pointer','Arrow','Name',tmp) + +if ~strcmp(SelnType,'alt') & ~isempty(h) & gcf==F + str = sprintf('Selected (%s) object',get(h,'Type')); + if strcmp(SelnType,'normal') + str = sprintf('%s: handle',str); + else + h = get(h,'Parent'); + str = sprintf('%s: handle of parent (%s) object',str,get(h,'Type')); + end + if nargout==0 + assignin('base','ans',h) + fprintf('\n%s: \n',str) + ans = h + else + varargout={h}; + end +else + varargout={[]}; +end + + + +otherwise +%======================================================================= +warning(['Illegal Action string: ',Action]) +end +return; +%======================================================================= + + +%======================================================================= +function copy_menu(F,G) +%======================================================================= +handles = findobj(get(F,'Children'),'Flat','Type','uimenu','Visible','on'); +if length(handles)==0, return; end; +for F1=handles', + if ~strcmp(get(F1,'Label'),'&Window'), + G1 = uimenu(G,'Label',get(F1,'Label'),... + 'CallBack',get(F1,'CallBack'),... + 'Position',get(F1,'Position'),... + 'Separator',get(F1,'Separator')); + copy_menu(F1,G1); + end; +end; +return; +%======================================================================= + + +%======================================================================= +function PRINTSTR = clean_PRINTSTR(PRINTSTR) +%======================================================================= +% Matlab 6.5 printing doesn't like the -append option if the file does +% not already exist +%----------------------------------------------------------------------- +off = findstr('-append',PRINTSTR); +if ~isempty(off), + bl = [0 find(isspace(PRINTSTR)) (length(PRINTSTR)+1)]; + for i=1:(length(bl)-1), + ca{i} = PRINTSTR((bl(i)+1):(bl(i+1)-1)); + end; + ca = strvcat(ca); + off1 = find(ca(:,1)~='-'); % either 'print' or a filename + if length(off1)>1, + fname = deblank(ca(off1(end),:)); + + % If there is no path to the file, then make it the + % current directory + [pth,nam,ext] = fileparts(fname); + if isempty(pth), fname = ['.' filesep nam ext]; end; + + fd = fopen(fname,'r'); + if fd~=-1, + % File exists, so -append can be used + fclose(fd); + else, + % File does not exist, so remove -append option + PRINTSTR(off:(off+7))=''; + end; + end; +end; diff --git a/spm/spm2/spm_fmri_spm_ui.m b/spm/spm2/spm_fmri_spm_ui.m new file mode 100644 index 0000000..939290f --- /dev/null +++ b/spm/spm2/spm_fmri_spm_ui.m @@ -0,0 +1,478 @@ +function [SPM] = spm_fmri_spm_ui(SPM) +% Setting up the general linear model for fMRI time-series +% FORMAT [SPM] = spm_fmri_spm_ui(SPM) +% +% creates SPM with the following fields +% +% xY: [1x1 struct] - data stucture +% nscan: [double] - vector of scans per session +% xBF: [1x1 struct] - Basis function stucture (see spm_fMRI_design) +% Sess: [1x1 struct] - Session stucture (see spm_fMRI_design) +% xX: [1x1 struct] - Design matric stucture (see spm_fMRI_design) +% xGX: [1x1 struct] - Global variate stucture +% xVi: [1x1 struct] - Non-sphericity stucture +% xM: [1x1 struct] - Masking stucture +% xsDes: [1x1 struct] - Design description stucture +% +% +% SPM.xY +% P: [n x ? char] - filenames +% VY: [n x 1 struct] - filehandles +% RT: Repeat time +% +% SPM.xGX +% +% iGXcalc: {'none'|'Scaling'} - Global normalization option +% sGXcalc: 'mean voxel value' - Calculation method +% sGMsca: 'session specific' - Grand mean scaling +% rg: [n x 1 double] - Global estimate +% GM: 100 - Grand mean +% gSF: [n x 1 double] - Global scaling factor +% +% SPM.xVi +% Vi: {[n x n sparse]..} - covariance components +% form: {'none'|'AR(1)'} - form of non-sphericity +% +% SPM.xM +% T: [n x 1 double] - Masking index +% TH: [n x 1 double] - Threshold +% I: 0 +% VM: - Mask filehandles +% xs: [1x1 struct] - cellstr description +% +% (see also spm_spm_ui) +% +%____________________________________________________________________________ +% +% spm_fmri_spm_ui configures the design matrix, data specification and +% filtering that specify the ensuing statistical analysis. These +% arguments are passed to spm_spm that then performs the actual parameter +% estimation. +% +% The design matrix defines the experimental design and the nature of +% hypothesis testing to be implemented. The design matrix has one row +% for each scan and one column for each effect or explanatory variable. +% (e.g. regressor or stimulus function). The parameters are estimated in +% a least squares sense using the general linear model. Specific profiles +% within these parameters are tested using a linear compound or contrast +% with the T or F statistic. The resulting statistical map constitutes +% an SPM. The SPM{T}/{F} is then characterized in terms of focal or regional +% differences by assuming that (under the null hypothesis) the components of +% the SPM (i.e. residual fields) behave as smooth stationary Gaussian fields. +% +% spm_fmri_spm_ui allows you to (i) specify a statistical model in terms +% of a design matrix, (ii) associate some data with a pre-specified design +% [or (iii) specify both the data and design] and then proceed to estimate +% the parameters of the model. +% Inferences can be made about the ensuing parameter estimates (at a first +% or fixed-effect level) in the results section, or they can be re-entered +% into a second (random-effect) level analysis by treating the session or +% subject-specific [contrasts of] parameter estimates as new summary data. +% Inferences at any level obtain by specifying appropriate T or F contrasts +% in the results section to produce SPMs and tables of p values and statistics. +% +% spm_fmri_spm calls spm_fMRI_design which allows you to configure a +% design matrix in terms of events or epochs. +% +% spm_fMRI_design allows you to build design matrices with separable +% session-specific partitions. Each partition may be the same (in which +% case it is only necessary to specify it once) or different. Responses +% can be either event- or epoch related, The only distinction is the duration +% of the underlying input or stimulus function. Mathematically they are both +% modeled by convolving a series of delta (stick) or box functions (u), +% indicating the onset of an event or epoch with a set of basis +% functions. These basis functions model the hemodynamic convolution, +% applied by the brain, to the inputs. This convolution can be first-order +% or a generalized convolution modeled to second order (if you specify the +% Volterra option). [The same inputs are used by the hemodynamic model or +% or dynamic causal models which model the convolution explicitly in terms of +% hidden state variables (see spm_hdm_ui and spm_dcm_ui).] +% Basis functions can be used to plot estimated responses to single events +% once the parameters (i.e. basis function coefficients) have +% been estimated. The importance of basis functions is that they provide +% a graceful transition between simple fixed response models (like the +% box-car) and finite impulse response (FIR) models, where there is one +% basis function for each scan following an event or epoch onset. The +% nice thing about basis functions, compared to FIR models, is that data +% sampling and stimulus presentation does not have to be sychronized +% thereby allowing a uniform and unbiased sampling of peri-stimulus time. +% +% Event-related designs may be stochastic or deterministic. Stochastic +% designs involve one of a number of trial-types occurring with a +% specified probably at successive intervals in time. These +% probabilities can be fixed (stationary designs) or time-dependent +% (modulated or non-stationary designs). The most efficient designs +% obtain when the probabilities of every trial type are equal. +% A critical issue in stochastic designs is whether to include null events +% If you wish to estimate the evoke response to a specific event +% type (as opposed to differential responses) then a null event must be +% included (even if it is not modelled explicitly). +% +% The choice of basis functions depends upon the nature of the inference +% sought. One important consideration is whether you want to make +% inferences about compounds of parameters (i.e. contrasts). This is +% the case if (i) you wish to use a SPM{T} to look separately at +% activations and deactivations or (ii) you with to proceed to a second +% (random-effect) level of analysis. If this is the case then (for +% event-related studies) use a canonical hemodynamic response function +% (HRF) and derivatives with respect to latency (and dispersion). Unlike +% other bases, contrasts of these effects have a physical interpretation +% and represent a parsimonious way of characterising event-related +% responses. Bases such as a Fourier set require the SPM{F} for +% inference. +% +% See spm_fMRI_design for more details about how designs are specified. +% +% Serial correlations in fast fMRI time-series are dealt with as +% described in spm_spm. At this stage you need to specify the filtering +% that will be applied to the data (and design matrix) to give a +% generalized least squares (GLS) estimate of the parameters required. +% This filtering is important to ensure that the GLS estimate is +% efficient and that the error variance is estimated in an unbiased way. +% +% The serial correlations will be estimated with a ReML (restricted +% maximum likelihood) algorithm using an autoregressive AR(1) model +% during parameter estimation. This estimate assumes the same +% correlation structure for each voxel, within each session. The ReML +% estimates are then used to correct for non-sphericity during inference +% by adjusting the statistics and degrees of freedom appropriately. The +% discrepancy between estimated and actual intrinsic (i.e. prior to +% filtering) correlations are greatest at low frequencies. Therefore +% specification of the high-pass filter is particularly important. +% +% High-pass filtering is implemented at the level of the +% filtering matrix K (as opposed to entering as confounds in the design +% matrix). The default cutoff period is 128 seconds. Use 'explore design' +% to ensure this cuttof is not removing too much experimental variance. +% Note that high-pass filtering uses a residual forming matrix (i.e. +% it is not a convolution) and is simply to a way to remove confounds +% without estimating their parameters explicitly. The constant term +% is also incorportated into this filter matrix. +% +%----------------------------------------------------------------------- +% Refs: +% +% Friston KJ, Holmes A, Poline J-B, Grasby PJ, Williams SCR, Frackowiak +% RSJ & Turner R (1995) Analysis of fMRI time-series revisited. NeuroImage +% 2:45-53 +% +% Worsley KJ and Friston KJ (1995) Analysis of fMRI time-series revisited - +% again. NeuroImage 2:178-181 +% +% Friston KJ, Frith CD, Frackowiak RSJ, & Turner R (1995) Characterising +% dynamic brain responses with fMRI: A multivariate approach NeuroImage - +% 2:166-172 +% +% Frith CD, Turner R & Frackowiak RSJ (1995) Characterising evoked +% hemodynamics with fMRI Friston KJ, NeuroImage 2:157-165 +% +% Josephs O, Turner R and Friston KJ (1997) Event-related fMRI, Hum. Brain +% Map. 0:00-00 +% +%_______________________________________________________________________ +% @(#)spm_fmri_spm_ui.m 2.52 Karl Friston, Jean-Baptiste Poline, Christian Buchel 03/12/18 +SCCSid = '2.52'; + +%-GUI setup +%----------------------------------------------------------------------- +[Finter,Fgraph,CmdLine] = spm('FnUIsetup','fMRI stats model setup',0); +spm_help('!ContextHelp',mfilename) + +global defaults + +% get design matrix and/or data +%======================================================================= +if ~nargin + + str = 'specify design or data'; + if spm_input(str,1,'b',{'design','data'},[1 0]); + + % specify a design + %------------------------------------------------------- + if sf_abort, spm_clf(Finter), return, end + SPM = spm_fMRI_design; + spm_fMRI_design_show(SPM); + return + + else + + % get design + %------------------------------------------------------- + load(spm_get(1,'SPM.mat','Select SPM.mat')); + + end + +else + + % get design matrix + %--------------------------------------------------------------- + SPM = spm_fMRI_design(SPM); + +end + +% get Repeat time +%----------------------------------------------------------------------- +try + RT = SPM.xY.RT; +catch + RT = spm_input('Interscan interval {secs}','+1'); + SPM.xY.RT = RT; +end + + +% session and scan number +%----------------------------------------------------------------------- +nscan = SPM.nscan; +nsess = length(nscan); + +% check data are specified +%----------------------------------------------------------------------- +try + SPM.xY.P; +catch + + % get filenames + %--------------------------------------------------------------- + P = []; + for i = 1:nsess + str = sprintf('select scans for session %0.0f',i); + q = spm_get(nscan(i),'.img',str); + P = strvcat(P,q); + end + + % place in data field + %--------------------------------------------------------------- + SPM.xY.P = P; + +end + + + +% Assemble remaining design parameters +%======================================================================= +spm_help('!ContextHelp',mfilename) +SPM.SPMid = spm('FnBanner',mfilename,SCCSid); + + +% Global normalization +%----------------------------------------------------------------------- +nsess = length(SPM.nscan); +try + SPM.xGX.iGXcalc; +catch + spm_input('Global intensity normalisation...',1,'d',mfilename) + str = 'remove Global effects'; + SPM.xGX.iGXcalc = spm_input(str,'+1','scale|none',{'Scaling' 'None'}); +end +SPM.xGX.sGXcalc = 'mean voxel value'; +SPM.xGX.sGMsca = 'session specific'; + + +% High-pass filtering and serial correlations +%======================================================================= + +% low frequency confounds +%----------------------------------------------------------------------- +try + HParam = SPM.xX.K(1).HParam; + HParam = HParam*ones(1,nsess); +catch + % specify low frequnecy confounds + %--------------------------------------------------------------- + spm_input('Temporal autocorrelation options','+1','d',mfilename) + switch spm_input('High-pass filter?','+1','b','none|specify'); + + case 'specify' % default 128 seconds + %------------------------------------------------------- + HParam = 128*ones(1,nsess); + str = 'cutoff period (secs)'; + HParam = spm_input(str,'+1','e',HParam,[1 nsess]); + + case 'none' % Inf seconds (i.e. constant term only) + %------------------------------------------------------- + HParam = Inf*ones(1,nsess); + end +end + +% create and set filter struct +%--------------------------------------------------------------- +for i = 1:nsess + K(i) = struct( 'HParam', HParam(i),... + 'row', SPM.Sess(i).row,... + 'RT', SPM.xY.RT); +end +SPM.xX.K = spm_filter(K); + + +% intrinsic autocorrelations (Vi) +%----------------------------------------------------------------------- +try + cVi = SPM.xVi.form; +catch + % Contruct Vi structure for non-sphericity ReML estimation + %=============================================================== + str = 'Correct for serial correlations?'; + cVi = {'none','AR(1)'}; + cVi = spm_input(str,'+1','b',cVi); +end + +% create Vi struct +%----------------------------------------------------------------------- + +if ~ischar(cVi) % AR coeficient[s] specified +%----------------------------------------------------------------------- + SPM.xVi.Vi = spm_Ce(nscan,cVi(1:3)); + cVi = ['AR( ' sprintf('%0.1f ',cVi) ')']; + +else + switch lower(cVi) + + case 'none' % xVi.V is i.i.d + %--------------------------------------------------------------- + SPM.xVi.V = speye(sum(nscan)); + cVi = 'i.i.d'; + + + otherwise % otherwise assume AR(0.2) in xVi.Vi + %--------------------------------------------------------------- + SPM.xVi.Vi = spm_Ce(nscan,0.2); + cVi = 'AR(0.2)'; + + end +end +SPM.xVi.form = cVi; + + + +%======================================================================= +% - C O N F I G U R E D E S I G N +%======================================================================= +spm_clf(Finter); +spm('FigName','Configuring, please wait...',Finter,CmdLine); +spm('Pointer','Watch'); + + +% get file identifiers +%======================================================================= + +%-Map files +%----------------------------------------------------------------------- +fprintf('%-40s: ','Mapping files') %-# +VY = spm_vol(SPM.xY.P); +fprintf('%30s\n','...done') %-# + +%-check internal consistency of images +%----------------------------------------------------------------------- +if any(any(diff(cat(1,VY.dim),1,1),1) & [1,1,1,0]) +error('images do not all have the same dimensions'), end +if any(any(any(diff(cat(3,VY.mat),1,3),3))) +error('images do not all have same orientation & voxel size'), end + +%-place in xY +%----------------------------------------------------------------------- +SPM.xY.VY = VY; + + +%-Compute Global variate +%======================================================================= +GM = 100; +q = length(VY); +g = zeros(q,1); +fprintf('%-40s: %30s','Calculating globals',' ') %-# +for i = 1:q + fprintf('%s%30s',char(sprintf('\b')*ones(1,30)),sprintf('%4d/%-4d',i,q)) %-# + g(i) = spm_global(VY(i)); +end +fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...done') %-# + +% scale if specified (otherwise session specific grand mean scaling) +%----------------------------------------------------------------------- +gSF = GM./g; +if strcmp(lower(SPM.xGX.iGXcalc),'none') + for i = 1:nsess + gSF(SPM.Sess(i).row) = GM./mean(g(SPM.Sess(i).row)); + end +end + +%-Apply gSF to memory-mapped scalefactors to implement scaling +%----------------------------------------------------------------------- +for i = 1:q + SPM.xY.VY(i).pinfo(1:2,:) = SPM.xY.VY(i).pinfo(1:2,:)*gSF(i); +end + +%-place global variates in global structure +%----------------------------------------------------------------------- +SPM.xGX.rg = g; +SPM.xGX.GM = GM; +SPM.xGX.gSF = gSF; + + +%-Masking structure automatically set to 80% of mean +%======================================================================= +try + TH = g.*gSF*defaults.mask.thresh; +catch + TH = g.*gSF*0.8; +end +SPM.xM = struct( 'T', ones(q,1),... + 'TH', TH,... + 'I', 0,... + 'VM', {[]},... + 'xs', struct('Masking','analysis threshold')); + + +%-Design description - for saving and display +%======================================================================= +for i = 1:nsess, ntr(i) = length(SPM.Sess(i).U); end +Fstr = sprintf('[min] Cutoff period %d seconds',min(HParam)); +SPM.xsDes = struct(... + 'Basis_functions', SPM.xBF.name,... + 'Number_of_sessions', sprintf('%d',nsess),... + 'Trials_per_session', sprintf('%-3d',ntr),... + 'Interscan_interval', sprintf('%0.2f {s}',SPM.xY.RT),... + 'High_pass_Filter', sprintf('Cutoff: %d {s}',SPM.xX.K(1).HParam),... + 'Serial_correlations', SPM.xVi.form,... + 'Global_calculation', SPM.xGX.sGXcalc,... + 'Grand_mean_scaling', SPM.xGX.sGMsca,... + 'Global_normalisation', SPM.xGX.iGXcalc); + + +%-Save SPM.mat +%----------------------------------------------------------------------- +fprintf('%-40s: ','Saving SPM configuration') %-# +save SPM SPM; +fprintf('%30s\n','...SPM.mat saved') %-# + + +%-Display Design report +%======================================================================= +fprintf('%-40s: ','Design reporting') %-# +fname = cat(1,{SPM.xY.VY.fname}'); +spm_DesRep('DesMtx',SPM.xX,fname,SPM.xsDes) +fprintf('%30s\n','...done') %-# + + +%-End: Cleanup GUI +%======================================================================= +spm_clf(Finter) +spm('FigName','Stats: configured',Finter,CmdLine); +spm('Pointer','Arrow') +fprintf('\n\n') + + +%======================================================================= +%- S U B - F U N C T I O N S +%======================================================================= + +function abort = sf_abort +%======================================================================= +if exist(fullfile('.','SPM.mat')) + str = { 'Current directory contains existing SPM file:',... + 'Continuing will overwrite existing file!'}; + + abort = spm_input(str,1,'bd','stop|continue',[1,0],1,mfilename); + if abort, fprintf('%-40s: %30s\n\n',... + 'Abort... (existing SPM files)',spm('time')), end +else + abort = 0; +end diff --git a/spm/spm2/spm_get.m b/spm/spm2/spm_get.m new file mode 100644 index 0000000..d32ae09 --- /dev/null +++ b/spm/spm2/spm_get.m @@ -0,0 +1,1842 @@ +function varargout = spm_get(varargin) +% User interface : filename selection +% FORMAT P = spm_get(n,Filter,Prompt,NewWDir,CmdLine); +% n - 0 - returns with empty P +% - [mn,mx] : prompts for between mn & mx items +% - scalar n => [n,n], i.e. must select n items +% - all(n) positive : prompts for files +% - any(n) negative : prompts for directories +% Filter - Filename filter {'*' is prepended} +% - numeric 0 for previous filtering +% Prompt - Prompt string +% NewWDir - New working directory +% CmdLine - CmdLine override switch, 0 for GUI, 1 for Command line. +% +% P - string matrix of full pathnames {one string per row} +% returned as a cellstr if iscellstr(Prompt) +%_______________________________________________________________________ +% +% spm_get allows interactive selection of filepaths/directory names +% from disk. +% +% if global CMDLINE exists and is >0, the command line is used. The +% CmdLine parameter overrides this choice. Note that since spm_input +% uses the command line if CMDLINE is true (unless overridden), setting +% CMDLINE to -1 results in the command line being used for questions, +% but the GUI for file selection. +% +% Otherwise, selection of files is via GUI. The select files window, +% enables the interactive directory display and selection of +% filenames. Directories are displated in red in the left listing, +% files in the right listing. File lists are filtered according to the +% current filter string, using the usual UNIX conventions (*,?,etc.). +% +% Arrows at the right of the listings pane allow the lists to be +% scrolled up and down. The bar button above the "up" arrow scrolls to +% the top of the list. +% +% Selecting files +% --------------- +% Clicking on an item (black) adds it to the list of those selected, +% the item is numbered and changes color (dark blue). The item last +% selected can be unselected by clicking it again. If a specific number +% of items have been requested (n), then this number of files must be +% selected. A status message at the foot of the window explains the +% current status. +% +% Clicking on a directory name (red) changes to that directory. The +% current directory name window can edited to change directory. Also, +% pull down menus of previous directories and subdirectories of the +% current directory are maintained. (On Windows platforms, an +% additional pull down menu of drives is also provided.) The red "pwd" +% button changes directory to the current MatLab working directory, the +% "home" button to the users home directory. +% +% All files in the current window can be selected *in the order in which +% they appear* with the "All" button, and the "Reset" button clears the +% current list. The "Edit" button enables interactive editing of the +% filename list, and the "Keybd" button invokes a command line +% interface. +% +% Click "Done" when finished. As a short cut, selecting items +% using the right mouse button is equivalent to selecting the item and +% pressing "Done". +% +% Summary views of directories +% ---------------------------- +% Directories with over 48 entries (after filtering) are shown +% summarised, with a single wildcarded entry for blocks of similar +% filenames shown alongside a small white number indicating the number +% of files in the block. Such blocks can be expanded by clicking +% "Extend" (middle mouse button) on the item, or by clicking the number +% of files text, whence the whole directory is shown with the +% appropriate filter. The entire directory can be shown by clicking the +% white "Summary View" text at the top of the item window. +% +% Filter string +% --------------------- +% The filter string for filenames is built as ['*',Filter] if Filter +% doesn't contain a wildcard '*', and appears in a single editable +% window. Subsequent calls to spm_get callbacks with the same filter +% string do not change the value of the filter string, allowing user +% edits of the filer string to persist. Clicking the Filter button +% resets the filter to '*', resulting in all files/directories being +% displayed, in summary view if there are sufficient files. Clicking +% the outline of the filter editable widget resets the filter string to +% the original filter string passed by the calling program. +% +% Filter can also be a cell array of the form {'*.img', 'noexpand'}. +% When it is a cell array, the first element is taken as the filter +% to use, and subsequent elements are passed as the third argument to +% spm_list_files_expand.m. +% +% Selecting Directories +% --------------------- +% The same interface is occasionally used for selecting directories, in +% which case the list of selectable items contains a list of +% subdirectories of the current directory. Use the current directory +% window and PullDown menu's to navigate to the required directories +% parent, and select the chosen subdirectory from the list presented. +% The Filter doesn't apply to the directory list. +% +% Keyboard Accelerators +% --------------------- +% Keyboard accelerators are available for item selection, editing the +% current directory and filter windows, and for some of the interface +% buttons: These work providing no GUI widget has the focus (click in +% the window background to remove focus from any GUI widgets). +% +% - Item selection - Items are highlighted (in italic) using ^K & ^J to +% move Up and Down the item list. The highlighted item is (de)selected +% using ^S. +% +% - CurrentDir & Filter editing - Initially, all typed characters, act +% on the CurrentDirectory widget, characters are appended, delete & +% backspace delete the rightmost character. ^E (Edit) toggles between +% the CurrentDir and Filter editable widgets. Return changes to the +% specifiec directory (CurrentDir widget) or applys the current filter +% (Fitler widget). ^U deletes the whole entry, ^W deletes the last +% pathname component, ^I resets the string to it's previous value. +% +% - General Accelerators - +% Space / ^D - Done +% ^P - pwd +% ^B - Keybd +% Esc - Reset +% +% - Tab - In addition, the usual tabbing between GUI objects is +% provided by the window interface. +% +% Programmers notes +% ----------------- +% The 'Select Files Window', created by the first call to spm_get, is +% 'Tag'ged 'SelFileWin'. This window is hidden at the end of the spm_get +% transaction, and is used by subsequent calls. This saves time, and +% also permits the storage of previously visited directories from +% transaction to transaction. +% +% CallBacks are handled as embedded functions within spm_get, format +% specifications for these embedded functions are given in the main +% body of the code. +% +%_______________________________________________________________________ +% @(#)spm_get.m 2.43 Andrew Holmes (X-platform stuff with Matthew Brett) 02/10/16 + +%======================================================================= +% - FORMAT specifications for embedded CallBack functions +%======================================================================= +% +% Callback and setup function for spm_get. +% FORMAT varargout = spm_get(varargin) +% - A multi function function! +% +% FORMAT F = spm_get('CreateFig',LastDirs,Filter) +% Sets up the file selection window as next avaliable figure. +% LastDirs - String matrix for directory history +% Filter - Filename filter +% F - Figure used +% +% FORMAT spm_help('FigKeyPressFcn',ch,F) +% Callback for handling keyboard accelerators +% ch - Character [default get(F,'CurrentCharacter')] +% F - Figure used [default gcbf] +% +% FORMAT F = spm_get('Initialise',Vis,n,Prompt,Filter,WDir) +% (Re)Initialise SelFileWin, create one if necessary. +% F - Figure used. +% Vis - Figure visibility (string, 'on'|'off'|'close') +% n - Items struct: .fi (get files), .mn (min #items), .mx (max #items) +% Prompt - Prompt string. +% Filter - Filename filter. +% WDir - [optional] New Working directory +% F - Figure used +% +% FORMAT spm_get('StatusLine',nP,n,F) +% Updates FileSelWin status line +% nP - #Items already selected +% n - Items struct: .fi (get files), .mn (min #items), .mx (max #items) +% F - Figure used [defaults to 'SelFileWin' 'Tag'ged figure] +% +% FORMAT spm_get('cd',NewDir,bNoDir) +% Callback function for change directory objects +% NewDir - New Working directory (if not held in current object) +% bNoDir - Supresses listing of new directory if true +% +% FORMAT spm_get('dir',WDir,Filter,NoComp) +% Lists current working directory and attatches callbacks to contents +% WDir - Working directory +% Defaults (unspecified or empty) to UserData of WDir Tagged object +% Filter - Filename Filter +% Overrides and sets the Filter object +% Defaults (unspecified or empty) to UserData of Filter object +% NoComp - If specified, forces full directory listing - no compression +% +% [sS,I] = FORMAT spm_get('StrSort',S) +% Simple string sort routine for string matrices +% S - String matrix to be sorted +% sS - Sorted string matrix +% I - Sort index: sS = S(I) +% +% FORMAT fS = spm_get('strfliplr',S) +% fliplr for string matrices, ignores trailing padding spaces +% S - String matrix to be flipped +% fS - left-right flipped version of S, with last non-space characters +% of S in first column +% +% FORMAT [FSpecs,FnamePos]=spm_get('FileSummary',Fnames,Cend,Filter,len) +% File summary routine +% Fnames - String matrix of filenames (all unique) +% Cend - CommonEND - 'front', 'end' or 'both' +% Specifies which end to take as common for file summary +% Defaults to 'both', which gives 'front' precedence over 'back' +% Filter - Filename filter - suffix filter is appended to 'front' items +% len - Length of section to define common files +% Defaults to 3 +% FSpecs - String matrix of file patterns, with n rows +% FnamePos - Matrix of n rows. +% Each row contains the indicies of all Fnames matching the pattern +% given in the corresponding row of FSpecs. Padded with zeros. +% +% FORMAT spm_get('Add',h) +% Adds current object (of object h) to selection +% h - Object handle of an item +% +% FORMAT spm_get('Delete',h) +% Deletes current object from the selection, if it was the last chosen +% h - Handle of a deletable item (Defaults to gcbo) +% +% FORMAT spm_get('Reset',F) +% Resets the selection and redisplays the directory +% F - Figure used [defaults to 'SelFileWin' 'Tag'ged figure] +% +% FORMAT spm_get('All',F) +% Adds all remaining unselected items to the selection +% F - Figure used [defaults to 'SelFileWin' 'Tag'ged figure] +% +% FORMAT P = spm_get('CmdLine',n,Prompt,P,WDir) +% Uses command line to get items +% n - Items struct: .fi (get files), .mn (min #items), .mx (max #items) +% Prompt - Prompt string +% P - Currently selected items +% WDir - Working directory to use (defaults to pwd) +% +% FORMAT P = spm_get('GUI2CmdLine') +% GUI gateway to command line input. +% P - Currently selected items +% +% FORMAT spm_get('Edit') +% Invokes window for editing currently selected items +% +% FORMAT spm_get('EditDone',OK) +% Processes the results of the edit. +% OK - 'OK' or 'CANCEL' - Edit status. +% +% FORMAT spm_get('Done') +% Callback for "Done" button. +% +% FORMAT cpath = spm_get('CPath',path,cwd) +% function to canonicalise paths: Prepends cwd to relative paths, processes +% '..' & '.' directories embedded in path. +% path - string matrix (or cell array of strings) containing path names +% cwd - current working directory [defaut '.'] +% cpath - conditioned paths, in same format as input path argument +% +% FORMAT str = spm_get('DrivesPullDownStr') +% returns string for Drives pull down menu on Windows platforms +% +% FORMAT [P,dir] = spm_get('Files',dir,fil) +% Extended gateway to spm_list_files: Returns full pathnames & canonicalises dir +% dir - directory within which list files (a string) +% parameter is canonicalised by spm_get('CPath',dir) +% [defaults to '.', the current directory] +% fil - file filter string E.g. 'sn*.img' [default '*'] +% P - string matrix of files in directory +% if nargout<2 (i.e. if dir is not returned), then these are +% full pathnames +% dir - full pathname of directory listed (after canonicalisation) +% +%----------------------------------------------------------------------- +% SUBFUNCTIONS: +% +% FORMAT so = dstrtrim(si) +% Double tailed strtrim - strips blanks from both ends of string matrix +% +% FORMAT rootf = isroot(path) +% Tests filepath in string path: Returns true if path is root directory +% +% FORMAT absf = isabspath(path) +% Tests filepath in string path: Returns true if path is absolute +%_______________________________________________________________________ +% Andrew Holmes (X-platform stuff with Matthew Brett) + +% Options to pass to spm_list_files_expand +%======================================================================= +persistent ListOpts +if isempty(ListOpts), ListOpts = {''}; end; + +%-Parameters +%======================================================================= +%-Default to unlimited file get when no arguments +if nargin == 0, Action=+Inf'; else, Action = varargin{1}; end +PJump = 1; %-Allow pointer jumping? + +if ~ischar(Action) +%======================================================================= +% P = spm_get(n,Filter,Prompt,NewWDir,CmdLine) + +%-Condition arguments +%----------------------------------------------------------------------- +if nargin<5 CmdLine=[]; else CmdLine=varargin{5}; end +CmdLine = spm('CmdLine',CmdLine); +if nargin<4 NewWDir=''; else NewWDir=varargin{4}; end +if nargin<3 Prompt='Select files...'; else Prompt=varargin{3}; end +if nargin<2 | isempty(varargin{2}), + Filter=0; +else + Filter = varargin{2}; + ListOpts = {''}; + if any(Action(:)<0), + ListOpts = {'noexpand'}; + end; + if iscell(Filter), + ListOpts = Filter(2:end); + Filter = Filter{1}; + end; +end + +%-Parse number of items parameter (Passed as "Action" parameter) +%----------------------------------------------------------------------- +n = struct( 'fi', ~any(Action(:)<0),... %-Get files flag + 'mn', min(abs(Action(:))),... %-Min # items + 'mx', max(abs(Action(:))) ); %-Max # items +if isinf(n.mn), n.mn=0; end + +if n.mx==0 + if iscellstr(Prompt), varargout={{}}; else, varargout={''}; end + return +end + +%-NB: spm_get callbacks use Filter=0 for previous filtering +%----------------------------------------------------------------------- +if ischar(Filter) + if ~any(Filter=='*'), Filter = ['*',Filter]; end +else + Filter=0; +end + +%-Computation +%======================================================================= + +if CmdLine>0 + + %-Command line version, if global CMDLINE is true, & not overridden + %--------------------------------------------------------------- + P = spm_get('CmdLine',n,char(Prompt),[],NewWDir); + +else + + %-GUI version + %--------------------------------------------------------------- + %-Set up FileSelWin + [F,cF] = spm_get('Initialise','on',n,char(Prompt),Filter,NewWDir); + + %-Jump cursor to SelFileWin + if PJump + PLoc = get(0,'PointerLocation'); + FRec = get(F,'Position'); + set(0,'PointerLocation',[FRec(1)+FRec(3)/2, FRec(2)+FRec(2)/2]) + end + + %-Wait until filenames have been selected + hDone = findobj(F,'Tag','Done'); + waitfor(hDone,'UserData') + + %-Exit with error if SelFileWin deleted + if ~ishandle(hDone), error('SPM file selector window was quit!'), end + + %-Get P & exit status + status = get(hDone,'UserData'); + P = get(findobj(F,'Tag','P'),'UserData'); + + %-Reset and hide SelFileWin + spm_get('Initialise','off'); + + %-Return focus to previous figure (if any) + set(0,'CurrentFigure',cF) + + %-Jump cursor back to previous location + if PJump, set(0,'PointerLocation',PLoc), end + + %-Exit with error if reset (status=-1) + if status == -1, error('SPM-GUI reset: spm_get bailing out!'), end +end + +%-Convert P to cellstr if Prompt is one +%----------------------------------------------------------------------- +if iscellstr(Prompt), if isempty(P), P={}; else, P = cellstr(P); end, end + +%-Log the transaction +%----------------------------------------------------------------------- +if exist('spm_log')==2 + spm_log([mfilename,' : ',char(Prompt),' :'],P); end + +varargout = {P}; +return +end + +%======================================================================= +% - Callbacks & Utility embedded functions +%======================================================================= + +switch lower(Action), case 'createfig' +%======================================================================= +% F = spm_get('CreateFig',LastDirs,Filter) + +%-Condition arguments +%----------------------------------------------------------------------- +if nargin<3 Filter=[]; +else + Filter=varargin{3}; +end +if nargin<2 | isempty(varargin{2}), LastDirs=pwd; else LastDirs=varargin{2}; end +LastDirs=strvcat(LastDirs,getenv('HOME')); +if (exist('spm.m')==2), LastDirs=strvcat(LastDirs,spm('Dir')); end + +%-Save current figure +cF = get(0,'CurrentFigure'); + +%-Create window, compute scaling for screen size +%----------------------------------------------------------------------- +WS = spm('WinScale'); %-Window scaling factors +FS = spm('FontSizes'); %-Scaled font sizes +PF = spm_platform('fonts'); %-Font names (for this platform) +S0 = get(0,'ScreenSize'); %-Screen size + +F = figure('IntegerHandle','off',... + 'Tag','SelFileWin',... + 'Name',sprintf('%s%s: SPMget',spm('ver'),spm('GetUser',' (%s)')),... + 'NumberTitle','off',... + 'Position',[S0(3),S0(4),0,0]/2 + [-400/2,-395/2,400,395].*WS,... + 'Resize','off',... + 'Color',[1 1 1]*.8,... + 'Units','Pixels',... + 'MenuBar','none',... + 'DefaultTextInterpreter','none',... + 'DefaultTextFontName',PF.helvetica,... + 'DefaultTextFontSize',FS(10),... + 'DefaultAxesFontName',PF.helvetica,... + 'DefaultUicontrolFontName',PF.helvetica,... + 'DefaultUicontrolFontSize',FS(10),... + 'DefaultUicontrolInterruptible','on',... + 'Visible','off'); +varargout = {F}; + +%-Reset CurrentFigure to previous figure +set(0,'CurrentFigure',cF) + + +%-User control objects with callbacks +%----------------------------------------------------------------------- + +uicontrol(F,'Style','Frame','Tag','P','UserData',[],... + 'Position',[001 271 400 124].*WS); + +% uicontrol(F,'Style','Frame',... +% 'BackgroundColor',[1 1 1]*.8,... +% 'Position',[010 355 355 030].*WS); + +uicontrol(F,'Style','Text','Tag','Prompt','UserData',[],... + 'String','',... + 'ToolTipString','',... + 'FontName',PF.times,... + 'FontWeight','Bold',... + 'FontAngle','Italic',... + 'FontSize',FS(16),... + 'ForegroundColor','k',... + 'HorizontalAlignment','Center',... + 'Position',[010 370 380 022].*WS); + +uicontrol(F,'Style','PopUp','Tag','LastDirsPopup',... + 'String',strvcat('Previous Directories...',LastDirs),... + 'ToolTipString','cd to previously visited directories',... + 'HorizontalAlignment','Left',... + 'ForegroundColor','r',... + 'UserData',size(LastDirs,1),... + 'Callback','spm_get(''cd'')',... + 'Position',[010 347 335 022].*WS); + +uicontrol(F,'Style','PushButton','Tag','CDpwd',... + 'String','pwd',... + 'ToolTipString','change to current Matlab working directory',... + 'ForegroundColor','r',... + 'UserData',0,... + 'CallBack','spm_get(''cd'',pwd)',... + 'Position',[345 347 045 022].*WS); + +WDir=strtrim(LastDirs(1,:)); +uicontrol(F,'Style','Edit','String',WDir,... + 'ToolTipString','current directory - edit (& press RETURN) to cd',... + 'Tag','WDir','UserData',WDir,... + 'ForegroundColor','r','BackgroundColor',[.8,.8,1],... + 'HorizontalAlignment','Left',... + 'CallBack','spm_get(''cd'')',... + 'Position',[010 325 380 022].*WS); + +if strcmp(spm_platform('filesys'),'win') + off=100; + uicontrol(F,'Style','PopUp','Tag','DrivesPopup',... + 'ToolTipString','drives',... + 'HorizontalAlignment','Left',... + 'ForegroundColor','r',... + 'String',spm_get('DrivesPullDownStr'),... + 'Callback',['spm_get(''cd''),'... + 'set(gcbo,''String'',spm_get(''DrivesPullDownStr''))'],... + 'Position',[010+335-off 303 off 022].*WS); +else + off=0; +end +uicontrol(F,'Style','PopUp','Tag','SubDirsPopup',... + 'ToolTipString','cd to subdirectories of this directory',... + 'HorizontalAlignment','Left',... + 'ForegroundColor','r',... + 'String','SubDirectories...',... + 'Callback','spm_get(''cd'')',... + 'Position',[010 303 335-off 022].*WS); + +uicontrol(F,'Style','PushButton','Tag','CDhome',... + 'String','home',... + 'ToolTipString','cd to your home directory',... + 'ForegroundColor','r',... + 'CallBack',['spm_get(''cd'',''',strtrim(LastDirs(2,:)),''')'],... + 'Position',[345 303 045 022].*WS); + +uicontrol(F,'Style','Pushbutton',... + 'String','Filter',... + 'ToolTipString','reset filter to ''*''',... + 'CallBack','spm_get(''dir'',[],''*'')',... + 'UserData','*',... + 'Position',[010 276 040 026].*WS); + +uicontrol(F,'Style','Pushbutton','String','',... + 'ToolTipString','click to reset filter to initial value',... + 'CallBack',[ 'spm_get(''dir'',[],get(findobj(gcbf,''Tag'',',... + '''Filter''),''UserData''))'],... + 'Position',[048 276 099 026].*WS); + +uicontrol(F,'Style','Edit','Tag','Filter',... + 'String','*',... + 'ToolTipString','UNIX style file filter string - edit to change',... + 'UserData','*',... + 'BackgroundColor',[.8,.8,1],... + 'Callback','spm_get(''dir'')',... + 'Position',[050 278 095 022].*WS); + +uicontrol(F,'Style','Pushbutton','String','All',... + 'ToolTipString','select all items in this directory',... + 'Callback','spm_get(''All'',gcbf)',... + 'Position',[155 278 030 022].*WS); + +uicontrol(F,'Style','Pushbutton','String','Edit',... + 'ToolTipString','edit list of items',... + 'ForegroundColor','b',... + 'Callback','spm_get(''Edit'')',... + 'Position',[190 278 040 022].*WS); + +uicontrol(F,'Style','Pushbutton','String','Keybd',... + 'ToolTipString','switch to keyboard input of items',... + 'ForegroundColor','k',... + 'Callback','spm_get(''GUI2CmdLine'')',... + 'Position',[235 278 050 022].*WS); + +uicontrol(F,'Style','Pushbutton','String','Reset',... + 'ToolTipString','reset selection',... + 'ForegroundColor','r',... + 'Callback','spm_get(''Reset'',gcbf)',... + 'Position',[290 278 050 022].*WS); + +uicontrol(F,'Style','Pushbutton','String','Done',... + 'ToolTipString','done - press when completed selection of items',... + 'ForegroundColor','m',... + 'Tag','Done','UserData',1,... + 'Callback','spm_get(''Done'')',... + 'Interruptible','off','BusyAction','Cancel',... + 'Position',[345 278 045 022].*WS); + +uicontrol(F,'Style','Slider','Tag','ScrollBar',... + 'ToolTipString','scroll',... + 'Callback',[... + 'set(gca,''Units'',''Points''),',... + 'set(gca,''Position'',',... + 'get(gcbo,''UserData'')-[0,get(gcbo,''Value''),0,0])'],... + 'Position',[380 030 020 240].*WS) + +uicontrol(F,'Style','Frame','Tag','StatusArea',... + 'Position',[001 000 400 030].*WS); + +if exist('spm_help.m')==2 + uicontrol(F,'Style','Pushbutton','String','?',... + 'ToolTipString','help on using spm_get',... + 'ForegroundColor','g',... + 'Callback','spm_help(''spm_get.m'')',... + 'Position',[370 005 020 020].*WS); +end + +uicontrol(F,'Style','Text','Tag','StatusLine',... + 'String','',... + 'FontAngle','Italic',... + 'HorizontalAlignment','Center',... + 'ForegroundColor','w',... + 'Position',[010 005 355 020].*WS); + +set(F,'KeyPressFcn',... + 'spm_get(''FigKeyPressFcn'',get(gcbf,''CurrentCharacter''),gcbf)') + + +case 'figkeypressfcn' +%======================================================================= +% spm_help('FigKeyPressFcn',ch,F) +if nargin<3, F = gcbf; else, F = varargin{3}; end +if nargin<2, ch=get(F,'CurrentCharacter'); else, ch=varargin{2}; end + +%-Empty ch - shift/control/&c. +if isempty(ch), return, end + +%-Keyboard accelerators for item selection +%----------------------------------------------------------------------- +if any(abs(ch)==[10,11,19]) % ^J,^K,^S + H = flipud(findobj(get(get(F,'CurrentAxes'),'Children'),... + 'Flat','HandleVisibility','on')); + if isempty(H), return, end + h = max([0,findobj(H,'FontWeight','bold')]); + hPos = max([0;find(H==h)]); + if abs(ch)==19 & hPos + %- ^S - Select + switch get(h,'Tag') + case 'IName', spm_get('Add',h) + case 'SelIName', spm_get('Delete',h) + case 'DirName', spm_get('cd',get(h,'UserData')) + end + return + end + nhPos = max(1,min(hPos-2*(abs(ch)-10.5),length(H))); + if hPos, set(h,'FontWeight','normal'), end + set(H(nhPos),'FontWeight','bold') + return +end + +%-General Accelerators +%----------------------------------------------------------------------- +if any(abs(ch)==[32,4,16,2,27]) % Space,^D,^P,^B,Esc + switch abs(ch) + case {32,4} %- Space/^D - Done + spm_get('Done') + case 16 %- ^P - Change to MatLab pwd + spm_get('cd',pwd) + case 2 %- ^B - Keyboard + spm_get('GUI2CmdLine') + case 27 %- Esc - Reset + spm_get('Reset') + end +end + +%-Accelerators for WDir & Filter Edit widgets +%----------------------------------------------------------------------- +%-Edit which widget? WDir or Filter? +hCDpwd = findobj(F,'Tag','CDpwd'); +EditWDir = get(hCDpwd,'UserData'); +if EditWDir, h = findobj(F,'Tag','WDir'); + else, h = findobj(F,'Tag','Filter'); end +str = get(h,'String'); + +if abs(ch)==9 %- ^I - reset string + str = get(h,'UserData'); +elseif abs(ch)==5 %- ^E - switch between Edit widgets, reset strings + set(hCDpwd,'UserData',~EditWDir) + str = get(h,'UserData'); +elseif abs(ch)==23 %- ^W - word delete + tmp = max(find(str==filesep)); + if ~isempty(tmp), str(tmp:end)=[]; end +elseif abs(ch)==13 %- Return - Goto topic / apply filter + if EditWDir, spm_get('cd',str) + else, spm_get('dir'), end + return +elseif any(abs(ch)==[32:126]) + str = [str, ch]; +elseif abs(ch)==21 %- ^U - kill + str = ''; +elseif any(abs(ch)==[8,127]) %-BackSpace or Delete + if length(str), str(length(str))=''; end +else %-Other character + return +end +set(h,'String',str) + + +case 'initialise' +%======================================================================= +% [F,cF] = spm_get('Initialise',Vis,n,Prompt,Filter,WDir) +% (Re)Initialise SelFileWin, create one if necessary. + +if nargin<6 WDir=''; else WDir=varargin{6}; end +if nargin<5 + Filter=0; +else + Filter=varargin{5}; +end +if nargin<4 Prompt='Select files...'; else Prompt=varargin{4}; end +if nargin<3 n=struct('fi',1,'mn',0,'mx',Inf); else n=varargin{3}; end +if nargin<2 Vis='on'; else Vis=varargin{2}; end + +%-Recover SelFileWin figure number +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); + +cF = get(0,'CurrentFigure'); %-Save current figure + +switch lower(Vis), case 'close' + close(F) + varargout = {[],cF}; + return +case {'off','reset'} + varargout = {F,cF}; %-Return figure handles + if isempty(F), return, end %-...if no SelFileWin + varargout = {F,cF}; %-Return figure handles + set(F,'Visible','off') %-Make window Invisible + set(findobj(F,'Tag','Done'),'UserData',1) %-Set Done UserData to 1 + if strcmp(lower(Vis),'reset') + set(findobj(F,'Tag','Done'),'UserData',-1) + end + delete(get(F,'CurrentAxes')) %-delete 'dir' axes + drawnow + return +case 'on' + if isempty(F), F=spm_get('CreateFig'); end %-Create SelFileWin + varargout = {F,cF}; %-Return figure handles + set(findobj(F,'Tag','Done'),'UserData',0) %-Init. Done UserData + delete(get(F,'CurrentAxes')) %-delete 'dir' axes + set(findobj(F,'Tag','P'),'UserData','') %-clear P + set(findobj(F,'Tag','Prompt'),... + 'String',Prompt,... + 'ToolTipString',Prompt,... + 'UserData',n) + %-Reset prompt, & n + spm_get('StatusLine',0,n,F) %-Reset StatusLine + set(findobj(F,'Tag','CDpwd'),'UserData',1) %-KeyPressFcn to edit + % WDir widget initially + %-Filter string: Only set if different to previously passed one + % (held as UserData of Filter Edit uicontrol) + if ischar(Filter) + if ~strcmp(Filter,get(findobj(F,'Tag','Filter'),'UserData')) + set(findobj(F,'Tag','Filter'),'String',Filter,'UserData',Filter) + end + end + + %-Change to new working directory, if specified, else display current + if ~isempty(WDir) + spm_get('cd',WDir) %-Change directory + else + spm_get('dir') %-Show current dir. + end + + %-Popup figure, retaining CurrentFigure + figure(F),drawnow %-PopUp figure + set(0,'CurrentFigure',cF) %-Return to prev. figure + +otherwise + error('Unrecognised ''Vis'' option') +end + + + +case 'statusline' +%======================================================================= +% spm_get('StatusLine',nP,n,F) +if nargin<4, F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); + else, F = varargin{4}; end +if nargin<3, n=get(findobj(F,'Tag','Prompt'),'UserData');else,n=varargin{3}; end +if nargin<2, nP=size(get(findobj(F,'Tag','P'),'UserData'),1);else,nP=varargin{2}; end + +str=['Selected ',int2str(nP)]; +if (n.mn==n.mx), str=sprintf('%s/%d',str,abs(n.mx)); end +if n.fi + str = [str,' file']; + if nP~=1, str=[str,'s']; end +else + str = [str,' director']; + if nP==1, str=[str,'y']; else, str=[str,'ies']; end +end + +if (n.mn~=n.mx) + if n.mn==0 + if isfinite(n.mx) + str=sprintf('%s (max %d)',str,n.mx); + end + else + if isinf(n.mx) + str=sprintf('%s (min %d)',str,n.mn); + else + str=sprintf('%s (min %d, max %d)',str,n.mn,n.mx); + end + end +end + + +if (nP>=n.mn) & (nP<=n.mx) + str = [str,', press "Done" when finished.']; +else + str = [str,'.']; +end + +set(findobj(F,'Tag','StatusLine'),'String',str) + + +case 'cd' +%======================================================================= +% spm_get('cd',NewDir,bNoDirList) + +%-Condition arguments +%----------------------------------------------------------------------- +if (nargin<3), bDirList=1; else, bDirList = ~varargin{3}; end +if (nargin<2), NewDir=''; else, NewDir=varargin{2}; end + +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +set(F,'Pointer','Watch') +WDir=get(findobj(F,'Tag','WDir'),'UserData'); + +if nargin<2 + %-Current object contains NewDir, either UIEdit, UIPopMenu or text + NewDir=get(gcbo,'String'); + if strcmp(get(gcbo,'Style'),'popupmenu') + val = get(gcbo,'Value'); + if val==1 set(F,'Pointer','Arrow'), return, end + NewDir=NewDir(val,:); + set(gcbo,'Value',1) + end +else + NewDir=varargin{2}; +end + + +%-Condition directory path +%----------------------------------------------------------------------- +NewDir = spm_get('CPath',NewDir,WDir); + + +%-Changing directory, delete current directory listing (Done again in +% Action=='dir', but neater to do here in advance on this occasion) +%----------------------------------------------------------------------- +delete(get(F,'CurrentAxes')) + + +%-Set up LastDirs +%----------------------------------------------------------------------- +%-Recover LastDirs & size of fixed part from popup menu object +LastDirs = get(findobj(F,'Tag','LastDirsPopup'),'String'); LastDirs(1,:)=[]; +Fs = get(findobj(F,'Tag','LastDirsPopup'),'UserData'); + +%-Add new directory +LastDirs = strvcat(NewDir,LastDirs); + +%-Extract fixed and variable parts of LastDirs +FLastDirs = LastDirs(end-Fs+1:end,:); +LastDirs(end-Fs+1:end,:)=[]; + +%-Delete any replications of NewDir within the variable part of LastDirs +if size(LastDirs,1)>1 + IDRows = 1+find(all( LastDirs(2:end,:) == ... + repmat(LastDirs(1,:),size(LastDirs,1)-1,1) ,2 ) ); + LastDirs(IDRows,:)=[]; +end + +%-Delete NewDir from top of LastDirs if present in fixed part of LastDirs +if any(all(FLastDirs==repmat(LastDirs(1,:),Fs,1),2)), LastDirs(1,:)=[]; end + +%-Lose directories from the bottom of variable LastDirs if oversize +Vs = 10; %-Maximum allowable number of variable LastDirs entries +if size(LastDirs,1)>Vs, LastDirs(Vs+1:end,:)=[]; end + +%-Put LastDirs and FLastDirs back together +LastDirs = [LastDirs; FLastDirs]; + + +%-Write LastDirs to LastDirsPopup, write new directory to WDir Edit widget +%----------------------------------------------------------------------- +set(findobj(F,'Tag','LastDirsPopup'),... + 'String',strvcat('Previous Directories...',LastDirs)) +set(findobj(F,'Tag','WDir'),'String',NewDir,'UserData',NewDir) + + +%-Display new directory, unless supressed +%----------------------------------------------------------------------- +if bDirList + spm_get('dir') +else + set(findobj(F,'Tag','SubDirsPopup'),'Value',1,... + 'String','SubDirectories...') + set(F,'Pointer','Arrow') + drawnow +end + + +case 'dir' +%======================================================================= +% spm_get('dir',WDir,Filter,NoComp) + +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +set(F,'Pointer','Watch') +delete(get(F,'CurrentAxes')), drawnow + +%-Condition parameters and setup variables +%----------------------------------------------------------------------- +if nargin<4, NoComp=0; else, NoComp=1; end +if nargin<3, + Filter=''; +else, + Filter=varargin{3}; +end +if nargin<2 | isempty(varargin{2}) + WDir = get(findobj(F,'Tag','WDir'),'UserData'); +else + WDir = strtrim(varargin{2}); +end + +n = get(findobj(F,'Tag','Prompt'),'UserData'); + +%-Sort out Filter +%----------------------------------------------------------------------- +if isempty(Filter) + Filter = get(findobj(F,'Tag','Filter'),'String'); + if isempty(Filter), Filter='*'; end +end +set(findobj(F,'Tag','Filter'),'String',Filter) + +%-Write current directory to WDir widget, if new directory specified +%----------------------------------------------------------------------- +if nargin>1 + set(findobj(F,'Tag','WDir'),'String',WDir,'UserData',WDir) +end + +%-Set up axis +%----------------------------------------------------------------------- +Rec = [0.02 0.086 0.92 0.58]; +hAxes = axes('Parent',F,'Tag','hAxes',... + 'Position',Rec,... + 'DefaultTextInterpreter','none',... + 'Units','Points',... + 'Visible','off'); +y = get(hAxes,'Position'); +y0 = floor(y(3)); +dy = 22; +set(hAxes,'Ylim',[0,y0]) + + +%-List current directory +%----------------------------------------------------------------------- +[Files,Dirs] = spm_list_files_expand(WDir,Filter,ListOpts); +if isempty(Dirs) + text(0,y0,'Permission denied, or non-existent directory',... + 'Parent',hAxes,'FontWeight','bold','Color','r'); + set(findobj(F,'Tag','ScrollBar'),'Visible','off') + set(F,'Pointer','Arrow') + return +else %-Exclude "." directory from Dirs, exclude ".." if in root + %-Exclude ".." from DirItems (used when selecting directories) + Dirs(Dirs(:,1)=='.',:)=[]; + DirItems = strvcat('.',Dirs); + if ~isroot(WDir), Dirs=strvcat('..',Dirs); end +end + +%-Create list of directories in pulldown menu +%----------------------------------------------------------------------- +set(findobj(F,'Tag','SubDirsPopup'),'Value',1,... + 'String',strvcat('SubDirectories...',Dirs)) + +%-Create list of directories with appropriate 'ButtonDownFcn': - +%----------------------------------------------------------------------- +y = y0-dy; +if size(Dirs,1) + for i = 1:size(Dirs,1) + h = text(0,y,strtrim(Dirs(i,:)),... + 'Parent',hAxes,... + 'Tag','DirName',... + 'FontWeight','bold','Color','r',... + 'UserData',strtrim(Dirs(i,:)),... + 'ButtonDownFcn','spm_get(''cd'',get(gcbo,''UserData''))',... + 'HandleVisibility','off'); + y = y - dy; + end + %-Note lowest position used (in points) + set(h,'Units','Points') + my = get(h,'Position')*[0;1;0]; +else + my = 0; +end + +%-Files or directories? +%----------------------------------------------------------------------- +if n.fi + %-Select file(s) - omit ".*" dot files + if ~isempty(Files), Files(Files(:,1)=='.',:)=[]; end + Items = Files; +else %-Select directory/ies - don't compress the listing + Items = DirItems; + NoComp = 1; +end + +%-Compressed summary view, or full view? +%----------------------------------------------------------------------- +if ~NoComp & size(Items,1)>32 + %-Use a compressed summary view + if Filter(end)=='*' + [IName,ItemPos] = spm_get('FileSummary',Items); + else + [IName,ItemPos] = spm_get('FileSummary',Items,'front',Filter); + end + text(0.45,y0,'Summary View - Click to expand',... + 'Parent',hAxes,... + 'Color','w',... + 'FontSize',spm('FontSize',9),... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic',... + 'ButtonDownFcn','spm_get(''dir'',[],[],1)',... + 'HandleVisibility','off'); +else + %-Use a standard view, each item with it's own representation + IName = Items; ItemPos = [1:size(Items,1)]'; +end + +%-Create list of Items with appropriate 'ButtonDownFcn': - +%----------------------------------------------------------------------- +y = y0-dy; +if size(IName,1) + for i = 1:size(IName,1) + cIName = IName(i,IName(i,:)~=' '); + cItemPos = ItemPos(i,ItemPos(i,:)>0); + nItems = length(cItemPos); + cItems = strtrim(Items(cItemPos,:)); + h = text(0.4,y,cIName,... + 'Parent',hAxes,... + 'Tag','IName',... + 'UserData',cItems,... + 'Color','k',... + 'ButtonDownFcn','spm_get(''Add'')',... + 'HandleVisibility','on'); + if nItems>1; + h = text(0.39,y-3,int2str(sum(ItemPos(i,:)>0)),... + 'Parent',hAxes,... + 'Color','w',... + 'FontSize',spm('FontSize',8),... + 'FontAngle','Italic',... + 'HorizontalAlignment','right',... + 'UserData',cIName,... + 'ButtonDownFcn',... + 'spm_get(''dir'',[],get(gcbo,''UserData''),1)',... + 'HandleVisibility','off'); + end + y = y - dy; + end + %-Note lowest position used (in points) + set(h,'Units','Points') + my = min(my,get(h,'Position')*[0;1;0]); +end + +%-Setup scrollbar +%----------------------------------------------------------------------- +h = findobj(F,'Tag','ScrollBar'); +if my>0 + set(h,'Visible','off') +else + set(h, 'UserData', get(hAxes,'Position'),... + 'Value', 0,... + 'Max', 0,... + 'Min', my-dy,... + 'SliderStep', min([0.5,1],[3*dy,(y0-dy)]/(-my+dy)),... + 'Visible', 'on') +end + +%-Done +%----------------------------------------------------------------------- +set(F,'Pointer','Arrow') + + +case 'strsort' +%======================================================================= +% [sS,I]=spm_get('StrSort',S) +% Utility string sorting routine for string matrices +if nargin<2, error('Sort what?'), else, S = varargin{2}; end + +if size(S,2)<=3 + a = min(abs(S(:)')); + b = max(abs(S(:)'))+1; + i = (b-a).^[size(S,2)-1:-1:0]; + [null,I] = sort(abs(S)*i'); + sS = S(I,:); +else + lS = size(S,2); + hS = S(:,1:3); + tS = S; + tS(:,1:3) = []; + [null,tI] = spm_get('StrSort',tS); + [null,hI] = spm_get('StrSort',hS(tI,:)); + I = tI(hI); + sS = S(I,:); +end +varargout = {sS,I}; + + +case 'strfliplr' +%======================================================================= +% fS = spm_get('strfliplr',S) +if nargin<2, error('Flip what?'), else, S = varargin{2}; end + +%-FlipLR the Fnames matrix, but watch out for trailing blanks/spaces +[nS,Sl] = size(S); +fS = char(zeros(nS,Sl)); +for i = 1:nS + c = max(find(S(i,:)~=' ')); + fS(i,:) = S(i,[c:-1:1,Sl:-1:c+1]); +end +varargout = {fS}; + + +case 'filesummary' +%======================================================================= +% [FSpecs,FnamePos]=spm_get('FileSummary',Fnames,Cend,Filter,len) +if nargin<5, len = 3; else len = varargin{5}; end +if nargin<4 | isempty(varargin{4}), + Filter = '*'; +else + Filter = varargin{4}; +end +if nargin<3, Cend='both'; else, Cend = varargin{3}; end +if nargin<2 | isempty(varargin{2}), error('Specify Fnames to summarise') +else Fnames = varargin{2}; end +%-Implicit assumption in this code is that no two files have the same name + +if strcmp(Cend,'front') + if size(Fnames,1)==1 | size(Fnames,2)0); + if length(chI) == 1 + %-Single file + %FSpecs = strvcat(FSpecs,hSpecs(i,hSpecs(i,:)~=' ')); + %KND: + FSpecs = strvcat(FSpecs,hSpecs(i,:)); + tmp = max([1,size(FnamePos,2)]); + FnamePos = [FnamePos,... + zeros(size(FnamePos).*[1 -1]+[0,tmp]);... + chI, zeros(1,tmp-1)]; + else + %-Multiple files - process by common endings + Cfnames = Fnames(chI,:); + %-Chop off common beginning + Cfnames(:,1:find(hSpecs(i,:)=='*')-1) = []; + %-Watch out for blank lines (e.g for files abc & abcde) + bI = find(all(Cfnames==' ',2)); + if ~isempty(bI) + %-Assumming unique input => one blank line at most + % NB: This may change ordering of groups by first member + FSpecs = strvcat(FSpecs,... + hSpecs(i,1:find(hSpecs(i,:)=='*')-1) ); + tmp = max([1,size(FnamePos,2)]); + FnamePos = [FnamePos,... + zeros(size(FnamePos).*[1 -1]+[0,tmp]);... + chI(bI), zeros(1,tmp-1)]; + Cfnames(bI,:) = []; + chI(bI) = []; + end + %-Even if we've deleted a blank line, there'll be some left + %-Look for common endings + [tSpecs,tI] = spm_get('FileSummary',Cfnames,'end',Filter,len); + %-If no common endings then don't expand to individual files! + if size(tI,1)>1 & size(tI,2)==1 + tSpecs = '*'; + tI = tI'; + end + for j = 1:size(tSpecs,1) + cI = chI(tI(j,tI(j,:)>0)); + if length(cI) == 1 + %-Unique, don't bother with '*'s + cFSpec = [hSpecs(i,1:find(hSpecs(i,:)=='*')-1),... + tSpecs(j,1:max(find(tSpecs(j,:)~=' ')) ) ]; + else + %-Don't double '*'s + cFSpec = [hSpecs(i,hSpecs(i,:)~=' '),... + tSpecs(j,2:max(find(tSpecs(j,:)~=' ')) ) ]; + end + FSpecs = strvcat(FSpecs,cFSpec); + tmp = max([length(cI),size(FnamePos,2)]); + FnamePos = [FnamePos,... + zeros(size(FnamePos).*[1 -1]+[0,tmp]);... + cI, zeros(1,tmp-length(cI))]; + end + end + end +else + error('Invalid Cend specifier') +end +varargout = {FSpecs,FnamePos}; + + +case 'add' +%======================================================================= +% spm_get('Add',H) +% Add filename to current list +%-H - [Optional] (vector of) handles to file/dir name objects +% + +%-Recover variables from holding objects +%----------------------------------------------------------------------- +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +SelType = get(F,'SelectionType'); +n = get(findobj(F,'Tag','Prompt'),'UserData'); +P = get(findobj(F,'Tag','P'),'UserData'); +WDir = get(findobj(F,'Tag','WDir'),'UserData'); + +if (nargin==2) + %-Multiple handles passed by 'All' CallBack + H=varargin{2}; +else + %-'Add' called by item callback - get handle & check selection + H=gcbo; + if strcmp(SelType,'extend') + IName = get(H,'String'); + if any(IName=='*') + spm_get('dir','',IName,1) + return + else + return + end + elseif strcmp(SelType,'alt') + spm_get('Add',H) + spm_get('Done') + return + end +end + +%-Add items to P (until P would be overfull) +%----------------------------------------------------------------------- +for h = H' + IName = get(h,'String'); + Items = get(h,'UserData'); + nItems = size(Items,1); + nP = size(P,1); + + %-Don't add any more if #items has been specified, + % and P would be overfull + if (nP+nItems>n.mx), break, end + + %-Add items to P + if WDir(end)~=filesep, WDir = [WDir,filesep]; end + FPath = [repmat(WDir,nItems,1),Items]; + P = strvcat(P,FPath); + if nItems==1 + tmp = [int2str(nP+1),' :',IName]; + else + tmp = [int2str(nP+1),'-',int2str(nP+nItems),' :',IName]; + end + set(h,'String',tmp,'Color','b',... + 'Tag','SelIName',... + 'ButtonDownFcn','spm_get(''Delete'')') +end + +%-Return new P to holding object +%----------------------------------------------------------------------- +set(findobj(F,'Tag','P'),'UserData',strtrim(P)); + +%-Update StatusLine +%----------------------------------------------------------------------- +spm_get('StatusLine',size(P,1),n,F) + + +case 'delete' +%======================================================================= +% spm_get('Delete',h) +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +if nargin<2, h=gcbo; else, h=varargin{2}; end +WDir = get(findobj(F,'Tag','WDir'),'UserData'); +if WDir(end)~=filesep, WDir = [WDir,filesep]; end +P = get(findobj(F,'Tag','P'),'UserData'); +n = get(findobj(F,'Tag','Prompt'),'UserData'); +IName = get(h,'String'); +IName(1:find(IName==':')) = []; +Items = get(h,'UserData'); +nItems = size(Items,1); +FPath = [repmat(WDir,nItems,1),Items]; +nP = size(P,1); + +%-Compare Items with end of P (Can only delete from the end) +tmp = strvcat(P(nP-(nItems-1):nP,:),FPath); +if all(all(tmp(1:nItems,:)==tmp(nItems+1:2*nItems,:))) + P(nP-(nItems-1):nP,:)=[]; + if ~isempty(P), P(:,all(P==' ',1))=[]; else, P=''; end + set(findobj(F,'Tag','P'),'UserData',P); + set(h,'String',IName,'Color','k',... + 'Tag','IName',... + 'ButtonDownFcn','spm_get(''Add'')') + spm_get('StatusLine',size(P,1),n,F) +end + + +case 'reset' +%======================================================================= +% spm_get('Reset',F) +if nargin<2, F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); + else, F = varargin{2}; end +set(findobj(F,'Tag','P'),'UserData',[]); +spm_get('dir') +spm_get('StatusLine') + + +case 'all' +%======================================================================= +% spm_get('All',F) +if nargin<2, F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); + else, F = varargin{2}; end +set(F,'Pointer','Watch') +H = flipud(findobj(get(get(F,'CurrentAxes'),'Children'),'Flat','Tag','IName')); +spm_get('Add',H); +set(F,'Pointer','Arrow') + + +case 'cmdline' +%======================================================================= +% P = spm_get('CmdLine',n,Prompt,P,WDir,AllowEnd) +if nargin<6, AllowEnd=0; else AllowEnd=varargin{6}; end +if nargin<5, WDir=''; else WDir=varargin{5}; end +if isempty(WDir), WDir=pwd; else, WDir=strtrim(WDir); end +if nargin<4, P=[]; else P=varargin{4}; end +if nargin<3, Prompt='Select files...'; else Prompt=varargin{3}; end +if nargin<2, n=struct('fi',1,'mn',0,'mx',Inf); else n=varargin{2}; end + +if n.mx==0, varargout={''}; return, end +nP=size(P,1); + +%-Print prompt +%----------------------------------------------------------------------- +fprintf('\n'), fprintf('%c',repmat('=',1,70)), fprintf('\n') +fprintf('\t%s\n',Prompt) +fprintf('%c',repmat('=',1,70)), fprintf('\n') +fprintf('Current working directory: %s\n',WDir) +fprintf('(Prepended to relative paths)\n') +if nP>0 + fprintf('\nAlready selected:\n') + for pP = [1:size(P,1)], fprintf('\t%s\n',P(pP,:)), end +end + +if nP>=n.mx + fprintf('\nMax # items already selected: Returning...\n\n' ) + varargout={P}; + return +end + +%-Print prompts for input +%----------------------------------------------------------------------- +fprintf('\nEnter paths ') +if n.fi + str = 'file'; if n.mx>1, str=[str,'s']; end +else + str = 'director'; if n.mx==1, str=[str,'y']; else, str=[str,'ies']; end +end +if AllowEnd | n.mn==0 + if isfinite(n.mx) + fprintf('to at most %d %s:\n',n.mx,str) + else + fprintf('to %s:\n',str) + end +else + if (n.mn==n.mx) + fprintf('to %d %s:\n',n.mx,str) + else + if isinf(n.mx) + fprintf('to at least %d %s:\n',n.mn,str) + else + fprintf('to %d-%d %s:\n',n.mn,n.mx,str) + end + end +end + +%-AllowEnd if asked for, or if a range of item numbers is OK +%----------------------------------------------------------------------- +Tstr = 'END'; +if AllowEnd | (n.mn~=n.mx) + fprintf(' (Type "%s" to terminate input.)\n',Tstr) +end + +%-Get files +%----------------------------------------------------------------------- +Done=0; +while ~( Done | (nP>=n.mx) ) + %-Get input + str = []; while isempty(str) + str=dstrtrim(input(sprintf(' %3d : ',nP+1),'s'));end + %-Prepend WDir to incomplete pathnames + if (~isabspath(str))&(~strcmp(str,Tstr)), str=fullfile(WDir,str); end + if n.fi,OK=exist(str)==2;else,OK=exist(str)==7;end + OKend = AllowEnd | (nP>=n.mn&nP<=n.mx); + while ~( OK | (strcmp(str,Tstr) & OKend) ) + if strcmp(str,Tstr) + fprintf('%c\tSelect %d-%d items!\n',7,n.mn,n.mx) + else, fprintf('%c\t%s isn''t valid!\n',7,str), end + str=[]; while isempty(str) + str=dstrtrim(input(sprintf(' %3d : ',nP+1),'s'));end + if (~isabspath(str))&(~strcmp(str,Tstr)) + str = fullfile(WDir,str); end + if n.fi,OK=exist(str)==2;else,OK=exist(str)==7;end + OKend = AllowEnd | (nP>=n.mn&nP<=n.mx); + end + if ~strcmp(str,Tstr), P=strvcat(P,str); end + nP = nP+1; + Done = strcmp(str,Tstr); +end + +varargout = {P}; + + +case 'gui2cmdline' +%======================================================================= +% P = spm_get('GUI2CmdLine') + +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +Prompt = get(findobj(F,'Tag','Prompt'),'String'); +n = get(findobj(F,'Tag','Prompt'),'UserData'); +WDir = get(findobj(F,'Tag','WDir'),'UserData'); +P = get(findobj(F,'Tag','P'),'UserData'); + +WS = get(F,'Position'); WS = [WS(3)/400,WS(4)/395,WS(3)/400,WS(4)/395]; +Handles = []; +h = uicontrol(F,'Style','Frame',... + 'Position',[000 000 400 395].*WS); +Handles = [Handles, h]; + +h = uicontrol(F,'Style','Text',... + 'String',Prompt,... + 'ToolTipString',Prompt,... + 'FontName',spm_platform('font','times'),... + 'FontWeight','Bold',... + 'FontAngle','Italic',... + 'FontSize',spm('FontSize',16),... + 'ForegroundColor','k',... + 'HorizontalAlignment','Center',... + 'Position',[010 370 380 022].*WS); +Handles = [Handles, h]; + +h = uicontrol(F,'Style','Frame',... + 'Position',[001 001 400 030].*WS); +Handles = [Handles, h]; + +h = uicontrol(F,'Style','Text',... + 'String','Use command window...',... + 'FontAngle','Italic',... + 'HorizontalAlignment','Center',... + 'ForegroundColor','w',... + 'Position',[020 005 360 020].*WS); +Handles = [Handles, h]; + +PNew = spm_get('CmdLine',n,Prompt,P,WDir,1); + +if ~strcmp(P(:),PNew(:)) + set(findobj(F,'Tag','P'),'UserData',PNew); + spm_get('dir') + spm_get('StatusLine',size(PNew,1),n,F) +end + +delete(Handles); + + +case 'edit' +%======================================================================= +% spm_get('Edit') + +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +n = get(findobj(F,'Tag','Prompt'),'UserData'); + +set(F,'Units','Pixels'); +WS = get(F,'Position'); WS = [WS(3)/400,WS(4)/395,WS(3)/400,WS(4)/395]; + +EditHandles = []; + +h = uicontrol(F,'Style','Frame',... + 'Tag','EditHandles',... + 'Position',[001 001 400 395].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Text',... + 'String',get(findobj(F,'Tag','Prompt'),'String'),... + 'FontName',spm_platform('font','times'),... + 'FontWeight','Bold',... + 'FontAngle','Italic',... + 'FontSize',spm('FontSize',16),... + 'ForegroundColor','k',... + 'HorizontalAlignment','Center',... + 'Position',[010 370 380 022].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Text',... + 'String','Edit the filename window...',... + 'ForegroundColor','w',... + 'HorizontalAlignment','Left',... + 'Position',[010 347 210 022].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Pushbutton','String','Cancel',... + 'ForegroundColor','r',... + 'Callback','spm_get(''EditDone'',''Cancel'')',... + 'Position',[220 347 070 022].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Pushbutton','String','OK',... + 'ForegroundColor','m',... + 'Callback','spm_get(''EditDone'',''OK'')',... + 'Position',[310 347 070 022].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Edit',... + 'String',cellstr(char(get(findobj(F,'Tag','P'),'UserData'))),... + 'Tag','EditWindow','UserData',0,... + 'HorizontalAlignment','Left',... + 'ForegroundColor','b','BackgroundColor',[.8,.8,1],... + 'Max',2,... + 'Callback','set(gco,''UserData'',1)',... + 'Position',[010 040 380 300].*WS); +EditHandles = [EditHandles, h]; + +h = uicontrol(F,'Style','Frame',... + 'Position',[001 001 400 030].*WS); +EditHandles = [EditHandles, h]; + +str=[]; if isfinite(n.mx), str=['Use only top ',int2str(n.mx),' lines. ']; end +h = uicontrol(F,'Style','Text',... + 'String',[str,'(Blank lines will be removed)'],... + 'FontAngle','Italic',... + 'HorizontalAlignment','Center',... + 'ForegroundColor','w',... + 'Position',[020 005 360 020].*WS); +EditHandles = [EditHandles, h]; + +set(findobj(F,'Tag','EditHandles'),'UserData',EditHandles) + + +case 'editdone' +%======================================================================= +% spm_get('EditDone',OK) +if nargin<2, OK=0; else, OK=strcmp(varargin{2},'OK'); end +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); + +EditHandles = get(findobj(F,'Tag','EditHandles'),'UserData'); +set(EditHandles,'Visible','off') +h_EditWindow = findobj(F,'Tag','EditWindow'); + +if OK & get(h_EditWindow,'UserData') + %-Only update if OK was pressed, and there was an edit. + P = get(h_EditWindow,'String'); + n = get(findobj(F,'Tag','Prompt'),'UserData'); + %-Condition P, by removing blank lines and truncating to n items. + P = P(~strcmp(P,'')); + if (isfinite(n.mx))&(~isempty(P)), P=P(1:min(length(P),n.mx)); end + %-Write P to 'P' 'Tag'ged object + set(findobj(F,'Tag','P'),'UserData',char(P)); + %-Redo directory listing + spm_get('dir') + %-Redo status line + spm_get('StatusLine',size(P,1),n,F) +end +delete(EditHandles), drawnow + + +case 'done' +%======================================================================= +% spm_get('Done') +F = findobj(get(0,'Children'),'Flat','Tag','SelFileWin'); +n = get(findobj(F,'Tag','Prompt'),'UserData'); + +%-If #files was specified, and not enough have been selected, then return +nP = size(get(findobj(F,'Tag','P'),'UserData'),1); +if (nPn.mx) + if (n.mn==n.mx) + str = sprintf('Must select %d item(s)!',n.mx); + else + str = sprintf('Must select %d-%d items!',n.mn,n.mx); + end + spm('Beep') + msgbox(str,sprintf('%s%s: %s...',spm('ver'),... + spm('GetUser',' (%s)'),mfilename),'error','non-modal') + drawnow + + % Not sure about this bit - JA + % set(F,'windowstyle','modal') + + return +end + +%-Done, set Done UserData tag for handling +set(findobj(F,'Tag','Done'),'UserData',1) + + +case 'cpath' +%======================================================================= +% cpath = spm_get('cpath',path,cwd) +if nargin<3, cwd=pwd; else, cwd=spm_get('CPath',varargin{3}); end +if nargin<2, error('insufficient arguments'), end +cpath = cellstr(varargin{2}); + +sepchar = filesep; %-File seperator character +dubsep = [sepchar,sepchar]; %-Double file separator character +rootlen = spm_platform('rootlen'); %-Length of root paths ('/' & 'C:\' &c) + +for i=1:prod(size(cpath)) + + %-Prepend cwd to relative pathnames + %--------------------------------------------------------------- + if ~isabspath(cpath{i}), cpath{i}=fullfile(cwd,cpath{i}); end + + %-Sort out stationary relative pathnames './' & '/.' + %--------------------------------------------------------------- + %-Remove midpath '/./' + cpath{i}=strrep(cpath{i},[sepchar,'.',sepchar], sepchar); + + %-Remove '.' from trailing '/.' + if length(cpath{i})>=2 & strcmp(cpath{i}(end-1:end),[sepchar,'.']) + cpath{i}(end)=''; end + + %-Remove trailing '/'s (unless root, in which case ensure trailing '/') + if isroot(cpath{i}) + if cpath{i}(end)~=sepchar, cpath{i}(end+1)=sepchar; end + else + while(length(cpath{i})>rootlen) & cpath{i}(end)==sepchar + cpath{i}(end)=''; + end + end + + %-Remove any residual '//'s + while length(cpath{i})>=2 & length(findstr(cpath{i},dubsep)) + if (ispc & strncmp(dubsep, cpath{i},2)) + %initial '\\' is used for network drive in Windows' world + cpath{i}= [sepchar , strrep(cpath{i},dubsep,sepchar)]; + else + cpath{i}=strrep(cpath{i},dubsep,sepchar); + end + end + + %-Sort out relative pathnames '/..' + %--------------------------------------------------------------- + %-Process midpath '/../' + t0 = 0; + downstr = [sepchar,'..',sepchar]; + while length(cpath{i})>=rootlen+4 & max([0,findstr(cpath{i},downstr)])>t0 + t2 = t0+min(findstr(cpath{i}(t0+1:end),downstr)); + t1 = t0+max([0,find(cpath{i}(t0+1:t2-1)==sepchar)]); + if t1==t0 | strcmp(cpath{i}(t1:t2),downstr) + t0=t2; + else + cpath{i}(t1:t2+2)=''; + end + end + + %-Process trailing '/..' (Don't remove first '/') + if length(cpath{i})>rootlen+2 & ... + strcmp(cpath{i}(end-2:end),[sepchar,'..']) + t2 = length(cpath{i})-2; + t1 = t0+max([0,find(cpath{i}(t0+1:t2-1)==sepchar)]); + if t1~=t0 & ~strcmp(cpath{i}(t1:t2),downstr) + cpath{i}(max(t1,rootlen+1):t2+2)=''; + end + end + + %-Remove any leading '/../'s + while length(cpath{i})>=rootlen+3 & ... + strcmp(cpath{i}(rootlen+[0:3]),downstr) + cpath{i}(rootlen+[1:3])=''; + end + + %-Canonicalise '/..' to '/' + if length(cpath{i})==rootlen+2 & ... + strcmp(cpath{i}(rootlen+[0:2]),[sepchar,'..']) + cpath{i}(rootlen+[1:2])=''; + end + + %-Remove any residual '//'s + while length(cpath{i})>=2 & length(findstr(cpath{i},dubsep)) + cpath{i}=strrep(cpath{i},dubsep,sepchar); end + + + %-Final canonicalisations for relative pathnames + %--------------------------------------------------------------- + % %-Remove leading './' + % if length(cpath{i})>2 & strcmp(cpath{i}(1:2),['.',sepchar]) + % cpath{i}(1:2)=''; end + + %-Canonicalise leading './../' to '../' + if length(cpath{i})>5 & strcmp(cpath{i}(1:5),['.',downstr]) + cpath{i}(1:2)=''; end + %-Canonicalise './..' to '..' + if strcmp(cpath{i},['.',sepchar,'..']), cpath{i}='..'; end + +end + +if ischar(varargin{2}), varargout={char(cpath)}; else, varargout={cpath}; end + + +case 'drivespulldownstr' +%======================================================================= +% str = spm_get('DrivesPullDownStr') +drivestr = spm_win32utils('drives'); +n = length(drivestr); +varargout = ... + {['Drives...',reshape(['|'*ones(1,n);drivestr;':'*ones(1,n)],1,3*n)]}; + + +case 'files' +%======================================================================= +% FORMAT [P,dir] = spm_get('Files',dir,fil) +if nargin<3, + fil='*'; +else, + fil = varargin{3}; +end +if nargin<2, dir='.'; else, dir = varargin{2}; end +dir = spm_get('CPath',dir); +[P,null] = spm_list_files_expand(dir,fil,ListOpts); + +%-Make into full pathnames if nargout<2 +if ~isempty(P) & nargout<2 + nP = size(P,1); + P = [repmat(dir,nP,1), repmat(filesep,nP,1), P]; +end + +varargout = {P,dir}; + + +otherwise +%======================================================================= +error('Illegal Action string') + + +%======================================================================= +end + + +%======================================================================= +%- S U B - F U N C T I O N S +%======================================================================= + +function so = dstrtrim(si) +%======================================================================= +if nargin==0, error('insufficient arguments'), end +if isempty(si), so=''; return, end +if ~ischar(si), error('input must be a string'), end + +b = any((si~=' ' & si~=0),1); +if all(~b), so=''; return, end +so = si(:,max(1,min(find(b))):min(max(find(b)),length(b))); + + +function rootf = isroot(path) %%-Platform specifics (MBrett) +%======================================================================= +%-Returns true if path is root directory, else false +switch (spm_platform('filesys')) +case 'unx' + rootf = strcmp(path,'/'); +case 'win' + %-Accepts e.g e: and e:\ as root paths + if (length(path)==2 & path(2)==':') | ... + (length(path)>2 & strcmp(path(2:end),':\')) + rootf = 1; + else + rootf = 0; + end +otherwise + error('isroot not coded for this filesystem'); +end + + +function absf = isabspath(path) %%-Platform specifics (MBrett) +%======================================================================= +%-Returns true if path is absolute, false if relative (or empty) +switch (spm_platform('filesys')) +case 'unx' + if (~isempty(path) & path(1)=='/'), absf=1; else, absf=0; end +case 'win' + if (length(path)>1 & path(2)==':'), absf=1; else, absf=0; end +otherwise + error('isabspath not coded for this filesystem'); +end +return + + +function [T]=strtrim(S); +% strtrim - remove blank spaces + +if iscell(S) + T=S; + for i=1:numel(S) + + T{i}=strtrim(S{i}); + end +elseif ischar(S) + T=fliplr(deblank(fliplr(deblank(S)))); +end + \ No newline at end of file diff --git a/spm/spm2/spm_imcalc_ui.m b/spm/spm2/spm_imcalc_ui.m new file mode 100644 index 0000000..774981c --- /dev/null +++ b/spm/spm2/spm_imcalc_ui.m @@ -0,0 +1,172 @@ +function [Q,Vo] = spm_imcalc_ui(P,Q,f,flags,varargin) +% Perform algebraic functions on images +% FORMAT Q = spm_imcalc_ui(P,Q,f,flags,Xtra_vars...) +% P - matrix of input image filenames +% [user prompted to select files if arg missing or empty] +% Q - name of output image +% [user prompted to enter filename if arg missing or empty] +% f - expression to be evaluated +% [user prompted to enter expression if arg missing or empty] +% flags - cell vector of flags: {dmtx,mask,type,hold} +% dmtx - Read images into data matrix? +% [defaults (missing or empty) to 0 - no] +% mask - implicit zero mask? +% [defaults (missing or empty) to 0] +% type - data type for output image (see spm_type) +% [defaults (missing or empty) to 4 - 16 bit signed shorts] +% hold - interpolation hold (see spm_slice_vol) +% [defaults (missing or empty) to 0 - nearest neighbour] +% Xtra_vars... - additional variables which can be used in expression +% Q (output) - full pathname of image written +% Vo - structure containing information on output image (see spm_vol) +% +%_______________________________________________________________________ +% +% spm_imcalc_ui uses spm_imcalc as an engine to perform user-specified +% algebraic manipulations on a set of images, with the result being +% written out as an image. The user is prompted to supply images to +% work on, a filename for the output image, and the expression to +% evaluate. The expression should be a standard matlab expression, +% within which the images should be referred to as i1, i2, i3,... etc. +% +% If the dmtx flag is set, then images are read into a data matrix X +% (rather than into seperate variables i1, i2, i3,...). The data matrix +% should be referred to as X, and contains images in rows. +% +% Computation is plane by plane, so in data-matrix mode, X is a NxK +% matrix, where N is the number of input images [prod(size(Vi))], and K +% is the number of voxels per plane [prod(Vi(1).dim(1:2))]. +% +% For data types without a representation of NaN, implicit zero masking +% assummes that all zero voxels are to be treated as missing, and +% treats them as NaN. NaN's are written as zero (by spm_write_plane), +% for data types without a representation of NaN. +% +% With images of different sizes and orientations, the size and +% orientation of the first is used for the output image. A warning is +% given in this situation. Images are sampled into this orientation +% using the interpolation specified by the hold parameter. [default - +% nearest neighbour] +% +% The image Q is written to current working directory unless a valid +% full pathname is given. +% +% Example expressions (f): +% +% i) Mean of six images (select six images) +% f = '(i1+i2+i3+i4+i5+i6)/6' +% ii) Make a binary mask image at threshold of 100 +% f = 'i1>100' +% iii) Make a mask from one image and apply to another +% f = 'i2.*(i1>100)' +% - here the first image is used to make the mask, which is +% applied to the second image +% iv) Sum of n images +% f = 'i1 + i2 + i3 + i4 + i5 + ...' +% v) Sum of n images (when reading data into a data-matrix - use dmtx arg) +% f = 'sum(X)' +% +% Parameters can be passed as arguments to override internal defaults +% (for hold, mask & type), or to pre-specify images (P), output +% filename (Q), or expression (f). Pass empty matrices for arguments +% not to be set. +% E.g. Q = spm_imcalc_ui({},'test','',{[],[],[],1}) +% ... pre-specifies the output filename as 'test.img' in the current +% working directory, and sets the interpolation hold to tri-linear. +% +% Further, additional variables for use in the computation can be +% passed at the end of the argument list. These should be referred to +% by the names of the arguments passed in the expression to be +% avaluated. E.g. if c is a 1xn vector of weights, then for n images, +% using the (dmtx) data-matrix version, the weighted sum can be +% computed using: +% Q = spm_imcalc_ui({},'test','c*X',{1},c) +% Here we've pre-specified the output filename, expression and passed +% the vector c as an additional variable (you'll be prompted to select +% the n images). +% +%_______________________________________________________________________ +% @(#)spm_imcalc_ui.m 2.7 John Ashburner, Andrew Holmes 02/09/05 + +%-GUI setup +%----------------------------------------------------------------------- +SCCSid = '2.7'; +[Finter,Fgraph,CmdLine] = spm('FnUIsetup','ImCalc',0); +SPMid = spm('FnBanner',mfilename,SCCSid); +spm_help('!ContextHelp',[mfilename,'.m']) + +%-Condition arguments +%----------------------------------------------------------------------- +if nargin<4, flags={}; end +if nargin<3, f=''; end +if nargin<2, Q=''; end +if nargin<1, P={}; end + +if isempty(P), P = spm_get(Inf,'IMAGE',{'Select images to work on'}); end +if isempty(P), error('no input images specified'), end +if isempty(Q), Q = spm_input('Output filename',1,'s'); end +if isempty(f), f = spm_input('Evaluated Function',2,'s'); end + +if length(flags)<4, hold=[]; else, hold=flags{4}; end +if isempty(hold), hold=0; end +if length(flags)<3, type=[]; else, type=flags{3}; end +if isempty(type), type=4; end, if ischar(type), type=spm_type(type); end +if length(flags)<2, mask=[]; else, mask=flags{2}; end +if isempty(mask), mask=0; end +if length(flags)<1, dmtx=[]; else, dmtx=flags{1}; end +if isempty(dmtx), dmtx=0; end + +spm('FigName','ImCalc: working',Finter,CmdLine); +spm('Pointer','Watch') + + +%-Map input files +%----------------------------------------------------------------------- +Vi = spm_vol(char(P)); +if isempty(Vi), error('no input images specified'), end + +%-Check for consistency of image dimensions and orientation / voxel size +%----------------------------------------------------------------------- +if length(Vi)>1 & any(any(diff(cat(1,Vi.dim),1,1),1)&[1,1,1,0]) + warning(['images don''t all have same dimensions',... + ' - using those of 1st image']), end +if any(any(any(diff(cat(3,Vi.mat),1,3),3))) + warning(['images don''t all have same orientation & voxel size',... + ' - using 1st image']), end + + +%-Work out filename for output image +%------------------------------------------------------------------ +Qdir = spm_str_manip(Q,'Hv'); +Qfil = [spm_str_manip(Q,'stv'),'.img']; +if ~exist(Qdir,'dir') + warning('Invalid directory: writing to current directory') + Qdir = '.'; +end +Q = spm_get('CPath',Qfil,Qdir); + +Vo = struct( 'fname', Q,... + 'dim', [Vi(1).dim(1:3),type],... + 'mat', Vi(1).mat,... + 'descrip', 'spm - algebra'); + + +%-Call spm_imcalc to handle computations +%------------------------------------------------------------------ +% args = {{dmtx,mask,hold},varargin{:}}; +% Vo = spm_imcalc(Vi,Vo,f,args{:}); +% +% KND: the way spm_imcalc_ui calls spm_imcalc does not preserve inputname! +% +Xtra_vars = ''; +for i=5:nargin + eval([inputname(i),' = varargin{i-4};']) + Xtra_vars = [Xtra_vars ',' inputname(i) ]; +end +Vo=eval(['spm_imcalc(Vi,Vo,f,{dmtx,mask,hold}' Xtra_vars ')']); + + +%-End +%------------------------------------------------------------------ +spm('Pointer'); +spm('FigName','ImCalc: done',Finter,CmdLine); diff --git a/spm/spm2/spm_list_fullfiles.m b/spm/spm2/spm_list_fullfiles.m new file mode 100644 index 0000000..13445fe --- /dev/null +++ b/spm/spm2/spm_list_fullfiles.m @@ -0,0 +1,33 @@ +function [Files]= spm_list_fullfiles(Dirs,Filter) +% spm_list_fullfiles() - List full files (including path) +% FORMAT [Files] = spm_list_fullfiles(Dirs [,Filter]) +% Dirs - directories to list (possibly more than one). +% Default: current directory ('.') +% Filter - e.g. '*.img' (default) +% Files - full filenames including paths +% Dirs - directories +%_______________________________________________________________________ +% +% See also: spm_list_files.m +%_______________________________________________________________________ +% @(#)spm_list_fullfiles.m 1.0 Karim N'Diaye 06/12/07 +if nargin<2 + Filter='*.img'; + if nargin<1 + Dirs={cd}; + end +end +if ischar(Dirs) + Dirs=cellstr(Dirs); +end +Files=[]; +for i=1:length(Dirs) + d=cd; + cd(Dirs{i}) + Dirs{i}=cd; + cd(d); + [f,d] = spm_list_files(Dirs{i},Filter); + f=[repmat([Dirs{i}, filesep], size(f,1), 1) f]; + Files=[Files; f]; +end + diff --git a/spm/spm2/spm_mask2.m b/spm/spm2/spm_mask2.m new file mode 100644 index 0000000..06add0a --- /dev/null +++ b/spm/spm2/spm_mask2.m @@ -0,0 +1,132 @@ +function spm_mask(P1,P2, thresh2) +% Masks Images. +% FORMAT spm_mask(P1,P2, thresh2) +% P1 - matrix of input image filenames from which +% to compute the mask. +% P2 - matrix of input image filenames on which +% to apply the mask. +% thresh2 - optional threshold(s) for defining the mask. If +% * thresh2=[x] keeps values ABOVE x (same as spm_mask) +% * thresh2=[x y] keeps masking values BETWEEN x and y (included) +% * thresh2=[x x] keeps masking voxels EXACTLY equal to x +% * thresh2={x [y z] t} keeps values matching x, t, OR falling +% between y and z (inclusive masking) +% +% The masked images are prepended with the prefix `m'. +% +% If any voxel in the series of images is zero (for data types without +% a floating point representation) or does not have a finite value (for +% floating point and double precision images), then that voxel is set to +% NaN or zero in all the images. +% +% If a list of masking files is passed, then if necessary, the threshold is +% expanded to match the length of this list. The resulting masking is then +% the INTERSECTION of all the (threshold-dependent) masks. +% +% Images sampled in different orientations and positions can be passed +% to the routine. Providing the `.mat' files are correct, then these +% should be handled appropriately. +%_______________________________________________________________________ +% @(#)spm_mask.m 2.12 John Ashburner 03/02/03 + +if nargin==0, + P1=spm_get(Inf,'IMAGE','Images to compute mask from'); + P2=spm_get(Inf,'IMAGE','Images to apply mask to'); +end; +if nargin==1, + P2 = P1; +end; +thresh={0}; +if nargin==3, + thresh=thresh2; + if not(iscell(thresh)) && isnumeric(thresh) + % makes it backward compatible with spm_mask + if size(thresh,2) == 1; thresh=[thresh repmat(Inf,size(thresh,1),1)]; end + thresh=mat2cell(mat2cell(thresh, ones(size(thresh,1),1),2 ), size(thresh,1),1); + elseif not(iscell(thresh{1})) + thresh={thresh}; + end +end; + +V1=spm_vol(P1); +V2=spm_vol(P2); + +m1=prod(size(V1)); +m2=prod(size(V2)); + +if size(thresh,1)==1, + thresh = repmat(thresh,m1,1); +end +if size(P1,1) ~= size(thresh,1), + error('threshold input is wrong size.'); +end; + + +% Create headers +VO=V2; +for i=1:m2, + [pth,nm,xt,vr] = fileparts(deblank(VO(i).fname)); + %VO(i).fname = fullfile(pth,['m' nm xt vr]); + VO(i).fname = ['m' nm '.img']; + VO(i).descrip = 'Masked'; + VO(i).mat = VO(1).mat; + VO(i).dim(1:3) = VO(1).dim(1:3); +end; +VO = spm_create_vol(VO); +M = VO(1).mat; +dim = VO(1).dim(1:3); + +spm_progress_bar('Init',VO(1).dim(3),'Masking','planes completed') +for j=1:dim(3), + + msk = zeros(dim(1:2)); + Mi = spm_matrix([0 0 j]); + + % Load slice j from all images + for i=1:m1 + M1 = M\V1(i).mat\Mi; + %if sum((M1(:)-Mi(:)).^2=thresh{i}{v}(1) & img<=thresh{i}{v}(2)) & finite(img)); + end + + end + end; + + end; + + msk = find(msk~=m1); + + % Write the images. + for i=1:m2, + M1 = M\V2(i).mat\Mi; + img = spm_slice_vol(V2(i),M1,dim(1:2),[1 0]); + img(msk) = NaN; + VO(i) = spm_write_plane(VO(i),img,j); +% if numel(msk)> spm_mat2hdr +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-18 Creation +% +% ----------------------------- Script History --------------------------------- + + +http://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind00&L=SPM&P=R220047 + + + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/spm/spm2/spm_mat_into_hdr.m b/spm/spm2/spm_mat_into_hdr.m new file mode 100644 index 0000000..792f50e --- /dev/null +++ b/spm/spm2/spm_mat_into_hdr.m @@ -0,0 +1,262 @@ +%SPM_MAT_INTO_HDR +% Based on: MAT_INTO_HDR + +function dsr=spm_mat_into_hdr(files) + +file_lst = dir(files); +file_lst = {file_lst.name}; +file1 = file_lst{1}; +[p n e]= fileparts(file1); + +for i=1:length(file_lst) + [p n e]= fileparts(file_lst{i}); + disp(['working on file ', num2str(i) ,' of ', num2str(length(file_lst)), ': ', n,e]); + process=1; + + if isequal(e,'.hdr') + mat=fullfile(p, [n,'.mat']); + hdr=file_lst{i}; + dsr=spm_read_hdr(hdr); + return + + if ~exist(mat,'file') + warning(['Cannot find file "',mat , '". File "', n, e, '" will not be processed.']); + process=0; + end + elseif isequal(e,'.mat') + hdr=fullfile(p, [n,'.hdr']); + mat=file_lst{i}; + + if ~exist(hdr,'file') + warning(['Can not find file "',hdr , '". File "', n, e, '" will not be processed.']); + process=0; + end + else + warning(['Input file must have .mat or .hdr extension. File "', n, e, '" will not be processed.']); + process=0; + end + + if process + load(mat); + R=M(1:3,1:3); + T=M(1:3,4); + T=R*ones(3,1)+T; + M(1:3,4)=T; + + [h filetype fileprefix machine]=load_nii_hdr(hdr); + h.hist.qform_code=0; + h.hist.sform_code=1; + h.hist.srow_x=M(1,:); + h.hist.srow_y=M(2,:); + h.hist.srow_z=M(3,:); + h.hist.magic='ni1'; + + fid = fopen(hdr,'w',machine); + save_nii_hdr(h,fid); + fclose(fid); + end +end + +return; % mat_into_hdr + + +function [ dsr ] = read_header(fid) + +% Original header structures +% struct dsr +% { +% struct header_key hk; /* 0 + 40 */ +% struct image_dimension dime; /* 40 + 108 */ +% struct data_history hist; /* 148 + 200 */ +% }; /* total= 348 bytes*/ + +dsr.hk = header_key(fid); +dsr.dime = image_dimension(fid); +dsr.hist = data_history(fid); + +% For Analyze data format +% +if ~strcmp(dsr.hist.magic, 'n+1') & ~strcmp(dsr.hist.magic, 'ni1') + dsr.hist.qform_code = 0; + dsr.hist.sform_code = 0; +end + +return % read_header + + + +%--------------------------------------------------------------------- +function [ hk ] = header_key(fid) + +fseek(fid,0,'bof'); + +% Original header structures +% struct header_key /* header key */ +% { /* off + size */ +% int sizeof_hdr /* 0 + 4 */ +% char data_type[10]; /* 4 + 10 */ +% char db_name[18]; /* 14 + 18 */ +% int extents; /* 32 + 4 */ +% short int session_error; /* 36 + 2 */ +% char regular; /* 38 + 1 */ +% char dim_info; % char hkey_un0; /* 39 + 1 */ +% }; /* total=40 bytes */ +% +% int sizeof_header Should be 348. +% char regular Must be 'r' to indicate that all images and +% volumes are the same size. + +hk.sizeof_hdr = fread(fid, 1,'int32')'; % should be 348! +hk.data_type = deblank(fread(fid,10,'*char')'); +hk.db_name = deblank(fread(fid,18,'*char')'); +hk.extents = fread(fid, 1,'int32')'; +hk.session_error = fread(fid, 1,'int16')'; +hk.regular = fread(fid, 1,'*char')'; +hk.dim_info = fread(fid, 1,'char')'; + +return % header_key + + +%--------------------------------------------------------------------- +function [ dime ] = image_dimension(fid) + +% Original header structures +% struct image_dimension +% { /* off + size */ +% short int dim[8]; /* 0 + 16 */ +% /* +% dim[0] Number of dimensions in database; usually 4. +% dim[1] Image X dimension; number of *pixels* in an image row. +% dim[2] Image Y dimension; number of *pixel rows* in slice. +% dim[3] Volume Z dimension; number of *slices* in a volume. +% dim[4] Time points; number of volumes in database +% */ +% float intent_p1; % char vox_units[4]; /* 16 + 4 */ +% float intent_p2; % char cal_units[8]; /* 20 + 4 */ +% float intent_p3; % char cal_units[8]; /* 24 + 4 */ +% short int intent_code; % short int unused1; /* 28 + 2 */ +% short int datatype; /* 30 + 2 */ +% short int bitpix; /* 32 + 2 */ +% short int slice_start; % short int dim_un0; /* 34 + 2 */ +% float pixdim[8]; /* 36 + 32 */ +% /* +% pixdim[] specifies the voxel dimensions: +% pixdim[1] - voxel width, mm +% pixdim[2] - voxel height, mm +% pixdim[3] - slice thickness, mm +% pixdim[4] - volume timing, in msec +% ..etc +% */ +% float vox_offset; /* 68 + 4 */ +% float scl_slope; % float roi_scale; /* 72 + 4 */ +% float scl_inter; % float funused1; /* 76 + 4 */ +% short slice_end; % float funused2; /* 80 + 2 */ +% char slice_code; % float funused2; /* 82 + 1 */ +% char xyzt_units; % float funused2; /* 83 + 1 */ +% float cal_max; /* 84 + 4 */ +% float cal_min; /* 88 + 4 */ +% float slice_duration; % int compressed; /* 92 + 4 */ +% float toffset; % int verified; /* 96 + 4 */ +% int glmax; /* 100 + 4 */ +% int glmin; /* 104 + 4 */ +% }; /* total=108 bytes */ + +dime.dim = fread(fid,8,'int16')'; +dime.intent_p1 = fread(fid,1,'float32')'; +dime.intent_p2 = fread(fid,1,'float32')'; +dime.intent_p3 = fread(fid,1,'float32')'; +dime.intent_code = fread(fid,1,'int16')'; +dime.datatype = fread(fid,1,'int16')'; +dime.bitpix = fread(fid,1,'int16')'; +dime.slice_start = fread(fid,1,'int16')'; +dime.pixdim = fread(fid,8,'float32')'; +dime.vox_offset = fread(fid,1,'float32')'; +dime.scl_slope = fread(fid,1,'float32')'; +dime.scl_inter = fread(fid,1,'float32')'; +dime.slice_end = fread(fid,1,'int16')'; +dime.slice_code = fread(fid,1,'char')'; +dime.xyzt_units = fread(fid,1,'char')'; +dime.cal_max = fread(fid,1,'float32')'; +dime.cal_min = fread(fid,1,'float32')'; +dime.slice_duration = fread(fid,1,'float32')'; +dime.toffset = fread(fid,1,'float32')'; +dime.glmax = fread(fid,1,'int32')'; +dime.glmin = fread(fid,1,'int32')'; + +return % image_dimension + + +%--------------------------------------------------------------------- +function [ hist ] = data_history(fid) + +% Original header structures +% struct data_history +% { /* off + size */ +% char descrip[80]; /* 0 + 80 */ +% char aux_file[24]; /* 80 + 24 */ +% short int qform_code; /* 104 + 2 */ +% short int sform_code; /* 106 + 2 */ +% float quatern_b; /* 108 + 4 */ +% float quatern_c; /* 112 + 4 */ +% float quatern_d; /* 116 + 4 */ +% float qoffset_x; /* 120 + 4 */ +% float qoffset_y; /* 124 + 4 */ +% float qoffset_z; /* 128 + 4 */ +% float srow_x[4]; /* 132 + 16 */ +% float srow_y[4]; /* 148 + 16 */ +% float srow_z[4]; /* 164 + 16 */ +% char intent_name[16]; /* 180 + 16 */ +% char magic[4]; % int smin; /* 196 + 4 */ +% }; /* total=200 bytes */ + +hist.descrip = deblank(fread(fid,80,'*char')'); +hist.aux_file = deblank(fread(fid,24,'*char')'); +hist.qform_code = fread(fid,1,'int16')'; +hist.sform_code = fread(fid,1,'int16')'; +hist.quatern_b = fread(fid,1,'float32')'; +hist.quatern_c = fread(fid,1,'float32')'; +hist.quatern_d = fread(fid,1,'float32')'; +hist.qoffset_x = fread(fid,1,'float32')'; +hist.qoffset_y = fread(fid,1,'float32')'; +hist.qoffset_z = fread(fid,1,'float32')'; +hist.srow_x = fread(fid,4,'float32')'; +hist.srow_y = fread(fid,4,'float32')'; +hist.srow_z = fread(fid,4,'float32')'; +hist.intent_name = deblank(fread(fid,16,'*char')'); +hist.magic = deblank(fread(fid,4,'*char')'); + +fseek(fid,253,'bof'); +hist.originator = fread(fid, 5,'int16')'; + +return % data_history + + + + + +% MAT_INTO_HDR The old versions of SPM (any version before SPM5) store +% an affine matrix of the SPM Reoriented image into a matlab file +% (.mat extension). The file name of this SPM matlab file is the +% same as the SPM Reoriented image file (.img/.hdr extension). +% +% This program will convert the ANALYZE 7.5 SPM Reoriented image +% file into NIfTI format, and integrate the affine matrix in the +% SPM matlab file into its header file (.hdr extension). +% +% WARNING: Before you run this program, please save the header +% file (.hdr extension) into another file name or into another +% folder location, because all header files (.hdr extension) +% will be overwritten after they are converted into NIfTI +% format. +% +% Usage: mat_into_hdr(filename); +% +% filename: file name(s) with .hdr or .mat file extension, like: +% '*.hdr', or '*.mat', or a single .hdr or .mat file. +% e.g. mat_into_hdr('T1.hdr') +% mat_into_hdr('*.mat') +% + +% - Jimmy Shen (pls@rotman-baycrest.on.ca) +% +%------------------------------------------------------------------------- \ No newline at end of file diff --git a/spm/spm2/spm_mip.m b/spm/spm2/spm_mip.m new file mode 100644 index 0000000..6d05653 --- /dev/null +++ b/spm/spm2/spm_mip.m @@ -0,0 +1,77 @@ +function spm_mip(Z,XYZ,M,DIM) +% SPM maximum intensity projection +% FORMAT spm_mip(Z,XYZ,M,DIM); +% Z - {1 x ?} vector point list of SPM values for MIP +% XYZ - {3 x ?} matrix of coordinates of points (Talairach coordinates) +% M - voxels - > mm matrix +% DIM - image dimensions {voxels} +%_______________________________________________________________________ +% +% If the data are 2 dimensional [DIM(3) = 1] the projection is simply an +% image, otherwise: +% +% spm_mip creates and displays a maximum intensity projection of a point +% list of voxel values (Z) and their location (XYZ) in three orthogonal +% views of the brain. It is assumed voxel locations conform to the space +% defined in the atlas of Talairach and Tournoux (1988). +% +% This routine loads a mip putline from MIP.mat. This is an image with +% contours and grids defining the space of Talairach & Tournoux (1988). +% mip95 corresponds to the Talairach atlas, mip96 to the MNI templates. +% The outline and grid are superimposed at intensity defaults.grid, +% defaulting to 0.6. +% +% A default colormap of 64 levels is assumed. The pointlist image is +% scaled to fit in the interval [0.25,1]*64 for display. Flat images +% are scaled to 1*64. +% +%_______________________________________________________________________ +% @(#)spm_mip.m 2.7 Karl Friston et al. 02/07/31 + + +%-Get GRID value +%----------------------------------------------------------------------- +global defaults +if ~isempty(defaults) & isfield(defaults,'grid'), + GRID = defaults.grid; +else, + GRID = 0.6; +end; + +%-Scale & offset point list values to fit in [0.25,1] +%----------------------------------------------------------------------- +Z = Z(:)'; +Z = Z - min(Z); +mZ = max(Z); +if mZ %-Scale + Z = (1 + 3*Z/mZ)/4; +else %-Image is flat: set to ones: + Z = ones(1,length(Z)); +end + +%-Single slice case +%======================================================================= +if DIM(3) == 1, + VOX = sqrt(sum(M(1:3,1:3).^2)); + XYZ = round(M\[XYZ; ones(1,size(XYZ,2))]); + mip = full(sparse(XYZ(1,:),XYZ(2,:),Z,DIM(1),DIM(2))); + image([1 DIM(1)]*VOX(1),[1 DIM(2)]*VOX(2),(1-mip'/max(mip(:)))*64); + axis xy image; + set(gca,'FontSize',8,'TickDir','in','XTick',[],'YTick',[]) + %xlabel('x'), ylabel('y') + return +end + +%-3d case +%======================================================================= +%-Load mip and create maximum intensity projection +%----------------------------------------------------------------------- +load MIP +mip = mip96*GRID; +c = [0 0 0 ; 0 0 1 ; 0 1 0 ; 0 1 1 + 1 0 0 ; 1 0 1 ; 1 1 0 ; 1 1 1] -0.5; +c = (M(1:3,1:3)*c')'; +dim = [(max(c)-min(c)) size(mip)]; +d = spm_project(Z,round(XYZ),dim); +mip = max(d,mip); +image(rot90((1 - mip)*64)); axis image; axis off; diff --git a/spm/spm2/spm_mip_ui.m b/spm/spm2/spm_mip_ui.m new file mode 100644 index 0000000..c008b96 --- /dev/null +++ b/spm/spm2/spm_mip_ui.m @@ -0,0 +1,711 @@ +function varargout=spm_mip_ui(varargin) +% GUI for displaying MIPs with interactive pointers +% FORMAT hMIPax = spm_mip_ui(Z,XYZ,M,DIM,F) +% Z - {1 x ?} vector point list of SPM values for MIP +% XYZ - {3 x ?} matrix of coordinates of points (Talairach coordinates) +% M - voxels - > mm matrix +% DIM - image dimensions {voxels} +% F - Figure (or axes) to work in [Defaults to gcf] +% hMIPax - handle of MIP axes +% +% FORMAT xyz = spm_mip_ui('GetCoords',h) +% h - Handle of MIP axes, or figure containing MIP axis [default gcf] +% xyz - Current Talairach coordinates of cursor +% +% FORMAT [xyz,d] = spm_mip_ui('SetCoords',xyz,h,hC) +% xyz - (Input) {3 x 1} vector of desired Talairach coordinates +% h - Handle of MIP axes, or figure containing MIP axis [default gcf] +% hC - Handle of calling object, if used as a callback. [Default 0] +% xyz - (Output) {3 x 1} vector of voxel centre nearest desired xyz co-ords +% d - Euclidian distance from desired co-ords & nearest voxel +%_______________________________________________________________________ +% +% spm_mip_ui displays a maximum intensity projection (using spm_mip) +% with draggable cursors. +% +% See spm_mip.m for details of MIP construction, display, and the brain +% outlines used. +% ---------------- +% +% The cursor can be dragged to new locations in three ways: +% +% (1) Point & drop: Using the primary "select" mouse button, click on a +% cursor and drag the crosshair which appears to the desired location. +% On dropping, the cursors jump to the voxel centre nearest the drop +% site. +% +% (2) Dynamic drag & drop: Using the middle "extend" mouse button, click on +% a cursor and drag it about. The cursor follows the mouse, jumping to +% the voxel centre nearest the pointer. A dynamically updating +% information line appears above the MIP and gives the current +% co-ordinates. If the current voxel centre is in the XYZ pointlist, +% then the corresponding image value is also printed. +% +% (3) Magnetic drag & drop: As with "Dynamic drag & drop", except the cursors +% jump to the voxel centre in the pointlist nearest to the cursor. Use +% the right "alt" mouse button for "magnetic drag & drop". +% +% In addition a ContextMenu is provided, giving the option to jump the +% cursors to the nearest suprathreshold voxel, the nearest local +% maxima, or to the global maxima. (Right click on the MIP to bring up +% the ContextMenu.) A message in the MatLab command window describes the +% jump. +% +% ---------------- +% +% The current cursor position (constrained to lie on a voxel) can be +% obtained by xyz=spm_mip_ui('GetCoords',hMIPax), and set with +% xyz=spm_mip_ui('SetCoords',xyz,hMIPax), where hMIPax is the handle of +% the MIP axes, or of the figure containing a single MIP [default gcf]. +% The latter rounds xyz to the nearest voxel center, returning the +% result. +% +% spm_mip_ui handles all the callbacks required for moving the cursors, and +% is "registry" enabled (See spm_XYZreg.m). Programmers help is below in the +% main body of the function. +% +%_______________________________________________________________________ +% @(#)spm_mip_ui.m 2.12 Andrew Holmes 00/02/21 + +%======================================================================= +% - FORMAT specifications for embedded CallBack functions +%======================================================================= +%( This is a multi function function, the first argument is an action ) +%( string, specifying the particular action function to take. ) +% +% FORMAT hMIPax = spm_mip_ui(Z,XYZ,V,F) +% [ShortCut] Defaults to hMIPax=spm_mip_ui('Display',Z,XYZ,V,F) +% +% FORMAT hMIPax = spm_mip_ui('Display',Z,XYZ,M,DIM,F) +% Displays the MIP and sets up cursors +% Z - {1 x ?} vector point list of SPM values for MIP +% XYZ - {3 x ?} matrix of coordinates of points (Talairach coordinates) +% M - voxels - > mm matrix +% DIM - image dimensions {voxels} +% F - Handle of figure (or axes) to work in [Defaults to gcf] +% hMIPax - handle of MIP axes +% +% FORMAT xyz = spm_mip_ui('GetCoords',h) +% Returns coordinates of current cursor position +% h - Handle of MIP axes [defaults to spm_mip_ui('FindMIPax')] +% xyz - Current Talairach coordinates of cursor +% +% FORMAT [xyz,d] = spm_mip_ui('SetCoords',xyz,h,hC) +% Sets cursor position +% xyz - (Input) {3 x 1} vector of desired Talairach coordinates +% h - Handle of MIP axes [defaults to spm_mip_ui('FindMIPax')] +% hC - Handle of calling object, if used as a callback. [Default 0] +% xyz - (Output) {3 x 1} vector of voxel centre nearest desired xyz co-ords +% d - Euclidian distance from desired co-ords & nearest voxel +% +% FORMAT spm_mip_ui('PosnMarkerPoints',xyz,h,r) +% Utility routine: Positions cursor markers +% xyz - {3 x 1} vector of Talairach coordinates for cursor +% h - Handle of MIP axes [defaults to spm_mip_ui('FindMIPax')] +% r - 'r' to move visible red cursors, 'g' to move invisible green cursors +% +% +% FORMAT [xyz,d] = spm_mip_ui('Jump',h,loc) +% Utility routine (CallBack of UIcontextMenu) to jump cursor +% h - Handle of MIP axes [defaults to spm_mip_ui('FindMIPax')] +% loc - String defining jump: 'dntmv' - don't move +% 'nrvox' - nearest suprathreshold voxel +% 'nrmax' - nearest local maxima +% 'glmax' - global maxima +% xyz - co-ordinates of voxel centre jumped to {3 x 1} vector +% d - (square) Euclidian distance jumped +% +% FORMAT spm_mip_ui('ShowGreens',xyz,h) +% Shows green secondary cursors at location xyz +% xyz - {3 x 1} vector of Talairach coordinates for cursor +% [Default UserData of gco] +% h - Handle of MIP axes, or figure containing MIP axis [default gcf] +% +% FORMAT spm_mip_ui('HideGreens',h) +% Hides green secondary marker points +% h - Handle of MIP axes, or figure containing MIP axis [default gcf] +% +% FORMAT hMIPax = spm_mip_ui('FindMIPax',h) +% Looks for / checks MIP axes 'Tag'ged 'hMIPax'... errors if no valid MIP axes +% h - Handle of MIP axes, or figure containing MIP axis [default gcf] +% hMIPax - Handle of valid MIP axis found (errors if multiple found) +% +% FORMAT spm_mip_ui('MoveStart') +% Utility routine: CallBack for starting cursor dragging +% This is the ButtonDownFcn for the cursor markers +% +% FORMAT spm_mip_ui('Move',DragType) +% Utility routine: Initiate cursor move +% DragType - 0 = Point & drop (no dragging) +% 1 = Drag'n'drop with dynamic coordinate/value updating +% 2 = Magnetic drag'n'drop with dynamic coordinate updating +% +% FORMAT spm_mip_ui('MoveEnd') +% Utility routine: End cursor move +%_______________________________________________________________________ + + +%-Condition arguments +%======================================================================= +if nargin==0 + error('Insufficient arguments') +elseif ~isstr(varargin{1}) + varargout={spm_mip_ui('Display',varargin{1:end})}; return +end + + +%-Axis offsets for 3d MIPs: +%======================================================================= +%-MIP pane dimensions and Talairach origin offsets +%-See spm_project.c for derivation +DXYZ = [182 218 182]; +CXYZ = [091 127 073]; +% DMIP = [DXYZ(2)+DXYZ(1), DXYZ(1)+DXYZ(3)]; +%-Coordinates of Talairach origin in multipane MIP image (Axes are 'ij' + rot90) +% Transverse: [Po(1), Po(2)] +% Saggital : [Po(1), Po(3)] +% Coronal : [Po(4), Po(3)] +% 4 voxel offsets in Y since using character '<' as a pointer. +Po(1) = CXYZ(2) -2; +Po(2) = DXYZ(3)+DXYZ(1) -CXYZ(1) +2; +Po(3) = DXYZ(3) -CXYZ(3) +2; +Po(4) = DXYZ(2) +CXYZ(1) -2; + + + +%======================================================================= +switch lower(varargin{1}), case 'display' +%======================================================================= +% hMIPax = spm_mip_ui('Display',Z,XYZ,M,DIM,F) +if nargin<5 + F = gcf; + hMIPax = []; +else + F = varargin{6}; + if isstr(F), F=spm_figure('FindWin',F); end + if ~ishandle(F), error('Invalid handle'), end + switch get(F,'Type'), case 'figure' + hMIPax = []; + case 'axes' + hMIPax = F; + F = get(hMIPax,'Parent'); + otherwise + error('F not a figure or axis handle') + end +end +if nargin<4, error('Insufficient arguments'), end +DIM = varargin{5}; +M = varargin{4}; +XYZ = varargin{3}; +Z = varargin{2}; + +xyz = spm_XYZreg('RoundCoords',[0;0;0],M,DIM); + + +%-Display MIP +%----------------------------------------------------------------------- +Funits = get(F,'Units'); +set(F,'Units','normalized') +if isempty(hMIPax) + hMIPax = axes('Position',[0.24 0.54 0.62 0.42],'Parent',F); +else + axes(hMIPax), cla reset +end + +%-NB: spm_mip's `image` uses a newplot, & screws stuff without the figure. +figure(F) +spm_mip(Z,XYZ,M,DIM); + +%-Canonicalise axis positioning & save +%----------------------------------------------------------------------- +%-We're assumming the MIP fills the MIP axes bounding box, which is only +% true if stretch-to-fit is on (which it isn't with `axis image`), or that +% the axis bounding box itself has the correct aspect ratio. +%-So, shrink axes to the correct AspectRatio. +% Get aspect ratio from MIP graphic in case 2D +AR = diff(get(hMIPax,'Xlim'))/diff(get(hMIPax,'Ylim')); +set(hMIPax,'Units','pixels') +MIPaxPos = get(hMIPax,'Position'); +if (MIPaxPos(3)/MIPaxPos(4) > AR), MIPaxPos(3) = MIPaxPos(4)*AR; + else, MIPaxPos(4) = MIPaxPos(3)./AR; end +set(hMIPax,'Position',MIPaxPos) +hMIPim = get(gca,'Children'); + +%-Print coordinates +%----------------------------------------------------------------------- +hMIPxyz = text(0,max(get(hMIPax,'YLim'))/2,... + {'{\bfSPM}{\itmip}',sprintf('[%g, %g, %g]',xyz(1:3))},... + 'Interpreter','TeX','FontName',spm_platform('font','times'),... + 'Color',[1,1,1]*.7,... + 'HorizontalAlignment','Center',... + 'VerticalAlignment','Bottom',... + 'Rotation',90,... + 'Tag','hMIPxyz',... + 'UserData',xyz); + +%-Create point markers +%----------------------------------------------------------------------- +if DIM(3) == 1 + %-2 dimensional data + %--------------------------------------------------------------- + hXr = text(xyz(1),xyz(2),'<','Color','r','Fontsize',16,... + 'Tag','hX1r',... + 'ButtonDownFcn','spm_mip_ui(''MoveStart'')'); + hXg = text(xyz(1),xyz(2),'<','Color','g','Fontsize',12,... + 'Tag','hX1g','Visible','off'); +else + %-Create point markers + %-------------------------------------------------------------- + hX1r = text(Po(1)+xyz(2),Po(2)+xyz(1),'<',... + 'Color','r','Fontsize',16,... + 'Tag','hX1r',... + 'ButtonDownFcn','spm_mip_ui(''MoveStart'')'); + hX2r = text(Po(1)+xyz(2),Po(3)-xyz(3),'<',...l + 'Color','r','Fontsize',16,... + 'Tag','hX2r',... + 'ButtonDownFcn','spm_mip_ui(''MoveStart'')'); + hX3r = text(Po(4)+xyz(1),Po(3)-xyz(3),'<',.... + 'Color','r','Fontsize',16,... + 'Tag','hX3r',... + 'ButtonDownFcn','spm_mip_ui(''MoveStart'')'); + hXr = [hX1r,hX2r,hX3r]; + + hX1g = text(Po(1),Po(2),'<','Color','g','Fontsize',12,... + 'Tag','hX1g','Visible','off'); + hX2g = text(Po(1),Po(3),'<','Color','g','Fontsize',12,... + 'Tag','hX2g','Visible','off'); + hX3g = text(Po(4),Po(3),'<','Color','g','Fontsize',12,... + 'Tag','hX3g','Visible','off'); + hXg = [hX1g,hX2g,hX3g]; +end + +%-Create UIContextMenu for marker jumping +%----------------------------------------------------------------------- +h = uicontextmenu('Tag','MIPconmen','UserData',hMIPax); +uimenu(h,'Label','MIP') +if isempty(XYZ), str='off'; else, str='on'; end +uimenu(h,'Separator','on','Label','goto nearest suprathreshold voxel',... + 'CallBack',['spm_mip_ui(''Jump'',',... + 'get(get(gcbo,''Parent''),''UserData''),''nrvox'');'],... + 'Interruptible','off','BusyAction','Cancel','Enable',str); +uimenu(h,'Separator','off','Label','goto nearest local maxima',... + 'CallBack',['spm_mip_ui(''Jump'',',... + 'get(get(gcbo,''Parent''),''UserData''),''nrmax'');'],... + 'Interruptible','off','BusyAction','Cancel','Enable',str); +% KND: +uimenu(h,'Separator','off','Label','goto maximum in a sphere',... + 'CallBack',['spm_mip_ui(''Jump'',',... + 'get(get(gcbo,''Parent''),''UserData''),''sphmax'');'],... + 'Interruptible','off','BusyAction','Cancel','Enable',str); +uimenu(h,'Separator','off','Label','goto global maxima',... + 'CallBack',['spm_mip_ui(''Jump'',',... + 'get(get(gcbo,''Parent''),''UserData''),''glmax'');'],... + 'Interruptible','off','BusyAction','Cancel','Enable',str); +uimenu(h,'Separator','on','Label','help',... + 'CallBack','spm_help(''spm_mip_ui'')',... + 'Interruptible','off','BusyAction','Cancel','Enable',str); +set(hMIPim,'UIContextMenu',h) + +%-Save handles and data +%----------------------------------------------------------------------- +set(hMIPax,'Tag','hMIPax','UserData',... + struct( 'hReg', [],... + 'hMIPxyz', hMIPxyz,... + 'XYZ', XYZ,... + 'Z', Z,... + 'M', M,... + 'DIM', DIM,... + 'hXr', hXr,... + 'hXg', hXg)) + +varargout = {hMIPax}; + + + +%======================================================================= +case 'getcoords' +%======================================================================= +% xyz = spm_mip_ui('GetCoords',h) +if nargin<2, h=spm_mip_ui('FindMIPax'); else h=varargin{2}; end +varargout = {get(getfield(get(h,'UserData'),'hMIPxyz') ,'UserData')}; + + + +%======================================================================= +case 'setcoords' +%======================================================================= +% [xyz,d] = spm_mip_ui('SetCoords',xyz,h,hC) +if nargin<4, hC=0; else, hC=varargin{4}; end +if nargin<3, h=spm_mip_ui('FindMIPax'); else, h=varargin{3}; end +if nargin<2, error('Set co-ords to what!'), else, xyz=varargin{2}; end + +%KND if many MIP windows... +if length(h)>1 + h=h(strmatch('Graphics',get(cell2mat(get(h, 'Parent')), 'Tag'))); + h=h(end); +end + +MD = get(h,'UserData'); + +%-Check validity of coords only when called without a caller handle +%----------------------------------------------------------------------- +if hC<=0 + [xyz,d] = spm_XYZreg('RoundCoords',xyz,MD.M,MD.DIM); + if d>0 & nargout<2, warning(sprintf(... + '%s: Co-ords rounded to neatest voxel center: Discrepancy %.2f',... + mfilename,d)), end +else + d = []; +end + +%-Move marker points, update internal cache in hMIPxyz +%----------------------------------------------------------------------- +spm_mip_ui('PosnMarkerPoints',xyz,h,'r'); +set(MD.hMIPxyz,'UserData',reshape(xyz(1:3),3,1)) +set(MD.hMIPxyz,'String',{'{\bfSPM}{\itmip}',sprintf('[%g, %g, %g]',xyz(1:3))}) + +%-Tell the registry, if we've not been called by the registry... +%----------------------------------------------------------------------- +if (~isempty(MD.hReg) & MD.hReg~=hC), spm_XYZreg('SetCoords',xyz,MD.hReg,h); end + +%-Return arguments +%----------------------------------------------------------------------- +varargout = {xyz,d}; + + + +%======================================================================= +case 'posnmarkerpoints' +%======================================================================= +% spm_mip_ui('PosnMarkerPoints',xyz,h,r) +if nargin<4, r='r'; else, r=varargin{4}; end +if ~any(strcmp(r,{'r','g'})), error('Invalid pointer colour spec'), end +if nargin<3, h=spm_mip_ui('FindMIPax'); else, h=varargin{3}; end +if nargin<2, xyz = spm_mip_ui('GetCoords',h); else, xyz = varargin{2}; end + +%-Get handles of marker points of appropriate colour from UserData of hMIPax +%----------------------------------------------------------------------- +hX = getfield(get(h,'UserData'),['hX',r]); + +%-Set marker points +%----------------------------------------------------------------------- +set(hX,'Units','Data') +if length(hX)==1 + tmp = get(varargin{3},'UserData'); + vx = sqrt(sum(tmp.M(1:3,1:3).^2)); + tmp = tmp.M\[xyz ; 1]; + tmp = tmp(1:2).*vx(1:2)'; + set(hX,'Position',[tmp(1), tmp(2), 1]) +else + set(hX(1),'Position',[ Po(1) + xyz(2), Po(2) + xyz(1), 0]) + set(hX(2),'Position',[ Po(1) + xyz(2), Po(3) - xyz(3), 0]) + set(hX(3),'Position',[ Po(4) + xyz(1), Po(3) - xyz(3), 0]) +end + + +%======================================================================= +case 'jump' +%======================================================================= +% [xyz,d] = spm_mip_ui('Jump',h,loc) +if nargin<3, loc='nrvox'; else, loc=varargin{3}; end +if nargin<2, h=spm_mip_ui('FindMIPax'); else, h=varargin{2}; end + +%-Get current location & MipData +%----------------------------------------------------------------------- +oxyz = spm_mip_ui('GetCoords',h); +MD = get(h,'UserData'); + + +%-Compute location to jump to +%----------------------------------------------------------------------- +if isempty(MD.XYZ), loc='dntmv'; end +switch lower(loc), case 'dntmv' + spm('alert!','No suprathreshold voxels to jump to!',mfilename,0); + varargout = {oxyz, 0}; + return +case 'nrvox' + str = 'nearest suprathreshold voxel'; + [xyz,i,d] = spm_XYZreg('NearestXYZ',oxyz,MD.XYZ); +case 'nrmax' + str = 'nearest local maxima'; + iM = inv(MD.M); + XYZvox = iM(1:3,:)*[MD.XYZ; ones(1,size(MD.XYZ,2))]; + [null,null,XYZvox,null] = spm_max(MD.Z,XYZvox); + XYZ = MD.M(1:3,:)*[XYZvox; ones(1,size(XYZvox,2))]; + [xyz,i,d] = spm_XYZreg('NearestXYZ',oxyz,XYZ); +case 'glmax' + str = 'global maxima'; + i = find(MD.Z==max(MD.Z)); + xyz = MD.XYZ(:,i); + d = sqrt(sum((oxyz-xyz).^2)); +case 'sphmax' + str = 'maxima in sphere'; + sph_r=inputdlg('Radius of the sphere?','Max in sphere',1,{'12'}); + if isempty(sph_r) + return + end + sph_r=str2num(sph_r{1}); + + iM = inv(MD.M); + XYZvox = iM(1:3,:)*[MD.XYZ; ones(1,size(MD.XYZ,2))]; + [d] = spm_XYZreg('Edist',oxyz,MD.XYZ); + i=find(d<=sph_r); + XYZvox = iM(1:3,:)*[MD.XYZ(:,i); ones(1,length(i))]; + + i_max = i(find(MD.Z(i)==max(MD.Z(i)))); + if ~isempty(i_max) + xyz = MD.XYZ(:,i_max); + d = sqrt(sum((oxyz-xyz).^2)); + else + xyz=NaN; + d = NaN; + end + +otherwise + warning('Unknown jumpmode') + varargout = {xyz,0}; + return +end + +%-Write jump report, jump, and return arguments +%----------------------------------------------------------------------- +fprintf(['\n\t%s:\tJumped %0.2fmm from [%3.0f, %3.0f, %3.0f],\n\t\t\t',... + 'to %s at [%3.0f, %3.0f, %3.0f]'],... + mfilename, d, oxyz, str, xyz) +try + fprintf(' -> voxel #[%d %d %d]', round(inv(MD.M)*[xyz; 1])); +end +fprintf('\n'); + +spm_mip_ui('SetCoords',xyz,h,h); +varargout = {xyz, d}; + + +%======================================================================= +case 'showgreens' +%======================================================================= +% spm_mip_ui('ShowGreens',xyz,h) +if nargin<3, h=get(0,'CurrentFigure'); else, h=varargin{3}; end +h = spm_mip_ui('FindMIPax',h); +if nargin<2, xyz=get(gcbo,'UserData'); else, xyz=varargin{2}; end + +spm_mip_ui('PosnMarkerPoints',xyz,h,'g') +set(getfield(get(h,'UserData'),'hXg'),'Visible','on') + +%-If called as a callback (xyz from gco), then set WindowButtonUpFcn +%----------------------------------------------------------------------- +if nargin<2 + set(gcbf,'WindowButtonUpFcn',[... + 'set(gcbf,''WindowButtonUpFcn'',''''),',... + 'spm_mip_ui(''HideGreens'',gcbf)']) +end + + + +%======================================================================= +case 'hidegreens' +%======================================================================= +% spm_mip_ui('HideGreens',h) +if nargin<2, h=get(0,'CurrentFigure'); else, h=varargin{2}; end +h = spm_mip_ui('FindMIPax',h); +set(getfield(get(h,'UserData'),'hXg'),'Visible','off') + + + +%======================================================================= +case 'findmipax' +%======================================================================= +% hMIPax = spm_mip_ui('FindMIPax',h) +% Checks / finds hMIPax handles +%-**** h is handle of hMIPax, or figure containing MIP (default gcf) +if nargin<2, h=get(0,'CurrentFigure'); else, h=varargin{2}; end +if isstr(h), h=spm_figure('FindWin',h); end +if ~ishandle(h), error('invalid handle'), end +if ~strcmp(get(h,'Tag'),'hMIPax'), h=findobj(h,'Tag','hMIPax'); end +if isempty(h), error('MIP axes not found'), end +if length(h)>1, error('Multiple MIPs in this figure'), end +varargout = {h}; + + + +%======================================================================= +case 'movestart' +%======================================================================= +% spm_mip_ui('MoveStart') +[cO,cF] = gcbo; +hMIPax = get(cO,'Parent'); +MD = get(hMIPax,'UserData'); + +%-Store useful quantities in UserData of gcbo, the object to be dragged +%----------------------------------------------------------------------- +set(hMIPax,'Units','Pixels') +set(cO,'UserData',struct(... + 'hReg', MD.hReg,... + 'xyz', spm_mip_ui('GetCoords',hMIPax),... + 'MIPaxPos', get(hMIPax,'Position')*[1,0;0,1;0,0;0,0],... + 'hMIPxyz', MD.hMIPxyz,... + 'M', MD.M,... + 'DIM', MD.DIM,... + 'hX', MD.hXr)) + +%-Initiate dragging +%----------------------------------------------------------------------- +if strcmp(get(cF,'SelectionType'),'normal') | isempty(MD.XYZ) + %-Set Figure callbacks for drop but no drag (DragType 0) + %--------------------------------------------------------------- + set(MD.hMIPxyz,'Visible','on','String',... + {'{\bfSPM}{\itmip}','\itPoint & drop...'}) + set(cF,'WindowButtonUpFcn', 'spm_mip_ui(''Move'',0)',... + 'Interruptible','off') + set(cF,'Pointer','CrossHair') +elseif strcmp(get(cF,'SelectionType'),'extend') + %-Set Figure callbacks for drag'n'drop (DragType 1) + %--------------------------------------------------------------- + set(MD.hMIPxyz,'Visible','on','String',... + {'{\bfSPM}{\itmip}','\itDynamic drag & drop...'}) + set(cF,'WindowButtonMotionFcn','spm_mip_ui(''Move'',1)',... + 'Interruptible','off') + set(cF,'WindowButtonUpFcn', 'spm_mip_ui(''MoveEnd'')',... + 'Interruptible','off') + set(cF,'Pointer','Fleur') +elseif strcmp(get(cF,'SelectionType'),'alt') + %-Set Figure callbacks for drag'n'drop with co-ord updating (DragType 2) + %--------------------------------------------------------------- + set(MD.hMIPxyz,'Visible','on','String',... + {'{\bfSPM}{\itmip}','\itMagnetic drag & drop...'}) + set(cF,'WindowButtonMotionFcn','spm_mip_ui(''Move'',2)',... + 'Interruptible','off') + set(cF,'WindowButtonUpFcn', 'spm_mip_ui(''MoveEnd'')',... + 'Interruptible','off') + set(cF,'Pointer','Fleur') +end + + + +%======================================================================= +case 'move' +%======================================================================= +% spm_mip_ui('Move',DragType) +if nargin<2, DragType = 2; else, DragType = varargin{2}; end +cF = gcbf; +cO = gco(cF); + +%-Get useful data from UserData of gcbo, the object to be dragged +%----------------------------------------------------------------------- +MS = get(cO,'UserData'); +b2d = MS.DIM(3) == 1; + +%-Work out where we are moving to - Use HandleGraphics to give positon +%----------------------------------------------------------------------- +set(cF,'Units','pixels') +d = get(cF,'CurrentPoint') - MS.MIPaxPos; +set(cO,'Units','pixels') +set(cO,'Position',d) +set(cO,'Units','data') +d = get(cO,'Position'); + +%-Work out xyz, depending on which view is being manipulated +%----------------------------------------------------------------------- +sMarker = get(cO,'Tag'); +if strcmp(sMarker,'hX1r') + if b2d + vx = sqrt(sum(MS.M(1:3,1:3).^2)); + tmp = [d(1)/vx(1) d(2)/vx(2) 1]'; + xyz = MS.M(1:3,:)*[tmp' 1]'; + else + xyz = [d(2) - Po(2); d(1) - Po(1); MS.xyz(3)]; + end +elseif strcmp(sMarker,'hX2r') + xyz = [MS.xyz(1); d(1) - Po(1); Po(3) - d(2)]; +elseif strcmp(sMarker,'hX3r') + xyz = [d(1) - Po(4); MS.xyz(2); Po(3) - d(2)]; +else + error('Can''t work out which marker point') +end + +%-Round coordinates according to DragType & set in hMIPxyz's UserData +%----------------------------------------------------------------------- +if DragType==0 + xyz = spm_XYZreg('RoundCoords',xyz,MS.M,MS.DIM); +elseif DragType==1 + xyz = spm_XYZreg('RoundCoords',xyz,MS.M,MS.DIM); + hMIPax = get(cO,'Parent'); + MD = get(hMIPax,'UserData'); + i = spm_XYZreg('FindXYZ',xyz,MD.XYZ); +elseif DragType==2 + hMIPax = get(cO,'Parent'); + MD = get(hMIPax,'UserData'); + [xyz,i,d] = spm_XYZreg('NearestXYZ',xyz,MD.XYZ); +end +set(MS.hMIPxyz,'UserData',xyz) + +%-Move marker points +%----------------------------------------------------------------------- +% spm_mip_ui('PosnMarkerPoints',xyz,hMIPax,'r') +set(MS.hX,'Units','Data') +if b2d + vx = sqrt(sum(MS.M(1:3,1:3).^2)); + tmp = MS.M\[xyz ; 1]; + tmp = tmp(1:2).*vx(1:2)'; + set(MS.hX,'Position',[tmp(1), tmp(2), 1],'Visible','on') +else + set(MS.hX(1),'Position',[ Po(1) + xyz(2), Po(2) + xyz(1), 0]) + set(MS.hX(2),'Position',[ Po(1) + xyz(2), Po(3) - xyz(3), 0]) + set(MS.hX(3),'Position',[ Po(4) + xyz(1), Po(3) - xyz(3), 0]) +end + + +%-Update dynamic co-ordinate strings (if appropriate DragType) +%----------------------------------------------------------------------- +if DragType==0 + spm_mip_ui('MoveEnd') +elseif DragType==1 + if isempty(i) + str = {'{\bfSPM}{\itmip}',sprintf('[%g, %g, %g]',xyz)}; + else + str = {'{\bfSPM}{\itmip}: ',... + sprintf('[%g, %g, %g]: %.4f',xyz,MD.Z(i))}; + end + set(MD.hMIPxyz,'String',str) +elseif DragType==2 + set(MD.hMIPxyz,'String',... + {'{\bfSPM}{\itmip}',sprintf('[%g, %g, %g]: %.4f',xyz,MD.Z(i))}) +else + error('Illegal DragType') +end + + + +%======================================================================= +case 'moveend' +%======================================================================= +% spm_mip_ui('MoveEnd') +cF = gcbf; +cO = gco(cF); +hMIPax = get(cO,'Parent'); +MS = get(cO,'UserData'); + +%-Reset WindowButton functions, pointer & SPMmip info-string +%----------------------------------------------------------------------- +set(gcbf,'WindowButtonMotionFcn',' ') +set(gcbf,'WindowButtonUpFcn',' ') +set(gcbf,'Pointer','arrow') +set(MS.hMIPxyz,'String',... + {'{\bfSPM}{\itmip}',sprintf('[%g, %g, %g]',get(MS.hMIPxyz,'UserData'))}) + +%-Set coordinates after drag'n'drop, tell registry +%----------------------------------------------------------------------- +% don't need to set internal coordinates 'cos 'move' does that +if ~isempty(MS.hReg) + spm_XYZreg('SetCoords',get(MS.hMIPxyz,'UserData'),MS.hReg,hMIPax); +end + + + +%======================================================================= +otherwise +%======================================================================= +error('Unknown action string') + +%======================================================================= +end diff --git a/spm/spm2/spm_move_spm.m b/spm/spm2/spm_move_spm.m new file mode 100644 index 0000000..dde3c9e --- /dev/null +++ b/spm/spm2/spm_move_spm.m @@ -0,0 +1,42 @@ +function [SPM]=spm_move_spm +[f,p]=uigetfile('SPM.mat', 'SPM file?') +load(fullfile(p,f)); +swd = SPM.swd; +[d2,f,ext] = fileparts(SPM.xY.VY(1).fname); +if ~exist(d2, 'dir') + d2=cd; +end +[d2]=uigetdir(d2,'New directory of functional data') +for i=1:size(SPM.xY.VY,1) + [d0,f,ext] = fileparts(SPM.xY.VY(i).fname); + if isempty(ext) + if ~exist(fullfile(d2,[f,'.img']),'file') + ext='.img'; + errordlg(sprintf('Data (%s.img) are not in this directory', [f ext])); + return + elseif ~exist(fullfile(d2,[f,'.hdr']),'file') + ext='.hdr'; + errordlg(sprintf('Data (%s.hdr) are not in this directory', [f ext])); + return + end + else + if ~exist(fullfile(d2,[f,ext]),'file') + errordlg('Data (%s) are not in this directory', [f,ext]); + return + end + end +end +% +% if ~exist(fullfile(p,'SPM.mat.bak')) +% copyfile(fullfile(p,'SPM.mat'), fullfile(p,'SPM.mat.bak')) +% end + +for i=1:size(SPM.xY.VY,1) + [d0,f,ext] = fileparts(SPM.xY.VY(i).fname); + if isempty(ext) + ext='.img'; + end + SPM.xY.VY(i).fname=fullfile(d2,[f, ext]); +end + +msgbox('You may now save your SPM data by typing in: ''save SPM.mat SPM'''); diff --git a/spm/spm2/spm_peristimulus_sampling.m b/spm/spm2/spm_peristimulus_sampling.m new file mode 100644 index 0000000..8b9d84b --- /dev/null +++ b/spm/spm2/spm_peristimulus_sampling.m @@ -0,0 +1,51 @@ +function [x,h]=spm_pst_smp(RT,onsets,NV,ST,nslices) +% check sampling of the HRF +try + addpath('D:\mtoolbox\spm2\') +end +if nargin < 1 + RT=2.5; +end +if nargin < 2 + onsets=cumsum(2.5+rand(1,10)/10) +end +if nargin < 3 + NV=(onsets(end)+32)/2.5; +end +if nargin < 4 + ST=1; +end +if ST >= RT + error('acquisition time can''t be longer than RT!!') +end +if isvector(onsets) + onsets=onsets(:)'; +end +figure +ha=axes; +line([0 32], [0 0], 'color','k'); +hold on +t=[0:32/.15]*.15; +y=normalize(spm_hrf(.15),inf); +plot(t,y) +set(ha,'Xlim', [0 32]) +% set(ha,'Xlim', [-RT*.1 RT*1.25], 'Ylim', [-.2 1.2], 'box', 'on') +% rectangle('position',[ ST 0 RT-ST .25], 'FaceColor', .85*[1 1 1]); +% line([-RT 2*RT], [0 0], 'color','k'); +% x=mod(onsets,RT); +x=RT*[0:NV-1]'*ones(1,length(onsets)) - ones(NV,1)*(onsets) + ST; +% x=x(:); +% x(x>32)=[]; +% x(x<0)=[]; +x(x>32)=NaN; +x(x<0)=NaN; +for j=1:length(onsets) + h(j)=plot(x(:,j),interp1(t,y,x(:,j)),'.', 'color', rand(1,3)); +end +str = sprintf('TR = %0.2f secs ',RT); +if ST>0 + str=[str sprintf('(including silent time = %0.2f secs)',ST)]; +end +xlabel('time (secs)') +title(str) +return diff --git a/spm/spm2/spm_resss.m b/spm/spm2/spm_resss.m new file mode 100644 index 0000000..de049d6 --- /dev/null +++ b/spm/spm2/spm_resss.m @@ -0,0 +1,125 @@ +function Vo = spm_resss(Vi,Vo,R,flags) +% Create residual sum of squares image (ResSS) +% FORMAT Vo = spm_resss(Vi,Vo,R,flags) +% Vi - vector of mapped image volumes to work on (from spm_vol) +% Vo - handle structure for mapped output image volume +% R - residual forming matrix +% flags - 'm' for implicit zero masking +% Vo (output) - handle structure of output image volume after modifications +% for writing +% +% Note that spm_create_image needs to be called external to this function - +% the header is not created! +%_______________________________________________________________________ +% +% Residuals are computed as R*Y, where Y is the data vector read from +% images mapped as Vi. The residual sum of squares image (mapped as Vo) +% is written. +% +%----------------------------------------------------------------------- +% +% For a simple linear model Y = X*B * E, with design matrix X, +% (unknown) parameter vector(s) B, and data matrix Y, the least squares +% estimates of B are given by b = inv(X'*X)*X'*Y. If X is rank +% deficient, then the Moore-Penrose pseudoinverse may be used to obtain +% the least squares parameter estimates with the lowest L2 norm: b = +% pinv(X)*Y. +% +% The fitted values are then y = X*b = X*inv(X'*X)*X'*Y, (or +% y=X*pinv(X)*Y). Since the fitted values y are usually known as +% "y-hat", X*inv(X'*X)*X' is known as the "hat matrix" for this model, +% denoted H. +% +% The residuals for this fit (estimates of E) are e = Y - y. +% Substituting from the above, e = (I-H)*Y, where I is the identity +% matrix (see eye). (I-H) is called the residual forming matrix, +% denoted R. +% +% Geometrically, R is a projection matrix, projecting the data into the +% subspace orthogonal to the design space. +% +% ---------------- +% +% For temporally smoothed fMRI models with convolution matrix K, R is a +% little more complicated: +% K*Y = K*X * B + K*E +% KY = KX * B + KE +% ...a little working shows that hat matrix is H = KX*inv(KX'*KX)*KX' +% (or KX*pinv(KX)), where KX=K*X. The smoothed residuals KE (=K*E) are +% then given from the temporally smoothed data KY (=K*Y) by y=H*KY. +% Thus the residualising matrix for the temporally smoothed residuals +% from the temporally smoothed data is then (I-H). +% +% Usually the image time series is not temporally smoothed, in which +% case the hat and residualising matrices must incorporate the temporal +% smoothing. The hat matrix for the *raw* (unsmoothed) time series Y is +% H*K, and the corresponding residualising matrix is R=(K-H*K). +% In full, that's +% R = (K - KX*inv(KX'*KX)*KX'*K) +% or R = (K - KX*pinv(KX)*K) when using a pseudoinverse +% +%----------------------------------------------------------------------- +% +% This function can also be used when the b's are images. The residuals +% are then e = Y - X*b, so let Vi refer to the vector of images and +% parameter estimates ([Y;b]), and then R is ([eye(n),-X]), where n is +% the number of Y images. +% +%----------------------------------------------------------------------- +% +% Don't forget to either apply any image scaling (grand mean or +% proportional scaling global normalisation) to the image scalefactors, +% or to combine the global scaling factors in the residual forming +% matrix. +%_______________________________________________________________________ +% @(#)spm_resss.m 2.9 Andrew Holmes, John Ashburner 02/08/13 + + +%-Argument checks +%----------------------------------------------------------------------- +if nargin<4, flags=''; end, if isempty(flags), flags='-'; end +mask = any(flags=='m'); +if nargin<3, error('insufficient arguments'); end +ni = size(R,2); %-ni = #images +if ni~=prod(size(Vi)), error('incompatible dimensions'); end +if Vo.dim(4)~=16, error('only float output images supported'), end + +%-Image dimension, orientation and voxel size checks +%----------------------------------------------------------------------- +[samef msg] = spm_vol_check(Vi, Vo); +if ~samef, disp(char(msg)),error('Cannot use images'),end; + + +%======================================================================= +% - C O M P U T A T I O N +%======================================================================= +fprintf('%-14s%16s',['(',mfilename,')'],'...initialising') %-# + +Y = zeros([Vo.dim(1:2),ni]); %-PlaneStack data + +im = logical(zeros(ni,1)); +for j=1:ni, im(j)=~spm_type(Vi(j).dim(4),'NaNrep'); end %-Images without NaNrep + +%-Loop over planes computing ResSS +for p=1:Vo.dim(3) + fprintf('%s%16s',char(sprintf('\b')*ones(1,16)),... + sprintf('...plane %3d/%-3d',p,Vo.dim(3))) %-# + + M = spm_matrix([0 0 p]); %-Sampling matrix + + %-Read plane data + for j=1:ni, Y(:,:,j) = spm_slice_vol(Vi(j),M,Vi(j).dim(1:2),0); end + + %-Apply implicit zero mask for image types without a NaNrep + if mask, Y(Y(:,:,im)==0)=NaN; end + + e = R*reshape(Y,prod(Vi(1).dim(1:2)),ni)'; %-residuals as DataMtx + ss = reshape(sum(e.^2,1),Vi(1).dim(1:2)); %-ResSS plane + Vo = spm_write_plane(Vo,ss,p); %-Write plane +end + + +%-End +%----------------------------------------------------------------------- +fprintf('%s%30s\n',char(sprintf('\b')*ones(1,30)),... + sprintf('...written %s',spm_str_manip(Vo.fname,'t'))) %-# diff --git a/spm/spm2/spm_results_ui.m b/spm/spm2/spm_results_ui.m new file mode 100644 index 0000000..5749ffd --- /dev/null +++ b/spm/spm2/spm_results_ui.m @@ -0,0 +1,1053 @@ +function varargout = spm_results_ui(varargin) +% User interface for SPM/PPM results: Display and analysis of regional effects +% FORMAT [hReg,xSPM,SPM] = spm_results_ui +% +% hReg - handle of MIP XYZ registry object +% (see spm_XYZreg for details) +% xSPM - structure containing specific SPM, distribution & filtering details +% (see spm_getSPM.m for contents) +% SDM - SPM structure containing generic parameters +% (see spm_spm.m for contents... +% +% NB: Results section GUI CallBacks use these data structures by name, which +% therefore *must* be assigned to the correctly named variables. +%_______________________________________________________________________ +% +% The SPM results section is for the interactive exploration and +% characterisation of the results of a statistical analysis. +% +% The user is prompted to select a SPM{T} or SPM{F}, that is +% thresholded at user specified levels. The specification of the +% contrasts to use and the height and size thresholds are described in +% spm_getSPM.m. The resulting SPM is then displayed in the graphics +% window as a maximum intensity projection, alongside the design matrix +% and contrasts employed. +% +% The cursors in the MIP can be moved (dragged) to select a particular +% voxel. The three mouse buttons give different drag and drop behaviour: +% Button 1 - point & drop; Button 2 - "dynamic" drag & drop with +% co-ordinate & SPM value updating; Button 3 - "magnetic" drag & drop, +% where the cursor jumps to the nearest suprathreshold voxel in the +% MIP, and shows the value there. (See spm_mip_ui.m, the MIP GUI handling +% function for further details.) +% +% The design matrix and contrast pictures are "surfable": Click and +% drag over the images to report associated data. Clicking with +% different buttons produces different results. Double-clicking +% extracts the underlying data into the base workspace. +% See spm_DesRep for further details. +% +% The current voxel specifies the voxel, suprathreshold cluster, or +% orthogonal planes (planes passing through that voxel) for subsequent +% localised utilities. +% +% A control panel in the interactive window enables interactive +% exploration of the results. +% +% p-value buttons: +% (i) volume - Tabulates p-values and statistics for entire volume. +% - see spm_list.m +% (ii) cluster - Tabulates p-values and statistics for nearest cluster +% - Note that the cursor will jump to the nearest +% suprathreshold voxel, if it is not already at a +% location with suprathreshold statistic. +% - see spm_list.m +% (iii) voxel - (not implemented yet) +% - see spm_****.m +% +% p-values for VOI button: +% S.V.C - Small Volume Correction: +% Tabulates p-values corrected for a small specified +% volume of interest. (Tabulation by spm_list.m) +% - see spm_VOI.m +% +% Data extraction buttons: +% V.O.I. - Extracts Eigentimeseries for small volumes of interest. +% - Data can be adjusted or not. +% - If temporal filtering was specified (fMRI), then it is the +% filtered data that is returned. +% - Choose a VOI of radius 0 to extract the (filtered &) +% adjusted data for a single voxel. Note that this vector +% will be scaled to have a 2-norm of 1. (See spm_regions.m +% for further details.) +% - The plot button also returns fitted and adjusted +% (after any filtering) data for the voxel being plotted.) +% - Note that the cursor will jump to the nearest voxel for +% which raw data was saved. +% - see spm_regions.m +% +% Visualisation buttons: +% (i) plot - Graphs of adjusted and fitted activity against +% various ordinates. +% - Note that the cursor will jump to the nearest +% suprathreshold voxel, if it is not already at a +% location with suprathreshold statistic. +% - Additionally, returns fitted and adjusted data to the +% MatLab base workspace. +% - see spm_graph.m +% (ii) overlays - Popup menu: Overlays of filtered SPM on a structural image +% - slices - Slices of the thresholded statistic image overlaid +% on a secondary image chosen by the user. Three +% transverse slices are shown, being those at the +% level of the cursor in the z-axis and the two +% adjacent to it. - see spm_transverse.m +% - sections - Orthogonal sections of the thresholded statistic +% image overlaid on a secondary image chosen by the user. +% The sections are through the cursor position. +% - see spm_sections.m +% - render - Render blobs on previously extracted cortical surface +% - see spm_render.m +% (iii) write filtered - Write out thresholded SPM as image +% - see spm_write_filtered.m +% +% +% The current cursor location can be set by editing the co-ordinate +% widgets at the bottom of the interactive window. (Note that many of the +% results section facilities are "linked" and can update co-ordinates. E.g. +% clicking on the co-ordinates in a p-value listing jumps to that location.) +% +% Graphics appear in the bottom half of the graphics window, additional +% controls and questions appearing in the interactive window. +% +% ---------------- +% +% The MIP uses a template outline in Talairach space. Consequently for +% the results section to display properly the input images to the +% statistics section should either be in Talairach space (with the +% ORIGIN correctly specified), or the ORIGIN header fields should be +% set to the voxel coordinates of the anterior commissure in the input +% images. See spm_format.man ("Data Format" in the help facility) for +% further details of the Analyze image format used by SPM. +% +% Similarly, secondary images should be aligned with the input images +% used for the statistical analysis. In particular the ORIGIN must +% correspond to (0,0,0) in XYZ, the vector of locations. +% +% ---------------- +% +% In addition to setting up the results section, spm_results_ui.m sets +% up the results section GUI and services the CallBacks. FORMAT +% specifications for embedded CallBack functions are given in the main +% body of the code. +%_______________________________________________________________________ +% @(#)spm_results_ui.m 2.42 Karl Friston, Andrew Holmes 03/02/28 +SCCSid = '2.42'; + +%======================================================================= +% - FORMAT specifications for embedded CallBack functions +%======================================================================= +%( This is a multi function function, the first argument is an action ) +%( string, specifying the particular action function to take. ) +% +% spm_results_ui sets up and handles the SPM results graphical user +% unterface, initialising an XYZ registry (see spm_XYZreg.m) to co-ordinate +% locations between various location controls. +% +%_______________________________________________________________________ +% +% FORMAT hReg = spm_results_ui('SetupGUI',M,DIM,xSPM,Finter) +% Setup results GUI in Interactive window +% M - 4x4 transformation matrix relating voxel to "real" co-ordinates +% DIM - 3 vector of image X, Y & Z dimensions +% xSPM - structure containing xSPM. Required fields are: +% .Z - minimum of n Statistics {filtered on u and k} +% .XYZmm - location of voxels {mm} +% Finter - handle (or 'Tag') of Interactive window (default 'Interactive') +% hReg - handle of XYZ registry object +% +% FORMAT spm_results_ui('DrawButts',hReg,DIM,Finter,WS,FS) +% Draw GUI buttons +% hReg - handle of XYZ registry object +% DIM - 3 vector of image X, Y & Z dimensions +% Finter - handle of Interactive window +% WS - WinScale [Default spm('WinScale') ] +% FS - FontSizes [Default spm('FontSizes')] +% +% FORMAT hFxyz = spm_results_ui('DrawXYZgui',M,DIM,xSPM,xyz,Finter) +% Setup editable XYZ control widgets at foot of Interactive window +% M - 4x4 transformation matrix relating voxel to "real" co-ordinates +% DIM - 3 vector of image X, Y & Z dimensions +% xSPM - structure containing SPM. Required fields are: +% .Z - minimum of n Statistics {filtered on u and k} +% .XYZmm - location of voxels {mm} +% xyz - Initial xyz location {mm} +% Finter - handle of Interactive window +% hFxyz - handle of XYZ control - the frame containing the edit widgets +% +% FORMAT spm_results_ui('EdWidCB') +% Callback for editable XYZ control widgets +% +% FORMAT spm_results_ui('UpdateSPMval',hFxyz) +% FORMAT spm_results_ui('UpdateSPMval',UD) +% Updates SPM value string in Results GUI (using data from UserData of hFxyz) +% hFxyz - handle of frame enclosing widgets - the Tag object for this control +% UD - XYZ data structure (UserData of hFxyz). +% +% FORMAT xyz = spm_results_ui('GetCoords',hFxyz) +% Get current co-ordinates from editable XYZ control +% hFxyz - handle of frame enclosing widgets - the Tag object for this control +% xyz - current co-ordinates {mm} +% NB: When using the results section, should use XYZregistry to get/set location +% +% FORMAT [xyz,d] = spm_results_ui('SetCoords',xyz,hFxyz,hC) +% Set co-ordinates to XYZ widget +% xyz - (Input) desired co-ordinates {mm} +% hFxyz - handle of XYZ control - the frame containing the edit widgets +% hC - handle of calling object, if used as a callback. [Default 0] +% xyz - (Output) Desired co-ordinates are rounded to nearest voxel if hC +% is not specified, or is zero. Otherwise, caller is assummed to +% have checked verity of desired xyz co-ordinates. Output xyz returns +% co-ordinates actually set {mm}. +% d - Euclidean distance between desired and set co-ordinates. +% NB: When using the results section, should use XYZregistry to get/set location +% +% FORMAT hFxyz = spm_results_ui('FindXYZframe',h) +% Find/check XYZ edit widgets frame handle, 'Tag'ged 'hFxyz' +% h - handle of frame enclosing widgets, or containing figure [default gcf] +% If isstr(h), then uses spm_figure('FindWin',h) to locate named figures +% hFxyz - handle of confirmed XYZ editable widgets control +% Errors if hFxyz is not an XYZ widget control, or a figure containing +% a unique such control +% +% FORMAT spm_results_ui('PlotUi',hAx) +% GUI for adjusting plot attributes - Sets up controls just above results GUI +% hAx - handle of axes to work with +% +% FORMAT spm_results_ui('PlotUiCB') +% CallBack handler for Plot attribute GUI +% +% FORMAT Fgraph = spm_results_ui('Clear',F,mode) +% Clears results subpane of Graphics window, deleting all but semi-permanent +% results section stuff +% F - handle of Graphics window [Default spm_figure('FindWin','Graphics')] +% mode - 1 [default] - clear results subpane +% - 0 - clear results subpane and hide results stuff +% - 2 - clear, but respect 'NextPlot' 'add' axes +% (which is set by `hold on`) +% Fgraph - handle of Graphics window +% +% FORMAT hMP = spm_results_ui('LaunchMP',M,DIM,hReg,hBmp) +% Prototype callback handler for integrating MultiPlanar toolbox +% +% FORMAT spm_results_ui('Delete',h) +% deletes HandleGraphics objects, but only if they're valid, thus avoiding +% warning statements from MatLab! +%_______________________________________________________________________ + + +%-Condition arguments +%----------------------------------------------------------------------- +if nargin == 0, Action='SetUp'; else, Action=varargin{1}; end + + +%======================================================================= +switch lower(Action), case 'setup' %-Set up results +%======================================================================= + +%-Initialise +%----------------------------------------------------------------------- +SPMid = spm('FnBanner',mfilename,SCCSid); +[Finter,Fgraph,CmdLine] = spm('FnUIsetup','Stats: Results'); +FS = spm('FontSizes'); + +% clear satfig if it exists +%----------------------------------------------------------------------- +hSat = findobj('tag','Satellite'); +spm_figure('clear',hSat); + +%-Get thresholded xSPM data and parameters of design +%======================================================================= +[SPM,xSPM] = spm_getSPM; +M = SPM.xVol.M; +DIM = SPM.xVol.DIM; + +% ensure pwd = swd so that relative filenames are valid +%----------------------------------------------------------------------- +cd(SPM.swd) + +%-Setup Results User Interface; Display MIP, design matrix & parameters +%======================================================================= +spm('FigName',['SPM{',xSPM.STAT,'}: Results'],Finter,CmdLine); + + +%-Setup results GUI +%----------------------------------------------------------------------- +spm_figure('Clear',Finter) +hReg = spm_results_ui('SetupGUI',M,DIM,xSPM,Finter); + +%-Setup design interrogation menu +%----------------------------------------------------------------------- +hDesRepUI = spm_DesRep('DesRepUI',SPM); +figure(Finter) + +%-Setup Maximium intensity projection (MIP) & register +%----------------------------------------------------------------------- +hMIPax = axes('Parent',Fgraph,'Position',[0.05 0.60 0.55 0.36],'Visible','off'); +hMIPax = spm_mip_ui(xSPM.Z,xSPM.XYZmm,M,DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); +if xSPM.STAT == 'P' + str = xSPM.STATstr; +else + str = ['SPM\{',xSPM.STATstr,'\}']; +end +text(240,260,str,... + 'Interpreter','TeX',... + 'FontSize',FS(14),'Fontweight','Bold',... + 'Parent',hMIPax) + + +%-Print comparison title +%----------------------------------------------------------------------- +hTitAx = axes('Parent',Fgraph,... + 'Position',[0.02 0.95 0.96 0.02],... + 'Visible','off'); + +text(0.5,0,xSPM.title,'Parent',hTitAx,... + 'HorizontalAlignment','center',... + 'VerticalAlignment','baseline',... + 'FontWeight','Bold','FontSize',FS(14)) + + +%-Print SPMresults: Results directory & thresholding info +%----------------------------------------------------------------------- +hResAx = axes('Parent',Fgraph,... + 'Position',[0.05 0.55 0.45 0.05],... + 'DefaultTextVerticalAlignment','baseline',... + 'DefaultTextFontSize',FS(9),... + 'DefaultTextColor',[1,1,1]*.7,... + 'Units','points',... + 'Visible','off'); +AxPos = get(hResAx,'Position'); set(hResAx,'YLim',[0,AxPos(4)]) +h = text(0,24,'SPMresults:','Parent',hResAx,... + 'FontWeight','Bold','FontSize',FS(14)); +text(get(h,'Extent')*[0;0;1;0],24,spm_str_manip(SPM.swd,'a30'),'Parent',hResAx) +text(0,12,sprintf('Height threshold %c = %0.2f',xSPM.STAT,xSPM.u),'Parent',hResAx) +text(0,00,sprintf('Extent threshold k = %0.0f voxels',xSPM.k), 'Parent',hResAx) + + +%-Plot design matrix +%----------------------------------------------------------------------- +hDesMtx = axes('Parent',Fgraph,'Position',[0.65 0.55 0.25 0.25]); +hDesMtxIm = image((SPM.xX.nKX + 1)*32); +xlabel('Design matrix') +set(hDesMtxIm,'ButtonDownFcn','spm_DesRep(''SurfDesMtx_CB'')',... + 'UserData',struct(... + 'X', SPM.xX.xKXs.X,... + 'fnames', {reshape({SPM.xY.VY.fname},size(SPM.xY.VY))},... + 'Xnames', {SPM.xX.name})) + +%-Plot contrasts +%----------------------------------------------------------------------- +nPar = size(SPM.xX.X,2); +xx = [repmat([0:nPar-1],2,1);repmat([1:nPar],2,1)]; +nCon = length(xSPM.Ic); +xCon = SPM.xCon; +if nCon + dy = 0.15/max(nCon,2); + hConAx = axes('Position',[0.65 (0.80 + dy*.1) 0.25 dy*(nCon-.1)],... + 'Tag','ConGrphAx','Visible','off'); + title('contrast(s)') + htxt = get(hConAx,'title'); + set(htxt,'Visible','on','HandleVisibility','on') +end + +for ii = nCon:-1:1 + axes('Position',[0.65 (0.80 + dy*(nCon - ii +.1)) 0.25 dy*.9]) + if xCon(xSPM.Ic(ii)).STAT == 'T' & size(xCon(xSPM.Ic(ii)).c,2) == 1 + + %-Single vector contrast for SPM{t} - bar + %--------------------------------------------------------------- + yy = [zeros(1,nPar);repmat(xCon(xSPM.Ic(ii)).c',2,1);zeros(1,nPar)]; + h = patch(xx,yy,[1,1,1]*.5); + set(gca,'Tag','ConGrphAx',... + 'Box','off','TickDir','out',... + 'XTick',spm_DesRep('ScanTick',nPar,10) - 0.5,'XTickLabel','',... + 'XLim', [0,nPar],... + 'YTick',[-1,0,+1],'YTickLabel','',... + 'YLim',[min(xCon(xSPM.Ic(ii)).c),max(xCon(xSPM.Ic(ii)).c)] +... + [-1 +1] * max(abs(xCon(xSPM.Ic(ii)).c))/10 ) + + else + + %-F-contrast - image + %--------------------------------------------------------------- + h = image((xCon(xSPM.Ic(ii)).c'/max(abs(xCon(xSPM.Ic(ii)).c(:)))+1)*32); + set(gca,'Tag','ConGrphAx',... + 'Box','on','TickDir','out',... + 'XTick',spm_DesRep('ScanTick',nPar,10),'XTickLabel','',... + 'XLim', [0,nPar]+0.5,... + 'YTick',[0:size(SPM.xCon(xSPM.Ic(ii)).c,2)]+0.5,.... + 'YTickLabel','',... + 'YLim', [0,size(xCon(xSPM.Ic(ii)).c,2)]+0.5 ) + + end + ylabel(num2str(xSPM.Ic(ii))) + set(h,'ButtonDownFcn','spm_DesRep(''SurfCon_CB'')',... + 'UserData', struct( 'i', xSPM.Ic(ii),... + 'h', htxt,... + 'xCon', xCon(xSPM.Ic(ii)))) +end + + +%-Store handles of results section Graphics window objects +%----------------------------------------------------------------------- +H = get(Fgraph,'Children'); +H = findobj(H,'flat','HandleVisibility','on'); +H = findobj(H); +Hv = get(H,'Visible'); +set(hResAx,'Tag','PermRes','UserData',struct('H',H,'Hv',{Hv})) + + +%-Finished results setup +%----------------------------------------------------------------------- +varargout = {hReg,xSPM,SPM}; +spm('Pointer','Arrow') + + +%======================================================================= +case 'setupgui' %-Set up results section GUI +%======================================================================= +% hReg = spm_results_ui('SetupGUI',M,DIM,xSPM,Finter) +if nargin < 5, Finter='Interactive'; else, Finter = varargin{5}; end +if nargin < 4, error('Insufficient arguments'), end +M = varargin{2}; +DIM = varargin{3}; +Finter = spm_figure('GetWin',Finter); +WS = spm('WinScale'); +FS = spm('FontSizes'); + +%-Create frame for Results GUI objects +%----------------------------------------------------------------------- +hReg = uicontrol(Finter,'Style','Frame','Position',[001 001 400 190].*WS,... + 'BackgroundColor',spm('Colour')); +hFResUi = uicontrol(Finter,'Style','Frame','Position',[008 007 387 178].*WS); + +%-Initialise registry in hReg frame object +%----------------------------------------------------------------------- +[hReg,xyz] = spm_XYZreg('InitReg',hReg,M,DIM,[0;0;0]); + +%-Setup editable XYZ widgets & cross register with registry +%----------------------------------------------------------------------- +hFxyz = spm_results_ui('DrawXYZgui',M,DIM,varargin{4},xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +%-Set up buttons for results functions +%----------------------------------------------------------------------- +spm_results_ui('DrawButts',hReg,DIM,Finter,WS,FS); + +varargout = {hReg}; + + + +%======================================================================= +case 'drawbutts' %-Draw results section buttons in Interactive window +%======================================================================= +% spm_results_ui('DrawButts',hReg,DIM,Finter,WS,FS) +% +if nargin<3, error('Insufficient arguments'), end +hReg = varargin{2}; +DIM = varargin{3}; +if nargin<4, Finter = spm_figure('FindWin','Interactive'); + else, Finter = varargin{4}; end +if nargin < 5, WS = spm('WinScale'); else, WS = varargin{5}; end +if nargin < 6, FS = spm('FontSizes'); else, FS = varargin{6}; end +PF = spm_platform('fonts'); + +%-p-values +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[010 090 110 085].*WS) +uicontrol(Finter,'Style','Text','String','p-values',... + 'Position',[020 168 050 015].*WS,... + 'FontName',PF.times,'FontWeight','Normal','FontAngle','Italic',... + 'FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w') +uicontrol(Finter,'Style','PushButton','String','volume','FontSize',FS(10),... + 'ToolTipString',... + 'tabulate summary of local maxima, p-values & statistics',... + 'Callback','spm_list(''List'',xSPM,hReg);',... + 'Interruptible','on','Enable','on',... + 'Position',[015 145 100 020].*WS) +uicontrol(Finter,'Style','PushButton','String','cluster','FontSize',FS(10),... + 'ToolTipString',... + 'tabulate p-values & statistics for local maxima of nearest cluster',... + 'Callback','spm_list(''ListCluster'',xSPM,hReg);',... + 'Interruptible','on','Enable','on',... + 'Position',[015 120 100 020].*WS) +uicontrol(Finter,'Style','PushButton','String','S.V.C.','FontSize',FS(10),... + 'ToolTipString',['Small Volume Correction - corrected p-values ',... + 'for a small search region'],... + 'Callback','spm_VOI(SPM,xSPM,hReg);',... + 'Interruptible','on','Enable','on',... + 'Position',[015 095 100 020].*WS) + + +%-SPM area - used for Volume of Interest +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[125 090 150 085].*WS) +uicontrol(Finter,'Style','Text','String','Regional responses',... + 'Position',[135 168 94 015].*WS,... + 'FontName',PF.times,'FontWeight','Normal','FontAngle','Italic',... + 'FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w') +uicontrol(Finter,'Style','PushButton','String','VOI',... + 'Position',[130 100 140 060].*WS,... + 'ToolTipString',... + 'Responses in volume of interest',... + 'Callback','[Y,xY] = spm_regions(xSPM,SPM,hReg)',... + 'Interruptible','on','Enable','on',... + 'FontName',PF.times,'FontWeight','Bold','FontAngle','Italic',... + 'FontSize',FS(32),... + 'HorizontalAlignment','Center',... + 'ForegroundColor',[1,1,1]*.5) + +%-Hemodynamic modeling +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[125 050 150 030].*WS) +global defaults +if strcmp(defaults.modality,'FMRI') +uicontrol(Finter,'Style','PushButton','String','Hemodynamics',... + 'FontSize',FS(10),... + 'ToolTipString','Hemodynamic modeling of regional response',... + 'Callback','[Ep,Cp,K1,K2] = spm_hdm_ui(xSPM,SPM,hReg);',... + 'Interruptible','on','Enable','on',... + 'Position',[130 055 140 020].*WS,... + 'ForegroundColor','r'); +end + +%-Not currently used +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[010 050 110 030].*WS) +if strcmp(defaults.modality,'FMRI') +uicontrol(Finter,'Style','PushButton','String',' ','FontSize',FS(10),... + 'ToolTipString',' ',... + 'Callback',' ',... + 'Interruptible','on','Enable','on',... + 'Position',[015 055 100 020].*WS) +end + +%-Visualisation +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[280 090 110 085].*WS) +uicontrol(Finter,'Style','Text','String','visualisation',... + 'Position',[290 168 065 015].*WS,... + 'FontName',PF.times,'FontWeight','Normal','FontAngle','Italic',... + 'FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w') +uicontrol(Finter,'Style','PushButton','String','plot','FontSize',FS(10),... + 'ToolTipString','plot data & contrasts at current voxel',... + 'Callback','[Y,y,beta,Bcov] = spm_graph(xSPM,SPM,hReg);',... + 'Interruptible','on','Enable','on',... + 'Position',[285 145 100 020].*WS) + +str = { 'overlays...','slices','sections','render', 'colin27'}; +tstr = { 'overlay filtered SPM on another image: ',... + '3 slices / ','ortho sections / ','render', 'sections from colin27''s canonical brain'}; +tmp = { 'spm_transverse(''set'',xSPM,hReg)',... + 'spm_sections(xSPM,hReg)',... + ['spm_render( struct( ''XYZ'', xSPM.XYZ,',... + '''t'', xSPM.Z'',',... + '''mat'', xSPM.M,',... + '''dim'', xSPM.DIM))'],... + 'spm_sections(xSPM,hReg,fullfile(spm(''dir''),''canonical'',''single_subj_T1.mnc''))'}; + % 'spm_sections_colin27(xSPM,hReg)'}; +if DIM(3) == 1, str(2 + 1) = []; tstr(2 + 1) = []; tmp(2) = []; end +uicontrol(Finter,'Style','PopUp','String',str,'FontSize',FS(10),... + 'ToolTipString',cat(2,tstr{:}),... + 'Callback','spm(''PopUpCB'',gcbo)',... + 'UserData',tmp,... + 'Interruptible','on','Enable','on',... + 'Position',[285 120 100 020].*WS) +uicontrol(Finter,'Style','PushButton','String','save','FontSize',FS(10),... + 'ToolTipString','save thresholded SPM as image',... + 'Callback',['spm_write_filtered(xSPM.Z,xSPM.XYZ,xSPM.DIM,xSPM.M,',... + 'sprintf(''SPM{%c}-filtered: u = %5.3f, k = %d'',',... + 'xSPM.STAT,xSPM.u,xSPM.k));'],... + 'Interruptible','on','Enable','on',... + 'Position',[285 095 100 020].*WS) + +%-ResultsUI controls +%----------------------------------------------------------------------- +uicontrol(Finter,'Style','Frame','Position',[280 050 110 030].*WS) + +hClear = uicontrol(Finter,'Style','PushButton','String','clear',... + 'ToolTipString','clears results subpane',... + 'FontSize',FS(9),'ForegroundColor','b',... + 'Callback',['spm_results_ui(''Clear''); ',... + 'spm_input(''!DeleteInputObj''),',... + 'spm_clf(''Satellite'')'],... + 'Interruptible','on','Enable','on',... + 'DeleteFcn','clc,spm_clf(''Graphics'')',... + 'Position',[285 055 035 018].*WS); + +hExit = uicontrol(Finter,'Style','PushButton','String','exit',... + 'ToolTipString','exit the results section',... + 'FontSize',FS(9),'ForegroundColor','r',... + 'Callback',['spm_clf(''Interactive''), spm_clf(''Graphics''),'... + 'close(spm_figure(''FindWin'',''Satellite'')),'... + 'clear'],... + 'Interruptible','on','Enable','on',... + 'Position',[325 055 035 018].*WS); + +hHelp = uicontrol(Finter,'Style','PushButton','String','?',... + 'ToolTipString','results section help',... + 'FontSize',FS(9),'ForegroundColor','g',... + 'Callback','spm_help(''spm_results_ui'')',... + 'Interruptible','on','Enable','on',... + 'Position',[365 055 020 018].*WS); + + +%======================================================================= +case 'drawxyzgui' %-Draw XYZ GUI area +%======================================================================= +% hFxyz = spm_results_ui('DrawXYZgui',M,DIM,xSPM,xyz,Finter) +if nargin<6, Finter=spm_figure('FindWin','Interactive'); + else, Finter=varargin{6}; end +if nargin < 5, xyz=[0;0;0]; else, xyz=varargin{5}; end +if nargin < 4, error('Insufficient arguments'), end +DIM = varargin{3}; +M = varargin{2}; +xyz = spm_XYZreg('RoundCoords',xyz,M,DIM); + +%-Locate windows etc... +%----------------------------------------------------------------------- +WS = spm('WinScale'); +FS = spm('FontSizes'); +PF = spm_platform('fonts'); + +%-Create XYZ control objects +%----------------------------------------------------------------------- +hFxyz = uicontrol(Finter,'Style','Frame','Position',[010 010 265 030].*WS); +uicontrol(Finter,'Style','Text','String','co-ordinates',... + 'Position',[020 033 078 016].*WS,... + 'FontName',PF.times,'FontWeight','Normal','FontAngle','Italic',... + 'FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w') + +uicontrol(Finter,'Style','Text','String','x =',... + 'Position',[020 015 024 018].*WS,... + 'FontName',PF.times,'FontSize',FS(10),'FontAngle','Italic',... + 'HorizontalAlignment','Center'); +hX = uicontrol(Finter,'Style','Edit','String',sprintf('%.2f',xyz(1)),... + 'ToolTipString','enter x-coordinate',... + 'Position',[044 015 056 020].*WS,... + 'FontSize',FS(10),'BackGroundColor',[.8,.8,1],... + 'HorizontalAlignment','Right',... + 'Tag','hX',... + 'Callback','spm_results_ui(''EdWidCB'')'); + +uicontrol(Finter,'Style','Text','String','y =',... + 'Position',[105 015 024 018].*WS,... + 'FontName',PF.times,'FontSize',FS(10),'FontAngle','Italic',... + 'HorizontalAlignment','Center') +hY = uicontrol(Finter,'Style','Edit','String',sprintf('%.2f',xyz(2)),... + 'ToolTipString','enter y-coordinate',... + 'Position',[129 015 056 020].*WS,... + 'FontSize',FS(10),'BackGroundColor',[.8,.8,1],... + 'HorizontalAlignment','Right',... + 'Tag','hY',... + 'Callback','spm_results_ui(''EdWidCB'')'); + +uicontrol(Finter,'Style','Text','String','z =',... + 'Position',[190 015 024 018].*WS,... + 'FontName',PF.times,'FontSize',FS(10),'FontAngle','Italic',... + 'HorizontalAlignment','Center') +hZ = uicontrol(Finter,'Style','Edit','String',sprintf('%.2f',xyz(3)),... + 'ToolTipString','enter z-coordinate',... + 'Position',[214 015 056 020].*WS,... + 'FontSize',FS(10),'BackGroundColor',[.8,.8,1],... + 'HorizontalAlignment','Right',... + 'Tag','hZ',... + 'Callback','spm_results_ui(''EdWidCB'')'); + +%-Statistic value reporting pane +%----------------------------------------------------------------------- +hFconB = uicontrol(Finter,'Style','Frame','Position',[280 010 110 030].*WS); +uicontrol(Finter,'Style','Text','String','statistic value',... + 'Position',[285 035 085 016].*WS,... + 'FontName',PF.times,'FontWeight','Normal','FontAngle','Italic',... + 'FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w') +hSPM = uicontrol(Finter,'Style','Text','String','',... + 'Position',[285 012 100 020].*WS,... + 'FontSize',FS(10),... + 'HorizontalAlignment','Center'); + + +%-Store data +%----------------------------------------------------------------------- +set(hFxyz,'Tag','hFxyz','UserData',struct(... + 'hReg', [],... + 'M', M,... + 'DIM', DIM,... + 'XYZ', varargin{4}.XYZmm,... + 'Z', varargin{4}.Z,... + 'hX', hX,... + 'hY', hY,... + 'hZ', hZ,... + 'hSPM', hSPM,... + 'xyz', xyz )); + +set([hX,hY,hZ],'UserData',hFxyz) +varargout = {hFxyz}; + + + +%======================================================================= +case 'edwidcb' %-Callback for editable widgets +%======================================================================= +% spm_results_ui('EdWidCB') + +hC = gcbo; +d = find(strcmp(get(hC,'Tag'),{'hX','hY','hZ'})); +hFxyz = get(hC,'UserData'); +UD = get(hFxyz,'UserData'); +xyz = UD.xyz; +nxyz = xyz; + +o = evalin('base',['[',get(hC,'String'),']'],'sprintf(''error'')'); +if ischar(o) | length(o)>1 + warning(sprintf('%s: Error evaluating ordinate:\n\t%s',... + mfilename,lasterr)) +else + nxyz(d) = o; + nxyz = spm_XYZreg('RoundCoords',nxyz,UD.M,UD.DIM); +end + +if abs(xyz(d)-nxyz(d))>0 + UD.xyz = nxyz; set(hFxyz,'UserData',UD) + if ~isempty(UD.hReg), spm_XYZreg('SetCoords',nxyz,UD.hReg,hFxyz); end + set(hC,'String',sprintf('%.3f',nxyz(d))) + spm_results_ui('UpdateSPMval',UD) +end + +%======================================================================= +case 'updatespmval' %-Update SPM value in GUI +%======================================================================= +% spm_results_ui('UpdateSPMval',hFxyz) +% spm_results_ui('UpdateSPMval',UD) +if nargin<2, error('insufficient arguments'), end +if isstruct(varargin{2}), UD=varargin{2}; else, UD = get(varargin{2},'UserData'); end +i = spm_XYZreg('FindXYZ',UD.xyz,UD.XYZ); +if isempty(i), str = ''; else, str = sprintf('%6.2f',UD.Z(i)); end +set(UD.hSPM,'String',str); + + +%======================================================================= +case 'getcoords' % Get current co-ordinates from XYZ widget +%======================================================================= +% xyz = spm_results_ui('GetCoords',hFxyz) +if nargin<2, hFxyz='Interactive'; else, hFxyz=varargin{2}; end +hFxyz = spm_results_ui('FindXYZframe',hFxyz); +varargout = {getfield(get(hFxyz,'UserData'),'xyz')}; + + + +%======================================================================= +case 'setcoords' % Set co-ordinates to XYZ widget +%======================================================================= +% [xyz,d] = spm_results_ui('SetCoords',xyz,hFxyz,hC) +if nargin<4, hC=0; else, hC=varargin{4}; end +if nargin<3, hFxyz=spm_results_ui('FindXYZframe'); else, hFxyz=varargin{3}; end +if nargin<2, error('Set co-ords to what!'), else, xyz=varargin{2}; end + +%-If this is an internal call, then don't do anything +if hFxyz==hC, return, end + +UD = get(hFxyz,'UserData'); + +%-Check validity of coords only when called without a caller handle +%----------------------------------------------------------------------- +if hC <= 0 + [xyz,d] = spm_XYZreg('RoundCoords',xyz,UD.M,UD.DIM); + if d>0 & nargout<2, warning(sprintf(... + '%s: Co-ords rounded to neatest voxel center: Discrepancy %.2f',... + mfilename,d)), end +else + d = []; +end + +%-Update xyz information & widget strings +%----------------------------------------------------------------------- +UD.xyz = xyz; set(hFxyz,'UserData',UD) +set(UD.hX,'String',sprintf('%.2f',xyz(1))) +set(UD.hY,'String',sprintf('%.2f',xyz(2))) +set(UD.hZ,'String',sprintf('%.2f',xyz(3))) +spm_results_ui('UpdateSPMval',UD) + +%-Tell the registry, if we've not been called by the registry... +%----------------------------------------------------------------------- +if (~isempty(UD.hReg) & UD.hReg~=hC) + spm_XYZreg('SetCoords',xyz,UD.hReg,hFxyz); +end + +%-Return arguments +%----------------------------------------------------------------------- +varargout = {xyz,d}; + + + +%======================================================================= +case 'findxyzframe' % Find hFxyz frame +%======================================================================= +% hFxyz = spm_results_ui('FindXYZframe',h) +% Sorts out hFxyz handles +if nargin<2, h='Interactive'; else, h=varargin{2}; end +if isstr(h), h=spm_figure('FindWin',h); end +if ~ishandle(h), error('invalid handle'), end +if ~strcmp(get(h,'Tag'),'hFxyz'), h=findobj(h,'Tag','hFxyz'); end +if isempty(h), error('XYZ frame not found'), end +if length(h)>1, error('Multiple XYZ frames found'), end +varargout = {h}; + + + +%======================================================================= +case 'plotui' %-GUI for plot manipulation +%======================================================================= +% spm_results_ui('PlotUi',hAx) +if nargin<2, hAx=gca; else, hAx=varargin{2}; end + +WS = spm('WinScale'); +FS = spm('FontSizes'); +Finter=spm_figure('FindWin','Interactive'); +figure(Finter) + +%-Check there aren't already controls! +%----------------------------------------------------------------------- +hGraphUI = findobj(Finter,'Tag','hGraphUI'); +if ~isempty(hGraphUI) %-Controls exist + hBs = get(hGraphUI,'UserData'); + if hAx==get(hBs(1),'UserData') %-Controls linked to these axes + return + else %-Old controls remain + delete(findobj(Finter,'Tag','hGraphUIbg')) + end +end + +%-Frames & text +%----------------------------------------------------------------------- +hGraphUIbg = uicontrol(Finter,'Style','Frame','Tag','hGraphUIbg',... + 'BackgroundColor',spm('Colour'),... + 'Position',[001 196 400 055].*WS); +hGraphUI = uicontrol(Finter,'Style','Frame','Tag','hGraphUI',... + 'Position',[008 202 387 043].*WS); +hGraphUIButtsF = uicontrol(Finter,'Style','Frame',... + 'Position',[010 205 380 030].*WS); +hText = uicontrol(Finter,'Style','Text','String','plot controls',... + 'Position',[020 227 080 016].*WS,... + 'FontName',spm_platform('font','times'),'FontWeight','Normal',... + 'FontAngle','Italic','FontSize',FS(10),... + 'HorizontalAlignment','Left',... + 'ForegroundColor','w'); + +%-Controls +%----------------------------------------------------------------------- +h1 = uicontrol(Finter,'Style','CheckBox','String','hold',... + 'ToolTipString','toggle hold to overlay plots',... + 'FontSize',FS(10),... + 'Value',strcmp(get(hAx,'NextPlot'),'add'),... + 'Callback',[... + 'if get(gcbo,''Value''), ',... + 'set(get(gcbo,''UserData''),''NextPlot'',''add''), ',... + 'else, ',... + 'set(get(gcbo,''UserData''),''NextPlot'',''replace''), ',... + 'end'],... + 'Interruptible','on','Enable','on',... + 'Position',[015 210 070 020].*WS); +h2 = uicontrol(Finter,'Style','CheckBox','String','grid',... + 'ToolTipString','toggle axes grid',... + 'FontSize',FS(10),... + 'Value',strcmp(get(hAx,'XGrid'),'on'),... + 'Callback',[... + 'if get(gcbo,''Value''), ',... + 'set(get(gcbo,''UserData''),''XGrid'',''on'','... + '''YGrid'',''on'',''ZGrid'',''on''), ',... + 'else, ',... + 'set(get(gcbo,''UserData''),''XGrid'',''off'','... + '''YGrid'',''off'',''ZGrid'',''off''), ',... + 'end'],... + 'Interruptible','on','Enable','on',... + 'Position',[090 210 070 020].*WS); +h3 = uicontrol(Finter,'Style','CheckBox','String','Box',... + 'ToolTipString','toggle axes box',... + 'FontSize',FS(10),... + 'Value',strcmp(get(hAx,'Box'),'on'),... + 'Callback',[... + 'if get(gcbo,''Value''), ',... + 'set(get(gcbo,''UserData''),''Box'',''on''), ',... + 'else, ',... + 'set(get(gcbo,''UserData''),''Box'',''off''), ',... + 'end'],... + 'Interruptible','on','Enable','on',... + 'Position',[165 210 070 020].*WS); +h4 = uicontrol(Finter,'Style','PopUp',... + 'ToolTipString','edit axis text annotations',... + 'FontSize',FS(10),... + 'String','text|Title|Xlabel|Ylabel',... + 'Callback','spm_results_ui(''PlotUiCB'')',... + 'Interruptible','on','Enable','on',... + 'Position',[240 210 070 020].*WS); +h5 = uicontrol(Finter,'Style','PopUp',... + 'ToolTipString','change various axes attributes',... + 'FontSize',FS(10),... + 'String','attrib|LineWidth|XLim|YLim|handle',... + 'Callback','spm_results_ui(''PlotUiCB'')',... + 'Interruptible','off','Enable','on',... + 'Position',[315 210 070 020].*WS); + +%-Handle storage for linking, and DeleteFcns for linked deletion +%----------------------------------------------------------------------- +set(hGraphUI,'UserData',[h1,h2,h3,h4,h5]) +set([h1,h2,h3,h4,h5],'UserData',hAx) + +set(hGraphUIbg,'UserData',... + [hGraphUI,hGraphUIButtsF,hText,h1,h2,h3,h4,h5],... + 'DeleteFcn','spm_results_ui(''Delete'',get(gcbo,''UserData''))') +set(hAx,'UserData',hGraphUIbg,... + 'DeleteFcn','spm_results_ui(''Delete'',get(gcbo,''UserData''))') + + + + +%======================================================================= +case 'plotuicb' +%======================================================================= +% spm_results_ui('PlotUiCB') +hPM = gcbo; +v = get(hPM,'Value'); +if v==1, return, end +str = cellstr(get(hPM,'String')); +str = str{v}; + +hAx = get(hPM,'UserData'); +switch str +case 'Title' + h = get(hAx,'Title'); + set(h,'String',spm_input('Enter title:',-1,'s+',get(h,'String'))) +case 'Xlabel' + h = get(hAx,'Xlabel'); + set(h,'String',spm_input('Enter X axis label:',-1,'s+',get(h,'String'))) +case 'Ylabel' + h = get(hAx,'Ylabel'); + set(h,'String',spm_input('Enter Y axis label:',-1,'s+',get(h,'String'))) +case 'LineWidth' + lw = spm_input('Enter LineWidth',-1,'e',get(hAx,'LineWidth'),1); + set(hAx,'LineWidth',lw) +case 'XLim' + XLim = spm_input('Enter XLim',-1,'e',get(hAx,'XLim'),[1,2]); + set(hAx,'XLim',XLim) +case 'YLim' + YLim = spm_input('Enter YLim',-1,'e',get(hAx,'YLim'),[1,2]); + set(hAx,'YLim',YLim) +case 'handle' + varargout={hAx}; +otherwise + warning(['Unknown action: ',str]) +end + +set(hPM,'Value',1) + + +%======================================================================= +case {'clear','clearpane'} %-Clear results subpane +%======================================================================= +% Fgraph = spm_results_ui('Clear',F,mode) +% mode 1 [default] usual, mode 0 - clear & hide Res stuff, 2 - RNP +if strcmp(lower(Action),'clearpane') + warning('''ClearPane'' action is grandfathered, use ''Clear'' instead') +end + +if nargin<3, mode=1; else, mode=varargin{3}; end +if nargin<2, F='Graphics'; else, F=varargin{2}; end +F = spm_figure('FindWin',F); + +%-Clear input objects from 'Interactive' window +%----------------------------------------------------------------------- +%spm_input('!DeleteInputObj') + + +%-Get handles of objects in Graphics window & note permanent results objects +%----------------------------------------------------------------------- +H = get(F,'Children'); %-Get contents of window +H = findobj(H,'flat','HandleVisibility','on'); %-Drop GUI components +h = findobj(H,'flat','Tag','PermRes'); %-Look for 'PermRes' object + +if ~isempty(h) + %-Found 'PermRes' object + % This has handles of permanent results objects in it's UserData + tmp = get(h,'UserData'); + HR = tmp.H; + HRv = tmp.Hv; +else + %-No trace of permanent results objects + HR = []; + HRv = {}; +end +H = setdiff(H,HR); %-Drop permanent results obj + + +%-Delete stuff as appropriate +%----------------------------------------------------------------------- +if mode==2 %-Don't delete axes with NextPlot 'add' + H = setdiff(H,findobj(H,'flat','Type','axes','NextPlot','add')); +end + +delete(H) + +if mode==0 %-Hide the permanent results section stuff + set(HR,'Visible','off') +else + set(HR,{'Visible'},HRv) +end + + +%======================================================================= +case 'launchmp' %-Launch multiplanar toolbox +%======================================================================= +% hMP = spm_results_ui('LaunchMP',M,DIM,hReg,hBmp) +if nargin<5, hBmp = gcbo; else, hBmp = varargin{5}; end +hReg = varargin{4}; +DIM = varargin{3}; +M = varargin{2}; + +%-Check for existing MultiPlanar toolbox +hMP = get(hBmp,'UserData'); +if ishandle(hMP) + figure(spm_figure('ParentFig',hMP)) + varargout = {hMP}; + return +end + +%-Initialise and cross-register MultiPlanar toolbox +hMP = spm_XYZreg_Ex2('Create',M,DIM); +spm_XYZreg('Xreg',hReg,hMP,'spm_XYZreg_Ex2'); + +%-Setup automatic deletion of MultiPlanar on deletion of results controls +set(hBmp,'Enable','on','UserData',hMP) +set(hBmp,'DeleteFcn','spm_results_ui(''delete'',get(gcbo,''UserData''))') + +varargout = {hMP}; + + + +%======================================================================= +case 'delete' %-Delete HandleGraphics objects +%======================================================================= +% spm_results_ui('Delete',h) +h = varargin{2}; +delete(h(ishandle(h))); + + +%======================================================================= +otherwise +%======================================================================= +error('Unknown action string') + +%======================================================================= +end + diff --git a/spm/spm2/spm_sections.m b/spm/spm2/spm_sections.m new file mode 100644 index 0000000..8967ce3 --- /dev/null +++ b/spm/spm2/spm_sections.m @@ -0,0 +1,36 @@ +function spm_sections(SPM,hReg,spms) +% rendering of regional effects [SPM{Z}] on orthogonal sections of +% (a brain from an img file if given) +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% spm_sections(SPM,hReg,imgfile) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = spm_figure('FindWin','Graphics'); +if nargin<3 +spms = spm_get(1,'IMAGE','select image for rendering on'); +end +spm_results_ui('Clear',Fgraph); +spm_orthviews('Reset'); +global st +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; +spm_orthviews('Image',spms,[0.05 0.05 0.9 0.45]); +spm_orthviews MaxBB; +spm_orthviews('register',hReg); +spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +spm_orthviews('Redraw'); diff --git a/spm/spm2/spm_spm.m b/spm/spm2/spm_spm.m new file mode 100644 index 0000000..4ca45cd --- /dev/null +++ b/spm/spm2/spm_spm.m @@ -0,0 +1,948 @@ +function [SPM] = spm_spm(SPM) +% [Re]ML Estimation of a General Linear Model +% FORMAT [SPM] = spm_spm(SPM) +% +% required fields of SPM: +% +% xY.VY - nScan x 1 struct array of mapped image volumes +% Images must have the same orientation, voxel size and data type +% - Any scaling should have already been applied via the image handle +% scalefactors. +% +% xX - Structure containing design matrix information +% - Required fields are: +% xX.X - Design matrix (raw, not temporally smoothed) +% xX.name - cellstr of parameter names corresponding to columns +% of design matrix +% - Optional fields are: +% xX.K - cell of session-specific structures (see spm_filter) +% - Design & data are pre-multiplied by K +% (K*Y = K*X*beta + K*e) +% - Note that K should not smooth across block boundaries +% - defaults to speye(size(xX.X,1)) +% xX.W - Optional whitening/weighting matrix used to give +% weighted least squares estimates (WLS). If not specified +% spm_spm will set this to whiten the data and render +% the OLS estimtes maximum likelihood +% i.e. W*W' = inv(xVi.V). +% +% xVi - structure describing intrinsic temporal non-sphericity +% - required fields are: +% xVi.Vi - array of non-sphericity components +% - defaults to {speye(size(xX.X,1))} - i.i.d. +% - specifying a cell array of contraints (Qi) +% These contraints invoke spm_reml to estimate +% hyperparameters assuming V is constant over voxels. +% that provide a high precise estimate of xX.V +% - Optional fields are: +% xX.V - Optional non-sphericity matrix. Cov(e) = sigma^2*V +% If not specified spm_spm will compute this using +% a 1st pass to identify signifcant voxels over which +% to estimate V. A 2nd pass is then used to re-estimate +% the parameters with WLS and save the ML estimates +% (unless xX.W is already specified) +% +% xM - Structure containing masking information, or a simple column vector +% of thresholds corresponding to the images in VY. +% - If a structure, the required fields are: +% xM.TH - nVar x nScan matrix of analysis thresholds, one per image +% xM.I - Implicit masking (0=>none, 1 => implicit zero/NaN mask) +% xM.VM - struct array of mapped explicit mask image volumes +% - (empty if no explicit masks) +% - Explicit mask images are >0 for valid voxels to assess. +% - Mask images can have any orientation, voxel size or data +% type. They are interpolated using nearest neighbour +% interpolation to the voxel locations of the data Y. +% - Note that voxels with constant data (i.e. the same value across +% scans) are also automatically masked out. +% +% +% In addition, the global default UFp is used to set a critical +% F-threshold for selecting voxels over which the non-sphericity +% is estimated (if required) +% +%_______________________________________________________________________ +% +% spm_spm is the heart of the SPM package. Given image files and a +% General Linear Model, it estimates the model parameters, variance +% hyerparameters, and smoothness of standardised residual fields, writing +% these out to disk in the current working directory for later +% interrogation in the results section. (NB: Existing analyses in the +% current working directory are overwritten). This directory +% now becomes the working directory for this analysis and all saved +% images are relative to this directory. +% +% The model is expressed via the design matrix (xX.X). The basic model +% at each voxel is of the form is Y = X*B + e, for data Y, design +% matrix X, (unknown) parameters B, and residual errors e. The errors +% are assummed to have a normal distribution. +% +% Sometimes confounds (e.g. drift terms in fMRI) are necessary. These +% can be specified directly in the design matrix or implicitly, in terms +% of a residual forming matrix K to give a generalised linear model +% K*Y = K*X*B + K*e. In fact K can be any matrix (e.g. a convolution +% matrix). +% +% In some instances i.i.d. assumptions about errors do not hold. For +% example, with serially correlated (fMRI) data or correlations among the +% levels of a factor in repeated measures designs. This non-sphericity +% can be specified in terms of components (SPM.xVi.Vi{i}). If specified +% these covariance components will then be estimated with ReML (restricted +% maximum likelihood) hyperparameters. This estimation assumes the same +% non-sphericity for voxels that exceed the global F-threshold. The ReML +% estimates can then used to whiten the data giving maximum likelihood (ML) +% or Gauss-Markov estimators. This entails a second pass of the data +% with an augmented model K*W*Y = K*W*X*B + K*W*e where W*W' = inv(xVi.V). +% xVi.V is the non-sphericity based on the hyperparameter esimates. +% W is stored in xX.W and cov(K*W*e) in xX.V. The covariance of the +% parameter estimates is then xX.Bcov = pinv(K*W*X)*xX.V*pinv(K*W*X)'; +% +% If you do not want ML estimates but want to use ordinary least squares +% (OLS) then simply set SPM.xX.W to the identity matrix. Any non-sphericity +% V will still be estimated but will be used to adjust the degrees of freedom +% of the ensuing statistics using the Satterthwaite approximation (c.f. +% the Greenhouse-Giesser corrections) +% +% If [non-spherical] variance components Vi are not specified xVi.Vi and +% xVi.V default to the identity matrix (i.e. i.i.d). The parameters are +% then estimated by OLS. In this instance the OLS and ML estimates are +% the same. +% +% Note that only a single voxel-specific hyperaprameter (i.e. variance +% component) is estimated, even if V is not i.i.d. This means spm_spm +% always implements a fixed-effects model. +% Random effects models can be emulated using a multi-stage procedure: +% This entails summarising the data with contrasts such that the fixed +% effects in a second model on the summary data are those effects of +% interest (i.e. the population effects). This means contrasts are +% re-entered into spm_spm to make an inference (SPM) at the next +% level. At this higher hierarchial level the residual variance for the +% model contains the appropriate variance components from lower levels. +% See spm_RandFX.man for further details and below. +% +% Under the additional assumption that the standardised residual images +% are non-stationary standard Gaussian random fields, results from +% Random field theory can be applied to estimate the significance +% statistic images (SPM's) adjusting p values for the multiple tests +% at all voxels in the search volume. The parameters required for +% this random field correction are the volume, and Lambda, the covariance +% matrix of partial derivatives of the standardised error fields. +% +% spm_est_smoothness estimates the variances of the partial derivatives +% in the axis directions (the diagonal of Lambda). The covariances (off +% diagonal elements of Lambda) are assumed to be zero. +% +% ---------------- +% +% +% The volume analsed is the intersection of the threshold masks, +% explicit masks and implicit masks. See spm_spm_ui for further details +% on masking options. +% +% +%----------------------------------------------------------------------- +% +% The output of spm_spm takes the form of an SPM.mat file of the analysis +% parameters, and 'float' flat-file images of the parameter and variance +% [hyperparameter] estimates. An 8bit zero-one mask image indicating the +% voxels assessed is also written out, with zero indicating voxels outside +% tha analysed volume. +% +% ---------------- +% +% The following SPM.fields are set by spm_spm (unless specified) +% +% xVi.V - estimated non-sphericity trace(V) = rank(V) +% xVi.h - hyperparameters xVi.V = xVi.h(1)*xVi.Vi{1} + ... +% xVi.Cy - spatially whitened (used by ReML to estimate h) +% xVi.CY - <(Y - )*(Y - )'> (used by spm_spm_Bayes) +% +% ---------------- +% +% Vbeta - struct array of beta image handles (relative) +% VResMS - file struct of ResMS image handle (relative) +% VM - file struct of Mask image handle (relative) +% +% ---------------- +% xX.W - if not specified W*W' = inv(x.Vi.V) +% xX.V - V matrix (K*W*Vi*W'*K') = correlations after K*W is applied +% xX.xKXs - space structure for K*W*X, the 'filtered and whitened' +% design matrix +% - given as spm_sp('Set',xX.K*xX.W*xX.X) - see spm_sp +% xX.pKX - pseudoinverse of K*W*X, computed by spm_sp +% xX.Bcov - xX.pKX*xX.V*xX.pKX - variance-covariance matrix of +% parameter estimates +% (when multiplied by the voxel-specific hyperparameter ResMS) +% (of the parameter estimates. (ResSS/xX.trRV = ResMS) ) +% xX.trRV - trace of R*V, computed efficiently by spm_SpUtil +% xX.trRVRV - trace of RVRV +% xX.erdf - effective residual degrees of freedom (trRV^2/trRVRV) +% xX.nKX - design matrix (xX.xKXs.X) scaled for display +% (see spm_DesMtx('sca',... for details) +% +% ---------------- +% +% xVol.M - 4x4 voxel->mm transformation matrix +% xVol.iM - 4x4 mm->voxel transformation matrix +% xVol.DIM - image dimensions - column vector (in voxels) +% xVol.XYZ - 3 x S vector of in-mask voxel coordinates +% xVol.S - Lebesgue measure or volume (in voxels) +% xVol.R - vector of resel counts (in resels) +% xVol.FWHM - Smoothness of components - FWHM, (in voxels) +% +% ---------------- +% +% xCon - See Christensen for details of F-contrasts. These are specified +% at the end of spm_spm after the non-sphericity V has been defined +% or estimated. The fist contrast tests for all effects of interest +% assuming xX.iB and xX.iG index confounding or nuisance effects. +% +% xCon - Contrast structure (created by spm_FcUtil.m) +% xCon.name - Name of contrast +% xCon.STAT - 'F', 'T' or 'P' - for F/T-contrast ('P' for PPMs) +% xCon.c - (F) Contrast weights +% xCon.X0 - Reduced design matrix (spans design space under Ho) +% It is in the form of a matrix (spm99b) or the +% coordinates of this matrix in the orthogonal basis +% of xX.X defined in spm_sp. +% xCon.iX0 - Indicates how contrast was specified: +% If by columns for reduced design matrix then iX0 contains the +% column indices. Otherwise, it's a string containing the +% spm_FcUtil 'Set' action: Usuall one of {'c','c+','X0'} +% (Usually this is the input argument F_iX0.) +% xCon.X1o - Remaining design space (orthogonal to X0). +% It is in the form of a matrix (spm99b) or the +% coordinates of this matrix in the orthogonal basis +% of xX.X defined in spm_sp. +% xCon.eidf - Effective interest degrees of freedom (numerator df) +% xCon.Vcon - ...for handle of contrast/ESS image (empty at this stage) +% xCon.Vspm - ...for handle of SPM image (empty at this stage) +% +% ---------------- +% +% +% The following images are written to file +% +% mask.{img,hdr} - analysis mask image +% 8-bit (uint8) image of zero-s & one's indicating which voxels were +% included in the analysis. This mask image is the intersection of the +% explicit, implicit and threshold masks specified in the xM argument. +% The XYZ matrix contains the voxel coordinates of all voxels in the +% analysis mask. The mask image is included for reference, but is not +% explicitly used by the results section. +% +% ---------------- +% +% beta_????.{img,hdr} - parameter images +% These are 16-bit (float) images of the parameter estimates. The image +% files are numbered according to the corresponding column of the +% design matrix. Voxels outside the analysis mask (mask.img) are given +% value NaN. +% +% ---------------- +% +% ResMS.{img,hdr} - estimated residual variance image +% This is a 32-bit (double) image of the residual variance estimate. +% Voxels outside the analysis mask are given value NaN. +% +% ---------------- +% +% RVP.{img,hdr} - estimated resels per voxel image +% This is a 32-bit (double) image of the RESELs per voxel estimate. +% Voxels outside the analysis mask are given value 0. These images +% reflect the nonstationary aspects the spatial autocorrelations. +% +% +%----------------------------------------------------------------------- +% +% References: +% +% Christensen R (1996) Plane Answers to Complex Questions +% Springer Verlag +% +% Friston KJ, Holmes AP, Worsley KJ, Poline JP, Frith CD, Frackowiak RSJ (1995) +% ``Statistical Parametric Maps in Functional Imaging: +% A General Linear Approach'' +% Human Brain Mapping 2:189-210 +% +% Worsley KJ, Friston KJ (1995) +% ``Analysis of fMRI Time-Series Revisited - Again'' +% Neuroimage 2:173-181 +% +%----------------------------------------------------------------------- +% +% For those interested, the analysis proceeds a "block" at a time, +% The block size conforms to maxMem that can be set as a global variable +% MAXMEM (in bytes) [default = 2^20] +% +%_______________________________________________________________________ +% @(#)spm_spm.m 2.66 Andrew Holmes, Jean-Baptiste Poline, Karl Friston 03/03/27 +SCCSid = '2.66'; + +%-Say hello +%----------------------------------------------------------------------- +SPMid = spm('FnBanner',mfilename,SCCSid); +Finter = spm('FigName','Stats: estimation...'); spm('Pointer','Watch') + +%-Get SPM.mat if necessary +%----------------------------------------------------------------------- +if nargin ==0 + swd = spm_str_manip(spm_get(1,'SPM.mat','Select SPM.mat'),'H'); + load(fullfile(swd,'SPM.mat')); + SPM.swd = swd; +end + +%-Change to SPM.swd if specified +%----------------------------------------------------------------------- +try + cd(SPM.swd); +end + +%-Ensure data are assigned +%----------------------------------------------------------------------- +try + SPM.xY.VY; +catch + helpdlg({ 'Please assign data to this design',... + 'Use fMRI under model specification'}); + spm('FigName','Stats: done',Finter); spm('Pointer','Arrow') + return +end + +%-Delete files from previous analyses +%----------------------------------------------------------------------- +if exist(fullfile('.','mask.img'),'file') == 2 + + str = {'Current directory contains SPM estimation files:',... + 'pwd = ',pwd,... + 'Existing results will be overwritten!'}; + + abort = spm_input(str,1,'bd','stop|continue',[1,0],1); + if abort + spm('FigName','Stats: done',Finter); spm('Pointer','Arrow') + return + else + str = sprintf('Overwriting old results\n\t (pwd = %s) ',pwd) + warning(str) + drawnow + end +end + +files = { 'mask.???','ResMS.???','RVP.???',... + 'beta_????.???','con_????.???','ResI_????.???',... + 'ess_????.???', 'spm?_????.???'}; + +for i=1:length(files) + if any(files{i} == '*'|files{i} == '?' ) + [j,null] = spm_list_files(pwd,files{i}); + for i=1:size(j,1) + spm_unlink(deblank(j(i,:))) + end + else + spm_unlink(files{i}) + end +end + + +%======================================================================= +% - A N A L Y S I S P R E L I M I N A R I E S +%======================================================================= + +%-Initialise +%======================================================================= +fprintf('%-40s: %30s','Initialising parameters','...computing') %-# +xX = SPM.xX; +[nScan nBeta] = size(xX.X); + + +%-If xM is not a structure then assumme it's a vector of thresholds +%----------------------------------------------------------------------- +try + xM = SPM.xM; +catch + xM = -ones(nScan,1)/0; +end +if ~isstruct(xM) + xM = struct( 'T', [],... + 'TH', xM,... + 'I', 0,... + 'VM', {[]},... + 'xs', struct('Masking','analysis threshold')); +end + +%-Check confounds (xX.K) and non-sphericity (xVi) +%----------------------------------------------------------------------- +if ~isfield(xX,'K') + xX.K = 1; +end +try + %-If covariance components are specified use them + %--------------------------------------------------------------- + xVi = SPM.xVi; +catch + + %-otherwise assume i.i.d. + %--------------------------------------------------------------- + xVi = struct( 'form', 'i.i.d.',... + 'V', speye(nScan,nScan)); +end + + +%-Get non-sphericity V +%======================================================================= +try + %-If xVi.V is specified proceed directly to parameter estimation + %--------------------------------------------------------------- + V = xVi.V; + str = 'parameter estimation'; + + +catch + % otherwise invoke ReML selecting voxels under i.i.d assumptions + %--------------------------------------------------------------- + V = speye(nScan,nScan); + str = '[hyper]parameter estimation'; +end + +%-Get whitening/Weighting matrix: If xX.W exists we will save WLS estimates +%----------------------------------------------------------------------- +try + %-If W is specified, use it + %------------------------------------------------------- + W = xX.W; +catch + if isfield(xVi,'V') + + % otherwise make W a whitening filter W*W' = inv(V) + %------------------------------------------------------- + [u s] = spm_svd(xVi.V); + s = spdiags(1./sqrt(diag(s)),0,nScan,nScan); + W = u*s*u'; + W = W.*(abs(W) > 1e-6); + xX.W = sparse(W); + else + % unless xVi.V has not been estimated - requiring 2 passes + %------------------------------------------------------- + W = speye(nScan,nScan); + str = 'hyperparameter estimation (1st pass)'; + end +end + + +%-Design space and projector matrix [pseudoinverse] for WLS +%======================================================================= +xX.xKXs = spm_sp('Set',spm_filter(xX.K,W*xX.X)); % KWX +xX.pKX = spm_sp('x-',xX.xKXs); % projector + +%-If xVi.V is not defined compute Hsqr and F-threshold under i.i.d. +%----------------------------------------------------------------------- +if ~isfield(xVi,'V') + Fcname = 'effects of interest'; + iX0 = [SPM.xX.iB SPM.xX.iG]; + xCon = spm_FcUtil('Set',Fcname,'F','iX0',iX0,xX.xKXs); + X1o = spm_FcUtil('X1o', xCon(1),xX.xKXs); + Hsqr = spm_FcUtil('Hsqr',xCon(1),xX.xKXs); + trRV = spm_SpUtil('trRV',xX.xKXs); + trMV = spm_SpUtil('trMV',X1o); + UFp = spm('GetGlobal','UFp'); + UF = spm_invFcdf(1 - UFp,[trMV,trRV]); +end + + +%-Image dimensions and data +%======================================================================= +VY = SPM.xY.VY; +M = VY(1).mat; +DIM = VY(1).dim(1:3)'; +xdim = DIM(1); ydim = DIM(2); zdim = DIM(3); + +% KND: 3D / 4D bug... +if numel(VY(1).dim)<4 + %VY(1).dim(end:4) = 1; + YNaNrep = NaN; +else + YNaNrep = spm_type(VY(1).dim(4),'nanrep'); +end + +%-Maximum number of residual images for smoothness estimation +%----------------------------------------------------------------------- +global defaults +MAXRES = defaults.stats.maxres; + +%-maxMem is the maximum amount of data processed at a time (bytes) +%----------------------------------------------------------------------- +MAXMEM = defaults.stats.maxmem; +nSres = min(nScan,MAXRES); +blksz = ceil(MAXMEM/8/nScan); %-block size +nbch = ceil(xdim*ydim/blksz); %-# blocks + + +fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...done') %-# + + +%-Initialise output images (unless this is a 1st pass for ReML) +%======================================================================= +if isfield(xX,'W') +fprintf('%-40s: %30s','Output images','...initialising') %-# + +%-Intialise the name of the new mask : current mask & conditions on voxels +%----------------------------------------------------------------------- +VM = struct( 'fname', 'mask.img',... + 'dim', [DIM',spm_type('uint8')],... + 'mat', M,... + 'pinfo', [1 0 0]',... + 'descrip', 'spm_spm:resultant analysis mask'); +VM = spm_create_vol(VM); + + +%-Intialise beta image files +%----------------------------------------------------------------------- +Vbeta(1:nBeta) = deal(struct(... + 'fname', [],... + 'dim', [DIM',spm_type('float')],... + 'mat', M,... + 'pinfo', [1 0 0]',... + 'descrip', '')); +for i = 1:nBeta + Vbeta(i).fname = sprintf('beta_%04d.img',i); + Vbeta(i).descrip = sprintf('spm_spm:beta (%04d) - %s',i,xX.name{i}); + spm_unlink(Vbeta(i).fname) +end +Vbeta = spm_create_vol(Vbeta,'noopen'); + + +%-Intialise residual sum of squares image file +%----------------------------------------------------------------------- +VResMS = struct( 'fname', 'ResMS.img',... + 'dim', [DIM',spm_type('double')],... + 'mat', M,... + 'pinfo', [1 0 0]',... + 'descrip', 'spm_spm:Residual sum-of-squares'); +VResMS = spm_create_vol(VResMS,'noopen'); + + +%-Intialise residual images +%----------------------------------------------------------------------- +VResI(1:nSres) = deal(struct(... + 'fname', [],... + 'dim', [DIM',spm_type('double')],... + 'mat', M,... + 'pinfo', [1 0 0]',... + 'descrip', 'spm_spm:Residual image')); + +for i = 1:nSres + VResI(i).fname = sprintf('ResI_%04d.img', i); + VResI(i).descrip = sprintf('spm_spm:ResI (%04d)', i); + spm_unlink(VResI(i).fname); +end +VResI = spm_create_vol(VResI); +end % (xX,'W') + +fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...initialised') %-# + + +%======================================================================= +% - F I T M O D E L & W R I T E P A R A M E T E R I M A G E S +%======================================================================= + + +%-Intialise variables used in the loop +%======================================================================= +xords = [1:xdim]'*ones(1,ydim); xords = xords(:)'; % plane X coordinates +yords = ones(xdim,1)*[1:ydim]; yords = yords(:)'; % plane Y coordinates +S = 0; % Volume (voxels) +s = 0; % Volume (voxels > UF) +Cy = 0; % spatially whitened +CY = 0; % for ReML +EY = 0; % for ReML +i_res = round(linspace(1,nScan,nSres))'; % Indices for residual + +%-Initialise XYZ matrix of in-mask voxel co-ordinates (real space) +%----------------------------------------------------------------------- +XYZ = zeros(3,xdim*ydim*zdim); + +%-Cycle over bunches blocks within planes to avoid memory problems +%======================================================================= +spm_progress_bar('Init',100,str,''); + +for z = 1:zdim %-loop over planes (2D or 3D data) + + % current plane-specific parameters + %------------------------------------------------------------------- + zords = z*ones(xdim*ydim,1)'; %-plane Z coordinates + CrBl = []; %-parameter estimates + CrResI = []; %-normalized residuals + CrResSS = []; %-residual sum of squares + Q = []; %-in mask indices for this plane + + for bch = 1:nbch %-loop over blocks + + %-# Print progress information in command window + %--------------------------------------------------------------- + str = sprintf('Plane %3d/%-3d, block %3d/%-3d',z,zdim,bch,nbch); + fprintf('\r%-40s: %30s',str,' ') %-# + + %-construct list of voxels in this block + %--------------------------------------------------------------- + I = [1:blksz] + (bch - 1)*blksz; %-voxel indices + I = I(I <= xdim*ydim); %-truncate + xyz = [xords(I); yords(I); zords(I)]; %-voxel coordinates + nVox = size(xyz,2); %-number of voxels + + %-Get data & construct analysis mask + %=============================================================== + fprintf('%s%30s',sprintf('\b')*ones(1,30),'...read & mask data')%-# + Cm = logical(ones(1,nVox)); %-current mask + + + %-Compute explicit mask + % (note that these may not have same orientations) + %--------------------------------------------------------------- + for i = 1:length(xM.VM) + + %-Coordinates in mask image + %------------------------------------------------------- + j = xM.VM(i).mat\M*[xyz;ones(1,nVox)]; + + %-Load mask image within current mask & update mask + %------------------------------------------------------- + Cm(Cm) = spm_get_data(xM.VM(i),j(:,Cm)) > 0; + end + + %-Get the data in mask, compute threshold & implicit masks + %--------------------------------------------------------------- + Y = zeros(nScan,nVox); + for i = 1:nScan + + %-Load data in mask + %------------------------------------------------------- + if ~any(Cm), break, end %-Break if empty mask + Y(i,Cm) = spm_get_data(VY(i),xyz(:,Cm)); + + Cm(Cm) = Y(i,Cm) > xM.TH(i); %-Threshold (& NaN) mask + if xM.I & ~YNaNrep & xM.TH(i) < 0 %-Use implicit mask + Cm(Cm) = abs(Y(i,Cm)) > eps; + end + end + + %-Mask out voxels where data is constant + %--------------------------------------------------------------- + Cm(Cm) = any(diff(Y(:,Cm),1)); + Y = Y(:,Cm); %-Data within mask + CrS = sum(Cm); %-# current voxels + + + %=============================================================== + %-Proceed with General Linear Model (if there are voxels) + %=============================================================== + if CrS + + %-Whiten/Weight data and remove filter confounds + %------------------------------------------------------- + fprintf('%s%30s',sprintf('\b')*ones(1,30),'filtering') %-# + + KWY = spm_filter(xX.K,W*Y); + + %-General linear model: Weighted least squares estimation + %------------------------------------------------------ + fprintf('%s%30s',sprintf('\b')*ones(1,30),' estimation') %-# + + beta = xX.pKX*KWY; %-Parameter estimates + res = spm_sp('r',xX.xKXs,KWY); %-Residuals + ResSS = sum(res.^2); %-Residual SSQ + clear KWY %-Clear to save memory + + + %-If ReML hyperparameters are needed for xVi.V + %------------------------------------------------------- + if ~isfield(xVi,'V') + + %-F-threshold & accumulate spatially whitened Y*Y' + %----------------------------------------------- + j = sum((Hsqr*beta).^2,1)/trMV > UF*ResSS/trRV; + j = find(j); + if length(j) + q = size(j,2); + s = s + q; + q = spdiags(sqrt(trRV./ResSS(j)'),0,q,q); + Y = Y(:,j)*q; + Cy = Cy + Y*Y'; + end + + end % (xVi,'V') + + + %-if we are saving the WLS parameters + %------------------------------------------------------- + if isfield(xX,'W') + + %-sample covariance and mean of Y (all voxels) + %----------------------------------------------- + CY = CY + Y*Y'; + EY = EY + sum(Y,2); + + %-Save betas etc. for current plane as we go along + %----------------------------------------------- + CrBl = [CrBl, beta]; + CrResI = [CrResI, res(i_res,:)]; + CrResSS = [CrResSS, ResSS]; + + end % (xX,'W') + clear Y %-Clear to save memory + + end % (CrS) + + %-Append new inmask voxel locations and volumes + %--------------------------------------------------------------- + XYZ(:,S + [1:CrS]) = xyz(:,Cm); %-InMask XYZ voxel coords + Q = [Q I(Cm)]; %-InMask XYZ voxel indices + S = S + CrS; %-Volume analysed (voxels) + + end % (bch) + + + %-Plane complete, write plane to image files (unless 1st pass) + %=================================================================== + if isfield(xX,'W') + + fprintf('%s%30s',sprintf('\b')*ones(1,30),'...saving plane') %-# + + %-Write Mask image + %------------------------------------------------------------------- + j = sparse(xdim,ydim); + if length(Q), j(Q) = 1; end + VM = spm_write_plane(VM, j, z); + + %-Write beta images + %------------------------------------------------------------------- + j = NaN*ones(xdim,ydim); + for i = 1:nBeta + if length(Q), j(Q) = CrBl(i,:); end + Vbeta(i) = spm_write_plane(Vbeta(i), j, z); + end + + %-Write residual images + %------------------------------------------------------------------- + for i = 1:nSres + if length(Q), j(Q) = CrResI(i,:); end + VResI(i) = spm_write_plane(VResI(i), j, z); + end + + %-Write ResSS into ResMS (variance) image scaled by tr(RV) above + %------------------------------------------------------------------- + if length(Q), j(Q) = CrResSS; end + VResMS = spm_write_plane(VResMS,j,z); + + end % (xX,'W') + + %-Report progress + %------------------------------------------------------------------- + fprintf('%s%30s',sprintf('\b')*ones(1,30),'...done') %-# + spm_progress_bar('Set',100*(bch + nbch*(z - 1))/(nbch*zdim)); + + +end % (for z = 1:zdim) +fprintf('\n') %-# +spm_progress_bar('Clear') + +%======================================================================= +% - P O S T E S T I M A T I O N C L E A N U P +%======================================================================= +if S == 0, warning('No inmask voxels - empty analysis!'), end + +%-close written image files (unless 1st pass) +%======================================================================= +if isfield(xX,'W') + + fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...closing files') %-# + VM = spm_close_vol(VM); + Vbeta = spm_close_vol(Vbeta); + VResI = spm_close_vol(VResI); + VResMS = spm_close_vol(VResMS); + +end % (xVi,'V') + +%-average sample covariance and mean of Y (over voxels) +%----------------------------------------------------------------------- +CY = CY/S; +EY = EY/S; +CY = CY - EY*EY'; + +%-If not defined, compute non-sphericity V using ReML Hyperparameters +%======================================================================= +if ~isfield(xVi,'V') + + %-REML estimate of residual correlations through hyperparameters (h) + %--------------------------------------------------------------- + str = 'Temporal non-sphericity (over voxels)'; + fprintf('%-40s: %30s\n',str,'...REML estimation') %-# + Cy = Cy/s; + + % ReML for separable designs and covariance components + %--------------------------------------------------------------- + if isstruct(xX.K) + m = length(xVi.Vi); + h = zeros(m,1); + V = sparse(nScan,nScan); + for i = 1:length(xX.K) + + % extract blocks from bases + %----------------------------------------------- + q = xX.K(i).row; + p = []; + Qp = {}; + for j = 1:m + if nnz(xVi.Vi{j}(q,q)) + Qp{end + 1} = xVi.Vi{j}(q,q); + p = [p j]; + end + end + + % design space for ReML (with confounds in filter) + %----------------------------------------------- + Xp = xX.X(q,:); + try + Xp = [Xp xX.K(i).X0]; + end + + % ReML + %----------------------------------------------- + fprintf('%-30s- %i\n',' ReML Block',i); + [Vp,hp] = spm_reml(Cy(q,q),Xp,Qp); + V(q,q) = V(q,q) + Vp; + h(p) = hp; + end + else + [V,h] = spm_reml(Cy,xX.X,xVi.Vi); + end + + % normalize non-sphericity and save hyperparameters + %--------------------------------------------------------------- + V = V*nScan/trace(V); + xVi.h = h; + xVi.V = V; % Save non-sphericity xVi.V + xVi.Cy = Cy; %-spatially whitened + SPM.xVi = xVi; % non-sphericity structure + + % If xX.W is not specified use W*W' = inv(V) to give ML estimators + %--------------------------------------------------------------- + if ~isfield(xX,'W') + save SPM SPM + clear + load SPM + SPM = spm_spm(SPM); + return + end +end + + +%-Use non-sphericity xVi.V to compute [effective] degrees of freedom +%======================================================================= +xX.V = spm_filter(xX.K,spm_filter(xX.K,W*V*W')'); % KWVW'K' +[trRV trRVRV] = spm_SpUtil('trRV',xX.xKXs,xX.V); % trRV (for X) +xX.trRV = trRV; % +xX.trRVRV = trRVRV; %-Satterthwaite +xX.erdf = trRV^2/trRVRV; % approximation +xX.Bcov = xX.pKX*xX.V*xX.pKX'; % Cov(beta) + + +%-Set VResMS scalefactor as 1/trRV (raw voxel data is ResSS) +%----------------------------------------------------------------------- +VResMS.pinfo(1) = 1/xX.trRV; +VResMS = spm_create_vol(VResMS,'noopen'); + + +%-Create 1st contrast for 'effects of interest' (all if not specified) +%======================================================================= +Fcname = 'effects of interest'; +try + iX0 = [xX.iB xX.iG]; +catch + iX0 = []; +end +xCon = spm_FcUtil('Set',Fcname,'F','iX0',iX0,xX.xKXs); + +%-Append contrasts for fMRI - specified by SPM.Sess(s).Fc(i) +%----------------------------------------------------------------------- +if isfield(SPM,'Sess') + for s = 1:length(SPM.Sess) + for i = 1:length(SPM.Sess(s).Fc) + iX0 = 1:nBeta; + iX = SPM.Sess(s).col(SPM.Sess(s).Fc(i).i); + iX0(iX) = []; + Fcname = sprintf('Sess(%d):%s',s,SPM.Sess(s).Fc(i).name); + xCon(end + 1) = spm_FcUtil('Set',Fcname,'F','iX0',iX0,xX.xKXs); + end + end +end + +%-Smoothness estimates of component fields and RESEL counts for volume +%======================================================================= +try + FWHM = SPM.xVol.FWHM; + VRpv = SPM.xVol.VRpv; + R = SPM.xVol.R; +catch + [FWHM,VRpv] = spm_est_smoothness(VResI,VM); + R = spm_resels_vol(VM,FWHM)'; +end + +%-Delete the residuals images +%======================================================================= +for i = 1:nSres, + spm_unlink([spm_str_manip(VResI(i).fname,'r') '.img']); + spm_unlink([spm_str_manip(VResI(i).fname,'r') '.hdr']); + spm_unlink([spm_str_manip(VResI(i).fname,'r') '.mat']); +end + + +%-Compute scaled design matrix for display purposes +%----------------------------------------------------------------------- +xX.nKX = spm_DesMtx('sca',xX.xKXs.X,xX.name); + + +fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...done') %-# + +%-Save remaining results files and analysis parameters +%======================================================================= +fprintf('%-40s: %30s','Saving results','...writing') %-# + +%-place fields in SPM +%----------------------------------------------------------------------- +SPM.xVol.XYZ = XYZ(:,1:S); %-InMask XYZ coords (voxels) +SPM.xVol.M = M; %-voxels -> mm +SPM.xVol.iM = inv(M); %-mm -> voxels +SPM.xVol.DIM = DIM; %-image dimensions +SPM.xVol.FWHM = FWHM; %-Smoothness data +SPM.xVol.R = R; %-Resel counts +SPM.xVol.S = S; %-Volume (voxels) +SPM.xVol.VRpv = VRpv; %-Filehandle - Resels per voxel + + +SPM.Vbeta = Vbeta; %-Filehandle - Beta +SPM.VResMS = VResMS; %-Filehandle - Hyperparameter +SPM.VM = VM; %-Filehandle - Mask + +SPM.xVi = xVi; % non-sphericity structure +SPM.xVi.CY = CY; %-<(Y - )*(Y - )'> + +SPM.xX = xX; %-design structure +SPM.xM = xM; %-mask structure + +SPM.xCon = xCon; %-contrast structure + +SPM.SPMid = SPMid; +SPM.swd = pwd; + + +%-Save analysis parameters in SPM.mat file +%----------------------------------------------------------------------- +save SPM SPM + +%======================================================================= +%- E N D: Cleanup GUI +%======================================================================= +fprintf('%s%30s\n',sprintf('\b')*ones(1,30),'...done') %-# +spm('FigName','Stats: done',Finter); spm('Pointer','Arrow') +fprintf('%-40s: %30s\n','Completed',spm('time')) %-# +fprintf('...use the results section for assessment\n\n') %-# diff --git a/spm/spm2/spm_vol.m b/spm/spm2/spm_vol.m new file mode 100644 index 0000000..e703e7c --- /dev/null +++ b/spm/spm2/spm_vol.m @@ -0,0 +1,152 @@ +function V = spm_vol(P) +% Get header information etc for images. +% FORMAT V = spm_vol(P) +% P - a matrix of filenames. +% V - a vector of structures containing image volume information. +% The elements of the structures are: +% V.fname - the filename of the image. +% V.dim - the x, y and z dimensions of the volume, and the +% datatype of the image. +% V.mat - a 4x4 affine transformation matrix mapping from +% voxel coordinates to real world coordinates. +% V.pinfo - plane info for each plane of the volume. +% V.pinfo(1,:) - scale for each plane +% V.pinfo(2,:) - offset for each plane +% The true voxel intensities of the jth image are given +% by: val*V.pinfo(1,j) + V.pinfo(2,j) +% V.pinfo(3,:) - offset into image (in bytes). +% If the size of pinfo is 3x1, then the volume is assumed +% to be contiguous and each plane has the same scalefactor +% and offset. +%____________________________________________________________________________ +% +% The fields listed above are essential for the mex routines, but other +% fields can also be incorporated into the structure. +% +% The images are not memory mapped at this step, but are mapped when +% the mex routines using the volume information are called. +% +% This is a replacement for the spm_map_vol and spm_unmap_vol stuff of +% MatLab4 SPMs (SPM94-97), which is now obsolete. +%_______________________________________________________________________ +% @(#)spm_vol.m 2.16 John Ashburner 03/05/23 + +% If is already a vol structure then just return; +if isstruct(P), V = P; return; end; + +V = subfunc2(P); +return; + +function V = subfunc2(P) +try + if iscell(P), + V = cell(size(P)); + for j=1:prod(size(P)), + if iscell(P{j}), + V{j} = subfunc2(P{j}); + else, + V{j} = subfunc1(P{j}); + end; + end; + else + V = subfunc1(P); + end; +catch + warning('Possible disk swapping in spm_vol.m'); + if iscell(P) + if P{1}(2)==':' + for i=1:size(P(:),1) + P{i}=P{i}(:,3:end); + end + end + else + if P(1,2)==':' + P=P(:,3:end); + end + end + if iscell(P), + V = cell(size(P)); + for j=1:prod(size(P)), + if iscell(P{j}), + V{j} = subfunc2(P{j}); + else, + V{j} = subfunc1(P{j}); + end; + end; + else + V = subfunc1(P); + end; + +end + +return; + +function V = subfunc1(P) +if size(P,1)==0, + V=[]; +else, + V(size(P,1),1) = struct('fname','', 'dim', [0 0 0 0], 'mat',eye(4), 'pinfo', [1 0 0]'); +end; +for i=1:size(P,1), + v = subfunc(P(i,:)); + if isempty(v), + hread_error_message(P(i,:)); + error(['Can''t get volume information for ''' P(i,:) '''']); + end; + f = fieldnames(v); + for j=1:size(f,1), + eval(['V(i).' f{j} ' = v.' f{j} ';']); + %V(i) = setfield(V(i),f{j},getfield(v,f{j})); + end; +end; +return; + +function V = subfunc(p) +p = deblank(p); +[pth,nam,ext] = fileparts(deblank(p)); +t = find(ext==','); + +n = []; +if ~isempty(t), + if length(t)==1, + n1 = ext((t+1):end); + if ~isempty(n1), + n = str2num(n1); + ext = ext(1:(t-1)); + end; + end; +end; +p = fullfile(pth,[nam ext]); + +if strcmp(ext,'.img') & exist(fullfile(pth,[nam '.hdr'])) == 2, + if isempty(n), V = spm_vol_ana(p); + else, V = spm_vol_ana(p,n); end; + if ~isempty(V), return; end; +else, % Try other formats + + % Try MINC format + if isempty(n), V=spm_vol_minc(p); + else, V=spm_vol_minc(p,n); end; + if ~isempty(V), return; end; + + % Try Ecat 7 + if isempty(n), V=spm_vol_ecat7(p); + else, V=spm_vol_ecat7(p,n); end; + if ~isempty(V), return; end; +end; +return; + + +%_______________________________________________________________________ +function hread_error_message(q) + +str = {... + 'Error reading information on:',... + [' ',spm_str_manip(q,'k40d')],... + ' ',... + 'Please check that it is in the correct format.'}; + +spm('alert*',str,mfilename,sqrt(-1)); + +return; +%_______________________________________________________________________ diff --git a/spm/spm5/spm_2008Oct17.ps b/spm/spm5/spm_2008Oct17.ps new file mode 100644 index 0000000000000000000000000000000000000000..e0b34fef62391183643b36de9c19574dd226f4ed GIT binary patch literal 13404 zcmcgzZExH*68?M!{2zE9479k~dRe_~z9n&UmqUCp;sQlc9}KNTuhnR!t)%tKE%M** znc<75^*V8iHVJmE;S8S{4u``bWgq?h{Nng!*)HVq?8Fy`2S-P*JDCq{_d=Y#{OR4x zS3iiKZlpNNhnu^$``G^=-ZsSv$^BFfwR|D|`QoxEtNcNJyj@JAU#?47QJel(|kbZ!1sdGBN-ur} zD%lbLABH%7)z+ok&MRPQ0q~;v@BWmp97|c<($i zk6HK3lJ~`p?gbh>?t7q0v1JB71CUuqR;kDri%#BFIhjHh6he4KU9AP_Bf0?HHbp+z zmNiMVyf`q{HE*RZA4jD z-5c2+j9%_Ec4+LTm|cygx@sIXz1a3QhzG68xWVfSFyv6I9zGTnMk52m0i#e@6O zi8X>&^aEm6U{(f%Am(Vj>~F<)-_zuSTCmJkwX*xsZV)`o8W6VJMbDSzE!K65DVofg z->ot}og=e|0!ZkcPC|Fub*YJbm3`!vv)&I0!ba``j zA-0}v)~f=`ujHP;T8fjzkzIBJU`I)LMLuvAE9pF>@^Y=|V$R6tJMczyA z8j)Nz9=DbY)rNdnt^2C?%6z$`%&H&2_ll}R4!*ACy@ymZ+_ak>bLCwWdDk}Ha#Pie zUCZmid;g==s;zj+9u{XCx@vhdSaZg9=vJ)7rmp1xASB|vzwzXXe+(7YhlfBamH9&DeOyo&*z$-C0d zH_hQEQC-Wrml!}NB}IZsy5(l=Mg%4APbxTefkq4=R3b;$nFs_{cr9$O5@0QxB@zv7 zHD*5%Vhd4(o4gm^o42P(bYe@EaUjx=w29&qmP?n{$QsD=b`)mo5IXTPHYS6XBvKW} zKBK6R^{T#WSJ-a1)-dn&P2OD~U1OP&TZQ)$SrV!LW7FO>cEMmReh^zbE@Lwd%VHWI zYEL=VlhJG{U@T;TePN4qViQAI-HPMg2E;g1)=Oi!5-_`sa&waR_ zk`tll*lX_rAvuTUshv;oB|)nd9NgOf0KXV@3tQ|{cF8qSDK3pn77%TDl8JUpP? zHo#|w+BioAWV*ulN{Q9|2CKlT+8w3Kn~e1wVf|=wQDh)Hj7q5o`B|9gz~aW{Dz;3c zwlnRNOnIrRk-x#}`U7L88K+UlHX8Ph{LxfCN88_QVq+yb%(S!jE4HEZ*!kFU#oZ2&h-VM^7G+1Z>48fL!MmA~b@!k+SOs-=Z=^Q0ZWi9A zwyo%Dh0i`QJvEI{V+0LX zZJ8=ygUlCUsun6CJX)-RykHP0Nt4M2X`+X^8$l!Bsv0kz{FtXrfd~)WP+Q-=lgH!X9~9`*AFkAKji4Ik7MPpGyd_&&n|Q7 zXNXoPHq{ZCb8orRf}Gom_bJ#F4MRdQ3S#*c4cE2S3`RR6R48fQr{4%h}F@Nh#w-;66+QcBW*q( zs~9oh$CRpBJ|60$t5sCAtMz7(SG;skc;kS?DC8n`=F}49r>eQd;a?j^;_PFdjmP34 zUAW**P>Wm5CEc_^+&xX3!%T^?inTi@ZOcPdPnfvkz-?pQ>wT}o^@)0+e0H{W0^@ z|HGzv$H(o76jg$PQPja-%`?@|$}n|JW2ViRId2?{b9N>VCYgaWBe4R`(x_DA24?d{jlD1fjf}Kn=!gG;fj&@^< zB-C(}rAqtIZ6v(O*Qb1xz}?{|V})~Km@0<<=nSLe^xV3a5p?;E+jw*JPUI`PQooP` zEygo@6n2#N4mAgb%yS(g^8kf0C+bc0*gc~T0pTUF9mQ?h-UZ_xWvO(9OFCn z@jBs=X1;~h3LQ+V=RKc*U(iVy%K7G%taL6o1AQYpy-baRM9d@HUE$t?I*>6wKJz(V ztRz8%?=+2(7%+1gE)MK1kvMuySKLFsz*3=R`<|lkaRK0;`226rLqFb&7Xd^ABl`Hk z6%846{v6cV)PM}HiG0*(MvsdcO+^`qGng@UqN@{PI$E&GE8r+GTrr+2wbtah?Xz zEQ!LaA3yx(%FmAfy{V5cX%v2T_4e$a-0NzAmx0*d0!;2zw`qc_@bdDmyXLPeOkQwO zt(H74WlEBo(TCsKlyJwCEQqyND3g3sugrE#nInOz35ve8DbZ*O$37x-?$1P&p?szP z$4p|Wh&b~TTzQ_IA0C|Jb8JOE+aX2=eS|tZh-i(SzCS#;z{go|v=qgR^uh~qgo6YV z?~qolX2W4Kz+o{a3})_suii4!BtXFa)?6y&^Og69!8Y3M<6Yb+JN5n)$JwTUezCjl_gO z(u78uN8toXTQ$p)afFI6Sj4edicnayEKFUj8Cw-4={P<`Xe1^Kk|q>V6ermPNn7-2Q=7=y$QQ?Kbi01gr%szuLVZaQB!3>8@ zo6X@xJxEM|e~#5w23-*?nhi2dPO#^W4L@m5`J8B6&XsH1dHW346v!w zQ#i-zGzk-NJWFTe{8N&)IoB)ZQw=ez*jLpRbFBgKpfsgPq7*EA&l=LvG7(amO#j;SCU^W-2QOY7$JYmGW@=lie7UMhhqa0~rnzv>Zrm!r9wrg#IkrM9-EUsZ4ET@JwNL;BJBqj`!CKM9a zur88Y!x}6VHriKXsF~)UXDLD<~!&MGXgK3pl&aeVMJIY%~432!^2EN+#f2h?Ud>XrpDUEgh4YLMl&2P ziIWT!pG9+gW`c=LW5R;jl!OU295yY9Q&UvXnZ%h-gEqz%Ifm*#6F6h$GI}N)tHG)eT1xy*uTmzdb#jQv) z93X5#iu;FDq;r%3&K7JWs2(-X$3%?M&)R>Lc&ri;j*l~eMa-w^5eWWN9I^pHI1-k# zw-4LBm&1AtnjIdYJ?`_@+xDlHqame-G(o|n!f;K$RL=2*wL1n;cjvB^8e)k0ploDJO8Loo% zsUSIipC#}oJoHXSoZ@v3x6v=_(}@u8$kYoa)r$Lm{Q~Upfc_AI{sw?J_|qQzntrYR V(&l+Dy6oT0;EtU&y?=9f@PDzHo0b3o literal 0 HcmV?d00001 diff --git a/spm/spm5/spm_config_realign_log.m b/spm/spm5/spm_config_realign_log.m new file mode 100644 index 0000000..d766ec2 --- /dev/null +++ b/spm/spm5/spm_config_realign_log.m @@ -0,0 +1,225 @@ +function logtxt = spm_config_realign_log(prog,val,options) +% spm_config_realign(prog,val) - Generates log for spm_realign +% [logtxt] = spm_config_realign(prog,val) +% logtxt is a cell array of string +% Example +% >> spm_log2html +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-17 Creation +% +% ----------------------------- Script History --------------------------------- + +% TODO : +% [logtxt] = spm_config_realign(job) +% [logtxt] = spm_config_realign(jobs) + +prog_infos=functions(prog) +jobname=sprintf('%s/', prog_infos.parentage{end:-1:1}); +jobname(end)=[]; +logtxt={}; +logtxt{end+1}=['SPM logging for: ' jobname]; +htmlfile = fullfile(fileparts(getfield(spm_vol(val.data{1}{1}),'fname')),'log',['log_' datestr(now,30)],[jobname '.html']); +logtxt{end+1}=['Into: ']; +logtxt{end+1}={'file' htmlfile}; +htmldir = fileparts(htmlfile); +if not(exist(htmldir, 'dir')) + logtxt{end+1}=['Creating new directory: ' ]; + logtxt{end+1}={'folder', htmldir}; + mkdir(htmldir) +end +try + switch jobname + case 'spm_config_realign/estimate' + mfile = which('spm_realign'); + if ~isequal(textread(mfile,'%s',4,'headerlines',82,'delimiter',' '),... + {'%', '$Id:', 'spm_realign.m', '433'}') % The native version at the time + logtxt{end+1}=sprintf('The spm_realign.m (%s) has changed! Default flags may also have changed.', mfile); + warning(logtxt(1)); + end + disp('REALIGNING IS COOL!') + def_flags = struct('quality',1,'fwhm',5,'sep',4,'interp',2,'wrap',[0 0 0],'rtm',0,'PW','','graphics',1,'lkp',1:6); + flags =mergestructs(def_flags,val.eoptions); + if flags.graphics + opts = {fullfile(htmldir,'realign_estimate.png'),'-noui','-painters','-dpng'}; + fg = spm_figure('FindWin','Graphics'); + logtxt{end+1} = {'Plot of the Movement Parameters'}; + print(fg,opts{:}); + logtxt{end+1} = {'picture',opts{1}}; + + else + logtxt{end+1}='Graphics must be generated for logging. Sorry...'; + + % rp_file = [spm_str_manip(prepend(getfield(spm_vol(val.data{1}{1}),'fname'),'rp_'),'s') '.txt']; + % P=textread(rp_file); + % plot_parameters(P) + end + case 'spm_config_realign/reslice'; + % to do + case 'spm_config_realign/estwrite_fun'; + % to do + otherwise + logtxt{end+1}=['Unknown function to log: ' jobname]; +end +catch + logtxt{end+1}=['Error while logging! ' lasterr]; +end +spm_log2html(htmlfile,logtxt) +return + + +% spm_realign +%_______________________________________________________________________ +function PO = prepend(PI,pre) +[pth,nm,xt,vr] = fileparts(deblank(PI)); +PO = fullfile(pth,[pre nm xt vr]); +return; + + +%_______________________________________________________________________ +function plot_parameters(P) +fg=spm_figure('FindWin','Graphics'); +if ~isempty(fg), + P = cat(1,P{:}); + if length(P)<2, return; end; + Params = zeros(numel(P),12); + for i=1:numel(P), + Params(i,:) = spm_imatrix(P(i).mat/P(1).mat); + end + + % display results + % translation and rotation over time series + %------------------------------------------------------------------- + spm_figure('Clear','Graphics'); + ax=axes('Position',[0.1 0.65 0.8 0.2],'Parent',fg,'Visible','off'); + set(get(ax,'Title'),'String','Image realignment','FontSize',16,'FontWeight','Bold','Visible','on'); + x = 0.1; + y = 0.9; + for i = 1:min([numel(P) 12]) + text(x,y,[sprintf('%-4.0f',i) P(i).fname],'FontSize',10,'Interpreter','none','Parent',ax); + y = y - 0.08; + end + if numel(P) > 12 + text(x,y,'................ etc','FontSize',10,'Parent',ax); end + + ax=axes('Position',[0.1 0.35 0.8 0.2],'Parent',fg,'XGrid','on','YGrid','on'); + plot(Params(:,1:3),'Parent',ax) + s = ['x translation';'y translation';'z translation']; + %text([2 2 2], Params(2, 1:3), s, 'Fontsize',10,'Parent',ax) + legend(ax, s, 0) + set(get(ax,'Title'),'String','translation','FontSize',16,'FontWeight','Bold'); + set(get(ax,'Xlabel'),'String','image'); + set(get(ax,'Ylabel'),'String','mm'); + + + ax=axes('Position',[0.1 0.05 0.8 0.2],'Parent',fg,'XGrid','on','YGrid','on'); + plot(Params(:,4:6)*180/pi,'Parent',ax) + s = ['pitch';'roll ';'yaw ']; + %text([2 2 2], Params(2, 4:6)*180/pi, s, 'Fontsize',10,'Parent',ax) + legend(ax, s, 0) + set(get(ax,'Title'),'String','rotation','FontSize',16,'FontWeight','Bold'); + set(get(ax,'Xlabel'),'String','image'); + set(get(ax,'Ylabel'),'String','degrees'); + + % print realigment parameters + spm_print +end +%_______________________________________________________________________ + + + + +%------------------------------------------------------------------------ +function estimate(varargin) +job = varargin{1}; +P = {}; +for i=1:length(job.data), + P{i} = strvcat(job.data{i}); +end; +flags.quality = job.eoptions.quality; +flags.fwhm = job.eoptions.fwhm; +flags.sep = job.eoptions.sep; +flags.rtm = job.eoptions.rtm; +flags.PW = strvcat(job.eoptions.weight); +flags.interp = job.eoptions.interp; +flags.wrap = job.eoptions.wrap; +spm_realign(P,flags); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function reslice(varargin) +job = varargin{1}; +P = strvcat(job.data); +flags.mask = job.roptions.mask; +flags.mean = job.roptions.which(2); +flags.interp = job.roptions.interp; +flags.which = job.roptions.which(1); +flags.wrap = job.roptions.wrap; +spm_reslice(P,flags); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function estwrite_fun(varargin) +job = varargin{1}; +P = {}; +for i=1:length(job.data), + P{i} = strvcat(job.data{i}); +end; +flags.quality = job.eoptions.quality; +flags.fwhm = job.eoptions.fwhm; +flags.sep = job.eoptions.sep; +flags.rtm = job.eoptions.rtm; +flags.PW = strvcat(job.eoptions.weight); +flags.interp = job.eoptions.interp; +flags.wrap = job.eoptions.wrap; +spm_realign(P,flags); + +P = strvcat(P); +flags.mask = job.roptions.mask; +flags.mean = job.roptions.which(2); +flags.interp = job.roptions.interp; +flags.which = job.roptions.which(1); +flags.wrap = job.roptions.wrap; +spm_reslice(P,flags); +return; + +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function vf = vfiles_reslice(job) +P = job.data; +if numel(P)>0 && iscell(P{1}), + P = cat(1,P{:}); +end; + +switch job.roptions.which(1), + case 0, + vf = {}; + case 1, + vf = cell(numel(P)-1,1); + for i=1:length(vf), + [pth,nam,ext,num] = spm_fileparts(P{i+1}); + vf{i} = fullfile(pth,['r', nam, ext, num]); + end; + otherwise, + vf = cell(numel(P),1); + for i=1:length(vf), + [pth,nam,ext,num] = spm_fileparts(P{i}); + vf{i} = fullfile(pth,['r', nam, ext, num]); + end; +end; +if job.roptions.which(2), + [pth,nam,ext,num] = spm_fileparts(P{1}); + vf = {vf{:}, fullfile(pth,['mean', nam, ext, num])}; +end; diff --git a/spm/spm5/spm_dicom_convert.m b/spm/spm5/spm_dicom_convert.m new file mode 100644 index 0000000..2b13239 --- /dev/null +++ b/spm/spm5/spm_dicom_convert.m @@ -0,0 +1,1180 @@ +function spm_dicom_convert(hdr,opts,root_dir,format) + +% Convert DICOM images into something that SPM can use +% FORMAT spm_dicom_convert(hdr,opts,root_dir,format) +% hdr - a cell array of DICOM headers from spm_dicom_headers +% opts - options +% 'all' - all DICOM files (default) +% 'mosaic' - the mosaic images +% 'standard' - standard DICOM files +% 'spect' - SIEMENS Spectroscopy DICOMs (position only) +% This will write out a mask image volume with 1's +% set at the position of spectroscopy voxel(s). +% 'raw' - convert raw FIDs (not implemented) +% root_dir - 'flat' - SPM5 standard, do not produce file tree +% With all other options, files will be sorted into +% directories according to their sequence/protocol names +% 'date_time' - Place files under ./ +% 'patid' - Place files under ./ +% 'patid_date' - Place files under ./ +% 'name' - Place files under ./ +% format - output format +% 'img' Two file (hdr+img) NIfTI format +% 'nii' Single file NIfTI format +% All images will contain a single 3D dataset, 4D images +% will not be created. +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience +% +% John Ashburner & Jesper Andersson +% $Id: spm_dicom_convert.m 917 2007-09-14 09:28:55Z volkmar $ +% +% This version of spm_dicom_convert has been hacked so that it can deal +% with MOSAIC type functional images whose headers have been stripped of +% the CSA header information. CSA refers to private DICOM header fields +% used by SIEMENS, which can go missing when images are archived to a DICOM +% server. The result is that SPM's DICOM import produces volumes that are +% very large, very thin, and contain a collection of seperate slices of +% brain. Now it seems to work for the images I have tested it with, but it +% may not work for yours. In particular, it is important to carefully check +% that your images are correctly oriented (not right-left flipped for +% example). +% +% I have also changed the default setting for the output file format +% from 'img' to 'nii'. +% +% SWR 2008-08-26 +% Sebastian Rieger, LabNIC, University of Geneva + + + +if nargin<2, opts = 'all'; end; +if nargin<3, root_dir='flat';end; +if nargin<4, format='nii';end; % Changed this from 'img' to 'nii'. + % SWR 2008-08-26 + +[images,guff] = select_tomographic_images(hdr); +[spect,images] = select_spectroscopy_images(images); +[mosaic,standard] = select_mosaic_images(images); + +if (strcmp(opts,'all') || strcmp(opts,'mosaic')) && ~isempty(mosaic), + convert_mosaic(mosaic,root_dir,format); +end; +if (strcmp(opts,'all') || strcmp(opts,'standard')) && ~isempty(standard), + convert_standard(standard,root_dir,format); +end; +if (strcmp(opts,'all') || strcmp(opts,'spect')) && ~isempty(spect), + convert_spectroscopy(spect,root_dir,format); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function convert_mosaic(hdr,root_dir,format) +spm_progress_bar('Init',length(hdr),'Writing Mosaic', 'Files written'); + +for i=1:length(hdr), + + % Output filename + %------------------------------------------------------------------- + fname = getfilelocation(hdr{i},root_dir,'f',format); + + % Image dimensions and data + %------------------------------------------------------------------- + nc = hdr{i}.Columns; + nr = hdr{i}.Rows; + + dim = [0 0 0]; + + try + dim(3) = read_NumberOfImagesInMosaic(hdr{i}); + % This will fail if the CSA header information is missing from a + % mosaic type DICOM file, so I have put it in a "try" statement. + % SWR 2008-08-20 + catch + dim(3) = (nc*nr) / ((max(hdr{i}.AcquisitionMatrix))^2); + % This is an attempt to guess the number of images in the mosaic if + % it cannot be read from CSA header information. Instead, the + % overall dimensions of the mosaic in pixels and the size of the + % acquisition matrix ("Columns", "Rows", and "AcquisitionMatrix" + % in the DICOM header) are used. + % SWR 2008-08-20 + end + + np = [nc nr]/ceil(sqrt(dim(3))); + dim(1:2) = np; + if ~all(np==floor(np)), + warning('%s: dimension problem [Num Images=%d, Num Cols=%d, Num Rows=%d].',... + hdr{i}.Filename,dim(3), nc,nr); + continue; + end; + + % Apparently, this is not the right way of doing it. + %np = read_AcquisitionMatrixText(hdr{i}); + %if rem(nc, np(1)) || rem(nr, np(2)), + % warning('%s: %dx%d wont fit into %dx%d.',hdr{i}.Filename,... + % np(1), np(2), nc,nr); + % return; + %end; + %dim = [np read_NumberOfImagesInMosaic(hdr{i})]; + + mosaic = read_image_data(hdr{i}); + volume = zeros(dim); + for j=1:dim(3), + img = mosaic((1:np(1))+np(1)*rem(j-1,nc/np(1)), (np(2):-1:1)+np(2)*floor((j-1)/(nc/np(1)))); + if ~any(img(:)), + volume = volume(:,:,1:(j-1)); + break; + end; + volume(:,:,j) = img; + end; + dim = size(volume); + dt = [spm_type('int16') spm_platform('bigend')]; + + % Orientation information + %------------------------------------------------------------------- + % Axial Analyze voxel co-ordinate system: + % x increases right to left + % y increases posterior to anterior + % z increases inferior to superior + + % DICOM patient co-ordinate system: + % x increases right to left + % y increases anterior to posterior + % z increases inferior to superior + + % T&T co-ordinate system: + % x increases left to right + % y increases posterior to anterior + % z increases inferior to superior + + analyze_to_dicom = [diag([1 -1 1]) [0 (dim(2)-1) 0]'; 0 0 0 1]*[eye(4,3) [-1 -1 -1 1]']; + + vox = [hdr{i}.PixelSpacing hdr{i}.SpacingBetweenSlices]; + pos = hdr{i}.ImagePositionPatient'; + orient = reshape(hdr{i}.ImageOrientationPatient,[3 2]); + orient(:,3) = null(orient'); + if det(orient)<0, orient(:,3) = -orient(:,3); end; + + % The image position vector is not correct. In dicom this vector points to + % the upper left corner of the image. Perhaps it is unlucky that this is + % calculated in the syngo software from the vector pointing to the center of + % the slice (keep in mind: upper left slice) with the enlarged FoV. + dicom_to_patient = [orient*diag(vox) pos ; 0 0 0 1]; + truepos = dicom_to_patient *[(size(mosaic)-dim(1:2))/2 0 1]'; + dicom_to_patient = [orient*diag(vox) truepos(1:3) ; 0 0 0 1]; + patient_to_tal = diag([-1 -1 1 1]); + mat = patient_to_tal*dicom_to_patient*analyze_to_dicom; + + + + % Maybe flip the image depending on SliceNormalVector from 0029,1010 + %------------------------------------------------------------------- + try + SliceNormalVector = read_SliceNormalVector(hdr{i}); + % This will fail if CSA header information is missing from a + % mosaic type DICOM file, so I have put it into a "try" statement. + % SWR 2008-08-20 + if det([reshape(hdr{i}.ImageOrientationPatient,[3 2]) SliceNormalVector(:)])<0; + volume = volume(:,:,end:-1:1); + mat = mat*[eye(3) [0 0 -(dim(3)-1)]'; 0 0 0 1]; + end; + catch + + % Ideally, another way to check orientation (without relying on + % CSA header information) should be implemented here. Until then, + % image orientation must be carefully checked manually! + % SWR 2008-08-20 + + end; + + + % Possibly useful information + %------------------------------------------------------------------- + tim = datevec(hdr{i}.AcquisitionTime/(24*60*60)); + descrip = sprintf('%gT %s %s TR=%gms/TE=%gms/FA=%gdeg %s %d:%d:%.5g Mosaic',... + hdr{i}.MagneticFieldStrength, hdr{i}.MRAcquisitionType,... + deblank(hdr{i}.ScanningSequence),... + hdr{i}.RepetitionTime,hdr{i}.EchoTime,hdr{i}.FlipAngle,... + datestr(hdr{i}.AcquisitionDate),tim(4),tim(5),tim(6)); + + % descrip = [deblank(descrip) ' ' hdr{i}.PatientsName]; + + if ~true, % LEFT-HANDED STORAGE + mat = mat*[-1 0 0 (dim(1)+1); 0 1 0 0; 0 0 1 0; 0 0 0 1]; + volume = flipdim(volume,1); + end; + + %if isfield(hdr{i},'RescaleSlope') && hdr{i}.RescaleSlope ~= 1, + % volume = volume*hdr{i}.RescaleSlope; + %end; + %if isfield(hdr{i},'RescaleIntercept') && hdr{i}.RescaleIntercept ~= 0, + % volume = volume + hdr{i}.RescaleIntercept; + %end; + %V = struct('fname',fname, 'dim',dim, 'dt',dt, 'mat',mat, 'descrip',descrip); + %spm_write_vol(V,volume); + + % Note that data are no longer scaled by the maximum amount. + % This may lead to rounding errors in smoothed data, but it + % will get around other problems. + RescaleSlope = 1; + RescaleIntercept = 0; + if isfield(hdr{i},'RescaleSlope') && hdr{i}.RescaleSlope ~= 1, + RescaleSlope = hdr{i}.RescaleSlope; + end; + if isfield(hdr{i},'RescaleIntercept') && hdr{i}.RescaleIntercept ~= 0, + RescaleIntercept = hdr{i}.RescaleIntercept; + end; + N = nifti; + N.dat = file_array(fname,dim,dt,0,RescaleSlope,RescaleIntercept); + N.mat = mat; + N.mat0 = mat; + N.mat_intent = 'Scanner'; + N.mat0_intent = 'Scanner'; + N.descrip = descrip; + create(N); + + % Write the data unscaled + dat = N.dat; + dat.scl_slope = []; + dat.scl_inter = []; + % write out volume at once - see spm_write_plane.m for performance comments + dat(:,:,:) = volume; + + spm_progress_bar('Set',i); +end; +spm_progress_bar('Clear'); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function convert_standard(hdr,root_dir,format) +hdr = sort_into_volumes(hdr); +for i=1:length(hdr), + write_volume(hdr{i},root_dir,format); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function vol = sort_into_volumes(hdr) + +% +% First of all, sort into volumes based on relevant +% fields in the header. +% + +vol{1}{1} = hdr{1}; +for i=2:length(hdr), + orient = reshape(hdr{i}.ImageOrientationPatient,[3 2]); + xy1 = hdr{i}.ImagePositionPatient*orient; + match = 0; + if isfield(hdr{i},'CSAImageHeaderInfo') && isfield(hdr{i}.CSAImageHeaderInfo,'name') + ice1 = sscanf( ... + strrep(get_numaris4_val(hdr{i}.CSAImageHeaderInfo,'ICE_Dims'), ... + 'X', '-1'), '%i_%i_%i_%i_%i_%i_%i_%i_%i')'; + dimsel = logical([1 1 1 1 1 1 0 0 1]); + else + ice1 = []; + end; + for j=1:length(vol), + orient = reshape(vol{j}{1}.ImageOrientationPatient,[3 2]); + xy2 = vol{j}{1}.ImagePositionPatient*orient; + dist2 = sum((xy1-xy2).^2); + + % This line is a fudge because of some problematic data that Bogdan, + % Cynthia and Stefan were trying to convert. I hope it won't cause + % problems for others -JA + dist2 = 0; + + if strcmp(hdr{i}.Modality,'CT') && ... + strcmp(vol{j}{1}.Modality,'CT') % Our CT seems to have shears in slice positions + dist2 = 0; + end; + if ~isempty(ice1) && isfield(vol{j}{1},'CSAImageHeaderInfo') && isfield(vol{j}{1}.CSAImageHeaderInfo(1),'name') + % Replace 'X' in ICE_Dims by '-1' + ice2 = sscanf( ... + strrep(get_numaris4_val(vol{j}{1}.CSAImageHeaderInfo,'ICE_Dims'), ... + 'X', '-1'), '%i_%i_%i_%i_%i_%i_%i_%i_%i')'; + if ~isempty(ice2) + identical_ice_dims=all(ice1(dimsel)==ice2(dimsel)); + else + identical_ice_dims = 0; % have ice1 but not ice2, -> + % something must be different + end, + else + identical_ice_dims = 1; % No way of knowing if there is no CSAImageHeaderInfo + end; + try + match = hdr{i}.SeriesNumber == vol{j}{1}.SeriesNumber &&... + hdr{i}.Rows == vol{j}{1}.Rows &&... + hdr{i}.Columns == vol{j}{1}.Columns &&... + sum((hdr{i}.ImageOrientationPatient - vol{j}{1}.ImageOrientationPatient).^2)<1e-5 &&... + sum((hdr{i}.PixelSpacing - vol{j}{1}.PixelSpacing).^2)<1e-5 && ... + identical_ice_dims && dist2<1e-3; + %if (hdr{i}.AcquisitionNumber ~= hdr{i}.InstanceNumber) || ... + % (vol{j}{1}.AcquisitionNumber ~= vol{j}{1}.InstanceNumber) + % match = match && (hdr{i}.AcquisitionNumber == vol{j}{1}.AcquisitionNumber) + %end; + % For raw image data, tell apart real/complex or phase/magnitude + if isfield(hdr{i},'ImageType') && isfield(vol{j}{1}, 'ImageType') + match = match && strcmp(hdr{i}.ImageType, vol{j}{1}.ImageType); + end; + if isfield(hdr{i},'SequenceName') && isfield(vol{j}{1}, 'SequenceName') + match = match && strcmp(hdr{i}.SequenceName,vol{j}{1}.SequenceName); + end; + if isfield(hdr{i},'SeriesInstanceUID') && isfield(vol{j}{1}, 'SeriesInstanceUID') + match = match && strcmp(hdr{i}.SeriesInstanceUID,vol{j}{1}.SeriesInstanceUID); + end; + if isfield(hdr{i},'EchoNumbers') && isfield(vol{j}{1}, 'EchoNumbers') + match = match && hdr{i}.EchoNumbers == vol{j}{1}.EchoNumbers; + end; + catch + match = 0; + end + if match + vol{j}{end+1} = hdr{i}; + break; + end; + end; + if ~match, + vol{end+1}{1} = hdr{i}; + end; +end; + +dcm = vol; +save('dicom_headers.mat','dcm'); + +% +% Secondly, sort volumes into ascending/descending +% slices depending on .ImageOrientationPatient field. +% + +vol2 = {}; +for j=1:length(vol), + orient = reshape(vol{j}{1}.ImageOrientationPatient,[3 2]); + proj = null(orient'); + if det([orient proj])<0, proj = -proj; end; + + z = zeros(length(vol{j}),1); + for i=1:length(vol{j}), + z(i) = vol{j}{i}.ImagePositionPatient*proj; + end; + [z,index] = sort(z); + vol{j} = vol{j}(index); + if length(vol{j})>1, + % dist = diff(z); + if any(diff(z)==0) + tmp = sort_into_vols_again(vol{j}); + vol{j} = tmp{1}; + vol2 = {vol2{:} tmp{2:end}}; + end; + end; +end; +vol = {vol{:} vol2{:}}; +for j=1:length(vol), + if length(vol{j})>1, + orient = reshape(vol{j}{1}.ImageOrientationPatient,[3 2]); + proj = null(orient'); + if det([orient proj])<0, proj = -proj; end; + z = zeros(length(vol{j}),1); + for i=1:length(vol{j}), + z(i) = vol{j}{i}.ImagePositionPatient*proj; + end; + [z,index] = sort(z); + dist = diff(z); + if sum((dist-mean(dist)).^2)/length(dist)>1e-4, + fprintf('***************************************************\n'); + fprintf('* VARIABLE SLICE SPACING *\n'); + fprintf('* This may be due to missing DICOM files. *\n'); + if checkfields(vol{j}{1},'PatientID','SeriesNumber','AcquisitionNumber','InstanceNumber'), + fprintf('* %s / %d / %d / %d \n',... + deblank(vol{j}{1}.PatientID), vol{j}{1}.SeriesNumber, ... + vol{j}{1}.AcquisitionNumber, vol{j}{1}.InstanceNumber); + fprintf('* *\n'); + end; + fprintf('* %20.4g *\n', dist); + fprintf('***************************************************\n'); + end; + end; +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function vol2 = sort_into_vols_again(volj) +if ~isfield(volj{1},'InstanceNumber'), + fprintf('***************************************************\n'); + fprintf('* The slices may be all mixed up and the data *\n'); + fprintf('* not really usable. Talk to your physicists *\n'); + fprintf('* about this. *\n'); + fprintf('***************************************************\n'); + vol2 = {volj}; + return; +end; + +fprintf('***************************************************\n'); +fprintf('* The AcquisitionNumber counter does not appear *\n'); +fprintf('* to be changing from one volume to another. *\n'); +fprintf('* Another possible explanation is that the same *\n'); +fprintf('* DICOM slices are used multiple times. *\n'); +%fprintf('* Talk to your MR sequence developers or scanner *\n'); +%fprintf('* supplier to have this fixed. *\n'); +fprintf('* The conversion is having to guess how slices *\n'); +fprintf('* should be arranged into volumes. *\n'); +if checkfields(volj{1},'PatientID','SeriesNumber','AcquisitionNumber'), + fprintf('* %s / %d / %d\n',... + deblank(volj{1}.PatientID), volj{1}.SeriesNumber, ... + volj{1}.AcquisitionNumber); +end; +fprintf('***************************************************\n'); + +z = zeros(length(volj),1); +t = zeros(length(volj),1); +d = zeros(length(volj),1); +orient = reshape(volj{1}.ImageOrientationPatient,[3 2]); +proj = null(orient'); +if det([orient proj])<0, proj = -proj; end; + +for i=1:length(volj), + z(i) = volj{i}.ImagePositionPatient*proj; + t(i) = volj{i}.InstanceNumber; +end; +% msg = 0; +[t,index] = sort(t); +volj = volj(index); +z = z(index); +msk = find(diff(t)==0); +if any(msk), + % fprintf('***************************************************\n'); + % fprintf('* These files have the same InstanceNumber: *\n'); + % for i=1:length(msk), + % [tmp,nam1,ext1] = fileparts(volj{msk(i)}.Filename); + % [tmp,nam2,ext2] = fileparts(volj{msk(i)+1}.Filename); + % fprintf('* %s%s = %s%s (%d)\n', nam1,ext1,nam2,ext2, volj{msk(i)}.InstanceNumber); + % end; + % fprintf('***************************************************\n'); + index = [true ; diff(t)~=0]; + t = t(index); + z = z(index); + d = d(index); + volj = volj(index); +end; + +%if any(diff(sort(t))~=1), msg = 1; end; +[z,index] = sort(z); +volj = volj(index); +t = t(index); +vol2 = {}; +while ~all(d), + i = find(~d); + i = i(1); + i = find(z==z(i)); + [t(i),si] = sort(t(i)); + volj(i) = volj(i(si)); + for i1=1:length(i), + if length(vol2)1, + z = zeros(length(hdr),1); + for i=1:length(hdr), + z(i) = hdr{i}.ImagePositionPatient*orient(:,3); + end; + z = mean(diff(z)); +else + if checkfields(hdr{1},'SliceThickness'), + z = hdr{1}.SliceThickness; + else + z = 1; + end; +end; +vox = [hdr{1}.PixelSpacing z]; +pos = hdr{1}.ImagePositionPatient'; +dicom_to_patient = [orient*diag(vox) pos ; 0 0 0 1]; +patient_to_tal = diag([-1 -1 1 1]); +mat = patient_to_tal*dicom_to_patient*analyze_to_dicom; +if strcmp(hdr{1}.Modality,'CT') && numel(hdr)>1 + shear = (hdr{1}.ImagePositionPatient-hdr{2}.ImagePositionPatient) ... + * reshape(hdr{1}.ImageOrientationPatient,[3 2]); + if shear(1) + warning('shear(1) = %f not applied\n', shear(1)); + end; + warning('shear(2) = %f applied\n', shear(2)); + try + prms = spm_imatrix(mat); + prms(12) = shear(2); + mat = spm_matrix(prms); + end; +end; + +% Possibly useful information +%------------------------------------------------------------------- +if checkfields(hdr{1},'AcquisitionTime','MagneticFieldStrength','MRAcquisitionType',... + 'ScanningSequence','RepetitionTime','EchoTime','FlipAngle',... + 'AcquisitionDate'), + tim = datevec(hdr{1}.AcquisitionTime/(24*60*60)); + descrip = sprintf('%gT %s %s TR=%gms/TE=%gms/FA=%gdeg %s %d:%d:%.5g',... + hdr{1}.MagneticFieldStrength, hdr{1}.MRAcquisitionType,... + deblank(hdr{1}.ScanningSequence),... + hdr{1}.RepetitionTime,hdr{1}.EchoTime,hdr{1}.FlipAngle,... + datestr(hdr{1}.AcquisitionDate),tim(4),tim(5),tim(6)); +else + descrip = hdr{1}.Modality; +end; + +if ~true, % LEFT-HANDED STORAGE + mat = mat*[-1 0 0 (dim(1)+1); 0 1 0 0; 0 0 1 0; 0 0 0 1]; +end; + +pinfo = [1 0 0]'; +if isfield(hdr{1},'RescaleSlope') || isfield(hdr{1},'RescaleIntercept'), + pinfo = repmat(pinfo,1,length(hdr)); + bytepix = spm_type('int16','bits')/8; + for i=1:length(hdr), + if isfield(hdr{i},'RescaleSlope'), pinfo(1,i) = hdr{i}.RescaleSlope; end; + if isfield(hdr{i},'RescaleIntercept'), pinfo(2,i) = hdr{i}.RescaleIntercept; end; + pinfo(3,i) = dim(1)*dim(2)*(i-1)*bytepix; + end; +end; + +% Write the image volume +%------------------------------------------------------------------- +spm_progress_bar('Init',length(hdr),['Writing ' fname], 'Planes written'); +%V = struct('fname',fname, 'dim',dim, 'dt',dt, 'pinfo',pinfo, 'mat',mat, 'descrip',descrip); +%V = spm_create_vol(V); +N = nifti; +N.dat = file_array(fname,dim,dt,0,pinfo(1),pinfo(2)); +N.mat = mat; +N.mat0 = mat; +N.mat_intent = 'Scanner'; +N.mat0_intent = 'Scanner'; +N.descrip = descrip; +create(N); +volume = zeros(dim); + +for i=1:length(hdr), + plane = read_image_data(hdr{i}); + + if isfield(hdr{i},'RescaleSlope'), plane = plane*hdr{i}.RescaleSlope; end; + if isfield(hdr{i},'RescaleIntercept'), plane = plane+hdr{i}.RescaleIntercept; end; + + plane = fliplr(plane); + if ~true, plane = flipud(plane); end; % LEFT-HANDED STORAGE + %V = spm_write_plane(V,plane,i); + % collect all planes before writing to disk + volume(:,:,i) = plane; + spm_progress_bar('Set',i); +end; +% write volume at once - see spm_write_plane for performance comments +N.dat(:,:,:) = volume; +spm_progress_bar('Clear'); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function convert_spectroscopy(hdr,root_dir,format) + +for i=1:length(hdr), + write_spectroscopy_volume(hdr(i),root_dir,format); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function write_spectroscopy_volume(hdr,root_dir,format) +% Output filename +%------------------------------------------------------------------- +fname = getfilelocation(hdr{1}, root_dir,'S',format); + +% Image dimensions +%------------------------------------------------------------------- +nc = get_numaris4_numval(hdr{1}.Private_0029_1210,'Columns'); +nr = get_numaris4_numval(hdr{1}.Private_0029_1210,'Rows'); + +dim = [nc nr numel(hdr)]; +dt = [spm_type('int16') spm_platform('bigend')]; + +% Orientation information +%------------------------------------------------------------------- +% Axial Analyze voxel co-ordinate system: +% x increases right to left +% y increases posterior to anterior +% z increases inferior to superior + +% DICOM patient co-ordinate system: +% x increases right to left +% y increases anterior to posterior +% z increases inferior to superior + +% T&T co-ordinate system: +% x increases left to right +% y increases posterior to anterior +% z increases inferior to superior + +analyze_to_dicom = [diag([1 -1 1]) [0 (dim(2)-1) 0]'; 0 0 0 1]*[eye(4,3) [-1 -1 -1 1]']; +orient = reshape(get_numaris4_numval(hdr{1}.Private_0029_1210,... + 'ImageOrientationPatient'),[3 2]); +orient(:,3) = null(orient'); +if det(orient)<0, orient(:,3) = -orient(:,3); end; +if length(hdr)>1, + z = zeros(length(hdr),1); + for i=1:length(hdr), + z(i) = get_numaris4_numval(hdr{i}.Private_0029_1210,... + 'ImagePositionPatient')*orient(:,3); + end; + z = mean(diff(z)); +else + try + z = get_numaris4_numval(hdr{1}.Private_0029_1210,... + 'SliceThickness'); + catch + z = 1; + end; +end; + +vox = [get_numaris4_numval(hdr{1}.Private_0029_1210,'PixelSpacing') z]; +pos = get_numaris4_numval(hdr{1}.Private_0029_1210,'ImagePositionPatient')'; +%dicom_to_patient = [orient*diag(vox) pos-1.5*orient*([0 vox(2) 0]') ; 0 0 0 1]; +dicom_to_patient = [orient*diag(vox) pos ; 0 0 0 1]; +patient_to_tal = diag([-1 -1 1 1]); +warning('Don''t know exactly what positions in spectroscopy files should be - just guessing!') +mat = patient_to_tal*dicom_to_patient*analyze_to_dicom; +if strcmp(hdr{1}.Modality,'CT') && numel(hdr)>1 + shear = (hdr{1}.ImagePositionPatient-hdr{2}.ImagePositionPatient) ... + * reshape(hdr{1}.ImageOrientationPatient,[3 2]); + if shear(1) + warning('shear(1) = %f not applied\n', shear(1)); + end; + warning('shear(2) = %f applied\n', shear(2)); + try + prms = spm_imatrix(mat); + prms(12) = shear(2); + mat = spm_matrix(prms); + end; +end; + +% Possibly useful information +%------------------------------------------------------------------- +if checkfields(hdr{1},'AcquisitionTime','MagneticFieldStrength','MRAcquisitionType',... + 'ScanningSequence','RepetitionTime','EchoTime','FlipAngle',... + 'AcquisitionDate'), + tim = datevec(hdr{1}.AcquisitionTime/(24*60*60)); + descrip = sprintf('%gT %s %s TR=%gms/TE=%gms/FA=%gdeg %s %d:%d:%.5g',... + hdr{1}.MagneticFieldStrength, hdr{1}.MRAcquisitionType,... + deblank(hdr{1}.ScanningSequence),... + hdr{1}.RepetitionTime,hdr{1}.EchoTime,hdr{1}.FlipAngle,... + datestr(hdr{1}.AcquisitionDate),tim(4),tim(5),tim(6)); +else + descrip = hdr{1}.Modality; +end; + +if ~true, % LEFT-HANDED STORAGE + mat = mat*[-1 0 0 (dim(1)+1); 0 1 0 0; 0 0 1 0; 0 0 0 1]; +end; + +pinfo = [1 0 0]'; +if isfield(hdr{1},'RescaleSlope') || isfield(hdr{1},'RescaleIntercept'), + pinfo = repmat(pinfo,1,length(hdr)); + bytepix = spm_type('int16','bits')/8; + for i=1:length(hdr), + if isfield(hdr{i},'RescaleSlope'), pinfo(1,i) = hdr{i}.RescaleSlope; end; + if isfield(hdr{i},'RescaleIntercept'), pinfo(2,i) = hdr{i}.RescaleIntercept; end; + pinfo(3,i) = dim(1)*dim(2)*(i-1)*bytepix; + end; +end; + +% Write the image volume +%------------------------------------------------------------------- +spm_progress_bar('Init',length(hdr),['Writing ' fname], 'Planes written'); +%V = struct('fname',fname, 'dim',dim, 'dt',dt, 'pinfo',pinfo, 'mat',mat, 'descrip',descrip); +%V = spm_create_vol(V); +N = nifti; +N.dat = file_array(fname,dim,dt,0,pinfo(1),pinfo(2)); +N.mat = mat; +N.mat0 = mat; +N.mat_intent = 'Scanner'; +N.mat0_intent = 'Scanner'; +N.descrip = descrip; +create(N); +volume = zeros(dim); + +for i=1:length(hdr), + plane = read_spect_data(hdr{i}); + + if isfield(hdr{i},'RescaleSlope'), plane = plane*hdr{i}.RescaleSlope; end; + if isfield(hdr{i},'RescaleIntercept'), plane = plane+hdr{i}.RescaleIntercept; end; + + plane = fliplr(plane); + if ~true, plane = flipud(plane); end; % LEFT-HANDED STORAGE + %V = spm_write_plane(V,plane,i); + % collect all planes before writing to disk + volume(:,:,i) = plane; + spm_progress_bar('Set',i); +end; +% write volume at once - see spm_write_plane for performance comments +N.dat(:,:,:) = volume; +spm_progress_bar('Clear'); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function [images,guff] = select_tomographic_images(hdr) +images = {}; +guff = {}; +for i=1:length(hdr), + if ~checkfields(hdr{i},'Modality') || ~(strcmp(hdr{i}.Modality,'MR') ||... + strcmp(hdr{i}.Modality,'PT') || strcmp(hdr{i}.Modality,'CT')) + disp(['Cant find appropriate modality information for "' hdr{i}.Filename '".']); + guff = {guff{:},hdr{i}}; + elseif ~checkfields(hdr{i},'StartOfPixelData','SamplesperPixel',... + 'Rows','Columns','BitsAllocated','BitsStored','HighBit','PixelRepresentation'), + disp(['Cant find "Image Pixel" information for "' hdr{i}.Filename '".']); + guff = {guff{:},hdr{i}}; + elseif isfield(hdr{i},'Private_2001_105f'), + % This field corresponds to: > Stack Sequence 2001,105F SQ VNAP, COPY + % http://www.medical.philips.com/main/company/connectivity/mri/index.html + % No documentation about this private field is yet available. + disp('Cant yet convert Phillips Intera DICOM.'); + guff = {guff{:},hdr{i}}; + elseif ~(checkfields(hdr{i},'PixelSpacing','ImagePositionPatient','ImageOrientationPatient')||isfield(hdr{i},'Private_0029_1210')), + disp(['Cant find "Image Plane" information for "' hdr{i}.Filename '".']); + guff = {guff{:},hdr{i}}; + elseif ~checkfields(hdr{i},'PatientID','SeriesNumber','AcquisitionNumber','InstanceNumber'), + disp(['Cant find suitable filename info for "' hdr{i}.Filename '".']); + if ~isfield(hdr{i},'SeriesNumber') + disp('Setting SeriesNumber to 1'); + hdr{i}.SeriesNumber=1; + images = {images{:},hdr{i}}; + end; + if ~isfield(hdr{i},'AcquisitionNumber') + disp('Setting AcquisitionNumber to 1'); + hdr{i}.AcquisitionNumber=1; + images = {images{:},hdr{i}}; + end; + if ~isfield(hdr{i},'InstanceNumber') + disp('Setting InstanceNumber to 1'); + hdr{i}.InstanceNumber=1; + images = {images{:},hdr{i}}; + end; + else + images = {images{:},hdr{i}}; + end; +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ + +function [mosaic,standard] = select_mosaic_images(hdr) +% This is the patched version of SPM's select_mosaic_images function. The +% original (see below) fails to recognise mosaic type DICOM files if the +% CSA image header info is missing. SWR 2008-08-26 +mosaic = {}; +standard = {}; +for i=1:length(hdr), + if (~checkfields(hdr{i},'ImageType','CSAImageHeaderInfo') ||... + isfield(hdr{i}.CSAImageHeaderInfo,'junk') ||... + isempty(read_AcquisitionMatrixText(hdr{i})) ||... + isempty(read_NumberOfImagesInMosaic(hdr{i}))) ... + && (isempty(strfind(hdr{i}.ImageType, 'MOSAIC'))) + % SWR: This last line identifies (at least some) mosaics even + % when there is no CSA image header present. SWR + + standard = {standard{:},hdr{i}}; + + else + mosaic = {mosaic{:},hdr{i}}; + end; +end; +return; +%_______________________________________________________________________ + +%{ +This is the original version of SPM's select_mosaic_images function: +%_______________________________________________________________________ +function [mosaic,standard] = (hdr) +mosaic = {}; +standard = {}; +for i=1:length(hdr), + if ~checkfields(hdr{i},'ImageType','CSAImageHeaderInfo') ||... + isfield(hdr{i}.CSAImageHeaderInfo,'junk') ||... + isempty(read_AcquisitionMatrixText(hdr{i})) ||... + isempty(read_NumberOfImagesInMosaic(hdr{i})) + standard = {standard{:},hdr{i}}; + else + mosaic = {mosaic{:},hdr{i}}; + end; +end; +return; +%_______________________________________________________________________ +%} + +%_______________________________________________________________________ +function [spect,images] = select_spectroscopy_images(hdr) +spectsel = zeros(1,numel(hdr)); +for i=1:length(hdr), + if isfield(hdr{i},'SOPClassUID') && isfield(hdr{i},'Private_0029_1210') + spectsel(i) = strcmp(hdr{i}.SOPClassUID,'1.3.12.2.1107.5.9.1'); + end; +end; +spect = hdr(logical(spectsel)); +images= hdr(~logical(spectsel)); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function ok = checkfields(hdr,varargin) +ok = 1; +for i=1:(nargin-1), + if ~isfield(hdr,varargin{i}), + ok = 0; + break; + end; +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function clean = strip_unwanted(dirty) +msk = find((dirty>='a'&dirty<='z') | (dirty>='A'&dirty<='Z') |... + (dirty>='0'&dirty<='9') | dirty=='_'); +clean = dirty(msk); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function img = read_image_data(hdr) +img = []; + +if hdr.SamplesperPixel ~= 1, + warning([hdr.Filename ': SamplesperPixel = ' num2str(hdr.SamplesperPixel) ' - cant be an MRI']); + return; +end; + +prec = ['ubit' num2str(hdr.BitsAllocated) '=>' 'uint32']; + +if isfield(hdr,'TransferSyntaxUID') && strcmp(hdr.TransferSyntaxUID,'1.2.840.10008.1.2.2') && strcmp(hdr.VROfPixelData,'OW'), + fp = fopen(hdr.Filename,'r','ieee-be'); +else + fp = fopen(hdr.Filename,'r','ieee-le'); +end; +if fp==-1, + warning([hdr.Filename ': cant open file']); + return; +end; + +fseek(fp,hdr.StartOfPixelData,'bof'); +img = fread(fp,hdr.Rows*hdr.Columns,prec); +fclose(fp); +if length(img)~=hdr.Rows*hdr.Columns, + error([hdr.Filename ': cant read whole image']); +end; + +img = bitshift(img,hdr.BitsStored-hdr.HighBit-1); + +if hdr.PixelRepresentation, + % Signed data - done this way because bitshift only + % works with signed data. Negative values are stored + % as 2s complement. + neg = logical(bitshift(bitand(img,uint32(2^hdr.HighBit)),-hdr.HighBit)); + msk = (2^hdr.HighBit - 1); + img = double(bitand(img,msk)); + img(neg) = img(neg)-2^(hdr.HighBit); +else + % Unsigned data + msk = (2^(hdr.HighBit+1) - 1); + img = double(bitand(img,msk)); +end; + +img = reshape(img,hdr.Columns,hdr.Rows); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function img = read_spect_data(hdr) +% Image dimensions +%------------------------------------------------------------------- +nc = get_numaris4_numval(hdr.Private_0029_1210,'Columns'); +nr = get_numaris4_numval(hdr.Private_0029_1210,'Rows'); +img = ones(nr,nc); +%_______________________________________________________________________ + +%_______________________________________________________________________ +function nrm = read_SliceNormalVector(hdr) +str = hdr.CSAImageHeaderInfo; +val = get_numaris4_val(str,'SliceNormalVector'); +for i=1:3, + nrm(i,1) = sscanf(val(i,:),'%g'); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function n = read_NumberOfImagesInMosaic(hdr) +str = hdr.CSAImageHeaderInfo; +val = get_numaris4_val(str,'NumberOfImagesInMosaic'); +n = sscanf(val','%d'); +if isempty(n), n=[]; end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function dim = read_AcquisitionMatrixText(hdr) +str = hdr.CSAImageHeaderInfo; +val = get_numaris4_val(str,'AcquisitionMatrixText'); +dim = sscanf(val','%d*%d')'; +if length(dim)==1, + dim = sscanf(val','%dp*%d')'; +end; +if isempty(dim), dim=[]; end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function val = get_numaris4_val(str,name) +name = deblank(name); +val = {}; +for i=1:length(str), + if strcmp(deblank(str(i).name),name), + for j=1:str(i).nitems, + if str(i).item(j).xx(1), + val = {val{:} str(i).item(j).val}; + end; + end; + break; + end; +end; +val = strvcat(val{:}); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function val = get_numaris4_numval(str,name) +val1 = get_numaris4_val(str,name); +for k = 1:size(val1,1) + val(k)=str2num(val1(k,:)); +end; +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ + +function fname = getfilelocation(hdr,root_dir,prefix,format) + +if nargin < 3 + prefix = 'f'; +end; + +if strncmp(root_dir,'ice',3) + root_dir = root_dir(4:end); + imtype = textscan(hdr.ImageType,'%s','delimiter','\\'); + try + imtype = imtype{1}{3}; + catch + imtype = ''; + end; + prefix = [prefix imtype get_numaris4_val(hdr.CSAImageHeaderInfo,'ICE_Dims')]; +end; + +if strcmp(root_dir, 'flat') + % Standard SPM5 file conversion + %------------------------------------------------------------------- + if checkfields(hdr,'SeriesNumber','AcquisitionNumber') + if checkfields(hdr,'EchoNumbers') + fname = sprintf('%s%s-%.4d-%.5d-%.6d-%.2d.%s', prefix, strip_unwanted(hdr.PatientID),... + hdr.SeriesNumber, hdr.AcquisitionNumber, hdr.InstanceNumber,... + hdr.EchoNumbers, format); + else + fname = sprintf('%s%s-%.4d-%.5d-%.6d.%s', prefix, strip_unwanted(hdr.PatientID),... + hdr.SeriesNumber, hdr.AcquisitionNumber, ... + hdr.InstanceNumber, format); + end; + else + fname = sprintf('%s%s-%.6d.%s',prefix, ... + strip_unwanted(hdr.PatientID),hdr.InstanceNumber, format); + end; + + fname = fullfile(pwd,fname); + return; +end; + +% more fancy stuff - sort images into subdirectories +if ~isfield(hdr,'ProtocolName') + if isfield(hdr,'SequenceName') + hdr.ProtocolName = hdr.SequenceName; + else + hdr.ProtocolName='unknown'; + end; +end; +if ~isfield(hdr,'SeriesDescription') + hdr.SeriesDescription = 'unknown'; +end; +if ~isfield(hdr,'EchoNumbers') + hdr.EchoNumbers = 0; +end; + +m = sprintf('%02d', floor(rem(hdr.StudyTime/60,60))); +h = sprintf('%02d', floor(hdr.StudyTime/3600)); +studydate = sprintf('%s_%s-%s', datestr(hdr.StudyDate,'yyyy-mm-dd'), ... + h,m); +switch root_dir + case 'date_time', + id = studydate; + case {'patid', 'patid_date', 'patname'}, + id = strip_unwanted(hdr.PatientID); +end; +serdes = strrep(strip_unwanted(hdr.SeriesDescription),... + strip_unwanted(hdr.ProtocolName),''); +protname = sprintf('%s%s_%.4d',strip_unwanted(hdr.ProtocolName), ... + serdes, hdr.SeriesNumber); +switch root_dir + case 'date_time', + dname = fullfile(pwd, id, protname); + case 'patid', + dname = fullfile(pwd, id, protname); + case 'patid_date', + dname = fullfile(pwd, id, studydate, protname); + case 'patname', + dname = fullfile(pwd, strip_unwanted(hdr.PatientsName), ... + id, protname); + otherwise + error('unknown file root specification'); +end; +if ~exist(dname,'dir'), + mkdir_rec(dname); +end; + +% some non-product sequences on SIEMENS scanners seem to have problems +% with image numbering in MOSAICs - doublettes, unreliable ordering +% etc. To distinguish, always include Acquisition time in image name +sa = sprintf('%02d', floor(rem(hdr.AcquisitionTime,60))); +ma = sprintf('%02d', floor(rem(hdr.AcquisitionTime/60,60))); +ha = sprintf('%02d', floor(hdr.AcquisitionTime/3600)); +fname = sprintf('%s%s-%s%s%s-%.5d-%.5d-%d.%s', prefix, id, ha, ma, sa, ... + hdr.AcquisitionNumber,hdr.InstanceNumber, ... + hdr.EchoNumbers,format); + +fname = fullfile(dname, fname); + +%_______________________________________________________________________ + +%_______________________________________________________________________ + +function suc = mkdir_rec(str) +% works on full pathnames only +opwd=pwd; +if str(end) ~= filesep, str = [str filesep];end; +pos = findstr(str,filesep); +suc = zeros(1,length(pos)); +for g=2:length(pos) + if ~exist(str(1:pos(g)-1),'dir'), + cd(str(1:pos(g-1)-1)); + suc(g) = mkdir(str(pos(g-1)+1:pos(g)-1)); + end; +end; +cd(opwd); +return; +%_______________________________________________________________________ + +%_______________________________________________________________________ +function ret = read_ascconv(hdr) +% In SIEMENS data, there is an ASCII text section with +% additional information items. This section starts with a code +% ### ASCCONV BEGIN ### +% and ends with +% ### ASCCONV END ### +% It is read by spm_dicom_headers into an entry 'MrProtocol' in CSASeriesHeaderInfo +% The additional items are assignments in C syntax, here they are just +% translated according to +% [] -> () +% " -> ' +% 0xX -> hex2dec('X') +% and collected in a struct. +ret=struct; + +% get ascconv data +X=get_numaris4_val(hdr.CSASeriesHeaderInfo,'MrProtocol'); + +ascstart = findstr(X,'### ASCCONV BEGIN ###'); +ascend = findstr(X,'### ASCCONV END ###'); + +if ~isempty(ascstart) && ~isempty(ascend) + tokens = textscan(char(X((ascstart+22):(ascend-1))),'%s', ... + 'delimiter',char(10)); + for k = 1:numel(tokens{1}) + tokens{1}{k}=regexprep(tokens{1}{k},'\[([0-9]*)\]','($1+1)'); + tokens{1}{k}=regexprep(tokens{1}{k},'"(.*)"','''$1'''); + tokens{1}{k}=regexprep(tokens{1}{k},'0x([0-9a-fA-F]*)','hex2dec(''$1'')'); + try + eval(['ret.' tokens{1}{k} ';']); + catch + disp(['AscConv: Error evaluating ''ret.' tokens{1}{k} ''';']); + end; + end; +end; +%_______________________________________________________________________ diff --git a/spm/spm5/spm_jobman.m b/spm/spm5/spm_jobman.m new file mode 100644 index 0000000..1baf882 --- /dev/null +++ b/spm/spm5/spm_jobman.m @@ -0,0 +1,2934 @@ +function varargout = spm_jobman(varargin) +% UI/Batching stuff +%_______________________________________________________________________ +% This code is based on an earlier version by Philippe Ciuciu and +% Guillaume Flandin of Orsay, France. +% +% FORMAT spm_jobman +% spm_jobman('interactive') +% spm_jobman('interactive',job) +% spm_jobman('interactive',job,node) +% spm_jobman('interactive','',node) +% Runs the user interface in interactive mode. +% +% FORMAT spm_jobman('serial') +% spm_jobman('serial',job) +% spm_jobman('serial',job,node) +% spm_jobman('serial','',node) +% Runs the user interface in serial mode. +% +% FORMAT spm_jobman('run',job) +% Runs a job. +% +% FORMAT spm_jobman('help',node) +% spm_jobman('help',node,width) +% Creates a cell array containing help information. This is justified +% to be 'width' characters wide. e.g. +% h = spm_jobman('help','jobs.spatial.coreg.estimate'); +% for i=1:numel(h),fprintf('%s\n',h{i}); end; +% +% node - indicates which part of the configuration is to be used. +% For example, it could be 'jobs.spatial.coreg'. +% +% job - can be the name of a jobfile (as a .mat or a .xml), or a +% 'jobs' variable loaded from a jobfile. +% +% +% FORMAT spm_jobman('defaults') +% Runs the interactive defaults editor. +% +% FORMAT spm_jobman('pulldown') +% Creates a pulldown 'TASKS' menu in the Graphics window. +% +% FORMAT spm_jobman('chmod') +% Changes the modality for the TASKS pulldown. +% +% FORMAT [tag,dat] = spm_jobman('harvest',c) +% Take a data structure, and extract what is needed to save it +% as a batch job (for experts only). +% +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_jobman.m 639 2006-09-28 17:09:17Z volkmar $ + + +if nargin==0 + setup_ui; +else + switch lower(varargin{1}) + case {'interactive'} + if nargin>=2 + setup_ui(varargin{2:nargin}); + else + setup_ui; + end; + + case {'serial'} + if nargin>=2, + serial(varargin{2:nargin}); + else + serial; + end; + + case {'run'} + if nargin<2 + error('Nothing to run'); + end; + run_job(varargin{2}); + + case {'defaults'}, + setup_ui('defaults'); + + case {'pulldown'} + pulldown; + + case {'chmod'} + if nargin>1, + chmod(varargin{2}); + end; + + case {'help'} + if nargin>=2, + varargout{1} = showdoc(varargin{2:nargin}); + else + varargout{1} = showdoc; + end; + + case {'harvest'} + [varargout{1:nargout}] = harvest(varargin{2:nargin}); + + otherwise + error(['"' varargin{1} '" - unknown option']); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function defaults_edit(varargin) +setup_ui('defaults'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function interactive(varargin) +ud = get(varargin{1},'UserData'); +if iscell(ud) + setup_ui(ud{:}); +else + setup_ui; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function setup_ui(varargin) +% Configure the user interface + +fg = clearwin; +fs = getdef('ui.fs'); +if numel(fs)~=1 || ~isnumeric(fs{1}) || numel(fs{1})~=1, + fs = 12; +else + fs = fs{1}; +end; + +col1 = getdef('ui.colour1'); +if numel(col1)~=1 || ~isnumeric(col1{1}) || numel(col1{1})~=3, + col1 = [0.8 0.8 1]; +else + col1 = col1{1}; +end; + +col2 = getdef('ui.colour2'); +if numel(col2)~=1 || ~isnumeric(col2{1}) || numel(col2{1})~=3, + col2 = [1 1 0.8]; +else + col2 = col2{1}; +end; + +col3 = getdef('ui.colour3'); +if numel(col3)~=1 || ~isnumeric(col3{1}) || numel(col3{1})~=3, + col3 = [0 0 0]; +else + col3 = col3{1}; +end; + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.02 0.31 0.48 0.67],... + 'Callback',@click_batch_box,... + 'Tag','batch_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'FontSize',fs,... + 'Value',1); +c0 = cntxtmnu(t); +c1 = uimenu('Label','Exp/Con All', 'Parent',c0); +uimenu('Label','Expand All', 'Parent',c1,'Callback',@expandall); +uimenu('Label','Contract All', 'Parent',c1,'Callback',@contractall); +uimenu('Label','Expand All Undefined Inputs', 'Parent',c1,'Callback',@expandallopen); + +t=uicontrol(fg,... + 'Style','listbox',... + 'ListBoxTop',1,... + 'Units','normalized',... + 'Position',[0.02 0.02 0.96 0.28],... + 'Tag','help_box',... + 'FontName','fixedwidth',... + 'FontSize',fs,... + 'ForegroundColor', col3,... + 'BackgroundColor',col2); +set(t,'Value',[], 'Enable', 'inactive', 'Max',2, 'Min',0); +workaround(t); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.74 0.47 0.24],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'FontSize',fs,... + 'Tag','opts_box'); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.49 0.47 0.24],... + 'Tag','val_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col2,... + 'Enable', 'inactive',... + 'Value',[],... + 'FontSize',fs,... + 'Max',2, 'Min',0); +set(t,'Value',[], 'Enable', 'on', 'Max',2, 'Min',0,'ListBoxTop',1); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.38 0.47 0.10],... + 'Tag','msg_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col2,... + 'Enable', 'inactive',... + 'Value',[],... + 'FontSize',fs,... + 'Max',2, 'Min',0); +cntxtmnu(t); + +if ~(nargin==1 && ischar(varargin{1}) && strcmp(varargin{1},'defaults')), + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.51 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Save',... + 'Callback',@save_job,... + 'FontSize',fs,... + 'Tag','save'); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.67 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Load',... + 'Callback',@load_job,... + 'FontSize',fs,... + 'Tag','load'); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.83 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Run',... + 'Callback',@run_struct,... + 'Tag','run',... + 'FontSize',fs,... + 'Enable', 'off'); + cntxtmnu(t); + if nargin>0 + initialise(varargin{:}); + else + initialise; + end; +else + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.51 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','OK',... + 'FontSize',fs,... + 'Callback',@ok_defaults); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.67 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Reset',... + 'FontSize',fs,... + 'Callback',@reset_defaults); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.83 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Cancel',... + 'FontSize',fs,... + 'Callback',@clearwin); + cntxtmnu(t); + initialise('defaults'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok_defaults(varargin) +harvest_def(get(batch_box,'UserData')); +clearwin; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function reset_defaults(varargin) +global defaults + +modality = []; +if isfield(defaults,'modality'), + modality = defaults.modality; +end; +spm_defaults; +if ~isfield(defaults,'modality') && ~isempty(modality), + defaults.modality = modality; +end; +pulldown; +clearwin; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function fg = clearwin(varargin) + +fg = spm_figure('findwin','Graphics'); +if isempty(fg), fg = spm_figure('Create','Graphics'); end; +delete(findobj(fg,'Parent',fg)); +delete(batch_box); +delete(opts_box); +spm('Pointer'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function expandall(varargin) +c = expcon(get(gco,'UserData'),1); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function contractall(varargin) +c = expcon(get(gco,'UserData'),0); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function expandallopen(varargin) +c = expopen(get(gco,'UserData')); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,sts] = expopen(c) +sts = 0; +if isfield(c,'expanded'), + sts=~all_set(c); +end; +if isfield(c,'val'), + for i=1:length(c.val), + [c.val{i} sts1] = expopen(c.val{i}); + sts = sts||sts1; + end; +end; +if isfield(c,'expanded') + c.expanded = sts; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = expcon(c,val) +if isfield(c,'expanded'), c.expanded = val; end; +if isfield(c,'val'), + for i=1:length(c.val), + c.val{i} = expcon(c.val{i},val); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function initialise(job,node) +% load the config file, possibly adding a job +% to it, and generally tidy it up. The batch box +% is updated to contain the current structure. +files_select_list('init'); +if nargin<1, job = ''; end; +if nargin<2, node = 'jobs'; end; +c = initialise_struct(job); +set(batch_box,'UserData',start_node(c,node)); +update_ui; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_job(job) +% Run a job. This function is not called via the UI. +c = initialise_struct(job); +if all_set(c), + run_struct1(c); +else + error('This job is not ready yet'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function click_batch_box(varargin) +% Called when the batch box is clicked + +remove_string_box; +if strcmp(get(get(varargin{1},'Parent'),'SelectionType'),'open') + run_in_current_node(@expand_contract,false); + str = get_strings(get(batch_box,'UserData')); + val = min(get(batch_box,'Value'),length(str)); + set(batch_box,'String',str,'Value',val); +else + run_in_current_node(@click_batch_box_fun,false); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function update_ui +[str,sts] = get_strings(get(batch_box,'UserData')); +val = min(get(batch_box,'Value'),length(str)); +set(batch_box,'String',str,'Value',val); +run_in_current_node(@click_batch_box_fun,false); + +run_but = findobj(0,'Tag','run'); +if sts + set(run_but,'Enable', 'on'); +else + set(run_but,'Enable', 'off'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [str,sts] = get_strings(c) +[unused,str,sts] = start_node(c,@get_strings1,0); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,str,sts] = get_strings1(c,l) +% Return the cell vector of strings displayed in the batch +% box, and also whether the job is runable. This is a recursive +% function that a branch of the data structure is passed to. + +if isfield(c,'hidden'), + sts = 1; + str = ''; + return; +end; + +sts = 1; +mrk = ' '; +nam = ''; +if isfield(c,'datacheck') && ~isempty(c.datacheck), + mrk = ' <-@'; + sts = 0; +end; +if isfield(c,'name'), nam = c.name; end; + +if isfield(c,'expanded') % && isfield(c,'val') && ~isempty(c.val) + + if strcmp(c.type,'repeat') && isfield(c,'num') + sts = (length(c.val) >= c.num(1)) &&... + (length(c.val) <= c.num(2)); + if ~sts + mrk = ' <-X'; + end; + end; + + if c.expanded + str = {[repmat('. ',1,l) '-' nam]}; + for i=1:length(c.val) + [c.val{i},str1,sts1] = get_strings1(c.val{i},l+1); + sts = sts && sts1; + if ~isempty(str1), + str = {str{:},str1{:}}; + end; + end; + else + str = {[repmat('. ',1,l) '+' nam]}; + for i=1:length(c.val) + [c.val{i},unused,sts1] = get_strings1(c.val{i},l+1); + sts = sts && sts1; + end; + if ~sts, + mrk = ' <-X'; + end; + end; + str{1} = [str{1} mrk]; +else + switch c.type + case 'files' + % If files are selected via "Input to/Output from" shortcuts, + % there is no guarantee that an allowed number of files is + % specified. This is checked here. + cn = c.num; + if (numel(cn) == 1) + if isfinite(cn) + cn = [cn cn]; + else + cn = [0 cn]; + + end; + end; + if isempty(c.val) || (numel(c.val{1}) < cn(1)) || ... + (numel(c.val{1}) > cn(2)) + mrk = ' <-X'; + sts = 0; + end; + case {'menu','entry','const','choice'} + if isempty(c.val) + mrk = ' <-X'; + sts = 0; + end; + case 'repeat' % don't know, whether this ever gets executed + if isfield(c,'num') + sts = (length(c.val) >= c.num(1)) &&... + (length(c.val) <= c.num(2)); + if ~sts + mrk = ' <-X'; + end; + end; + end; + str = {[repmat('. ',1,l) ' ' nam mrk]}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = all_set(c) +% Return whether all the necessary fields have been filled in. +% This is a recursive function that a branch of the data structure +% is passed to. + +if isfield(c,'hidden'), + ok = true; + return; +end; + +ok = true; + +switch c.type +case {'files','menu','entry','const','choice'} + if isempty(c.val) + ok = false; + end; + +case {'branch','repeat'} + if strcmp(c.type,'repeat') && isfield(c,'num') + ok = ok && (length(c.val) >= c.num(1)) && ... + (length(c.val) <= c.num(2)); + end; + if ok, + for i=1:length(c.val), + ok1 = all_set(c.val{i}); + ok = ok && ok1; + if ~ok, break; end; + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function click_options_box(varargin) +% The function called when the options box is clicked + +dat = get(opts_box,'UserData'); +if ~isempty(dat) + fun = dat{get(opts_box,'Value')}; + run_in_current_node(fun.fun,true,fun.args{:}); + if fun.redraw, update_ui; end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function varargout = run_in_current_node(varargin) +% Get the current node, and run a job in it +varargout = {}; +c = get(batch_box,'UserData'); +n = get(batch_box,'Value'); +show_msg(''); +va = {c,@run_in_current_node1,n,varargin{:}}; +[c,unused,varargout{:}] = start_node(va{:}); +set(batch_box,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,varargout] = start_node(c,fun,varargin) +persistent node; +if isempty(node) + node = {'jobs'}; +end; +varargout = {}; +if nargin==2 + tmp = [0 find([fun '.']=='.')]; + node = {}; + for i=1:length(tmp)-1 + node = {node{:},fun((tmp(i)+1):(tmp(i+1)-1))}; + end; + c = make_nodes(c,node); + return; +end; +va = {c,node,fun,varargin{:}}; +[c,unused,varargout{1:nargout-1}] = start_node1(va{:}); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = make_nodes(c,node) +if isfield(c,'tag') && ~strcmp(gettag(c),node{1}) + return; +end; +if isfield(c,'tag') + node = {node{2:end}}; + if isempty(node), return; end; +end; +if isfield(c,'values') && (~isfield(c,'val') ||... + isempty(c.val) || ~iscell(c.val) ||... + ~strcmp(gettag(c.val{1}),node{1})) + for i=1:length(c.values) + if strcmp(gettag(c.values{i}),node{1}) + c.val = {c.values{i}}; + c.val{1} = make_nodes(c.val{1},node); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,sts,varargout] = start_node1(c,node,fun,varargin) +varargout = {}; +if nargin<4, varargin = {}; end; +if isfield(c,'tag') && ~strcmp(gettag(c),node{1}) + varargout = cell(1,nargout-2); + sts = 0; + return; +end; +if isfield(c,'tag'), + node = {node{2:end}}; +end; +if isempty(node) + [c,varargout{1:nargout-2}] = feval(fun,c,varargin{:}); + sts = 1; + return; +end; +if isfield(c,'val'), + for i=1:length(c.val) + [c.val{i},sts,varargout{1:nargout-2}] = start_node1(c.val{i},node,fun,varargin{:}); + if sts, return; end; + end; +end; +keyboard +error('No such node'); % Should never execute +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,n,varargout] = run_in_current_node1(c,n,fun,modify,varargin) +% Satellite for run_in_current_node + +varargout = {}; +if nargin<5, varargin = {}; end; +if isfield(c,'hidden'), return; end; + +n = n-1; +if n<0, return; end; +if n==0, + if ~isfield(c,'datacheck'), + show_msg(''); + else + show_msg(c.datacheck); + end; + [c,varargout{:}] = feval(fun,c,varargin{:}); +end; + +if isfield(c,'expanded') && ~isempty(c.val) + if c.expanded, + val = c.val; + c.val = {}; + for i=1:length(val) + [tmp,n,varargout{:}] = run_in_current_node1(val{i},n,fun,modify,varargin{:}); + if ~isempty(tmp) + if iscell(tmp) + c.val = {c.val{:}, tmp{:}}; + else + c.val = {c.val{:}, tmp}; + end; + end; + end; + if modify && isfield(c,'check'), + if all_set(c), + [unused,val] = harvest(c); + c.datacheck = feval(c.check,val); + end; + end; + if isfield(c,'datacheck') && ~isempty(c.datacheck), + show_msg(c.datacheck); + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = click_batch_box_fun(c,unused) +% Mostly set up the options box, but also update the help and value boxes + +if ~isempty(opts_box) + dat = {}; + str = {}; + + switch c.type + case {'const'} + % do nothing + + case {'files'} + spm('pointer','watch'); + str = {str{:}, 'Specify Files'}; + dat = {dat{:}, struct('fun',@file_select,'args',{{}},'redraw',1)}; + addvfiles(c.id,[],c); + addinfiles(c); + [filestr filedat] = files_select_list('listall'); + str = {str{:}, filestr{:}}; + dat = {dat{:}, filedat{:}}; + spm('pointer','arrow'); + + case {'menu'} + str = {str{:}, 'Specify Menu Item'}; + dat = {dat{:}, struct('fun',@menu_entry,'args',{{}},'redraw',0)}; + + case {'entry'} + str = {str{:}, 'Specify Text'}; + dat = {dat{:}, struct('fun',@text_entry,'args',{{}},'redraw',1)}; + + case {'branch','choice','repeat'} + if strcmp(c.type,'repeat') + for i=1:length(c.values) + if ~isfield(c.values{i},'hidden'), + str = {str{:},['New "' c.values{i}.name '"']}; + dat = {dat{:}, struct('fun',@series,'args',{{c.values{i}}},'redraw',1)}; + end; + end; + + elseif strcmp(c.type,'choice') + for i=1:length(c.values) + if ~isfield(c.values{i},'hidden'), + str = {str{:},['Choose "' c.values{i}.name '"']}; + dat = {dat{:}, struct('fun',@choose,'args',{{c.values{i}}},'redraw',1)}; + end; + end; + end; + end; + + if isfield(c,'removable') + str = {str{:},['Remove Item "' c.name '"'],['Replicate Item "' c.name '"']}; + dat = {dat{:}, struct('fun',@remove,'args',{{}},'redraw',1),... + struct('fun',@replicate,'args',{{}},'redraw',1)}; + end; + + if ~same(get(opts_box,'String')',str) + val = 1; + else + val = get(opts_box,'Value'); + end; + val = max(min(length(str),val),min(1,length(str))); + set(opts_box,'String',str,'UserData',dat,'Callback',@click_options_box,'Value',val); +end; + +show_value(c); + +% Update help +txt = ''; +if isfield(c,'help'), txt = c.help; end; +help_box = findobj(0,'tag','help_box'); +if ~isempty(help_box) + set(help_box,'String',' '); + workaround(help_box); + ext = get(help_box,'Extent'); + pos = get(help_box,'position'); + pw = floor(pos(3)/ext(3)*21-4); + set(help_box,'String',spm_justify(help_box,txt)); + workaround(help_box); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = expand_contract(c,unused) +% Expand/contract a node (for visualisation) + +if isfield(c,'expanded') && ~isempty(c.val) + if c.expanded + c.expanded = false; + else + c.expanded = true; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = menu_entry(c,unused) +% Setup opts box for menu entry + +if isfield(c,'labels') && isfield(c,'values') + str = {}; + dat = {}; + if ~isempty(c.val) + val = c.val{1}; + else + val = ''; + end; + dv = 1; + for i=1:length(c.values) + if ~(ischar(val) && strcmp(val,'')) && same(c.values{i},val) + str{i} = ['* ' c.labels{i}]; + dv = i; + else + str{i} = [' ' c.labels{i}]; + end; + dat{i} = struct('fun',@menuval,'args',{{c.values{i}}},'redraw',1); + end; + set(opts_box,'String',str,'UserData',dat,'Callback',@click_options_box,'Value',dv); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c] = file_select(c) +% Select files +try + set(batch_box,'Enable', 'inactive'); + set(opts_box, 'Enable', 'inactive'); + + if ~isempty(c.val), + sel = c.val{1}; + else + sel = ''; + end; + if isfield(c,'dir'), + dr = c.dir; + else + dr = pwd; + end; + if isfield(c,'ufilter') + uf = c.ufilter; + else + uf = '.*'; + end; + [s,ok] = spm_select(c.num,c.filter,c.name,sel,dr,uf); + if ok, c.val{1} = cellstr(s); end; + files_select_list('addinfiles', sprintf('Input to "%s"', c.name), ... + c.val{1}, c.id); +catch +end; +spm_select('clearvfiles'); +set(batch_box,'Enable', 'on'); +set(opts_box, 'Enable', 'on'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = text_entry(c) +% Create a string box and prompt, while hiding the opts box + +opts_box = findobj(gcf,'tag','opts_box'); +pos = get(opts_box,'Position'); +set(opts_box,'Visible','off'); +fs = get(opts_box,'FontSize'); +fa = get(opts_box,'FontAngle'); +fw = get(opts_box,'FontWeight'); +clf = get(opts_box,'ForegroundColor'); +clb = get(opts_box,'BackgroundColor'); + +n = []; +m = []; +if isfield(c,'num'), n = c.num; end; +if isfield(c,'extras'), m = c.extras; end; + +newstring = uicontrol(gcf,... + 'Style','edit',... + 'Units','normalized',... + 'Position',[pos(1:3) pos(4)/2],... + 'Tag','string_box',... + 'HorizontalAlignment','left',... + 'FontSize',fs,... + 'FontAngle',fa,... + 'FontWeight',fw,... + 'ForegroundColor',clf,... + 'BackgroundColor',clb,... + 'Callback',@accept_string); +cntxtmnu(newstring); + +strM=''; +switch lower(c.strtype) +case 's', TTstr='enter string'; +case 'e', TTstr='enter expression - evaluated'; +case 'n', TTstr='enter expression - natural number(s)'; + if ~isempty(m), strM=sprintf(' (in [1,%d])',m); TTstr=[TTstr,strM]; end +case 'w', TTstr='enter expression - whole number(s)'; + if ~isempty(m), strM=sprintf(' (in [0,%d])',m); TTstr=[TTstr,strM]; end +case 'i', TTstr='enter expression - integer(s)'; +case 'r', TTstr='enter expression - real number(s)'; + if ~isempty(m), TTstr=[TTstr,sprintf(' in [%g,%g]',min(m),max(m))]; end +case 'c', TTstr='enter indicator vector e.g. 0101... or abab...'; + if ~isempty(m) && isfinite(m), strM=sprintf(' (%d)',m); end +otherwise, TTstr='enter expression'; +end + +if isempty(n), n=NaN; end +n=n(:); if length(n)==1, n=[n,1]; end; dn=length(n); +if any(isnan(n)) || (prod(n)==1 && dn<=2) || (dn==2 && min(n)==1 && isinf(max(n))) + str = ''; + lstr = ''; +elseif dn==2 && min(n)==1 + str = sprintf('[%d]',max(n)); + lstr = [str,'-vector: ']; +elseif dn==2 && sum(isinf(n))==1 + str = sprintf('[%d]',min(n)); + lstr = [str,'-vector(s): ']; +else + str=''; + for i = 1:dn, + if isfinite(n(i)), + str = sprintf('%s,%d',str,n(i)); + else + str = sprintf('%s,*',str); + end + end + str = ['[',str(2:end),']']; + lstr = [str,'-matrix: ']; +end +strN = sprintf('%s',lstr); +col = get(gcf,'Color'); +uicontrol(gcf,'Style','text',... + 'Units','normalized',... + 'BackgroundColor',col,... + 'String',[strN,strM,TTstr],... + 'Tag','string_prompt',... + 'HorizontalAlignment','Left',... + 'FontSize',fs,... + 'FontAngle',fa,... + 'FontWeight',fw,... + 'Position',[pos(1:3)+[0 pos(4)/2 0] pos(4)/2]); + +if isfield(c,'val') && ~isempty(c.val) + val = c.val{1}; + if ischar(val) + tmp = val'; + tmp = tmp(:)'; + set(newstring,'String',tmp); + elseif isnumeric(val) + if ndims(val)>2, + set(newstring,'String',['reshape([', num2str(val(:)'), '],[' num2str(size(val)) '])']); + else + if size(val,1)==1, + set(newstring,'String',num2str(val(:)')); + elseif size(val,2)==1, + set(newstring,'String',['[' num2str(val(:)') ']''']); + else + str = ''; + for i=1:size(val,1), + str = [str ' ' num2str(val(i,:)) ';']; + end; + set(newstring,'String',str); + end; + end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function accept_string(varargin) +% Accept a typed in string? +run_in_current_node(@stringval,true,get(varargin{1},'String')); +update_ui; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function remove_string_box +% Delete the string box and prompt, making the opts box +% visible again +delete(findobj(0,'Tag','string_box')); +delete(findobj(0,'Tag','string_prompt')); +set(opts_box,'Visible','on'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function show_value(c) +% Update the value box + +valtxt = {''}; +% col = [1 0 0]; + +switch c.type +case {'menu'} + if isfield(c,'val') && ~isempty(c.val) + if isfield(c,'labels') && isfield(c,'values') + val = c.val{1}; + for i=1:length(c.values) + if same(c.values{i},val) + valtxt = c.labels{i}; + % col = [0 0 0]; + break; + end; + end; + end; + end; + +case {'const','entry'} + if isfield(c,'val') && ~isempty(c.val) + val = c.val{1}; + if isempty(val) + valtxt = ''; + else + if isnumeric(val) + sz = size(val); + if length(sz)>2 + valtxt = sprintf('%dx',sz); + valtxt = [valtxt(1:(end-1)) ' Numeric Array']; + else + valtxt = cell(size(val,1),1); + for i=1:size(val,1) + valtxt{i} = sprintf('%14.8g ',val(i,:)); + end; + end; + elseif(ischar(val)) + valtxt = val; + else + valtxt = 'Can not display'; + end; + end; + % col = [0 0 0]; + end; + +case {'files'} + if isfield(c,'val') && ~isempty(c.val) + if isempty(c.val{1}) || isempty(c.val{1}{1}) + valtxt = ''; + else + valtxt = c.val{1}; + end; + % col = [0 0 0]; + end; + +case {'choice'} + if isfield(c,'val') && length(c.val)==1 + valtxt = {'A choice, where',['"' c.val{1}.name '"'], 'is selected.'}; + % col = [0.5 0.5 0.5]; + else + valtxt = {'A choice, with', 'nothing selected.'}; + % col = [0.5 0.5 0.5]; + end; + +case {'repeat'} + ln = length(c.val); s = 's'; if ln==1, s = ''; end; + valtxt = ['A series containing ' num2str(length(c.val)) ' item' s '.']; + % col = [0.5 0.5 0.5]; + +case {'branch'} + ln = length(c.val); s = 's'; if ln==1, s = ''; end; + valtxt = {['A branch holding ' num2str(length(c.val)) ' item' s '.']}; + if isfield(c,'prog'), + valtxt = {valtxt{:}, '', ' User specified values',... + ' from this branch will be',... + ' collected and passed to',... + ' an executable function',... + ' when the job is run.'}; + end; + % col = [0.5 0.5 0.5]; + +otherwise + valtxt = 'What on earth is this???'; +end; +val_box = findobj(0,'tag','val_box'); +if ~isempty(val_box) + % set(val_box,'String',valtxt,'ForegroundColor',col); + set(val_box,'String',valtxt); + workaround(val_box); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = remove(c,varargin) +% Remove node c +if strcmp(questdlg(['Remove "' c.name '"?'],'Confirm','Yes','No','Yes'),'Yes'), + c = {}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = replicate(c,varargin) +% Replicate node c +c = {c,uniq_id(c)}; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = choose(c,val) +% Specify the value of c to be val +c.val{1} = uniq_id(val); +c.expanded = true; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = menuval(c,val) +% Specify the value of c to be val +c.val{1} = val; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = stringval(c,val) +% Accept (or not) a typed in string + +msg = 'SUCCESS: Values accepted'; + +switch c.strtype +case {'s'} + c.val{1} = val; + show_value(c); + remove_string_box; + +case {'s+'} + msg = 'FAILURE: Cant do s+ yet'; + beep; + remove_string_box; + +otherwise + n = Inf; + if isfield(c,'num') + n = c.num; + end; + if isfield(c,'extras') + [val,msg] = spm_eeval(val,c.strtype,n,c.extras); + else + [val,msg] = spm_eeval(val,c.strtype,n); + end; + + if ischar(val) + beep; + msg = ['FAILURE: ' msg]; + else + c.val{1} = val; + show_value(c); + remove_string_box; + msg = ['SUCCESS: ' msg]; + end; +end; +show_msg(msg); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = series(c,new) +% Add a new repeat +c.expanded = true; +new.removable = true; +if isfield(c,'val') + c.val = {c.val{:},uniq_id(new)}; +else + c.val = {uniq_id(new)}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function setdef(strin,val) +global defaults + +if isempty(defaults), spm_defaults; end; +if ischar(val) && strcmp(val,''), return; end; +o = find(strin=='.'); +df = cell(1,length(o)+1); +prev = 1; +for i=1:length(o), + df{i} = strin(prev:(o(i)-1)); + prev = o(i)+1; +end; +df{end} = strin(prev:end); +defaults = setdef_sub(defaults,df,val); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function d = setdef_sub(d,df,val) +if isempty(df), + d = val; +else + if ~isfield(d,df{1}),d.(df{1}) = []; end; + d.(df{1}) = setdef_sub(d.(df{1}),df(2:end),val); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function val = getdef(strin) +% Get value of one of the SPM defaults + +global defaults + +val = getdef_sub(defaults,strin); +if ischar(val) && strcmp(val,'') + val = {}; +else + val = {val}; +end; +%fprintf('%s\n',strin); +%disp(val) +%disp('----'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = getdef_sub(defs,field) +% Satellite function for getdef + +o = find(field=='.'); +if isempty(o) + if isfield(defs,field) + c = defs.(field); + else + c = ''; + end; + return; +end; +if isfield(defs,field(1:(o-1))) + c = getdef_sub(defs.(field(1:(o-1))),field((o+1):end)); +else + c = ''; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = same(a,b) +% Are two data structures identical? + +% Innocent until proven guilty +t = true; + +% Check the dimensions +if isempty(a) && isempty(b) + t = true; return; +end; +sa = size(a); +sb = size(b); +if length(sa) ~= length(sb) + t = false; return; +end; +if ~all(sa==sb) + t = false; return; +end; + +% Check the classes +ca = class(a); +if ~strcmp(ca,class(b)), t = false; return; end; + +% Recurse through data structure +switch ca +case {'double','single','sparse','char','int8','uint8',... + 'int16','uint16','int32','uint32','logical'} + msk = ((a==b) | (isnan(a)&isnan(b))); + if ~all(msk(:)), t = false; return; end; + +case {'struct'} + fa = fieldnames(a); + fb = fieldnames(b); + if length(fa) ~= length(fb), t = false; return; end; + for i=1:length(fa) + if ~strcmp(fa{i},fb{i}), t = false; return; end; + for j=1:length(a) + if ~same(a(j).(fa{i}),b(j).(fb{i})) + t = false; return; + end; + end; + end; + +case {'cell'} + for j=1:length(a(:)) + if ~same(a{j},b{j}), t = false; return; end; + end; + +case {'function_handle'} + if ~strcmp(func2str(a),func2str(b)) + t = false; return; + end; + +otherwise + warning(['Unknown class "' ca '"']); + t = false; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = batch_box +t = findobj(0,'tag','batch_box'); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = opts_box +t = findobj(0,'tag','opts_box'); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function save_job(varargin) +% Save a batch job +c = get(batch_box,'UserData'); spm('Pointer','Watch'); +[unused,jobs] = harvest(c); +spm('Pointer'); +%eval([tag '=val;']); +cll = {'*.mat','Matlab .mat file';'*.m','Matlab script file';'*.xml','XML file'}; +[filename, pathname, FilterIndex] = uiputfile(cll,'Save job as'); +if ischar(filename) + [unused,unused,ext] = fileparts(filename); + if isempty(ext) + ext = cll{FilterIndex}(2:end); + filename = [filename ext]; + end + switch ext + case '.xml', + spm('Pointer','Watch'); + savexml(fullfile(pathname,filename),'jobs'); + spm('Pointer'); + case '.mat', + if spm_matlab_version_chk('7') >= 0, + save(fullfile(pathname,filename),'-V6','jobs'); + else + save(fullfile(pathname,filename),'jobs'); + end; + case '.m', + treelist('jobs',struct('exps',1, 'dval',2, 'fname', ... + fullfile(pathname,filename))); + otherwise + questdlg(['Unknown extension (' ext ')'],'Nothing saved','OK','OK'); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function load_job(varargin) +% Load a set of batch jobs and possibly merge it + +[filenames sts] = spm_select([1 Inf], 'batch', 'Load job file(s)'); +if sts + filenames = cellstr(filenames); + newjobs = {}; + for cf = 1:numel(filenames) + [p,nam,ext] = fileparts(filenames{cf}); + switch ext + case '.xml', + spm('Pointer','Watch'); + try + loadxml(filenames{cf},'jobs'); + catch + questdlg('LoadXML failed',filenames{cf},'OK','OK'); + return; + end; + spm('Pointer'); + case '.mat' + try + load(filenames{cf},'jobs'); + catch + questdlg('Load failed',filenames{cf},'OK','OK'); + end; + case '.m' + opwd = pwd; + try + cd(p); + eval(nam); + catch + questdlg('Load failed',filenames{cf},'OK','OK'); + end; + cd(opwd); + otherwise + questdlg(['Job ' nam ': Unknown extension (' ext ')'],... + 'This job not loaded','OK','OK'); + end; + if exist('jobs','var') + newjobs = {newjobs{:} jobs{:}}; + clear jobs; + else + questdlg(['No jobs (' nam ext ')'],'No jobs','OK','OK'); + end; + end; + if ~isempty(newjobs) + spm('Pointer','Watch'); + initialise(newjobs); + spm('Pointer'); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_struct(varargin) +% Get data structure from handle, and run it +% If an error occured, then return to user interface +c = get(batch_box,'UserData'); +[unused,job] = harvest(c); +try +run_struct1(c); +catch + disp('Error running job:'); + disp(lasterr); + setup_ui(job); +end; +disp('--------------------------'); +disp('Done.'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_struct1(c) +% Run a batch job from a data structure + +if isfield(c,'prog') + prog = c.prog; + [unused,val] = harvest(c); + disp('--------------------------'); + disp(['Running "' c.name '"']); + [Finter,unused,CmdLine] = spm('FnUIsetup',c.name); + spm('Pointer','Watch'); + spm('FigName',[c.name ': running'],Finter,CmdLine); + + if 0 + try + feval(prog,val); + spm('FigName',[c.name ': done'],Finter,CmdLine); + catch + disp(['An error occurred when running "' c.name '"']); + disp( '--------------------------------'); + disp(lasterr); + disp( '--------------------------------'); + spm('FigName',[c.name ': failed'],Finter,CmdLine); + errordlg({['An error occurred when running "' c.name '"'],lasterr},'SPM Jobs'); + end; + spm('Pointer'); + else + feval(prog,val); + spm('FigName',[c.name ': done'],Finter,CmdLine); + %prog_infos=functions(prog) + %prog_log=[prog_infos.parentage{end} '_log']; + %if exist(prog_log) > 1 + try + spm_log2html(prog,val); + disp(sprintf('Generating log on %s',c.name)); + catch + disp(sprintf('Error while generating log on %s',c.name)); + end + %else + % prog_msg=sprintf('No function found for generating log on %s. Try making a: %s',c.name, prog_log); + %end + %disp(prog_msg); + spm('Pointer'); + end; + +else + if isfield(c,'val') + for i=1:length(c.val) + run_struct1(c.val{i}); + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function harvest_def(c) +switch c.type, +case{'const','menu','files','entry'}, + if isfield(c,'def') && numel(c.val)==1, + setdef(c.def,c.val{1}); + end; + +otherwise + for i=1:length(c.val), + harvest_def(c.val{i}); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [tag,val,typ] = harvest(c) +% Take a data structure, and extract what is needed to save it +% as a batch job + +tag = 'unknown'; +val = []; +typ = c.type; +switch(typ) +case {'const','menu','files','entry'} + tag = gettag(c); + if ~isempty(c.val) + val = c.val{1}; + else + val = ''; + end; + +case {'branch'} + tag = gettag(c); + if isfield(c,'val') + val = []; + for i=1:length(c.val) + [tag1,val1] = harvest(c.val{i}); + val.(tag1) = val1; + end; + end; + +case {'repeat'} + tag = gettag(c); + if length(c.values)==1 && strcmp(c.values{1}.type,'branch'), + cargs = {}; + for i=1:numel(c.values{1}.val), + cargs = {cargs{:},gettag(c.values{1}.val{i}),{}}; + end; + val = struct(cargs{:}); + + if isfield(c,'val') + for i=1:length(c.val), + [tag1,val1,typ1] = harvest(c.val{i}); + val(i) = val1; + end; + end; + else + val = {}; + if isfield(c,'val') + for i=1:length(c.val), + [tag1,val1,typ1] = harvest(c.val{i}); + if length(c.values)>1, + if iscell(val1) + val1 = struct(tag1,{val1}); + else + val1 = struct(tag1,val1); + end; + end; + val = {val{:}, val1}; + end; + end; + end; + +case {'choice'} + if isfield(c,'tag'), tag = gettag(c); end; + [tag1,val1] = harvest(c.val{1}); + if iscell(val1) + val = struct(tag1,{val1}); + else + val = struct(tag1,val1); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function tag = gettag(c) +% Get a tag field - possibly from one of the kids + +if (strcmp(c.type,'repeat') || strcmp(c.type,'choice')) && numel(c.values)>0 + tag = gettag(c.values{1}); + for i=2:length(c.values) + if ~strcmp(tag,gettag(c.values{i})) + tag = c.tag; + return; + end; + end; +else + tag = c.tag; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c0 = cntxtmnu(ob) +c0 = uicontextmenu('Parent',get(ob,'Parent')); +set(ob,'uicontextmenu',c0); +c1 = uimenu('Label','Font', 'Parent',c0); + uimenu('Label','Plain', 'Parent',c1,'Callback','set(gco,''FontWeight'',''normal'',''FontAngle'',''normal'');'); + uimenu('Label','Bold', 'Parent',c1,'Callback','set(gco,''FontWeight'',''bold'', ''FontAngle'',''normal'');'); + uimenu('Label','Italic', 'Parent',c1,'Callback','set(gco,''FontWeight'',''normal'',''FontAngle'',''italic'');'); + uimenu('Label','Bold-Italic','Parent',c1,'Callback','set(gco,''FontWeight'',''bold'', ''FontAngle'',''italic'');'); +c1 = uimenu('Label','Fontsize','Parent',c0); +fs = [8 9 10 12 14 16 18]; % [20 24 28 32 36 44 48 54 60 66 72 80 88 96]; +for i=fs, + uimenu('Label',sprintf('%-3d',i),'Parent',c1,'Callback',@fszoom,'UserData',i); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function workaround(t) +set(t,'Value',[], 'Enable', 'on', 'Max',2, 'Min',0,'ListBoxTop',1); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function addvfiles(id,c,c0) +if (nargin<2)||isempty(c), + c = get(batch_box,'UserData'); +end; +if nargin<3 + c0 = []; +end; +files_select_list('clearvfiles'); +vf =addvfiles1(c,id,{},c0); +spm_select('clearvfiles'); +spm_select('addvfiles',vf); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [vf,sts]=addvfiles1(c,id,vf,c0) +sts = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; + +if isfield(c,'vfiles'), + if ~find_id(c,id), + [c,unused,ok] = get_strings1(c,0); + if ok, + [unused,job] = harvest(c); + vf1 = feval(c.vfiles,job); + if ~isempty(c0) + files = filter_files(c0, vf1); + else + files = vf1; + end; + if ~isempty(files) + files_select_list('addvfiles', sprintf('Output from "%s"', ... + c.name), ... + files, c.id); + end; + vf = {vf{:}, vf1{:}}; + end; + else + sts = 1; + end; + return; +end; + +switch c.type, +case {'repeat','choice','branch'}, + for i=1:length(c.val), + [vf,sts]=addvfiles1(c.val{i},id,vf,c0); + if sts, return; end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function addinfiles(c0,c) +id = c0.id; +if nargin<2, + c = get(batch_box,'UserData'); +end; +files_select_list('clearinfiles'); +addinfiles1(c,id,'',c0); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function sts=addinfiles1(c,id,progname,c0) +sts = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; + +if find_id(c,id), + sts = 1; +end; + +switch c.type, +case 'files' + if ~isempty(c.val) && ~isempty(c.val{1}) + files = filter_files(c0,c.val{1}); + if ~isempty(files) + files_select_list('addinfiles', ... + sprintf('Input to "%s->%s"', ... + progname, c.name), ... + files, c.id); + end; + end; +case {'repeat','choice','branch'}, + if isfield(c,'prog') + progname = c.name; + oldin = files_select_list('getinnum'); + end; + for i=1:length(c.val), + sts=addinfiles1(c.val{i},id,progname,c0); + if sts, return; end; + end; + if isfield(c,'prog') + newin = files_select_list('getinnum'); + if (newin-oldin > 1) + files_select_list('allinfiles', ... + sprintf('All inputs to %s',progname),... + oldin+1, newin); + end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ffiles = filter_files(c,files) +if strcmp(c.filter, 'image')||strcmp(c.filter,'dir') + filter = ['ext' c.filter]; +else + filter = c.filter; +end; +if isfield(c,'ufilter') + uf = c.ufilter; + if uf(1) == '^' % This will not work with full pathnames + uf=uf(2:end); + end; +else + uf = '.*'; +end; +ffiles = spm_select('filter', files, ... + filter, uf); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function varargout = files_select_list(c,varargin) +persistent vfstr; +persistent vfdat; +persistent vffiles; +persistent vfid; +persistent instr; +persistent indat; +persistent infiles; +persistent inid; +if isstruct(c) + switch lower(varargin{1}) + case 'getvf' + c.val{1} = vffiles{varargin{2}}; + case 'getin' + c.val{1} = infiles{varargin{2}}; + end; + varargout{1} = c; + return; +end; +if ~iscell(vfstr) && ~strcmp(lower(c),'init') + files_select_list('init'); +end; +switch lower(c) +case 'init' + vfstr = {}; + vfdat = {}; + vffiles = {}; + vfid = []; + instr = {}; + indat = {}; + infiles = {}; + inid = []; +case 'clearvfiles' + vfstr = {}; + vfdat = {}; + vffiles = {}; + vfid = []; +case 'clearinfiles' + instr = {}; + indat = {}; + infiles = {}; + inid = []; +case 'addvfiles' + nvfind = numel(vfstr)+1; + vfid(nvfind) = varargin{3}; + vfstr{nvfind} = varargin{1}; + vfdat{nvfind} = struct('fun',@files_select_list,'args',{{'getvf', nvfind}}, ... + 'redraw',1); + vffiles{nvfind} = varargin{2}(:); +case 'addinfiles' + ninind = numel(instr)+1; + inid(ninind) = varargin{3}; + instr{ninind} = varargin{1}; + indat{ninind} = struct('fun',@files_select_list,'args',{{'getin', ninind}}, ... + 'redraw',1); + infiles{ninind} = varargin{2}(:); +case 'allinfiles' + ninind = numel(instr)+1; + inid(ninind) = -1; + instr{ninind} = varargin{1}; + indat{ninind} = struct('fun',@files_select_list,'args',{{'getin', ninind}}, ... + 'redraw',1); + infiles{ninind} = cat(1,infiles{varargin{2}:varargin{3}}); +case 'getinnum' + varargout{1} = numel(instr); +case 'listall' + varargout{1} = {vfstr{:} instr{:}}; + varargout{2} = {vfdat{:} indat{:}}; +end +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = find_id(c,id) +ok = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +if c.id==id, + ok = 1; + return; +end; +if isfield(c,'val'), + for i=1:length(c.val), + ok = find_id(c.val{i},id); + if ok, return; end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = uniq_id(c) +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +c.id = rand(1); +if isfield(c,'val'), + for i=1:length(c.val), + c.val{i} = uniq_id(c.val{i}); + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function show_msg(txt) +lb = findobj('tag','msg_box'); +if isempty(txt), + set(lb,'String',{}); +else + msg = get(lb,'String'); + if iscell(txt), + msg = {msg{:} txt{:}}; + else + msg = {msg{:} txt}; + end; + set(lb,'String',msg); +end; +drawnow; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +%function beep +%fprintf('%c',7); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown +% Create a pulldown for individual jobs +c = initialise_struct; +fg = spm_figure('findwin','Graphics'); +if isempty(fg), return; end; +set(0,'ShowHiddenHandles','on'); +delete(findobj(fg,'tag','jobs')); +set(0,'ShowHiddenHandles','off'); +f0 = uimenu(fg,'Label','TASKS','HandleVisibility','off','tag','jobs'); +pulldown1(f0,c,c.tag); +uimenu(f0,'Label','Batch','CallBack',@interactive,'Separator','on'); +uimenu(f0,'Label','Defaults','CallBack',@defaults_edit,'Separator','off'); +f1 = uimenu(f0,'Label','Sequential'); +pulldown2(f1,c,c.tag); + +if 0, % Currently unused + f1 = uimenu(f0,'Label','Modality'); + modalities = {'FMRI','PET','EEG'}; + for i=1:length(modalities) + tmp = modalities{i}; + if strcmp(tmp,getdef('modality')), + tmp = ['*' tmp]; + else + tmp = [' ' tmp]; + end; + uimenu(f1,'Label',tmp,'CallBack',@chmod); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown1(f0,c0,tag0) +if ~isfield(c0,'values'), return; end; +for i=1:length(c0.values), + c1 = c0.values{i}; + if isstruct(c1) && ~isfield(c1,'hidden'), + tag1 = tag0; + if isfield(c1,'tag'), + tag1 = [tag1 '.' c1.tag]; + end; + if isfield(c1,'prog'), + uimenu(f0,'Label',c1.name,'CallBack',@interactive,'UserData',{'',tag1}); + else + f1 = uimenu(f0,'Label',c1.name); + pulldown1(f1,c1,tag1); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown2(f0,c0,tag0) +if ~isfield(c0,'values'), return; end; +for i=1:length(c0.values), + c1 = c0.values{i}; + if isstruct(c1) && ~isfield(c1,'hidden'), + tag1 = tag0; + if isfield(c1,'tag'), + tag1 = [tag1 '.' c1.tag]; + end; + if isfield(c1,'prog'), + if findcheck(c1), + uimenu(f0,'Label',c1.name,'Enable','off'); + else + uimenu(f0,'Label',c1.name,'CallBack',@run_serial,'UserData',{'',tag1}); + end; + else + f1 = uimenu(f0,'Label',c1.name); + pulldown2(f1,c1,tag1); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function hascheck = findcheck(c) +hascheck = false; +if ~isstruct(c) || ~isfield(c,'type'), return; end; +if isfield(c,'check'), + hascheck = true; + return; +end; +if isfield(c,'values'), + for i=1:numel(c.values), + hascheck = findcheck(c.values{i}); + if hascheck, return; end; + end; +end; +if isfield(c,'val'), + for i=1:numel(c.val), + hascheck = findcheck(c.val{i}); + if hascheck, return; end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function chmod(mod,varargin) +global defaults +if isempty(defaults), spm_defaults; end; +if ischar(mod), + %if strcmpi(defaults.modality,mod), + % spm('ChMod',mod); + %end; + defaults.modality = mod; +else + tmp = get(mod,'Label'); + defaults.modality = tmp(2:end); +end; +pulldown; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function fszoom(varargin) +fs = sscanf(get(varargin{1},'Label'),'%d'); +set(gco,'FontSize',fs); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_serial(varargin) +ud = get(varargin{1},'UserData'); +if iscell(ud) + serial(ud{:}); +else + serial; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function serial(job,node) + +if nargin<2, node = 'jobs'; end; + +fg = spm_figure('FindWin','Interactive'); +if isempty(fg), fg = spm('CreateIntWin'); end; +delete(findobj(fg,'Parent',fg)); +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.02 0.02 0.96 0.62],... + 'Tag','help_box2',... + 'FontName','fixedwidth',... + 'FontSize',12,... + 'BackgroundColor',[1 1 1]); +set(t,'Value',[], 'Enable', 'inactive', 'Max',2, 'Min',0); +workaround(t); +cntxtmnu(t); +spm('Pointer'); +drawnow; + +if nargin>0, + c = initialise_struct(job); +else + c = initialise_struct; +end; + +c = start_node(c,node); +c = start_node(c,@run_ui,{}); +spm_input('!DeleteInputObj'); +delete(findobj(fg,'Parent',fg)); +[unused,jobs] = harvest(c); +%savexml('job_last.xml','jobs'); +run_job(jobs); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = run_ui(c,varargin) + +nnod=1; +while(1), + nod = nnod; + [ci,unused,hlp] = get_node(c,nod); + if isempty(ci), break; end; + + help_box = findobj(0,'tag','help_box2'); + if ~isempty(help_box), + set(help_box,'String',' '); + workaround(help_box); + ext = get(help_box,'Extent'); + pos = get(help_box,'position'); + pw = floor(pos(3)/ext(3)*21-4); + set(help_box,'String',spm_justify(pw,hlp)); + workaround(help_box); + + if isfield(c,'prog'), + try + set(help_box,'HandleVisibility','off'); + [Finter,unused,CmdLine] = spm('FnUIsetup',c.name); + spm('FigName',[c.name ': setup'],Finter,CmdLine); + catch + end; + set(help_box,'HandleVisibility','on'); + end; + end; + + pos = 1; + + switch ci.type, + case {'const','files','menu','entry'} + nnod = nod + 1; + + vl = {''}; + if isfield(ci,'def'), vl = getdef(ci.def); end; + if numel(vl)~=0 && (~ischar(vl{1}) || ~strcmp(vl{1},'')), + getit = 0; + if ~isfield(ci,'val') || ~iscell(ci.val) || isempty(ci.val), + ci.val = vl; + end; + else + getit = 1; + end; + + switch ci.type, + case {'const'} + case {'files'} + num = ci.num; + + if getit, + if ~isempty(ci.val), + sel = ci.val{1}; + else + sel = ''; + end; + addvfiles(ci.id,c); + if isfield(ci,'dir'), + dr = ci.dir; + else + dr = pwd; + end; + if isfield(ci,'ufilter') + uf = ci.ufilter; + else + uf = '.*'; + end; + [ci.val{1},ok] = spm_select(num,ci.filter,ci.name,sel,dr,uf); + if ~ok, + error('File Selector was deleted.'); + end; + spm_select('clearvfiles'); + ci.val{1} = cellstr(ci.val{1}); + end; + + case {'menu'} + dv = []; + if getit, + if isfield(ci,'val') && ~isempty(ci.val), + for i=1:length(ci.values) + if same(ci.values{i},ci.val{1}) + dv = i; + end; + end; + end; + lab = ci.labels{1}; + for i=2:length(ci.values), + lab = [lab '|' ci.labels{i}]; + end; + if isempty(dv), + ind = spm_input(ci.name,pos,'m',lab,1:length(ci.values)); + else + ind = spm_input(ci.name,pos,'m',lab,1:length(ci.values),dv); + end; + ci.val = {ci.values{ind}}; + end; + + case {'entry'} + n1 = Inf; + if isfield(ci,'num'), n1 = ci.num; end; + if getit, + val = ''; + if isfield(ci,'val') && ~isempty(ci.val) && ~strcmp(ci.val{1},''), + val = ci.val{1}; + end; + if isfield(ci,'extras') + val = spm_input(ci.name,pos,ci.strtype,val,n1,ci.extras); + else + val = spm_input(ci.name,pos,ci.strtype,val,n1); + end; + ci.val{1} = val; + end; + end; + + case {'repeat'}, + lab = 'Done'; + for i=1:length(ci.values) + lab = [lab '|New "' ci.values{i}.name '"']; + end; + tmp = spm_input(ci.name,pos,'m',lab,0:length(ci.values)); + if tmp, + ci.val = {ci.val{:}, uniq_id(ci.values{tmp})}; + nnod = nod; + else + nnod = nod + 1; + end; + + case {'choice'} + nnod = nod + 1; + lab = ci.values{1}.name; + for i=2:length(ci.values) + lab = [lab '|' ci.values{i}.name]; + end; + tmp = spm_input(ci.name,pos,'m',lab,1:length(ci.values)); + ci.val = {uniq_id(ci.values{tmp})}; + otherwise + error('This should not happen.'); + end; + c = set_node(c,nod,ci); +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [ci,n,hlp] = get_node(c,n) +ci = []; +hlp = ''; +switch c.type, +case {'const','files','menu','entry'} + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + +case 'choice' + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + [ci,n,hlp] = get_node(c.val{1},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + +case 'branch', + for i=1:numel(c.val), + [ci,n,hlp] = get_node(c.val{i},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + end; + +case 'repeat', + for i=1:numel(c.val), + [ci,n,hlp] = get_node(c.val{i},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + end; + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; +otherwise + error('This should not happen'); + +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,n] = set_node(c,n,ci) +switch c.type, +case {'const','files','menu','entry'} + n = n-1; + if n==0, + c = ci; + return; + end; + +case 'choice' + n = n-1; + if n==0, + c = ci; + return; + end; + [c.val{1},n] = set_node(c.val{1},n,ci); + if n<0,return; end; + +case 'branch', + for i=1:numel(c.val), + [c.val{i},n] = set_node(c.val{i},n,ci); + if n<0,return; end; + end; + +case 'repeat', + for i=1:numel(c.val), + [c.val{i},n] = set_node(c.val{i},n,ci); + if n<0,return; end; + end; + n = n-1; + if n==0, + c = ci; + return; + end; + +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = initialise_struct(job) +% load the config file, possibly adding a job +% to it, and generally tidy it up. The batch box +% is updated to contain the current structure. + +persistent c0 +if isempty(c0), + c0 = spm_config; + c0 = tidy_struct(c0); +end; +c = insert_defs(c0); +if nargin==1 && ischar(job) && strcmp(job,'defaults'), + c = defsub(c,{}); + c.name = 'SPM Defaults'; +else + c = hide_null_jobs(c); + if nargin>0 && ~isempty(job), + job = fromfile(job); + c = job_to_struct(c,job,'jobs'); + c = uniq_id(c); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,defused] = defsub(c,defused) +if nargin<2, defused = {}; end; +if isfield(c,'prog'), c = rmfield(c,'prog'); end; +switch c.type, +case {'const'} + c = []; + +case {'menu','entry','files'} + if ~isfield(c,'def') || any(strcmp(c.def,defused)), + c = []; + else + defused = {defused{:},c.def}; + end; + +case {'branch'} + msk = true(1,length(c.val)); + for i=1:length(c.val), + [c.val{i},defused] = defsub(c.val{i},defused); + msk(i) = ~isempty(c.val{i}); + end; + c.val = c.val(msk); + if isempty(c.val), c = []; end; + +case {'choice','repeat'} + c.type = 'branch'; + c.val = c.values; + c = rmfield(c,'values'); + [c,defused] = defsub(c,defused); + +end; +if isfield(c,'vfiles'), c = rmfield(c,'vfiles'); end; +if isfield(c,'check'), c = rmfield(c,'check'); end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = insert_defs(c) +% Recursively descend through the tree structure, +% and assigning default values. +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +switch c.type +case {'menu','entry','files'} + if isfield(c,'def') + c.val = getdef(c.def); + if strcmp(c.type,'files') && ~isempty(c.val) + if ~isempty(c.val{1}) + c.val = {cellstr(c.val{1})}; + else + c.val = {{}}; + end; + end; + end; + +case {'repeat','choice'}, + if isfield(c,'values') + for i=1:numel(c.values) + c.values{i} = insert_defs(c.values{i}); + end; + end; +end; +if isfield(c,'val') + for i=1:numel(c.val) + c.val{i} = insert_defs(c.val{i}); + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = tidy_struct(c) +% Recursively descend through the tree structure, cleaning up +% fields that may be missing and adding an 'expanded' field +% where necessary. + +if ~isstruct(c) || ~isfield(c,'name') || ~isfield(c,'type') + return; +end; +c.id = rand(1); + +if ~isfield(c,'help'), c.help = {}; end; +if ischar(c.help), c.help = {c.help}; end; + +switch c.type +case {'const'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'val') + disp(c); warning(['No val field for "' c.name '"']); + c.val = {''}; + end; + +case {'menu'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + + if ~isfield(c,'labels') || ~isfield(c,'values') + disp(c); warning(['No labels and values field for "' c.name '"']); + c.labels = {}; + c.values = {}; + end; + if length(c.labels) ~= length(c.values) + disp(c); warning(['Labels and values fields incompatible for "' c.name '"']); + c.labels = {}; + c.values = {}; + end; + if ~isfield(c,'help'), c.help = {'Option selection by menu'}; end; + +case {'entry'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'strtype') + disp(c); warning(['No strtype field for "' c.name '"']); + c.strtype = 'e'; + end; + if ~isfield(c,'num') + disp(c); warning(['No num field for "' c.name '"']); + c.num = [1 1]; + end; + if length(c.num)~=2 + disp(c); warning(['Num field for "' c.name '" is wrong length']); + c.num = [Inf 1]; + end; + if ~isfield(c,'help'), c.help = {'Option selection by text entry'}; end; + +case {'files'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'filter') + disp(c); warning(['No filter field for "' c.name '"']); + c.filter = '*'; + end; + if ~isfield(c,'num') + disp(c); warning(['No num field for "' c.name '"']); + c.num = Inf; + end; + if length(c.num)~=1 && length(c.num)~=2 + disp(c); warning(['Num field for "' c.name '" is wrong length']); + c.num = Inf; + end; + if isfield(c,'val') && iscell(c.val) && numel(c.val)>=1, + if ischar(c.val{1}) + c.val{1} = cellstr(c.val{1}); + end; + end; + if ~isfield(c,'help'), c.help = {'File selection'}; end; + +case {'branch'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'val') + disp(c); warning(['No val field for "' c.name '"']); + c.val = {}; + end; + + c.expanded = false; + if ~isfield(c,'help'), c.help = {'Branch structure'}; end; + +case {'choice'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'values') || ~iscell(c.values) + disp(c); error(['Bad values for "' c.name '"']); + end; + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; + if ~isfield(c,'val') || ~iscell(c.val) || length(c.val) ~= 1 + c.val = {c.values{1}}; + end; + c.expanded = true; + if ~isfield(c,'help'), c.help = {'Choice structure'}; end; + +case {'repeat'} + if ~isfield(c,'values') || ~iscell(c.values) + disp(c); error(['Bad values for "' c.name '"']); + end; + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; + if length(c.values)>1 && ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if length(c.values)==1 && isfield(c,'tag') + % disp(c); warning(['"' c.name '" has unused tag']); + c = rmfield(c,'tag'); + end; + c.expanded = true; + if ~isfield(c,'help'), c.help = {'Repeated structure'}; end; + + if isfield(c,'num') && numel(c.num)==1, + if finite(c.num), + c.num = [c.num c.num]; + else + c.num = [0 c.num]; + end; + end; + +end; + +if ~isfield(c,'val'), c.val = {}; end; + +%switch c.type +%case {'menu','entry','files'} +% %if isempty(c.val) +% if isfield(c,'def') +% c.val = getdef(c.def); +% if strcmp(c.type,'files') && ~isempty(c.val) +% c.val = {cellstr(c.val{1})}; +% end; +% end; +% %end; +%end; + +if isfield(c,'val') + for i=1:length(c.val) + c.val{i} = tidy_struct(c.val{i}); + end; +end; +if isfield(c,'values') && strcmp(c.type,'repeat') + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function job = fromfile(job) +if ischar(job) + [pth,nam,ext] = fileparts(job); + if strcmp(ext,'.xml') + spm('Pointer','Watch'); + try + loadxml(job,'jobs'); + catch + questdlg('LoadXML failed',job,'OK','OK'); + return; + end; + spm('Pointer'); + elseif strcmp(ext,'.mat') + try + load(job,'jobs'); + catch + questdlg('Load failed',job,'OK','OK'); + return; + end; + else + questdlg(['Unknown extension (' ext ')'],'Nothing loaded','OK','OK'); + return; + end; + job = jobs; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = hide_null_jobs(c) +c = hide_null_jobs1(c); +c = hide_null_jobs2(c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,flg] = hide_null_jobs1(c) +if ~isstruct(c) || ~isfield(c,'type'), + flg = true; + return; +end; + +if ~include(c), + flg = false; + c.hidden = true; + return; +end; + +switch c.type, +case {'repeat','branch','choice'}, + msk1 = true; + msk2 = true; + if isfield(c,'val') && ~isempty(c.val), + msk1 = true(1,numel(c.val)); + for i=1:length(c.val) + [c.val{i},msk1(i)] = hide_null_jobs1(c.val{i}); + end; + end; + if isfield(c,'values') && ~isempty(c.values), + msk2 = true(1,numel(c.values)); + for i=1:length(c.values) + [c.values{i},msk2(i)] = hide_null_jobs1(c.values{i}); + end; + end; + flg = any(msk1) || any(msk2); + if ~flg, c.hidden = true; end; +otherwise + flg = true; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = include(c) +% Check that the modality is OK +ok = true; +if isfield(c,'modality'), + mod = getdef('modality'); + if ~isempty(mod), + mod = mod{1}; + ok = false; + for i=1:length(c.modality), + if strcmpi(c.modality{i},mod), + ok = true; + return; + end; + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,flg] = hide_null_jobs2(c) +if ~isstruct(c) || ~isfield(c,'type') + flg = 0; + return; +end; +if isfield(c,'prog'), + flg = 1; + return; +end; + +switch c.type, +case {'repeat','branch','choice'}, + flg = 0; + msk1 = []; + msk2 = []; + if isfield(c,'val'), + msk1 = ones(1,numel(c.val)); + for i=1:length(c.val) + [c.val{i},msk1(i)] = hide_null_jobs2(c.val{i}); + end; + end; + if isfield(c,'values'), + msk2 = ones(1,numel(c.values)); + for i=1:length(c.values) + [c.values{i},msk2(i)] = hide_null_jobs2(c.values{i}); + end; + end; + if (sum(msk1) + sum(msk2))>0, flg = 1; end; + if ~flg, c.hidden = 1; end; +otherwise + flg = 0; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = job_to_struct(c,job,tag) +% Modify a structure based on a batch job +if isstruct(c) && isfield(c,'hidden'), + return; +end; +switch c.type +case {'const','menu','files','entry'} + if ~strcmp(gettag(c),tag), return; end; + if ischar(job) && strcmp(job,'') + c.val = {}; + else + c.val{1} = job; + end; + +case {'branch'} + if ~strcmp(gettag(c),tag), return; end; + if ~isstruct(job), return; end; + + tag = fieldnames(job); + for i=1:length(tag) + for j=1:length(c.val) + if strcmp(gettag(c.val{j}),tag{i}) + c.val{j} = job_to_struct(c.val{j},job.(tag{i}),tag{i}); + break; + end; + end; + end; + +case {'choice'} + if ~strcmp(gettag(c),tag), return; end; + if ~isstruct(job), return; end; + tag = fieldnames(job); + if length(tag)>1, return; end; + tag = tag{1}; + for j=1:length(c.values) + if strcmp(gettag(c.values{j}),tag) + c.val = {job_to_struct(c.values{j},job.(tag),tag)}; + end; + end; + +case {'repeat'} + if ~strcmp(gettag(c),tag), return; end; + if length(c.values)==1 && strcmp(c.values{1}.type,'branch') + if ~isstruct(job), return; end; + for i=1:length(job) + if strcmp(gettag(c.values{1}),tag) + c.val{i} = job_to_struct(c.values{1},job(i),tag); + c.val{i}.removable = true; + end; + end; + elseif length(c.values)>1 + if ~iscell(job), return; end; + for i=1:length(job) + tag = fieldnames(job{i}); + if length(tag)>1, return; end; + tag = tag{1}; + for j=1:length(c.values) + if strcmp(gettag(c.values{j}),tag) + c.val{i} = job_to_struct(c.values{j},job{i}.(tag),tag); + c.val{i}.removable = true; + break; + end; + end; + end; + else + if ~iscell(job), return; end; + for i=1:length(job) + c.val{i} = job_to_struct(c.values{1},job{i},tag); + c.val{i}.removable = true; + end; + end; + +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc(str,wid) +if nargin<1, str = ''; end; +if nargin<2, wid = 60; end; + +tmp = [0 find([str '.']=='.')]; +node = {}; +for i=1:length(tmp)-1, + tmp1 = str((tmp(i)+1):(tmp(i+1)-1)); + if ~isempty(tmp1), + node = {node{:},tmp1}; + end; +end; +if numel(node)>1 && strcmp(node{1},'jobs'), + node = node(2:end); +end; + +c = initialise_struct; +doc = showdoc1(node,c,wid); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc1(node,c,wid) +doc = {}; +if isempty(node), + doc = showdoc2(c,'',wid); + return; +end; + +if isfield(c,'values'), + for i=1:numel(c.values), + if isfield(c.values{i},'tag') && strcmp(node(1),c.values{i}.tag), + doc = showdoc1(node(2:end),c.values{i},wid); + return; + end; + end; +end; + +if isfield(c,'val'), + for i=1:numel(c.val), + if isfield(c.val{i},'tag') && strcmp(node(1),c.val{i}.tag), + doc = showdoc1(node(2:end),c.val{i},wid); + return; + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc2(c,lev,wid) +doc = {''}; +if ~isempty(lev) && sum(lev=='.')==1, + % doc = {doc{:},repmat('_',1,80),''}; +end; + +if isfield(c,'name'), + str = sprintf('%s %s', lev, c.name); + %under = repmat('-',1,length(str)); + doc = {doc{:},str}; + % if isfield(c,'modality'), + % txt = 'Only for '; + % for i=1:numel(c.modality), + % txt = [txt ' ' c.modality{i}]; + % end; + % doc = {doc{:},'',txt, ''}; + %end; + if isfield(c,'help'); + hlp = spm_justify(wid,c.help); + doc = {doc{:},hlp{:}}; + end; + + switch (c.type), + case {'repeat'}, + if length(c.values)==1, + doc = {doc{:}, '', sprintf('Repeat "%s", any number of times.',c.values{1}.name)}; + else + doc = {doc{:}, '', 'Any of the following options can be chosen, any number of times'}; + i = 0; + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.values{ii}.name)}; + end; + end; + end; + doc = {doc{:},''}; + + case {'choice'}, + doc = {doc{:}, '', 'Any one of these options can be selected:'}; + i = 0; + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.values{ii}.name)}; + end; + end; + doc = {doc{:},''}; + + case {'branch'}, + doc = {doc{:}, '', sprintf('This item contains %d fields:', length(c.val))}; + i = 0; + for ii=1:length(c.val), + if isstruct(c.val{ii}) && isfield(c.val{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.val{ii}.name)}; + end; + end; + doc = {doc{:},''}; + + case {'menu'}, + doc = {doc{:}, '', 'One of these values is chosen:'}; + for k=1:length(c.labels), + doc = {doc{:}, sprintf(' %2d) %s', k, c.labels{k})}; + end; + doc = {doc{:},''}; + + case {'files'}, + if length(c.num)==1 && isfinite(c.num(1)) && c.num(1)>=0, + tmp = spm_justify(wid,sprintf('A "%s" file is selected by the user.',c.filter)); + else + tmp = spm_justify(wid,sprintf('"%s" files are selected by the user.\n',c.filter)); + end; + doc = {doc{:}, '', tmp{:}, ''}; + + case {'entry'}, + switch c.strtype, + case {'e'}, + d = 'Evaluated statements'; + case {'n'}, + d = 'Natural numbers'; + case {'r'}, + d = 'Real numbers'; + case {'w'}, + d = 'Whole numbers'; + otherwise, + d = 'Values'; + end; + tmp = spm_justify(wid,sprintf('%s are entered.',d)); + doc = {doc{:}, '', tmp{:}, ''}; + end; + + i = 0; + doc = {doc{:},''}; + if isfield(c,'values'), + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + lev1 = sprintf('%s%d.', lev, i); + doc1 = showdoc2(c.values{ii},lev1,wid); + doc = {doc{:}, doc1{:}}; + end; + end; + end; + if isfield(c,'val'), + for ii=1:length(c.val), + if isstruct(c.val{ii}) && isfield(c.val{ii},'name'), + i = i+1; + lev1 = sprintf('%s%d.', lev, i); + doc1 = showdoc2(c.val{ii},lev1,wid); + doc = {doc{:}, doc1{:}}; + end; + end; + end; + doc = {doc{:}, ''}; +end; + + diff --git a/spm/spm5/spm_log2html.m b/spm/spm5/spm_log2html.m new file mode 100644 index 0000000..09ea46f --- /dev/null +++ b/spm/spm5/spm_log2html.m @@ -0,0 +1,154 @@ +function htmlfile = spm_log2html(prog, val, options) +%SPM_LOG2HTML - Log report on SPM processing to HTML file +% [] = spm_log2html(prog, val, options) print log to the html file named in output +% +% Example +% >> spm_log2html +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-17 Creation +% +% ----------------------------- Script History --------------------------------- + +% I guess there exists an xml -> html thingy I could use somewhere... + +prog_infos=functions(prog) +% jobname=sprintf('%s:', prog_infos.parentage{end:-1:1}); +% jobname(end)=[]; +jobname=sprintf('%s', prog_infos.parentage{1}); +logtxt={}; +logtxt{end+1}=['SPM logging for: ' jobname]; +htmlfile = fullfile(fileparts(getfield(spm_vol(val.data{1}{1}),'fname')),'log',[jobname '.html']); +logtxt{end+1}=['Into: ']; +logtxt{end+1}={'file' htmlfile}; +htmldir = fileparts(htmlfile); +% if exist(htmldir, 'dir') +% if length(dir(htmldir)) > 2 +% htmldir_old=fullfile(fileparts(htmldir), ['log_' datestr(now,30)]); +% movefile(htmldir,-) +% logtxt{end+1}=['Renaming older directory: ' ]; +% logtxt{end+1}={'folder', htmldir_old}; +% mkdir(htmldir) +% end +% end +if not(exist(htmldir, 'dir')) + logtxt{end+1}=['Creating new directory: ' ]; + logtxt{end+1}={'folder', htmldir}; + mkdir(htmldir) +end + +switch jobname + case 'estimate' + logtxt=log_realign(val,htmldir,logtxt); + case 'reslice'; + % to do + case 'estwrite_fun'; + % to do + otherwise + logtxt{end+1}=['Unknown function to log: ' jobname]; +end +log2html(htmlfile,logtxt) +return + +function [spname]=shortpathname(pname) +% shortens file names +spname=[pname(1:10) '...' pname(end-15:end)]; + +function [hpname]=htmlpathname(pname) +% Replace filesep in file path with slashes (/) for HTML compatibility +hpname = strrep(pname,filesep,'/'); + +function []=log2html(htmlfile, log) +% print out to html file +save(fullfile(fileparts(htmlfile),'spm_log2html.mat'),'log'); +fid=fopen(htmlfile,'wt'); +html_header(fid); +fprintf(fid,'

      '); +for i=1:length(log); + if ischar(log{i}) + if i>1 + fprintf(fid, '

      \n

      '); + end + fprintf(fid, '%s', log{i}); + else + switch log{i}{1} + case 'picture' + fprintf(fid, '',htmlpathname(log{i}{2}),htmlpathname(log{i}{2}),shortpathname(log{i}{2})); + case {'folder' 'file'} + fprintf(fid, '%s',htmlpathname(log{i}{2}),shortpathname(log{i}{2})); + end + end +end +fprintf(fid,'Done.

      \n\n'); +if fid > 2 + fclose(fid); + try + browser = '"C:\Documents and Settings\ndiayek\Local Settings\Application Data\Google\Chrome\Application\chrome.exe"' + system([browser ' "' htmlfile '"']); + catch + browser = '"C:\program Files\Mozilla Firefox\firefox.exe" '; + end; +end +return + +function [logtxt]=html_header(fid) +fprintf(fid,'\n'); +fprintf(fid,'\n'); +fprintf(fid,'

      Processing steps:

        '); +fprintf(fid,'
      1. realign'); +fprintf(fid,'
      2. segment'); +fprintf(fid,'
      3. normalize'); +fprintf(fid,'
      4. smooth'); +fprintf(fid,'
      5. design'); +fprintf(fid,'

      '); + + + +function [logtxt]=html_footer(htmlfile, logtxt) + + + +function [logtxt] = log_design(val,htmldir,logtxt) +% Log of DESIGN results + + +function [logtxt] = log_realign(val,htmldir,logtxt) +% Log of REALIGN results +mfile = which('spm_realign'); +if ~isequal(textread(mfile,'%s',4,'headerlines',82,'delimiter',' '),... + {'%', '$Id:', 'spm_realign.m', '433'}') % The native version at the time + logtxt{end+1}=sprintf('The spm_realign.m (%s) has changed! Default flags may also have changed.', mfile); + warning(logtxt(1)); +end +def_flags = struct('quality',1,'fwhm',5,'sep',4,'interp',2,'wrap',[0 0 0],'rtm',0,'PW','','graphics',1,'lkp',1:6); +flags =mergestructs(def_flags,val.eoptions); +if flags.graphics + opts = {fullfile(htmldir,'realign_estimate.png'),'-noui','-painters','-dpng'}; + fg = spm_figure('FindWin','Graphics'); + logtxt{end+1} = {'Plot of the Movement Parameters'}; + % export figure in image file + print(fg,opts{:}); + logtxt{end+1} = {'picture','realign_estimate.png'}; +else + logtxt{end+1}='Graphics must be generated for logging. Sorry...'; + % rp_file = [spm_str_manip(prepend(getfield(spm_vol(val.data{1}{1}),'fname'),'rp_'),'s') '.txt']; + % P=textread(rp_file); + % plot_parameters(P) +end +return + + +function [logtxt] = log_smooth(val,htmldir,logtxt) +% Log of SMOOTH results +mfile = which('spm_smooth'); +logtxt(end+1)='todo'; +return diff --git a/spm/spm5/spm_vol.m b/spm/spm5/spm_vol.m new file mode 100644 index 0000000..ddd3179 --- /dev/null +++ b/spm/spm5/spm_vol.m @@ -0,0 +1,185 @@ +function V = spm_vol(P) +% Get header information etc for images. +% FORMAT V = spm_vol(P) +% P - a matrix of filenames. +% V - a vector of structures containing image volume information. +% The elements of the structures are: +% V.fname - the filename of the image. +% V.dim - the x, y and z dimensions of the volume +% V.dt - A 1x2 array. First element is datatype (see spm_type). +% The second is 1 or 0 depending on the endian-ness. +% V.mat - a 4x4 affine transformation matrix mapping from +% voxel coordinates to real world coordinates. +% V.pinfo - plane info for each plane of the volume. +% V.pinfo(1,:) - scale for each plane +% V.pinfo(2,:) - offset for each plane +% The true voxel intensities of the jth image are given +% by: val*V.pinfo(1,j) + V.pinfo(2,j) +% V.pinfo(3,:) - offset into image (in bytes). +% If the size of pinfo is 3x1, then the volume is assumed +% to be contiguous and each plane has the same scalefactor +% and offset. +%____________________________________________________________________________ +% +% The fields listed above are essential for the mex routines, but other +% fields can also be incorporated into the structure. +% +% The images are not memory mapped at this step, but are mapped when +% the mex routines using the volume information are called. +% +% Note that spm_vol can also be applied to the filename(s) of 4-dim +% volumes. In that case, the elements of V will point to a series of 3-dim +% images. +% +% This is a replacement for the spm_map_vol and spm_unmap_vol stuff of +% MatLab4 SPMs (SPM94-97), which is now obsolete. +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_vol.m 504 2006-04-25 13:44:50Z volkmar $ + +if nargin==0, + V = struct('fname', {},... + 'dim', {},... + 'dt', {},... + 'pinfo', {},... + 'mat', {},... + 'n', {},... + 'descrip', {},... + 'private',{}); + return; +end; + +% If is already a vol structure then just return; +if isstruct(P), V = P; return; end; +try + V = subfunc2(P); +catch + P=myspm_updatepath(P); + V = subfunc2(P); +end +return; + +function V = subfunc2(P) +if iscell(P), + V = cell(size(P)); + for j=1:numel(P), + try + if iscell(P{j}), + V{j} = subfunc2(P{j}); + else + V{j} = subfunc1(P{j}); + end; + catch + % Handling of files being moved around... + persistent pwd + if ~isempty(pwd) + end +warning('Not found: %s\n Try changing filesep...', P{j}) + P{j} = translocate(P{j}); + if iscell(P{j}), + V{j} = subfunc2(P{j}); + else + V{j} = subfunc1(P{j}); + end; + warning('ok! filesep has been changed in %s', P{j}) + end + end; +else + try + V = subfunc1(P); + catch + V = subfunc1(translocate(P)); + warning('ok! filesep has been changed in %s', P) + end +end; +return; + +function Q=translocate(P) +% from Linux to Win & vice-versa. +if isunix + Q = strrep(P, '\', filesep); +else + Q = strrep(P, '/', filesep); +end +return + +function V = subfunc1(P) +if isempty(P), + V = []; + return; +end; + +counter = 0; +for i=1:size(P,1), + v = subfunc(P(i,:)); + [V(counter+1:counter+size(v, 2),1).fname] = deal(''); + [V(counter+1:counter+size(v, 2),1).mat] = deal([0 0 0 0]); + [V(counter+1:counter+size(v, 2),1).mat] = deal(eye(4)); + [V(counter+1:counter+size(v, 2),1).mat] = deal([1 0 0]'); + if isempty(v), + hread_error_message(P(i,:)); + error(['Can''t get volume information for ''' P(i,:) '''']); + end + + f = fieldnames(v); + for j=1:size(f,1) + eval(['[V(counter+1:counter+size(v,2),1).' f{j} '] = deal(v.' f{j} ');']); + end + counter = counter + size(v,2); +end + +return; + +function V = subfunc(p) +V = []; +p = deblank(p); +[pth,nam,ext] = fileparts(deblank(p)); +t = find(ext==','); + +n = []; +if ~isempty(t), + t = t(1); + n1 = ext((t+1):end); + if ~isempty(n1), + n = str2num(n1); + ext = ext(1:(t-1)); + end; +end; +p = fullfile(pth,[nam ext]); + +if strcmpi(ext,'.nii') || (strcmpi(ext,'.img') && ... + (exist(fullfile(pth,[nam '.hdr']),'file') || exist(fullfile(pth,[nam '.HDR']),'file'))), + if isempty(n), V = spm_vol_nifti(p); + else V = spm_vol_nifti(p,n); end; + + if isempty(n) && length(V.private.dat.dim) > 3 + V0(1) = V; + for i = 2:V.private.dat.dim(4) + V0(i) = spm_vol_nifti(p, i); + end + V = V0; + end + + if ~isempty(V), return; end; + +else % Try other formats + error('%s: Unknown file format.',p); +end; +return; + + +%_______________________________________________________________________ +function hread_error_message(q) + +str = {... + 'Error reading information on:',... + [' ',spm_str_manip(q,'k40d')],... + ' ',... + 'Please check that it is in the correct format.'}; + +spm('alert*',str,mfilename,sqrt(-1)); + +return; +%_______________________________________________________________________ diff --git a/spm/spm_check_realign.m b/spm/spm_check_realign.m new file mode 100644 index 0000000..0d8c4e4 --- /dev/null +++ b/spm/spm_check_realign.m @@ -0,0 +1,109 @@ +function varargout = spm_check_realign(SPM) +%SPM_CHECK_REALIGN - One line description goes here. +% [] = spm_check_realign(SPM) +% +% Example +% >> spm_check_realign +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-13 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + SPM=uigetpathfile('rp*.txt'); +end +if ischar(SPM) + if exist(SPM,'file') + SPM=load(SPM); + elseif exist(SPM,'dir') + SPM=load(fullfile(SPM, 'SPM.mat')); + else + error('Unknown file/directory: %s', SPM); + end +end +if isstruct(SPM) + if isfield(SPM,'SPM') + SPM=SPM.SPM; + end + lcd=pwd; + try;cd(SPM.swd);end + [p,f,e]=fileparts(SPM.xY.VY(1).fname); + try + P=load(fullfile(p, 'rp_f_0001.txt')); + catch + try + P=load(fullfile(fileparts(p), 'rp_f_0001.txt')); + catch + error('Can''t find rp_*.txt'); + end + end +elseif size(SPM,2)==6 + P=SPM; +else + error('Wrong type of data') +end +[ax]=plot_parameters2(P); +if nargout>0 + varargout={P,ax}; +end + +% Adapted from spm_realign.m/plot_parameters (SPM2) +%_______________________________________________________________________ +function ax=plot_parameters2(Params) +if iscell(Params) + Params = cat(1,Params{:}); +end +if length(Params)<2, return; end; + +% +% for i=1:numel(P), +% Params(i,:) = spm_imatrix(P(i).mat/P(1).mat); +% end + +% display results +% translation and rotation over time series +%------------------------------------------------------------------- +% spm_figure('Clear','Graphics'); +fg=gcf; +set(fg,'Name','Image realignment'); +%ax=axes('Position',[0.1 0.65 0.8 0.2])%,'Parent',fg,'Visible','off'); +% set(get(ax,'Title'),'String','Image realignment (check)','FontSize',16,'FontWeight','Bold','Visible','on'); +%x = 0.1; +%y = 0.9; +% for i = 1:min([numel(P) 12]) +% text(x,y,[sprintf('%-4.0f',i) ],'FontSize',10,'Interpreter','none','Parent',ax); +% y = y - 0.08; +% end +% if numel(P) > 12 +% text(x,y,'................ etc','FontSize',10,'Parent',ax); end + +ax(1)=subplot(2,1,1,'Parent',fg,'XGrid','on','YGrid','on'); +hp=plot(Params(:,1:3),'Parent',ax(1)); +s = {'x translation' 'y translation' 'z translation'}; +%text([2 2 2], Params(2, 1:3), s, 'Fontsize',10,'Parent',ax) +set(get(ax(1),'Title'),'String','translation','FontSize',16,'FontWeight','Bold'); +%set(get(ax,'Xlabel'),'String','image'); +set(get(ax(1),'Ylabel'),'String','mm'); +legend(hp, s, 0) + +%ax=axes('Position',[0.1 0.05 0.8 0.2],'Parent',fg,'XGrid','on','YGrid','on'); +ax(2)=subplot(2,1,2,'Parent',fg,'XGrid','on','YGrid','on'); +hp=plot(Params(:,4:6)*180/pi,'Parent',ax(2)); +s = {'pitch';'roll ';'yaw '}; +%text([2 2 2], Params(2, 4:6)*180/pi, s, 'Fontsize',10,'Parent',ax) +set(get(ax(2),'Title'),'String','rotation','FontSize',16,'FontWeight','Bold'); +set(get(ax(2),'Xlabel'),'String','image'); +set(get(ax(2),'Ylabel'),'String','degrees'); +legend(hp, s, 0) +return; +%_______________________________________________________________________ diff --git a/spm/spm_log2html/spm_jobman.m b/spm/spm_log2html/spm_jobman.m new file mode 100644 index 0000000..1baf882 --- /dev/null +++ b/spm/spm_log2html/spm_jobman.m @@ -0,0 +1,2934 @@ +function varargout = spm_jobman(varargin) +% UI/Batching stuff +%_______________________________________________________________________ +% This code is based on an earlier version by Philippe Ciuciu and +% Guillaume Flandin of Orsay, France. +% +% FORMAT spm_jobman +% spm_jobman('interactive') +% spm_jobman('interactive',job) +% spm_jobman('interactive',job,node) +% spm_jobman('interactive','',node) +% Runs the user interface in interactive mode. +% +% FORMAT spm_jobman('serial') +% spm_jobman('serial',job) +% spm_jobman('serial',job,node) +% spm_jobman('serial','',node) +% Runs the user interface in serial mode. +% +% FORMAT spm_jobman('run',job) +% Runs a job. +% +% FORMAT spm_jobman('help',node) +% spm_jobman('help',node,width) +% Creates a cell array containing help information. This is justified +% to be 'width' characters wide. e.g. +% h = spm_jobman('help','jobs.spatial.coreg.estimate'); +% for i=1:numel(h),fprintf('%s\n',h{i}); end; +% +% node - indicates which part of the configuration is to be used. +% For example, it could be 'jobs.spatial.coreg'. +% +% job - can be the name of a jobfile (as a .mat or a .xml), or a +% 'jobs' variable loaded from a jobfile. +% +% +% FORMAT spm_jobman('defaults') +% Runs the interactive defaults editor. +% +% FORMAT spm_jobman('pulldown') +% Creates a pulldown 'TASKS' menu in the Graphics window. +% +% FORMAT spm_jobman('chmod') +% Changes the modality for the TASKS pulldown. +% +% FORMAT [tag,dat] = spm_jobman('harvest',c) +% Take a data structure, and extract what is needed to save it +% as a batch job (for experts only). +% +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% John Ashburner +% $Id: spm_jobman.m 639 2006-09-28 17:09:17Z volkmar $ + + +if nargin==0 + setup_ui; +else + switch lower(varargin{1}) + case {'interactive'} + if nargin>=2 + setup_ui(varargin{2:nargin}); + else + setup_ui; + end; + + case {'serial'} + if nargin>=2, + serial(varargin{2:nargin}); + else + serial; + end; + + case {'run'} + if nargin<2 + error('Nothing to run'); + end; + run_job(varargin{2}); + + case {'defaults'}, + setup_ui('defaults'); + + case {'pulldown'} + pulldown; + + case {'chmod'} + if nargin>1, + chmod(varargin{2}); + end; + + case {'help'} + if nargin>=2, + varargout{1} = showdoc(varargin{2:nargin}); + else + varargout{1} = showdoc; + end; + + case {'harvest'} + [varargout{1:nargout}] = harvest(varargin{2:nargin}); + + otherwise + error(['"' varargin{1} '" - unknown option']); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function defaults_edit(varargin) +setup_ui('defaults'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function interactive(varargin) +ud = get(varargin{1},'UserData'); +if iscell(ud) + setup_ui(ud{:}); +else + setup_ui; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function setup_ui(varargin) +% Configure the user interface + +fg = clearwin; +fs = getdef('ui.fs'); +if numel(fs)~=1 || ~isnumeric(fs{1}) || numel(fs{1})~=1, + fs = 12; +else + fs = fs{1}; +end; + +col1 = getdef('ui.colour1'); +if numel(col1)~=1 || ~isnumeric(col1{1}) || numel(col1{1})~=3, + col1 = [0.8 0.8 1]; +else + col1 = col1{1}; +end; + +col2 = getdef('ui.colour2'); +if numel(col2)~=1 || ~isnumeric(col2{1}) || numel(col2{1})~=3, + col2 = [1 1 0.8]; +else + col2 = col2{1}; +end; + +col3 = getdef('ui.colour3'); +if numel(col3)~=1 || ~isnumeric(col3{1}) || numel(col3{1})~=3, + col3 = [0 0 0]; +else + col3 = col3{1}; +end; + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.02 0.31 0.48 0.67],... + 'Callback',@click_batch_box,... + 'Tag','batch_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'FontSize',fs,... + 'Value',1); +c0 = cntxtmnu(t); +c1 = uimenu('Label','Exp/Con All', 'Parent',c0); +uimenu('Label','Expand All', 'Parent',c1,'Callback',@expandall); +uimenu('Label','Contract All', 'Parent',c1,'Callback',@contractall); +uimenu('Label','Expand All Undefined Inputs', 'Parent',c1,'Callback',@expandallopen); + +t=uicontrol(fg,... + 'Style','listbox',... + 'ListBoxTop',1,... + 'Units','normalized',... + 'Position',[0.02 0.02 0.96 0.28],... + 'Tag','help_box',... + 'FontName','fixedwidth',... + 'FontSize',fs,... + 'ForegroundColor', col3,... + 'BackgroundColor',col2); +set(t,'Value',[], 'Enable', 'inactive', 'Max',2, 'Min',0); +workaround(t); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.74 0.47 0.24],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'FontSize',fs,... + 'Tag','opts_box'); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.49 0.47 0.24],... + 'Tag','val_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col2,... + 'Enable', 'inactive',... + 'Value',[],... + 'FontSize',fs,... + 'Max',2, 'Min',0); +set(t,'Value',[], 'Enable', 'on', 'Max',2, 'Min',0,'ListBoxTop',1); +cntxtmnu(t); + +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.51 0.38 0.47 0.10],... + 'Tag','msg_box',... + 'ForegroundColor', col3,... + 'BackgroundColor',col2,... + 'Enable', 'inactive',... + 'Value',[],... + 'FontSize',fs,... + 'Max',2, 'Min',0); +cntxtmnu(t); + +if ~(nargin==1 && ischar(varargin{1}) && strcmp(varargin{1},'defaults')), + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.51 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Save',... + 'Callback',@save_job,... + 'FontSize',fs,... + 'Tag','save'); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.67 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Load',... + 'Callback',@load_job,... + 'FontSize',fs,... + 'Tag','load'); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.83 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Run',... + 'Callback',@run_struct,... + 'Tag','run',... + 'FontSize',fs,... + 'Enable', 'off'); + cntxtmnu(t); + if nargin>0 + initialise(varargin{:}); + else + initialise; + end; +else + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.51 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','OK',... + 'FontSize',fs,... + 'Callback',@ok_defaults); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.67 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Reset',... + 'FontSize',fs,... + 'Callback',@reset_defaults); + cntxtmnu(t); + + t=uicontrol(fg,... + 'style','pushbutton',... + 'units','normalized',... + 'Position',[0.83 0.31 0.15 0.06],... + 'ForegroundColor', col3,... + 'BackgroundColor',col1,... + 'String','Cancel',... + 'FontSize',fs,... + 'Callback',@clearwin); + cntxtmnu(t); + initialise('defaults'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok_defaults(varargin) +harvest_def(get(batch_box,'UserData')); +clearwin; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function reset_defaults(varargin) +global defaults + +modality = []; +if isfield(defaults,'modality'), + modality = defaults.modality; +end; +spm_defaults; +if ~isfield(defaults,'modality') && ~isempty(modality), + defaults.modality = modality; +end; +pulldown; +clearwin; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function fg = clearwin(varargin) + +fg = spm_figure('findwin','Graphics'); +if isempty(fg), fg = spm_figure('Create','Graphics'); end; +delete(findobj(fg,'Parent',fg)); +delete(batch_box); +delete(opts_box); +spm('Pointer'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function expandall(varargin) +c = expcon(get(gco,'UserData'),1); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function contractall(varargin) +c = expcon(get(gco,'UserData'),0); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function expandallopen(varargin) +c = expopen(get(gco,'UserData')); +str = get_strings(c); +val = min(get(gco,'Value'),length(str)); +set(gco,'String',str,'Value',val,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,sts] = expopen(c) +sts = 0; +if isfield(c,'expanded'), + sts=~all_set(c); +end; +if isfield(c,'val'), + for i=1:length(c.val), + [c.val{i} sts1] = expopen(c.val{i}); + sts = sts||sts1; + end; +end; +if isfield(c,'expanded') + c.expanded = sts; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = expcon(c,val) +if isfield(c,'expanded'), c.expanded = val; end; +if isfield(c,'val'), + for i=1:length(c.val), + c.val{i} = expcon(c.val{i},val); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function initialise(job,node) +% load the config file, possibly adding a job +% to it, and generally tidy it up. The batch box +% is updated to contain the current structure. +files_select_list('init'); +if nargin<1, job = ''; end; +if nargin<2, node = 'jobs'; end; +c = initialise_struct(job); +set(batch_box,'UserData',start_node(c,node)); +update_ui; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_job(job) +% Run a job. This function is not called via the UI. +c = initialise_struct(job); +if all_set(c), + run_struct1(c); +else + error('This job is not ready yet'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function click_batch_box(varargin) +% Called when the batch box is clicked + +remove_string_box; +if strcmp(get(get(varargin{1},'Parent'),'SelectionType'),'open') + run_in_current_node(@expand_contract,false); + str = get_strings(get(batch_box,'UserData')); + val = min(get(batch_box,'Value'),length(str)); + set(batch_box,'String',str,'Value',val); +else + run_in_current_node(@click_batch_box_fun,false); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function update_ui +[str,sts] = get_strings(get(batch_box,'UserData')); +val = min(get(batch_box,'Value'),length(str)); +set(batch_box,'String',str,'Value',val); +run_in_current_node(@click_batch_box_fun,false); + +run_but = findobj(0,'Tag','run'); +if sts + set(run_but,'Enable', 'on'); +else + set(run_but,'Enable', 'off'); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [str,sts] = get_strings(c) +[unused,str,sts] = start_node(c,@get_strings1,0); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,str,sts] = get_strings1(c,l) +% Return the cell vector of strings displayed in the batch +% box, and also whether the job is runable. This is a recursive +% function that a branch of the data structure is passed to. + +if isfield(c,'hidden'), + sts = 1; + str = ''; + return; +end; + +sts = 1; +mrk = ' '; +nam = ''; +if isfield(c,'datacheck') && ~isempty(c.datacheck), + mrk = ' <-@'; + sts = 0; +end; +if isfield(c,'name'), nam = c.name; end; + +if isfield(c,'expanded') % && isfield(c,'val') && ~isempty(c.val) + + if strcmp(c.type,'repeat') && isfield(c,'num') + sts = (length(c.val) >= c.num(1)) &&... + (length(c.val) <= c.num(2)); + if ~sts + mrk = ' <-X'; + end; + end; + + if c.expanded + str = {[repmat('. ',1,l) '-' nam]}; + for i=1:length(c.val) + [c.val{i},str1,sts1] = get_strings1(c.val{i},l+1); + sts = sts && sts1; + if ~isempty(str1), + str = {str{:},str1{:}}; + end; + end; + else + str = {[repmat('. ',1,l) '+' nam]}; + for i=1:length(c.val) + [c.val{i},unused,sts1] = get_strings1(c.val{i},l+1); + sts = sts && sts1; + end; + if ~sts, + mrk = ' <-X'; + end; + end; + str{1} = [str{1} mrk]; +else + switch c.type + case 'files' + % If files are selected via "Input to/Output from" shortcuts, + % there is no guarantee that an allowed number of files is + % specified. This is checked here. + cn = c.num; + if (numel(cn) == 1) + if isfinite(cn) + cn = [cn cn]; + else + cn = [0 cn]; + + end; + end; + if isempty(c.val) || (numel(c.val{1}) < cn(1)) || ... + (numel(c.val{1}) > cn(2)) + mrk = ' <-X'; + sts = 0; + end; + case {'menu','entry','const','choice'} + if isempty(c.val) + mrk = ' <-X'; + sts = 0; + end; + case 'repeat' % don't know, whether this ever gets executed + if isfield(c,'num') + sts = (length(c.val) >= c.num(1)) &&... + (length(c.val) <= c.num(2)); + if ~sts + mrk = ' <-X'; + end; + end; + end; + str = {[repmat('. ',1,l) ' ' nam mrk]}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = all_set(c) +% Return whether all the necessary fields have been filled in. +% This is a recursive function that a branch of the data structure +% is passed to. + +if isfield(c,'hidden'), + ok = true; + return; +end; + +ok = true; + +switch c.type +case {'files','menu','entry','const','choice'} + if isempty(c.val) + ok = false; + end; + +case {'branch','repeat'} + if strcmp(c.type,'repeat') && isfield(c,'num') + ok = ok && (length(c.val) >= c.num(1)) && ... + (length(c.val) <= c.num(2)); + end; + if ok, + for i=1:length(c.val), + ok1 = all_set(c.val{i}); + ok = ok && ok1; + if ~ok, break; end; + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function click_options_box(varargin) +% The function called when the options box is clicked + +dat = get(opts_box,'UserData'); +if ~isempty(dat) + fun = dat{get(opts_box,'Value')}; + run_in_current_node(fun.fun,true,fun.args{:}); + if fun.redraw, update_ui; end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function varargout = run_in_current_node(varargin) +% Get the current node, and run a job in it +varargout = {}; +c = get(batch_box,'UserData'); +n = get(batch_box,'Value'); +show_msg(''); +va = {c,@run_in_current_node1,n,varargin{:}}; +[c,unused,varargout{:}] = start_node(va{:}); +set(batch_box,'UserData',c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,varargout] = start_node(c,fun,varargin) +persistent node; +if isempty(node) + node = {'jobs'}; +end; +varargout = {}; +if nargin==2 + tmp = [0 find([fun '.']=='.')]; + node = {}; + for i=1:length(tmp)-1 + node = {node{:},fun((tmp(i)+1):(tmp(i+1)-1))}; + end; + c = make_nodes(c,node); + return; +end; +va = {c,node,fun,varargin{:}}; +[c,unused,varargout{1:nargout-1}] = start_node1(va{:}); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = make_nodes(c,node) +if isfield(c,'tag') && ~strcmp(gettag(c),node{1}) + return; +end; +if isfield(c,'tag') + node = {node{2:end}}; + if isempty(node), return; end; +end; +if isfield(c,'values') && (~isfield(c,'val') ||... + isempty(c.val) || ~iscell(c.val) ||... + ~strcmp(gettag(c.val{1}),node{1})) + for i=1:length(c.values) + if strcmp(gettag(c.values{i}),node{1}) + c.val = {c.values{i}}; + c.val{1} = make_nodes(c.val{1},node); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,sts,varargout] = start_node1(c,node,fun,varargin) +varargout = {}; +if nargin<4, varargin = {}; end; +if isfield(c,'tag') && ~strcmp(gettag(c),node{1}) + varargout = cell(1,nargout-2); + sts = 0; + return; +end; +if isfield(c,'tag'), + node = {node{2:end}}; +end; +if isempty(node) + [c,varargout{1:nargout-2}] = feval(fun,c,varargin{:}); + sts = 1; + return; +end; +if isfield(c,'val'), + for i=1:length(c.val) + [c.val{i},sts,varargout{1:nargout-2}] = start_node1(c.val{i},node,fun,varargin{:}); + if sts, return; end; + end; +end; +keyboard +error('No such node'); % Should never execute +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,n,varargout] = run_in_current_node1(c,n,fun,modify,varargin) +% Satellite for run_in_current_node + +varargout = {}; +if nargin<5, varargin = {}; end; +if isfield(c,'hidden'), return; end; + +n = n-1; +if n<0, return; end; +if n==0, + if ~isfield(c,'datacheck'), + show_msg(''); + else + show_msg(c.datacheck); + end; + [c,varargout{:}] = feval(fun,c,varargin{:}); +end; + +if isfield(c,'expanded') && ~isempty(c.val) + if c.expanded, + val = c.val; + c.val = {}; + for i=1:length(val) + [tmp,n,varargout{:}] = run_in_current_node1(val{i},n,fun,modify,varargin{:}); + if ~isempty(tmp) + if iscell(tmp) + c.val = {c.val{:}, tmp{:}}; + else + c.val = {c.val{:}, tmp}; + end; + end; + end; + if modify && isfield(c,'check'), + if all_set(c), + [unused,val] = harvest(c); + c.datacheck = feval(c.check,val); + end; + end; + if isfield(c,'datacheck') && ~isempty(c.datacheck), + show_msg(c.datacheck); + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = click_batch_box_fun(c,unused) +% Mostly set up the options box, but also update the help and value boxes + +if ~isempty(opts_box) + dat = {}; + str = {}; + + switch c.type + case {'const'} + % do nothing + + case {'files'} + spm('pointer','watch'); + str = {str{:}, 'Specify Files'}; + dat = {dat{:}, struct('fun',@file_select,'args',{{}},'redraw',1)}; + addvfiles(c.id,[],c); + addinfiles(c); + [filestr filedat] = files_select_list('listall'); + str = {str{:}, filestr{:}}; + dat = {dat{:}, filedat{:}}; + spm('pointer','arrow'); + + case {'menu'} + str = {str{:}, 'Specify Menu Item'}; + dat = {dat{:}, struct('fun',@menu_entry,'args',{{}},'redraw',0)}; + + case {'entry'} + str = {str{:}, 'Specify Text'}; + dat = {dat{:}, struct('fun',@text_entry,'args',{{}},'redraw',1)}; + + case {'branch','choice','repeat'} + if strcmp(c.type,'repeat') + for i=1:length(c.values) + if ~isfield(c.values{i},'hidden'), + str = {str{:},['New "' c.values{i}.name '"']}; + dat = {dat{:}, struct('fun',@series,'args',{{c.values{i}}},'redraw',1)}; + end; + end; + + elseif strcmp(c.type,'choice') + for i=1:length(c.values) + if ~isfield(c.values{i},'hidden'), + str = {str{:},['Choose "' c.values{i}.name '"']}; + dat = {dat{:}, struct('fun',@choose,'args',{{c.values{i}}},'redraw',1)}; + end; + end; + end; + end; + + if isfield(c,'removable') + str = {str{:},['Remove Item "' c.name '"'],['Replicate Item "' c.name '"']}; + dat = {dat{:}, struct('fun',@remove,'args',{{}},'redraw',1),... + struct('fun',@replicate,'args',{{}},'redraw',1)}; + end; + + if ~same(get(opts_box,'String')',str) + val = 1; + else + val = get(opts_box,'Value'); + end; + val = max(min(length(str),val),min(1,length(str))); + set(opts_box,'String',str,'UserData',dat,'Callback',@click_options_box,'Value',val); +end; + +show_value(c); + +% Update help +txt = ''; +if isfield(c,'help'), txt = c.help; end; +help_box = findobj(0,'tag','help_box'); +if ~isempty(help_box) + set(help_box,'String',' '); + workaround(help_box); + ext = get(help_box,'Extent'); + pos = get(help_box,'position'); + pw = floor(pos(3)/ext(3)*21-4); + set(help_box,'String',spm_justify(help_box,txt)); + workaround(help_box); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = expand_contract(c,unused) +% Expand/contract a node (for visualisation) + +if isfield(c,'expanded') && ~isempty(c.val) + if c.expanded + c.expanded = false; + else + c.expanded = true; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = menu_entry(c,unused) +% Setup opts box for menu entry + +if isfield(c,'labels') && isfield(c,'values') + str = {}; + dat = {}; + if ~isempty(c.val) + val = c.val{1}; + else + val = ''; + end; + dv = 1; + for i=1:length(c.values) + if ~(ischar(val) && strcmp(val,'')) && same(c.values{i},val) + str{i} = ['* ' c.labels{i}]; + dv = i; + else + str{i} = [' ' c.labels{i}]; + end; + dat{i} = struct('fun',@menuval,'args',{{c.values{i}}},'redraw',1); + end; + set(opts_box,'String',str,'UserData',dat,'Callback',@click_options_box,'Value',dv); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c] = file_select(c) +% Select files +try + set(batch_box,'Enable', 'inactive'); + set(opts_box, 'Enable', 'inactive'); + + if ~isempty(c.val), + sel = c.val{1}; + else + sel = ''; + end; + if isfield(c,'dir'), + dr = c.dir; + else + dr = pwd; + end; + if isfield(c,'ufilter') + uf = c.ufilter; + else + uf = '.*'; + end; + [s,ok] = spm_select(c.num,c.filter,c.name,sel,dr,uf); + if ok, c.val{1} = cellstr(s); end; + files_select_list('addinfiles', sprintf('Input to "%s"', c.name), ... + c.val{1}, c.id); +catch +end; +spm_select('clearvfiles'); +set(batch_box,'Enable', 'on'); +set(opts_box, 'Enable', 'on'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = text_entry(c) +% Create a string box and prompt, while hiding the opts box + +opts_box = findobj(gcf,'tag','opts_box'); +pos = get(opts_box,'Position'); +set(opts_box,'Visible','off'); +fs = get(opts_box,'FontSize'); +fa = get(opts_box,'FontAngle'); +fw = get(opts_box,'FontWeight'); +clf = get(opts_box,'ForegroundColor'); +clb = get(opts_box,'BackgroundColor'); + +n = []; +m = []; +if isfield(c,'num'), n = c.num; end; +if isfield(c,'extras'), m = c.extras; end; + +newstring = uicontrol(gcf,... + 'Style','edit',... + 'Units','normalized',... + 'Position',[pos(1:3) pos(4)/2],... + 'Tag','string_box',... + 'HorizontalAlignment','left',... + 'FontSize',fs,... + 'FontAngle',fa,... + 'FontWeight',fw,... + 'ForegroundColor',clf,... + 'BackgroundColor',clb,... + 'Callback',@accept_string); +cntxtmnu(newstring); + +strM=''; +switch lower(c.strtype) +case 's', TTstr='enter string'; +case 'e', TTstr='enter expression - evaluated'; +case 'n', TTstr='enter expression - natural number(s)'; + if ~isempty(m), strM=sprintf(' (in [1,%d])',m); TTstr=[TTstr,strM]; end +case 'w', TTstr='enter expression - whole number(s)'; + if ~isempty(m), strM=sprintf(' (in [0,%d])',m); TTstr=[TTstr,strM]; end +case 'i', TTstr='enter expression - integer(s)'; +case 'r', TTstr='enter expression - real number(s)'; + if ~isempty(m), TTstr=[TTstr,sprintf(' in [%g,%g]',min(m),max(m))]; end +case 'c', TTstr='enter indicator vector e.g. 0101... or abab...'; + if ~isempty(m) && isfinite(m), strM=sprintf(' (%d)',m); end +otherwise, TTstr='enter expression'; +end + +if isempty(n), n=NaN; end +n=n(:); if length(n)==1, n=[n,1]; end; dn=length(n); +if any(isnan(n)) || (prod(n)==1 && dn<=2) || (dn==2 && min(n)==1 && isinf(max(n))) + str = ''; + lstr = ''; +elseif dn==2 && min(n)==1 + str = sprintf('[%d]',max(n)); + lstr = [str,'-vector: ']; +elseif dn==2 && sum(isinf(n))==1 + str = sprintf('[%d]',min(n)); + lstr = [str,'-vector(s): ']; +else + str=''; + for i = 1:dn, + if isfinite(n(i)), + str = sprintf('%s,%d',str,n(i)); + else + str = sprintf('%s,*',str); + end + end + str = ['[',str(2:end),']']; + lstr = [str,'-matrix: ']; +end +strN = sprintf('%s',lstr); +col = get(gcf,'Color'); +uicontrol(gcf,'Style','text',... + 'Units','normalized',... + 'BackgroundColor',col,... + 'String',[strN,strM,TTstr],... + 'Tag','string_prompt',... + 'HorizontalAlignment','Left',... + 'FontSize',fs,... + 'FontAngle',fa,... + 'FontWeight',fw,... + 'Position',[pos(1:3)+[0 pos(4)/2 0] pos(4)/2]); + +if isfield(c,'val') && ~isempty(c.val) + val = c.val{1}; + if ischar(val) + tmp = val'; + tmp = tmp(:)'; + set(newstring,'String',tmp); + elseif isnumeric(val) + if ndims(val)>2, + set(newstring,'String',['reshape([', num2str(val(:)'), '],[' num2str(size(val)) '])']); + else + if size(val,1)==1, + set(newstring,'String',num2str(val(:)')); + elseif size(val,2)==1, + set(newstring,'String',['[' num2str(val(:)') ']''']); + else + str = ''; + for i=1:size(val,1), + str = [str ' ' num2str(val(i,:)) ';']; + end; + set(newstring,'String',str); + end; + end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function accept_string(varargin) +% Accept a typed in string? +run_in_current_node(@stringval,true,get(varargin{1},'String')); +update_ui; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function remove_string_box +% Delete the string box and prompt, making the opts box +% visible again +delete(findobj(0,'Tag','string_box')); +delete(findobj(0,'Tag','string_prompt')); +set(opts_box,'Visible','on'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function show_value(c) +% Update the value box + +valtxt = {''}; +% col = [1 0 0]; + +switch c.type +case {'menu'} + if isfield(c,'val') && ~isempty(c.val) + if isfield(c,'labels') && isfield(c,'values') + val = c.val{1}; + for i=1:length(c.values) + if same(c.values{i},val) + valtxt = c.labels{i}; + % col = [0 0 0]; + break; + end; + end; + end; + end; + +case {'const','entry'} + if isfield(c,'val') && ~isempty(c.val) + val = c.val{1}; + if isempty(val) + valtxt = ''; + else + if isnumeric(val) + sz = size(val); + if length(sz)>2 + valtxt = sprintf('%dx',sz); + valtxt = [valtxt(1:(end-1)) ' Numeric Array']; + else + valtxt = cell(size(val,1),1); + for i=1:size(val,1) + valtxt{i} = sprintf('%14.8g ',val(i,:)); + end; + end; + elseif(ischar(val)) + valtxt = val; + else + valtxt = 'Can not display'; + end; + end; + % col = [0 0 0]; + end; + +case {'files'} + if isfield(c,'val') && ~isempty(c.val) + if isempty(c.val{1}) || isempty(c.val{1}{1}) + valtxt = ''; + else + valtxt = c.val{1}; + end; + % col = [0 0 0]; + end; + +case {'choice'} + if isfield(c,'val') && length(c.val)==1 + valtxt = {'A choice, where',['"' c.val{1}.name '"'], 'is selected.'}; + % col = [0.5 0.5 0.5]; + else + valtxt = {'A choice, with', 'nothing selected.'}; + % col = [0.5 0.5 0.5]; + end; + +case {'repeat'} + ln = length(c.val); s = 's'; if ln==1, s = ''; end; + valtxt = ['A series containing ' num2str(length(c.val)) ' item' s '.']; + % col = [0.5 0.5 0.5]; + +case {'branch'} + ln = length(c.val); s = 's'; if ln==1, s = ''; end; + valtxt = {['A branch holding ' num2str(length(c.val)) ' item' s '.']}; + if isfield(c,'prog'), + valtxt = {valtxt{:}, '', ' User specified values',... + ' from this branch will be',... + ' collected and passed to',... + ' an executable function',... + ' when the job is run.'}; + end; + % col = [0.5 0.5 0.5]; + +otherwise + valtxt = 'What on earth is this???'; +end; +val_box = findobj(0,'tag','val_box'); +if ~isempty(val_box) + % set(val_box,'String',valtxt,'ForegroundColor',col); + set(val_box,'String',valtxt); + workaround(val_box); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = remove(c,varargin) +% Remove node c +if strcmp(questdlg(['Remove "' c.name '"?'],'Confirm','Yes','No','Yes'),'Yes'), + c = {}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = replicate(c,varargin) +% Replicate node c +c = {c,uniq_id(c)}; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = choose(c,val) +% Specify the value of c to be val +c.val{1} = uniq_id(val); +c.expanded = true; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = menuval(c,val) +% Specify the value of c to be val +c.val{1} = val; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = stringval(c,val) +% Accept (or not) a typed in string + +msg = 'SUCCESS: Values accepted'; + +switch c.strtype +case {'s'} + c.val{1} = val; + show_value(c); + remove_string_box; + +case {'s+'} + msg = 'FAILURE: Cant do s+ yet'; + beep; + remove_string_box; + +otherwise + n = Inf; + if isfield(c,'num') + n = c.num; + end; + if isfield(c,'extras') + [val,msg] = spm_eeval(val,c.strtype,n,c.extras); + else + [val,msg] = spm_eeval(val,c.strtype,n); + end; + + if ischar(val) + beep; + msg = ['FAILURE: ' msg]; + else + c.val{1} = val; + show_value(c); + remove_string_box; + msg = ['SUCCESS: ' msg]; + end; +end; +show_msg(msg); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = series(c,new) +% Add a new repeat +c.expanded = true; +new.removable = true; +if isfield(c,'val') + c.val = {c.val{:},uniq_id(new)}; +else + c.val = {uniq_id(new)}; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function setdef(strin,val) +global defaults + +if isempty(defaults), spm_defaults; end; +if ischar(val) && strcmp(val,''), return; end; +o = find(strin=='.'); +df = cell(1,length(o)+1); +prev = 1; +for i=1:length(o), + df{i} = strin(prev:(o(i)-1)); + prev = o(i)+1; +end; +df{end} = strin(prev:end); +defaults = setdef_sub(defaults,df,val); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function d = setdef_sub(d,df,val) +if isempty(df), + d = val; +else + if ~isfield(d,df{1}),d.(df{1}) = []; end; + d.(df{1}) = setdef_sub(d.(df{1}),df(2:end),val); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function val = getdef(strin) +% Get value of one of the SPM defaults + +global defaults + +val = getdef_sub(defaults,strin); +if ischar(val) && strcmp(val,'') + val = {}; +else + val = {val}; +end; +%fprintf('%s\n',strin); +%disp(val) +%disp('----'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = getdef_sub(defs,field) +% Satellite function for getdef + +o = find(field=='.'); +if isempty(o) + if isfield(defs,field) + c = defs.(field); + else + c = ''; + end; + return; +end; +if isfield(defs,field(1:(o-1))) + c = getdef_sub(defs.(field(1:(o-1))),field((o+1):end)); +else + c = ''; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = same(a,b) +% Are two data structures identical? + +% Innocent until proven guilty +t = true; + +% Check the dimensions +if isempty(a) && isempty(b) + t = true; return; +end; +sa = size(a); +sb = size(b); +if length(sa) ~= length(sb) + t = false; return; +end; +if ~all(sa==sb) + t = false; return; +end; + +% Check the classes +ca = class(a); +if ~strcmp(ca,class(b)), t = false; return; end; + +% Recurse through data structure +switch ca +case {'double','single','sparse','char','int8','uint8',... + 'int16','uint16','int32','uint32','logical'} + msk = ((a==b) | (isnan(a)&isnan(b))); + if ~all(msk(:)), t = false; return; end; + +case {'struct'} + fa = fieldnames(a); + fb = fieldnames(b); + if length(fa) ~= length(fb), t = false; return; end; + for i=1:length(fa) + if ~strcmp(fa{i},fb{i}), t = false; return; end; + for j=1:length(a) + if ~same(a(j).(fa{i}),b(j).(fb{i})) + t = false; return; + end; + end; + end; + +case {'cell'} + for j=1:length(a(:)) + if ~same(a{j},b{j}), t = false; return; end; + end; + +case {'function_handle'} + if ~strcmp(func2str(a),func2str(b)) + t = false; return; + end; + +otherwise + warning(['Unknown class "' ca '"']); + t = false; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = batch_box +t = findobj(0,'tag','batch_box'); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function t = opts_box +t = findobj(0,'tag','opts_box'); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function save_job(varargin) +% Save a batch job +c = get(batch_box,'UserData'); spm('Pointer','Watch'); +[unused,jobs] = harvest(c); +spm('Pointer'); +%eval([tag '=val;']); +cll = {'*.mat','Matlab .mat file';'*.m','Matlab script file';'*.xml','XML file'}; +[filename, pathname, FilterIndex] = uiputfile(cll,'Save job as'); +if ischar(filename) + [unused,unused,ext] = fileparts(filename); + if isempty(ext) + ext = cll{FilterIndex}(2:end); + filename = [filename ext]; + end + switch ext + case '.xml', + spm('Pointer','Watch'); + savexml(fullfile(pathname,filename),'jobs'); + spm('Pointer'); + case '.mat', + if spm_matlab_version_chk('7') >= 0, + save(fullfile(pathname,filename),'-V6','jobs'); + else + save(fullfile(pathname,filename),'jobs'); + end; + case '.m', + treelist('jobs',struct('exps',1, 'dval',2, 'fname', ... + fullfile(pathname,filename))); + otherwise + questdlg(['Unknown extension (' ext ')'],'Nothing saved','OK','OK'); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function load_job(varargin) +% Load a set of batch jobs and possibly merge it + +[filenames sts] = spm_select([1 Inf], 'batch', 'Load job file(s)'); +if sts + filenames = cellstr(filenames); + newjobs = {}; + for cf = 1:numel(filenames) + [p,nam,ext] = fileparts(filenames{cf}); + switch ext + case '.xml', + spm('Pointer','Watch'); + try + loadxml(filenames{cf},'jobs'); + catch + questdlg('LoadXML failed',filenames{cf},'OK','OK'); + return; + end; + spm('Pointer'); + case '.mat' + try + load(filenames{cf},'jobs'); + catch + questdlg('Load failed',filenames{cf},'OK','OK'); + end; + case '.m' + opwd = pwd; + try + cd(p); + eval(nam); + catch + questdlg('Load failed',filenames{cf},'OK','OK'); + end; + cd(opwd); + otherwise + questdlg(['Job ' nam ': Unknown extension (' ext ')'],... + 'This job not loaded','OK','OK'); + end; + if exist('jobs','var') + newjobs = {newjobs{:} jobs{:}}; + clear jobs; + else + questdlg(['No jobs (' nam ext ')'],'No jobs','OK','OK'); + end; + end; + if ~isempty(newjobs) + spm('Pointer','Watch'); + initialise(newjobs); + spm('Pointer'); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_struct(varargin) +% Get data structure from handle, and run it +% If an error occured, then return to user interface +c = get(batch_box,'UserData'); +[unused,job] = harvest(c); +try +run_struct1(c); +catch + disp('Error running job:'); + disp(lasterr); + setup_ui(job); +end; +disp('--------------------------'); +disp('Done.'); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_struct1(c) +% Run a batch job from a data structure + +if isfield(c,'prog') + prog = c.prog; + [unused,val] = harvest(c); + disp('--------------------------'); + disp(['Running "' c.name '"']); + [Finter,unused,CmdLine] = spm('FnUIsetup',c.name); + spm('Pointer','Watch'); + spm('FigName',[c.name ': running'],Finter,CmdLine); + + if 0 + try + feval(prog,val); + spm('FigName',[c.name ': done'],Finter,CmdLine); + catch + disp(['An error occurred when running "' c.name '"']); + disp( '--------------------------------'); + disp(lasterr); + disp( '--------------------------------'); + spm('FigName',[c.name ': failed'],Finter,CmdLine); + errordlg({['An error occurred when running "' c.name '"'],lasterr},'SPM Jobs'); + end; + spm('Pointer'); + else + feval(prog,val); + spm('FigName',[c.name ': done'],Finter,CmdLine); + %prog_infos=functions(prog) + %prog_log=[prog_infos.parentage{end} '_log']; + %if exist(prog_log) > 1 + try + spm_log2html(prog,val); + disp(sprintf('Generating log on %s',c.name)); + catch + disp(sprintf('Error while generating log on %s',c.name)); + end + %else + % prog_msg=sprintf('No function found for generating log on %s. Try making a: %s',c.name, prog_log); + %end + %disp(prog_msg); + spm('Pointer'); + end; + +else + if isfield(c,'val') + for i=1:length(c.val) + run_struct1(c.val{i}); + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function harvest_def(c) +switch c.type, +case{'const','menu','files','entry'}, + if isfield(c,'def') && numel(c.val)==1, + setdef(c.def,c.val{1}); + end; + +otherwise + for i=1:length(c.val), + harvest_def(c.val{i}); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [tag,val,typ] = harvest(c) +% Take a data structure, and extract what is needed to save it +% as a batch job + +tag = 'unknown'; +val = []; +typ = c.type; +switch(typ) +case {'const','menu','files','entry'} + tag = gettag(c); + if ~isempty(c.val) + val = c.val{1}; + else + val = ''; + end; + +case {'branch'} + tag = gettag(c); + if isfield(c,'val') + val = []; + for i=1:length(c.val) + [tag1,val1] = harvest(c.val{i}); + val.(tag1) = val1; + end; + end; + +case {'repeat'} + tag = gettag(c); + if length(c.values)==1 && strcmp(c.values{1}.type,'branch'), + cargs = {}; + for i=1:numel(c.values{1}.val), + cargs = {cargs{:},gettag(c.values{1}.val{i}),{}}; + end; + val = struct(cargs{:}); + + if isfield(c,'val') + for i=1:length(c.val), + [tag1,val1,typ1] = harvest(c.val{i}); + val(i) = val1; + end; + end; + else + val = {}; + if isfield(c,'val') + for i=1:length(c.val), + [tag1,val1,typ1] = harvest(c.val{i}); + if length(c.values)>1, + if iscell(val1) + val1 = struct(tag1,{val1}); + else + val1 = struct(tag1,val1); + end; + end; + val = {val{:}, val1}; + end; + end; + end; + +case {'choice'} + if isfield(c,'tag'), tag = gettag(c); end; + [tag1,val1] = harvest(c.val{1}); + if iscell(val1) + val = struct(tag1,{val1}); + else + val = struct(tag1,val1); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function tag = gettag(c) +% Get a tag field - possibly from one of the kids + +if (strcmp(c.type,'repeat') || strcmp(c.type,'choice')) && numel(c.values)>0 + tag = gettag(c.values{1}); + for i=2:length(c.values) + if ~strcmp(tag,gettag(c.values{i})) + tag = c.tag; + return; + end; + end; +else + tag = c.tag; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c0 = cntxtmnu(ob) +c0 = uicontextmenu('Parent',get(ob,'Parent')); +set(ob,'uicontextmenu',c0); +c1 = uimenu('Label','Font', 'Parent',c0); + uimenu('Label','Plain', 'Parent',c1,'Callback','set(gco,''FontWeight'',''normal'',''FontAngle'',''normal'');'); + uimenu('Label','Bold', 'Parent',c1,'Callback','set(gco,''FontWeight'',''bold'', ''FontAngle'',''normal'');'); + uimenu('Label','Italic', 'Parent',c1,'Callback','set(gco,''FontWeight'',''normal'',''FontAngle'',''italic'');'); + uimenu('Label','Bold-Italic','Parent',c1,'Callback','set(gco,''FontWeight'',''bold'', ''FontAngle'',''italic'');'); +c1 = uimenu('Label','Fontsize','Parent',c0); +fs = [8 9 10 12 14 16 18]; % [20 24 28 32 36 44 48 54 60 66 72 80 88 96]; +for i=fs, + uimenu('Label',sprintf('%-3d',i),'Parent',c1,'Callback',@fszoom,'UserData',i); +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function workaround(t) +set(t,'Value',[], 'Enable', 'on', 'Max',2, 'Min',0,'ListBoxTop',1); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function addvfiles(id,c,c0) +if (nargin<2)||isempty(c), + c = get(batch_box,'UserData'); +end; +if nargin<3 + c0 = []; +end; +files_select_list('clearvfiles'); +vf =addvfiles1(c,id,{},c0); +spm_select('clearvfiles'); +spm_select('addvfiles',vf); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [vf,sts]=addvfiles1(c,id,vf,c0) +sts = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; + +if isfield(c,'vfiles'), + if ~find_id(c,id), + [c,unused,ok] = get_strings1(c,0); + if ok, + [unused,job] = harvest(c); + vf1 = feval(c.vfiles,job); + if ~isempty(c0) + files = filter_files(c0, vf1); + else + files = vf1; + end; + if ~isempty(files) + files_select_list('addvfiles', sprintf('Output from "%s"', ... + c.name), ... + files, c.id); + end; + vf = {vf{:}, vf1{:}}; + end; + else + sts = 1; + end; + return; +end; + +switch c.type, +case {'repeat','choice','branch'}, + for i=1:length(c.val), + [vf,sts]=addvfiles1(c.val{i},id,vf,c0); + if sts, return; end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function addinfiles(c0,c) +id = c0.id; +if nargin<2, + c = get(batch_box,'UserData'); +end; +files_select_list('clearinfiles'); +addinfiles1(c,id,'',c0); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function sts=addinfiles1(c,id,progname,c0) +sts = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; + +if find_id(c,id), + sts = 1; +end; + +switch c.type, +case 'files' + if ~isempty(c.val) && ~isempty(c.val{1}) + files = filter_files(c0,c.val{1}); + if ~isempty(files) + files_select_list('addinfiles', ... + sprintf('Input to "%s->%s"', ... + progname, c.name), ... + files, c.id); + end; + end; +case {'repeat','choice','branch'}, + if isfield(c,'prog') + progname = c.name; + oldin = files_select_list('getinnum'); + end; + for i=1:length(c.val), + sts=addinfiles1(c.val{i},id,progname,c0); + if sts, return; end; + end; + if isfield(c,'prog') + newin = files_select_list('getinnum'); + if (newin-oldin > 1) + files_select_list('allinfiles', ... + sprintf('All inputs to %s',progname),... + oldin+1, newin); + end; + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ffiles = filter_files(c,files) +if strcmp(c.filter, 'image')||strcmp(c.filter,'dir') + filter = ['ext' c.filter]; +else + filter = c.filter; +end; +if isfield(c,'ufilter') + uf = c.ufilter; + if uf(1) == '^' % This will not work with full pathnames + uf=uf(2:end); + end; +else + uf = '.*'; +end; +ffiles = spm_select('filter', files, ... + filter, uf); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function varargout = files_select_list(c,varargin) +persistent vfstr; +persistent vfdat; +persistent vffiles; +persistent vfid; +persistent instr; +persistent indat; +persistent infiles; +persistent inid; +if isstruct(c) + switch lower(varargin{1}) + case 'getvf' + c.val{1} = vffiles{varargin{2}}; + case 'getin' + c.val{1} = infiles{varargin{2}}; + end; + varargout{1} = c; + return; +end; +if ~iscell(vfstr) && ~strcmp(lower(c),'init') + files_select_list('init'); +end; +switch lower(c) +case 'init' + vfstr = {}; + vfdat = {}; + vffiles = {}; + vfid = []; + instr = {}; + indat = {}; + infiles = {}; + inid = []; +case 'clearvfiles' + vfstr = {}; + vfdat = {}; + vffiles = {}; + vfid = []; +case 'clearinfiles' + instr = {}; + indat = {}; + infiles = {}; + inid = []; +case 'addvfiles' + nvfind = numel(vfstr)+1; + vfid(nvfind) = varargin{3}; + vfstr{nvfind} = varargin{1}; + vfdat{nvfind} = struct('fun',@files_select_list,'args',{{'getvf', nvfind}}, ... + 'redraw',1); + vffiles{nvfind} = varargin{2}(:); +case 'addinfiles' + ninind = numel(instr)+1; + inid(ninind) = varargin{3}; + instr{ninind} = varargin{1}; + indat{ninind} = struct('fun',@files_select_list,'args',{{'getin', ninind}}, ... + 'redraw',1); + infiles{ninind} = varargin{2}(:); +case 'allinfiles' + ninind = numel(instr)+1; + inid(ninind) = -1; + instr{ninind} = varargin{1}; + indat{ninind} = struct('fun',@files_select_list,'args',{{'getin', ninind}}, ... + 'redraw',1); + infiles{ninind} = cat(1,infiles{varargin{2}:varargin{3}}); +case 'getinnum' + varargout{1} = numel(instr); +case 'listall' + varargout{1} = {vfstr{:} instr{:}}; + varargout{2} = {vfdat{:} indat{:}}; +end +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = find_id(c,id) +ok = 0; +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +if c.id==id, + ok = 1; + return; +end; +if isfield(c,'val'), + for i=1:length(c.val), + ok = find_id(c.val{i},id); + if ok, return; end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = uniq_id(c) +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +c.id = rand(1); +if isfield(c,'val'), + for i=1:length(c.val), + c.val{i} = uniq_id(c.val{i}); + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function show_msg(txt) +lb = findobj('tag','msg_box'); +if isempty(txt), + set(lb,'String',{}); +else + msg = get(lb,'String'); + if iscell(txt), + msg = {msg{:} txt{:}}; + else + msg = {msg{:} txt}; + end; + set(lb,'String',msg); +end; +drawnow; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +%function beep +%fprintf('%c',7); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown +% Create a pulldown for individual jobs +c = initialise_struct; +fg = spm_figure('findwin','Graphics'); +if isempty(fg), return; end; +set(0,'ShowHiddenHandles','on'); +delete(findobj(fg,'tag','jobs')); +set(0,'ShowHiddenHandles','off'); +f0 = uimenu(fg,'Label','TASKS','HandleVisibility','off','tag','jobs'); +pulldown1(f0,c,c.tag); +uimenu(f0,'Label','Batch','CallBack',@interactive,'Separator','on'); +uimenu(f0,'Label','Defaults','CallBack',@defaults_edit,'Separator','off'); +f1 = uimenu(f0,'Label','Sequential'); +pulldown2(f1,c,c.tag); + +if 0, % Currently unused + f1 = uimenu(f0,'Label','Modality'); + modalities = {'FMRI','PET','EEG'}; + for i=1:length(modalities) + tmp = modalities{i}; + if strcmp(tmp,getdef('modality')), + tmp = ['*' tmp]; + else + tmp = [' ' tmp]; + end; + uimenu(f1,'Label',tmp,'CallBack',@chmod); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown1(f0,c0,tag0) +if ~isfield(c0,'values'), return; end; +for i=1:length(c0.values), + c1 = c0.values{i}; + if isstruct(c1) && ~isfield(c1,'hidden'), + tag1 = tag0; + if isfield(c1,'tag'), + tag1 = [tag1 '.' c1.tag]; + end; + if isfield(c1,'prog'), + uimenu(f0,'Label',c1.name,'CallBack',@interactive,'UserData',{'',tag1}); + else + f1 = uimenu(f0,'Label',c1.name); + pulldown1(f1,c1,tag1); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function pulldown2(f0,c0,tag0) +if ~isfield(c0,'values'), return; end; +for i=1:length(c0.values), + c1 = c0.values{i}; + if isstruct(c1) && ~isfield(c1,'hidden'), + tag1 = tag0; + if isfield(c1,'tag'), + tag1 = [tag1 '.' c1.tag]; + end; + if isfield(c1,'prog'), + if findcheck(c1), + uimenu(f0,'Label',c1.name,'Enable','off'); + else + uimenu(f0,'Label',c1.name,'CallBack',@run_serial,'UserData',{'',tag1}); + end; + else + f1 = uimenu(f0,'Label',c1.name); + pulldown2(f1,c1,tag1); + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function hascheck = findcheck(c) +hascheck = false; +if ~isstruct(c) || ~isfield(c,'type'), return; end; +if isfield(c,'check'), + hascheck = true; + return; +end; +if isfield(c,'values'), + for i=1:numel(c.values), + hascheck = findcheck(c.values{i}); + if hascheck, return; end; + end; +end; +if isfield(c,'val'), + for i=1:numel(c.val), + hascheck = findcheck(c.val{i}); + if hascheck, return; end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function chmod(mod,varargin) +global defaults +if isempty(defaults), spm_defaults; end; +if ischar(mod), + %if strcmpi(defaults.modality,mod), + % spm('ChMod',mod); + %end; + defaults.modality = mod; +else + tmp = get(mod,'Label'); + defaults.modality = tmp(2:end); +end; +pulldown; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function fszoom(varargin) +fs = sscanf(get(varargin{1},'Label'),'%d'); +set(gco,'FontSize',fs); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function run_serial(varargin) +ud = get(varargin{1},'UserData'); +if iscell(ud) + serial(ud{:}); +else + serial; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function serial(job,node) + +if nargin<2, node = 'jobs'; end; + +fg = spm_figure('FindWin','Interactive'); +if isempty(fg), fg = spm('CreateIntWin'); end; +delete(findobj(fg,'Parent',fg)); +t=uicontrol(fg,... + 'Style','listbox',... + 'Units','normalized',... + 'Position',[0.02 0.02 0.96 0.62],... + 'Tag','help_box2',... + 'FontName','fixedwidth',... + 'FontSize',12,... + 'BackgroundColor',[1 1 1]); +set(t,'Value',[], 'Enable', 'inactive', 'Max',2, 'Min',0); +workaround(t); +cntxtmnu(t); +spm('Pointer'); +drawnow; + +if nargin>0, + c = initialise_struct(job); +else + c = initialise_struct; +end; + +c = start_node(c,node); +c = start_node(c,@run_ui,{}); +spm_input('!DeleteInputObj'); +delete(findobj(fg,'Parent',fg)); +[unused,jobs] = harvest(c); +%savexml('job_last.xml','jobs'); +run_job(jobs); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = run_ui(c,varargin) + +nnod=1; +while(1), + nod = nnod; + [ci,unused,hlp] = get_node(c,nod); + if isempty(ci), break; end; + + help_box = findobj(0,'tag','help_box2'); + if ~isempty(help_box), + set(help_box,'String',' '); + workaround(help_box); + ext = get(help_box,'Extent'); + pos = get(help_box,'position'); + pw = floor(pos(3)/ext(3)*21-4); + set(help_box,'String',spm_justify(pw,hlp)); + workaround(help_box); + + if isfield(c,'prog'), + try + set(help_box,'HandleVisibility','off'); + [Finter,unused,CmdLine] = spm('FnUIsetup',c.name); + spm('FigName',[c.name ': setup'],Finter,CmdLine); + catch + end; + set(help_box,'HandleVisibility','on'); + end; + end; + + pos = 1; + + switch ci.type, + case {'const','files','menu','entry'} + nnod = nod + 1; + + vl = {''}; + if isfield(ci,'def'), vl = getdef(ci.def); end; + if numel(vl)~=0 && (~ischar(vl{1}) || ~strcmp(vl{1},'')), + getit = 0; + if ~isfield(ci,'val') || ~iscell(ci.val) || isempty(ci.val), + ci.val = vl; + end; + else + getit = 1; + end; + + switch ci.type, + case {'const'} + case {'files'} + num = ci.num; + + if getit, + if ~isempty(ci.val), + sel = ci.val{1}; + else + sel = ''; + end; + addvfiles(ci.id,c); + if isfield(ci,'dir'), + dr = ci.dir; + else + dr = pwd; + end; + if isfield(ci,'ufilter') + uf = ci.ufilter; + else + uf = '.*'; + end; + [ci.val{1},ok] = spm_select(num,ci.filter,ci.name,sel,dr,uf); + if ~ok, + error('File Selector was deleted.'); + end; + spm_select('clearvfiles'); + ci.val{1} = cellstr(ci.val{1}); + end; + + case {'menu'} + dv = []; + if getit, + if isfield(ci,'val') && ~isempty(ci.val), + for i=1:length(ci.values) + if same(ci.values{i},ci.val{1}) + dv = i; + end; + end; + end; + lab = ci.labels{1}; + for i=2:length(ci.values), + lab = [lab '|' ci.labels{i}]; + end; + if isempty(dv), + ind = spm_input(ci.name,pos,'m',lab,1:length(ci.values)); + else + ind = spm_input(ci.name,pos,'m',lab,1:length(ci.values),dv); + end; + ci.val = {ci.values{ind}}; + end; + + case {'entry'} + n1 = Inf; + if isfield(ci,'num'), n1 = ci.num; end; + if getit, + val = ''; + if isfield(ci,'val') && ~isempty(ci.val) && ~strcmp(ci.val{1},''), + val = ci.val{1}; + end; + if isfield(ci,'extras') + val = spm_input(ci.name,pos,ci.strtype,val,n1,ci.extras); + else + val = spm_input(ci.name,pos,ci.strtype,val,n1); + end; + ci.val{1} = val; + end; + end; + + case {'repeat'}, + lab = 'Done'; + for i=1:length(ci.values) + lab = [lab '|New "' ci.values{i}.name '"']; + end; + tmp = spm_input(ci.name,pos,'m',lab,0:length(ci.values)); + if tmp, + ci.val = {ci.val{:}, uniq_id(ci.values{tmp})}; + nnod = nod; + else + nnod = nod + 1; + end; + + case {'choice'} + nnod = nod + 1; + lab = ci.values{1}.name; + for i=2:length(ci.values) + lab = [lab '|' ci.values{i}.name]; + end; + tmp = spm_input(ci.name,pos,'m',lab,1:length(ci.values)); + ci.val = {uniq_id(ci.values{tmp})}; + otherwise + error('This should not happen.'); + end; + c = set_node(c,nod,ci); +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [ci,n,hlp] = get_node(c,n) +ci = []; +hlp = ''; +switch c.type, +case {'const','files','menu','entry'} + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + +case 'choice' + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + [ci,n,hlp] = get_node(c.val{1},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + +case 'branch', + for i=1:numel(c.val), + [ci,n,hlp] = get_node(c.val{i},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + end; + +case 'repeat', + for i=1:numel(c.val), + [ci,n,hlp] = get_node(c.val{i},n); + if ~isempty(ci), + hlp = {hlp{:},repmat('=',1,20),'',['* ' upper(c.name)],c.help{:},'',''}; + return; + end; + end; + n = n-1; + if n==0, + ci = c; + hlp = {['* ' upper(c.name)],c.help{:},'',''}; + return; + end; +otherwise + error('This should not happen'); + +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,n] = set_node(c,n,ci) +switch c.type, +case {'const','files','menu','entry'} + n = n-1; + if n==0, + c = ci; + return; + end; + +case 'choice' + n = n-1; + if n==0, + c = ci; + return; + end; + [c.val{1},n] = set_node(c.val{1},n,ci); + if n<0,return; end; + +case 'branch', + for i=1:numel(c.val), + [c.val{i},n] = set_node(c.val{i},n,ci); + if n<0,return; end; + end; + +case 'repeat', + for i=1:numel(c.val), + [c.val{i},n] = set_node(c.val{i},n,ci); + if n<0,return; end; + end; + n = n-1; + if n==0, + c = ci; + return; + end; + +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = initialise_struct(job) +% load the config file, possibly adding a job +% to it, and generally tidy it up. The batch box +% is updated to contain the current structure. + +persistent c0 +if isempty(c0), + c0 = spm_config; + c0 = tidy_struct(c0); +end; +c = insert_defs(c0); +if nargin==1 && ischar(job) && strcmp(job,'defaults'), + c = defsub(c,{}); + c.name = 'SPM Defaults'; +else + c = hide_null_jobs(c); + if nargin>0 && ~isempty(job), + job = fromfile(job); + c = job_to_struct(c,job,'jobs'); + c = uniq_id(c); + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,defused] = defsub(c,defused) +if nargin<2, defused = {}; end; +if isfield(c,'prog'), c = rmfield(c,'prog'); end; +switch c.type, +case {'const'} + c = []; + +case {'menu','entry','files'} + if ~isfield(c,'def') || any(strcmp(c.def,defused)), + c = []; + else + defused = {defused{:},c.def}; + end; + +case {'branch'} + msk = true(1,length(c.val)); + for i=1:length(c.val), + [c.val{i},defused] = defsub(c.val{i},defused); + msk(i) = ~isempty(c.val{i}); + end; + c.val = c.val(msk); + if isempty(c.val), c = []; end; + +case {'choice','repeat'} + c.type = 'branch'; + c.val = c.values; + c = rmfield(c,'values'); + [c,defused] = defsub(c,defused); + +end; +if isfield(c,'vfiles'), c = rmfield(c,'vfiles'); end; +if isfield(c,'check'), c = rmfield(c,'check'); end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = insert_defs(c) +% Recursively descend through the tree structure, +% and assigning default values. +if ~isstruct(c) || ~isfield(c,'type'), + return; +end; +switch c.type +case {'menu','entry','files'} + if isfield(c,'def') + c.val = getdef(c.def); + if strcmp(c.type,'files') && ~isempty(c.val) + if ~isempty(c.val{1}) + c.val = {cellstr(c.val{1})}; + else + c.val = {{}}; + end; + end; + end; + +case {'repeat','choice'}, + if isfield(c,'values') + for i=1:numel(c.values) + c.values{i} = insert_defs(c.values{i}); + end; + end; +end; +if isfield(c,'val') + for i=1:numel(c.val) + c.val{i} = insert_defs(c.val{i}); + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = tidy_struct(c) +% Recursively descend through the tree structure, cleaning up +% fields that may be missing and adding an 'expanded' field +% where necessary. + +if ~isstruct(c) || ~isfield(c,'name') || ~isfield(c,'type') + return; +end; +c.id = rand(1); + +if ~isfield(c,'help'), c.help = {}; end; +if ischar(c.help), c.help = {c.help}; end; + +switch c.type +case {'const'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'val') + disp(c); warning(['No val field for "' c.name '"']); + c.val = {''}; + end; + +case {'menu'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + + if ~isfield(c,'labels') || ~isfield(c,'values') + disp(c); warning(['No labels and values field for "' c.name '"']); + c.labels = {}; + c.values = {}; + end; + if length(c.labels) ~= length(c.values) + disp(c); warning(['Labels and values fields incompatible for "' c.name '"']); + c.labels = {}; + c.values = {}; + end; + if ~isfield(c,'help'), c.help = {'Option selection by menu'}; end; + +case {'entry'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'strtype') + disp(c); warning(['No strtype field for "' c.name '"']); + c.strtype = 'e'; + end; + if ~isfield(c,'num') + disp(c); warning(['No num field for "' c.name '"']); + c.num = [1 1]; + end; + if length(c.num)~=2 + disp(c); warning(['Num field for "' c.name '" is wrong length']); + c.num = [Inf 1]; + end; + if ~isfield(c,'help'), c.help = {'Option selection by text entry'}; end; + +case {'files'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'filter') + disp(c); warning(['No filter field for "' c.name '"']); + c.filter = '*'; + end; + if ~isfield(c,'num') + disp(c); warning(['No num field for "' c.name '"']); + c.num = Inf; + end; + if length(c.num)~=1 && length(c.num)~=2 + disp(c); warning(['Num field for "' c.name '" is wrong length']); + c.num = Inf; + end; + if isfield(c,'val') && iscell(c.val) && numel(c.val)>=1, + if ischar(c.val{1}) + c.val{1} = cellstr(c.val{1}); + end; + end; + if ~isfield(c,'help'), c.help = {'File selection'}; end; + +case {'branch'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'val') + disp(c); warning(['No val field for "' c.name '"']); + c.val = {}; + end; + + c.expanded = false; + if ~isfield(c,'help'), c.help = {'Branch structure'}; end; + +case {'choice'} + if ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if ~isfield(c,'values') || ~iscell(c.values) + disp(c); error(['Bad values for "' c.name '"']); + end; + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; + if ~isfield(c,'val') || ~iscell(c.val) || length(c.val) ~= 1 + c.val = {c.values{1}}; + end; + c.expanded = true; + if ~isfield(c,'help'), c.help = {'Choice structure'}; end; + +case {'repeat'} + if ~isfield(c,'values') || ~iscell(c.values) + disp(c); error(['Bad values for "' c.name '"']); + end; + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; + if length(c.values)>1 && ~isfield(c,'tag') + disp(c); warning(['No tag field for "' c.name '"']); + c.tag = 'unknown'; + end; + if length(c.values)==1 && isfield(c,'tag') + % disp(c); warning(['"' c.name '" has unused tag']); + c = rmfield(c,'tag'); + end; + c.expanded = true; + if ~isfield(c,'help'), c.help = {'Repeated structure'}; end; + + if isfield(c,'num') && numel(c.num)==1, + if finite(c.num), + c.num = [c.num c.num]; + else + c.num = [0 c.num]; + end; + end; + +end; + +if ~isfield(c,'val'), c.val = {}; end; + +%switch c.type +%case {'menu','entry','files'} +% %if isempty(c.val) +% if isfield(c,'def') +% c.val = getdef(c.def); +% if strcmp(c.type,'files') && ~isempty(c.val) +% c.val = {cellstr(c.val{1})}; +% end; +% end; +% %end; +%end; + +if isfield(c,'val') + for i=1:length(c.val) + c.val{i} = tidy_struct(c.val{i}); + end; +end; +if isfield(c,'values') && strcmp(c.type,'repeat') + for i=1:length(c.values) + c.values{i} = tidy_struct(c.values{i}); + end; +end; + +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function job = fromfile(job) +if ischar(job) + [pth,nam,ext] = fileparts(job); + if strcmp(ext,'.xml') + spm('Pointer','Watch'); + try + loadxml(job,'jobs'); + catch + questdlg('LoadXML failed',job,'OK','OK'); + return; + end; + spm('Pointer'); + elseif strcmp(ext,'.mat') + try + load(job,'jobs'); + catch + questdlg('Load failed',job,'OK','OK'); + return; + end; + else + questdlg(['Unknown extension (' ext ')'],'Nothing loaded','OK','OK'); + return; + end; + job = jobs; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = hide_null_jobs(c) +c = hide_null_jobs1(c); +c = hide_null_jobs2(c); +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,flg] = hide_null_jobs1(c) +if ~isstruct(c) || ~isfield(c,'type'), + flg = true; + return; +end; + +if ~include(c), + flg = false; + c.hidden = true; + return; +end; + +switch c.type, +case {'repeat','branch','choice'}, + msk1 = true; + msk2 = true; + if isfield(c,'val') && ~isempty(c.val), + msk1 = true(1,numel(c.val)); + for i=1:length(c.val) + [c.val{i},msk1(i)] = hide_null_jobs1(c.val{i}); + end; + end; + if isfield(c,'values') && ~isempty(c.values), + msk2 = true(1,numel(c.values)); + for i=1:length(c.values) + [c.values{i},msk2(i)] = hide_null_jobs1(c.values{i}); + end; + end; + flg = any(msk1) || any(msk2); + if ~flg, c.hidden = true; end; +otherwise + flg = true; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function ok = include(c) +% Check that the modality is OK +ok = true; +if isfield(c,'modality'), + mod = getdef('modality'); + if ~isempty(mod), + mod = mod{1}; + ok = false; + for i=1:length(c.modality), + if strcmpi(c.modality{i},mod), + ok = true; + return; + end; + end; + end; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function [c,flg] = hide_null_jobs2(c) +if ~isstruct(c) || ~isfield(c,'type') + flg = 0; + return; +end; +if isfield(c,'prog'), + flg = 1; + return; +end; + +switch c.type, +case {'repeat','branch','choice'}, + flg = 0; + msk1 = []; + msk2 = []; + if isfield(c,'val'), + msk1 = ones(1,numel(c.val)); + for i=1:length(c.val) + [c.val{i},msk1(i)] = hide_null_jobs2(c.val{i}); + end; + end; + if isfield(c,'values'), + msk2 = ones(1,numel(c.values)); + for i=1:length(c.values) + [c.values{i},msk2(i)] = hide_null_jobs2(c.values{i}); + end; + end; + if (sum(msk1) + sum(msk2))>0, flg = 1; end; + if ~flg, c.hidden = 1; end; +otherwise + flg = 0; +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function c = job_to_struct(c,job,tag) +% Modify a structure based on a batch job +if isstruct(c) && isfield(c,'hidden'), + return; +end; +switch c.type +case {'const','menu','files','entry'} + if ~strcmp(gettag(c),tag), return; end; + if ischar(job) && strcmp(job,'') + c.val = {}; + else + c.val{1} = job; + end; + +case {'branch'} + if ~strcmp(gettag(c),tag), return; end; + if ~isstruct(job), return; end; + + tag = fieldnames(job); + for i=1:length(tag) + for j=1:length(c.val) + if strcmp(gettag(c.val{j}),tag{i}) + c.val{j} = job_to_struct(c.val{j},job.(tag{i}),tag{i}); + break; + end; + end; + end; + +case {'choice'} + if ~strcmp(gettag(c),tag), return; end; + if ~isstruct(job), return; end; + tag = fieldnames(job); + if length(tag)>1, return; end; + tag = tag{1}; + for j=1:length(c.values) + if strcmp(gettag(c.values{j}),tag) + c.val = {job_to_struct(c.values{j},job.(tag),tag)}; + end; + end; + +case {'repeat'} + if ~strcmp(gettag(c),tag), return; end; + if length(c.values)==1 && strcmp(c.values{1}.type,'branch') + if ~isstruct(job), return; end; + for i=1:length(job) + if strcmp(gettag(c.values{1}),tag) + c.val{i} = job_to_struct(c.values{1},job(i),tag); + c.val{i}.removable = true; + end; + end; + elseif length(c.values)>1 + if ~iscell(job), return; end; + for i=1:length(job) + tag = fieldnames(job{i}); + if length(tag)>1, return; end; + tag = tag{1}; + for j=1:length(c.values) + if strcmp(gettag(c.values{j}),tag) + c.val{i} = job_to_struct(c.values{j},job{i}.(tag),tag); + c.val{i}.removable = true; + break; + end; + end; + end; + else + if ~iscell(job), return; end; + for i=1:length(job) + c.val{i} = job_to_struct(c.values{1},job{i},tag); + c.val{i}.removable = true; + end; + end; + +end; +return; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc(str,wid) +if nargin<1, str = ''; end; +if nargin<2, wid = 60; end; + +tmp = [0 find([str '.']=='.')]; +node = {}; +for i=1:length(tmp)-1, + tmp1 = str((tmp(i)+1):(tmp(i+1)-1)); + if ~isempty(tmp1), + node = {node{:},tmp1}; + end; +end; +if numel(node)>1 && strcmp(node{1},'jobs'), + node = node(2:end); +end; + +c = initialise_struct; +doc = showdoc1(node,c,wid); +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc1(node,c,wid) +doc = {}; +if isempty(node), + doc = showdoc2(c,'',wid); + return; +end; + +if isfield(c,'values'), + for i=1:numel(c.values), + if isfield(c.values{i},'tag') && strcmp(node(1),c.values{i}.tag), + doc = showdoc1(node(2:end),c.values{i},wid); + return; + end; + end; +end; + +if isfield(c,'val'), + for i=1:numel(c.val), + if isfield(c.val{i},'tag') && strcmp(node(1),c.val{i}.tag), + doc = showdoc1(node(2:end),c.val{i},wid); + return; + end; + end; +end; +%------------------------------------------------------------------------ + +%------------------------------------------------------------------------ +function doc = showdoc2(c,lev,wid) +doc = {''}; +if ~isempty(lev) && sum(lev=='.')==1, + % doc = {doc{:},repmat('_',1,80),''}; +end; + +if isfield(c,'name'), + str = sprintf('%s %s', lev, c.name); + %under = repmat('-',1,length(str)); + doc = {doc{:},str}; + % if isfield(c,'modality'), + % txt = 'Only for '; + % for i=1:numel(c.modality), + % txt = [txt ' ' c.modality{i}]; + % end; + % doc = {doc{:},'',txt, ''}; + %end; + if isfield(c,'help'); + hlp = spm_justify(wid,c.help); + doc = {doc{:},hlp{:}}; + end; + + switch (c.type), + case {'repeat'}, + if length(c.values)==1, + doc = {doc{:}, '', sprintf('Repeat "%s", any number of times.',c.values{1}.name)}; + else + doc = {doc{:}, '', 'Any of the following options can be chosen, any number of times'}; + i = 0; + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.values{ii}.name)}; + end; + end; + end; + doc = {doc{:},''}; + + case {'choice'}, + doc = {doc{:}, '', 'Any one of these options can be selected:'}; + i = 0; + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.values{ii}.name)}; + end; + end; + doc = {doc{:},''}; + + case {'branch'}, + doc = {doc{:}, '', sprintf('This item contains %d fields:', length(c.val))}; + i = 0; + for ii=1:length(c.val), + if isstruct(c.val{ii}) && isfield(c.val{ii},'name'), + i = i+1; + doc = {doc{:}, sprintf(' %2d) %s', i,c.val{ii}.name)}; + end; + end; + doc = {doc{:},''}; + + case {'menu'}, + doc = {doc{:}, '', 'One of these values is chosen:'}; + for k=1:length(c.labels), + doc = {doc{:}, sprintf(' %2d) %s', k, c.labels{k})}; + end; + doc = {doc{:},''}; + + case {'files'}, + if length(c.num)==1 && isfinite(c.num(1)) && c.num(1)>=0, + tmp = spm_justify(wid,sprintf('A "%s" file is selected by the user.',c.filter)); + else + tmp = spm_justify(wid,sprintf('"%s" files are selected by the user.\n',c.filter)); + end; + doc = {doc{:}, '', tmp{:}, ''}; + + case {'entry'}, + switch c.strtype, + case {'e'}, + d = 'Evaluated statements'; + case {'n'}, + d = 'Natural numbers'; + case {'r'}, + d = 'Real numbers'; + case {'w'}, + d = 'Whole numbers'; + otherwise, + d = 'Values'; + end; + tmp = spm_justify(wid,sprintf('%s are entered.',d)); + doc = {doc{:}, '', tmp{:}, ''}; + end; + + i = 0; + doc = {doc{:},''}; + if isfield(c,'values'), + for ii=1:length(c.values), + if isstruct(c.values{ii}) && isfield(c.values{ii},'name'), + i = i+1; + lev1 = sprintf('%s%d.', lev, i); + doc1 = showdoc2(c.values{ii},lev1,wid); + doc = {doc{:}, doc1{:}}; + end; + end; + end; + if isfield(c,'val'), + for ii=1:length(c.val), + if isstruct(c.val{ii}) && isfield(c.val{ii},'name'), + i = i+1; + lev1 = sprintf('%s%d.', lev, i); + doc1 = showdoc2(c.val{ii},lev1,wid); + doc = {doc{:}, doc1{:}}; + end; + end; + end; + doc = {doc{:}, ''}; +end; + + diff --git a/spm/spm_log2html/spm_log2html.m b/spm/spm_log2html/spm_log2html.m new file mode 100644 index 0000000..09ea46f --- /dev/null +++ b/spm/spm_log2html/spm_log2html.m @@ -0,0 +1,154 @@ +function htmlfile = spm_log2html(prog, val, options) +%SPM_LOG2HTML - Log report on SPM processing to HTML file +% [] = spm_log2html(prog, val, options) print log to the html file named in output +% +% Example +% >> spm_log2html +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-17 Creation +% +% ----------------------------- Script History --------------------------------- + +% I guess there exists an xml -> html thingy I could use somewhere... + +prog_infos=functions(prog) +% jobname=sprintf('%s:', prog_infos.parentage{end:-1:1}); +% jobname(end)=[]; +jobname=sprintf('%s', prog_infos.parentage{1}); +logtxt={}; +logtxt{end+1}=['SPM logging for: ' jobname]; +htmlfile = fullfile(fileparts(getfield(spm_vol(val.data{1}{1}),'fname')),'log',[jobname '.html']); +logtxt{end+1}=['Into: ']; +logtxt{end+1}={'file' htmlfile}; +htmldir = fileparts(htmlfile); +% if exist(htmldir, 'dir') +% if length(dir(htmldir)) > 2 +% htmldir_old=fullfile(fileparts(htmldir), ['log_' datestr(now,30)]); +% movefile(htmldir,-) +% logtxt{end+1}=['Renaming older directory: ' ]; +% logtxt{end+1}={'folder', htmldir_old}; +% mkdir(htmldir) +% end +% end +if not(exist(htmldir, 'dir')) + logtxt{end+1}=['Creating new directory: ' ]; + logtxt{end+1}={'folder', htmldir}; + mkdir(htmldir) +end + +switch jobname + case 'estimate' + logtxt=log_realign(val,htmldir,logtxt); + case 'reslice'; + % to do + case 'estwrite_fun'; + % to do + otherwise + logtxt{end+1}=['Unknown function to log: ' jobname]; +end +log2html(htmlfile,logtxt) +return + +function [spname]=shortpathname(pname) +% shortens file names +spname=[pname(1:10) '...' pname(end-15:end)]; + +function [hpname]=htmlpathname(pname) +% Replace filesep in file path with slashes (/) for HTML compatibility +hpname = strrep(pname,filesep,'/'); + +function []=log2html(htmlfile, log) +% print out to html file +save(fullfile(fileparts(htmlfile),'spm_log2html.mat'),'log'); +fid=fopen(htmlfile,'wt'); +html_header(fid); +fprintf(fid,'

      '); +for i=1:length(log); + if ischar(log{i}) + if i>1 + fprintf(fid, '

      \n

      '); + end + fprintf(fid, '%s', log{i}); + else + switch log{i}{1} + case 'picture' + fprintf(fid, '',htmlpathname(log{i}{2}),htmlpathname(log{i}{2}),shortpathname(log{i}{2})); + case {'folder' 'file'} + fprintf(fid, '%s',htmlpathname(log{i}{2}),shortpathname(log{i}{2})); + end + end +end +fprintf(fid,'Done.

      \n\n'); +if fid > 2 + fclose(fid); + try + browser = '"C:\Documents and Settings\ndiayek\Local Settings\Application Data\Google\Chrome\Application\chrome.exe"' + system([browser ' "' htmlfile '"']); + catch + browser = '"C:\program Files\Mozilla Firefox\firefox.exe" '; + end; +end +return + +function [logtxt]=html_header(fid) +fprintf(fid,'\n'); +fprintf(fid,'\n'); +fprintf(fid,'

      Processing steps:

        '); +fprintf(fid,'
      1. realign'); +fprintf(fid,'
      2. segment'); +fprintf(fid,'
      3. normalize'); +fprintf(fid,'
      4. smooth'); +fprintf(fid,'
      5. design'); +fprintf(fid,'

      '); + + + +function [logtxt]=html_footer(htmlfile, logtxt) + + + +function [logtxt] = log_design(val,htmldir,logtxt) +% Log of DESIGN results + + +function [logtxt] = log_realign(val,htmldir,logtxt) +% Log of REALIGN results +mfile = which('spm_realign'); +if ~isequal(textread(mfile,'%s',4,'headerlines',82,'delimiter',' '),... + {'%', '$Id:', 'spm_realign.m', '433'}') % The native version at the time + logtxt{end+1}=sprintf('The spm_realign.m (%s) has changed! Default flags may also have changed.', mfile); + warning(logtxt(1)); +end +def_flags = struct('quality',1,'fwhm',5,'sep',4,'interp',2,'wrap',[0 0 0],'rtm',0,'PW','','graphics',1,'lkp',1:6); +flags =mergestructs(def_flags,val.eoptions); +if flags.graphics + opts = {fullfile(htmldir,'realign_estimate.png'),'-noui','-painters','-dpng'}; + fg = spm_figure('FindWin','Graphics'); + logtxt{end+1} = {'Plot of the Movement Parameters'}; + % export figure in image file + print(fg,opts{:}); + logtxt{end+1} = {'picture','realign_estimate.png'}; +else + logtxt{end+1}='Graphics must be generated for logging. Sorry...'; + % rp_file = [spm_str_manip(prepend(getfield(spm_vol(val.data{1}{1}),'fname'),'rp_'),'s') '.txt']; + % P=textread(rp_file); + % plot_parameters(P) +end +return + + +function [logtxt] = log_smooth(val,htmldir,logtxt) +% Log of SMOOTH results +mfile = which('spm_smooth'); +logtxt(end+1)='todo'; +return diff --git a/spm/spm_mm2vox.m b/spm/spm_mm2vox.m new file mode 100644 index 0000000..bc96eb8 --- /dev/null +++ b/spm/spm_mm2vox.m @@ -0,0 +1,52 @@ +function M = spm_mm2vox(V,XYZmm,dim) +%SPM_MM2VOX - Retrieve coordinates in voxels from millimeters +% [M] = spm_mm2vox(V,XYZmm,dim) +% +% Example +% >> spm_mm2vox +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-06-12 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<3 + dim=find(size(XYZmm) == 3); + if length(dim)~=1 + error('XYZmm must be a 3 by N matrix') + end +end +if ischar(V) + if exist(V,'file') + V=spm_vol(V); + end +end +if isstruct(V) + if isfield(V, 'mat') + V=V.mat; + end + if isfield(V, 'MAT') + V=V.MAT; + end +end +MAT=V; + +s = size(XYZmm); +if s(dim) ~= 3 + error('The %d-th dimension of XYZmm should be 3', dim) +end + +XYZmm = nd2array(XYZmm,dim); +XYZmm = [XYZmm ; ones(1, size(XYZmm,2))]; + +M = inv(MAT)*XYZmm; +M = M(1:3,:); +M = nd2array(M,-dim,s); diff --git a/spm/spm_mysections.m b/spm/spm_mysections.m new file mode 100644 index 0000000..f30274d --- /dev/null +++ b/spm/spm_mysections.m @@ -0,0 +1,58 @@ +function spm_mysections(input,varargin) +%SPM_MYSECTIONS - Display views +% [] = spm_mysections(input) +% +% Example +% >> spm_mysections +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-07-03 Creation +% +% ----------------------------- Script History --------------------------------- + +function spm_mysections(SPM,,hReg) +% rendering of regional effects [SPM{Z}] on orthogonal sections of +% colin27's brain +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = spm_figure('FindWin','Graphics'); +if isempty(Fgraph) + Fgraph = spm_figure('Create','Graphics'); +end +%spms = spm_get(1,'IMAGE','select image for rendering on'); +spms = fullfile(spm('dir'), 'canonical', 'single_subj_T1.nii'); +if ~exist(spms) + spms = fullfile(spm('dir'), 'canonical', 'single_subj_T1.mnc'); +end + +spm_results_ui('Clear',Fgraph); +spm_orthviews('Reset'); +global st +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; +spm_orthviews('Image',spms,[0.05 0.05 0.9 0.45]); +spm_orthviews MaxBB; +spm_orthviews('register',hReg); +spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +spm_orthviews('Redraw'); diff --git a/spm/spm_render2.m b/spm/spm_render2.m new file mode 100644 index 0000000..0cd4650 --- /dev/null +++ b/spm/spm_render2.m @@ -0,0 +1,278 @@ +function [varargout]=spm_render2(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +showbar=1 + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + +if isstruct(dat) & isfield(dat, 'rend') + rend=dat.rend; + mxmx=dat.mxmx; + mnmn=dat.mnmn; + clear dat; +else + + % get surface + %----------------------------------------------------------------------- + if nargin < 3, + rendfile = fullfile(spm('Dir'),'rend', 'render_single_subj.mat') + % rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); + end; + + % Perform the rendering + %======================================================================= + spm('Pointer','Watch') + load(rendfile); + + if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; + end; + + if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; + for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; + end; + if showbar, spm_progress_bar('Clear'); end; + + if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + + mx = zeros(length(rend),1)+eps; + mn = zeros(length(rend),1); + + for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; + end; + + mxmx = max(mx); + mnmn = min(mn); + +end + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = spm_figure('GetWin','Graphics'); +spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +if showbar, hght = 0.95; else, hght = 0.5; end; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 1, hght],'Visible','off'); +image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[rem(i-1,2)*0.5, floor((i-1)/2)*hght/nrow, 0.5, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Colors=[1 0 0; 1 .7 0 ]; + Colors=[1 0 1; 1 .7 0 ]; + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + ren = repmat(ren, [ 1 1 3]); + % KND: + rgb=[]; + for j=1:length(rend{i}.data), + X = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + col = Colors(j,:); + if isempty(rgb) + rgb=zeros([size(X) 3]); + end + rgb = rgb + repmat(reshape(col, [1,1,3]), size(X)).*repmat(X, [1 1 3]); + end + rgb= rgb*1.3+0.8*ren; + % rgb = rgb.*ren + ren.*repmat(all(rgb==0,3), [1 1 3]); + rgb=min(rgb,1); + rgb=max(rgb,0); + + % X = cell(3,1); + % for j=1:length(rend{i}.data), + % X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + % end + % for j=(length(rend{i}.data)+1):3 + % X{j}=zeros(size(X{1})); + % end + % rgb = zeros([size(ren) 3]); + % tmp = ren.*max(1-X{1}-X{2}-X{3},0); + % rgb(:,:,1) = tmp + X{1}; + % rgb(:,:,2) = tmp + X{2}; + % rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[rem(i-1,2)*0.5, floor((i-1)/2)*hght/nrow, 0.5, hght/nrow],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + drawnow + + end; +end; + +spm('Pointer') +if nargout>0 + varargout={rend,mxmx,mnmn}; +end +return; + diff --git a/spm/spm_sample_vol.m b/spm/spm_sample_vol.m new file mode 100644 index 0000000..e69de29 diff --git a/spm/spm_sections_colin27.m b/spm/spm_sections_colin27.m new file mode 100644 index 0000000..7349085 --- /dev/null +++ b/spm/spm_sections_colin27.m @@ -0,0 +1,30 @@ +function spm_sections(SPM,hReg) +% rendering of regional effects [SPM{Z}] on orthogonal sections of +% colin27's brain +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = spm_figure('FindWin','Graphics'); +%spms = spm_get(1,'IMAGE','select image for rendering on'); +spms= fullfile(spm('dir'), 'canonical', 'single_subj_T1.mnc'); +spm_results_ui('Clear',Fgraph); +spm_orthviews('Reset'); +global st +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; +spm_orthviews('Image',spms,[0.05 0.05 0.9 0.45]); +spm_orthviews MaxBB; +spm_orthviews('register',hReg); +spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +spm_orthviews('Redraw'); diff --git a/spm/spm_update.m b/spm/spm_update.m new file mode 100644 index 0000000..d95869d --- /dev/null +++ b/spm/spm_update.m @@ -0,0 +1,69 @@ +function spm_update(update) +% Check (and install) SPM8 updates from the FIL FTP server +% FORMAT spm_update +% This function will connect itself to the FIL FTP server, compare the +% version number of the updates with the one of the SPM installation +% currently in the MATLAB path and will display the outcome. +% +% FORMAT spm_update(update) +% Invoking this function with any input parameter will do the same as +% above but will also attempt to download and install the updates. +%__________________________________________________________________________ +% Copyright (C) 2010-2013 Wellcome Trust Centre for Neuroimaging + +% Guillaume Flandin +% $Id: spm_update.m 5235 2013-02-04 15:30:21Z guillaume $ + +url = 'ftp://ftp.fil.ion.ucl.ac.uk/spm/spm8_updates/'; + +if ~nargin + update = false; +else + update = true; +end + +[s,sts] = urlread(url); +if ~sts, error('Cannot access the FIL FTP server.'); end +n = regexp(s,'spm8_updates_r(\d.*?)\.zip','tokens','once'); +if isempty(n) + fprintf(' There are no updates available yet.\n'); + return; +else + n = str2double(n{1}); +end + +try + [v,r] = spm('Ver','',1); r = str2double(r); +catch + error('SPM cannot be found in MATLAB path.'); +end +if ~strcmp(v,'SPM8'), error('Your SPM version is %s and not SPM8',v); end +rs = [3042 3164 3408 3684 4010 4290 4667 5236]; +if isnan(r), r = rs(1); end +if floor(r) == 8 + try + r = rs(round((r-floor(r))*10)+1); + catch + r = rs(end); + end +end + +if n > r + fprintf(' A new version of SPM is available on:\n'); + fprintf(' %s\n',url); + fprintf(' (Your version: %d - New version: %d)\n',r,n); + + if update + d = spm('Dir'); + delete(get(0,'Children')); spm('clean'); evalc('spm_rmpath'); + try + s = unzip([url sprintf('spm8_updates_r%d.zip',n)], d); + fprintf(' %d files have been updated.\n',numel(s)); + catch + fprintf(' Update failed: check file permissions.\n'); + end + addpath(d); + end +else + fprintf(' Your version of SPM is up to date.\n'); +end diff --git a/spm2.m b/spm2.m new file mode 100644 index 0000000..e652f86 --- /dev/null +++ b/spm2.m @@ -0,0 +1,3 @@ +function [spm2path]=spm2(varargin) +% spm2() - starts SPM2 on Karim's computers +myspm('ver','spm2','do','run', varargin{:}) \ No newline at end of file diff --git a/spm5.m b/spm5.m new file mode 100644 index 0000000..dc2c4d5 --- /dev/null +++ b/spm5.m @@ -0,0 +1,3 @@ +function [spmpath]=spm5(varargin) +% spm2() - starts SPM5 on Karim's computers +spmpath = myspm('ver','spm5','do','run', varargin{:}); diff --git a/spm_defaults.m b/spm_defaults.m new file mode 100644 index 0000000..0b3b75d --- /dev/null +++ b/spm_defaults.m @@ -0,0 +1,126 @@ + +% Sets the defaults which are used by SPM +% +% FORMAT spm_defaults +%_______________________________________________________________________ +% +% This file is intended to be customised for the site. +% Individual users can make copies which can be stored in their own +% matlab subdirectories. If ~/matlab is ahead of the SPM directory +% in the MATLABPATH, then the users own personal defaults are used. +% +% Care must be taken when modifying this file +%_______________________________________________________________________ +% @(#)spm_defaults.m 2.23 John Ashburner, Andrew Holmes 03/04/16 + +global defaults + +% Misc +%======================================================================= +defaults.grid = 0.4; +defaults.cmdline = 0; +defaults.logfile = ''; +defaults.printstr = [];%spm_figure('DefPrintCmd'),'spm2.ps']; + +% File format specific +%======================================================================= +defaults.analyze.multivol = 0; +defaults.analyze.flip = 1; % <<= Very important. Relates to L/R +% Changed by KND: +% defaults.analyze.flip = 0; % <<= Very important. Relates to L/R +% but now in the CMU it's 1... + +% Stats defaults +%======================================================================= +defaults.stats.maxmem = 2^20; +defaults.stats.maxres = 64; +defaults.stats.fmri.ufp = 0.001; +defaults.stats.fmri.t = 16; +defaults.stats.fmri.t0 = 8; +defaults.stats.pet.ufp = 0.05; + +defaults.stats.fmri.t0 = 1; + +defaults.modality = 'FMRI'; + + +% Mask defaults +%======================================================================= +defaults.mask.thresh = 0.8; + +% Realignment defaults +%======================================================================= +defaults.realign.estimate.quality = 0.75; +defaults.realign.estimate.weight = 0; +defaults.realign.estimate.interp = 2; +defaults.realign.estimate.wrap = [0 0 0]; +defaults.realign.write.mask = 1; +defaults.realign.write.interp = 4; +defaults.realign.write.wrap = [0 0 0]; + +% Unwarp defaults +%======================================================================= +defaults.unwarp.estimate.fwhm = 4; +defaults.unwarp.estimate.basfcn = [10 10]; +defaults.unwarp.estimate.regorder= 1; +defaults.unwarp.estimate.regwgt = 1e5; +defaults.unwarp.estimate.soe = 1; +defaults.unwarp.estimate.rem = 1; +defaults.unwarp.estimate.jm = 0; +defaults.unwarp.estimate.noi = 5; +defaults.unwarp.estimate.expround= 'Average'; +% +% Unwarp uses defaults.realign.write +% defaults for writing. +% + +% Coregistration defaults +%======================================================================= +defaults.coreg.estimate.cost_fun = 'nmi'; +defaults.coreg.estimate.sep = [4 2]; +defaults.coreg.estimate.tol = [0.02 0.02 0.02 0.001 0.001 0.001 0.01 0.01 0.01 0.001 0.001 0.001]; +defaults.coreg.estimate.fwhm = [7 7]; +defaults.coreg.write.interp = 1; +defaults.coreg.write.wrap = [0 0 0]; +defaults.coreg.write.mask = 0; + +% Spatial Normalisation defaults +%======================================================================= +defaults.normalise.estimate.smosrc = 8; +defaults.normalise.estimate.smoref = 0; +defaults.normalise.estimate.regtype = 'mni'; +defaults.normalise.estimate.weight = ''; +defaults.normalise.estimate.cutoff = 25; +defaults.normalise.estimate.nits = 16; +defaults.normalise.estimate.reg = 1; +defaults.normalise.estimate.wtsrc = 0; +defaults.normalise.write.preserve = 0; +defaults.normalise.write.bb = [[-78 -112 -50];[78 76 85]]; +%defaults.normalise.write.vox = [2 2 2]; +defaults.normalise.write.vox = [3 3 3]; +defaults.normalise.write.interp = 1; +defaults.normalise.write.wrap = [0 0 0]; + +% Segmentation defaults +%======================================================================= +defaults.segment.estimate.priors = str2mat(... + fullfile(spm('Dir'),'apriori','gray.mnc'),... + fullfile(spm('Dir'),'apriori','white.mnc'),... + fullfile(spm('Dir'),'apriori','csf.mnc')); +defaults.segment.estimate.reg = 0.01; +defaults.segment.estimate.cutoff = 30; +defaults.segment.estimate.samp = 3; +defaults.segment.estimate.bb = [[-88 88]' [-122 86]' [-60 95]']; +defaults.segment.estimate.affreg.smosrc = 8; +defaults.segment.estimate.affreg.regtype = 'mni'; +%defaults.segment.estimate.affreg.weight = fullfile(spm('Dir'),'apriori','brainmask.mnc'); +defaults.segment.estimate.affreg.weight = ''; +defaults.segment.write.cleanup = 1; +defaults.segment.write.wrt_cor = 1; + +% Bias field estimation defaults +%======================================================================= +defaults.bias.nbins = 256; % Number of histogram bins +defaults.bias.reg = 0.01; % Regularisation +defaults.bias.cutoff = 30; % DCT frequency cutoff (mm) + diff --git a/spm_mm2vox.m b/spm_mm2vox.m new file mode 100644 index 0000000..bc96eb8 --- /dev/null +++ b/spm_mm2vox.m @@ -0,0 +1,52 @@ +function M = spm_mm2vox(V,XYZmm,dim) +%SPM_MM2VOX - Retrieve coordinates in voxels from millimeters +% [M] = spm_mm2vox(V,XYZmm,dim) +% +% Example +% >> spm_mm2vox +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-06-12 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<3 + dim=find(size(XYZmm) == 3); + if length(dim)~=1 + error('XYZmm must be a 3 by N matrix') + end +end +if ischar(V) + if exist(V,'file') + V=spm_vol(V); + end +end +if isstruct(V) + if isfield(V, 'mat') + V=V.mat; + end + if isfield(V, 'MAT') + V=V.MAT; + end +end +MAT=V; + +s = size(XYZmm); +if s(dim) ~= 3 + error('The %d-th dimension of XYZmm should be 3', dim) +end + +XYZmm = nd2array(XYZmm,dim); +XYZmm = [XYZmm ; ones(1, size(XYZmm,2))]; + +M = inv(MAT)*XYZmm; +M = M(1:3,:); +M = nd2array(M,-dim,s); diff --git a/spm_render2.m b/spm_render2.m new file mode 100644 index 0000000..0cd4650 --- /dev/null +++ b/spm_render2.m @@ -0,0 +1,278 @@ +function [varargout]=spm_render2(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +showbar=1 + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + +if isstruct(dat) & isfield(dat, 'rend') + rend=dat.rend; + mxmx=dat.mxmx; + mnmn=dat.mnmn; + clear dat; +else + + % get surface + %----------------------------------------------------------------------- + if nargin < 3, + rendfile = fullfile(spm('Dir'),'rend', 'render_single_subj.mat') + % rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); + end; + + % Perform the rendering + %======================================================================= + spm('Pointer','Watch') + load(rendfile); + + if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; + end; + + if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; + for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; + end; + if showbar, spm_progress_bar('Clear'); end; + + if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + + mx = zeros(length(rend),1)+eps; + mn = zeros(length(rend),1); + + for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; + end; + + mxmx = max(mx); + mnmn = min(mn); + +end + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = spm_figure('GetWin','Graphics'); +spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +if showbar, hght = 0.95; else, hght = 0.5; end; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 1, hght],'Visible','off'); +image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[rem(i-1,2)*0.5, floor((i-1)/2)*hght/nrow, 0.5, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Colors=[1 0 0; 1 .7 0 ]; + Colors=[1 0 1; 1 .7 0 ]; + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + ren = repmat(ren, [ 1 1 3]); + % KND: + rgb=[]; + for j=1:length(rend{i}.data), + X = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + col = Colors(j,:); + if isempty(rgb) + rgb=zeros([size(X) 3]); + end + rgb = rgb + repmat(reshape(col, [1,1,3]), size(X)).*repmat(X, [1 1 3]); + end + rgb= rgb*1.3+0.8*ren; + % rgb = rgb.*ren + ren.*repmat(all(rgb==0,3), [1 1 3]); + rgb=min(rgb,1); + rgb=max(rgb,0); + + % X = cell(3,1); + % for j=1:length(rend{i}.data), + % X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + % end + % for j=(length(rend{i}.data)+1):3 + % X{j}=zeros(size(X{1})); + % end + % rgb = zeros([size(ren) 3]); + % tmp = ren.*max(1-X{1}-X{2}-X{3},0); + % rgb(:,:,1) = tmp + X{1}; + % rgb(:,:,2) = tmp + X{2}; + % rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[rem(i-1,2)*0.5, floor((i-1)/2)*hght/nrow, 0.5, hght/nrow],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + drawnow + + end; +end; + +spm('Pointer') +if nargout>0 + varargout={rend,mxmx,mnmn}; +end +return; + diff --git a/spm_sections_colin27.m b/spm_sections_colin27.m new file mode 100644 index 0000000..7349085 --- /dev/null +++ b/spm_sections_colin27.m @@ -0,0 +1,30 @@ +function spm_sections(SPM,hReg) +% rendering of regional effects [SPM{Z}] on orthogonal sections of +% colin27's brain +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = spm_figure('FindWin','Graphics'); +%spms = spm_get(1,'IMAGE','select image for rendering on'); +spms= fullfile(spm('dir'), 'canonical', 'single_subj_T1.mnc'); +spm_results_ui('Clear',Fgraph); +spm_orthviews('Reset'); +global st +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; +spm_orthviews('Image',spms,[0.05 0.05 0.9 0.45]); +spm_orthviews MaxBB; +spm_orthviews('register',hReg); +spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +spm_orthviews('Redraw'); diff --git a/sprintf2.m b/sprintf2.m new file mode 100644 index 0000000..9f4fb87 --- /dev/null +++ b/sprintf2.m @@ -0,0 +1,86 @@ +function t = sprintf2(varargin) +%SPRINTF2 - Intelligent sprintf +% S = sprintf2(A) tries to guess what would be the best format for A +% +% S = sprintf2(FORMAT, A, ...) behaves like the native SPRINTF +% +% Example +% >> sprintf2(pi) +% +% See also: sprintf, fprintf + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-01 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin>1 + s= sprintf(varargin{:}); + return +end +y=varargin{1}; +t=''; +if isempty(y) + return +end + brakets = '[]'; +if numel(y)>1 & ~ischar(y) + t = [brakets(1)]; + if isvector(y) && numel(y)<100 || (iscell(y) && size(y,1)<100) + if size(y,1)==1 + sep = ','; + elseif iscell(y) + sep = sprintf('\t'); + else + sep = ';'; + end + if iscell(y) + y=transpose(y); + end + for i=1:numel(y) + if i>1 + t = [t sep]; + end + if iscell(y) + yy=y{i}; + if mod(i+1,size(y,1))==0 + t=[t sprintf('\n')]; + end + else + yy= y(i); + end + t = [t sprintf2(yy)]; + end + else + t = [ t '...' ]; + end + t = [t brakets(end)]; + return +end + + +if isnumeric(y) + t = sprintf('%g',y); +elseif ischar(y) + t = sprintf('%s',y); +elseif islogical(y) + if y + t = sprintf('true'); + else + t = sprintf('false'); + end +elseif iscell(y) + brakets ='{}'; + t = [ brakets(1) sprintf2(y{1}) brakets(end) ]; +elseif isa(y,'function_handle') + t = char(y); +else + t = sprintf('%s','???'); +end \ No newline at end of file diff --git a/sprintfcell.m b/sprintfcell.m new file mode 100644 index 0000000..7c982b7 --- /dev/null +++ b/sprintfcell.m @@ -0,0 +1,42 @@ +function S = sprintf2cell(F,varargin) +%SPRINTF2CELL - sprintf to separate cells +% [] = sprintf2cell(input) +% +% Example +% >> sprintf2cell +% +% See also: + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-10-05 Creation +% +% ----------------------------- Script History --------------------------------- + +S = {sprintf(F)}; +if nargin>1 + sz = cellfun('prodofsize',varargin); + u = unique(sz(sz~= 1)); + if numel(u) > 1 + error('arguments should be of the same size') + end + for i=1:u + A = {}; + for j = 1:(nargin-1) + if iscell(varargin{j}) + end + if sz(j)==1 + A{end+1} = varargin{j}; + else + A{end+1} = varargin{j}(i); + end + end + S{i,1} = sprintf(F,A{:}); + end +end \ No newline at end of file diff --git a/squeeze2.m b/squeeze2.m new file mode 100644 index 0000000..005f52c --- /dev/null +++ b/squeeze2.m @@ -0,0 +1,24 @@ +function b = squeeze(a,dims) +%SQUEEZE Remove singleton dimensions & squeeze some others +% B = SQUEEZE(A) behaves as the native SQUEEZE() +% B = SQUEEZE(A, [d1 d2 ... ]) reshapes so that dimensions d1, d2 etc. +% are merged into a single one +% +% For example, +% squeeze(rand(2,1,3)) +% is 2-by-3. +% +% See also SHIFTDIM, SQUEEZE. + +if nargin==1 + b=squeeze(a); +end + +if ndims(a)>2, + siz = size(a); + siz(siz==1) = []; % Remove singleton dimensions. + siz = [siz ones(1,2-length(siz))]; % Make sure siz is at least 2-D + b = reshape(a,siz); +else + b = a; +end diff --git a/ssetfield.m b/ssetfield.m new file mode 100644 index 0000000..9c3dc7a --- /dev/null +++ b/ssetfield.m @@ -0,0 +1,74 @@ +function [s]=ssetfield(s,varargin); +%SSETFIELD - Special SETFIELD for "field.subfield" structures +% S = SSETFIELD(S,'f.sf',V) sets the contents of the specified +% subfield "sf" of a given field "f" to the value V. +% This would be equivalent to the syntax: S.field.subfield = V. +% But it creates field "f" when missing. +% S must be a 1-by-1 structure. The changed structure is returned. + +% KND : 2005-07-06 : Adapted from SETFIELD. + +% NOT YET : +% +% S = SETFIELD(S,{i,j},'field.subfield.subsubfield',{k},{p},{q},V) +% is equivalent to the syntax: +% S(i,j).field(k).subfield(p).subsubfield(q) = V; +% Field references are passed as strings. +% +% See: SETFIELD + +% Check for sufficient inputs +if (isempty(varargin) | length(varargin) < 2) + error('KND:SSETFIELD:InsufficientInputs', 'Not enough input arguments.'); +end + +% The most common case +arglen = length(varargin); +strField = varargin{1}; +if isempty(strField) + error('KND:SSETFIELD:EmptyFieldname', 'Empty field name.'); +end +if (arglen==2) + if ~isempty(findstr('.', strField)) + [f,sf]=strtok(strField,'.'); + s1=ssetfield([], sf(2:end), varargin{end}); + s=mergestructs(s,setfield([], f, s1)); + else + s.(deblank(strField)) = varargin{end}; + %warning('MATLAB:SETFIELD:DeprecatedFunction:SingleInput', ... + % sprintf(['SETFIELD is deprecated. Please use: \n' ... + % 's.(fieldname) instead of setfield(s,fieldname)'])); + end + return +end +error('KND:SSETFIELD:WrongNumberOfInputs', 'Only 3 inputs are allowed.'); +return + + +% The following needs to bee adapted for recursion into fields & +% subfields. + +subs = varargin(1:end-1); +for i = 1:arglen-1 + index = varargin{i}; + if (isa(index, 'cell')) + types{i} = '()'; + elseif isstr(index) + types{i} = '.'; + subs{i} = deblank(index); % deblank field name + else + error('MATLAB:SETFIELD:DeprecatedFunction:InvalidType','Inputs must be either cell arrays or strings.'); + end +end + +% Perform assignment +try + s = builtin('subsasgn', s, struct('type',types,'subs',subs), varargin{end}); + %warning('MATLAB:SETFIELD:DeprecatedFunction:MultiInput', ... + % sprintf(['SETFIELD is deprecated. Please use: \n' ... + % 's(i,j).(fieldname)(k) instead of setfield(s,{i,j},fieldname,{k}) OR \n' ... + % 's(i,j).(field1).(field2) instead of setfield(s,{i,j},field1,field2)'])); +catch + error('MATLAB:SETFIELD:DeprecatedFunction', lasterr) +end + diff --git a/sstruct.m b/sstruct.m new file mode 100644 index 0000000..8291b73 --- /dev/null +++ b/sstruct.m @@ -0,0 +1,16 @@ +function [s]=sstruct(varargin) +%SSTRUCT - Special struct construction for dealing with fields & subfields +% [S]=SSTRUCT('field1',VALUES1,'field2.subfield1',VALUES2,...) creates +% a structure array with the specified fields, subfields and values. +% +% NB: Contrary to the native STRUCT, SSTRUCT doesn't create structure +% arrays from arrayed values. +% +% See also: sfield, issfield, sfieldnames +s=[]; +for i=1:2:length(varargin) + if ~ischar(varargin{i}) + error('KND:SSTRUCT:InvalidFieldname', 'Field names should be of type CHAR.'); + end + s=ssetfield(s, varargin{i}, varargin{i+1}); +end diff --git a/ssvep/flicker1.m b/ssvep/flicker1.m new file mode 100644 index 0000000..23cf7c0 --- /dev/null +++ b/ssvep/flicker1.m @@ -0,0 +1,50 @@ +% rotating hemifield flickering checkerboard +rcycles = 8; % number of white/black circle pairs +tcycles = 24; % number of white/black angular segment pairs (integer) +flicker_freq = 4; % full cycle flicker frequency (Hz) +flick_dur = 1/flicker_freq/2; +period = 30; % rotation period (sec) +[w, rect] = SCREEN('OpenWindow', 0, 128); +HideCursor +xc = rect(3)/2; +yc = rect(4)/2; +% make stimulus +hi_index=255; +lo_index=0; +bg_index =128; +xysize = rect(4); +s = xysize/sqrt(2); % size used for mask +xylim = 2*pi*rcycles; +[x,y] = meshgrid(-xylim:2*xylim/(xysize-1):xylim, - ... +xylim:2*xylim/(xysize-1):xylim); +at = atan2(y,x); +checks = ((1+sign(sin(at*tcycles)+eps) .* ... +sign(sin(sqrt(x.^2+y.^2))))/2) * (hi_index-lo_index) + lo_index; +circle = x.^2 + y.^2 <= xylim^2; +checks = circle .* checks + bg_index * ~circle; +t(1) = SCREEN('MakeTexture', w, checks); +t(2) = SCREEN('MakeTexture', w, hi_index - checks); % reversed contrast +flick = 1; +flick_time = 0; +start_time = GetSecs; +while (1) % animation loop +thetime = GetSecs - start_time; % time (sec) since loop started +if thetime > flick_time % time to reverse contrast? +flick_time = flick_time + flick_dur; % set next flicker time +flick = 3 - flick; +end +SCREEN('DrawTexture', w, t(flick)); +% draw mask +theta = 2*pi * mod(thetime, period)/period; +st = sin(theta); +ct = cos(theta); +xy = s * [-st,-ct; -st-ct,st-ct; st-ct,st+ct; st,ct] + ... +ones(4,1) * [xc yc]; +SCREEN('FillPoly', w, bg_index, xy); +SCREEN('Flip', w); +if KbCheck +break % exit loop upon key press +end +end +ShowCursor +SCREEN('Close',w); \ No newline at end of file diff --git a/staircase/CreateStaircase.m b/staircase/CreateStaircase.m new file mode 100755 index 0000000..4cceb0c --- /dev/null +++ b/staircase/CreateStaircase.m @@ -0,0 +1,37 @@ +function [staircase] = CreateStaircase(ptarget,xstart,sstart,dstart,chancefloor) + +if nargin < 5 + chancefloor = false; +end +if nargin < 4 + error('Missing input argument(s).'); +end + +staircase = struct; + +staircase.ptarget = ptarget; + +staircase.i = 1; +staircase.x = nan.*ones(1, 1000); +staircase.r = nan.*ones(1, 1000); + +staircase.scur = staircase.stepinfo(1,1); +staircase.dcur = staircase.stepinfo(2,1); +staircase.ncur = staircase.stepinfo(3,1); + +staircase.j = 0; + +staircase.x = nan(1,1000); staircase.x(1) = xstart; +staircase.r = nan(1,1000); +staircase.p = nan(1,1000); + +staircase.scur = sstart; +staircase.dcur = dstart; +staircase.wcur = 0; + +staircase.nstp = 0; +staircase.istp = nan(1,1000); + +staircase.chancefloor = chancefloor; + +end diff --git a/staircase/GetStaircaseResults.m b/staircase/GetStaircaseResults.m new file mode 100755 index 0000000..9bd806d --- /dev/null +++ b/staircase/GetStaircaseResults.m @@ -0,0 +1,45 @@ +function [results] = GetStaircaseResults(staircase) + +if nargin < 1 + error('Missing input argument.'); +end + +results = struct; + +results.ptarget = staircase.ptarget; + +results.n = staircase.i-1; + +results.x = staircase.x(1:results.n); +results.r = staircase.r(1:results.n); +results.p = staircase.p(1:results.n); + +results.nstp = length(find(staircase.istp <= results.n)); +results.istp = staircase.istp(1:results.nstp); + +results.nrev = staircase.nrev; +results.irev = staircase.irev(1:results.nrev); + +results.ndec = staircase.ndec; +results.idec = staircase.idec; +if isempty(icvg) + if isempty(results.idec) + icvg = []; + else + icvg = results.idec(end); + end +elseif icvg > results.n + icvg = nan; +end +results.icvg = icvg; +if ~isnan(icvg) + results.pc = mean(results.r(icvg:end)); + try + results.x0 = quantile(results.x(icvg:end), [0.25,0.5,0.75]); + catch + results.x0 =[NaN,median(results.x(icvg:end)),NaN]; + end +else + results.pc = nan; + results.x0 = [nan,nan,nan]; +end diff --git a/staircase/GetStaircaseThreshold.m b/staircase/GetStaircaseThreshold.m new file mode 100755 index 0000000..ffbbe06 --- /dev/null +++ b/staircase/GetStaircaseThreshold.m @@ -0,0 +1,23 @@ +function [results] = GetStaircaseThreshold(results,iout) + +if nargin < 2 + error('Missing input argument(s).'); +end + +iout = min(iout,length(results.istp)-1); +i1st = results.istp(iout)+1; + +xthres = 10^mean(log10(results.x(results.istp(iout+1:end)))); +pthres = []; + +rthres = results.r(i1st:end); +if all(ismember(rthres,[0 1])) + pthres = mean(rthres); +elseif all(ismember(rthres,[-2 -1 +1 +2])) + pthres = 0.5*(nnz(rthres == +1)/nnz(abs(rthres) == 1)+nnz(rthres == +2)/nnz(abs(rthres) == 2)); +end + +results.xthres = xthres; +results.pthres = pthres; + +end \ No newline at end of file diff --git a/staircase/GetStaircaseVariable.m b/staircase/GetStaircaseVariable.m new file mode 100755 index 0000000..2ba72e1 --- /dev/null +++ b/staircase/GetStaircaseVariable.m @@ -0,0 +1,7 @@ +function [x] = GetStaircaseVariable(staircase) + +if nargin < 1, error('Not enough input arguments.'); end + +x = staircase.x(staircase.i); + +end diff --git a/staircase/RefreshStaircase.m b/staircase/RefreshStaircase.m new file mode 100755 index 0000000..4f2a4fc --- /dev/null +++ b/staircase/RefreshStaircase.m @@ -0,0 +1,37 @@ +function [staircase] = RefreshStaircase(staircase) + +if nargin < 1 + error('missing input argument.'); +end + +if ~isnan(staircase.r(staircase.i)) + if ~mod(staircase.i-staircase.j,staircase.dcur) + staircase.nstp = staircase.nstp+1; + staircase.istp(staircase.nstp) = staircase.i; + rcur = staircase.r(staircase.i-staircase.dcur+1:staircase.i); + if all(ismember(rcur,[0,1])) + p = mean(rcur); + else + error('unable to refresh staircase.'); + end + if staircase.chancefloor + pcur = max(p,0.5); + else + pcur = p; + end + staircase.wcur = staircase.ptarget-pcur; + staircase.p(staircase.i) = p; + staircase.x(staircase.i+1) = staircase.x(staircase.i)*10^(staircase.wcur*staircase.scur); + else + staircase.p(staircase.i) = 0; + staircase.x(staircase.i+1) = staircase.x(staircase.i); + end + staircase.i = staircase.i+1; + if staircase.i == length(staircase.x) + staircase.x = [staircase.x,nan(1,staircase.i)]; + staircase.r = [staircase.r,nan(1,staircase.i)]; + staircase.p = [staircase.p,nan(1,staircase.i)]; + end +end + +end \ No newline at end of file diff --git a/staircase/SetStaircaseResponse.m b/staircase/SetStaircaseResponse.m new file mode 100755 index 0000000..882da21 --- /dev/null +++ b/staircase/SetStaircaseResponse.m @@ -0,0 +1,10 @@ +function [staircase] = SetStaircaseResponse(staircase,x,r) + +if nargin < 3 + error('Missing input argument(s).'); +end + +staircase.x(staircase.i) = x; +staircase.r(staircase.i) = r; + +end \ No newline at end of file diff --git a/staircase/ShowStaircaseResults.m b/staircase/ShowStaircaseResults.m new file mode 100644 index 0000000..352ede4 --- /dev/null +++ b/staircase/ShowStaircaseResults.m @@ -0,0 +1,20 @@ +function ShowStaircaseResults(results) + +if nargin < 1, error('Not enough input arguments.'); end + +figure; +hold on +ylim(10.^[floor(log10(min(results.x))),ceil(log10(max(results.x)))]); +if ~isnan(results.icvg) + area([results.icvg,results.n], results.x0(3)*[1,1], results.x0(1), 'FaceColor', [0.8,1.0,0.8], 'EdgeColor', 'none'); + plot([results.icvg,results.n], results.x0(2)*[1,1], 'g-'); + plot(results.icvg*[1,1], ylim, 'k-'); +end +plot(results.istp, results.x(results.istp), 'b-'); +plot(results.irev, results.x(results.irev), 'r.'); +plot(results.idec(1:results.ndec), results.x(results.idec(1:results.ndec)), 'ro'); +hold off +set(gca, 'Layer', 'top', 'YScale', 'lin', 'Box', 'on'); +xlabel('Trial index'); +ylabel('Psychophysical variable'); +title(sprintf('Psychophysical threshold = %.2g = 10^{%.2f}, probability correct = %.3f', results.x0(2), log10(results.x0(2)), results.pc)); diff --git a/staircase/UpdateStaircase.m b/staircase/UpdateStaircase.m new file mode 100755 index 0000000..6bf5a61 --- /dev/null +++ b/staircase/UpdateStaircase.m @@ -0,0 +1,20 @@ +function [staircase] = UpdateStaircase(staircase,xnew,snew,dnew) + +if nargin < 4 + error('Missing input argument(s).'); +end + +staircase = RefreshStaircase(staircase); +staircase.j = staircase.i-1; + +if ~isempty(xnew) + staircase.x(staircase.i) = xnew; +end +if ~isempty(snew) + staircase.scur = snew; +end +if ~isempty(dnew) + staircase.dcur = dnew; +end + +end \ No newline at end of file diff --git a/staircase/Weibull.m b/staircase/Weibull.m new file mode 100644 index 0000000..788e90c --- /dev/null +++ b/staircase/Weibull.m @@ -0,0 +1,13 @@ +function y = Weibull(p,x) +%y = Weibull(p,x) +% +%Parameters: p.b slope +% p.t threshold yeilding ~80% correct +% x intensity values. + +g = 0.5; %chance performance +e = (.5)^(1/3); %threshold performance ( ~80%) + +%here it is. +k = (-log( (1-e)/(1-g)))^(1/p.b); +y = 1- (1-g)*exp(- (k*x/p.t).^p.b); diff --git a/staircase/old/CreateStaircase.m b/staircase/old/CreateStaircase.m new file mode 100644 index 0000000..299bb3c --- /dev/null +++ b/staircase/old/CreateStaircase.m @@ -0,0 +1,39 @@ +function [staircase] = CreateStaircase(pctarget, stepinfo, xstart, pfdir) +% s = CreateStaircase(pctarget, stepinfo, xstart, pfdir) +% +% pctarget: +if nargin < 4, pfdir = +1; end +if nargin < 3, error('Not enough input arguments.'); end + +staircase = struct; + +staircase.pctarget = pctarget; +staircase.stepinfo = stepinfo; +staircase.pfdir = sign(pfdir); + +staircase.i = 1; +staircase.x = nan.*ones(1, 1000); +staircase.r = nan.*ones(1, 1000); + +staircase.scur = staircase.stepinfo(1,1); +staircase.dcur = staircase.stepinfo(2,1); +staircase.ncur = staircase.stepinfo(3,1); + +staircase.j = 0; +staircase.w = []; + +staircase.wcur = 0; +staircase.wold = 0; + +staircase.nstp = 0; +staircase.istp = nan.*ones(1, 1000); + +staircase.nrev = 0; +staircase.irev = nan.*ones(1, 1000); + +staircase.ndec = 0; +staircase.idec = nan.*ones(1, size(staircase.stepinfo, 2)-1); + +staircase.x(1) = xstart; + +end diff --git a/staircase/old/GetStaircaseResults.m b/staircase/old/GetStaircaseResults.m new file mode 100644 index 0000000..c1aca3c --- /dev/null +++ b/staircase/old/GetStaircaseResults.m @@ -0,0 +1,44 @@ +function [results] = GetStaircaseResults(staircase, icvg) + +if nargin < 2, icvg = []; end +if nargin < 1, error('Not enough input arguments.'); end + +results = struct; + +results.pctarget = staircase.pctarget; +results.stepinfo = staircase.stepinfo; +results.pfdir = staircase.pfdir; + +results.n = staircase.i-1; +results.x = staircase.x(1:results.n); +results.r = staircase.r(1:results.n); + +results.nstp = staircase.nstp; +results.istp = staircase.istp(1:results.nstp); + +results.nrev = staircase.nrev; +results.irev = staircase.irev(1:results.nrev); + +results.ndec = staircase.ndec; +results.idec = staircase.idec; +if isempty(icvg) + if isempty(results.idec) + icvg = []; + else + icvg = results.idec(end); + end +elseif icvg > results.n + icvg = nan; +end +results.icvg = icvg; +if ~isnan(icvg) + results.pc = mean(results.r(icvg:end)); + try + results.x0 = quantile(results.x(icvg:end), [0.25,0.5,0.75]); + catch + results.x0 =[NaN,median(results.x(icvg:end)),NaN]; + end +else + results.pc = nan; + results.x0 = [nan,nan,nan]; +end diff --git a/staircase/old/GetStaircaseVariable.m b/staircase/old/GetStaircaseVariable.m new file mode 100644 index 0000000..2ba72e1 --- /dev/null +++ b/staircase/old/GetStaircaseVariable.m @@ -0,0 +1,7 @@ +function [x] = GetStaircaseVariable(staircase) + +if nargin < 1, error('Not enough input arguments.'); end + +x = staircase.x(staircase.i); + +end diff --git a/staircase/old/ShowStaircaseResults.m b/staircase/old/ShowStaircaseResults.m new file mode 100644 index 0000000..352ede4 --- /dev/null +++ b/staircase/old/ShowStaircaseResults.m @@ -0,0 +1,20 @@ +function ShowStaircaseResults(results) + +if nargin < 1, error('Not enough input arguments.'); end + +figure; +hold on +ylim(10.^[floor(log10(min(results.x))),ceil(log10(max(results.x)))]); +if ~isnan(results.icvg) + area([results.icvg,results.n], results.x0(3)*[1,1], results.x0(1), 'FaceColor', [0.8,1.0,0.8], 'EdgeColor', 'none'); + plot([results.icvg,results.n], results.x0(2)*[1,1], 'g-'); + plot(results.icvg*[1,1], ylim, 'k-'); +end +plot(results.istp, results.x(results.istp), 'b-'); +plot(results.irev, results.x(results.irev), 'r.'); +plot(results.idec(1:results.ndec), results.x(results.idec(1:results.ndec)), 'ro'); +hold off +set(gca, 'Layer', 'top', 'YScale', 'lin', 'Box', 'on'); +xlabel('Trial index'); +ylabel('Psychophysical variable'); +title(sprintf('Psychophysical threshold = %.2g = 10^{%.2f}, probability correct = %.3f', results.x0(2), log10(results.x0(2)), results.pc)); diff --git a/staircase/old/UpdateStaircase.m b/staircase/old/UpdateStaircase.m new file mode 100644 index 0000000..ae12961 --- /dev/null +++ b/staircase/old/UpdateStaircase.m @@ -0,0 +1,63 @@ +function [staircase] = UpdateStaircase(staircase, r, x) +% sc2 = UpdateStaircase(sc1, accuracy) +% sc1: Staircase struct previously initialized +% accuracy = 0 (incorrect) or 1 (correct) +% Ouput: +% sc2: Updated staircase struct + +if nargin < 2, error('Not enough input arguments.'); end + +staircase.r(staircase.i) = r; +if nargin>2 + staircase.x(staircase.i) = x; +end + +if ~mod(staircase.i-staircase.j, staircase.dcur) + staircase.nstp = staircase.nstp+1; + staircase.istp(staircase.nstp) = staircase.i; + % Number of correct responses on the last 'dcur' trials (see stepinfo) + nc = sum(staircase.r(staircase.i-staircase.dcur+1:staircase.i)); + if isempty(staircase.w) + staircase.w = GetStaircaseWeights(staircase.pctarget, staircase.dcur); + end + % Get the weights for 'nc' correct responses + staircase.wcur = staircase.w(nc+1); + if abs(sign(staircase.wcur)-sign(staircase.wold)) > 1 + % We have a reversal at this trial... + staircase.nrev = staircase.nrev+1; + staircase.irev(staircase.nrev) = staircase.i; + % If # of reversals for this size of steps has been reached go to + % the next + if staircase.nrev == staircase.ncur + staircase.ndec = staircase.ndec+1; + staircase.idec(staircase.ndec) = staircase.i; + staircase.scur = staircase.stepinfo(1,staircase.ndec+1); + staircase.dcur = staircase.stepinfo(2,staircase.ndec+1); + staircase.ncur = staircase.ncur+staircase.stepinfo(3,staircase.ndec+1); + staircase.w = GetStaircaseWeights(staircase.pctarget, staircase.dcur); + staircase.j = staircase.i; + end + end + staircase.wold = staircase.wcur; + staircase.x(staircase.i+1) = staircase.x(staircase.i)*10^(staircase.pfdir*staircase.wcur*staircase.scur); +else + staircase.x(staircase.i+1) = staircase.x(staircase.i); +end + +staircase.i = staircase.i+1; + +if staircase.i == length(staircase.x) + staircase.x = [staircase.x,nan(1, staircase.i)]; + staircase.r = [staircase.r,nan(1, staircase.i)]; +end +if staircase.nrev == length(staircase.irev) + staircase.irev = [staircase.irev,nan(1, staircase.nrev)]; +end + +end + +function [w] = GetStaircaseWeights(pc, d) +b = factorial(d)./(factorial(0:+1:d).*factorial(d:-1:0)).*pc.^(0:+1:d).*(1-pc).^(d:-1:0); +w = pc-linspace(0, 1, d+1); +w = w./sum(b.*abs(w)); +end diff --git a/staircase/testStaircase.m b/staircase/testStaircase.m new file mode 100644 index 0000000..70d9a42 --- /dev/null +++ b/staircase/testStaircase.m @@ -0,0 +1,76 @@ +function sc=run +set(0,'DefaultFigureWindowStyle','docked') +%addpath('/Users/ndiaye/mtoolbox/matlab-washington') +p.t = .5; +p.b = 2; +example(p) +coh = @(x)10.^-x; +ptarget = .7; + +xstart=-log10(0.3); +sstart = .1; +dstart = 4; +chancefloor = 1; + +%sc= CreateStaircase(.7,[[0.1;10;4],[0.02;2;Inf]],x,-1); +sc= CreateStaircase(ptarget,xstart,sstart,dstart,chancefloor) + +Weibull(p,xstart) +n=300; +for i=1:n; + x=GetStaircaseVariable(sc); + r = randlength(DIRS) + error('No directory found for brainstorm3') +end +brainstorm \ No newline at end of file diff --git a/start_eeglab.m b/start_eeglab.m new file mode 100644 index 0000000..06980c8 --- /dev/null +++ b/start_eeglab.m @@ -0,0 +1,4 @@ +% starts eeglab +addpath(fullfile(fileparts(fileparts(mfilename('fullpath'))), 'mtoolbox', 'eeglab')); +addpath(fullfile(fileparts(fileparts(mfilename('fullpath'))), 'mtoolbox', 'eeglab2008October01_beta')); +eeglab diff --git a/start_spm.m b/start_spm.m new file mode 100644 index 0000000..06fcd75 --- /dev/null +++ b/start_spm.m @@ -0,0 +1,3 @@ +mypath +addpath(fullfile(HOMEDIR, 'mtoolbox', 'spm2'), '-BEGIN' ) +spm \ No newline at end of file diff --git a/startup.m b/startup.m new file mode 100644 index 0000000..21260ef --- /dev/null +++ b/startup.m @@ -0,0 +1,120 @@ +DoMatlabUpdate = false; +disp('Hi Karim,') +[hostname,hostname]=system('hostname'); +switch upper(deblank(hostname)) + case 'D5BDS81J' + disp('Welcome on FREDERIC''s PC!') + case 'IMAGERIE2-PV' + disp('Welcome on STEPHANIE''s PC!') + DoMatlabUpdate = 0; + case 'MONTBLANC' + disp('Welcome on the MONTBLANC Linux Blast @ LabNIC!') + case 'KARIMND' + + disp('Welcome on the LENA138/Windows station!') + homedir = 'E:/ndiaye/home'; + otherwise + if ~isempty(strfind(lower(hostname), 'chups.jussieu.fr')) + disp('Welcome at the COGIMAGE Lab!') + lcd=cd;cd('~');homedir=cd;cd(lcd); + switch strrep(hostname, '.chups.jussieu.fr', '') + case 'lena138.lena' + disp('Welcome on the COGIMAGE Lena138 station!') + %lcd=cd;cd('~');homedir=cd;cd(lcd); + end + end +end +disp(' ') + +[HOMEDIR]=mypath + +if not(exist(HOMEDIR, 'dir')) + warning(sprintf(['Directory %s does not exist!\n' ... + 'HOMEDIR variable unset'], HOMEDIR)) + clear HOMEDIR +else + disp(sprintf('HOMEDIR variable set to: %s', HOMEDIR)) + % addpath(fullfile(HOMEDIR, 'mtoolbox', 'lib')); + addpath(fullfile(HOMEDIR, 'matlab')); + %cd(fullfile(HOMEDIR, 'matlab')) +end + + +[USBDIR]=usbpath; + + +if isempty(USBDIR) || any(isnan(USBDIR)) + warning(sprintf(['No USB key found.\n' ... + 'USBDIR variable unset'])) + clear USBDIR +elseif not(exist(USBDIR, 'dir')) + warning(sprintf(['Directory %s does not exist!\n' ... + 'USBDIR variable unset'], USBDIR)) + clear USBDIR +else + disp(sprintf('USB key is: %s', USBDIR)) + % addpath(fullfile(USBDIR, 'mtoolbox', 'lib')); + addpath(fullfile(USBDIR, 'matlab')); + if DoMatlabUpdate + if exist('C:\Program Files\WinMerge') + if exist(HOMEDIR,'dir') && exist(USBDIR,'dir') + system(['"C:\Program Files\WinMerge\WinMerge.exe" /r /e /f "*.m" /x ' fullfile(HOMEDIR, 'matlab') ' ' fullfile(USBDIR, 'matlab')]) + end + end + end +end + +% try +% addpath 'C:\Program Files\MATLAB704\toolbox\matlab\datafun\' +% end + +% cd(fullfile(HOMEDIR, 'matlab')) + +if ~exist('DoMatlabUpdate','var') + DoMatlabUpdate = 1; +end + +% SVN update +switch upper(deblank(hostname)) + case 'D5BDS81J' + disp('SVU update...') + !svn update + !svn commit --message "Automatic update by startup.m" + case 'IMAGERIE2-PV' + disp('Welcome on STEPHANIE''s PC!') + case 'MONTBLANC' + disp('Welcome on the MONTBLANC Linux Blast!') + case 'LENA138.LENA.CHUPS.JUSSIEU.FR' + disp('SVN update...') + !svn update ~/matlab + !svn commit ~/matlab --message "Automatic update by startup.m" + case 'KARIMND' + disp('SVN update...') + !svn update . + !svn commit . --message "Automatic update by startup.m" +end + +if DoMatlabUpdate + try + matlabupdate + catch + warning('Couldn''t update your MATLAB scripts & functions...') + end +end +DoMatlabUpdate = 0; + +if exist('G:/mtoolbox/javaclasses') + javaaddpath G:/mtoolbox/javaclasses +end +if exist('g:\mtoolbox\Psychtoolbox\PsychJava') + javaaddpath g:\mtoolbox\Psychtoolbox\PsychJava +end +if exist('F:/mtoolbox/javaclasses') + javaaddpath F:/mtoolbox/javaclasses +end + +% warning('off','MATLAB:dispatcher:nameConflict') + +disp(' '); +disp(' '); + diff --git a/stat/alpha_significance.m b/stat/alpha_significance.m new file mode 100644 index 0000000..af49f18 --- /dev/null +++ b/stat/alpha_significance.m @@ -0,0 +1,18 @@ +function [sig,alpha]=alpha_significance(alpha,pv,alphas,pThresholds) +% [sig,alpha]=alpha_significance(alpha,pv,alphas, pThresholds) +% +% This function finds the significant value according to a given alpha with +% FWER specified by alphas and their corresponding thresholds +% +% Ex: +% >> [alphas,pThresholds,pv]=permttest_norm2(X1,X2); +% >> [sig,alpha]=alpha_significance(0.05,pv,alphas,pThresholds); +% +% In this example, you compare X1 and X2, sig will have 1 at any position +% where significativity is below 0.05 + +i=max(find(alphas?.50?for?factor?2? +% and?W?=?0.68,?p?>?.50?for?the?interaction;? +% this?test?cannot?be?performed?for?factor?1?since?it?has?only?two?levels +% but?we?generated?the?data?such?that?it?is?also?homogenous. +% The?Greenhouse?Geiser?and?the?Huynh?Feldt?epsilons?are?close?to?1?so?that +%?we?don?t?need?to?use?corrections?(Huynh,?1978,?Rouanet?and?Lepine,?1970). + +% Effect?name? SS?? dl?? MS?? F?? p<0.001 +% Factor?1?? 10621?? 1?? 10621?? 76.8? ***? +% Error?? 2073?? 15?? 135???? +% Factor?2?? 11784?? 4?? 8196?? 16.4? *** +% Error?? 4378?? 60? ?72.9???? +% Interaction??2250?? 4?? 562?? 6.52? ***? +% Error?? 5171?? 60?? 86.2???? +% Subject: F(1,?15)?=?710,?p?F) +% Residuals 4 349.13 87.28 +% +% Error: Subject:Task +% Df Sum Sq Mean Sq F value Pr(>F) +% Task 1 30.0000 30.0000 7.3469 0.05351 . +% Residuals 4 16.3333 4.0833 +% --- +% Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 +% +% Error: Subject:Valence +% Df Sum Sq Mean Sq F value Pr(>F) +% Valence 2 9.8000 4.9000 1.4591 0.2883 +% Residuals 8 26.8667 3.3583 +% +% Error: Subject:Task:Valence +% Df Sum Sq Mean Sq F value Pr(>F) +% Task:Valence 2 1.4000 0.7000 0.2907 0.7553 +% Residuals 8 19.2667 2.4083 +% +% But to perform post-hoc we need to go through LME +% +% require(MASS) +% require(nlme) +% require(multcomp) +% lme.ex4 <- lme(Recall ~ Task + Valence, random = ~1 | Subject/(Task*Valence), data = data.example4) + + +a= [ 8 9 5 7 9 10 12 13 14 16 13 14 13 13 12 15 16 14 12 14 15 17 18 20 6 7 9 4 9 10 ]; +a = reshape(a,[3 2 5]) +myanova(a,2,1:2); + +%% http://blog.gribblelab.org/2009/03/09/repeated-measures-anova-using-r/ +% > dv <- c(1,3,4,2,2,3,2,5,6,3,4,4,3,5,6) +% > subject <- factor(c("s1","s1","s1","s2","s2","s2","s3","s3","s3", +% + "s4","s4","s4","s5","s5","s5")) +% > myfactor <- factor(c("f1","f2","f3","f1","f2","f3","f1","f2","f3", +% + "f1","f2","f3","f1","f2","f3")) +% > mydata <- data.frame(dv, subject, myfactor) +% +% Error: subject +% Df Sum Sq Mean Sq F value Pr(>F) +% Residuals 4 12.4 3.1 +% +% Error: subject:myfactor +% Df Sum Sq Mean Sq F value Pr(>F) +% myfactor 2 14.9333 7.4667 13.576 0.002683 ** +% Residuals 8 4.4000 0.5500 +% +% > require(nlme) +% > am2 <- lme(dv ~ myfactor, random = ~1|subject/myfactor, data=mydata) +% > anova(am2) +% numDF denDF F-value p-value +% (Intercept) 1 8 60.40869 0.0001 +% myfactor 2 8 13.57575 0.0027 +% +% > require(multcomp) +% > summary(glht(am2,linfct=mcp(myfactor="Tukey"))) +% Linear Hypotheses: +% Estimate Std. Error z value Pr(>|z|) +% f2 - f1 == 0 1.600 0.469 3.411 0.00185 ** +% f3 - f1 == 0 2.400 0.469 5.117 < 1e-04 *** +% f3 - f2 == 0 0.800 0.469 1.706 0.20308 +% +d = [ + 1 1 1 1 + 2 3 1 2 + 3 4 1 3 + 4 2 2 1 + 5 2 2 2 + 6 3 2 3 + 7 2 3 1 + 8 5 3 2 + 9 6 3 3 + 10 3 4 1 + 11 4 4 2 + 12 4 4 3 + 13 3 5 1 + 14 5 5 2 + 15 6 5 3 ] +X = reshape(d(:,2),[ 3 5 ]); +[p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(X,1,1) + +%[Qc,HSDc] = tukeyhsd(dfe,ng,alpha,ns,MSe) + + +% [Qc,HSDc,Q,pairs,MX] = tukeyhsd(X,nf,alpha,fx,dfe,SSe) +[Qc,HSDc,Q,pairs,MX] = tukeyhsd(X,1,0.05) + + + +%% [R] Tukey HSD (or other post hoc tests) following repeated measures ANOVA +% https://stat.ethz.ch/pipermail/r-help/2008-May/163433.html +% +% ## Example +% require(MASS) ## for oats data set +% require(nlme) ## for lme() +% require(multcomp) ## for multiple comparison stuff +% +% Aov.mod <- aov(Y ~ N + V + Error(B/V), data = oats) +% Lme.mod <- lme(Y ~ N + V, random = ~1 | B/V, data = oats) +% +% summary(Aov.mod) +% anova(Lme.mod) +% +% summary(Lme.mod) +% summary(glht(Lme.mod, linfct=mcp(V="Tukey"))) +% +% E.g. with gribblelab data +% summary(glht(l, linfct=mcp(myfactor="Tukey"))) + + +%% http://yatani.jp/HCIstats/PostHoc +% Post-hoc Tests +% > aov <- aov(Value ~ factor(Group) + Error(factor(Participant)/factor(Group)), data) +% > summary(aov) +% Error: factor(Participant) +% Df Sum Sq Mean Sq F value Pr(>F) +% Residuals 7 5.1667 0.7381 +% Error: factor(Participant):factor(Group) +% Df Sum Sq Mean Sq F value Pr(>F) +% factor(Group) 2 22.7500 11.3750 10.92 0.001388 ** +% Residuals 14 14.5833 1.0417 +% + +X =[ 1 2 4 1 1 2 2 3 3 4 4 2 3 4 4 3 4 5 3 5 5 3 4 6] +X = reshape(X,[8 5])'; +myanova(X,1,1) + + + + diff --git a/stat/anovaeffects.m b/stat/anovaeffects.m new file mode 100644 index 0000000..9e59395 --- /dev/null +++ b/stat/anovaeffects.m @@ -0,0 +1,16 @@ +function [fx]=anovaeffects(nf,m) +% anovaeffects - List effects and their interaction in a factorial design +% [fx]=anovaeffects(nf) +% List main effects and interaction(s) in factorial design with [nf] factors +% [fx] is a N-by-1 cell array +% +% [fx]=anovaeffects(nf,m) +% m: maximum number of interacting factors (default: 3) + +fx={}; +if nargin<2 + m=min(nf,3); +end +for i=1:m + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end diff --git a/stat/anovalevels.m b/stat/anovalevels.m new file mode 100644 index 0000000..eef2791 --- /dev/null +++ b/stat/anovalevels.m @@ -0,0 +1,69 @@ +function [I L]= anovalevels(X,nf,labels) +%ANOVALEVELS - Put labels on levels of each factor in a design matrix X +% [I] = anovalevels(X) creates an array I with as many rows as there are +% elements in X and as many columns as its dimensions, where X contains +% the data of a full factorial ANOVA (see: myanova), so that each rows of +% I indicate for each X(:) the level in each factor it corresponds to. +% The concatenation [I X(:)] can then be used with by rmaov2, for +% example. +% +% [I] = anovalevels(X, nf) consider only the first nf dimensions of X as +% factors (the rest is supposed to be multivariate data) +% +% [L,I] = anovalevels(X, nf, labels) uses the specified labels instead +% of numerical indices. labels must be a cell array of length nf, with +% each labels{i} being itself an array of length = size(X,i) +% +% Example +% >> anovalevels(rand(3,2)) +% >> anovalevels(rand(3,2),2,{1:3 , {'a' 'b'}}) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-14 Creation +% KND 2008-11-11 Processes text labels +% KND 2010-05-04 Renamed factorlabels -> anovalevels +% ----------------------------- Script History --------------------------------- + +sx=size(X); +if nargin<2 + nf=length(sx); +end +ns=prod(sx(1:nf)); +if nargin==3 + nl=cellfun('length', labels); + if ~all(nl(1:nf)==sx(1:nf) | ~(nl>1)) %| ~all(cellfun('isreal', [labels{nl==1}]) & (cellfun('length', [labels{nl==1}]) == sx(nl==1))) + error('Wrong size of labels') + end +end + +I=zeros(ns,nf); +for i=1:nf + z=ones(prod(sx(1:i-1)),1)*(1:sx(i)); + z=z(:)*ones(1,prod(sx(i+1:end))); + I(:,i)=z(:); +end + +if nargin>2 + L=cell(size(I)); + for i=1:nf + if iscell(labels{i}) + L(:,i)=labels{i}(I(:,i)); + else + L(:,i)=num2cell(labels{i}(I(:,i))); + end + end + %permute outputs + J=I; + I=L; + L=J; + clear J; +end \ No newline at end of file diff --git a/stat/anovand.m b/stat/anovand.m new file mode 100644 index 0000000..9d0661f --- /dev/null +++ b/stat/anovand.m @@ -0,0 +1,1533 @@ +function [p,t,stats,terms] = anovand(y,group,varargin) +%ANOVAND N-way analysis of variance (ANOVA) of multidimensional data +% P=ANOVAN(Y,GROUP) performs multi-way (n-way) anova on the vector Y +% grouped by entries in the cell array GROUP. Each cell of GROUP must +% contain a grouping variable that can be a categorical variable, numeric +% vector, character matrix, or single-column cell array of strings. +% Each grouping variable must have the same number of items as Y. The +% fitted anova model includes the main effects of each grouping variable. +% All grouping variables are treated as fixed effects by default. The +% result P is a vector of p-values, one per term. +% +% P=ANOVAN(Y,GROUP,'PARAM1',val1,'PARAM2',val2,...) specifies one or +% more of the following name/value pairs: +% +% Parameter Value +% 'alpha' A value between 0 and 1 requesting 100*(1-alpha)% +% confidence bounds (default 0.05 for 95% confidence) +% 'continuous' A vector of indices indicating which grouping variables +% should be treated as continuous predictors rather than +% as categorical predictors +% 'display' Either 'on' (the default) to display an anova table +% or 'off' to omit the display +% 'nested' A matrix M of 0's and 1's specifying the nesting +% relationships among the grouping variables. M(i,j) +% is 1 if variable i is nested in variable j. +% 'random' A vector of indices indicating which grouping variables +% are random effects (all are fixed by default) +% 'sstype' The type of sum of squares 1, 2, 3, or 'h' (default=3) +% 'varnames' Grouping variables names in a character matrix or +% a cell array of strings, one per grouping variable +% (default names are 'X1', 'X2', ...) +% +% 'model' The model to use, specified as one of the following: +% +% 'linear' to use only main effects of all factors (default) +% 'interaction' for main effects plus two-factor interactions +% 'full' to include interactions of all levels +% an integer representing the maximum interaction order, for example +% 3 means main effects plus two- and three-factor interactions +% a matrix of term definitions as accepted by the X2FX function, +% but all entries must be 0 or 1 (no higher powers) +% +% [P,T,STATS,TERMS]=ANOVAN(...) also returns a cell array T containing +% the anova table, a structure STATS containing a variety of statistics, +% and a matrix TERMS describing the terms used (suitable for use as the +% MODEL input argument if you run ANOVAN again). +% +% For models without random effects, the anova table T contains columns +% for terms, sum of squares, degrees of freedom, an indication of whether +% the term is singular, mean square, F statistic, and P value. For models +% with random effects there are additional columns showing the term type +% (fixed or random), expected mean square, denominator mean square for F, +% denominator degrees of freedom for F, denominator definition, variance +% component estimate, lower bound for variance, and upper bound for +% variance. +% +% For the 'sstype' parameter, values 1-3 produce the usual type 1, type 2, +% or type 3 sums of squares. The value 'h' produces sums of squares for +% a hierarchical model that is similar to type 2, but with continuous as +% well as categorical factors used to determine the hierarchy of terms. +% +% The STATS structure contains the fields listed below, in addition +% to a number of other fields required for doing multiple comparisons +% using the MULTCOMPARE function: +% coeffs estimated coefficients +% coeffnames name of term for each coefficient +% vars matrix of grouping variable values for each term +% resid residuals from the fitted model +% +% These fields exist if there are random effects: +% ems expected mean squares +% denom denominator definition +% rtnames names of random terms +% varest variance component estimates (one per random term) +% varci confidence intervals for variance components +% +% Example: +% load carbig +% [p, atab] = anovan(MPG, {Cylinders Origin Model_Year}, ... +% 'model',2, 'sstype',2, ... +% 'varnames',strvcat('Cyl', 'Org', 'Yr')) +% This example performs three-way anova on MPG using the factors +% Cylinders, Origin, and Year. The model will have all two-factor +% interactions but not the three-factor interaction. Sum of +% squares are Type 2. +% +% See also MULTCOMPARE, ANOVA1, ANOVA2, MANOVA1. + +% Also supports older calling sequence: +% P=ANOVAN(Y,GROUP,MODEL,SSTYPE,VARNAME,DISPLAYOPT) +% In addition to the matrix form of the model specification, the function +% allows MODEL to be a vector V of integers. In this compressed form +% each element describes a term, so the Ith term includes the Jth grouping +% variable if BITGET(V(I),J)==1 +% +% +% References: +% Dunn, O.J., and V.A. Clark (1974), "Applied Statistics: +% Analysis of Variance and Regression," Wiley, New York. +% Goodnight, J.H., and F.M. Speed (1978), "Computing Expected Mean +% Squares," SAS Institute, Cary, NC. +% Milliken, G.A., and D.E. Johnson, "Analysis of Messy Data," +% Chapman & Hall, New York. +% Seber, G.A.F. (1977), "Linear Regression Analysis," Wiley, +% New York. + +% Copyright 1993-2007 The MathWorks, Inc. +% $Revision: 1.9.2.11 $ $Date: 2007/05/23 19:14:56 $ + +% First: argument checking and selection of defaults +error(nargchk(2,Inf,nargin,'struct')); +% if (numel(y)~=length(y)) +% error('stats:anovan:VectorRequired','Y must be a vector.'); +% end + +% if (size(y,1)==1), y=y(:); end +dostats = (nargout>=3); % true to compute output stats structure + +if ~iscell(group) && ~isa(group,'categorical') + if isnumeric(group) && size(group,1)==size(y,1) + group = num2cell(group,1); + else + error('stats:anovan:BadGroup',... + 'GROUP must be a cell array or matrix of grouping variables.') + end +end +group = group(:); +ng = length(group); + +% Which style of calling sequence are we using? +newstyle = true; +if ~isempty(varargin) && nargin<=6 + va1 = varargin{1}; + if ~ischar(va1) || isempty(va1) + newstyle = false; + elseif ~isempty(strmatch(va1,{'l' 'i' 'f' 'linear' 'interaction' 'full'},... + 'exact')) + newstyle = false; + end +end + +if newstyle + % Calling sequence with named arguments + okargs = {'model' 'sstype' 'varnames' 'display' 'alpha' ... + 'random' 'continuous' 'nested'}; + defaults = {1 3 '' 'on' 0.05 ... + false(ng,1) [] []}; + + % Skip error detection... + % [eid emsg model sstype varnames displayopt alpha ... + % randomvar continuous vnested] = ... + % statgetargs(okargs,defaults,varargin{:}); + % if ~isempty(eid) + % error(sprintf('stats:anovan:%s',eid),emsg); + % end +else + % Old-style calling sequence with fixed argument positions + model = 1; + sstype = 3; + varnames = ''; + displayopt = 'on'; + continuous = []; + vnested = []; + if nargin>=3, model = varargin{1}; end + if nargin>=4, sstype = varargin{2}; end + if nargin>=5, varnames = varargin{3}; end + if nargin>=6, displayopt = varargin{4}; end + alpha = 0.05; + randomvar = false(ng,1); +end + +% Check optional arguments +[varnames,termlist,randomvar,sstype,continuous,vnested] = argcheck(ng,... + varnames,model,randomvar,sstype,alpha,continuous,vnested); +doems = any(randomvar); % true to compute expected mean squares +if isequal(lower(sstype),'h') + sstype = 2; + dohier = true; +else + dohier = false; +end +if any(vnested(:)) + varnames = makenestednames(varnames,vnested); +end + +% STEP 1: Remove NaN's and prepare grouping variables. +% Also, make sure all groups are rows, and create group index and name arrays. +[y,allgrps,nanrow,varinfo] = removenans(y,group,continuous); +n = length(y); + +% STEP 2: Create dummy variable arrays for each grouping variable. +% STEP 2a: For type 3 ss, create constraints for each grouping variable. +varinfo.varnames = varnames; +varinfo = makedummyvars(continuous,allgrps,vnested,varinfo); + +% STEP 3: Create dummy variable arrays for each term in the model. +nterms = size(termlist,1); +fulltermlist = showtermnesting(termlist,vnested); +tnested = gettermnesting(fulltermlist,vnested,continuous); + +[ignore,sindex] = sortrows(fulltermlist); +terminfo = makedummyterms(sindex, termlist, varinfo, ... + continuous, tnested); + +% STEP 4: Create the full design matrix +[dmat,cmat,termname] = makedesignmat(terminfo,n); + +% STEP 5: Fit the full model and compute the residual sum of squares +mu = mean(y); +y = y - mu; % two passes to improve accuracy +mu2 = mean(y); +mu = mu + mu2; +y = y - mu2; +sst = sum(y.^2); +if ~dostats + [ssx,dfx,dmat2,y] = dofit(dmat, y, cmat, sst, mu); +else + % Do initial fit requesting stats structure, then convert from full-rank + % to overdetermined form, then find a label for each coefficient + [ssx,dfx,dmat2,y,stats] = dofit(dmat,y,cmat,sst,mu); + [codes,names] = convertstats(stats,terminfo,varinfo,continuous); +end + +sse = sst - ssx; +dfe = n - dfx; + +% STEP 6: Determine which models to compare for testing each term +ssw = -ones(nterms, 1); % sum of squares with this term +sswo = ssw; % sum of squares without this term +dfw = ssw; % residual d.f. with this term +dfwo = ssw; % residual d.f. without this term + +switch sstype + case 1 + modw = tril(ones(nterms)); % get model with this term + k = nterms; % locations of model with all terms + case 2 + modw = termsnotcontained(fulltermlist,vnested,continuous,dohier); + k = (sum(modw,2) == nterms); + TnotC = modw; + case 3 + modw = ones(nterms); + k = 1:nterms; + TnotC = termsnotcontained(fulltermlist,vnested,continuous,dohier); +end +modw = logical(modw); +modwo = logical(modw - eye(nterms)); % get model without this term + +% STEP 7: Fit each model, get its residual SS and d.f. +ssw(k) = ssx; % for full model we already know the results +dfw(k) = dfx; + +% Fit each model separately +dfboth = [dfw; dfwo]; +if doems + Llist = cell(nterms,1); +end + +% Consider interactions before their components for type 3 ss, so +% examine the terms in decreasing order of the number factors in the term +if sstype==3 + termsize = sum(fulltermlist,2)'; + [stermsize,sindices] = sort(termsize); + sindices = [sindices(:); sindices(:)]; +else + sindices = [(1:size(termlist,1)), (1:size(termlist,1))]'; +end + +% Fit all required subsets of the full model +fitsubmodels; % nested function + +% STEP 7A: Compute expected means squares if requested +if doems + emsMat = makeemsmat(dmat, cmat, nterms, Llist, termname); +end + +% STEP 8: Compute the sum of squares attributed to each term +ssterm = ssw - sswo; +dfterm = dfw - dfwo; +ssterm(dfterm==0) = 0; % make this exact + +% STEP 9: Compute the mean square for each term +msterm = ssterm ./ max(1, dfterm); +mse = sse * (dfe>0) / max(1, dfe); + +% STEP 9a: Equate computed and expected mean squares, then solve for +% variance component estimates +randomterm = find(termlist*randomvar > 0); % indices of random terms +if isempty(randomterm) + msdenom = repmat(mse, size(msterm)); + dfdenom = repmat(dfe, size(msterm)); +else + [msdenom,dfdenom,varest,varci,txtdenom,txtems,denommat,rtnames] = ... + getRandomInfo(msterm,dfterm,mse,dfe,emsMat,randomterm,... + terminfo.tnames,alpha); +end + +% STEP 10: Compute an F statistic for each term +fstat = repmat(Inf, size(msterm)); +t1 = (msdenom>0); +t2 = (msterm>0); +fstat(t1) = msterm(t1) ./ msdenom(t1); +fstat(~(t1|t2)) = NaN; + +% STEP 11: Compute the p-value for each term +pval = repmat(NaN, size(fstat)); +t = (dfdenom>0 & dfterm>0); +pval(t) = 1 - fcdf(fstat(t), dfterm(t), dfdenom(t)); +p = pval; + +% Create anova table as a cell array +sing = (dfterm < terminfo.dfterm0); % is non-nested term singular? +if ~isempty(tnested) + sing(any(tnested,2)) = false; +end + +[tbl, t] = maketable; % nested function + +if (nargout > 3), terms = termlist; end + +if (isequal(displayopt,'on')) + switch(sstype) + case 1, cap = 'Sequential (Type I) sums of squares.'; + case 2, if dohier + cap = 'Hierarchical (modified Type II) sums of squares'; + else + cap = 'Hierarchical (Type II) sums of squares.'; + end + otherwise, cap = 'Constrained (Type III) sums of squares.'; + end + if (any(sing)), cap = [cap ' Terms marked with # are not full rank.']; end + digits = [-1 -1 -1 -1 2 4]; + figh = statdisptable(tbl, 'N-Way ANOVA', 'Analysis of Variance',cap,digits); + set(figh,'HandleVisibility','callback'); +end + +% Store additional information for multiple comparisons +if dostats + stats = makestats(stats); % nested function +end + +% ----- nested function +function fitsubmodels + for j=length(sindices):-1:1 + % Find the next model index to fit + k = sindices(j); + + % Look in unsorted arrays to see if we have already fit this model + if j>nterms + k0 = k+nterms; + else + k0 = k; + end + if dfboth(k0)~=-1 + continue + end + + % Find the model with this index + if (j > nterms) + thismod = modwo(k, :); + else + thismod = modw(k, :); + end + + % Get the design matrix for this model + keepterms = find(thismod); + clist = ismember(termname, [0 keepterms]); + X = dmat2(:,clist); + C = cmat(:,clist); + + % Fit this model + [ssx0,dfx0] = dofit(X, y, C); + + % If this model is the "without" model for a term, compute L + if doems && j>nterms + if sstype==1 + prevterms = (1:nterms)F'}; ... + terminfo.tnames tbl]; + + % Add random effects information if required + if ~isempty(randomterm) + rterms = [randomterm; nterms+1]; + C = size(tbl,2); + tbl(1,end+1:end+8) = {'Type' 'Expected MS' 'MS denom' 'd.f. denom' 'Denom. defn.' ... + 'Var. est.' 'Var. lower bnd' 'Var. upper bnd'}; + tbl(1+(1:nterms),C+1) = {'fixed'}; + tbl(1+rterms,C+1) = {'random'}; + tbl(1+(1:length(txtems)),C+2) = txtems; + tbl(1+(1:length(msdenom)),C+3) = num2cell(msdenom(:)); + tbl(1+(1:length(dfdenom)),C+4) = num2cell(dfdenom(:)); + tbl(1+(1:length(txtdenom)),C+5)= txtdenom; + tbl(1+rterms,C+6) = num2cell(varest); + tbl(1+rterms,C+7) = num2cell(varci(:,1)); + tbl(1+rterms,C+8) = num2cell(varci(:,2)); + end + + % Add total information + tbl{end+1,1} = 'Total'; + tbl{end,2} = sst; + tbl{end,3} = n-1; + tbl{end,4} = 0; + + % So far this is the table for the output argument + t = tbl; + + % For display, mark terms that are rank deficient + tbl{1,1} = [' ' tbl{1,1}]; + for r=2:size(tbl,1) + x = tbl{r,1}; + if (tbl{r,4}) + x = ['# ' x]; + else + x = [' ' x]; + end + tbl{r,1} = x; + end + tbl = tbl(:,[1 2 3 5 6 7]); + end % of nested function maketable + +end % of main function + + +% -------------------------- +function m = termsnotcontained(terms,vnested,continuous,dohier) +%TERMSNOTCONTAINED Creates a logical matrix indicating term containment +% m(i,j)==1 iff t(i) is not contained by t(j) + +% For starters, omit continuous variables from this test +contnum = find(continuous); +t = terms; +t(:,contnum) = 0; + +% The main test: no overlap between terms included in t(i) and not in t(j) +m = (t*~t') > 0; + +% Now consider continuous variables (X) +nterms = size(terms,1); +for j=1:length(contnum) + v = terms(:,contnum(j)); + vv = repmat(v,1,nterms); + if dohier + % A cannot be contained in B if A has a higher power of X + m = m | vv>vv'; + else + % A cannot be contained in B if they don't match on X + m = m | vv~=vv'; + end +end + +% Set diagonals to 1 because we want proper containment +m(1:(nterms+1):end) = 1; +end + +% -------------------------- +function v = makemodel(p,ng,vnested) +%MAKEMODEL Helper function to make model matrix +% P = max model term size, NG = number of grouping variables +% or +% P = vector of term codes +% VNESTED is a matrix specifying direct or indirect nesting. + +% We want a matrix with one row per term. Each row has a 1 for +% the variables participating in the term. There will be rows +% summing up to 1, 2, ..., p. + +if numel(p)==1 + % Create model matrix from a scalar max order value + vgen = 1:ng; + v = eye(ng); % linear terms + for j=2:min(p,ng) + c = nchoosek(vgen,j); % generate column #'s with 1's + nrows = size(c,1); % generate row #'s + r = repmat((1:nrows)',1,j); % and make it conform with c + m = zeros(nrows,ng); % create a matrix to get new rows + m(r(:)+nrows*(c(:)-1)) = 1; % fill in 1's + v = [v; m]; % append rows + end +else + % Create model matrix from terms encoded as bit patterns + nterms = length(p); + v = zeros(nterms,ng); + for j=1:nterms + tm = p(j); + while(tm) + % Get last-numbered effect remaining + lne = 1 + floor(log2(tm)); + tm = bitset(tm, lne, 0); + v(j,lne) = 1; + end + end +end + +% Remove terms forbidden by nesting +[nestee,nester] = find(vnested); +bad = any(v(:,nestee) & v(:,nester), 2); +v(bad,:) = []; + +end + +% -------------------------- +function [ssx,dfx,dmat2,y2,stats] = dofit(dmat,y,cmat,sst,mu) +%DOFIT Do constrained least squares fit and reduce data for subsequent fits + +% Find the null space of the constraints matrix +[Qc,Rc,Ec] = qr(cmat'); +pc = Rrank(Rc); +Qc0 = Qc(:,pc+1:end); + +% Do qr decomposition on design matrix projected to null space +Dproj = dmat*Qc0; +[Qd,Rd,Ed] = qr(Dproj,0); +dfx = Rrank(Rd); +Qd = Qd(:,1:dfx); +Rd = Rd(1:dfx,1:dfx); + +% Fit y to design matrix in null space +y2 = Qd' * y; % rotate y into that space +zq = Rd \ y2; % fit rotated y to projected design matrix + +z = zeros(length(Ed),1); % coefficient vector extend to full size ... +z(Ed(1:dfx)) = zq; % ... and in correct order for null space + +b = Qc0 * z; % coefficients back in full space +ssx = norm(y2)^2; % sum of squares explained by fit + +% Return reduced design matrix if requested +if nargout>2 + dmat2 = Qd' * dmat; +end + +% Prepare for multiple comparisons if requested +if (nargout >= 3) + stats.source = 'anovan'; + + % Get residuals + yhat = Dproj * z; + stats.resid = y - yhat; + + % Calculate coefficients, then adjust for previously removed mean + t = b; + if ~isempty(t) + t(1) = t(1) + mu; % undo mean adjustment before storing + end + stats.coeffs = t; + + RR = zeros(dfx,size(Dproj,2)); + RR(:,Ed(1:dfx)) = Rd; + stats.Rtr = RR'; + [qq,rr,ee] = qr(dmat,0); + pp = Rrank(rr); + rowbasis = zeros(pp,size(rr,2)); + rowbasis(:,ee) = rr(1:pp,:); + stats.rowbasis = rowbasis; + stats.dfe = length(y) - dfx; + stats.mse = (sst - ssx) / max(1, stats.dfe); + stats.nullproject = Qc0; +end +end + +% --------------------- +function p = Rrank(R,tol) +%RRANK Compute rank of R factor after qr decomposition +if (min(size(R))==1) + d = abs(R(1,1)); +else + d = abs(diag(R)); +end +if nargin<2 + tol = 100 * eps(class(d)) * max(size(R)); +end +p = sum(d > tol*max(d)); +end + +% ---------------------- +function ems = getems(L,R,termnums) +%GETEMS Final step in expected mean square computation +% The L array is an array of constraints on the coefficients, +% R is the R factor in a QR decomposition X, and termnums is a +% vector mapping R column numbers to term numbers. The output is +% a vector of expected mean square coefficients with one element +% per term. The first element is for the constant term, and +% the last is for the error term. See "Computing Expected Mean +% Squares" by Goodnight and Speed, 1978. + +% In G&S notation, form the matrix L*pinv(X'*X)*L'. +dfL = size(L,1); +temp = L/R; +LML = temp*temp'; + +% Create the Cholesky decomposition U and then compute U\L. +U = cholcov(LML); +C = U'\L; + +% Sum the squared values of the columns other than the column for +% the constant term, and assign the sums to terms. +sumsq = sum(C(:,2:end).^2,1); +cols = termnums(2:end); +rows = ones(size(cols)); +ems = accumarray([rows(:),cols(:)], sumsq) / dfL; +ems(:,end+1) = 1; % add entry for error term +end + +% ----------------------------- +function L = getL(X, curcols, incols, L2) +%GETL Get L hypothesis matrix for the current term after adjusting for +% terms that remain "in" for this test, making the whole thing +% orthogonal to the matrix L2 containing hypotheses for terms that +% contain the current term. +% +% Type incols L2 +% ---- -------------------- ---------------- +% 1 lower-numbered terms empty +% 2 non-containing terms empty +% 3 non-containing terms containing terms + +x1 = X(:,curcols); % the current term +x0 = X(:,incols); % terms that remain "in" when testing x1 + +% Find hypothesis for the current term. First remove effects of terms it does +% not contain (these terms remain in the model when testing the current term). +[Q0,R,E] = qr(x0,0); +tol = 100 * max(size(x0)) * eps(R(1,1)); +if min(size(R))>1 + p = sum(abs(diag(R)) > tol); +else + p = 1; +end + +Q0 = Q0(:,1:p); +adjx1 = x1 - Q0 * (Q0' * x1); + +% Now find a full-rank basis for the adjusted effect. +[Q2,R,E] = qr(adjx1,0); +tol = 100 * max(size(R)) * eps(R(1,1)); +if min(size(R))>1 + p = sum(abs(diag(R)) > tol); +else + p = 1; +end +Q2 = Q2(:,1:p); +L = Q2' * X; + +% Make L rows orthogonal to the L rows for containing terms. +if ~isempty(L2) + L2tr = L2'; + [Q,R,E] = qr(L2tr,0); + L = (L' - Q * (Q' * L'))'; + + % Make L full rank + [Q,R,E] = qr(L,0); + tol = 100 * max(size(L)) * eps(R(1,1)); + if min(size(R))>1 + p = sum(abs(diag(R)) > tol); + else + p = 1; + end + if p= tol); + indices = e(nonzeroterms); + tnums = randomterms(indices); + if length(nonzeroterms) == 1 + % If it's a single term, use it exactly + msDenom(j) = msTerm(tnums); + dfDenom(j) = dfTerm(tnums); + txtdenom{j} = sprintf('MS(%s)',tnames{tnums}); + else + % Otherwise use the linear combination and Satterthwaite's approximation + linprod = b(nonzeroterms) .* msTerm(tnums); + msDenom(j) = sum(linprod); + if any(dfTerm(tnums) == 0) + dfDenom(j) = NaN; + else + dfDenom(j) = msDenom(j)^2 / sum((linprod.^2) ./ dfTerm(tnums)); + end + txtdenom{j} = linprodtxt(b(nonzeroterms),tnames(tnums),'MS'); + end + + % Next get an expression for the expected mean square + prefix = repmat('Q',nterms+1,1); % quadratic form for fixed effects + prefix(randomterms,1) = 'V'; % variance for random effects + txtems{j} = linprodtxt(ems(j,:),tnames,prefix); +end + +% Get the variance component estimates +[varest,varci] = varcompest(ems,randomterms,msTerm,dfTerm,alpha); + +% Package up the results +denommat = B'; +rtnames = tnames(randomterms); +end + +% ----------------------------------------- +function [varest,varci] = varcompest(ems,Rterms,msTerm,dfTerm,alpha) +%VARCOMPEST Estimate variance components from obs. & exp. mean squares + +nterms = length(msTerm) - 1; % not including error term + +Fterms = find(~ismember(1:nterms, Rterms)); +Fterms = Fterms(:); + +% Get A and B so that expected means square is Av+Bq +% where v is the variances and q is quadratic forms in the fixed effects +B = ems(Rterms, Fterms); +A = ems(Rterms, Rterms); +const = msTerm(Rterms) - B*msTerm(Fterms); +Ainv = pinv(A); % should be well-conditioned and easily invertible +varest = Ainv * const; + +% Get confidence bounds for the variance components +varci = repmat(NaN,length(varest),2); +if all(dfTerm>0) + L = msTerm .* dfTerm ./ chi2inv(1-alpha/2,dfTerm); + U = msTerm .* dfTerm ./ chi2inv(alpha/2,dfTerm); + AinvB = Ainv * B; + for j=find(varest'>0) + Rcoeffs = Ainv(j,:); + Fcoeffs = AinvB(j,:); + t = (Rcoeffs>0); + s = (Fcoeffs>0); + cL = 0; + cU = 0; + if any(t) + cL = cL + dot(Rcoeffs(t), L(Rterms(t))); + cU = cU + dot(Rcoeffs(t), U(Rterms(t))); + end + if any(~t) + cL = cL + dot(Rcoeffs(~t), U(Rterms(~t))); + cU = cU + dot(Rcoeffs(~t), L(Rterms(~t))); + end + if any(s) + cL = cL + dot(Fcoeffs(s), L(Fterms(s))); + cU = cU + dot(Fcoeffs(s), U(Fterms(s))); + end + if any(~s) + cL = cL + dot(Fcoeffs(~s), U(Fterms(~s))); + cU = cU + dot(Fcoeffs(~s), L(Fterms(~s))); + end + varci(j,1) = max(0,cL); + varci(j,2) = max(0,cU); + end +end +end + +% ------------------------------------------------ +function txt=linprodtxt(coeffs,names,prefix) +%LINPRODTXT Create a text representing a linear combination of some things + +txt = ''; +plustxt = ''; + +% If things will display as 0 or 1, make them exact +tol = sqrt(eps(class(coeffs))) * max(abs(coeffs)); +coeffs(abs(coeffs)1 + preftxt = deblank(prefix(i,:)); + end + + txt = sprintf('%s%s%s%s(%s)',txt,signtxt,coefftxt,preftxt,names{i}); + plustxt = '+'; + end +end +end + +% ------------------- +function [varnames,termlist,randomvar,sstype,continuous,vnested] = ... + argcheck(ng,varnames,model,randomvar,sstype,alpha,continuous,vnested) +% variable names +if isempty(varnames) + varnames = cellstr([repmat('X',ng,1) strjust(num2str((1:ng)'),'left')]); +else + if (iscell(varnames)), varnames = varnames(:); end + if (size(varnames,1) ~= ng) + error('stats:anovan:InputSizeMismatch','VARNAMES must have %d rows', ng); + elseif (~(ischar(varnames) || iscellstr(varnames))) + error('stats:anovan:BadVarNames',... + 'VARNAMES must be a character matrix or cell array of strings.'); + elseif (ischar(varnames)) + varnames = cellstr(varnames); + end +end + +% sum-of-squares type +if isempty(sstype) + sstype = 3; +elseif ~isscalar(sstype) || (sstype ~= 1 && sstype ~= 2 && sstype ~= 3 && lower(sstype) ~= 'h') + error('stats:anovan:BadSumSquares','SSTYPE must be 1, 2, or 3.'); +end + +% continuous must be a logical vector indicating continuous variables +if islogical(continuous) && length(continuous)==ng && numel(continuous)==ng + continuous = continuous(:); +elseif isnumeric(continuous) && all(ismember(continuous(:),1:ng)) + continuous = ismember(1:ng,continuous); +else + error('stats:anovan:BadContinuous',... + 'CONTINUOUS must be a vector of indices between 1 and %d.', ng); +end + +% nested must be a binary matrix +if ~isempty(vnested) + if ~isequal(size(vnested),[ng ng]) || ~all(vnested(:)==0 | vnested(:)==1) + error('stats:anovan:BadNested',... + 'The NESTED parameter must be a %d-by-%d matrix of 0''s and 1''s.',... + ng,ng); + end + + % find all indirect nesting + vnested = nest_d2i(vnested); +end + +% alpha (confidence level is 100*(1-alpha)% +if ~isnumeric(alpha) || numel(alpha)~=1 || alpha<=0 || alpha>=1 + error('stats:anovan:BadAlpha','ALPHA must be a scalar between 0 and 1.'); +end + +% Randomvar may be a logical vector indicating the random variables +if islogical(randomvar) && length(randomvar)==ng && numel(randomvar)==ng + randomvar = randomvar(:); +elseif isnumeric(randomvar) && all(ismember(randomvar(:),1:ng)) + % or it may be an index vector -- convert to logical + randomvar = ismember((1:ng)', randomvar(:)); +else + error('stats:anovan:BadRandomVar',... + 'RANDOMVAR must be a vector of indices between 1 and %d.', ng); +end +if any(randomvar(continuous)) + error('stats:anovan:BadRandomVar',... + 'You cannot specify a continuous predictor as having a random effect'); +end + +% model +if isempty(model) + model = 1; +elseif ~isnumeric(model) + if strcmp(model, 'linear') || strcmp(model, 'l') + model = 1; + elseif strcmp(model, 'interaction') || strcmp(model, 'i') + model = 2; + elseif strcmp(model, 'full') || strcmp(model, 'f') + model = ng; + else + error('stats:anovan:BadModel','MODEL is invalid.'); + end +elseif min(size(model))>1 || ... + (isequal(size(model),[1 ng]) && all(ismember(model,0:1))) + % Matrix form of input + if (any(model~=floor(model)|model<0)) + error('stats:anovan:BadModel',... + 'MODEL matrix entries must be non-negative integers.'); + elseif size(model,2)~=ng + error('stats:anovan:InputSizeMismatch',... + 'MODEL matrix must have %d columns.',ng); + end +else + if (any(model~=floor(model)|model<=0)) + % Original vector form, no longer advertised + error('stats:anovan:BadModel','MODEL is invalid.'); + end + model = model(:); +end + +% convert model to numeric matrix list of terms +if (length(model)==1) || (any(size(model)==1) && size(model,2)~=ng) + % Convert from scalar or coded integer to matrix form + termlist = makemodel(model, ng, vnested); +else + termlist = model; +end + +% look for invalid model terms +t = all(termlist==0,2); +termlist(t,:) = []; % remove constant term -- it's implicit +if any(any(termlist(:,~continuous)>1)) + error('stats:anovan:BadModel',... + 'MODEL cannot have squared or higher terms for categorical factors.'); +end +if ~isempty(vnested) + % Must not have A(B) and B(A) + if any(any(vnested & vnested')) + error('stats:anovan:BadNesting',... + 'Circular nesting (such as A(B) and B(A)) is not allowed.'); + end + + % Must not have an interaction between B and A(B) + [nestee,nester] = find(vnested); + bad = any(termlist(:,nestee) & termlist(:,nester), 2); + if any(bad) + error('stats:anovan:BadModel',... + ['MODEL must not have an interaction between a nested factor'... + '\nand the factor that nests it.']); + end +end +end + +% ------------------ +function emsMat = makeemsmat(dmat, cmat, nterms, Llist, termname) + +% Factor the design matrix X appended with the constraints matrix C, +% getting a full-rank R factor. +xc = [dmat; cmat]; +[Qxc,Rxc,Exc] = qr(xc,0); +tol = sqrt(eps(class(Rxc))); +rankRxc = Rrank(Rxc,tol); +Rxc0 = zeros(rankRxc,size(Rxc,2)); +Rxc0(:,Exc) = Rxc(1:rankRxc,:); + +% Compute expected mean squares for each term. +emsMat = zeros(nterms,0); +for k=1:nterms + termems = getems(Llist{k},Rxc0,termname); + emsMat(k,1:length(termems)) = termems; +end +emsMat(nterms+1,end) = 1; % for error term +end + +% ---------------------- +function [codes,names] = convertstats(stats,terminfo,varinfo,continuous) + +allnames = varinfo.allnames; +varnames = varinfo.varnames; +ng = length(varnames); +fullcoef = stats.coeffs; +codes = zeros(length(fullcoef), ng); +names = cell(length(fullcoef),1); +base = 1; +names{1} = 'Constant'; + +% compute names +for j=1:length(terminfo.levelcodes) + M = terminfo.levelcodes{j}; + varlist = terminfo.termvars{j}; + v1 = varlist(1); + vals1 = allnames{v1}; + nrows = size(M,1); + codes(base+(1:nrows),varlist) = M; + for k=1:nrows + if continuous(v1) + nm = varnames{v1}; + else + nm = sprintf('%s=%s',varnames{v1},vals1{M(k,1)}); + end + for i=2:length(varlist) + v2 = varlist(i); + vals2 = allnames{v2}; + if continuous(v2) + nm2 = varnames{v2}; + else + nm2 = sprintf('%s=%s',varnames{v2},vals2{M(k,i)}); + end + nm = sprintf('%s * %s',nm,nm2); + end + names{base+k} = nm; + end + base = base+nrows; +end +end + +% -------------------------------- +function terminfo = makedummyterms(sindex,termlist,varinfo,continuous,tnested) + +ncols = 1; +[nterms,nfactors] = size(termlist); + +termdum = cell(nterms, 1); % dummy variable = design matrix cols +termconstr = cell(nterms,1); % constraints to make each term well defined +levelcodes = cell(nterms, 1); % codes for levels of each M row +tnames = cell(nterms, 1); % name for entire term, e.g. A*B +dfterm0 = zeros(nterms, 1); % nominal d.f. for each term +termvars = cell(nterms, 1); % list of vars in each term +termlength = zeros(size(sindex));% length of each term (number of columns) + +auxtermlist = zeros(0,nfactors); % may need to create temp terms for nesting +auxtermdum = cell(0,1); % may need their dummy variables + +isnested = false; + +% For each term, +for j=1:nterms + % Get dummy columns, var list, term name, etc + sj = sindex(j); + tm = termlist(sj,:); + if ~isempty(tnested) + isnested = any(tnested(sj,:)); + end + [tdum,vars,tn,df0,tconstr] = maketerm(tm,isnested,varinfo,j,sindex,... + termlist,termdum,termconstr,tnames,dfterm0); + + % Store this term's information + k = size(tdum, 2); + termlength(sindex(j),1) = k; + ncols = ncols + k; + termdum{sj} = tdum; + termvars{sj} = vars; + levelcodes{sj} = fliplr(fullfact(varinfo.vlevels(vars(end:-1:1)))); + tnames{sj,1} = tn; + dfterm0(sj) = df0; + + % For a nested term, figure out the constraint now + if isnested + % First get dummy variables for this term and its nesters + if any(tm(continuous)) + % Ignore any continuous variable contributions to this term + tmcat = tm; % this term, cat predictors only + tmcat(continuous) = 0; + ntmcat = termlist(tnested(sj,:),:); + ntmcat(:,continuous) = 0; % nesting terms, cat predictors only + [Ydum,auxtermlist,auxtermdum] =findtermdum(tmcat,termlist,termdum,... + auxtermlist,auxtermdum,varinfo); + Ydum = Ydum{1}; + [Xdum,auxtermlist,auxtermdum] =findtermdum(ntmcat,termlist,termdum,... + auxtermlist,auxtermdum,varinfo); + else + % No continuous variables, so work with the whole term + Ydum = tdum; + Xdum = termdum(tnested(sj,:)>0); + end + + % Constrain the part of this term in its nesters to be 0 + tconstr = gettermconstr(Ydum, Xdum); + end + termconstr{sj} = tconstr; +end +tnames{length(tnames)+1,1} = 'Error'; + +% Package up term info into a structure +terminfo.termdum = termdum; +terminfo.termconstr = termconstr; +terminfo.levelcodes = levelcodes; +terminfo.tnames = tnames; +terminfo.dfterm0 = dfterm0; +terminfo.termvars = termvars; +terminfo.termlength = termlength; +end + +% ----------------------------------- +function [y,allgrps,nanrow,varinfo] = removenans(y,group,continuous) + +% Find NaNs among response and group arrays +n = size(y,1); +nanrow = any(isnan(y(:,:)),2); +ng = length(group); +for j=1:ng + gj = group{j}; + if (size(gj,1) == 1), gj = gj(:); end + if (size(gj,1) ~= n) + error('stats:anovan:InputSizeMismatch',... + 'Group variable %d must have %d elements.',j,n); + end + if (ischar(gj)), gj = cellstr(gj); end + if ~isvector(gj) + error('stats:anovan:BadGroup',... + 'Grouping variable must be a vector or a character array.'); + end + + group{j} = gj; + if (isnumeric(gj)) + nanrow = (nanrow | isnan(gj)); + elseif isa(gj,'categorical') + nanrow = (nanrow | isundefined(gj)); + else + nanrow = (nanrow | strcmp(gj,'')); + end +end + +% Remove rows with NaN anywhere +y(nanrow,:) = []; +n = size(y,1); +ng = length(group); +dfvar = zeros(ng,1); +allgrps = zeros(n, ng); +allnames = cell(ng,1); + +% Get arrays describing the groups +for j=1:ng + gj = group{j}; + gj(nanrow,:) = []; + group{j} = gj; + if continuous(j) + dfvar(j) = 1; + allgrps(:,j) = gj; + else + [gij,gnj] = grp2idx(gj); + nlevels = size(gnj,1); + dfvar(j) = nlevels - 1; + allgrps(:,j) = gij; + allnames{j} = gnj; + end +end + +% The df and allnames information does not yet reflect nesting. We will +% fix up allnames for nested variables later, and not use df for them. + +varinfo.df = dfvar; +varinfo.allnames = allnames; +end + +% ----------------------------- +function varinfo = makedummyvars(continuous,allgrps,vnested,varinfo) +% Create main effect term values for each variable + +ng = size(allgrps,2); +vdum = cell(ng,1); % dummy terms for variables +vconstr = cell(ng,1); % constraints +vlevels = ones(ng,1); % levels corresponding to each dummy term +vmeans = zeros(ng,1); % variable means, used for continuous factors +varnames = varinfo.varnames; +allnames = varinfo.allnames; + +for j=1:ng + if continuous(j) + % For continuous variables, use the variable itself w/o constraints + vdum{j} = allgrps(:,j); + vconstr{j} = ones(0,1); + vmeans(j) = mean(allgrps(:,j)); + elseif isempty(vnested) || ~any(vnested(j,:)) + % Create dummy variable arrays for each grouping variable + % using a sum-to-zero constraint + vdum{j} = idummy(allgrps(:,j), 3); + nlevgrp = size(vdum{j},2); + vconstr{j} = ones(1,nlevgrp); % sum-to-zero constraint for categorical + vlevels(j) = nlevgrp; + else + % Create dummy variable arrays for a nested variable + nesternums = find(vnested(j,:)); + allvars = allgrps(:,[nesternums, j]); + [ugrps,ignore2,grpnum] = unique(allvars,'rows'); + vdum{j} = idummy(grpnum,3); + vconstr{j} = []; % to be computed later + vlevels(j) = size(vdum{j},2); + + % Fix up names for nested variables + levelnames = varinfo.allnames{j}; + namesj = cell(vlevels(j),1); + nester1names = allnames{nesternums(1)}; + for rnum = 1:vlevels(j) + nesterlist = nester1names{ugrps(rnum,1)}; + for k = 2:length(nesternums) + nesterknames = allnames{nesternums(k)}; + nesterlist = sprintf('%s,%s',nesterlist,... + nesterknames{ugrps(rnum,k)}); + end + namesj{rnum} = sprintf('%s(%s)',levelnames{ugrps(rnum,end)},... + nesterlist); + end + varinfo.allnames{j} = namesj; + end +end + +varinfo.vdum = vdum; +varinfo.vconstr = vconstr; +varinfo.vlevels = vlevels; +varinfo.vmeans = vmeans; +end + +% ----------------------------- +function [dmat,cmat,termname] = makedesignmat(terminfo,n) + +termlength = terminfo.termlength; +ncols = sum(termlength); + +nconstr = sum(cellfun('size',terminfo.termconstr,1)); +dmat = ones(n, ncols+1); % to hold design matrix +cmat = zeros(nconstr,ncols); % to hold constraints matrix +cbase = 0; % base from which to fill in cmat +termname = zeros(ncols,1); +termstart = cumsum([2; termlength(1:end-1)]); +termend = termstart + termlength - 1; +for j=1:length(termlength) + clist = termstart(j):termend(j); + dmat(:, clist) = terminfo.termdum{j}; + C = terminfo.termconstr{j}; + nC = size(C,1); + cmat(cbase+1:cbase+nC,clist) = C; + termname(clist) = j; + cbase = cbase + nC; +end +end + + +% ----------------------------- +function tnested = gettermnesting(fulltermlist,vnested,continuous) +% Create matrix with (i,j) indicating if term i is nested in term j + +% No nested variables implies no nested terms +if isempty(vnested) + tnested = []; + return +end + +% Work with categorical and continuous terms separately +ctermlist = fulltermlist(:,continuous); +fulltermlist(:,continuous) = 0; + +nterms = size(fulltermlist,1); +tnested = zeros(nterms); + +% If A(B), then any term containing A may be nested in one containing B +[nestee,nester] = find(vnested); +for j=1:length(nester) + hasnestee = (fulltermlist(:,nestee(j))>0); + hasnester = (fulltermlist(:,nester(j))>0); + tnested(hasnestee,hasnester) = 1; +end + +% But terms are not nested within themselves +tnested(1:nterms+1:end) = 0; + +% And there is no nesting relationship if the continuous vars don't match +for j=1:size(ctermlist,2) + c = repmat(ctermlist(:,j),1,nterms); + tnested = tnested & (c == c'); +end + +% And the full representation for a nesting term must be a subset of the +% full representation for a nested term +[nestee,nester] = find(tnested); +for j=1:length(nester) + if any(fulltermlist(nestee(j),:) < fulltermlist(nester(j),:)) + tnested(nestee(j),nester(j)) = 0; + end +end + +end + +% ---------------------------- +function constr = gettermconstr(tdum,nesterdum) + +% Create X matrix containing design matrix columns of nester terms +if iscell(nesterdum) + Xnester = cat(2,nesterdum{:}); +else + Xnester = nesterdum; +end +nnested = size(Xnester,2); + +% Find unique combinations of nested and nesting terms +Xboth = [Xnester tdum]; +Uboth = unique(Xboth,'rows'); + +% Find constraints to force the part of the nested terms in the column +% space of the nesting terms to be zero +[Q,R,E] = qr(Uboth(:,1:nnested)); +rnk = Rrank(R); +Q = Q(:,1:rnk); +constr = Q*(Q'*Uboth(:,nnested+1:end)); + +% Remove redundant constraints +[Q,R,E] = qr(constr',0); +rnk = Rrank(R); +constr = constr(E(1:rnk),:); +end + + +% ---------------------------- +function nestednames = makenestednames(varnames,vnested) + +nestednames = varnames; + +nestedvars = find(any(vnested,2)); +for j=1:length(nestedvars) + k = nestedvars(j); + thelist = sprintf('%s,',varnames{vnested(k,:)>0}); + nestednames{k} = sprintf('%s(%s)',varnames{k},thelist(1:end-1)); +end +end + +% ---------------------------- +function fulltermlist = showtermnesting(termlist,vnested) + +fulltermlist = termlist; + +[nestee,nester] = find(vnested); +for j=1:length(nester) + t = fulltermlist(:,nestee(j))>0; + fulltermlist(t,nester(j)) = 1; +end +end + + +% ---------------------------- +function [tdum,vars,tn,df0,tconstr] = maketerm(tm,isnested,varinfo,j,sindex,termlist,... + termdum,termconstr,tnames,dfterm0) +% Make term info such as dummy vars, name, constraints + +% Loop over elements of the term +df0 = 1; +tdum = []; % empty term so far +tconstr = 1; % empty constraints so far +tn = ''; % blank name so far +vars = find(tm); % list of variables making up terms +pwrs = tm(vars); % and their exponents +tm = (tm>0); % and a boolean mask for them +for varidx = 1:length(vars) + % Process each variable participating in this term + varnum = vars(varidx); % variable name + thispwr = pwrs(1); % power of this variable + tm(varnum) = 0; % term without this variable + pwrs(1) = []; % powers without this variable + df0 = df0 * varinfo.df(varnum); % d.f. so far + + % Combine its dummy variable with the part computed so far + G = varinfo.vdum{varnum}; % dummy vars for this grouping var + thisname = varinfo.varnames{varnum}; + if thispwr>1 + G = G .^ thispwr; + thisname = sprintf('%s^%d',thisname,thispwr); + end + tdum = termcross(G,tdum); % combine G into term dummy vars + + % Construct the term name and constraints matrix + if nargout>1 + if (isempty(tn)) + tn = thisname; + if ~isnested + tconstr = varinfo.vconstr{varnum}; + end + else + tn = [tn '*' thisname]; + if ~isnested + tconstr = [kron(varinfo.vconstr{varnum},eye(size(tconstr,2))); + kron(eye(length(varinfo.vconstr{varnum})),tconstr)]; + end + end + end + + if varidx1 + % If the rest of this term is computed, take advantage of that + prevterms = termlist(sindex(1:j-1),:); + oldtm = find(all(prevterms(:,tm) == repmat(pwrs,size(prevterms,1),1),2)); + oldtm = oldtm(~any(prevterms(oldtm,~tm),2)); + if (length(oldtm) > 0) + k = sindex(oldtm(1)); + tdum = termcross(termdum{k}, tdum); + if nargout>1 + if ~isnested + oconstr = termconstr{k}; + tconstr = [kron(tconstr, eye(size(oconstr,2))); + kron(eye(size(tconstr,2)), oconstr)]; + end + tn = [tn '*' tnames{k}]; + df0 = df0 * dfterm0(k); + end + break; + end + end +end +if (isempty(tn)), tn = 'Constant'; end +end + +% ---------------------------- +function [dum,auxtermlist,auxtermdum] =findtermdum(tms,termlist,termdum,... + auxtermlist,auxtermdum,varinfo) + + +nterms = size(tms,1); +dum = cell(nterms,1); +for j=1:nterms + tm = tms(j,:); + + % Try to find this term among the terms in the model + oldtm = find(all(termlist == repmat(tm,size(termlist,1),1),2)); + if ~isempty(oldtm) + dum{j} = termdum{oldtm(1)}; + continue + end + + % Try to find this term among the auxiliary terms + oldtm = find(all(auxtermlist == repmat(tm,size(auxtermlist,1),1),2)); + if ~isempty(oldtm) + dum{j} = auxtermdum{oldtm(1)}; + continue + end + + % Create an auxiliary term + dum{j} = maketerm(tm,[],varinfo,0); + + auxtermdum{end+1} = dum{j}; + auxtermlist(end+1,:) = tm; +end +end + +% --------------------------- +function m = nest_d2i(nested) +% Take matrix specifying at least direct nesting relationships, and +% return matrix that includes all indirect nesting relationships +m = nested; +n = size(m,1); +m0 = zeros(n); +while(~isequal(m,m0)) + m0 = m; + m = double(m | ((m*m) > 0)); +end +end \ No newline at end of file diff --git a/stat/binocdf.m b/stat/binocdf.m new file mode 100644 index 0000000..9ab3ce9 --- /dev/null +++ b/stat/binocdf.m @@ -0,0 +1,121 @@ +function y = binocdf(x,n,p) +%BINOCDF Binomial cumulative distribution function. +% Y=BINOCDF(X,N,P) returns the binomial cumulative distribution +% function with parameters N and P at the values in X. +% +% The size of Y is the common size of the input arguments. A scalar input +% functions as a constant matrix of the same size as the other inputs. +% +% The algorithm uses the cumulative sums of the binomial masses. + +% Reference: +% [1] M. Abramowitz and I. A. Stegun, "Handbook of Mathematical +% Functions", Government Printing Office, 1964, 26.1.20. + +% B.A. Jones 1-12-93 +% Copyright (c) 1993 by The MathWorks, Inc. +% $Revision: 1.1 $ $Date: 1993/05/24 18:53:29 $ + +if nargin < 3, + error('Requires three input arguments.'); +end + +scalarnp = (prod(size(n)) == 1 & prod(size(p)) == 1); + +%[errorcode x n p] = distchck(3,x,n,p); + +% if errorcode > 0 +% error('The arguments must be the same size or be scalars.'); +% end + +% Initialize Y to 0. +y=zeros(size(x)); + +% Y = 1 if X >= N +k = find(x >= n); +if any(k); + y(k) = ones(size(k)); +end + +% Compute Y when 0 < X < N. +xx = floor(x); +k = find(xx >= 0 & xx < n); + +% Accumulate the binomial masses up to the maximum value in X. +if any(k) + val = min(max(max(n)),max(max(xx))); + if scalarnp + tmp = cumsum(binopdf(0:val,n(1),p(1))); + y(k) = tmp(xx(k) + 1); + else + i = [0:val]'; + compare = i(:,ones(size(k))); + index(:) = xx(k); + index = index(:,ones(size(i)))'; + nbig(:) = n(k); + nbig = nbig(:,ones(size(i)))'; + pbig(:) = p(k); + pbig = pbig(:,ones(size(i)))'; + y0 = binopdf(compare,nbig,pbig); + indicator = find(compare > index); + y0(indicator) = zeros(size(indicator)); + y(k) = sum(y0); + end +end + +% Make sure that round-off errors never make P greater than 1. +k = find(y > 1); +if any(k) + y(k) = ones(size(k)); +end + +% Return NaN if any arguments are outside of their respective limits. +k1 = find(n < 0 | p < 0 | p > 1 | round(n) ~= n | x < 0); +if any(k1) + y(k1) = NaN * ones(size(k1)); +end + + + +function y = binopdf(x,n,p) +% BINOPDF Binomial probability density function. +% Y = BINOPDF(X,N,P) returns the binomial probability density +% function with parameters N and P at the values in X. +% Note that the density function is zero unless X is an integer. +% +% The size of Y is the common size of the input arguments. A scalar input +% functions as a constant matrix of the same size as the other inputs. + +% Reference: +% [1] M. Abramowitz and I. A. Stegun, "Handbook of Mathematical +% Functions", Government Printing Office, 1964, 26.1.20. + +% Copyright (c) 1993 by The MathWorks, Inc. +% $Revision: 1.1 $ $Date: 1993/05/24 18:53:34 $ + + +if nargin < 3, + error('Requires three input arguments'); +end + +% [errorcode x n p] = distchck(3,x,n,p); +% +% if errorcode > 0 +% error('The arguments must be the same size or be scalars.'); +% end +% +% Initialize Y to zero. +y = zeros(size(x)); + +% Binomial distribution is defined on positive integers less than N. +k = find(x >= 0 & x == round(x) & x <= n); +if any(k), + nk = round(exp(gammaln(n(k) + 1) - gammaln(x(k) + 1) - gammaln(n(k) - x(k) + 1))); + y(k) = nk .* p(k) .^x(k) .* (1 - p(k)) .^ (n(k) - x(k)); +end + +k1 = find(n < 0 | p < 0 | p > 1 | round(n) ~= n); +if any(k1) + y(k1) = NaN * ones(size(k1)); +end + diff --git a/stat/chi2_cdf.m b/stat/chi2_cdf.m new file mode 100644 index 0000000..c60515f --- /dev/null +++ b/stat/chi2_cdf.m @@ -0,0 +1,32 @@ +function [y]=chi2_cdf(x,dof,invcdf) +%chi2_cdf - Cumulative Distribution Function (CDF) of Chi² (Chi square) distribution +% [P]=chi2_cdf(chi2,dof) +% To get the Chi2 from the p-value (i.e. inverse cdf): +% Chi2 = chi2_cdf(P,-dof,1) +% +% KND, 2011 + +if nargin<3 + invcdf=0; +end +if dof<0 + dof=-dof; + invcdf=1; +end +if invcdf + y=ones(size(x)); + y(x==0)=0; + y(x==1)=Inf; + y(x<0)=NaN; + for i=find(y==1); + fun = @(y)(abs(chi2_cdf(y,dof)-x(i))); + % Guess starting point from normal approximation + y0 = dof+2*sqrt(dof)*erfcinv(2*x(i)); + y0 = max(0,y0); + [y(i),fval,flag,o]=fminsearch(fun,y0); + end +else + y = gammainc(x/2,dof/2); + y(x<0)=NaN; +end +return \ No newline at end of file diff --git a/stat/cohen_d.m b/stat/cohen_d.m new file mode 100644 index 0000000..04a3f2a --- /dev/null +++ b/stat/cohen_d.m @@ -0,0 +1,55 @@ +function [d,h,sigma_d,r2]=cohen_d(X1,X2,variant,parameters) +% cohen_d() - Computes Cohen's d' effect size and variants +% [d]=cohen_d(X1,X2) +% [d]=cohen_d(X1,X2,variant) with 'variant' being: +% 'none' (default) +% 'winsor' +% [d,h]=cohen_d(...) also compute Hedge's corrected d +% [d,h,sigma_d]=cohen_d(...) outputs sigma_d the S.D. of d so that +% Conf. Interval for d = d +/- 1.96*sigma_d +% +% [d,h,sigma_d,r2]=cohen_d(...) outputs r2 the percent variance explained + +if nargin<3 + options =[]; +end + +m2=0; +n2=0; +v2=0; +if nargin>1 + if isvector(X1) & isvector(X2) + X2=X2(:); + X1=X1(:); + end + m2=mean(X2); + n2=size(X2,1); + v2=var(X2); +elseif isvector(X1) + X1=X(:); +end + +if nargin>2 + switch lower(variant) + case 'none' + case {'winsor', 'winsorized', 'trimmed'} + +end +end + +m1=mean(X1); +n1=size(X1,1); +v1=var(X1); + +n = n1+n2; +pooled_v = ((n1-1)*v1 + (n2-1)*v2)./(n-2); + +d = (m1 - m2)./sqrt(pooled_v); + +% Hedges and Olkin's correction for small samples +% Hedges, L. and Olkin, I. (1985) +% Statistical Methods for Meta-Analysis. +% New York: Academic Press. +h = d*(1-3/(4*n-9)); +sigma_d = sqrt(n/n1/n2 + d.^2/2/n); +r2 = d.^2./(d.^2+4); diff --git a/stat/coincidence_matrix.m b/stat/coincidence_matrix.m new file mode 100644 index 0000000..b063e58 --- /dev/null +++ b/stat/coincidence_matrix.m @@ -0,0 +1,99 @@ +function [C] = coincidence_matrix(X) +levx = (unique(X(~isnan(X)))); +nval = numel(x); +cm = zeros(nval); +mu = no - sum(isnan(R)); + +P = nchoosek(r,2); +P = [ P ; fliplr(P) ]; +P = sortrows([ [r(:) r(:)] ; P ]); +np = size(P,1); +%Coincidence values +C = repmat(R, [ 1 1 np]) == permute(repmat(P',[1 1 nm ]), [1 3 2]); +C = squeeze(sum(all(C),2)) +% ... into matrix +C = reshape(C,[nr nr]); +C = C' + C; +n = 2*nm; +nc = sum(C); +dimx = size(X); + +% http://pbil.univ-lyon1.fr/library/concord/R/concord +% # calculates the coincidence matrix for the kripp.alpha() function +% +% coincidence.matrix<-function(x) { +% levx<-(levels(as.factor(x))) +% nval<-length(levx) +% # set up a coincidence matrix to hold the match/mismatch data +% cm<-matrix(rep(0,nval*nval),nrow=nval) +% dimx<-dim(x) +% # calculate correction factor (?) for data with missing values +% vn<-function(datavec) sum(!is.na(datavec)) +% if(any(is.na(x))) mc<-apply(x,2,vn)-1 +% else mc<-rep(1,dimx[2]) +% for(col in 1:dimx[2]) { +% for(i1 in 1:(dimx[1]-1)) { +% for(i2 in (i1+1):dimx[1]) { +% if(!is.na(x[i1,col]) && !is.na(x[i2,col])) { +% index1<-which(levx==x[i1,col]) +% index2<-which(levx==x[i2,col]) +% cm[index1,index2]<-cm[index1,index2]+(1+(index1==index2))/mc[col] +% if(index1 != index2) cm[index2,index1]<-cm[index1,index2] +% } +% } +% } +% } +% nmv<-sum(apply(cm,2,sum)) +% return(list(statistic=NA,coincidence.matrix=cm,data.values=levx,nmatchval=nmv)) +% } +% +% # calculates Krippendorff's alpha +% +% kripp.alpha<-function(x,method="nominal") { +% if(!missing(x)) { +% cm<-coincidence.matrix(x) +% dimcm<-dim(cm$coincidence.matrix) +% # upper triangle of the coincidence matrix as a vector +% utcm<-as.vector(cm$coincidence.matrix[upper.tri(cm$coincidence.matrix)]) +% # diagonal of the coincidence matrix +% diagcm<-diag(cm$coincidence.matrix) +% # sum of diagonal elements of coincidence matrix +% occ<-sum(diagcm) +% # the marginal sums for the coincidence matrix +% nc<-apply(cm$coincidence.matrix,1,sum) +% # calculate this term to simplify +% ncnc<-sum(nc*(nc-1)) +% # need the data values for interval and ratio methods +% dv<-as.numeric(cm$data.values) +% diff2<-rep(0,length(utcm)) +% ncnk<-rep(0,length(utcm)) +% ck<-1 +% for(k in 2:dimcm[2]) { +% for(c in 1:(k-1)) { +% ncnk[ck]<-nc[c]*nc[k] +% if(method == "nominal") diff2[ck]<-1 +% if(method == "ordinal") { +% diff2[ck]<-nc[c]/2 +% if(k > (c+1)) { +% for(g in (c+1):(k-1)) { +% diff2[ck]<-diff2[ck]+nc[g] +% } +% } +% diff2[ck]<-diff2[ck]+nc[k]/2 +% diff2[ck]<-diff2[ck]^2 +% } +% if(method == "interval") diff2[ck]<-(dv[c]-dv[k])^2 +% if(method == "ratio") { +% diff2[ck]<-(dv[c]-dv[k])^2/(dv[c]+dv[k])^2 +% } +% ck<-ck+1 +% } +% } +% cm$statistic<-1-(cm$nmatchval-1)*sum(utcm*diff2)/sum(ncnk*diff2) +% return(cm) +% } +% else { +% cat("Usage: kripp.alpha(x,method=c(\"nominal\",\"ordinal\",\"interval\",\"ratio\"))\n") +% cat("\twhere x is a classifier by object matrix of classifications\n\n") +% } +% } diff --git a/stat/compare_anovas.m b/stat/compare_anovas.m new file mode 100644 index 0000000..9b28d9b --- /dev/null +++ b/stat/compare_anovas.m @@ -0,0 +1,3 @@ + + +stats=Compute_anova_Optimized(dim_to_get,X,sujets,Logique,1,signedF, minusLogp); \ No newline at end of file diff --git a/stat/cronbach.m b/stat/cronbach.m new file mode 100644 index 0000000..daf658c --- /dev/null +++ b/stat/cronbach.m @@ -0,0 +1,46 @@ +function a=cronbach(X) +%cronbach - Calculates the Cronbach's alpha of a data set X. +% +% a=cronbach(X) +% a is the Cronbach's alpha. +% X is the data set (Observations by Items). +% + +% Reference: +% Cronbach L J (1951): Coefficient alpha and the internal structure of +% tests. Psychometrika 16:297-333 + +a=1/(1-1/size(X,2))*(1-sum(var(X))./var(sum(X,2))); + +% +% % Alexandros Leontitsis +% % Department of Education +% % University of Ioannina +% % Ioannina +% % Greece +% % +% % e-mail: leoaleq@yahoo.com +% % Homepage: http://www.geocities.com/CapeCanaveral/Lab/1421 +% % +% % June 10, 2005. +% +% if nargin<1 | isempty(X)==1 +% error('You shoud provide a data set.'); +% else +% % X must be a 2 dimensional matrix +% if ndims(X)~=2 +% error('Invalid data set.'); +% end +% end +% +% +% % Calculate the number of items +% k=size(X,2); +% +% % Calculate the variance of the items' sum +% VarTotal=; +% +% % Calculate the item variance +% SumVarX=; +% +% % Calculate the Cronbach's alpha diff --git a/stat/distributionPlot/countEntries.m b/stat/distributionPlot/countEntries.m new file mode 100644 index 0000000..8f954f0 --- /dev/null +++ b/stat/distributionPlot/countEntries.m @@ -0,0 +1,110 @@ +function [uniqueEntries,numberOfOccurences,whereIdx] = countEntries(m,isRow, keepNaN) +%COUNTENTRIES returns all unique entries (sorted) in the array m and how many times the respective entries occured +% +%SYNOPSIS [uniqueEntries,numberOfOccurences] = countEntries(m,isRow) +% +%INPUT m : any matrix (not cells or structs) +% isRow(opt) : should rows be counted or not [1/{0}] +% (if it's cols, transpose m before calling the function!) +% keepNaN (opt) : count NaN as entry? [{1}/0] If 0, NaNs (or +% NaN-containing rows) are removed after sorting, so +% that whereIdx still refers to the original position +% of the uniqueEntries in the input array. +% +%OUTPUT uniqueEntries : unique(m) +% numberOfOccurences : how many times the unique entries appear in m +% whereIdx : where in m do the entries appear? (m = uniqueEntries(whereIdx,:)) +% +%c: 11/03, jonas +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + +%---test input +if iscell(m) || isstruct(m) + error('cells and structs are not supportet as input'); +end + +if nargin < 2 || isempty(isRow) + doRow = 0; +else + if isRow == 1; + doRow = 1; + elseif isRow == 0 + doRow = 0; + else + error('input argument isRow has to be 1 or 0!') + end +end +if nargin < 3 || isempty(keepNaN) + keepNaN = true; +end +%---end test input + + + +if ~doRow %do the fast method + + %make m into a vector + m = m(:); + + %get unique Entries. sort them first, though + m = sort(m); + + [uniqueEntries, uniqueIdx, whereIdx] = unique(m); + + if ~keepNaN + % remove NaN, inf + badIdx = find(~isfinite(uniqueEntries)); + uniqueEntries(badIdx) = []; + uniqueIdx(badIdx) = []; + whereIdx(ismember(whereIdx,badIdx)) = []; + end + + %uniqueIdx returns the last occurence of the respective unique entry + %having sorted m before, we can now count the number of occurences + if size(uniqueEntries,1)>size(uniqueEntries,2) + uniqueIdx = [0;uniqueIdx]; + else + uniqueIdx = [0,uniqueIdx]; + end + + numberOfOccurences = diff(uniqueIdx); + +else %do it the complicated way + + %we do not care about the ordering of the matrix here: if the user + %specified rows, he/she wanted a columnVector as output (or should read the help) + [uniqueEntries, dummy, uniqueIdx] = unique(m,'rows'); + + %rember output + whereIdx = uniqueIdx; + + if ~keepNaN + % remove NaN, inf + badIdx = find(any(~isfinite(uniqueEntries),2)); + uniqueEntries(badIdx,:) = []; + whereIdx(ismember(whereIdx,badIdx)) = []; + uniqueIdx = whereIdx; + end + + %uniqueIdx returns the indexList where uniqueEntriy #x occurs. + %We will now sort this list and take a diff to find where this index + %changes. + %adding zero and length(uniqueIndex) to the vector, we can now via + %another diff see how many entries there are (see example) + + %example m: [11,11,22,33,33,22,22,22,44,11] + %corresponding uniqueEntries, uniqueIdx: [11,22,33,44] / [1 1 2 3 3 2 2 2 4 1] + + %sort: [1 1 1 2 2 2 2 3 3 4] + sortedIdx = sort(uniqueIdx); + + %diff: [0 0 1 0 0 0 1 0 1] + sortedIdxDiff = diff(sortedIdx); + + %find and add entries: [0 3 7 9 10] + changeValueIdx = [0;find(sortedIdxDiff);length(uniqueIdx)]; + + %diff again for the numberOfOccurences: [3 4 2 1] + numberOfOccurences = diff(changeValueIdx); +end \ No newline at end of file diff --git a/stat/distributionPlot/distributionPlot.m b/stat/distributionPlot/distributionPlot.m new file mode 100644 index 0000000..8bfcc21 --- /dev/null +++ b/stat/distributionPlot/distributionPlot.m @@ -0,0 +1,270 @@ +function handles = distributionPlot(varargin) +%DISTRIBUTIONPLOT plots distributions similar to boxplot +% +% SYNOPSIS: handles = distributionPlot(data,distWidth,showMM,xNames,histOpt,divFactor,invert) +% handles = distributionPlot(ah,...) +% +% INPUT data : cell array of length nData (with data shaped as vectors) or +% m-by-nData array of values +% distWidth : (opt) width of distributions. 1 means that the maxima +% of two adjacent distributions might touch. Negative numbers +% indicate that the distributions should have constant width, i.e +% the density is only expressed through greylevels. +% Values between 1 and 2 are like values between 0 and 1, except +% that densities are not expressed via graylevels. Default: 1.9 +% showMM : (opt) if 1, mean and median are shown as red circles and +% green squares, respectively. Default: 1 +% 2: only mean +% 3: only median +% xNames : (opt) cell array of length nData containing x-tick names +% (instead of the default '1,2,3') +% histOpt : (opt) histogram type to plot +% 0 : use hist command (no smoothing, fixed number of +% bins) +% 1 : smoothened histogram using ksdensity with +% Epanechnikov-kernel. Default. +% 2 : histogram command (no smoothing, automatic +% determination of bin width) +% divFactor : (opt) Parameter dependent on histOpt. +% histOpt == 0: divFactor = # of bins. Default: 25. +% Alternatively, pass a vector which will be +% interpreted as bin centers. +% histOpt == 1: divFactor decides by how much the default +% kernel-width is multiplied in order to avoid an +% overly smooth histogram. Default: 1/2 +% histOpt == 2: divFactor decides by how much the +% automatic bin width is multiplied in order to have +% more (<1) or less (>1) detail. Default: 1 +% histOpt == 3: divFacor specifies the bin locations +% invert : (opt) if 1, image will be white on black. Default: 0 +% ah (opt) axes handle to plot the distribution. Default: gca +% +% OUTPUT handles : 1-by-3 cell array with patch-handles for the +% distributions, plot handles for mean/median, and the +% axes handle +% +% REMARKS +% +% created with MATLAB ver.: 7.6.0.324 (R2008a) on Windows_NT +% +% created by: Jonas Dorn +% DATE: 08-Jul-2008 +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +%==================================== +%% TEST INPUT +%==================================== + +% set defaults +def_xNames = []; +def_showMM = 1; +def_distWidth = 1.9; +def_histOpt = 1; +def_divFactor = [25,2,1]; +def_invert = false; +useGray = true; + +if nargin == 0 + error('not enough input arguments') +end + +% check for axes handle +if ~iscell(varargin{1}) && length(varargin{1}) == 1 && ... + ishandle(varargin{1}) && strcmp(get(varargin{1},'Type'),'axes') + ah = varargin{1}; + data = varargin{2}; + varargin(1:2) = []; + newAx = false; +else + ah = gca; + data = varargin{1}; + varargin(1) = []; + newAx = true; +end + +% check data. If not cell, convert +if ~iscell(data) + [nPoints,nData] = size(data); + data = mat2cell(data,nPoints,ones(nData,1)); +else + % get nData + data = data(:); + nData = length(data); + % make sure all are vectors + badCol = ~cellfun(@isvector,data); + if any(badCol) + warning('DISTRIBUTIONPLOT:AUTORESHAPE',... + 'Elements %s of the cell array are not vectors. They will be reshaped automatically',... + num2str(find(badCol)')); + data(badCol) = cellfun(@(x)(x(:)),data(badCol),'UniformOutput',false); + end +end + + +% check for names, defaults +if ~isempty(varargin) && ~isempty(varargin{1}) + distWidth = varargin{1}; + if distWidth == 0 + error('distWidth==0 will not plot anything') + end +else + distWidth = def_distWidth; +end +if distWidth > 1 + distWidth = distWidth - 1; + useGray = false; +end +if length(varargin) > 1 && ~isempty(varargin{2}) + showMM = varargin{2}; +else + showMM = def_showMM; +end +if length(varargin) > 2 && ~isempty(varargin{3}) + xNames = varargin{3}; +else + xNames = def_xNames; +end +if length(varargin) > 3 && ~isempty(varargin{4}) + histOpt = varargin{4}; +else + histOpt = def_histOpt; +end +if length(varargin) > 4 && ~isempty(varargin{5}) + divFactor = varargin{5}; +else + divFactor = def_divFactor(histOpt+1); +end +if length(varargin) > 5 && ~isempty(varargin{6}) + invert = varargin{6}; +else + invert = def_invert; +end + + +% set hold on +holdState = get(ah,'NextPlot'); +set(ah,'NextPlot','add'); + +% if new axes: invert +if newAx && invert + set(gca,'Color','k') +end + +%=================================== + + + +%=================================== +%% PLOT DISTRIBUTIONS +%=================================== + +% assign output +hh = cell(nData,1); +[m,md] = deal(nan(nData,1)); + +% get base x-array +xBase = abs(distWidth) .* [-0.5;0.5;0.5;-0.5]; + +% loop through data. Prepare patch input, then draw patch into gca +for iData = 1:nData + currentData = data{iData}; + % only plot if there is some finite data + if ~isempty(currentData) && any(isfinite(currentData)) + + switch histOpt + case 0 + % use hist + [xHist,yHist] = hist(currentData,divFactor); + + case 1 + % use ksdensity + + % make histogram (use ksdensity for now) + % x,y are switched relative to normal histogram + [xHist,yHist,u] = ksdensity(currentData,'kernel','epanechnikov'); + % take smaller kernel to avoid over-smoothing + if divFactor ~= 1 + [xHist,yHist] = ksdensity(currentData,'kernel','epanechnikov','width',u/divFactor); + end + + case 2 + % use histogram + [xHist,yHist] = histogram(currentData,divFactor); + end + + % find y-step + dy = min(diff(yHist)); + + % create x,y arrays + nPoints = length(xHist); + xArray = repmat(xBase,1,nPoints); + yArray = repmat([-0.5;-0.5;0.5;0.5],1,nPoints); + + % x is iData +/- almost 0.5, multiplied with the height of the + % histogram + if distWidth > 0 + xArray = xArray.*repmat(xHist,4,1)./max(xHist) + iData; + else + xArray = xArray + iData; + end + + % yData is simply the bin locations + yArray = repmat(yHist,4,1) + dy*yArray; + + % add patch + axes(ah); + if invert + if useGray + hh{iData} = patch(xArray,yArray,repmat(xHist/max(xHist),[4,1,3])); + else + hh{iData} = patch(xArray,yArray,'w'); + end + else + if useGray + hh{iData} = patch(xArray,yArray,repmat(1-xHist/max(xHist),[4,1,3])); + else + hh{iData} = patch(xArray,yArray,'k'); + end + end + set(hh{iData},'EdgeColor','none') + + m(iData) = nanmean(currentData); + md(iData) = nanmedian(currentData); + end +end % loop + +if showMM + % plot mean, median. Mean is filled red circle, median is green square + if any(showMM==[1,2]) + mh = plot(1:nData,m,'or','MarkerFaceColor','r'); + end + if any(showMM==[1,3]) + mdh = plot(1:nData,md,'sg'); + end +end + +% if ~empty, use xNames +set(ah,'XTick',1:nData); +if ~isempty(xNames) + set(ah,'XTickLabel',xNames) +end +% have plot start/end properly +xlim([0,nData+1]) + +%========================== + + +%========================== +%% CLEANUP & ASSIGN OUTPUT +%========================== + +if nargout > 0 + handles{1} = hh; + if showMM + handles{2} = [mh;mdh]; + end + handles{3} = ah; +end + +set(ah,'NextPlot',holdState); \ No newline at end of file diff --git a/stat/distributionPlot/histogram.m b/stat/distributionPlot/histogram.m new file mode 100644 index 0000000..dc1bfef --- /dev/null +++ b/stat/distributionPlot/histogram.m @@ -0,0 +1,207 @@ +function [N,X,sp] = histogram(varargin) +% HISTOGRAM generates a histogram using the "optimal" number of bins +% +% If called with no output argument, histogram plots into the current axes +% +% SYNOPSIS [N,X,sp] = histogram(data,factor,normalize) +% [...] = histogram(data,'smooth') +% [...] = histogram(axesHandle,...) +% +% INPUT data: vector of input data +% factor: (opt) factor by which the bin-widths are multiplied +% if 'smooth' (or 's'), a smooth histogram will be formed. +% (requires the spline toolbox). For an alternative +% approach to a smooth histogram, see ksdensity.m +% if 'discrete' (or 'd'), the data is assumed to be a discrete +% collection of values. Note that if every data point is, +% on average, repeated at least 3 times, histogram will +% consider it a discrete distribution automatically. +% if 'continuous' (or 'c'), histogram is not automatically +% checking for discreteness. +% normalize : if 1 (default), integral of histogram equals number +% data points. If 0, height of bins equals counts. +% This option is exclusive to non-"smooth" histograms +% axesHandle: (opt) if given, histogram will be plotted into these +% axes, even if output arguments are requested +% +% OUTPUT N : number of points per bin (value of spline) +% X : center position of bins (sorted input data) +% sp : definition of the smooth spline +% +% REMARKS: The smooth histogram is formed by calculating the cumulative +% histogram, fitting it with a smoothening spline and then taking +% the analytical derivative. If the number of data points is +% markedly above 1000, the spline is fitting the curve too +% locally, so that the derivative can have huge peaks. Therefore, +% only 1000-1999 points are used for estimation. +% Note that the integral of the spline is almost exactly the +% total number of data points. For a standard histogram, the sum +% of the hights of the bins (but not their integral) equals the +% total number of data points. Therefore, the counts might seem +% off. +% +% WARNING: If there are multiples of the minimum value, the +% smooth histogram might get very steep at the beginning and +% produce an unwanted peak. In such a case, remove the +% multiple small values first (for example, using isApproxEqual) +% +% +% c: 2/05 jonas +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% test input +if nargin < 1 + error('not enough input arguments for histogram') +end + +% check for axes handle +if length(varargin{1}) == 1 && ishandle(varargin{1}); + axesHandle = varargin{1}; + varargin(1) = []; +else + % ensure compatibility to when axesHandle was given as last input + if nargin == 3 && ishandle(varargin{end}) && varargin{end} ~= 0 + axesHandle = varargin{end}; + varargin(end) = []; + else + axesHandle = 0; + end +end + +% assign data +numArgIn = length(varargin); +data = varargin{1}; +data = data(:); + +% check for non-finite data points +data(~isfinite(data)) = []; + +% check for "factor" +if numArgIn < 2 || isempty(varargin{2}) + factor = 1; +else + factor = varargin{2}; +end +if ischar(factor) + switch factor + case {'smooth','s'} + factor = -1; + case {'discrete','d'} + factor = -2; + case {'continuous','c'} + factor = -3; + otherwise + error('The only string inputs permitted for histogram.m are ''smooth'',''discrete'', or ''continuous''') + end +else + % check for normalize, but do so only if there is no "smooth". Note + % that numArgIn is not necessarily equal to nargin + if numArgIn < 3 || isempty(varargin{3}) + normalize = true; + else + normalize = varargin{3}; + end +end + +% doPlot is set to 1 for now. We change it to 0 below if necessary. +doPlot = 1; + +nData = length(data); +% check whether we do a standard or a smooth histogram +if factor ~= -1 + % check for discrete distribution + [xx,nn] = countEntries(data); + % consider the distribution discrete if there are, on average, 3 + % entries per bin + nBins = length(xx); + if factor == -2 || (factor ~= -3 && nBins*3 < nData) + % discrete distribution. + nn = nn'; + xx = xx'; + else + % not a discrete distribution + if nData < 20 + warning('HISTOGRAM:notEnoughDataPoints','Less than 20 data points!') + nBins = ceil(nData/4); + else + + % create bins with the optimal bin width + % W = 2*(IQD)*N^(-1/3) + interQuartileDist = diff(prctile(data,[25,75])); + binLength = 2*interQuartileDist*length(data)^(-1/3)*factor; + + % number of bins: divide data range by binLength + nBins = round((max(data)-min(data))/binLength); + + if ~isfinite(nBins) + nBins = length(unique(data)); + end + + end + + + + % histogram + [nn,xx] = hist(data,nBins); + % adjust the height of the histogram + if normalize + Z = trapz(xx,nn); + nn = nn * nData/Z; + end + + end + if nargout > 0 + N = nn; + X = xx; + doPlot = axesHandle; + end + if doPlot + if axesHandle + bar(axesHandle,xx,nn,1); + else + bar(xx,nn,1); + end + end + +else + % make cdf, smooth with spline, then take the derivative of the spline + + % cdf + xData = sort(data); + yData = 1:nData; + + % when using too many data points, the spline fits very locally, and + % the derivatives can still be huge. Good results can be obtained with + % 500-1000 points. Use 1000 for now + step = max(floor(nData/1000),1); + xData2 = xData(1:step:end); + yData2 = yData(1:step:end); + + % spline. Use strong smoothing + cdfSpline = csaps(xData2,yData2,1./(1+mean(diff(xData2))^3/0.0006)); + + % pdf is the derivative of the cdf + pdfSpline = fnder(cdfSpline); + + % histogram + if nargout > 0 + xDataU = unique(xData); + N = fnval(pdfSpline,xDataU); + X = xDataU; + % adjust the height of the histogram + Z = trapz(X,N); + N = N * nData/Z; + sp = pdfSpline; + % set doPlot. If there is an axesHandle, we will plot + doPlot = axesHandle; + end + % check if we have to plot. If we assigned an output, there will only + % be plotting if there is an axesHandle. + if doPlot + if axesHandle + plot(axesHandle,xData,fnval(pdfSpline,xData)); + else + plot(xData,fnval(pdfSpline,xData)); + end + end +end \ No newline at end of file diff --git a/stat/distributionfit.m b/stat/distributionfit.m new file mode 100644 index 0000000..5e3c86b --- /dev/null +++ b/stat/distributionfit.m @@ -0,0 +1,188 @@ +function [pdffit,offset,A,B,resnorm,h] = distributionfit(data,distribution,nbins) +%function [pdffit,offset,A,B,resnorm,h] = distributionfit(data,distribution,nbins) +%PURPOSE jdc rev. 06-jun-05 +% Fit one of three probability distributions (normal, lognormal, weibull) +% to input data vector. If the distribution is specified as 'best' the dis- +% tribution that best fits the data is selected automatically. +%INPUT +% If nargin==1, "distribution" is prompted for and entered interactively +% +% data - n x 1 or 1 x n input data vector +% distribution - probability distribution to fit to "data". Can +% be 'normal', 'lognormal', 'weibull', or 'best' ... default: 'best' +% nbins - number of bar-chart bins ......................... default: sqrt(length(data)) +%OUTPUT +% pdffit - fitted probability density function - n x 2 matrix with column 1 the +% x-values, column 2 the y values +% offset - amount by which the data was offset for lognormal or weibull fits +% (to satisfy the positive-definite requirements for these distributions). +% Note: this is roughly equivalent to fitting a 3- rather than a 2-parameter +% distribution. +% A,B - distribution parameters - mu and sigma for normal and lognormal distributions, +% scale and shape parameters for weibull distribution +% h - handles to the bar chart and probability density curve +% +%TYPICAL FUNCTION CALLS +% distributionfit(randn(10000,1)); +% distributionfit(wblrnd(2,3,10000,1)); +% distributionfit(wblrnd(2,3,10000,1),'weibull'); +% distributionfit(lognrnd(1.5,.5,10000,1),'lognormal'); +% distributionfit(lognrnd(1.5,.5,10000,1),'best'); +% distributionfit(lognrnd(1.5,.5,10000,1),'lognormal'); +% +%REFERENCE +% Statistics Toolbox Version 3.0.2, function HISTFIT.M + +data = data(~isnan(data)); +data = data(:); +ndata = length(data); +if nargin<3 | isempty(nbins), nbins = ceil(sqrt(ndata)); end +if nargin==1, + distID = menu('Choose a Distribution','Normal','Lognormal','Weibull','best'); +else + if strfind(lower(distribution),'lognormal'), distID = 2; + elseif strfind(lower(distribution),'normal' ), distID = 1; + elseif strfind(lower(distribution),'weibull' ), distID = 3; + elseif strfind(lower(distribution),'best' ), distID = 4; + elseif isempty(distribution), distID = 4; + end +end +switch distID + case 1, distribution = 'Normal'; + case 2, distribution = 'Lognormal'; + case 3, distribution = 'Weibull'; + case 4 + data = sort(data); + cdfe = (1:ndata)'/ndata; % experimental cdf + phat = mle(data,'distribution','Normal'); + A = phat(1); % for normal & lognormal, phat = [mu std], for weibull, = [A B] + B = phat(2); + cdft = cdf('Normal',data,A,B); % best-fit cdf + residuals = cdfe-cdft; + resnormNormal = residuals'*residuals; + %------------------------------------- + offset = -min(data)+10*eps; + offsetdata = data+offset; % zero-shift data so smallest value is 0+ + phat = mle(offsetdata,'distribution','Lognormal'); + A = phat(1); % for normal & lognormal, phat = [mu std], for weibull, = [A B] + B = phat(2); + cdft = cdf('Lognormal',offsetdata,A,B); % best-fit cdf + residuals = cdfe-cdft; + resnormLognormal = residuals'*residuals; + %------------------------------------- + phat = mle(offsetdata,'distribution','Weibull'); + A = phat(1); % for normal & lognormal, phat = [mu std], for weibull, = [A B] + B = phat(2); + cdft = cdf('Weibull',offsetdata,A,B); % best-fit cdf + residuals = cdfe-cdft; + resnormWeibull = residuals'*residuals; + %------------------------------------- + resnorms = [resnormNormal resnormLognormal resnormWeibull]; + distID = find(resnorms==min(resnorms)); + switch distID + case 1, distribution = 'Normal'; + case 2, distribution = 'Lognormal'; + case 3, distribution = 'Weibull'; + end +end +if distID==2 | distID==3, + offset = -min(data)+10*eps; + data = data+offset; % zero-shift data for lognormal and weibull fits so smallest value is 0+ +elseif distID==1, + offset = 0; +end +%---------------------------------------------------------------------- +figure +[n,xbin]=hist(data,nbins); +hh = bar(xbin,n,1); % get number of counts per bin and bin width +xd = get(hh,'Xdata'); % retrieve the x-coordinates of the bins. +rangex = max(xd(:)) - min(xd(:)); % find the bin range +binwidth = rangex/nbins; % find the width of each bin. +close(gcf); % close figure (will replot on probability scale) +%---------------------------------------------------------------------- +ch = get(0,'children'); +if isempty(ch), + figure(1); +else + figure(max(ch)+1); +end +set(0,'Units','inches'); +ss = get(0,'ScreenSize'); +set(0,'Units','pixels'); +width = 3; +height = 3; +edge = 0.25; +set(gcf,'Units','inches','Position',[ss(3)-width-edge ss(4)-height-edge width height],... + 'Color',[.8 .8 .8],'InvertHardCopy','off','PaperPosition',[1 1 width height]); +nscaled = n/(ndata*binwidth); % convert bin counts to probabilities +hh = bar(xbin,nscaled,1); % draw the probability-scaled bars +set(hh,'EdgeColor',[.6 .6 .6],'FaceColor',[.9 .9 .9]); +set(gca,'FontSize',8); +xlabel('Data'); +ylabel('Probability Density'); +%---------------------------------------------------------------------- +phat = mle(data,'distribution',distribution); % probability distribution parameter estimation +A = phat(1); % for normal & lognormal, phat = [mu std], for weibull, = [A B] +B = phat(2); +switch distID % get limits for plotting the best-fit pdf curve + case 1, + lolim = norminv(0.0001,A,B); + hilim = norminv(0.9999,A,B); + case 2, + lolim = logninv(0.0001,A,B); + hilim = logninv(0.9999,A,B); + case 3, + lolim = wblinv(0.0001,A,B); + hilim = wblinv(0.9999,A,B); +end +xpdf = (lolim:(hilim-lolim)/100:hilim); % construct the x-vector for the pdf curve +ypdf = pdf(distribution,xpdf,A,B); +hh1 = line(xpdf,ypdf,'Color','r','LineWidth',2); % overplot the histogram with the best-fit pdf curve +pdffit = [xpdf(:) ypdf(:)]; +%---------------------------------------------------------------------- +data = sort(data); % compute resnorm +cdfe = (1:ndata)'/ndata; % experimental cdf +cdft = cdf(distribution,data,A,B); % best-fit cdf +residuals = cdfe-cdft; +resnorm = residuals'*residuals; +%---------------------------------------------------------------------- +xlim = get(gca,'Xlim'); +ylim = get(gca,'Ylim'); +trd = text(xlim(2),ylim(2),distribution,'FontSize',8,'HorizontalAlignment','right','VerticalAlignment','bottom'); +ext = extent(trd); +tld = text(ext(1),ylim(2),'Distribution: ', 'FontSize',8,'HorizontalAlignment','right','VerticalAlignment','bottom'); + +trr = text(xlim(2),ylim(2)-ext(4),sprintf('%8.1e ',resnorm),'FontSize',8,'HorizontalAlignment','right','VerticalAlignment','middle'); +ext = extent(trr); +tll = text(ext(1),ylim(2)-ext(4),'Resnorm: ','FontSize',8,'HorizontalAlignment','right','VerticalAlignment','middle'); + +tt = text(xlim(2),ylim(2)-ext(4),sprintf('%4.2f ',A),'FontSize',8,'HorizontalAlignment','right','Visible','off'); +ext = extent(tt); + +i = 1; +switch distID + case {1,2} + if distID==2, + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'Zero Shift: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%+5.2f',offset)); + i = i+1; + end + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'Sigma: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%4.2f',B)); + i = i+1; + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'Mu: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%4.2f',A)); + case 3 + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'Zero Shift: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%+5.2f',offset)); + i = i+1; + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'scale: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%4.2f',A)); + i = i+1; + tl(i) = text(ext(1),ylim(2)-(i+1)*ext(4),'shape: '); + tr(i) = text(ext(1),ylim(2)-(i+1)*ext(4),sprintf('%4.2f',B)); +end +set(tl,'Color','k','FontSize',8,'HorizontalAlignment','right','VerticalAlignment','middle'); +set(tr,'Color','k','FontSize',8,'HorizontalAlignment','left', 'VerticalAlignment','middle'); +%---------------------------------------------------------------------- +h = [hh; hh1]; diff --git a/stat/dunnsidak.m b/stat/dunnsidak.m new file mode 100644 index 0000000..feeaa0a --- /dev/null +++ b/stat/dunnsidak.m @@ -0,0 +1,34 @@ +function [sig,alpha]=dunnsidak(alpha, n) +% DUNNSIDAK - Dunn-Sidak adjustment of alpha level for multiple comparisons +% alpha2=dunnsidak(alpha1, n) computes the new alpha2 to use when running +% n tests in order to achieve a familywise error rate of alpha +% alpha = 1 - (1-alpha1).^(1./n) +% +% [sig,alphas]=holm(alpha,p) assess the significance of the p-values +% coming from multiple tests according to the Dunn-Sidak correction +% yielding a familywise error rate of alpha. p being a vector of +% p-values, sig will be a logical vector of the same size. +% +% See also: holm, hochberg + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-11-05 Creation +% +% ----------------------------- Script History --------------------------------- + +if numel(n)==1 & n>=1 + alpha=1-(1-alpha).^(1./n); + sig=alpha; + return +end +p=n; +n=numel(p); +alpha=dunnsidak(alpha,n); +sig=p<=alpha; \ No newline at end of file diff --git a/stat/effectsizes_to_errorrates.m b/stat/effectsizes_to_errorrates.m new file mode 100644 index 0000000..92a0e4c --- /dev/null +++ b/stat/effectsizes_to_errorrates.m @@ -0,0 +1,47 @@ +% +% What is your error rate with a D prime of +% http://www.sportsci.org/resource/stats/effectmag.html +% +% NB: +% To take a familiar example of a physical sex difference, the effect size +% for U.S. male-female differences in height is very large at d = 1.93.) +% I found that it means approx. 1/6 men would be categorized as women in a +% cutoff, and 2.7% are below women's mean height) + +clear d r m m2 D v er +D= [0:.1:2 2:1:5] % 1.93 +for j=1:numel(D) + r=zeros(1,100); + for i=1:100 + x=randn(10000,1); + y=randn(10000,1)+D(j); + d(i,j)=cohen_d(x,y); + % percentage below cutoff + er(i,1)=mean([ymean([x;y])]); + er(i,2)=mean([ymean([y])]); + er(i,3)=mean(y=0) + varargout{1} = spm_Fcdf(x,v,w); +else + varargout{1} = spm_invFcdf(1+x,v,w); +end + +return + + +function F = spm_Fcdf(x,v,w) +% Cumulative Distribution Function (CDF) of F (Fisher-Snedecor) distribution +% FORMAT F = spm_Fpdf(x,df) +% FORMAT F = spm_Fpdf(x,v,w) +% +% x - F-variate (F has range [0,Inf) ) +% df - Degrees of freedom, concatenated along last dimension +% Eg. Scalar (or column vector) v & w. Then df=[v,w]; +% v - Shape parameter 1 / numerator degrees of freedom (v>0) +% w - Shape parameter 2 / denominator degrees of freedom (w>0) +% F - CDF of F-distribution with [v,w] degrees of freedom at points x +%_______________________________________________________________________ +% +% spm_Fcdf implements the Cumulative Distribution Function of the F-distribution. +% +% Definition: +%----------------------------------------------------------------------- +% The CDF F(x) of the F distribution with degrees of freedom v & w, +% defined for positive integer degrees of freedom v & w, is the +% probability that a realisation of an F random variable X has value +% less than x F(x)=Pr{X0 & w>0, and for x in [0,Inf) (See Evans et al., Ch16). +% +% Variate relationships: (Evans et al., Ch16 & 37) +%----------------------------------------------------------------------- +% The square of a Student's t variate with w degrees of freedom is +% distributed as an F-distribution with [1,w] degrees of freedom. +% +% For X an F-variate with v,w degrees of freedom, w/(w+v*X^2) has +% distributed related to a Beta random variable with shape parameters +% w/2 & v/2. +% +% Algorithm: +%----------------------------------------------------------------------- +% Using the relationship with the Beta distribution: The CDF of the +% F-distribution with v,w degrees of freedom is related to the +% incomplete beta function by: +% Pr(X1; +if sum(xa)>1 & any(any(diff(as(xa,:)),1)) + error('non-scalar args must match in size'), end + +%-Computation +%----------------------------------------------------------------------- +%-Initialise result to zeros +F = zeros(rs); + +%-Only defined for strictly positive v & w. Return NaN if undefined. +md = ( ones(size(x)) & v>0 & w>0 ); +if any(~md(:)), F(~md) = NaN; + warning('Returning NaN for out of range arguments'), end + +%-Non-zero where defined and x>0 +Q = find( md & x>0 ); +if isempty(Q), return, end +if xa(1), Qx=Q; else Qx=1; end +if xa(2), Qv=Q; else Qv=1; end +if xa(3), Qw=Q; else Qw=1; end + +%-Compute +F(Q) = 1 - betainc(w(Qw)./(w(Qw) + v(Qv).*x(Qx)),w(Qw)/2,v(Qv)/2); + + + +function x = spm_invFcdf(F,v,w) +% Inverse Cumulative Distribution (CDF) of F (Fisher-Snedecor) distribution +% FORMAT x = spm_invFpdf(F,df) +% FORMAT x = spm_invFpdf(F,v,w) +% +% F - CDF (lower tail p-value) +% df - Degrees of freedom, concatenated along last dimension +% Eg. Scalar (or column vector) v & w. Then df=[v,w]; +% v - Shape parameter 1 / numerator degrees of freedom (v>0) +% w - Shape parameter 2 / denominator degrees of freedom (w>0) +% x - F-variate (F has range [0,Inf) ) +%_______________________________________________________________________ +% +% spm_Fcdf implements the inverse Cumulative Distribution Function +% for the F-distribution. +% +% Definition: +%----------------------------------------------------------------------- +% The CDF F(x) of the F distribution with degrees of freedom v & w, +% defined for positive integer degrees of freedom v & w, is the +% probability that a realisation of an F random variable X has value +% less than x F(x)=Pr{X0 & w>0, and for x in [0,Inf) (See Evans et al., Ch16). +% +% Variate relationships: (Evans et al., Ch16 & 37) +%----------------------------------------------------------------------- +% The square of a Student's t variate with w degrees of freedom is +% distributed as an F-distribution with [1,w] degrees of freedom. +% +% For X an F-variate with v,w degrees of freedom, w/(w+v*X^2) has +% distribution related to a Beta random variable with shape parameters +% w/2 & v/2, as described below. +% +% Algorithm: +%----------------------------------------------------------------------- +% Using the routine spm_invBcdf for the Beta distribution, with +% appropriate parameters: The CDF of the F-distribution with v,w +% degrees of freedom is related to the incomplete beta function by: +% Pr(X1; +if sum(xa)>1 & any(any(diff(as(xa,:)),1)) + error('non-scalar args must match in size'), end + +%-Computation +%----------------------------------------------------------------------- +%-Initialise result to zeros +x = zeros(rs); + +%-Only defined for F in [0,1] & strictly positive v & w. +% Return NaN if undefined. +md = ( F>=0 & F<=1 & v>0 & w>0 ); +if any(~md(:)), x(~md) = NaN; + warning('Returning NaN for out of range arguments'), end + +%-Special cases: x=0 when F=0, x=Inf when F=1 +x(md & F==1) = Inf; + +%-Compute where defined & not special case +Q = find( md & F>0 & F<1 ); +if isempty(Q), return, end +if xa(1), QF=Q; else QF=1; end +if xa(2), Qv=Q; else Qv=1; end +if xa(3), Qw=Q; else Qw=1; end + +%-Compute +bQ = spm_invBcdf(1-F(QF),w(Qw)/2,v(Qv)/2); +x(Q) = (w(Qw)./bQ -w(Qw))./v(Qv); + +function x = spm_invBcdf(F,v,w,tol) +% Inverse Cumulative Distribution Function (CDF) of Beta distribution +% FORMAT x = spm_invBcdf(F,v,w,tol) +% +% F - CDF (lower tail p-value) +% v - Shape parameter (v>0) +% w - Shape parameter (w>0) +% x - Beta ordinates at which CDF F(x)=F +% tol - tolerance [default 10^-6] +%__________________________________________________________________________ +% +% spm_invBcdf implements the inverse Cumulative Distribution Function +% for Beta distributions. +% +% Returns the Beta-variate x such that Pr{X0 & w>0 and for x in [0,1] (See Evans et al., Ch5). +% The Cumulative Distribution Function (CDF) F(x) is the probability +% that a realisation of a Beta random variable X has value less than +% x. F(x)=Pr{X1; +if sum(xa)>1 & any(any(diff(as(xa,:)),1)) + error('non-scalar args must match in size'), end + +%-Computation - Undefined and special cases +%----------------------------------------------------------------------- +%-Initialise result to zeros +x = zeros(rs); + +%-Only defined for F in [0,1] & strictly positive v & w. +% Return NaN if undefined. +md = ( F>=0 & F<=1 & v>0 & w>0 ); +if any(~md(:)), x(~md) = NaN; + warning('Returning NaN for out of range arguments'), end + +%-Special cases: x=0 when F=0, x=1 when F=1 +x(md & F==1) = 1; + +%-Compute where defined & not special case +%----------------------------------------------------------------------- +Q = find( md & F>0 & F<1 ); +if isempty(Q), return, end +if xa(1), FQ=F(Q); FQ=FQ(:); else, FQ=F*ones(length(Q),1); end +if xa(2), vQ=v(Q); vQ=vQ(:); else, vQ=v*ones(length(Q),1); end +if xa(3), wQ=w(Q); wQ=wQ(:); else, wQ=w*ones(length(Q),1); end +%-?Q=?Q(:) stuff is to avoid discrepant orientations of vector arguments! + +%-Interval bisection +%----------------------------------------------------------------------- +a = zeros(length(Q),1); fa = a-FQ; +b = ones(length(Q),1); fb = b-FQ; +i = 0; +xQ = a+1/2; +QQ = 1:length(Q); + +while length(QQ) & i 0; + a(QQ(mQQ)) = xQ(QQ(mQQ)); fa(QQ(mQQ)) = fxQQ(mQQ); + b(QQ(~mQQ)) = xQ(QQ(~mQQ)); fb(QQ(~mQQ)) = fxQQ(~mQQ); + xQ(QQ) = a(QQ) + (b(QQ)-a(QQ))/2; + QQ = QQ( (b(QQ)-a(QQ))>tol ); + i = i+1; +end + +if i==maxIt, warning('convergence criteria not reached - maxIt reached'), end + +x(Q) = xQ; diff --git a/stat/friedman_posthoc.m b/stat/friedman_posthoc.m new file mode 100644 index 0000000..08fdc2b --- /dev/null +++ b/stat/friedman_posthoc.m @@ -0,0 +1,106 @@ +function [p]=friedman_posthoc + + + +% /* +% * Post-hoc analyses for a Friedman test of mean ranks in dependent samples +% * see Schaich & Hamerle (1984) and Conover (1971, 1980) as cited by Bortz, Lienert & Boehnke (2000, p. 275) +% * +% * Author: +% * Timo Gnambs +% * URL: http://timo.gnambs.at +% * Last modified: 2004-06-04 +% * +% * +% * Literature: +% * > Bortz, J., Lienert, G. & Boehnke, K. (2000). Verteilungsfreie Methoden in der Biostatistik. Berlin: Springer. +% * > Schaich, E. & Hamerle, A. (1984). Verteilungsfreie statistische Prüfverfahren. Berlin: Springer. +% * > Conover, W. J. (1971,1980). Practical nonparametric statistics. New York: Wiley. +% * +% * Instruction: +% * Modify the two passages titled "Configuration 1" and "Configuration +% */. +% +% +% temporary. +% select if($casenum = 1). +% +% +% /* START Configuration 1 */ +% * Load demo file. +% get file = spss_friedmanph.sav. +% * Significance level. +% compute #alpha = 0.05. +% * Number of variables to compare. +% compute #varcnt = 4. +% * Sample size. +% compute #sample = 5. +% +% * Maximum number of allowed loops. +% * This value must be greater than the sample size (#sample), else SPSS produces errors. +% set mxloop = 500. +% +% /* END Configuration 1 */ +% +% +% compute #chisq = idf.chisq((1 - #alpha), (#varcnt - 1)). +% compute #t = abs(idf.t(#alpha / 2, (#sample - 1) * (#varcnt - 1))). +% write outfile = friedmanposthoctmp / #chisq #t. +% exe. +% +% matrix. +% +% /* Load data to matrix */ +% read sig /file=friedmanposthoctmp /field = 1 to 16 /size = {1,2}. +% +% +% /* START Configuration 2 */ +% +% * Load variables to compare. +% get m /file=* /variables var1 var2 var3 var4. +% +% /* END Configuration 2 */ +% +% +% /* Ranked data */ +% compute #rnked = m. +% loop #i = 1 to nrow(m) by 1. +% compute #tmp = rnkorder(m(#i,:)). +% compute #rnked(#i,:) = #tmp. +% end loop. +% +% /* Sum of ranks */ +% compute #sums = csum(#rnked). +% compute msums = #sums / nrow(m). +% +% /* Rank differences */ +% compute mdiff = ident(ncol(m),ncol(m)). +% loop #j = 1 to (ncol(m)) by 1. +% loop #k = 1 to #j by 1. +% compute mdiff(#j,#k) = msums(#j) - msums(#k). +% compute mdiff(#k,#j) = -mdiff(#j,#k). +% end loop. +% end loop. +% +% /* Critical rank difference */ +% compute cdiff = sqrt(sig(1,1)) * sqrt((ncol(m) * (ncol(m) + 1)) / (nrow(m) * 6)). +% compute cdiff2 = sig(1,2) * sqrt((2 * (mssq(#rnked) - mssq( #sums) / nrow(m))) / (nrow(m) * (nrow(m) - 1) * (ncol(m) - 1))). +% +% /* Print results */ +% print /title 'Post-hoc analyses for Friedman test'. +% print /title 'Author: Timo Gnambs '. +% print /title '----------------------'. +% print ncol(m) /format = f8.0 /title 'Number of variables:'. +% print nrow(m) /format = f8.0 /title 'Sample size:'. +% print msums /format = f8.2 /title 'Mean rank of variables:' /cnames m. +% print mdiff /format f8.2 /title 'Mean rank difference of variables:'. +% print cdiff /format f8.2 /title 'Critical rank difference (Schaich & Hamerle, 1984):'. +% print cdiff2 /format f8.2 /title 'Critical rank difference (Conover, 1971, 1980):'. +% print /title '----------------------'. +% +% end matrix. +% exe. +% +% /* Delete temporary file */ +% erase file = friedmanposthoctmp. +% exe. \ No newline at end of file diff --git a/stat/friedman_test.m b/stat/friedman_test.m new file mode 100644 index 0000000..dcd22f7 --- /dev/null +++ b/stat/friedman_test.m @@ -0,0 +1,110 @@ +function [p,F,fx,epsilon,df,dfe,SS,SSe,SSt,Y]=friedman_test(X,nf,rp) +% friedman_test - Friedman's Test: N-way non-parametric ANOVA (using ranks) +% [p,F,fx]=friedman_test(X,nf) +% X should be [Factor1 x Factor2 x ... x Subjects x ...] +% nf is the number of factors +% rp is the list of within-subject factors +% +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt,Y]=friedman_test(...) +% ouputs data from myanova and Y, the rank matrix +% +% See also: myanova +% Uses: myanova, tiedrank +if nargin<3 + rp=[]; +end +if not(isempty(rp)) & ~all(ismember(1:nf, rp)) + error('Cannot deal with split-plot (ie. mixed) designs') +end +% This test is an ANOVA on the rank +sX=size(X); +ng=sX(1:nf); % nb of groups in each factor +png=prod(ng); % nb of cells +if isempty(rp) + %data are ranked across subjects + X=reshape(X,png*sX(nf+1),[]); +else + %data are ranked within subjects + X=reshape(X,png,[]); +end +Y=tiedrank(X); +Y=reshape(Y,sX); +if nargout>3 + [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(Y,nf,rp); +else + [p,F,fx]=myanova(Y,nf,rp); +end +return + +%% This example is in the SAS Sample library. +% TEST DATA: +% http://www.biostat.wustl.edu/archives/html/jmp-l/1995/msg00168.html +% columns: TREATMENT, 4-level within +% rows: SUBJECTS N=6 +X =[32.6 36.4 29.5 29.4 ; + 42.7 47.1 32.9 40.2 ; + 35.3 40.1 33.6 35 ; + 35.2 40.3 35.7 40 ; + 33.2 34.3 33.2 34 ; + 33.1 34.4 33.1 34.1 ]'; +% WARNING : the following does not used tied ranks! +% so tweak the data an epsilon bit... +X(1,5)=X(1,5)-1e-10; +X(1,6)=X(1,6)-1e-10; +friedman_test(X,1,1) +% Results : +% Response: Rank within Block +% Effect Test +% Source Nparm DF Sum of Squares F Ratio Prob>F +% BLOCK 5 5 0.000000 0.0000 1.0000 +% TRTMENT 3 3 19.333333 9.0625 0.0011 +% +% Step 4: +% TO CALCULATE THE CHI-SQUARE, +% MULTIPLY THE SUM-OF-SQUARES FOR TREATMENT BY +% 12/((T*(T+1)) WHERE T IS THE NUMBER OF TREATMENTS. + + + +%% Example from ZAR, p. 265 +X=[ 7.0 5.3 4.9 8.8 + 9.9 5.7 7.6 8.9 + 8.5 4.7 5.5 8.1 + 5.1 3.5 2.8 3.3 + 10.3 7.7 8.4 9.1]; + +% Cousineau 2005; TQPM +% Simulated data of a 2-by-5 exp with 16 subjects +X=str2num(urlread('http://www.tqmp.org/Content/vol01-1/p042/p042.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +p=myanova(X,2,1:2) +% all the variances are homogeneous and spherical, Tabachnik & Fidell, 1996 +% Mauchly s W = 0.74, p > .50 for factor 2 +% and W = 0.68, p > .50 for the interaction; + + +%% Avec R +%% http://www.r-statistics.com/2010/02/post-hoc-analysis-for-friedmans-test-r-code/ +X=[5.40, 5.50, 5.55, + 5.85, 5.70, 5.75, + 5.20, 5.60, 5.50, + 5.55, 5.50, 5.40, + 5.90, 5.85, 5.70, + 5.45, 5.55, 5.60, + 5.40, 5.40, 5.35, + 5.45, 5.50, 5.35, + 5.25, 5.15, 5.00, + 5.85, 5.80, 5.70, + 5.25, 5.20, 5.10, + 5.65, 5.55, 5.45, + 5.60, 5.35, 5.45, + 5.05, 5.00, 4.95, + 5.50, 5.50, 5.40, + 5.45, 5.55, 5.50, + 5.55, 5.55, 5.35, + 5.45, 5.50, 5.55, + 5.50, 5.45, 5.25, + 5.65, 5.60, 5.40, + 5.70, 5.65, 5.55, + 6.30, 6.30, 6.25] \ No newline at end of file diff --git a/stat/ftest.m b/stat/ftest.m new file mode 100644 index 0000000..09930e0 --- /dev/null +++ b/stat/ftest.m @@ -0,0 +1,33 @@ +function [p, f] = ftest(d1, d2) +%FTEST F-test for two samples. +% FTEST(X1, X2) gives the probability that the F value +% calculated as the rati of the variances of the two samples is +% greater than observed, i.e. the significance level. +% [P, F] = FTEST(X1, X2) gives the probability P and returns +% the value of F. +% +% A small value of P would lead to reject the hypothesis that +% both data sets are sampled from distributions with the same +% variances. +% +%See also : TTEST, TEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +f = v1 / v2 ; +df1 = n1 - 1 ; +df2 = n2 - 1 ; +if (v1 > v2) + p = 2 * betainc( df2 / (df2 + df1 * f), df2 / 2, df1 / 2) ; +else + f = 1 / f ; + p = 2 * betainc( df1 / (df1 + df2 * f), df1 / 2, df2 / 2) ; +end +if (p > 1) + p = 2 - p ; +end \ No newline at end of file diff --git a/stat/goutte/avevar.m b/stat/goutte/avevar.m new file mode 100644 index 0000000..7072847 --- /dev/null +++ b/stat/goutte/avevar.m @@ -0,0 +1,17 @@ +function [xbar, varx] = avevar(v) +%AVEVAR average and variance of sample. +% AVEVAR(X) gives the average of the sample in X. +% X is a vector of values. +% [A, V] = AVEVAR(X) returns the average of X in A, +% and the variance in V. The variance is corrected +% using the two-pass formula. +% +% Ref: [1] Chan, Golub and LeVeque. 1983. American +% Statistician, vol. 37, pp. 242--247. +% [2] Press et al. 1992. Numerical recipes in C. +% Cambridge university press. +[n l] = size(v) ; +x = reshape(v, n*l, 1) ; +xbar = sum(x) / n / l ; +d = x - xbar ; +varx = ( sum(d .* d) - sum(d) * sum(d) / n / l) / (n * l - 1) ; diff --git a/stat/goutte/bootstrap.m b/stat/goutte/bootstrap.m new file mode 100644 index 0000000..f597a65 --- /dev/null +++ b/stat/goutte/bootstrap.m @@ -0,0 +1,47 @@ +function [biais, variance, fboot] = bootstrap(f, X, B, P1, P2, P3) +%BOOTSTRAP Bootstrap estimates of bias and variance. +% +% [BIAS VAR Fboot] = BOOTSTRAP('f', X, B) gives the following elements +% calculated by the bootstrap method using B replications: +% - bias of f(X), +% - variance of f(X), +% - corrected f(X). +% The data in X must be organised in rows (see function CORRCOEF) +% The bias formula is the standard one (not .632). +% +% [BIAS VAR Fboot] = BOOTSTRAP('f', X, B, opt1, opt2, opt3) allows to +% pass up to 3 additional arguments to 'f'. +% +% BOOTSTRAP needs the AVEVAR function. +% (c) 1997, C. Goutte. +% See also: JACKKNIFE. + +if (nargin < 3) | (nargin > 6) + error('BOOTSTRAP: wrong number of arguments.') ; +end + +[N P] = size(X) ; +if (N < 2) + error('BOOTSTRAP: not enough samples.') +end +evalstr = [f, '(X_i'] ; +for i = 1:(nargin - 3) + evalstr = [evalstr, ',P', int2str(i)] ; +end +evalstr = [evalstr, ')'] ; + +f_i = zeros(B,1) ; +X_i = X ; +fhat = eval(evalstr) ; + +for i = 1:B + idx_i = ceil(rand(1,N)*N) ; +% disp(idx_i) + X_i = X(idx_i, :) ; + f_i(i) = eval(evalstr) ; +end +[fboot, variance] = avevar(f_i) ; +biais = (fboot - fhat) ; +fboot = 2 * fhat - fboot ; + +% (c) 16/05/97, CG. diff --git a/stat/goutte/budget.txt b/stat/goutte/budget.txt new file mode 100644 index 0000000..940fe2a --- /dev/null +++ b/stat/goutte/budget.txt @@ -0,0 +1,24 @@ +18.0 .5 .1 6.7 .5 2.1 2.0 0 26.4 41.5 2.2 +14.1 .8 .1 15.3 1.9 3.7 .5 0 29.8 31.3 2.5 +13.6 .7 .7 6.8 .6 7.1 .7 0 33.8 34.4 1.6 +14.3 1.7 1.7 6.9 1.2 7.4 .8 0 37.7 26.2 2.1 +10.3 1.5 .4 9.3 .6 8.5 .9 0 38.4 27.2 2.9 +13.4 1.4 .5 8.1 .7 8.6 1.8 0 38.5 25.3 1.7 +13.5 1.1 .5 9.0 .6 9.0 3.4 0 36.8 23.5 2.6 +12.9 1.4 .3 9.4 .6 9.3 4.3 0 41.1 19.4 1.3 +12.3 .3 .1 11.9 2.4 3.7 1.7 1.9 42.4 23.1 .2 +7.6 1.2 3.2 5.1 .6 5.6 1.8 10.0 29.0 35.0 .9 +10.5 .3 .4 4.5 1.8 6.6 2.1 10.1 19.9 41.6 2.2 +10.0 0.6 0.6 9.0 1.0 8.1 3.2 11.8 28.0 25.8 1.9 +10.6 .8 .3 8.9 3.0 10.0 6.4 13.4 27.4 19.2 0 +8.8 2.6 1.4 7.8 1.4 12.4 6.2 11.3 29.3 18.5 .3 +10.1 1.1 1.2 5.9 1.4 9.5 6.0 5.9 40.7 18.2 0 +15.6 1.6 10.0 11.4 7.6 8.8 4.8 3.4 32.2 4.6 0 +11.2 1.3 16.5 12.4 15.8 8.1 4.9 3.4 20.7 4.2 1.5 +12.9 1.5 7.0 7.9 12.1 8.1 5.3 3.9 36.1 5.2 0 +10.9 5.3 9.7 7.6 9.6 9.4 8.5 4.6 28.2 6.2 0 +13.1 4.4 7.3 5.7 9.8 12.5 8.0 5.0 26.7 7.5 0 +12.8 4.7 7.5 6.6 6.8 15.7 9.7 5.3 24.5 6.4 .0 +12.4 4.3 8.4 9.1 6.0 19.5 10.6 4.7 19.8 3.5 1.7 +11.4 6.0 9.5 5.9 5.0 21.1 10.7 4.2 20.0 4.4 1.8 +12.8 2.8 7.1 8.5 4.0 23.8 11.3 3.7 18.8 7.2 0 diff --git a/stat/goutte/ftest.m b/stat/goutte/ftest.m new file mode 100644 index 0000000..09930e0 --- /dev/null +++ b/stat/goutte/ftest.m @@ -0,0 +1,33 @@ +function [p, f] = ftest(d1, d2) +%FTEST F-test for two samples. +% FTEST(X1, X2) gives the probability that the F value +% calculated as the rati of the variances of the two samples is +% greater than observed, i.e. the significance level. +% [P, F] = FTEST(X1, X2) gives the probability P and returns +% the value of F. +% +% A small value of P would lead to reject the hypothesis that +% both data sets are sampled from distributions with the same +% variances. +% +%See also : TTEST, TEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +f = v1 / v2 ; +df1 = n1 - 1 ; +df2 = n2 - 1 ; +if (v1 > v2) + p = 2 * betainc( df2 / (df2 + df1 * f), df2 / 2, df1 / 2) ; +else + f = 1 / f ; + p = 2 * betainc( df1 / (df1 + df2 * f), df1 / 2, df2 / 2) ; +end +if (p > 1) + p = 2 - p ; +end \ No newline at end of file diff --git a/stat/goutte/jackknife.m b/stat/goutte/jackknife.m new file mode 100644 index 0000000..c3e3d61 --- /dev/null +++ b/stat/goutte/jackknife.m @@ -0,0 +1,46 @@ +function [biais, variance, fjack] = jackknife(f, X, P1, P2, P3) +%JACKKNIFE Jackknife estimates of bias and variance. +% +% [BIAS VAR Fjack] = JACKKNIFE('f', X) gives the following elements +% calculated by the jackknife method: +% - bias of f(X), +% - variance of f(X), +% - corrected f(X). +% The data in X must be organised in rows (see function CORRCOEF) +% +% [BIAS VAR Fjack] = JACKKNIFE('f', X, opt1, opt2, opt3) allows to +% pass up to 3 additional arguments to 'f'. +% +% JACKKNIFE needs the AVEVAR function. +% (c) 1997, C. Goutte. +% See also: BOOTSTRAP. + +if (nargin < 2) | (nargin > 5) + error('JACKKNIFE: wrong number of arguments.') ; +end + +[N P] = size(X) ; +if (N < 2) + error('JACKNIFE: not enough samples.') +end +evalstr = [f, '(X_i'] ; +for i = 1:(nargin - 2) + evalstr = [evalstr, ',P', int2str(i)] ; +end +evalstr = [evalstr, ')'] ; + +f_i = zeros(N,1) ; +X_i = X ; +fhat = eval(evalstr) ; + +for i = 1:N + idx_i = [1:(i-1), (i+1):N] ; + X_i = X(idx_i, :) ; + f_i(i) = eval(evalstr) ; +end +[fbar, variance] = avevar(f_i) ; +variance = (N - 1) * (N - 1) * variance / N ; +biais = (N - 1) * (fbar - fhat) ; +fjack = N * fhat - (N - 1) * fbar ; + +% (c) 16/05/97, CG. \ No newline at end of file diff --git a/stat/goutte/kstest.m b/stat/goutte/kstest.m new file mode 100644 index 0000000..fe6a550 --- /dev/null +++ b/stat/goutte/kstest.m @@ -0,0 +1,46 @@ +function [p, d] = kstest(v1, v2) +%KSTEST Kolmogorov-Smirnov test of two arrays. +% KSTEST(V1, V2) gives the significance level of V1 and V2 being +% sampled from the same distribution. +% [PROB, D] = KSTEST(V1, V2) returns : +% PROB : the probability of the KS statistics to be greater +% than observed on V1 and V2, +% D : the observed KS statistics. +% where V1 and V2 are the locations of the samples. +% +% When PROB is close to 0, the samples are probably from different +% distributions. +% +% To test a sample V against a distribution, produce a *big* sample VS +% from this distribution, and test KTEST(V, VS). +% +% See also: QKS. +if (nargin ~= 2) + error('KSTEST: requires 2 samples.') ; +end + +[nl1 nc1] = size(v1) ; +if ((nl1 *nc1 <= 0) | (min([nl1 nc1]) ~= 1)) + error('KSTEST: first argument is empty or has wrong dimensions.') ; +end +[nl2 nc2] = size(v2) ; +if ((nl2 *nc2 <= 0) | (min([nl2 nc2]) ~= 1)) + error('KSTEST: second argument is empty or has wrong dimensions.') ; +end + +n1 = nl1 * nc1 ; +d1 = reshape(v1, n1, 1) ; +n2 = nl2 * nc2 ; +d2 = reshape(v2, n2, 1) ; +%[d1 d2 ]' +h = zeros(1, n1 + n2) ; + +for i=1:n1 + h1(i) = length(find(d1 <= d1(i))) * 1/n1 - length(find(d2 <= d1(i))) * 1/n2 ; +end +for i=1:n2 + h2(i) = length(find(d1 <= d2(i))) * 1/n1 - length(find(d2 <= d2(i))) * 1/n2 ; +end +d = max([abs(h1) abs(h2)]) ; +n = sqrt(n1 * n2 / (n1 + n2)) ; +p = qks((n + 0.12 + 0.11/n) * d) ; diff --git a/stat/goutte/pca.m b/stat/goutte/pca.m new file mode 100644 index 0000000..bca4269 --- /dev/null +++ b/stat/goutte/pca.m @@ -0,0 +1,118 @@ +function [Y, lbd, cos2, CC] = pca(X, P, labels) +%PCA Principal Components Analysis +% +% Y = PCA(X, P) returns the first P principal components of X. +% X must be a NxL matrix of N vectors in L dimensions. +% +% Y = PCA(X, P, LABELS) displays several plots related to the PCA: +% . projection of data on the first two principal axes, +% . correlation circle, +% . % inertia of the principal components, +% . angles of the data w.r.t. the PC subspace. +% If LABELS is a matrix containing N rows of text, each row is used +% to label the corresponding data point, otherwise data go unlabelled. +% +% Additional outputs: [Y, LBD, C2, CC] = PCA(X, P [, LABELS]), where +% Y is the projection of X on the first P principal components, +% LBD contains the % inertia of the required P components, +% C2 is the squared cosine between projected data and original data, +% CC is the correlation between the input features and the first P P.C. +% +% See also: . +if (nargin < 2) or (nargin > 4) + error('PCANA: wrong number of arguments.') +end + +[N, L] = size(X) ; +if (P < 1) + error('PCANA: must return at least 1 principal component.') +end +if (P > L) + error('PCANA: can''t get more principal components than dimensions.') +end + +if (nargin == 2) + verbose = 0 ; +end + +%%%%%%%%%% + +R = corrcoef(X) ; +% XM= ones(N,1) * mean(X') ; +% Xc = X' - XM ; +% [U, S, V] = svd(Xc, 0) ; +[V, S] = eig(R) ; +[l, idx] = sort(diag(S)') ; +l = fliplr(l) ; +idx = fliplr(idx) ; + +% Coordonees centrees reduites. +XCR = (X - ones(N,1)*mean(X)) / diag(std(X)) ; +%PC = (Xc * V(:,idx)' + XM)' ; +PC = (XCR * V(:,idx) ) ; + +% P first principal components: +Y = PC(:, 1:P) ; + +% P first portions of inertia: +lbd = l(1:P) / sum(l) ; + +% Squared cosines of projection vs. original data: +cos2 = sum((Y.^2)') ./ sum((XCR.^2)') ; + +% Correlations of features with PCs: +CC = V(:,idx) * diag(sqrt(l)) ; + +if (nargin == 3) + figure + subplot(2,2,1) ; + plot(PC(:,1), PC(:,2), '+') ; + if (size(labels, 1) == N) + for i = 1:N + text(PC(i,1), PC(i,2), [' ', labels(i,:)]) ; + end + end + xlabel('First principal axis') ; + ylabel('Second principal axis') ; + title('Data projection on the first two principal axes') + subplot(2,2,2) ; + plot(cos(2*pi*(0:100)/100), sin(2*pi*(0:100)/100)) ; + hold on, plot([-1, 1], [0, 0]), plot([0, 0], [-1, 1]) ; + plot(CC(:,1), CC(:,2), 'x') ; + for k = 1:L + text(CC(k,1)+.03, CC(k,2)+.03, num2str(k)) ; + end + xlabel('First PC') ; + ylabel('Second PC') ; + title('Correlation of features with first 2 PCs') + subplot(2,2,3) ; + hh = plot(l/sum(l), '--') ; + set(hh, 'LineWidth', 3) ; + hold on, hh = plot(cumsum(l)/sum(l)) ; + set(hh, 'LineWidth', 3) ; + axis([1 L 0 1]) ; + plot([2 2], [0 1]) ; + xlabel('PC no.') ; + ylabel('Inertia') ; + legend('PC inertia', 'Cumulated inertia') ; + title('Repartition of inertia on the PCs') ; + subplot(2,2,4) ; + hold on + hh = plot(acos(sqrt(cos2))/pi*180, 1:N, '+') ; + set(hh, 'LineWidth', 3) ; + hold on + for i = 1:N + hh = plot([0, acos(sqrt(cos2(i)))/pi*180], [i, i], '-') ; + set(hh, 'LineWidth', 3) ; + end + set(gca, 'Box', 'on') ; + set(gca, 'YLim', [1 N]) ; + if (size(labels, 1) == N) + set(gca, 'YTick', 1:N) ; + set(gca, 'YTickLabels', labels) ; + end + xlabel('Angle (deg)') + title('Angle of data with the PC plan') +end + +CC = CC(:,1:P) ; diff --git a/stat/goutte/pttest.m b/stat/goutte/pttest.m new file mode 100644 index 0000000..21d5cdb --- /dev/null +++ b/stat/goutte/pttest.m @@ -0,0 +1,41 @@ +function [p, t, df] = pttest(d1, d2) +%PTTEST Student's paired t-test. +% PTTEST(X1, X2) gives the probability that Student's t +% calculated on paired data X1 and X2 is higher than +% observed, i.e. the "significance" level. This is used +% to test whether two paired samples have significantly +% different means. +% [P, T] = PTTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works for PAIRED SAMPLES, i.e. when elements of X1 +% and X2 correspond one-on-one somehow. +% E.g. residuals of two models on the same data. +% +%See also: TTEST, UTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +if (n1 ~= n2) + error('PTTEST: paired samples must have the same number of elements !') +end +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = n1 - 1 ; +cab = (x1 - a1)' * (x2 - a2) / (n1 - 1) ; +if (a1 ~= a2) + % use abs to avoid numerical errors for very similar data + % for which v1+v2-2cab may be close to 0. + t = (a1 - a2) / sqrt(abs(v1 + v2 - 2 * cab) / n1) ; + p = betainc( df / (df + t*t), df/2, 0.5) ; +else + t = 0 ; + p = 1 ; +end diff --git a/stat/goutte/qks.m b/stat/goutte/qks.m new file mode 100644 index 0000000..3352400 --- /dev/null +++ b/stat/goutte/qks.m @@ -0,0 +1,58 @@ +function P = qks(M, tol) +%QKS Kolmogorov-Smirnov probability. +% QKS(x) computes the function that enters into the calculation +% of the significance level in a Kolmogorov-Smirnov test. +% +oo +% .-- [ k-1 2 2 ] +% Q (x) = 2 > [ (-1) exp(-2.x .k ) ] +% KS '-- [ ] +% k=1 +% Ref.: Numerical Recipes, 2nd ed. pp.623-628 +% QKS(M) calculates QKS(x) for each x in M. +% QKS(M, TOL) uses TOL as the precision required for the convergence. +% The default value is MATLAB's eps (1e-8). +% +% See also: KSTEST, QKS2. +if (nargin < 1 | nargin > 2) + error('QKS: requires one or two arguments.') ; +end + +if (nargin == 1) + tol = eps ; +else + if (tol <= 0) + error('QKS: precision must be strictly positive.') ; + end +end + +[nl, nc] = size(M) ; +if ((nl * nc) <= 0) + error('QKS: first argument is empty or has wrong dimensions.') ; +end + +n = nl * nc ; +X = reshape(M, n, 1) ; +P = ones(n, 1) ; + +for i = find(X ~= 0)' + coeff = 2 ; + alpha = -2 * X(i, 1) * X(i, 1) ; + sss = 0 ; + k = 1 ; + ui = coeff * exp(alpha) ; + while (( abs(ui) > tol * sss ) & ( k < 100 )) + sss = sss + ui ; + k = k + 1 ; + coeff = - coeff ; + ui = coeff * exp(alpha * k * k) ; + end + if (k == 100) +% Ca n'a pas converge + P(i,1) = 1 ; + else +% Ca a converge : on arrondit a epsilon pres. + P(i,1) = round((sss + ui) / tol) * tol ; + end +end + +P = reshape(P, nl, nc) ; diff --git a/stat/goutte/test.m b/stat/goutte/test.m new file mode 100644 index 0000000..c967377 --- /dev/null +++ b/stat/goutte/test.m @@ -0,0 +1,35 @@ +function [p, s] = test(x1, x2, type) +%TEST statistical test of two samples. +% TEST(X1, X2, 'test') gives the confidence level for +% different tests of the two samples X1 and X2. +% +% 'test' Null hypothesis Assumption on distributions Type +% ----------------------------------------------------------------- +% 't' Means are equal The variances are equal t-test +% 'u' Means are equal The variances are not equal t-test +% 'p' Means are equal The data are paired t-test +% 'f' Variances are equal F-test +% +% TEST(X1, X2) performs a t-test (for equal variances) by default. +% +% [P S] = TEST(X1, X2, ['test']) returns the confidence level in P +% and the value of the statistic (t or F) in S. +% +% Ref: Press et al. 1992. Numerical recipes in C. 14.2, Cambridge. +% +%See also : TTEST, UTEST, PTEST, FTEST. +if (nargin == 2) + type = 't' ; +end + + +if (type == 't') + [p s] = ttest(x1, x2) ; +elseif (type == 'u') + [p s] = uttest(x1, x2) ; +elseif (type == 'p') + [p s] = pttest(x1, x2) ; +elseif (type == 'f') + [p s] = ftest(x1, x2) ; +end + diff --git a/stat/goutte/ttest.m b/stat/goutte/ttest.m new file mode 100644 index 0000000..26c85cc --- /dev/null +++ b/stat/goutte/ttest.m @@ -0,0 +1,30 @@ +function [p, t] = ttest(d1, d2) +%TTEST Student's t-test for equal variances. +% TTEST(X1, X2) gives the probability that Student's t +% calculated on data X1 and X2, sampled from distributions +% with the same variance, is higher than observed, i.e. +% the "significance" level. This is used to test whether +% two sample have significantly different means. +% [P, T] = TTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works if the samples are drawn from distributions with +% the SAME VARIANCE. Otherwise, use UTTEST. +% +%See also: UTTEST, PTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = n1 + n2 - 2 ; +pvar = ((n1 - 1) * v1 + (n2 - 1) * v2) / df ; +t = (a1 - a2) / sqrt( pvar * (1/n1 + 1/n2)) ; +p = betainc( df / (df + t*t), df/2, 0.5) ; diff --git a/stat/goutte/uttest.m b/stat/goutte/uttest.m new file mode 100644 index 0000000..f989423 --- /dev/null +++ b/stat/goutte/uttest.m @@ -0,0 +1,30 @@ +function [p, t, df] = uttest(d1, d2) +%UTTEST Student's t-test for unequal variances. +% UTTEST(X1, X2) gives the probability that Student's t +% calculated on data X1 and X2, sampled from distributions +% with different variances, is higher than observed, i.e. +% the "significance" level. This is used to test whether +% two sample have significantly different means. +% [P, T] = UTTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works if the samples are drawn from distributions with +% DIFFERENT VARIANCE. Otherwise, use TTEST. +% +%See also: TTEST, PTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = (v1 / n1 + v2 / n2) * (v1 / n1 + v2 / n2) / ... + ( (v1 / n1) * (v1 / n1) / (n1 - 1) + (v2 / n2) * (v2 / n2) / (n2 -1) ) ; +t = (a1 - a2) / sqrt( v1 / n1 + v2 / n2 ) ; +p = betainc( df / (df + t*t), df/2, 0.5) ; diff --git a/stat/hedge_g.m b/stat/hedge_g.m new file mode 100644 index 0000000..11eb52e --- /dev/null +++ b/stat/hedge_g.m @@ -0,0 +1,32 @@ +function [g_star,g,v_star]=hedge_g(X1,X2) +% Computes effect size g, as suggested by Larry Hedges in 1981. +% [g_star,g]=functionhedge_g(X1,X2) +% + +X1=X1(:); +X2=X2(:); + +m1=mean(X1); +m2=mean(X2); + +n1=size(X1,1); +n2=size(X2,1); + +v1=var(X1); +v2=var(X2); + +%s Hedge's pooled variance +% note the -2 in the denominator +a=n1+n2-2; +v_star = ((n1-1)*v1 + (n2-1)*v2)/a; + +g = (m1 - m2)/sqrt(v_star); + +if 0 + J = gamma(a/2)/(sqrt(a/2)*gamma((a-1)/2)); +else + % approximate + J = 1 - 3/(a-1); +end + +g_star=J*g; diff --git a/stat/hochberg.m b/stat/hochberg.m new file mode 100644 index 0000000..368d389 --- /dev/null +++ b/stat/hochberg.m @@ -0,0 +1,46 @@ +function [sig,alpha]=hochberg(alpha,n) +% HOCHBERG - Hochberg's adjustment of alpha level for multiple comparisons +% +% alpha2=hochberg(alpha1, n) computes the new alpha2 to use when running +% n tests with a familywise error rate of alpha +% +% [sig,alphas]=hochberg(alpha,p) assess the significance of the p-values +% coming from multiple tests according to the Hochberg's procedure +% yielding a familywise error rate of alpha. p being a vector of +% p-values, sig will be a logical vector of the same size. +% +% See also: dunnsidak, hochberg + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-11-05 Creation +% +% ----------------------------- Script History --------------------------------- + +% Ref: +% http://www.unc.edu/courses/2007spring/biol/145/001/docs/lectures/Oct6.html +% + +if numel(n)==1 & n>=1 + alpha=alpha.*(1./(n-(0:n-1))); + sig=alpha; + return +end +p=n; +sz=size(p); +[p,ip]=sort(p(:)); +n=numel(p); +alpha=alpha.*(1./(n-(tiedrank(p)-1))); +sig=logical(p.*0); +i=find(p<=alpha(:)); +if ~isempty(i) + sig(1:i(end))=1; +end +sig(ip)=sig; +sig=reshape(sig,sz); \ No newline at end of file diff --git a/stat/holm.m b/stat/holm.m new file mode 100644 index 0000000..6dd59b7 --- /dev/null +++ b/stat/holm.m @@ -0,0 +1,47 @@ +function [sig,alpha]=holm(alpha,n) +% HOLM - Holm adjustment of alpha level for multiple comparisons +% +% alpha2=holm(alpha1, n) computes the new alpha2 to use when running +% n tests with a familywise error rate of alpha +% +% [sig,alphas]=holm(alpha,p) assess the significance of the p-values +% coming from multiple tests according to the Holm's procedure yielding a +% familywise error rate of alpha. p being a vector of p-values, sig will +% be a logical vector of the same size. +% +% See also: dunnsidak, hochberg + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-11-05 Creation +% +% ----------------------------- Script History --------------------------------- + +% Ref: +% http://www.unc.edu/courses/2007spring/biol/145/001/docs/lectures/Oct6.html +% + +if numel(n)==1 & n>=1 + alpha=alpha.*(1./(n-(0:n-1))); + sig=alpha; + return +end +p=n; +sz=size(p); +[p,ip]=sort(p(:)); +n=numel(p); +% alpha=holm(alpha,n); +alpha=alpha.*(1./(n-(tiedrank(p)-1))); +sig=logical(p.*0+1); +i=find(p>alpha(:)); +if ~isempty(i) + sig(i(1):end)=0; +end +sig(ip)=sig; +sig=reshape(sig,sz); \ No newline at end of file diff --git a/stat/krippendorff_alpha.m b/stat/krippendorff_alpha.m new file mode 100644 index 0000000..02779d3 --- /dev/null +++ b/stat/krippendorff_alpha.m @@ -0,0 +1,61 @@ +function a = krippendorff_alpha(R) +%KRIPPENDORFF_ALPHA - Krippendorff’s Alpha-Reliability between raters +% [] = krippendorff_alpha(input) +% +% Example +% >> krippendorff_alpha +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-09-23 Creation +% +% ----------------------------- Script History --------------------------------- + + +R = [ 'a a b b d c c c e d d a ' ... + ' b a b b b c c c e d d d '] +R = reshape(R(R~=' '),12,2)' - 'a' + + +R= [1 2 3 3 2 1 4 1 2 NaN NaN NaN + 1 2 3 3 2 2 4 1 2 5 NaN NaN + NaN 3 3 3 2 3 4 2 2 5 1 3 + 1 2 3 3 2 4 4 1 2 5 1 NaN ]; + + +[no , nm] = size(R); +if no==2 + if ~any(isnan(R)) + r = (unique(R(~isnan(R)))); + nr = numel(r); + P = nchoosek(r,2); + P = [ P ; fliplr(P) ]; + P = sortrows([ [r(:) r(:)] ; P ]); + np = size(P,1); + %Coincidence values + C = repmat(R, [ 1 1 np]) == permute(repmat(P',[1 1 nm ]), [1 3 2]); + C = squeeze(sum(all(C),2)) + % ... into matrix + C = reshape(C,[nr nr]); + C = C' + C; + n = 2*nm; + nc = sum(C); + sc = sum(nc.*(nc-1)) + a = (n-1)*sum(diag(C)) - sc; + a = a / (n*(n-1)-sc) + else + mu = no - sum(isnan(R)); + + end + +end +return +%% diff --git a/stat/kstest.m b/stat/kstest.m new file mode 100644 index 0000000..fe6a550 --- /dev/null +++ b/stat/kstest.m @@ -0,0 +1,46 @@ +function [p, d] = kstest(v1, v2) +%KSTEST Kolmogorov-Smirnov test of two arrays. +% KSTEST(V1, V2) gives the significance level of V1 and V2 being +% sampled from the same distribution. +% [PROB, D] = KSTEST(V1, V2) returns : +% PROB : the probability of the KS statistics to be greater +% than observed on V1 and V2, +% D : the observed KS statistics. +% where V1 and V2 are the locations of the samples. +% +% When PROB is close to 0, the samples are probably from different +% distributions. +% +% To test a sample V against a distribution, produce a *big* sample VS +% from this distribution, and test KTEST(V, VS). +% +% See also: QKS. +if (nargin ~= 2) + error('KSTEST: requires 2 samples.') ; +end + +[nl1 nc1] = size(v1) ; +if ((nl1 *nc1 <= 0) | (min([nl1 nc1]) ~= 1)) + error('KSTEST: first argument is empty or has wrong dimensions.') ; +end +[nl2 nc2] = size(v2) ; +if ((nl2 *nc2 <= 0) | (min([nl2 nc2]) ~= 1)) + error('KSTEST: second argument is empty or has wrong dimensions.') ; +end + +n1 = nl1 * nc1 ; +d1 = reshape(v1, n1, 1) ; +n2 = nl2 * nc2 ; +d2 = reshape(v2, n2, 1) ; +%[d1 d2 ]' +h = zeros(1, n1 + n2) ; + +for i=1:n1 + h1(i) = length(find(d1 <= d1(i))) * 1/n1 - length(find(d2 <= d1(i))) * 1/n2 ; +end +for i=1:n2 + h2(i) = length(find(d1 <= d2(i))) * 1/n1 - length(find(d2 <= d2(i))) * 1/n2 ; +end +d = max([abs(h1) abs(h2)]) ; +n = sqrt(n1 * n2 / (n1 + n2)) ; +p = qks((n + 0.12 + 0.11/n) * d) ; diff --git a/stat/kstest2.m b/stat/kstest2.m new file mode 100644 index 0000000..c3128d1 --- /dev/null +++ b/stat/kstest2.m @@ -0,0 +1,47 @@ +function [p, d] = kstest2(v1, v2) +%ktest2() - Kolmogorov-Smirnov test of two arrays. +% KSTEST2(V1, V2) gives the significance level of V1 and V2 being +% sampled from the same distribution. +% [PROB, D] = KSTEST2(V1, V2) returns : +% PROB : the probability of the KS statistics to be greater +% than observed on V1 and V2, +% D : the observed KS statistics. +% where V1 and V2 are the locations of the samples. +% +% When PROB is close to 0, the samples are probably from different +% distributions. +% +% To test a sample V against a distribution, produce a *big* sample VS +% from this distribution, and test KTEST(V, VS). +% +% See also: QKS. + +if (nargin ~= 2) + error('KSTEST: requires 2 samples.') ; +end + +[nl1 nc1] = size(v1) ; +if ((nl1 *nc1 <= 0) | (min([nl1 nc1]) ~= 1)) + error('KSTEST: first argument is empty or has wrong dimensions.') ; +end +[nl2 nc2] = size(v2) ; +if ((nl2 *nc2 <= 0) | (min([nl2 nc2]) ~= 1)) + error('KSTEST: second argument is empty or has wrong dimensions.') ; +end + +n1 = nl1 * nc1 ; +d1 = reshape(v1, n1, 1) ; +n2 = nl2 * nc2 ; +d2 = reshape(v2, n2, 1) ; +%[d1 d2 ]' +h = zeros(1, n1 + n2) ; + +for i=1:n1 + h1(i) = length(find(d1 <= d1(i))) * 1/n1 - length(find(d2 <= d1(i))) * 1/n2 ; +end +for i=1:n2 + h2(i) = length(find(d1 <= d2(i))) * 1/n1 - length(find(d2 <= d2(i))) * 1/n2 ; +end +d = max([abs(h1) abs(h2)]) ; +n = sqrt(n1 * n2 / (n1 + n2)) ; +p = qks((n + 0.12 + 0.11/n) * d) ; diff --git a/stat/levenetest.m b/stat/levenetest.m new file mode 100644 index 0000000..3d26b36 --- /dev/null +++ b/stat/levenetest.m @@ -0,0 +1,153 @@ +function [Levenetest] = Levenetest(X,alpha) +%Levene's Test for Homogeneity of Variances. +%[In the Levene's test the data are transforming to yij = abs[xij - mean(xj)] +%and uses the F distribution performing an one-way ANOVA using y as the +%dependent variable (Brownlee, 1965; Miller, 1986)]. +% +% Syntax: function [Levenetest] = Levenetest(X,alfa) +% +% Inputs: +% X - data matrix (Size of matrix must be n-by-2; data=column 1, sample=column 2). +% alpha - significance level (default = 0.05). +% Outputs: +% - Sample variances vector. +% - Whether or not the homoscedasticity was met. +% +% Example: From the example 10.1 of Zar (1999, p.180), to test the Levene's +% homoscedasticity of data with a significance level = 0.05. +% +% Diet +% --------------------------------- +% 1 2 3 4 +% --------------------------------- +% 60.8 68.7 102.6 87.9 +% 57.0 67.7 102.1 84.2 +% 65.0 74.0 100.2 83.1 +% 58.6 66.3 96.5 85.7 +% 61.7 69.8 90.3 +% --------------------------------- +% +% Data matrix must be: +% X=[60.8 1;57.0 1;65.0 1;58.6 1;61.7 1;68.7 2;67.7 2;74.0 2;66.3 2;69.8 2; +% 102.6 3;102.1 3;100.2 3;96.5 3;87.9 4;84.2 4;83.1 4;85.7 4;90.3 4]; +% +% Calling on Matlab the function: +% Levenetest(X) +% +% Answer is: +% +% The number of samples are: 4 +% +% ---------------------------- +% Sample Size Variance +% ---------------------------- +% 1 5 9.3920 +% 2 5 8.5650 +% 3 4 7.6567 +% 4 5 8.3880 +% ---------------------------- +% +% Levene's Test for Equality of Variances F=0.0335, df1= 3, df2=15 +% Probability associated to the F statistic = 0.9914 +% The associated probability for the F test is larger than 0.05 +% So, the assumption of homoscedasticity was met. +% + +% Created by A. Trujillo-Ortiz and R. Hernandez-Walls +% Facultad de Ciencias Marinas +% Universidad Autonoma de Baja California +% Apdo. Postal 453 +% Ensenada, Baja California +% Mexico. +% atrujo@uabc.mx +% +% April 11, 2003. +% +% To cite this file, this would be an appropriate format: +% Trujillo-Ortiz, A. and R. Hernandez-Walls. (2003). Levenetest: Levene's test for +% homogeneity of variances. A MATLAB file. [WWW document]. URL http://www.mathworks.com/ +% matlabcentral/fileexchange/loadFile.do?objectId=3375&objectType=FILE +% +% References: +% +% Brownlee, K. A. (1965) Statistical Theory and Methodology in Science +% and Engineering. New York: John Wiley & Sons. +% Miller, R. G. Jr. (1986) Beyond ANOVA, Basics of Applied Statistics. +% New York: John Wiley & Sons. +% Zar, J. H. (1999), Biostatistical Analysis (2nd ed.). +% NJ: Prentice-Hall, Englewood Cliffs. p. 180. +% + +if nargin < 2, + alpha = 0.05; +end + +Y=X; +k=max(Y(:,2)); +fprintf('The number of samples are:%2i\n\n', k); + +%Levene's Procedure. +n=[];s2=[];Z=[]; +indice=Y(:,2); +for i=1:k + Ye=find(indice==i); + eval(['Y' num2str(i) '=Y(Ye,1);']); + eval(['mY' num2str(i) '=mean(Y(Ye,1));']); + eval(['n' num2str(i) '=length(Y' num2str(i) ') ;']); + eval(['s2' num2str(i) '=(std(Y' num2str(i) ').^2) ;']); + eval(['Z' num2str(i) '= abs((Y' num2str(i) ') - mY' num2str(i) ');']); + eval(['xn= n' num2str(i) ';']); + eval(['xs2= s2' num2str(i) ';']); + eval(['x= Z' num2str(i) ';']); + n=[n;xn];s2=[s2;xs2];Z=[Z;x]; +end + +Y=[Z Y(:,2)]; + +fprintf('-----------------------------\n'); +disp(' Sample Size Variance') +fprintf('-----------------------------\n'); +for i=1:k + fprintf(' %d %2i %.4f\n',i,n(i),s2(i)) +end +fprintf('-----------------------------\n'); +disp(' ') + +C=(sum(Y(:,1)))^2/length(Y(:,1)); %correction term. +SST=sum(Y(:,1).^2)-C; %total sum of squares. +dfT=length(Y(:,1))-1; %total degrees of freedom. + +indice=Y(:,2); +for i=1:k + Ye=find(indice==i); + eval(['A' num2str(i) '=Y(Ye,1);']); +end + +A=[]; +for i=1:k + eval(['x =((sum(A' num2str(i) ').^2)/length(A' num2str(i) '));']); + A=[A,x]; +end + +SSA=sum(A)-C; %sample sum of squares. +dfA=k-1; %sample degrees of freedom. +SSE=SST-SSA; %error sum of squares. +dfE=dfT-dfA; %error degrees of freedom. +MSA=SSA/dfA; %sample mean squares. +MSE=SSE/dfE; %error mean squares. +F=MSA/MSE; %F-statistic. +v1=dfA;df1=v1; +v2=dfE;df2=v2; + +P = 1 - fcdf(F,v1,v2); %probability associated to the F-statistic. + +fprintf('Levene''s Test for Equality of Variances F=%3.4f, df1=%2i, df2=%2i\n', F,df1,df2); +fprintf('Probability associated to the F statistic = %3.4f\n', P); + +if P >= alpha; + fprintf('The associated probability for the F test is equal or larger than% 3.2f\n', alpha); + fprintf('So, the assumption of homoscedasticity was met.\n'); +else + fprintf('The associated probability for the F test is smaller than% 3.2f\n', alpha); + fprintf('So, the assumption of homoscedasticity was not met.\n'); +end \ No newline at end of file diff --git a/stat/mvrnorm.m b/stat/mvrnorm.m new file mode 100644 index 0000000..562b8fd --- /dev/null +++ b/stat/mvrnorm.m @@ -0,0 +1,96 @@ +function = mvrnorm(input,varargin) +%MVRNORM - Robust Correlation by Rich Herrington +% [] = mvrnorm(input) +% +% Example +% >> mvrnorm +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-13 Creation +% +% ----------------------------- Script History --------------------------------- + +% Dealing with Outliers in Bivariate Data: Robust Correlation +% By Dr. Rich Herrington, Research and Statistical Support Consultant +% +% R script: +% +% # n=sample size +% # p=number of columns +% # u=mean of columns +% # s=standard deviation of columns +% # S=correlation matrix +% +% mvrnorm <- function(n, p, u, s, S) { +% Z <- matrix(rnorm(n*p), p, n) +% t(u + s*t(chol(S))%*% Z) +% } +% +% # Sample from Bivariate Normal +% +% z<-mvrnorm(n=100, p=2, u=c(100,100), s=c(15,15), S=matrix(c(1, .4, .4, 1), ncol=2, nrow=2,byrow=T)) +% +% # Fit least squares regression +% +% z.fit<-lm(z[,1]~z[,2]) +% z.fit +% +% # Plot scatterplot +% plot(z[,1], z[,2]) +% +% # Plot best fit line +% abline(z.fit) +% +% # Calculate Pearson's Correlation +% cor(z[,1], z[,2]) + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/stat/mwwtest.m b/stat/mwwtest.m new file mode 100644 index 0000000..8b43990 --- /dev/null +++ b/stat/mwwtest.m @@ -0,0 +1,129 @@ +function STATS=mwwtest(x1,x2) +%Mann-Whitney-Wilcoxon non parametric test for two unpaired groups. +%This file execute the non parametric Mann-Whitney-Wilcoxon test to evaluate the +%difference between unpaired samples. If the number of combinations is less than +%20000, the algorithm calculates the exact ranks distribution; else it +%uses a normal distribution approximation. The result is not different from +%RANKSUM MatLab function, but there are more output informations. +%There is an alternative formulation of this test that yields a statistic +%commonly denoted by U. Also the U statistic is computed. +% +% Syntax: STATS=MWWTEST(X1,X2) +% +% Inputs: +% X1 and X2 - data vectors. +% Outputs: +% - T and U values and p-value when exact ranks distribution is used. +% - T and U values, mean, standard deviation, Z value, and p-value when +% normal distribution is used. +% If STATS nargout was specified the results will be stored in the STATS +% struct. +% +% Example: +% +% X1=[181 183 170 173 174 179 172 175 178 176 158 179 180 172 177]; +% +% X2=[168 165 163 175 176 166 163 174 175 173 179 180 176 167 176]; +% +% Calling on Matlab the function: mwwtest(X1,X2) +% +% Answer is: +% +% MANN-WHITNEY-WILCOXON TEST +% -------------------------------------------------------------------------------- +% Sample size is good enough to use the normal distribution approximation +% +% T U mT sT zT p-value (1-tailed) +% -------------------------------------------------------------------------------- +% 270.0000 150.0000 232.5000 24.1071 1.5348 0.0624 +% -------------------------------------------------------------------------------- +% +% Created by Giuseppe Cardillo +% giuseppe.cardillo-edta@poste.it +% +% To cite this file, this would be an appropriate format: +% Cardillo G. (2009). MWWTEST: Mann-Whitney-Wilcoxon non parametric test for two unpaired samples. +% http://www.mathworks.com/matlabcentral/fileexchange/25830 + +%Input Error handling +if ~isvector(x1) || ~isvector(x2) + error('MWWTEST requires vector rather than matrix data.'); +end +if ~all(isfinite(x1)) || ~all(isnumeric(x1)) || ~all(isfinite(x2)) || ~all(isnumeric(x2)) + error('Warning: all X1 and X2 values must be numeric and finite') +end + +L=[length(x1) length(x2)]; k=min(L); N=sum(L); N1=N+1; %set the basic parameter + +[A,B]=tiedrank([x1(:); x2(:)]); %compute the ranks and the ties +%Compute the Mann-Whitney-Wilcon statistic summing the ranks of the sample with +%the less number of elements. +if L(1)<=L(2) + T=sum(A(1:k)); +else + T=sum(A(k+1:end)); +end + +%There is an alternative formulation of this test that yields a statistic +%commonly denoted by U. U is related to T by the formula U=T-k*(k+1)/2, +%where k is the size of the smaller sample (or either sample if both contain +%the same number of individuals). For a presentation of the U statistic, see: +% S. Siegel and N. J. Castellan, Jr., Nonparametric Statistics for the +% Behavioral Sciences, 2d ed. McGraw-Hill, New York, 1988, Section 6.4, “The +% Wilcoxon-Mann-Whitney U Test.â€? +%For a detailed derivation and discussion of the Mann-Whitney test as developed +%here, as well as its relationship to U, see: +% F. Mosteller and R. Rourke, Sturdy Statistics: Nonparametrics and Order +% Statistics, Addison-Wesley, Reading, MA, 1973, Chapter 3, “Ranking Methods for +% Two Independent Samples.â€? +U=T-k*(k+1)/2; + + +tr=repmat('-',1,80); %set the divisor +disp('MANN-WHITNEY-WILCOXON TEST') +disp(tr) +%if the number of combinations to obtain the exact MWW distribution is >20000 +%use the normal approximation +if round(exp(gammaln(N1)-gammaln(k+1)-gammaln(N1-k))) > 20000 + mT=k*N1/2; %mean + sT=realsqrt(prod(L)/12*(N1-2*B/N/(N^2-1))); %standard deviation + zT=(abs(T-mT)-0.5)/sT; %z-value with correction for continuity + %p=1-normcdf(zT); %p-value + p = 1-(0.5 * erfc(-zT ./ sqrt(2))); + %display results + disp('Sample size is good enough to use the normal distribution approximation') + disp(' ') + fprintf('T\t\tU\t\tmT\t\tsT\t\tzT\t\tp-value (1-tailed)\n') + disp(tr) + fprintf('%0.4f\t%0.4f\t%0.4f\t%0.4f\t\t%0.4f\t\t%0.4f\n',T,U,mT,sT,zT,p) + if nargout + STATS.method='Normal approximation'; + STATS.T=T; + STATS.U=U; + STATS.mean=mT; + STATS.std=sT; + STATS.z=zT; + STATS.p=p; + end +else + z=1:N; + M=combnk(z,k); %M is the matrix of all possible combinations of N elements taken k at time + pdf=sum(z(M),2); %probability density function of the MWW distribution + %to compute the p-value see how many values are more extreme of the observed + %T and then divide for the total number of combinations + p=length(pdf(pdf>=T))/length(pdf); + %display results + disp('The exact Mann-Whitney-Wilcoxon distribution was used') + disp(' ') + fprintf('T\t\tU\tp-value (1-tailed)\n') + disp(tr) + fprintf('%0.4f\t%0.4f\t%0.4f\n',T,U,p) + if nargout + STATS.method='Exact distribution'; + STATS.T=T; + STATS.U=U; + STATS.p=p; + end +end +disp(tr) +disp(' ') diff --git a/stat/myanova.m b/stat/myanova.m new file mode 100644 index 0000000..e8a0e30 --- /dev/null +++ b/stat/myanova.m @@ -0,0 +1,700 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon,verbose,posthoc) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% nf: number of factors +% This function is vectorized, ie. ANOVA is computed for each value in X +% beyond the 'replicates' (i.e. subject) dimension, which is (nf+1). +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% eta: percentage of explained variance by each factor +% epsilon: sphericity correction if applicable +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated/within-subject factors in a within-subject design +% rp: an array listing the dimensions of repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser correction or Huynh-Feldt (if eGG>.7) +% To apply no correction, set epsilon=1 (default) +% +% [...]=myanova(X,nf,rp,epsilon,verbose) +% verbose = 1 will display a table of results +% +% Examples: +% +% X(1:2,1:3,1:10) = data from 2 tasks by 3 condition for 10 subjects, +% both factors (dimensions 1 and 2) are within-subject factors: +% >> [p,F,fx]=myanova(X,2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% X(1:3,1:4,1:10) = data from 3 groups of 10 subjects performing 4 tasks +% only the second factor (dimension 2 of X) is a within-subject variable: +% >> [p,F,fx]=myanova(X,2,[2]) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() + +% ----------------------------- Script History --------------------------------- +% KND 2007...2008 many changes... +% KND 2008-08-27 Corrected version (at last!) +% +% ----------------------------- Script History --------------------------------- + +% Version 2.0 - 27-Aug-2008 +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +if ~isscalar(nf) + error('Number of factors should be a scalar'); +end +if nargin<3 + rp=[]; +end + +% Number of groups for each factor: +ng=sX(1:nf); +% Number of cells: +nc=prod(ng); +% Number of replicates, ie. samples in each group: +nr=sX(nf+1); +%Total number of observations: +no=nc*nr; +% Dimensions of (univariate) dependent variables: +svar=[sX(nf+2:end)]; +if ~isempty(rp) && nr<2 + error('You must have more than one observation per cell or more than one subject per condition') +end +% if (nr<=1) +% error('myanova doesn''t work with 1 subject / group!') +% end + +if nargin<3 + rp=[]; +end + if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('Mixed designs (split plot) ANOVA unavailable!') + end +% if ~isempty(rp) & nf>2 +% error('Repeated measure ANOVA is only available for 2 factor designs!') +% end +if nargin<4 + epsilon=1; +end +if nargin<5 || isempty(verbose) + % No display for massively univariate data... + verbose = (nargout==0) & prod([1 svar])<10; +end +if isempty(epsilon) + epsilon=NaN; +end +if nargin<6 + posthoc=[]; +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Posthoc tests +if isempty(posthoc) + % No display for massively univariate data... + if verbose + posthoc = 1; + else + posthoc = 0; + end +end +if iscell(posthoc) + posthoc_fx = posthoc; + posthoc=1; +elseif isequal(posthoc,1) + posthoc_fx = cell(nfx,1 ); +end + +% Within Group/Error stats +% Mean in each cell +mXw=mean(X,nf+1); +% Residual Error of the model +SSe=X-repmat(mXw,[ones(1,nf) nr 1]); +SSe=reshape(SSe, nc*nr, []).^2; +SSe=sum(SSe); +dfe=nc*(nr-1); +MSe=squeeze(SSe/dfe); +% pre-allocate sum of squares of effects and errors: +SSbe=repmat(SSe,nfx,1); +SS=NaN.*SSbe; +%keeps the full model unexplained variance for later +MSw=MSe; +dfw=dfe; + +% Population stats +dft=(nc*nr)-1; +% Grand mean value +mX=reshape(mXw, nc, []); +mX=mean(mX,1); +% Correction factor: +% cX=mX.^2./(nc*nr); + +% These are not used afterwards +SSt=sum((reshape(X, nc*nr, [])-repmat(mX,[nc*nr 1])).^2); +% MSt=squeeze(SSt/dft); + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,nc,[]); + mXr=mean(mXr,2); + SSr=nc*sum((reshape(mXr, nr, []) - repmat(mX,[nr 1])).^2); +end + + + +% Sphericity checking +if isnan(epsilon) % | ischar(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end +varargout{1} = epsilon; + +% Number of groups in between subjects +if ~isempty(rp) + tmp=zeros(1,nf); + tmp(rp)=1; + rp=logical(tmp); + % number of cells for between-subject factors + ncb=prod(ng(~rp)); + nc=nc/ncb; + % Order factors so that within ones come first, followed by the between + % fxw = [find(rp) find(~rp)]; + % ngw = sX(pfxw); +else + rp=logical(zeros(1,nf)); +end + + +% % Within Group/Error stats +% % i.e unmodeled error +% mXe=mean(X,nf+1); +% SSe=X-repmat(mXe,[ones(1,nf) nr 1]); +% SSe=reshape(SSe, [nc nr svar]).^2; +% SSe=sum(sum(SSe)); +% MSe=squeeze(SSe/dfe); + + +% Population stats +dft=(no)-1; +% mX=reshape(mXe,nc,[svar]); +% varargout{1}=epsilon; +% end +if nargout > 8 || verbose==1 + varargout{6}=SSt; +end + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + % Dimensions of the factors pooled through factor j + nj=setdiff(1:nf,j); + % Nb of cells for effect j + ncj = prod(ng(j)); + % Nb of cells pooled by effect j + nbj = nc./ncj; + % Degrees of freedom for this effect + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j nj nf+1:nX]); + mXb=reshape(mXb,ncj,nbj,[]); + mXb=mean(mXb,2); + SSb=nr*nbj*sum((reshape(mXb,ncj, []) - repmat(mX,[ncj 1])).^2); + + if length(j)>1 + % Interaction: + % we need to remove the variance due to embedded effects from the + % Sum of Squares of the current interaction effect + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + % Keep track of the SS of the current effect + SS(i,:)=SSb; + MSb=SSb./dfb; + + dfe=nc*(nr-1); + if any(rp(j)) + % Correct Error term to account for repeated measurements + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j nj nf+2:nX]); + mXe=reshape(mXe,nr*ncj,nbj,[]); + mXe=mean(mXe,2); + % Unexplained variance for this effect: + SSe=nbj*sum((reshape(mXe, nr*ncj, []) - repmat(mX,[nr*ncj 1])).^2); + % Subtract replication/subject variance and the effect itself + SSe=SSe-SSr-SSb; + for k=1:i-1 + %remove embedded factors effects and error terms + if all(ismember(fx{k}, j)) + SSe=SSe-SS(k,:)-SSbe(k,:); + end + end + SSbe(i,:)=SSe; + end + MSe=squeeze(SSbe(i,:)/dfe); + % % MSr=squeeze(SSr/dfr); + % else + % dfw=nc*(nr-1); + % MSw=squeeze(SSw/dfw); + % + % dfe=dfw; + % MSe=MSw; + % end + dfb=dfb.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + % dfb=dfb.*epsilon(i,:); + % dfw=dfw.*epsilon(i,:); + % F(i,:)=squeeze(MSb)./MSw; + % p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + % end + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>4 || verbose==1 + varargout{2}(i,:)=dfb; + end + if nargout>5 || verbose==1 + %if any(rp) + varargout{3}(i,:)=dfe; + %else + % varargout{3}(i,:)=dfw; + %end + end + if nargout>6 || verbose==1 + varargout{4}(i,:)=SSb; + end + if nargout>7 || verbose==1 + %if any(rp) + varargout{5}(i,:)=SSe; + %else + % varargout{5}(i,:)=SSw; + %end + end +end + +if prod(sX)>nc*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + +if verbose + [ignore,df,dfe,SSb,SSe,SSt]=deal(varargout{:}); + MS=SS./df; + + %Display results + fprintf([repmat('-',1,80) '\n'] ); + fprintf(['%' num2str(max(cellfun('length', fx))*2+15) 's \t| df \t| SS \t| MS \t| F \t| p\n'], 'ANOVA results'); + fprintf([repmat('-',1,80) '\n'] ); + for j=1:min(size(p,2),6) + if size(p,2)>1 + fprintf('MULTIDIMENSIONAL DATA: [%d] ...\n',j) + end + + for i=1:length(fx) + if i<=nf + label=sprintf('Factor #%d',i); + else + label=['Interaction ' sprintf('%d*',fx{i})]; + label=label(1:end-1); + end + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],label); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\t% 8.4g\t %g\n',... + label,df(i),SS(i,j),MS(i,j),F(i,j),p(i,j)); + if any(rp) || i==nfx + label=sprintf([ '%' num2str(length(label)) 's'],'Error'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g\n',... + label,dfe(i),SSe(i,j),SSe(i,j)./dfe(i)); + end + end + + if any(rp) + MS_r=SSr./dfr; + label=sprintf([ '%' num2str(length(label)) 's'],'Subj/Repl'); + fprintf('%s: \t % 3.3g \t% 8.4g\t% 8.4g',... + label,dfr,SSr(j),MS_r(j)); + % The following is wrong: + % MSw is not the correct error term for the subj effect + % F_r=squeeze(MS_r)./MSw; + % p_r=1-f_cdf(F_r,dfr,dfw); + % fprintf('\t% 8.4g\t %g\n',... + % F_r(j),p_r(j)); + fprintf('\n'); + end + + label=sprintf([ '%' num2str(max(cellfun('length', fx))*2+15) 's'],'Total'); + fprintf('%s: \t % 3.3g \t% 8.4g\n',... + label,dft,SSt(j)); + if size(p,2)>1 + fprintf([repmat('. ',1,40) '\n']) + end + + end + if j3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + + +function [SS]= sumofsquares(X,j,nf,ncj,nbj,nX,mXw) + % Between groups stats for a given factor j + % ncj. Nb of cells for effect j + %ncj = prod(ng(j)); + % nbj: Nb of cells pooled by effect j + %nbj = nc./ncj; + mXb=permute(mX, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb,ncj,nbj,[]); + mXb=mean(mXb,2); + SS=nr*nbj*sum((reshape(mXb,ncj, []) - repmat(mX,[ncj 1])).^2); + +return + + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 (repeated measure one-way ANOVA) +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F = (1454/2)/(695.3/12) = 727/57.94 = 12.6 + + +% BETWEEN SUBJECT DESIGN WITH 2 REPLICATES +% ======================================== +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F observed = 28.283 12.393 1.973 +% F critique = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) +[p,F]=myanova(X,2,[]) + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +% +[p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'TRIAL x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + + +% http://lib.stat.cmu.edu/DASL/Datafiles/airpullutionfiltersdat.html +% 1. NOISE = Noise level reading (decibels) +% 2. SIZE = Vehicle size: 1 small 2 medium 3 large +% 3. TYPE = 1 standard silencer 2 Octel filter +% 4. SIDE = 1 right side 2 left side of car +% and 3 replicates + +x=[ + 810 1 1 1 + 820 1 1 1 + 820 1 1 1 + 840 2 1 1 + 840 2 1 1 + 845 2 1 1 + 785 3 1 1 + 790 3 1 1 + 785 3 1 1 + 835 1 1 2 + 835 1 1 2 + 835 1 1 2 + 845 2 1 2 + 855 2 1 2 + 850 2 1 2 + 760 3 1 2 + 760 3 1 2 + 770 3 1 2 + 820 1 2 1 + 820 1 2 1 + 820 1 2 1 + 820 2 2 1 + 820 2 2 1 + 825 2 2 1 + 775 3 2 1 + 775 3 2 1 + 775 3 2 1 + 825 1 2 2 + 825 1 2 2 + 825 1 2 2 + 815 2 2 2 + 825 2 2 2 + 825 2 2 2 + 770 3 2 2 + 760 3 2 2 + 765 3 2 2 + ]; +[i,nl]=dgrouping(x(:,2:end)); +X(i)=x(:,1); +X=reshape(X,nl); + +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% M1 = 11.0 M2 = 13.0 M3 = 14.2 + +% Two-way ANOVA from Cousineau 2007 +X= [ + 550 580 610 + 605 635 655 + 660 690 710 + ]'; + + +% Cousineau ? +X= [ + 150. 44. 71. 59. 132. 74. 1. + 335. 270. 156. 160. 118. 230. 1. + 149. 52. 91. 115. 43. 154. 1. + 159. 31. 127. 212. 71. 224. 1. + 159. 0. 35. 75. 71. 34. 1. + 292. 125. 184. 246. 225. 170. 1. + 297. 187. 66. 96. 209. 74. 1. + 170. 37. 42. 66. 114. 81. 1. + 346. 175. 177. 192. 239. 140. 2. + 426. 329. 236. 76. 102. 232. 2. + 359. 238. 183. 123. 183. 30. 2. + 272. 60. 82. 85. 101. 98. 2. + 200. 271. 263. 216. 241. 227. 2. + 366. 291. 263. 144. 220. 180. 2. + 371. 364. 270. 308. 219. 267. 2. + 497. 402. 294. 216. 284. 255. 2. + 282. 186. 225. 134. 189. 169. 3. + 317. 31. 85. 120. 131. 205. 3. + 362. 104. 144. 114. 115. 127. 3. + 338. 132. 91. 77. 108. 169. 3. + 263. 94. 141. 142. 120. 195. 3. + 138. 38. 16. 95. 39. 55. 3. + 329. 62. 62. 6. 93. 67. 3. + 292. 139. 104. 184. 193. 122. 3. + ]; +X=reshape(X(:,1:6),[8,3,6]); +X=permute(X,[1 3 2]); + + +% Cousineau 2005; TQPM +% Simulated data of a 2-by-5 exp with 16 subjects +X=str2num(urlread('http://www.tqmp.org/Content/vol01-1/p042/p042.dat')); +X=reshape(X(:,end),[16,5,2]); +X=permute(X,[3 2 1]); +myanova(X,2,1:2) +% all the variances are homogeneous and spherical, Tabachnik & Fidell, 1996 +% Mauchly s W = 0.74, p > .50 for factor 2 +% and W = 0.68, p > .50 for the interaction; +% this test cannot be performed for factor 1 since it has only two levels +% but we generated the data such that it is also homogenous. +% The Greenhouse Geiser and the Huynh Feldt epsilons are close to 1 so that +% we don t need to use corrections (Huynh, 1978, Rouanet and Lepine, 1970). + +% Effect name SS dl MS F p<0.001 +% Factor 1 10621 1 10621 76.8 *** +% Error 2073 15 135 +% Factor 2 11784 4 8196 16.4 *** +% Error 4378 60 72.9 +% Interaction 2250 4 562 6.52 *** +% Error 5171 60 86.2 +% Subject: F(1, 15) = 710, p < .001) + +% Analyzed using SPSS15:; +% Tests of Between-Subjects Effects +% Dependent Variable: X +% Source Type III Sum of Squares df Mean Square F Sig. +% Intercept Hypothesis 66283627.628 1 66283627.628 710.851 .000 +% Error 1398682.399 15 93245.493(a) +% fx1 Hypothesis 10621.640 1 10621.640 76.829 .000 +% Error 2073.752 15 138.250(b) +% fx2 Hypothesis 4784.064 4 1196.016 16.389 .000 +% Error 4378.604 60 72.977(c) +% Subject Hypothesis 1398682.399 15 93245.493 745.749 .000 +% Error 1314.799 10.515 125.036(d) +% fx1 * fx2 Hypothesis 2250.918 4 562.729 6.529 .000 +% Error 5171.445 60 86.191(e) +% fx1 * Subject Hypothesis 2073.752 15 138.250 1.604 .100 +% Error 5171.445 60 86.191(e) +% fx2 * Subject Hypothesis 4378.604 60 72.977 .847 .739 +% Error 5171.445 60 86.191(e) +% fx1*fx2*Subj Hypothesis 5171.445 60 86.191 . . +% Error .000 0 .(f) +% (a) MS(Subject) +% (b) MS(fx1 * Subject) +% (c) MS(fx2 * Subject) +% (d) 1.000 MS(fx1 * Subject) + MS(fx2 * Subject) - MS(fx1 * fx2 * Subject) +% (e) MS(fx1 * fx2 * Subject) +% (f) MS(Error) + + + + +% Loftus & Masson 1994 +% Reported in Cousineau 2005 +% X(2*5*6) = R vs U | SOA 50/100/200/400 | SUBJ(6) +X= [ + 1 450 462 12 460 482 22 460 497 37 480 507 27 + 2 510 492 -18 515 530 15 520 534 14 504 550 46 + 3 492 508 16 512 522 10 503 553 50 520 539 19 + 4 524 532 8 530 543 13 517 546 29 503 553 50 + 5 420 409 -11 424 452 28 431 468 37 446 472 26 + 6 540 550 10 538 528 -10 552 575 23 562 598 36 + ]; +X=reshape(X(:,2:end),6,3,4); +X=permute(X(:,1:2,:),[2 3 1]); + + +% Loftus % Masson +% TABLE 2: Hypothetical Subject Means for a Within-Subject Design +% Raw data Normalized data +% Subject Incongruous Congruous Neutral Mi Incongruous Congruous Neutral Mi +X= [ + 1 784 632 651 689.0 848.0 696.0 715.0 753.0 + 2 853 702 689 748.0 858.0 707.0 694.0 753.0 + 3 622 598 606 608.7 766.3 742.3 750.3 753.0 + 4 954 873 855 894.0 813.0 732.0 714.0 753.0 + 5 634 600 595 609.7 777.3 743.3 738.3 753.0 + 6 751 729 740 740.0 764.0 742.0 753.0 753.0 + 7 918 877 893 896.0 775.0 734.0 750.0 753.0 + 8 894 801 822 839.0 808.0 715.0 736.0 753.0 + ]; + +X=reshape(X(:,2:4),8,3); +X=permute(X,[2 1]); +myanova(X,1,1) +% +% ANOVA +% Source df SS MS F +% +% Subjects 7 280,178 +% Conditions 2 27,984 13,992 13.08 +% S * C 14 14,972 1,069 +% Total 23 323,133 + + +clc; +for i=1:2; for j=1:3; for k=1:5; for l=1:10; + xx(i,j,k,l)=randn; + fprintf('%d\t%d\t%d\t%d\t%f\n', i,j,k,l,xx(i,j,k,l)); +end;end;end;end \ No newline at end of file diff --git a/stat/myanova3.m b/stat/myanova3.m new file mode 100644 index 0000000..36ed703 --- /dev/null +++ b/stat/myanova3.m @@ -0,0 +1,301 @@ +function [p,F,fx,varargout]=myanova(X,nf,rp,epsilon) +% myanova - N-way ANOVA +% [p,F,fx]=myanova(X,nf) +% [p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=... +% Performs a N-way beween subjects anova on X +% +%INPUTS: +% X = [ factor1 x factor2 x ... x factorN x replicates x ...] +% This function is vectorized, ie. anova is computed for each value in X +% after the 'replicates' (i.e. subject) dimension. +% nf: number of factors +% +%OUTPUTS: +% p: the Null hypothesis probability +% F: the F-values +% fx: a cell array listing the tested effects. +% eta: percentage of explained variance by each factor +% epsilon: sphericity correction if applicable +% +%OPTIONAL INPUTS: +% [...]=myanova(X,nf,rp) +% To specifiy repeated factors in a within-subject design +% rp: an array listing the repeated factors +% +% [...]=myanova(X,nf,rp,epsilon) +% Correct for non-spherical data using epsilon (expanded to match the +% size of measures, if necessary). If epsilon=NaN, epsilon(s) will be +% computed using Greenhouse-Geisser or Huynh-Feldt (if eGG>.7) +% +% Ex: +% 2 tasks by 3 condition for 10 subjects, within subject design: +% >> [p,F,fx]=myanova(X(1:2,1:3,1:10),2,1:2) +% p: 3x1 array +% F: 3x1 array +% fx: 3x1 cells: { 1 , 2 , [ 1 2 ]} +% +% Requires: f_cdf() + +sX=[size(X) 1]; +nX=ndims(X); +if nargin<2 + error('Number of factors (nf) is mandatory') +end +% Number of groups for each factor +ng=sX(1:nf); +% Nb of cells +png=prod(ng); +% Number of replicates, ie. samples in each group +nr=sX(nf+1); +%Size of dependent variables (DV) +szd=[size(X) ones(1,nf)]; +szd=szd(nf+2:end); +% Number of DV +pszd=prod(szd); + +if nargin<3 + rp=[]; +end +if ~isempty(rp) & ~all(ismember(1:nf,rp)) + error('Mixed designs (split plot) ANOVA unavailable!') +end +if ~isempty(rp) & nf>3 + error('Repeated measure ANOVA is only available for 2 factor designs!') +end +if nargin<4 + epsilon=1; +end + +% Within Group/Error stats +mXw=sum(X,nf+1)./sX(nf+1); +SSw=X-repmat(mXw,[ones(1,nf) nr 1]); +SSw=reshape(SSw, [png*nr, szd]); +SSw=sum(SSw.^2); +if (nr>1) + dfw=png*(nr-1); + MSw=squeeze(SSw/dfw); +else + error('(my)anova doesn''t work with 1 subject / group!') +end + +% Population stats +%Total number of freedom +dft=(png*nr)-1; +mX=reshape(mXw, [png, szd]); +% Mean value of DV per subject +mX=sum(mX,1)./png; + +% Useful value: +sX2=sum(reshape(X, [png*nr, szd]),1).^2./(png*nr); + +% These are not used afterwards +SSt=sum(reshape(X, [png*nr, szd]).^2,1); +SSt=SSt-sX2; +MSt=squeeze(SSt/dft); + +error +unterminated program!!! + +if ~isempty(rp) + % Correct Within Error term to account for repeated measurements + dfr=(nr-1); + mXr=permute(X, [nf+1 1:nf nf+2:nX]); + mXr=reshape(mXr,nr,png,pszd); + mXr=mean(mXr,2); + % SSr=png*sum((reshape(mXr, nr, szd) - repmat(mX,[nr 1])).^2); + SSr=png*(sum(reshape(mXr, nr, szd).^2,1) - mX2); + SSw=SSt-SSr; +end + +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); + +% Sphericity checking +if isnan(epsilon) + % check for sphericity first + if all(ng<=2) + epsilon=1; + else + [eGG,eHF]=sphericity(X,nf); + epsilon=eGG; + epsilon(eGG>.7)=eHF(eGG>.7); + epsilon(ng==2)=1; + epsilon=min(epsilon,1); + end +end +if numel(epsilon)==1; + epsilon=epsilon*ones(nfx,prod(sX(nf+2:end))); +elseif length(epsilon(:))==nfx + epsilon=epsilon(:)*ones(1,prod(sX(nf+2:end))); +end + +% [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... +if nargout > 3 + varargout{1}=epsilon; +end +if nargout > 8 + varargout{6}=SSt; +end + +for i=1:length(fx) + j=fx{i}; + % Between groups stats for each factor + dfb=prod(ng(j)-1); + mXb=permute(mXw, [j setdiff(1:nf,j) nf+1:nX]); + mXb=reshape(mXb, prod(ng(j)),png/prod(ng(j)), []); + mXb=mean(mXb,2); + SSb=nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) - repmat(mX,[prod(ng(j)) 1])).^2); + if length(j)>1 + % Interaction: + % we need to remove single factor variance from the Sum of Squares + for k=1:i-1 + if all(ismember(fx{k}, j)) + SSb=SSb-SS(k,:); + end + end + end + SS(i,:)=SSb; + MSb=SSb./dfb; + + if not(isempty(rp)) + % Correct Error term to account for repeated measurements + if length(j)==1 + dfe=(nr-1)*dfb; + mXe=permute(X, [nf+1 j setdiff(1:nf,j) nf+2:nX]); + mXe=reshape(mXe,nr*prod(ng(j)),png/prod(ng(j)),[]); + mXe=mean(mXe,2); + SSe=png/prod(ng(j))*sum((reshape(mXe, nr*prod(ng(j)), []) - repmat(mX,[nr*prod(ng(j)) 1])).^2); + SSe=SSe-SSr-SSb; + SSbe(i,:)=SSe; + else + % Interaction effects residuals + % + % WARNING !!!! + % + % the following does NOT work for more-than-2-factors design! + % + dfe=(png-sum(ng-1)-1)*(nr-1); + mXe=reshape(X,png*nr,[]); + SSe=sum((mXe - repmat(mX,[nr*png 1])).^2); + SSe=SSe-SSr-sum(SSbe(1:nf,:))-sum(SS(1:nfx,:)); + end + MSe=squeeze(SSe/dfe); + MSr=squeeze(SSr/dfr); + dfb=dfb.*epsilon(i,:); + dfe=dfe.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSe; + p(i,:)=1-f_cdf(F(i,:),dfb,dfe); + else + dfb=dfb.*epsilon(i,:); + dfw=dfw.*epsilon(i,:); + F(i,:)=squeeze(MSb)./MSw; + p(i,:)=1-f_cdf(F(i,:),dfb,dfw); + end + % [p,F,fx,epsilon(1),df(2),dfe(3),SS(4),SSe(5),SSt(6)]=... + if nargout>4 + varargout{2}(i,:)=dfb; + end + if nargout>5 + if not(isempty(rp)) + varargout{3}(i,:)=dfe; + else + varargout{3}(i,:)=dfw; + end + end + if nargout>6 + varargout{4}(i,:)=SSb; + end + if nargout>7 + if not(isempty(rp)) + varargout{5}(i,:)=SSe; + else + varargout{5}(i,:)=SSw; + end + end +end + +if prod(sX)>png*nr + p=reshape(p,[nfx,sX(nf+2:end)]); + F=reshape(F,[nfx,sX(nf+2:end)]); +end + + + +return + + +if nargout>3 + SS(nfx+1,:)=SSt; + SS(nfx+2,:)=SSw; + SS(nfx+3,:)=SSr; + SS(nfx+4,:)=SSe; +end +if nargout>4 + df(nfx+1,:)=dft; + df(nfx+2,:)=dfw; + df(nfx+3,:)=dfr; + df(nfx+4,:)=dfe; +end +if nargout>5 + MS(nfx+1,:)=MSt; + MS(nfx+2,:)=MSw; + MS(nfx+3,:)=MSr; + MS(nfx+4,:)=MSe; +end + + +return + +%% RESSOURCES +% http://www.brown.edu/Research/LCE/Fall2004/Within%20subjs.pdf +% + +%% EXAMPLES +% +% from Zar, 1999, pp. 250 sqq. +% Ex. 12.5 repeated measure ANOVA +X= [ + 164 152 178 + 202 181 222 + 143 136 132 + 210 194 216 + 228 219 245 + 173 159 182 + 161 157 165 + ]'; +% F= 727/57.94 = 12.6 + +% http://www.richland.edu/james/lecture/m170/ch13-2wy.html +% SS = 512.8667 449.4667 143.1333 136.0000 1241.4667 +% F = 3.682 3.056 2.641 +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) + + + + +% % http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +% X=[ 8 9 8 8 9 7 10 9 10; 9 10 9 10 9 13 8 9 9; 8 7 7 12 7 9 10 9 7; 6 8 9 8 10 10 12 9 10; 7 6 7 11 12 8 8 11 9]; +% X=reshape(X,5,3,3); +% +% % COND TRIAL SUBJECT +% X=permute(X,[3 2 1]); +% +% [p,F]=myanova(X,2,1:2) +% l=factorlabels(X) +% rm_anova2(X(:), l(:,3),l(:,1),l(:,2),{'COND', 'TRIAL'}) +% % 'Source' 'SS' 'df' 'MS' 'F' 'p' +% % 'COND' [24.8444] [ 2] [12.4222] [4.0216] [0.0618] +% % 'TRIAL' [ 0.3111] [ 2] [ 0.1556] [0.0625] [0.9399] +% % 'COND x TRIAL' [ 1.6889] [ 4] [ 0.4222] [0.1907] [0.9397] +% % 'COND x Subj' [24.7111] [ 8] [ 3.0889] [] [] +% % 'COND x Subj' [19.9111] [ 8] [ 2.4889] [] [] +% % 'COND x TRIAL x Subj' [35.4222] [16] [ 2.2139] [] [] + + \ No newline at end of file diff --git a/stat/myanovaeffects.m b/stat/myanovaeffects.m new file mode 100644 index 0000000..fd76895 --- /dev/null +++ b/stat/myanovaeffects.m @@ -0,0 +1,27 @@ +function [fx]=myanovaeffects(nf,factornames) +% myanovaeffects - List effects and their interaction in a factorial design +% [fx]=myanovaeffects(nf) +% List main effects and interaction(s) in factorial design with [nf] factors +% [fx] is a N-by-1 cell array +% +% [fx]=myanovaeffects(nf,factornames) +% Makes up a cell list of char listing instead of the factor index, +% their names according to factornames. +% Example: +% >> myanovaeffects(2, {'FACTOR1','FACTOR2'}) +% outputs: { 'FACTOR1' 'FACTOR2' 'FACTOR1*FACTOR2' } +% +% See also: myanova +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +if nargin>1 + for i=1:length(fx) + fxn{i,1}=factornames{fx{i}(1)}; + for j=2:length(fx{i}) + fxn{i,1}=[ fxn{i} '*' factornames{fx{i}(j)}]; + end + end + fx=fxn; +end \ No newline at end of file diff --git a/stat/mypermtest.m b/stat/mypermtest.m new file mode 100644 index 0000000..247916d --- /dev/null +++ b/stat/mypermtest.m @@ -0,0 +1,266 @@ +function [pv,S0,S,P]=mypermtest(X,X2,dim_p,dim_m,NP,tails) +% mypermtest - permutation test +% [pv,S,T,P]=mypermtest(X1,X2,dimP,dimM,NP) +% [pv]=mypermtest(X,ns,dim,NP,ftest[abstmax],fparams) +% +%Inputs: +% X1,X2: Data matrices. +% If only X1 is given, the permutation dimension (dim_p) should be given. +% Alternatively: +% X can be a single data matrix. But the number of samples (ie subjects) +% in the first condition should be set using: ns +% I.e. X = [ X1 ; X2 ] & ns=size(X1,1) +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : paired permutations (default) +% Use dim_p < 0 for unpaired samples. +% dimM: Dimensions of data over which the maximum T-value is to be found. +% Default: all dimensions +% NP: Number of permutations (may lead to exhaustive permutation, +% for example if NP <= 2^N-1 using paired data) +% +%Outputs: +% pv: thresholds at the given p-values, computed from the permutations +% T: observed T-values +% S: T-values from the permutations +% P: permutations used + +% NOT YET: +% tails ; one/two tailed tests + +% ftest: function applied on data. +% Default is 'maxabst', i.e. compute the maximum (two-tailed) T-value +% fparams: cell array indicating the parameters passed to the function +% when called + +NMAX_UNPAIRED=15; % maximum number of observations for exhaustive search for unpaired samples +NMAX_PAIRED=30; % maximum number of observations for exhaustive search in paired samples +NPERMS=10000; %Max. number of permutations + +%initialize parameters +if nargin<3 + dim=find(size(X)>1); + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + dim=dim(1); + dim_p=dim; +else + dim=abs(dim_p); +end + + +% ORIGINAL OBSERVATIONS +sX=size(X); +nX=length(sX); +X=permute(X, [dim setdiff(1:nX,dim)]); +% the shape of the measurement data +nsX=size(X); +nsX(1)=[]; +ndX=ndims(X); + +if nargin<4 + dim_m=1:ndX-1; +end + +if prod(size(X2))>1 + X2=permute(X2, [dim setdiff(1:nX,dim)]); + sX2=size(X2); + if ~isequal(sX(setdiff(1:nX,dim)), sX2(2:end)) + error('X1 and X2 should be of the same size in the non-permuted dimensions!') + end + X=cat(1,X,X2); + N=[sX(dim) sX2(1)]; + clear sX2; +elseif prod(size(X2))==1 + N=[X2 sX(dim)-X2]; +else + error('Check inputs!') +end +clear X2; + +% Now compute the number of exhaustive permutations +if dim_p>0 + % We compute only one half of the permutations for paired samples + Nexh=2^(N(1)-1)-1; +else + Nexh=factorial(N(1)+N(2))/(factorial(N(1))*factorial(N(2)))-1; +end + +exhaustive=0; +if nargin<5 + if (dim_p>0 & (N(1)+N(2))Nexh + warning(sprintf('Cannot do %d permutations. For this dataset, the maximum is: %d.\nThis latter value will be used.',NP, Nexh)); + NP=Nexh; + exhaustive=1; +end + +if NP>NPERMS + warning(sprintf('Too many permutations! Only %d will be performed.',NPERMS)); + NP = NPERMS; + exhaustive=0; +end + +% DEBUG: +NP = min(500,NP); + +% List of permutations/randomizations +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + P=sprintf(sprintf('%%0%dd',N(1)), str2num(dec2bin(1:NP))); + P=reshape(P==49, [N(1),NP])'; + else + % non exhaustive + P=round(rand(NP,N(1))); + end + P=[P 1-P].*N(1)+repmat(1:N(1), [NP,2]); +else + % non-paired perms + if exhaustive + % all possible perms + p=nchoosek(1:(N(1)+N(2)),N(1)); + p(1,:)=[]; % the 1st is not a permutation + for i=1:NP + P(i,:)=[p(i,:) setdiff(1:(N(1)+N(2)),p(i,:))]; + end + clear p + else + % non exhaustive + for i=1:NP + P(i,:)=randperm(N(1)+N(2)); + end + end +end + +% PERMUTATION LOOP +for i=0:NP + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:); + end + + Z=mean(Y(1:N(1),:))-mean(Y(N(1)+(1:N(2)),:)); + Z= Z ./ sqrt( std(Y(1:N(1),:)).^2/N(1) + std(Y(N(1)+(1:N(2)),:)).^2/N(2)); + Z= abs(Z); + Z=reshape(Z,nsX); + + if i==0 + S0=Z; + sz=size(S0); + % preallocate memory + S=zeros([NP,sz]); + else + if ~isequal(dim_m,1:(ndX-1)) + Z=submax(Z,dim_m); + else + Z=max(Z(:)); + end + S(i,:)=Z(:); + end + +end + + +% Compute pvalues based on permutation statistics +pv=(sum(repmat(shiftdim(S0, -1),[NP 1])<=S)+1)/(NP+1); +pv=shiftdim(pv, 1); + +return + + +% FORGET THE REST! + +% S=sort(S); + +for pp=1:length(pthres) + Thd(pp,:) = S(ceil((length(S)*(1-pthres(pp)))),:); +end +S0=S0(1,:); + +return + +function [Z]=submax(Z,dims) +sZ=size(Z); +odims=setdiff(1:length(sZ),dims); +pdims=prod(sZ(dims)); +Z=permute(Z, [dims odims]); +Z=reshape(Z,[pdims, sZ(odims) 1]); +Z=abs(Z); +Z=max(Z,[],1); +Z=repmat(Z,[pdims 1]); +Z=reshape(Z,[sZ(dims) sZ(odims) 1]); +Z=ipermute(Z, [dims odims]); + + + +return + +% +% OLDIES +% + + +function [Z]=pseudoT(Y1,Y2) +% default function: max of pseudo-t +% sqrt((std_PA_orig.*std_PA_orig/JA)+(std_PB_orig.*std_PB_orig/JB)); +Z=(mean(Y1)-mean(Y2)) ./ sqrt( std(Y1).*std(Y1)/size(Y1,1) + std(Y2).*std(Y2)/size(Y2,1) ); + +function [Z]=maxabst(Y1,Y2,dims) +[Z]=pseudoT(Y1,Y2); +% remove the 1st (subjects) dimension: +Z=shiftdim(Z,1); +sZ=size(Z); +odims=setdiff(1:length(sZ),dims); +pdims=prod(sZ(dims)); +Z=permute(Z, [dims odims]); +Z=reshape(Z,[pdims, sZ(odims) 1]); +Z=abs(Z); +Z=max(Z,[],1); +Z=repmat(Z,[pdims 1]); +Z=reshape(Z,[sZ(dims) sZ(odims) 1]); +Z=ipermute(Z, [dims odims]); + + +return + + +% EX: +% X=rand(3,5)+cumsum(ones(3,5)) +% [th,o,ss]=mypermtest(X,1,2,[.05],500,'myanova', {1}) + +if nargin<7 + fparams={}; +end +if nargin<8 + ftest='maxabst'; + % Matlab's inline calls are slow ! + % f=inline('mean(x)/std(x)','x'); + + % Maximum of T values will be search along all measurement dimensions + fparams={1:(ndims(X)-1)}; +end + + +if singleinput + Y=reshape(Y,[N(1)+N(2) nsX]); + Y=ipermute(Y, [dim setdiff(1:nX,[dim])]); + Z=feval(ftest,Y,fparams{:}); +else + Y1=reshape(Y(1:N(1),:), [N(1), nsX]); + Y2=reshape(Y(N(1)+(1:N(2)),:), [N(2), nsX]); + Z=feval(ftest,Y1,Y2,fparams{:}); +end + diff --git a/stat/myplannedcomp.m b/stat/myplannedcomp.m new file mode 100644 index 0000000..1a4aff1 --- /dev/null +++ b/stat/myplannedcomp.m @@ -0,0 +1,8 @@ +function [p,fx,t]=pc(X,nf) + +[p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(X,nf); +% nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) + +Y=cat(j, subarray(X,i,j), mean(subarray(X,i,-j),j)) + +p \ No newline at end of file diff --git a/stat/myposthoc.m b/stat/myposthoc.m new file mode 100644 index 0000000..4fc6c42 --- /dev/null +++ b/stat/myposthoc.m @@ -0,0 +1,8 @@ +function [p,fx,t]=ph(X,nf) + +[p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(X,nf); +% nr*png/prod(ng(j))*sum((reshape(mXb, prod(ng(j)), []) + +Y=cat(j, subarray(X,i,j), mean(subarray(X,i,-j),j)) + +p \ No newline at end of file diff --git a/stat/myrmanova.m.bad b/stat/myrmanova.m.bad new file mode 100644 index 0000000000000000000000000000000000000000..a0a608f6afc1b2961d8e3b83a995b8aead3cba11 GIT binary patch literal 19990 zcmeHPUvuNgao4$AmEyYg!7q89oJ%6LM}Zjp2lr@3yCStbi;^r#THVTP6-a^DiC-?io&iWu(%tUaXP;vqc0mm0Pj^pu&vZ}E zK)ao`<9Z*heYE!XU#@-m<(F$~YgOEM|7dOP2S3>PXzek*{`p=Xt^FwL+()1NX6DeH zz5fJU_$%C}&yJ4|>z8RdtJi8?s(7Ivr8ml8I;o}c>p_icrm3r@W^0z}HfM1|=Nn1T z7j1UE(Dde$bfB`xoudOD^+#ui@Id@oqLoO(S=%#JdWK{wwtG`Jbn)!}z4CcH*{g8v$sKM7_|BJbwq+1g|y_^o$c3a2DN@mk2 z@wYC0Z@5N$s&R!gO;y>!&mKP5@lwCedh@8tIA;fgluBHt>2=en>nhvr9zT50^W!&u zTxZ)eZ*b{9e6Z&MM|V05Mu9)9v*Wp6Wva>AexF)9jH`8(*9}{?-X0A6S-N%PMPomy zv;Ix$Cl4Pyokl5yw6*6)tqUqLvik7Ly$2~tq&FSmF|G0{p)9ah9*ni`N!4OS=D)z<` zufAxyBR$&9&DGp@UPHIJ zZpo4E=qATVSFiI?Zm61zi9`%=uIo0&wiwN`H#DYKhk5^s^7@zbd+qUtX{j4Gcxr~W zG3Y0}!8Zc!Pj9XoYT$t4Y|P$diNRbeOkVvfWUJIK4RagyOv99DP}eBK-tf~%YqYvg zT00w~6j>Vy3c#Cwf{GjQjG$un(>6w!gzb&~yurhTOw~Z3xk1|2Ggi^z4gj_<0XSQ zn59dLmD5vaM9{+rt?O9;vtMW3Da^Xg*^WP8+_i;SS7DnovwrHuH!$kbJm)}`*1j7I z;%PD+rCXg&uVyQ1!9YJb>5*ZEf!?38c4wb;PIsp4V1JJtAouXu=d8EgowDQB-W2AS zO!_xz@wILV24m(}eAkBgkA(kw`@iD<7smhEH}wBu|6zcCcmJQ~{=WdE|C#&$-&?&u z4gVj@{G$Img8z&A-G8pF{qPG+LH~^Ve~R{R;tvB)5o_BmTHFfj7Y6;BD7Z+c(=e%t z_02^Zq@jOt{MtP^I_->quAZKpwob;Uufx{Si96~Zx313K;?_QU)89QB4K#k)-@U%- zKRbPU_O?AbDYr zyFk6Y_UxrzI)`n`7qGY2k(}%H(lizqbFXIp_&t_|o6^m@Wvt;fzyw#>WR7)jaTU30 zX}PvsK*P)$PF>R_yx-4K+%NzCT3h?kKLYT-{oe9_K51VKcEkCLo9+Fludl66QT)E&Qgb~5&t<=5SwbKPw_HwVY3qy3#Hqt7R9@}iBr(77gkIJ@ayb$7OLKN&$E z^ug{mA8_Z@(eY_}|Kx_}#SOUitrB4deeGAp3v$ zz2$#&Vm?3SVf!R_@}$!~J?OOB`@K`h^wks00lAFbxBchsr2p(mGCbQKbx$E{k}HjU z+-EfUby?OCV;^$>^r63dIvH+b`2R6y0L%E(kU2tV--54N@c-7b`0wBR?++3C{R@c$ z|E2f;mi>PX`~RARkLwfM|Bm(V&x-bc6e~%97%L2Aw(v!iTX+JsMZkM&6xWg_Rhxz0 zjUOv-rbA^EL>HkyNawMy>>NBj>0PvrFFO0}gP!tY`|z-{zpHfik6XJ(+k34=&R(l` zfx!6oe(z%EhYB0qRWGEky!S1+EVnjK?rJ2jYet=CF`8EDjqB`V%P`E*Xp3{3Z&@SG`XiqxuP33RZIQ~Qa7u{B8 zZ?AQ7M3dLEPV4BR)$R0por8U$2dcZ!1H<~m>OngWu!-g_R}kE-n|fWd<zeJ4oBabO^09;VpNCEz1$$VTa?avuA$iI-N&TjeUR zI_f4X{~{{CWGn}`s90VvvuHlik~FSNyz9!q55v(ss+6&Rk6qz%m5r`9Hy>%Aa1%fh z;P^%QjtxihiPv5)%fq8vNVjE;8R4z6^7j70>2^+R`3@QHrFR;$R}EgD1W_dk-ujhU zRokrUo3h(LEiUkSQTS87T9)^?+&$Sl?(B5Bt$mtgw)fc1_VIR|ov#mHGDT59Z}rtJ zxS1$(G$RlbfEdZ53K+DC3S|X=PmMQ==HJdnPgHbx4l6MSU*`Gma9R|lf14U z<|>ot&{IMjMO@F6k~k%$=Ldsqyr(XQn=s?MpPx(#8|2X zkYTl(J=^kiCLXuxfUvyirV`IK*}HcTE97?l72p?wTV+C~2C|nlNYLeSD~_k}LeGo* z{NRp%RacAM^<{tYpbldq5eb?psN{BEg&ya$;3ZGylM1~r`LW7{Zto(-Boq_u_?Bu( zrMzE7?&VI8HUW>Y^0~vI59Q8#)F1{g;tE(oWaD|86YK2w(r2S-7*4OSkH~_AUB%OA zTwm?|ey`o#Rv2*tO7w86Rr8<;*OE+S}C zsR8aSCa$v?s`0JS#Q5_Gg8n-$er z_V4Q?{{iNNM#}Lt^;Y#@LBm%~4fl-FqwCE3JuL8J5Hi7cf0hylrito>U54{Vbax9DbU*!^j`e?*HZ7_{( zY%mgDG~T3li{53oD)nl86PEW=tY(O6y4KlYh|z&VUEVS?jc=AORBIHB5!86x_hK=0 z@T{C|KF&Bu6|lcPxLj>><;4*OXQlkqi^^r7$Xp%)VGAIV`&Cr*UHs6*_V7XMBcKw= zH1$%tS3kv)oe;xXV9Ni5qi2}k(ri>_xth$)$7+_V%iMe#%yJEx>jQ#7UOh>0>ZZj0lqVz(}d%c$p%z~5Y2y-3eoK()Lud30g8V&I1<36iS&aO6z6Ld+Qtg|P6 zdgc2O8^_c6EMXM5NyMz`v2pMQ1taMuy~-N^p2GI~Y&v4(uFA@C=4E*$)L{)ebvT3? z7p8-C21@EHt!LPd^M^PUna$oy7?{u-EE*^^KzqC-d2-fo%rN!OQ@=7ftFrS~Eb&vE z#T>z@LVsUvVkCWnq%Q^L%zueqZez}0LIsn$!*-@+4!y%EUt=_{2>#Ptq>&MfpNb!er*yhCd z;=yHY?`f;n#zYcoE>UJfxVY=25CGab+wLABoFj79*(jb)*b6Vl zp;p&*asG3rFq|!8$roS1dqeeWg>g+W8TvHyae8OS(E9{)1e-?w))iJZV#$CB@vOnl zrRcHfX57>mw;h?Gsd#a4mR8fU8ivkr)DL%-p&^XJU4!9}aMna~@PdOlMmAEojV7iG zI5`Z9Bg1B#Vm2i8mt{y}owcD16>gX~6TDfgSgxt)IM%$0TwAkirmX-?gE|FFf+_4t z>-c%AwaH~^_L;-I49 zLP|5ZD3=VF_Qi3oAwX!3qB*Eb9oAiuP;k6j*2D3rG=Rf{db(mc8h%yNVqlGdW!YIH zm#1pcp=XsXfbFay z0e9^xD>=aI*sPQ_FOiNS>WB=g;n3pg3`Zo>ie5c~)k8#3tpCM}mc2kX&u7*4%f{r! 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If not given, perform the test along the first non +% singleton dimension. +% +% MYTTEST(X, r,dim) with r single number specifying the dimension +% from which the two groups are formed, therefore, +% size(X,r) must be equal to 2 +% (and r must be different from dim) +% +% MYTTEST(X1, X2, dim, wtest) : wtest specify the test to be used: +% 'ttest' : t-test for equal variances [default] +% 'uttest' : t-test for unequal variances +% 'pttest' : t-test for paired samples +% +% MYTTEST(X1, X2, dim, wtest, varcorr) apply a matrix 'varcorr' on +% the denominator (ie. on empirical variance) before computing the +% T-value. +% +% MYTTEST(X1, [], [dim, ...]) performs a one-sample t-test. +% +% [P, T, CI, d, g, sigma_d] = TTEST(...) gives this probability P and +% the value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% d is the Cohen's d measure of the effect size. +% sigma_d is such that 1.96*sigma is the 95% Confidence Interval on d +% g is Hedges' measure of effect size (). +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. An effect size of d=0.2 is considered as small; d=0.5 is +% medium and d>0.8 indicates a big effect. +% +% Example: X1 and X2 are [ N x [voxelsX x voxelsY x voxelsZ ] fMRI-volume ] +% corresponding to two conditions run with the same pool +% of (N) subjects +% To test whether some voxel value differ significantly +% between conditions: myttest(X1,X2,1,'pttest') +% + +% Adapted from C. Goutte's functions by K. N'Diaye, 2005/04/20 +if nargin<4 + wtest='ttest'; +end +if nargin==1 + X2=[]; +end +if isequal(X2,0) || isempty(X2) + X2=0.*X1; + wtest='onesample'; +elseif numel(X2)==1; + if ~isequal(size(X1,X2),2) + error('MyTTest:WrongDimension','Dimension along which the comparison is made must have only 2 levels') + end + r=X2; + X2=subarray(X1,2,r); + X1=subarray(X1,1,r); +end +if nargin<3, + dim=[]; +end +UseVarCorr=0; +if nargin>4 + UseVarCorr=1; +end +if not(isnumeric(dim)) & ischar(dim) + wtest=dim; + dim=[]; +end +if isempty(dim) + % Determine which dimension to use + dim = min(find(size(X1)~=1)); + if isempty(dim), dim = 1; end +end +if dim<1 + error('myttest: wrong dimension argument') +end +if dim>1 + p=[ dim, 1:dim-1 dim+1:ndims(X1) ]; + X1=permute(X1, p); + X2=permute(X2, p); +end + +s1=size(X1); +s2=size(X2); +if not(isequal(s1(2:end), s2(2:end))) + error('myttest: X1 and X2 must be the same size along the variable''s dimension(s)') +end +n1=size(X1,1); +n2=size(X2,1); +X1=X1(:,:);% reshape(X1,[n1 prod(s1)/n1 ]); +X2=X2(:,:);% reshape(X2,[n2 prod(s2)/n2 ]); + +tmap=repmat(NaN,1,prod(s1(2:end))); +pmap=tmap; +d=pmap; + +if isequal(s1, s2) + k=find(all(X1 == X2)); + pmap(k)=1; + tmap(k)=0; +else + k=[]; +end + +I=find(all(isfinite(X1))&all(isfinite(X2))); % make a test only on 'finite' numbers +I=setdiff(I,k); % remove columns which are identical in X1 and X2 +nI=length(I); +if nI2 + d(I)=(a1)./sqrt((v1)./2); + end + + case 'ttest' + df = n1 + n2 - 2 ; + n = 1./(1./n1 + 1./n2); + % Pooled variance + pvar = ((n1 - 1) * v1 + (n2 - 1) * v2) ./ df ; + + case 'uttest' + n = 1./(1./n1 + 1./n2) ; + pvar = (v1 ./ n1 + v2 ./ n2) ; + % Welch-Satterthwaite equation to approximate pooled d.f.: + df = pvar .* pvar ./ ( ... + (v1 ./ n1) .* (v1 ./ n1) ./ (n1 - 1) + ... + (v2 ./ n2) .* (v2 ./ n2) ./ (n2 - 1) ); + pvar = n.* pvar ; + + case {'paired' 'pttest'} + wtest='paired'; + if ~isequal(s1,s2) + error('Sizes of X1 and X2 should be equal for paired test.') + end + if any(a1(:) ~= a2(:)) + % use abs to avoid numerical errors for very similar data + % for which v1+v2-2cab may be close to 0. + df = n1 - 1 ; + cab = sum((X1(:,I) - repmat(a1,[n1 1])) .* (X2(:,I) - repmat(a2,[n1 1]))) / (n1 - 1) ; + n = n1; + pvar = abs(v1 + v2 - 2 .* cab) ; + + if nargout>2 + d(I) = (a1-a2)./sqrt(pvar./2); + warning('Paired variance used for computing d'); + end + else + warning('myttest:IdenticalSamples',['myttest: data are too similar to be compared, try using' ... + ' ''abs'' on your data']); + t = zeros(1,nI); + p = ones(1,nI); + end + + otherwise + error('Unknown test') +end +if UseVarCorr + pvar = varcorr*pvar; +end + +t = (a1 - a2) ./ sqrt( pvar ./ n ) ; +p = betainc( df ./ (df + t.*t), df/2, 0.5) ; +pmap(I)=p; +tmap(I)=t; + +if nargout>3 + d = pmap.*NaN; + d(I) = (a1-a2)./sqrt(pvar); + sigma_d = sqrt(n/n1/n2 + d.^2/2/n); + if isequal(wtest,'paired') + warning('Paired variance used for computing Cohen''s d'); + end +end +if nargout>4 + g = d.*(1-3./(4*(n1+n2)-9)); +end +% reshape the output so that it matches the input dimensions +if length(s1)>2 + rsize = @(x)reshape(x,s1(2:end)); + pmap=rsize(pmap); + tmap=reshape(tmap,s1(2:end)); + if nargout>3 + d=reshape(d,s1(2:end)); + sigma_d = rsize(sigma_d); + end + if nargout>5 + g=reshape(g,s1(2:end)); + end +end +if nargout == 0 + figure + if numel(2)==1 + a2=a1.*0+a2; + end + if numel(a1)>1 + x=1:numel(a1); + else x=1:2 + end + barerrorbar(x, [a1(:) a2(:)]', sqrt([v1(:)/n1 v2(:)/n2])',0) + legend({'Mean' 'S.E.'}) +end diff --git a/stat/octave_anovan.m b/stat/octave_anovan.m new file mode 100644 index 0000000..2541ad3 --- /dev/null +++ b/stat/octave_anovan.m @@ -0,0 +1,366 @@ +% Perform a multi-way analysis of variance (ANOVA). The goal is to test +% whether the population means of data taken from {k} different +% groups are all equal. +% +% Data is a single vector {data} with groups specified by +% a corresponding matrix of group labels {grps}, where {grps} +% has the same number of rows as {data}. For example, if +% {data} = [1.1;1.2]; {grps}= [1,2,1; 1,5,2]; +% then data point 1.1 was measured under conditions 1,2,1 and +% data point 1.2 was measured under conditions 1,5,2. +% Note that groups do not need to be sequentially numbered. +% +% By default, a 'linear' model is used, computing the N main effects +% with no interactions. this may be modified by param 'model' +% +% p= anovan(data,groups, 'model', modeltype) +% - modeltype = 'linear': compute N main effects +% - modeltype = 'interaction': compute N effects and +% N*(N-1) two-factor interactions +% - modeltype = 'full': compute interactions at all levels +% +% Under the null of constant means, the statistic {f} follows an F +% distribution with {df_b} and {df_e} degrees of freedom. +% +% The p-value (1 minus the CDF of this distribution at {f}) is +% returned in {pval}. +% +% If no output argument is given, the standard one-way ANOVA table is +% printed. +% +% BUG: DFE is incorrect for modeltypes != full +% @end deftypefn +% Copyright (C) 2003-2005 Andy Adler +% +% Octave is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2, or (at your option) +% any later version. +% +% Octave is distributed in the hope that it will be useful, but +% WITHOUT ANY WARRANTY; without even the implied warranty of +% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +% General Public License for more details. +% +% You should have received a copy of the GNU General Public License +% along with Octave; see the file COPYING. If not, write to the Free +% Software Foundation, 59 Temple Place - Suite 330, Boston, MA +% 02111-1307, USA. +% Author: Andy Adler +% Based on code by: KH +% $Id: anovan.m,v 1.10 2005/05/30 13:04:41 adb014 Exp $ +% +% TESTING RESULTS: +% 1. ANOVA ACCURACY: www.itl.nist.gov/div898/strd/anova/anova.html +% Passes 'easy' test. Comes close on 'Average'. Fails 'Higher'. +% This could be fixed with higher precision arithmetic +% 2. Matlab anova2 test +% www.mathworks.com/access/helpdesk/help/toolbox/stats/anova2.html +% % From web site: +% popcorn= [ 5.5 4.5 3.5; 5.5 4.5 4.0; 6.0 4.0 3.0; +% 6.5 5.0 4.0; 7.0 5.5 5.0; 7.0 5.0 4.5]; +% % Define groups so reps = 3 +% groups = [ 1 1;1 2;1 3;1 1;1 2;1 3;1 1;1 2;1 3; +% 2 1;2 2;2 3;2 1;2 2;2 3;2 1;2 2;2 3 ]; +% anovan( vec(popcorn'), groups, 'model', 'full') +% % Results same as Matlab output +% 3. Matlab anovan test +% www.mathworks.com/access/helpdesk/help/toolbox/stats/anovan.html +% % From web site +% y = [52.7 57.5 45.9 44.5 53.0 57.0 45.9 44.0]'; +% g1 = [1 2 1 2 1 2 1 2]; +% g2 = {'hi';'hi';'lo';'lo';'hi';'hi';'lo';'lo'}; +% g3 = {'may'; 'may'; 'may'; 'may'; 'june'; 'june'; 'june'; 'june'}; +% anovan( y', [g1',g2',g3']) +% % Fails because we always do interactions + + +function [PVAL, FSTAT, DF_B, DFE] = anovan (data, grps, varargin) + +% if nargin <= 1 +% usage ('anovan (data, grps)'); +% end + +% test supplied parameters +modeltype= 'linear'; +for idx= 3:2:nargin + param= varargin{idx-2}; + value= varargin{idx-1}; + if strcmp(param, 'model') + modeltype= value; + % elseif strcmp(param % add other parameters here + else + error(sprintf('parameter %s is not supported', param)); + end +end + +if ~isvector (data) + error ('anova: for `anova (data, grps) data must be a vector'); +end + +nd = size (grps,1); % number of data points +nw = size (grps,2); % number of anova 'ways' +if (~ isvector (data) || (length(data) ~= nd)) + % error ('anova: grps must be a matrix of the same number of rows as data'); +end + +[g,grp_map] = relabel_groups (grps); +if strcmp(modeltype, 'linear') + max_interact = 1; +elseif strcmp(modeltype,'interaction') + max_interact = 2; +elseif strcmp(modeltype,'full') + max_interact = size(grps,1); +else + error(sprintf('modeltype %s is not supported', modeltype)); +end +ng = length(grp_map); +int_tbl = interact_tbl (nw, ng, max_interact ); +[gn, gs, gss] = raw_sums(data, g, ng, int_tbl); + +stats_tbl = int_tbl(2:size(int_tbl,1),:)>0; +nstats= size(stats_tbl,1); +stats= zeros( nstats+1, 5); % SS, DF, MS, F, p +for i= 1:nstats + [SS, DF, MS]= factor_sums( gn, gs, gss, stats_tbl(i,:), ng, nw); + stats(i,1:3)= [SS, DF, MS]; +end + +% The Mean squared error is the data - avg for each possible measurement +% This calculation doesn't work unless there is replication for all grps +% SSE= sum( gss(sel) ) - sum( gs(sel).^2 ./ gn(sel) ); +SST= gss(1) - gs(1)^2/gn(1); +SSE= SST - sum(stats(:,1)); + +% KND: Error with the following! +sel = select_pat( ones(1,nw), ng, nw); %incorrect for modeltypes != full +DFE= sum( (gn(sel)-1).*(gn(sel)>0) ); +MSE= SSE/DFE; +stats(nstats+1,1:3)= [SSE, DFE, MSE]; + +for i= 1:nstats + MS= stats(i,3); + DF= stats(i,2); + F= MS/MSE; + pval = 1 - f_cdf (F, DF, DFE); + stats(i,4:5)= [F, pval]; +end + +if nargout==0; + printout( stats, stats_tbl ); +else + PVAL= stats(1:nstats,5); + FSTAT=stats(1:nstats,4); + DF_B= stats(1:nstats,2); + DF_E= DFE; +end +return + + +% relabel groups to a mapping from 1 to ng +% Input +% grps input grouping +% Output +% g relabelled grouping +% grp_map map from output to input grouping +function [g,grp_map] = relabel_groups(grps) +grp_vec= vec(grps); +s= sort (grp_vec); +uniq = 1+[0;find(diff(s))]; +% mapping from new grps to old groups +grp_map = s(uniq); +% create new group g +ngroups= length(uniq); +g= zeros(size(grp_vec)); +for i = 1:ngroups + g( find( grp_vec== grp_map(i) ) ) = i; +end +g= reshape(g, size(grps)); +return + +% Create interaction table +% +% Input: +% nw number of 'ways' +% ng number of ANOVA groups +% max_interact maximum number of interactions to consider +% default is nw +function int_tbl =interact_tbl(nw, ng, max_interact) +combin= 2^nw; +inter_tbl= zeros( combin, nw); +idx= (0:combin-1)'; +for i=1:nw; + inter_tbl(:,i) = ( rem(idx,2^i) >= 2^(i-1) ); +end + +% find elements with more than max_interact 1's +idx = ( sum(inter_tbl',1) > max_interact ); +inter_tbl(idx,:) =[]; +combin= size(inter_tbl,1); % update value + +%scale inter_tbl +% use ng+1 to map combinations of groups to integers +% this would be lots easier with a hash data structure +int_tbl = inter_tbl .* (ones(combin,1) * (ng+1).^(0:nw-1) ); +return + +% Calculate sums for each combination +% +% Input: +% g relabelled grouping matrix +% ng number of ANOVA groups +% max_interact +% +% Output (virtual (ng+1)x(nw) matrices): +% gn number of data sums in each group +% gs sum of data in each group +% gss sumsqr of data in each group +function [gn, gs, gss] = raw_sums(data, g, ng, int_tbl); +nw= size(g,2); +ndata= size(g,1); +gn=zeros((ng+1)^nw, 1); +gs=zeros((ng+1)^nw, 1); +gss=zeros((ng+1)^nw, 1); +for i=1:ndata + % need offset by one for indexing + datapt= data(i); + idx = 1+ int_tbl*g(i,:)'; + gn(idx)=gn(idx)+1; + gs(idx)=gs(idx)+datapt; + gss(idx)=gss(idx)+datapt^2; +end +return + +% Calcualte the various factor sums +% Input: +% gn number of data sums in each group +% gs sum of data in each group +% gss sumsqr of data in each group +% select binary vector of factor for this 'way'? +% ng number of ANOVA groups +% nw number of ways + +function [SS,DF]= raw_factor_sums( gn, gs, gss, select, ng, nw); +sel= select_pat( select, ng, nw); +ss_raw= gs(sel).^2 ./ gn(sel); +SS= sum( ss_raw( ~isnan(ss_raw) )); +if length(find(select>0))==1 + DF= sum(gn(sel)>0)-1; +else + DF= 1; %this isn't the real DF, but needed to multiply +end +return + +function [SS, DF, MS]= factor_sums( gn, gs, gss, select, ng, nw); +SS=0; +DF=1; + +ff = find(select); +lff= length(ff); +% zero terms added, one term subtracted, two added, etc +for i= 0:2^lff-1 + remove= find( rem( floor( i * 2.^(-lff+1:0) ), 2) ); + sel1= select; + if ~isempty(remove) + sel1( ff( remove ) )=0; + end + [raw_sum,raw_df]= raw_factor_sums(gn,gs,gss,sel1,ng,nw); + + add_sub= (-1)^length(remove); + SS = SS + add_sub*raw_sum; + DF = DF*raw_df; +end + +MS= SS/DF; +return + +% Calcualte the various factor sums +% Input: +% select binary vector of factor for this 'way'? +% ng number of ANOVA groups +% nw number of ways +function sel= select_pat( select, ng, nw); +% if select(i) is zero, remove nonzeros +% if select(i) is zero, remove zero terms for i + +persistent field +%field=[]; + +if length(select) ~= nw; + error('length of select must be = nw'); +end +ng1= ng+1; + +if isempty(field) + % expand 0:(ng+1)^nw in base ng+1 + field= (0:(ng1)^nw-1)'* ng1.^(-nw+1:0); + field= rem( floor( field), ng1); + % select zero or non-zero elements + + %knd + field= (field>0); +end +%disp('selection pattern') %debug +sel= find( all( field == ones(ng1^nw,1)*select(:)', 2) ); + +return + + +function printout( stats, stats_tbl ); +nw= size( stats_tbl,2); +[jnk,order]= sort( sum(stats_tbl,2) ); + +fprintf('\n%d-way ANOVA Table (Factors A%s):\n\n', nw, ... + sprintf(',%c',('A')+(1:nw-1)) ); +fprintf('Source of Variation Sum Sqr df MeanSS Fval p-value\n'); +fprintf('*********************************************************************\n'); +fprintf('Error %10.2f %4d %10.2f\n', stats( size(stats,1),1:3)); + +for i= order(:)' + str= sprintf(' %c x',('A')+find(stats_tbl(i,:)>0)-1 ); + str= str(1:length(str)-2); % remove x + fprintf('Factor %15s %10.2f %4d %10.2f %7.3f %7.6f\n', ... + str, stats(i,:) ); +end +fprintf('\n'); +return + +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/14.shtml +data=[7 9 9 8 12 10 ... + 9 8 10 11 13 13 ... + 9 10 10 12 10 12]'; +grp = [1,1; 1,1; 1,2; 1,2; 1,3; 1,3; + 2,1; 2,1; 2,2; 2,2; 2,3; 2,3; + 3,1; 3,1; 3,2; 3,2; 3,3; 3,3]; +data=[7 9 9 8 12 10 9 8 ... + 9 8 10 11 13 13 10 11 ... + 9 10 10 12 10 12 10 12]'; +grp = [1,4; 1,4; 1,5; 1,5; 1,6; 1,6; 1,7; 1,7; + 2,4; 2,4; 2,5; 2,5; 2,6; 2,6; 2,7; 2,7; + 3,4; 3,4; 3,5; 3,5; 3,6; 3,6; 3,7; 3,7]; +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/9.shtml +data=[9.5 11.1 11.9 12.8 ... + 10.9 10.0 11.0 11.9 ... + 11.2 10.4 10.8 13.4]'; +grp= [1:4,1:4,1:4]'; +% Test Data from http://maths.sci.shu.ac.uk/distance/stats/13.shtml +data=[7.56 9.68 11.65 ... + 9.98 9.69 10.69 ... + 7.23 10.49 11.77 ... + 8.22 8.55 10.72 ... + 7.59 8.30 12.36]'; +grp = [1,1;1,2;1,3; + 2,1;2,2;2,3; + 3,1;3,2;3,3; + 4,1;4,2;4,3; + 5,1;5,2;5,3]; +% Test Data from www.mathworks.com/ +% access/helpdesk/help/toolbox/stats/linear10.shtml +data=[23 27 43 41 15 17 3 9 20 63 55 90]; +grp= [ 1 1 1 1 2 2 2 2 3 3 3 3; + 1 1 2 2 1 1 2 2 1 1 2 2]'; + + + +function [y]=vec(x) +y=x(:); diff --git a/stat/p_rep.m b/stat/p_rep.m new file mode 100644 index 0000000..dc11e97 --- /dev/null +++ b/stat/p_rep.m @@ -0,0 +1,54 @@ +function [prep prep2]= p_rep(p,tails) +%P_REP - Probability of re +% [prep prep2] = p_rep(p,tails) +% Computes prep, the probabilityy of replication according to Killeen +% prep2 is the approximation +% Example +% >> p_rep(ttest( +% +% References: Peter Killeen (2005) An alternative to null-hypothesis +% significance tests. Psychological Science, 16, 345-353. + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-10-28 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin==0 + p = (-4.5:.05:-.5); + % p = 10.^(p-.5).*(mod(2*p,2))+10.^(p+log10(.5)).*(1-mod(2*p,2)); + p = 10.^(p-.5); + plot(p,p_rep(p), 'LineWidth', 2, 'marker', 'none') + set(gca, 'XScale', 'log') + set(gca, 'Ygrid', 'on') + set(gca, 'XTick', [.0001 .001 .01 .1]) + set(gca, 'XTickLabel', get(gca, 'XTick')) + set(gca, 'Xgrid', 'on') + set(gca, 'XMinorGrid', 'off') + xlabel('p value') + ylabel('p_{rep}') + title('$\displaystyle p_{rep} = \left(1+\left(\frac{p}{1-p}\right)^{\frac{2}{3}}\right)^{-1}$','interpreter','latex') + axis square + set([gca get(gca, 'Title') get(gca, 'Xlabel') get(gca, 'Ylabel')], 'FontSize', 16) +end + +if nargin<2 + tails=1; +end +if not(isequal(tails, 1) || isequal(tails, 2)) + error('Tails should be 1 or 2') +end +p=p./tails; +prep=normcdf(norminv(1-(p))./2.^.5); +prep2=1./(1+(p./(1-p)).^(2/3)); +return + + +function p = normcdf(z) +p = 0.5 * erfc(-z ./ sqrt(2)); diff --git a/stat/permftest.m b/stat/permftest.m new file mode 100644 index 0000000..b09ca8b --- /dev/null +++ b/stat/permftest.m @@ -0,0 +1,404 @@ +function [pv,fx,F0,P,PS]=permftest(X,dimF,varargin) +% permftest - N-way permutation univariate test (within design only) +% [pv,F,fx,P,PS] = permktest(X,dimF,dimP,dimM,NP,TimeBar) +% +% Performs a permutation test with the data analoguous to +% a one-way ANOVA testing the hypothesis H0: +% All groups X1, X2, ... have the same mean +% +%MANDATORY INPUTS: +% X is [ SUBJECT x FACTOR1 x FACTOR2 [...] x MEASURE1 x [...] ] +% dimF: Dimensions of the factors (in the previous example, with 2 factors: [2 3] +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% dimM: Dimensions of data across which the maximum F-value is computed. +% E.g.Default is: all dimensions besides the "permuted" dimensions +% NP: Number of random permutations. (Default: 10000) +% TimeBar: if not 0, a progression time bar is displayed (default: 1) +%OUTPUTS: +% pv: (Approximate) p-values of the observed data, computed from the permutations +% fx: List of effects tested +% F: [ length(fx) x Ma x Mb...] Observed Fisher's discriminant values +% P: [NP x (N1+N2+...)] List of permutations used +% PS: [ P x Ma x Mb... ] Matrix of permutation statistics (may be quite big!) +% +% See also: permttest, permktest +% Author: Karim N'Diaye, on advice from Jacques Martinerie, CNRS UPR640 +% Created: Sep 2005 + + +% We have something like: +% X= [ X(1)11 X(2 + + +% X={X1 , ... Xi, ... Xn}: a cell array of [Ni x Ma x Mb...] data matrices. +% Alternatively: +% X can be a single data matrix. But the number of samples (ie subjects) +% in each condition should be set using 'grp' +% I.e. X = [ X1 ; X2 ; X3] +% grp = [ size(X1,1) size(X2,1) size(X3,1) ]; +% +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : within-subject permutations (used as default) +% Use -dim_p for unpaired samples/subjects +% dimM: Dimensions of data across which the maximum T-value is computed. +% Default is: all dimensions besides the "permuted" dimensions +% (typically: [2 3 ... ndims(X)]) +% NP: Number of random permutations. (Default: 10000) +% TimeBar: if not 0, a progression time bar is displayed (default: 1) +% + + +% [pv ... ] = permktest(X,grp,dimP,dimM,NP,TimeBar) + +NPERMS=9999; % Max. number of permutations (instead of 10000 to have nice p values after division by (NP+1)) +NMAX_GROUPS=36; % Max. number of groups : cf 'symbols' in dec2base +NMAX_SUBJECTS=1000; % Max number of subjects + +% Metrics to be used +% metrics='fisher discriminant'; +metrics='euclidian distance'; + +% Variables used in this script: +% dim_p : subject (ie. samples, observation) diemsion in the data X +% dim = abs(dim_p) +% dimF = factor dimensions in X (not their size) +% NL : number of levels for each factor, NL=size(X,dimF) +% N : number of obs in each cell (ie group) + + +%initialize parameters +% if iscell(X) +% nparams=nargin-1; +% params=varargin(1:nparams); +% else +% N=varargin{1}; +% end +nparams=nargin-2; +params=varargin(1:nparams); +if nparams<1 + dim_p=[]; +else + dim_p=params{1}; +end +if nparams<2, + dim_m=[]; +else, + dim_m=params{2}; +end +if nparams<3 + NP=[]; +else + NP=params{3}; +end +if nparams<4 + TimeBar=1; +else + TimeBar=params{4}; +end +if TimeBar %& 0 + try + htimer = timebar('Permutation Statistics','Progress...'); + catch + warning('Function timebar.m missing. Use waitbar instead') + htimer = waitbar(0,'Permutation Statistics'); + end +else + htimer = NaN; +end + +if isempty(dim_p) + if iscell(X) + dim=find(size(X{1})>1); + else + dim=find(size(X)>1); + end + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + dim=dim(1); + dim_p=dim; +end +dim=abs(dim_p); + +% We will reshape the data X so that groups and subjects make the first +% dimension of X. +% That is for a LETTER x NUMBER : +% X = [ A1 ; B1 ; ... ; A2 ; B2 ... ] +% N(i,j,k...) will keep track of the number of samples (ie. subjects) in each +% group: N(1,1)=size(A1) ; N(2,1)=size(B2) etc. + +% if iscell(X) +% Y=X;X=[]; +% ndX=ndims(Y{1}); +% dX1=setdiff(1:ndX,dim); % non permuted dims +% for i=1:length(Y) +% X=cat(1, X, permute(Y{i}, [dim dX1])); +% N(i)=size(Y{i},dim); +% Y{i}=[]; +% end +% else +ndX=ndims(X); +dX1=setdiff(1:ndX,[dim dimF]); +% Put subjects in the first dimension and factors in the following ones +X=permute(X, [dim dimF dX1]); +sX=size(X); +% Number of factors: +nf=length(dimF); +% Population in each cell: +N=sX(1)*ones(sX(dimF)); +NL=sX(dimF); % Number of level in each factor +NG=prod(NL); % Number of cells +NS=sum(N(:)); % Total Number of samples +if NS>NMAX_SUBJECTS + error('Too many subjects!') +end +if dim_p>0 & length(unique(N))>1 + error('Repeated measure design must have the same number of samples in each group') +end +if NG>NMAX_GROUPS + error('Too many groups!') +end + +% Default is to compute the maximum T value across all dimensions of the +% measurement data +if isempty(dim_m) + dim_m=setdiff(1:ndX,[dim dimF]); +end +dim_m=unique(dim_m(:))'; +if max(dim_m)>ndX + error('Wrong dimM dimensions!') +end +if ismember(dim_p,dim_m) + error(sprintf('Wrong dimM dimensions: [%d] is already set as the permuted dimension!\n' , dim)) +end +% Reindex dimensions in the new X configuration: +if ~isempty(dim_m) + dim_m=dim_m+(dim_m0 + % Paired case: + Nexh=factorial(NG)^(N(1))-1; +else + % Unpaired case: + n=cumprod(1:max(N(:))); % hand made factorial + Nexh=factorial(NS)/prod(n(N(:)))-1; +end + +% Set the number of perms to be computed +exhaustive=0; +if isempty(NP) + if Nexh <= NPERMS + NP=Nexh; + exhaustive=1; + else + NP=NPERMS; + exhaustive=0; + end +end + +if NP>Nexh + warning(sprintf('Cannot do %d permutations. For this dataset, the maximum is: %d.',NP, Nexh)); +elseif NP==Nexh; + exhaustive=1; +end + +% if NP>NPERMS +% warning(sprintf('Too many permutations! Only %d will be performed.',NPERMS)); +% NP = NPERMS; +% exhaustive=0; +% end + +% WARNING: +% Creating the exhaustive list of permutations is rather painful and +% quite uninteresteing as we may pretty often be well above 10'000 perms +% (e.g. 3 groups of 6 subjects lead to 46656 perms in a within design!) +% Therefore: +exhaustive=0; + +% List of permutations/randomizations +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + % Within subject perms: + % Would be: P1=flipud(fliplr(perms(1:NG))); + % Between subject perms: + % Something like: P=dec2basen(1:NP,NG,N(1))+1; + error('no exhaustive search available!') + else + % within-subject & between-groups random permutations: + [ignore,P]=sort(rand(NP,N(1),NG),3); + % so that, with: group=a, b,...n & subject=1,2,...N + % P(i,:)= [ a1,a2,...,aN b1,b2, ... nN ] + P=(P-1)*N(1)+repmat(reshape(repmat([1:N(1)]',[1,NG]),[1, N(1), NG]), [NP,1]); + end +else + % non-paired perms + if exhaustive % do all possible perms + error('no exhaustive search available!') + else % non exhaustive + [ignore,P]=sort(rand(NP,NS),2); + end +end + +% List of effects and interactions between factors +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=size(fx,1); + +% This works only for within design! +idx=reshape(1:NS,[N(1) NL]); + +% Now we make up the indices of each group in the first column of X +for i=1:nfx + % For each effect, we will test, we list all possible pairs of groups + % Examples: + % one factor with 3 levels(1,2,3): 1 vs 2, 1 vs 3, 2 vs 3 + % 2 factors, 3 by 2 interaction: A1/A2 A1/A3 A1/B1 A1/B2 A2/A3 ... B1/B2 + % + ngrps{i}=prod(NL(fx{i})); + %First, all pairs in a given effect (fx{i}) + pairs{i}=nchoosek(1:ngrps{i},2); + npairs=size(pairs{i},1); + for j=1:npairs + % In each pair, get the indices of the first group then those of + % the second + for k=1:2 + idx_pairs{i}{j,k}=subarray(idx, [{[] ; -1} [ num2cell(ind2sub2(NL(fx{i}),pairs{i}(j,k))); num2cell(fx{i}+1)]]); + end + end + for j=1:ngrps{i} + % Index of elements in each group + idx_grp{i}{j}=subarray(idx, [{[] ; -1} [ num2cell(ind2sub2(NL(fx{i}),j)); num2cell(fx{i}+1)]]); + end + +end +% +% for j=fx{i} % factor +% for k=1:NL(j) % level +% idx_group{i}{j,k}=[1:N(fx{i}(k))] +% end +% idx_pairs{j,k}=[1:N(pairs(j,k))]+sum([0 N([1:pairs(j,k)-1])]); +% end +% for j=1:NG +% % Index of elements in each group +% idx_grp{j}=[1:N(j)]+sum([0 N([1:j-1])]); % index of the group elements +% end + + +% +% PERMUTATION LOOP +% +for i=0:NP + + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:); + end + + % Generalized K-class Fisher's linear discriminant criterion : + % R. A. Fisher. The statistical utilization of multiple measurements. Ann. Eugen., 8:376-386, 1938. + % C. R. Rao. The utilization of multiple measurements in problems of biological classification. J. Roy. Stat. Soc. ser. B, 10:159-203, 1948. + + % Between group disparity + Z=zeros([nfx nsX]); + % Pooled variance: + K=zeros([nfx nsX]); + switch lower(metrics) + case 'fisher discriminant' + for ifx=1:nfx + npairs=size(pairs{ifx},1); + for j=1:npairs + Z(ifx,:)=Z(ifx,:)+abs(mean(Y(idx_pairs{ifx}{j,1},:)) - mean(Y(idx_pairs{ifx}{j,2},:))).^2; + end + Z(ifx,:)=Z(ifx,:)./npairs; + for j=1:ngrps{ifx} + % within-group variance (weighted with group size) + K(ifx,:)=K(ifx,:)+var(Y(idx_grp{ifx}{j},:),1)*N(j); + end + % Generalized Fisher's discriminant: + K(ifx,:)=Z(ifx,:)./K(ifx,:); + end + case 'euclidian distance' + [K,K]=myanova(permute(reshape(Y,sX),[dimF,1,(nf+2):ndX]),nf,1:nf); + end + + clear Z; % save some memory space + K=reshape(K,[nfx nsX]); + + if i==0 + F0=K; + sz=size(F0); + S=zeros(sz); + if nargout>3 + PS=zeros([NP sz(1) sz(3:end) 1]); + end + else + K=max(K,[],2); + if nargout>3 + PS(ifx, i,:)=K(:,:)'; + end + S=S+(repmat(K,[1 nsX(1)])>=abs(F0)); + if ishandle(htimer),try,if isequal(get(htimer, 'tag'), 'timebar'), timebar(htimer,i/NP),else,waitbar(i/NP,htimer);end;catch,end,end + end + clear K; +end +% Compute p-values +pv=(S+1)/(NP+1); +pv=reshape(pv, [nfx sX([dim_m setdiff(2:ndX,[dimF dim_m])]) 1]); +F0=reshape(F0, [nfx sX([dim_m setdiff(2:ndX,[dimF dim_m])]) 1]); +if ~isequal(dim_m, 0) + % permute back to put dimension across which the statistics maximum is + % computed at their original places + pv=ipermute(pv, [1 dim_m-nf setdiff(nf:ndX-nf, dim_m-nf)]); + F0=ipermute(F0, [1 dim_m-nf setdiff(nf:ndX-nf, dim_m-nf)]); +end +if nargout>3 + PS=reshape(PS, [NP nsX(2:end)]); +end +if ishandle(htimer),try,close(htimer),end,end +return + + +%% Validation using normally distributed random values: +% +% Simulate a design with 2 additive factor +% x=randn(100,4,2);x=x+cumsum(cumsum(ones(size(x)), 3),2)/10; +% +% Parametric 2 way ANOVA (indepentent samples) +% myanova(permute(x, [2 3 1 4 5]),2) +% +% [1]: 0.0013 +% [2]: 0.0009 +% [1x2]: 0.2255 +% +% anova2(permute(x, [2 3 1]), 2) give the same +% +% Repeated measures: +% myanova(permute(x, [2 3 1 4 5]),2,1:2) +% 0.0017 , 0.0017 , 0.2212 +% +% Permutation test yields: +% permftest(x, [2 3], -1, [],999) +% 0.0040 0.0020 0.0010 + + diff --git a/stat/permktest.m b/stat/permktest.m new file mode 100644 index 0000000..9b51a53 --- /dev/null +++ b/stat/permktest.m @@ -0,0 +1,308 @@ +function [pv,K0,P,PS]=permktest(X,varargin) +% permktest - One-way permutation univariate test +% [pv,K,P,PS] = permktest(X,dimP,dimM,NP,TimeBar) +% [pv ... ] = permktest(X,grp,dimP,dimM,NP,TimeBar) +% +% Performs a permutation test with the data analoguous to +% a one-way ANOVA testing the hypothesis H0: +% All groups X1, X2, ... have the same mean +% +%MANDATORY INPUTS: +% X={X1 , ... Xi, ... Xn}: a cell array of [Ni x Ma x Mb...] data matrices. +% Alternatively: +% X can be a single data matrix. But the number of samples (ie subjects) +% in each condition should be set using 'grp' +% I.e. X = [ X1 ; X2 ; X3] +% grp = [ size(X1,1) size(X2,1) size(X3,1) ]; +% +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : within-subject permutations (used as default) +% Use -dim_p for unpaired samples/subjects +% dimM: Dimensions of data across which the maximum T-value is computed. +% Default is: all dimensions besides the "permuted" dimensions +% (typically: [2 3 ... ndims(X)]) +% NP: Number of random permutations. (Default: 10000) +% TimeBar: if not 0, a progression time bar is displayed (default: 1) +% +%OUTPUTS: +% pv: (Approximate) p-values of the observed data, computed from the permutations +% K: [Ma x Mb...] Observed Fisher's discriminant values +% P: [NP x (N1+N2+...)] List of permutations used +% PS: [ P x Ma x Mb... ] Matrix of permutation statistics (may be quite big!) +% +% See also: permttest +% Author: Karim N'Diaye, on advice from Jacques Martinerie, CNRS UPR640 +% Created: Sep 2005 + +NPERMS=9999; % Max. number of permutations (instead of 10000 to have nice p values after division by (NP+1)) +NMAX_GROUPS=36; % Max. number of groups : cf 'symbols' in dec2base +NMAX_SUBJECTS=1000; % Max number of subjects + +%initialize parameters +if iscell(X) + nparams=nargin-1; + params=varargin(1:nparams); +else + N=varargin{1}; +end +if nparams<1 + dim_p=[]; +else + dim_p=params{1}; +end +if nparams<2, + dim_m=[]; +else, + dim_m=params{2}; +end +if nparams<3 + NP=[]; +else + NP=params{3}; +end +if nparams<4 + TimeBar=1; +else + TimeBar=params{4}; +end +if TimeBar + try + htimer = timebar('Permutation Statistics','Progress...'); + catch + warning('Function timebar.m missing. Use waitbar instead') + htimer = waitbar(0,'Permutation Statistics'); + end +else + htimer = NaN; +end + +if isempty(dim_p) + if iscell(X) + dim=find(size(X{1})>1); + else + dim=find(size(X)>1); + end + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + dim=dim(1); + dim_p=dim; +end +dim=abs(dim_p); + +% We will reshape the data X so that groups and subjects make the first +% dimension of X. +% That is: +% X = [ Grp1 ; Grp2 ; ... ] +% N will keep track of the number of samples (ie. subjects) in each +% group: N(i)=size(Grp(i),1) etc. +if iscell(X) + Y=X;X=[]; + ndX=ndims(Y{1}); + dX1=setdiff(1:ndX,dim); % non permuted dims + for i=1:length(Y) + X=cat(1, X, permute(Y{i}, [dim dX1])); + N(i)=size(Y{i},dim); + Y{i}=[]; + end +else + ndX=ndims(X); + dX1=setdiff(1:ndX,dim); + % Put subjects in the first dimension + X=permute(X, [dim grp dX1]); + N=size(X,1)*ones(size(X,2)); +end +sX=size(X); +if sum(N)>NMAX_SUBJECTS + error('Too many subjects!') +end +if dim_p>0 & length(unique(N))>1 + error('Repeated measure design must have the same number of samples in each group') +end +NS=sum(N); % Total Number of samples +NG=length(N); % Number of groups +if NG>NMAX_GROUPS + error('Too many groups!') +end + +% Default is to compute the maximum T value across all dimensions of the +% measurement data +if isempty(dim_m) + dim_m=setdiff(1:ndX,dim); +end +dim_m=unique(dim_m(:))'; +if max(dim_m)>ndX + error('Wrong dimM dimensions!') +end +if ismember(dim_p,dim_m) + error(sprintf('Wrong dimM dimensions: [%d] is already set as the permuted dimension!\n' , dim)) +end +dim_m=dim_m+(dim_m0); + +% Define a practical shape for the measurement data +% (so that the maximum across dimension(s) is easy to compute) +if dim_m==0 + nsX=[sX(2:end) 1]; +else + X=permute(X,[1 dim_m setdiff(2:ndX, dim_m)]); + nsX=[prod(sX(dim_m)) sX(setdiff(2:ndX, dim_m)) 1]; +end + +% Now compute the number of exhaustive permutations +if dim_p>0 + % Paired case: + Nexh=factorial(NG)^(N(1))-1; +else + % Unpaired case: + n=cumprod(1:max(N(:))); % hand made factorial + Nexh=factorial(NS)/prod(n(N(:)))-1; +end + +% Set the number of perms to be computed +exhaustive=0; +if isempty(NP) + if Nexh <= NPERMS + NP=Nexh; + exhaustive=1; + else + NP=NPERMS; + exhaustive=0; + end +end + +if NP>Nexh + warning(sprintf('Cannot do %d permutations. For this dataset, the maximum is: %d.',NP, Nexh)); +elseif NP==Nexh; + exhaustive=1; +end + +% if NP>NPERMS +% warning(sprintf('Too many permutations! Only %d will be performed.',NPERMS)); +% NP = NPERMS; +% exhaustive=0; +% end + +% WARNING: +% Creating the exhaustive list of permutations is rather painful and +% quite uninteresteing as we may pretty often be well above 10'000 perms +% (e.g. 3 groups of 6 subjects lead to 46656 perms in a within design!) +% Therefore: +exhaustive=0; + +% List of permutations/randomizations +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + % Within subject perms: + % Would be: P1=flipud(fliplr(perms(1:NG))); + % Between subject perms: + % Something like: P=dec2basen(1:NP,NG,N(1))+1; + error('no exhaustive search available!') + else + % within-subject & between-groups random permutations: + [ignore,P]=sort(rand(NP,N(1),NG),3); + % so that, with: group=a, b,...n & subject=1,2,...N + % P(i,:)= [ a1,a2,...,aN b1,b2, ... nN ] + P=(P-1)*N(1)+repmat(reshape(repmat([1:N(1)]',[1,NG]),[1, N(1), NG]), [NP,1]); + end +else + % non-paired perms + if exhaustive % do all possible perms + error('no exhaustive search available!') + else % non exhaustive + [ignore,P]=sort(rand(NP,NS),2); + end +end + +% List of pairwise comparisons between groups +pairs=nchoosek(1:NG,2); +npairs=size(pairs,1); +for j=1:npairs + for k=1:2 + idx_pairs{j,k}=[1:N(pairs(j,k))]+sum([0 N([1:pairs(j,k)-1])]); + end +end +for j=1:NG + % Index of elements in each group + idx_grp{j}=[1:N(j)]+sum([0 N([1:j-1])]); % index of the group elements +end +% +% PERMUTATION LOOP +% +for i=0:NP + + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:); + end + + % Generalized K-class Fisher's linear discriminant criterion : + % R. A. Fisher. The statistical utilization of multiple measurements. Ann. Eugen., 8:376-386, 1938. + % C. R. Rao. The utilization of multiple measurements in problems of biological classification. J. Roy. Stat. Soc. ser. B, 10:159-203, 1948. + + % Between group disparity + Z=zeros([1 nsX]); + for j=1:npairs + Z=Z+abs(mean(Y(idx_pairs{j,1},:)) - mean(Y(idx_pairs{j,2},:))).^2; + end + Z=Z./npairs; + % Pooled variance: + K=zeros([1 nsX]); + for j=1:NG + % within-group variance (weighted with group size) + K=K+var(Y(idx_grp{j},:),1)*N(j); + end + % Generalized Fisher's discriminant: + K=Z./K; + clear Z; % save some memory space + K=reshape(K,nsX); + + if i==0 + K0=K; + sz=size(K0); + S=zeros(sz); + if nargout>3 + PS=zeros([NP sz(2:end) 1]); + end + else + K=max(K,[],1); + if nargout>3 + PS(i,:)=K(:)'; + end + S=S+(repmat(K,[nsX(1) 1])>=abs(K0)); + if ishandle(htimer),try,if isequal(get(htimer, 'tag'), 'timebar'), timebar(htimer,i/NP),else,waitbar(i/NP,htimer);end;catch,end,end + end +end +% Compute p-values +pv=(S+1)/(NP+1); +if ~isequal(dim_m, 0) + pv=reshape(pv, [sX([dim_m setdiff(2:ndX,dim_m)]) 1]); + K0=reshape(K0, [sX([dim_m setdiff(2:ndX,dim_m)]) 1]); + pv=ipermute(pv, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); + K0=ipermute(K0, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); +else + pv=reshape(pv, [1 sX(2:end) 1]); + K0=reshape(K0, [1 sX(2:end) 1]); +end +if nargout>3 + PS=reshape(PS, [NP nsX(2:end)]); +end +if ishandle(htimer),try,close(htimer),end,end +return + + +% % Validated using normally distributed random values: +% +% X1=randn(50,1); +% [p,K,P,PS]=permftest({X1,X1,X1+.3},-1); +% % Gives (almost) equal p-values as: +% [pa,Fa]=myanova(cat(1,X1',X1',X1'+.3),1) +% +% % Unequal number of samples: +% X3=randn(25,1)+.3; +% [p,K,P,PS]=permftest({X1,X3},-1); +% anova(1,[X1;X3], [ones(50,1);2*ones(25,1);]) \ No newline at end of file diff --git a/stat/permtest/permtest.m b/stat/permtest/permtest.m new file mode 100644 index 0000000..637cc8b --- /dev/null +++ b/stat/permtest/permtest.m @@ -0,0 +1,401 @@ +function [pv,S0,NP,PS,P]=permtest(X,X2,statistic,dim_p,dim_m,NP,TimeBar,tails,varargin) +% permtest - Generic permutation/randomization test +% [pv,S0,NP,PS,P] = permtest(X1,X2,statistic,dim_p,dim_m,NP,TimeBar,tails,[testoptions]) +% [pv ... ] = permtest(X, N1,statistic,...) +% +% Performs a permutation test with the data +% +%MANDATORY INPUTS: +% X1,X2: [N1 x Ma x Mb...] and [ N2 x Ma x Mb x...] Multidimensional matrices +% of Ni samples/subjects for each group, eg. [ Subjects x Channel x Time ] +% Alternatively: +% X can be a single data matrix. But the number of samples (ie subjects) +% in the first group should be set using 'N1' +% I.e. X = [ X1 ; X2 ] & N1=size(X1,1)=nb of samples in group 1 +% +% statistic: Name of the statistic to use: +% 'meandiff' (mean difference) +% 'tvalue' (Student's t-value) +% 'pseudotvalue' (tvalue with smoothed variance) +% 'signtest' +% 'wilcoxon' (aka. signed ranks) +% 'edist'(euclidian distance, on dimension dim_m) +% +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : paired permutations (default) +% Use negative dim_p for unpaired samples/subjects +% dimM: Dimensions of data across which the maximum T-value is computed. +% For multidimensional data, eg. [ Subject x Channel x Time ], +% control of Family-wise Error Rate requires to compute T-value +% across all dimensions (starting after the permuted one. +% Default is: all dimensions besides the "permuted" dimensions +% (typically: [2 3 ... ndims(X)]) +% NP: Number of permutations (may be reduced if bigger than the number of permutations, +% for example if NP > 2^N-1 using paired data) +% If not specify, permttest uses 10000 (at most). +% Set NP=inf so to enforce exhaustive permutations, ie. all possible permutations +% (this may lead to HUGE numbers of permutations, avoid with unpaired tests) +% TimeBar: 1 (default) or 0. To display a progress bar. +% tails: 1- (one: X1>X2) or 2- (two: X1X2) tailed test (default: 2) +% testoptions: List of parameters required for the chosen test +% 'ttest'|'mann-whitney'|'wilcoxon': testoptions={}; +% 'pseudottest': testoptions{1}=smooting kernel +% 'edist': testoptions={} +% +%OUTPUTS: +% pv: p-values of the observed data, computed from the permutations +% (dimensions subjects and dim_m are squeezed). This is a fairly good +% approximation of the parametric test when data are normally +% distributed. But it is still valid when they are not! +% S0: [Ma x Mb...] Observed values of the statistic +% NP: Number of permutations actually performed +% PS: [P x Ma x Mb... ] Matrix of permutation statistics (may be quite big!) +% P: [NP x (N1+N2)] List of permutations used +% +% References: +% On euclidian distance: Greenblatt, Brain Topography, 2004 +% +% Authors: +% K² Team, aka. K. N'Diaye (kndiaye01yahoo.fr> & K. Jerbi (jerbichups.jussieu.fr) +% CNRS UPR640, Lab. d'imagerie cérébrale et neurosciences cognitives +% Hopital de la Salpetriere, Paris, France +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% K² 2006-02-02 Creation +% KND 2006-02-14 Added euclidian distance test ('edist') +% KND 2010-11-12 May now use function handle +% ----------------------------- Script History --------------------------------- + +NMAX_UNPAIRED=15; % maximum number of observations for exhaustive search for unpaired samples +NMAX_PAIRED=30; % maximum number of observations for exhaustive search in paired samples +NMAX_SUBJECTS=1000; % Max number of subjects +NPERMS=9999; % Default number of permutations +STATISTICS={'tvalue','meandiff','tvaluesmoothed','signtest','wilcoxon','edist'}; +PAIREDSTAT={'wilcoxon', 'mann-whitney', 'signtest', 'plusminus'}; +%Note for authors: +% 'mann-whitney' : check code below before making it available to user +% 'plusminus' : should be ok +% 'plusminus' (sum of X1>X2 along dim_m) + +%initialize parameters +if nargin<3 + error('Test Statistic need to be specified (e.g. ''meandiff'' or ''tvalue'')!') +end +testargs ={}; +if (iscell(statistic)) + testargs = statistic{2:end}; + statistic=statistic{1}; +end +if isa(statistic, 'function_handle') + testfun = statistic; + statistic = 'fun'; +elseif not(ismember(statistic, STATISTICS)) + error('Wrong type of test! Possible test statistics are:\n%s\n', sprintf('%s ', STATISTICS{:})) +end +if nargin<4 + dim_p=[]; +end +if nargin<5 + dim_m=[]; +end +if nargin<6 + NP=[]; +end +if nargin<7 + TimeBar=1; % KJ, default is off now... +end +if nargin<8 + tails=2; +end +if ~isequal(tails,1) && ~isequal(tails,2) && ~isequal(tails,-1) + error('Tails can be 1 or 2') +end + +%% Checking dimensions +% +if isempty(dim_p) + dim=find(size(X)>1,1); + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + %dim=dim(1); + if ndims(X2)>=dim + if size(X,dim) ~= size(X2,dim) + dim=-dim; + end + end + dim_p=dim; +end +dim=abs(dim_p); +options=varargin; +if dim_p<0 && ~isempty(strmatch(statistic, PAIREDSTAT)) + error('Unpaired data not supported for %s statistics, are you still a Student? LOL',statistic) +end + + +%% RESHAPING ORIGINAL DATA +% +% Data in X (and possibly in X2) will be concatenated (if needed) and +% reshaped so that following computations are made easier. +% Resulting size of X will be: [ (N1+N2) "dim_m"(1) "dim_m"(2) (...) ] +% i.e - subjects are put in the first dimension, group 1 above group 2 +% - data from the dimension(s) dim_m are put as the second, third... dimension of X +% - additional dimensions (tested separately, ie univariately) follow +% +ndX=ndims(X); +dX1=setdiff(1:ndX,dim); +sX1=[size(X) 1 1]; +% Put subjects in the first dimension +X=permute(X, [dim dX1]); +sX=[size(X) ones(1,ndX)]; +if numel(X2)>1 % X2 is a matrix + X2=permute(X2, [dim dX1]); + sX2=[size(X2) ones(1,ndX)]; + if ~isequal(sX(2:end), sX2(2:end)) + error('X1 and X2 should be of the same size in the non-permuted dimensions!') + end + X=cat(1,X,X2); + N=[sX(1) sX2(1)]; + clear sX2; +elseif numel(X2)==1 % X2 is the number of samples in the first group + N=[X2 sX(1)-X2]; +else + error('Check inputs!') +end +clear X2; +X=double(X); +if sum(N)>NMAX_SUBJECTS + error('Too many subjects!') +end +if dim_p>0 && N(1) ~= N(2) + error('Paired data should have the same number of samples!') +end + +%% SETTING dim_m VARIABLE & SHAPE OF X ALONG IT +% +% Default is to compute the maximum T value across all dimensions of the +% measurement data (dim_m). +if isempty(dim_m) + dim_m=setdiff(1:ndX,dim); +end +dim_m=unique(dim_m(:))'; +if any(dim_m>ndX) + error('Wrong dimM dimensions!') +end +if any(ismember(dim_p,dim_m)) + error(sprintf('Wrong dimM dimensions: [%d] is already set as the permuted dimension!\n' , dim)) +end +dim_m1=dim_m; +dim_m=dim_m+(dim_m0); + +%% PUT DATA INTO A SINGLE ARRAY FOR EFFICENCY +% Define a practical shape for the measurement data (all dim_m dimensions +% as a single vector) so that the maximum across dimension is easy to +% compute +if dim_m==0 + nsX=[1 sX(2:end)]; +elseif ndX==2 + nsX=[1 sX(2:end)]; +else + X=permute(X,[1 dim_m setdiff(2:ndX, dim_m)]); + nsX=[prod(sX(dim_m)) sX(setdiff(2:ndX, dim_m)) 1]; + X=reshape(X,[size(X,1) nsX]); +end + + +%% NUMBER OF PERMUTATIONS +% +% Now compute the number of exhaustive permutations +if dim_p>0 + if tails==2 + % We compute only one half of the permutations for paired samples + Nexh=2^(N(1)-1)-1; + else + Nexh=2^(N(1))-1; + end +else + Nexh=factorial(N(1)+N(2))/(factorial(N(1))*factorial(N(2)))-1; +end + +exhaustive=0; +if isempty(NP) + if (dim_p>0 && (N(1)+N(2))0 + msg=[ msg ' paired']; + end + warning(sprintf([ 'You are under-sampling (with %d permutations)!\nFor this dataset (with %s subjects),'... + 'the possible number of permutations is: %d.'],NP,msg,Nexh)); + end + elseif isequal(NP, inf) + if TimeBar + disp(sprintf('You have requested exhaustive permutations: %d.',Nexh)); + end + NP=Nexh; + exhaustive=1; + elseif NP>Nexh + if TimeBar + msg=sprintf('%d', N(1)); + if dim_p>0 + msg=[ msg ' paired']; + end + warning(sprintf([ 'You are over-sampling (with %d permutations)!\nFor this dataset (with %s subjects),'... + 'the maximum number of permutations is: %d.'],NP,msg,Nexh)); + end + elseif NP==Nexh; + exhaustive=1; + else + if NP>NPERMS + if TimeBar + warning(sprintf('So many permutations to be done (%d) may take a long time!',NP)); + end + end + end +end + + +%% LIST OF PERMUTAIONS +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + P=49==(dec2bin(1:NP,N(1))); + else + % non exhaustive + P=round(rand(NP,N(1))); + end + P=[P 1-P].*N(1)+repmat(1:N(1), [NP,2]); +else + % non-paired perms + if exhaustive % do all possible perms + p=nchoosek(1:(N(1)+N(2)),N(1)); + p(1,:)=[]; % the 1st is not a permutation + for i=1:NP + P(i,:)=[p(i,:) setdiff(1:(N(1)+N(2)),p(i,:))]; + end + clear p + else % non exhaustive + [ignore,P]=sort(rand(NP,N(1)+N(2)),2); + end +end + +%% DISPLAY TIMEBAR +if TimeBar + try + htimer = timebar('Permutation Statistics','Progress...'); + catch + warning('Function timebar.m missing. waitbar.m is used instead') + htimer = waitbar(0,'Permutation Statistics'); + end +else + htimer = NaN; +end + +%% PERMUTATION LOOP +for i=0:NP + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:,:); + end + + switch(statistic) + case 'tvalue' + Z=tvalue(Y(1:N(1),:),Y(N(1)+(1:N(2)),:)); + case 'meandiff' + Z=sum(Y(1:N(1),:),1)./N(1)-sum(Y(N(1)+(1:N(2)),:),1)./N(2); %this is to use difference of mean instead of T-statistic (KJ) + case 'pseudotvalue' + Z=pseudotvalue(Y(1:N(1),:),Y(N(1)+(1:N(2)),:),options{1}); + case 'signtest' + Z=sign(Y(1:N(1),:)-Y(N(1)+(1:N(2)),:)); + Z=sum(Z,1).^2./sum(abs(Z),1); + case 'wilcoxon' + Z=Y(1:N(1),:)-Y(N(1)+(1:N(2)),:); + Z=sign(Z).*tiedrank(abs(Z),1); + Z=sum(Z(:,:),1); + % case 'mann-whitney' + % Z=tiedrank(Y(:,:),1); + % Z=sum(Z(1:N(1),:),1); + case 'edist' + if i==0 + nsX(1)=1; + sX1(dim_m)=[]; + dim=dim-sum(dim_m1Y(N(1)+(1:N(2)),:),1); + case 'fun' + Z=feval(testfun,Y(1:N(1),:),Y(N(1)+(1:N(2)),:),testargs{:}); + end + Z=reshape(Z,nsX); + if tails==2 + Z=abs(Z); + end + if i==0 + S0=Z; + sz=size(S0); + S=zeros(sz); + if nargout>3 + %pack; + PS=zeros([NP sz(2:end) 1],'single'); + end + else + Z=max(Z,[],1); + if nargout>3 + PS(i,:)=Z(:)'; + end + S=S+(repmat(Z,[nsX(1) 1])>=S0); + if TimeBar,try if isequal(get(htimer,'tag'),'timebar'),timebar(htimer,i/NP),else waitbar(i/NP,htimer);end;catch,TimeBar=0;end,end + end +end + +%% COMPUTE RESULTING P-VALUES +pv=(S+1)./(NP+1); + +%% PROCESSING OUTPUTS +if ndX>2 + % Put back the dim_m dimension at their original place + if ~isequal(dim_m, 0) + pv=ipermute(pv, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); + S0=ipermute(S0, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); + end +end +if dim>1 || ndX>2 + sX1(dim)=[]; + pv=reshape(pv, sX1); + S0=reshape(S0, sX1); +end +if nargout>3 + PS=reshape(PS, [NP nsX(2:end)]); +end +try,if ishandle(htimer),close(htimer),end,drawnow;end +return + + +%% Validation: +X1=randn(100,1); +X=X1+0.2+randn(size(X1)); +% Paired case: +[p,K,P,PS]=permttest(X1,X,1,[],999,0);p +myttest(X1,X,1,'pttest') +% Unpaired (unequal variance) +[p,K,P,PS]=permttest(X1,X,-1,[],999,0);p +myttest(X1,X,1,'uttest') \ No newline at end of file diff --git a/stat/permtest/permtest_cluster.m b/stat/permtest/permtest_cluster.m new file mode 100644 index 0000000..8bf1e78 --- /dev/null +++ b/stat/permtest/permtest_cluster.m @@ -0,0 +1,119 @@ +function [clusters,pvclusters,pv,S,P,PS]=permtest_cluster(X1,X2,testname,vc,threshold,dims,NP,tails,st,TimeBar,varargin) +%permtest_cluster - Cluster-level permutation test +% [clusters,pvclusters,pv,S] = permtest_cluster(X1,X2,testname,vc,threshold,dims,st,NP,TimeBar,tails,testoptions) +% Performs two-pass permutation test for cluster-level inference +% On the firts pass, an uncorrected permutation test is performed on +% data. From this, the cluster-level significance level is assessed +% using connectivity information provided. +% +% MANDATORY INPUTS: +% X1,X2: 2D-data [Subjects x Measures] or [Measures x Subjects] (see permtest) +% testname: Name of the test used at the first level +% 'ttest'|'diff'|'pseudottest'|'mann-whitney'|'wilcoxon' +% OPTIONAL INPUTS: +% dimP: permuted dimension (default: 1. see permtest) +% vc: connectivity (if vc==1, assumed continuous, eg. time) +% threshold: primary threshold on uncorrected alpha significance +% default: 0.05 +% st: choice of the statistics: +% - 'probmass' (default): probability mass +% - { 'area' AREA} : area of the cluster. AREA should be a +% vector of areas associated to each vertices +% - 'size': number of vertices +% NP: number of permutations (default:see permtest) +% TimeBar: display TimeBar (default:see permtest) +% tails: 1 or 2-tail testing (default: 2) +% testoptions: parameters used by the chosen test +% (e.g. smoothing kernel for pseudottest) +% OUTPUTS: +% clusters: cell array of clusters +% pvcluster: p-value as approximated by permutations on clusters +% pv: uncorrected p-values at each measure point +% S: observed statistics in the data +% +% Example +% >> [c,pc]=permtest_cluster(x1,x2,'peusodttest',1,mni.vertconn,... +% 0.05,'pmass',9999,1,mni.smooth.W) +% +% See also: permtest, permtest_norm + +% Author: Th K&K Team. (kndiaye01yahoo.fr & jerbichups.jussieu.fr) +% Copyright (C) 2006 +% This program isfree software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% K&K 2006-01-05 Creation +% KND 2006-02-01 'area' option +% ----------------------------- Script History --------------------------------- + +if ndims(squeeze(X1))>2 + error('Cannot deal with multiple dimensions') +end + +if ~exist('dimP','var') + dimP=[]; +end +if ~exist('vc','var') + vc=[]; +end +if ~isequal(vc,1) && (~iscell(vc) || size(vc,1)~=size(vc,1)) && ~isempty(vc) + error('Connectivity Information provided through ''vc'' is of wrong type'); +end +if ~exist('dimM','var') + if iscell(vc) + dimM=find(size(X1)==length(vc)); + else + [ignore,dimM]=max(size(X1)); + end + fprintf('Clustering on dimension: %d\n', dimM); +end +if ~exist('threshold','var') + threshold=0.05; +end +if ~exist('st','var') + st='pmass'; +end +if ~exist('NP','var') + NP=[]; +end +if ~exist('TimeBar','var') + TimeBar=1; +end +if ~exist('tails','var') + tails=2; +end +if ~ismember(st{1}, { 'probmass' 'area' 'size' }) + error('Wrong cluster-level statistic!') +end + + +[pv,S,NP,P,PS] = permtest(X1,X2,testname,dimP,0,NP,TimeBar,tails,varargin{:}); +if nargout<5 + clear P; +end +PS=squeeze(PS); +pv=squeeze(pv); +T_thd=quantile(PS,1-threshold); +if tails==2 + TT=abs(S); +else + TT=S; +end + +if ischar(st) + st={st}; +end + +switch(st{1}) + case 'probmass' + [clusters,pvclusters]=prob_clusters(TT(:).*(TT(:)>=T_thd(:)),PS.*(PS>=repmat(T_thd(:)',NP,1)),vc,TimeBar); + case 'area' + [clusters,pvclusters]=prob_clusters(st{2}(:).*(TT(:)>=T_thd(:)),repmat(st{2}(:)',NP,1).*(PS>=repmat(T_thd(:)',NP,1)),vc,TimeBar); + case 'size' + [clusters,pvclusters]=prob_clusters(TT(:)>=T_thd(:),PS>=repmat(T_thd(:)',NP,1),vc,TimeBar); +end +return +%[FaceNormal, FaceArea, FaceCenter, VertexNormal, VertexArea, SuspectFace, NumFacesEachVertex, Duplicated_Faces, Not_Twice_Faces] = tessellation_stats( diff --git a/stat/permttest.m b/stat/permttest.m new file mode 100644 index 0000000..4859b51 --- /dev/null +++ b/stat/permttest.m @@ -0,0 +1,320 @@ +function [pv,S0,P,PS]=permttest(X,X2,dim_p,dim_m,NP,TimeBar,tails) +% permttest - Two-sided permutation pseudo T-test +% [pv,T,P,PS] = permtest2(X1,X2,dimP,dimM,NP,TimeBar,tails) +% [pv ... ] = permtest2(X ,N1,dimP,...) +% +% Performs a two-sided permutation pseudo T-test with the data, testing +% the following HO hypothesis: +% mean(X1) = mean(X2) +% +%MANDATORY INPUTS: +% X1,X2: [N1 x Ma x Mb...] and [ N2 x Ma x Mb x...] Multidimensional matrices +% of Ni samples/subjects for each group, eg. [ Subjects x Channel x Time ] +% Alternatively: +% X can be a single data matrix. But the number of samples (ie subjects) +% in the first group should be set using 'N1' +% I.e. X = [ X1 ; X2 ] & N1=size(X1,1) +% If N1<0 , define the dimension of the two samples +% +%OPTIONAL INPUTS (use [] for default values): +% dimP: Permuted dimensions (ie. subjects). Default: first non singleton +% If dim_p > 0 : paired permutations (default) +% Use negative dim_p for unpaired samples/subjects +% dimM: Dimensions of data across which the maximum T-value is computed. +% For multidimensional data, eg. [ Subject x Channel x Time ], +% control of Family-wise Error Rate requires to compute T-value +% across all dimensions (starting after the permuted one. +% Default is: all dimensions besides the "permuted" dimensions +% (typically: [2 3 ... ndims(X)]) +% NP: Number of permutations (may be reduced if bigger than the number of permutations, +% for example if NP > 2^N-1 using paired data) +% If not specify, permttest uses 10000 (at most). +% Set NP=inf so to enforce exhaustive permutations, ie. all possible permutations +% (this may lead to HUGE numbers of permutations, avoid with unpaired tests) +% TimeBar: 1 (default) or 0. To display a progress bar. +% tails: 1- (one: X1>X2) or 2- (two: X1X2) tailed test (default: 2) +% +%OUTPUTS: +% pv: (Approximate) p-values of the observed data, computed from the permutations +% T: [Ma x Mb...] Observed pseudo T-values +% P: [NP x (N1+N2)] List of permutations used +% PS: [P x Ma x Mb... ] Matrix of permutation statistics (may be quite big!) +% +% Author: Karim N'Diaye, CNRS UPR640 +% Created: Sep 2005 + +% NOT YET: + +% P-value normalization: +% To normalize distribution on a given dimension, use negative +% values in dimM. E.g. to normalize across space: dimM=[1 -2] or [ 1 2 -2] +% (order/repetition has no importance) +% See: Pantazis et al., NeuroImage, 2005 +% +% tails: 1 for one-sided [ X1>X2 ] +% 2 (default) two-sided test [ X1X2 ] +% ftest: function applied on data. +% Default is 'maxabst', i.e. compute the maximum (two-tailed) T-value +% fparams: cell array indicating the parameters passed to the function +% when called + +NMAX_UNPAIRED=15; % maximum number of observations for exhaustive search for unpaired samples +NMAX_PAIRED=30; % maximum number of observations for exhaustive search in paired samples +NMAX_SUBJECTS=1000; % Max number of subjects +NPERMS=9999; % Default number of permutations + +%initialize parameters +if nargin<3 + dim_p=[]; +end +if nargin<4 + dim_m=[]; +end +if nargin<5 + NP=[]; +end +if nargin<6 + TimeBar=1; % KJ, default is off now... +end +if nargin<7 + tails=[]; +end + +if isempty(tails) + tails=2; +end +if ~isequal(tails,1) && ~isequal(tails,2) + error('Tails can be 1 or 2') +end + +if isempty(dim_p) + dim=find(size(X)>1); + if isempty(dim) + error('Input X has only singleton or null dimensions!') + end + dim=dim(1); + dim_p=dim; +end +dim=abs(dim_p); + +% ORIGINAL OBSERVATIONS +% Data in X (and possibly in X2) will be concatenated (if needed) and +% reshaped so that folowing computations are made easier. +ndX=ndims(X); +dX1=setdiff(1:ndX,dim); +sX0=size(X); +% Put subjects in the first dimension +X=permute(X, [dim dX1]); +sX=size(X); +if numel(X2)>1 % X2 is a matrix + X2=permute(X2, [dim dX1]); + sX2=size(X2); + if ~isequal(sX(2:end), sX2(2:end)) + error('X1 and X2 should be of the same size in the non-permuted dimensions!') + end + if dim_p>0 & sX(1) ~= sX2(1) + error('X1 and X2 should have the same number of observations/subjects for paired data!') + end + X=cat(1,X,X2); + N=[sX(1) sX2(1)]; + clear sX2; +elseif numel(X2)==1 + if X2>0 + % X2 is the number of samples in the first group + N=[X2 sX0(1)-X2]; + elseif sX0(-X2)==2 + % X2 is the dimension defining the two samples + pX2=1:ndims(X); + pX2(-X2+(-X2NMAX_SUBJECTS + error('Too many subjects!') +end + +% Default is to compute the maximum T value across all dimensions of the +% measurement data +if isempty(dim_m) + dim_m=setdiff(1:ndX,dim); +end +dim_m=unique(dim_m(:))'; +if max(dim_m)>ndX + error('Wrong dimM dimensions!') +end +if ismember(dim_p,dim_m) + error(sprintf('Wrong dimM dimensions: [%d] is already set as the permuted dimension!\n' , dim)) +end +dim_m=dim_m+(dim_m0); + +% Define a practical shape for the measurement data +% (so that the maximum across dimension is easy to compute) +if dim_m==0 + nsX=[1 sX(2:end)]; +else + X=permute(X,[1 dim_m setdiff(2:ndX, dim_m)]); + nsX=[prod(sX(dim_m)) sX(setdiff(2:ndX, dim_m)) 1]; +end + +% Now compute the number of exhaustive permutations +if dim_p>0 + if tails==2 + % We compute only one half of the permutations for paired samples + Nexh=2^(N(1)-1)-1; + else + Nexh=2^(N(1))-1; + end +else + Nexh=factorial(N(1)+N(2))/(factorial(N(1))*factorial(N(2)))-1; +end + +exhaustive=0; +if isempty(NP) + if (dim_p>0 && (N(1)+N(2))Nexh + if TimeBar + warning(sprintf('You are over-sampling! For this dataset, the maximum number of permutations is: %d.',Nexh)); + end + elseif NP==Nexh; + exhaustive=1; + end +end +% if NP>NPERMS +% warning(sprintf('Too many permutations! Only %d will be performed.',NPERMS)); +% NP = NPERMS; +% exhaustive=0; +% end +% DEBUG: +% NP = min(500,NP); + + +% List of permutations +if dim_p>0 + % paired permutations + if exhaustive + % compute exhaustive list of perms + P=49==(dec2bin(1:NP,N(1))); + else + % non exhaustive + P=round(rand(NP,N(1))); + end + P=[P 1-P].*N(1)+repmat(1:N(1), [NP,2]); +else + % non-paired perms + if exhaustive % do all possible perms + p=nchoosek(1:(N(1)+N(2)),N(1)); + p(1,:)=[]; % the 1st is not a permutation + for i=1:NP + P(i,:)=[p(i,:) setdiff(1:(N(1)+N(2)),p(i,:))]; + end + clear p + else % non exhaustive + [ignore,P]=sort(rand(NP,N(1)+N(2)),2); + end +end + +if TimeBar + try + htimer = timebar('Permutation Statistics','Progress...'); + catch + warning('Function timebar.m missing. waitbar.m is used instead') + htimer = waitbar(0,'Permutation Statistics'); end +else + htimer = NaN; +end + +% PERMUTATION LOOP +for i=0:NP + if i==0 + % At the 0-th permutation, evaluate original data + Y=X; + else + Y=X(P(i,:),:); + end + +% Z=mean(Y(1:N(1),:),1)-mean(Y(N(1)+(1:N(2)),:),1); +% Z= Z ./ sqrt( std(Y(1:N(1),:),[],1).^2/N(1) + std(Y(N(1)+(1:N(2)),:),[],1).^2/N(2)); + Z=tvalue(Y(1:N(1),:),Y(N(1)+(1:N(2)),:)); + Z=reshape(Z,nsX); + + if i==0 + S0=Z; + sz=size(S0); + S=zeros(sz); + if nargout>3 + pack; + PS=zeros([NP sz(2:end) 1],'single'); + end + else + if tails==2 + Z=abs(Z); + end + Z=max(Z,[],1); + if nargout>3 + PS(i,:)=Z(:)'; + end + if tails==2 + S=S+(repmat(Z,[nsX(1) 1])>=abs(S0)); + else + S=S+(repmat(Z,[nsX(1) 1])>=S0); + end + if ishandle(htimer),try,if isequal(get(htimer, 'tag'), 'timebar'), timebar(htimer,i/NP),else,waitbar(i/NP,htimer);end;catch,end,end + end +end + +% Compute p-values +pv=(S+1)/(NP+1); +if ~isequal(dim_m, 0) + pv=reshape(pv, [sX([dim_m setdiff(2:ndX,dim_m)]) 1]); + S0=reshape(S0, [sX([dim_m setdiff(2:ndX,dim_m)]) 1]); + if ndX>2 + pv=ipermute(pv, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); + S0=ipermute(S0, [dim_m-1 setdiff(1:ndX-1, dim_m-1)]); + end +else + pv=reshape(pv, [sX(2:end) 1]); + S0=reshape(S0, [sX(2:end) 1]); +end +if nargout>3 + PS=reshape(PS, [NP nsX(2:end)]); +end +if ishandle(htimer),try,close(htimer),end,end +return + + +% Validation: +X1=randn(100,1); +X=X1+0.2+randn(size(X1)); +% Paired case: +[p,K,P,PS]=permttest(X1,X,1,[],999,0);p +myttest(X1,X,1,'pttest') +% Unpaired (unequal variance) +[p,K,P,PS]=permttest(X1,X,-1,[],999,0);p +myttest(X1,X,1,'uttest') \ No newline at end of file diff --git a/stat/permttest_cluster.m b/stat/permttest_cluster.m new file mode 100644 index 0000000..c0a13bf --- /dev/null +++ b/stat/permttest_cluster.m @@ -0,0 +1,246 @@ +function [clusters,pvclusters,pv,S,T,P,PS,S_sort]=permttest_cluster(X1,X2,dimP,dimM,vc,threshold,st,NP,TimeBar,tails) +%permttest_cluster - Cluster-level permutation test +% [clusters,pvclusters] = permttest_cluster(X1,X2,dimP,dimM,vcM,NP,threshold,TimeBar,tails,st) +% Performs two-pass permutation test for cluster-level inference +% On the firts pass, an uncorrected permutation test is performed on +% data. From this, the cluster-level assessment is performed using +% connectivity information provided. +% The choice of the cluster statistics 'mass' +% MANDATORY INPUTS: +% X1,X2: data (see permttest) +% OPTIONAL INPUTS: +% dimP: permuted dimension (default: see permttest) +% dimM: dimension used for clustering (typically: vertices or time) +% vc: connectivity (if vc==1, assumed continuous, eg. time) +% threshold: primary threshold on uncorrected alpha significance +% default: 0.05 +% st: choice of the statistics: 'mass' (default) or 'size'. +% NP: number of permutations (default:see permttest) +% TimeBar: display TimeBar (default:see permttest) +% tails: 1 or 2-tail testing (default: 2) +% OUTPUTS: +% clusters: cell array of clusters +% pvcluster: p-value as approximated by permutations +% +% Example +% >> [c,pc]=permttest_cluster(x1,x2,1 +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program isfree software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-05 Creation +% +% ----------------------------- Script History --------------------------------- + +if ndims(X1)>2 + error('Cannot deal with multiple dimensions') +end + +if ~exist('dimP','var') + dimP=[]; +end +if ~isempty(dimP) & ~isequal(abs(dimP),1) + error('Data matrices X1 and X2 should be: [Subjects]x[Vertices]x[Time Samples]') +end +if ~exist('vc','var') + vc=[]; +end +if ~isempty('vc') + vc=1; +end +if ~exist('dimM','var') + if iscell(vc) + dimM=find(size(X1)==length(vc)); + else + [ignore,dimM]=max(size(X1)); + end + fprintf('Clustering on dimension: %d\n', dimM); +end +if ~exist('threshold','var') + threshold=0.05; +end +if ~exist('st','var') + st='mass'; +end +if ~exist('NP','var') + NP=[]; +end +if ~exist('TimeBar','var') + TimeBar=0; +end +if ~exist('tails','var') + tails=2; +end +[pv,T,P,PS] = permttest(X1,X2,dimP,0,NP,TimeBar,tails); +T_thd=quantile(PS,1-threshold); +NP=size(PS,1); +if tails==2 + TT=abs(T); +end +switch(st) + case 'mass' + [clusters,pclusters]=prob_clusters(TT.*(TT>=shiftdim(T_thd)),PS.*(PS>=repmat(T_thd,NP,1)),vc); + case 'size' + [clusters,pclusters]=prob_clusters(TT>=shiftdim(T_thd),PS>=repmat(T_thd,NP,1),vc); +end +pvclusters=1-pclusters; % this is now a p-value... + +return + + +%==================================================================== +%% OLD STUFF (now use prob_clusters) +% +% + + + +clear P; +sX=size(pv); +NP=size(PS,1); +T_thd=quantile(PS,1-threshold); +T_thd=reshape(T_thd, sX); +PS=reshape(PS, [NP sX 1]); +PS=permute(PS, [1 dimM setdiff(2:length(sX), dimM)]); +sX=size(PS); +S=ones(NP,1); +for i=1:NP + if isempty(vcM) + s=piecemeal(shiftdim(PS(i,:,:),1)>=T_thd(:,:)); + if isempty(s) + s=0; + else + s=max(s); + end + S(i)=s; + else + clusters=tex_clusters(abs(T)>=T_thd,vcM) + for i=1:length(clusters{1}); + sz(i)=length(clusters{1}{i}); + end + end +end +if isempty(vcM) + [sz,samples]=piecemeal(abs(T)>=T_thd); + for i=1:length(sz); + clusters{i}=samples(i)+[1:sz(i)]-1; + end +else + clusters=tex_clusters(abs(T)>=T_thd,vcM) + for i=1:length(clusters{1}); + sz(i)=length(clusters{1}{i}); + end +end + +if isempty(sz) + clusters={}; + pclusters=[]; + return +end + +[sz,i]=sort(sz); +sz=flipud(sz); +i=flipud(i); +clusters=clusters(i); +for i=1:length(sz) + pclusters(i)=(sum(S>=sz(i))+1)/(NP+1); +end + +%==================================================================== +%% OLD STUFF +% +% + + +for k=1:blk:NV + kk=[k:min(k+blk-1,NV)]; + clear pv_tmp T_tmp P PS + tic + + toc + + if k==1 + % Those allocations cannot be done earlier as we don't know NP + NP=size(PS,1); + S=ones(NP,1); + T=zeros(szX(2:end)); + pv=zeros(szX(2:end)); + end + % Minimal p-value across channels, time etc for each perm(but not + % across perms) + S = min([S pvalue_fast(PS(:,:))]')'; + T(kk,:)=T_tmp; + pv(kk,:)=pv_tmp; +end + +S_sort = sort(S); +alphas = find(diff(S_sort)~=0)/length(S_sort); +pThresholds=S_sort(find(diff(S_sort)~=0)); +if nargout>3 + pv_alpha=alpha_threshold(alphas,pThresholds,pv); +end +return + +function [pA] = pvalue_fast( A ) +% calculate p-values of a matrix A +% p-values are calculated column-wise +A=A(:,:); +pA=zeros(size(A)); +[Y,I] = sort(-A); +n=size(A,1); +%fast calculation of p values ignoring common elements +for i=1:size(A,2) + pA(I(:,i),i) = 1:n; +end +pA=pA./n; +return + + +%========================================================================== +%%OLDER STUFF... + + + +S = ones(M,1); %initialize with worst case +T_orig_pvalue = zeros(size(T_orig)); +for k = 1:K %for all channels/sources + MF = []; %MF holds all data from same channel k (MxF matrix) + for m = 1:M %for all permutations + MF = [MF; T{m}(k,:)]; + end + %convert MF into p-values + MFpvalue = pvalue_fast(MF')'; + %Update S statistic, S = minmin_kf T_kf + %we find minimum component for each channel k each time, iterate for K channels + S = min([S MFpvalue]')'; +end + +S_sort = sort(S); + +bst_message_window('Convert Perm statistics into P-values -> Done') +delete(hwait) + +%This is not completely correct +%The empirical distribution of S_sort is discrete and the left +%tail is not clearly defined +%Instead of 5% threshold, you may achieve 7.6% or something like that + +% p_steps = find(diff(S_sort)~=0)/length(S_sort); +% true_pvalue = S_sort(length(S_sort)*closest(pthres,S_sort)); + +%Sth = S_sort(length(S_sort)*0.05) + +%Significant values: +%T_orig_pvalue > Sth +return + + + + diff --git a/stat/permttest_norm.m b/stat/permttest_norm.m new file mode 100644 index 0000000..95f7eff --- /dev/null +++ b/stat/permttest_norm.m @@ -0,0 +1,83 @@ +function [alphas,thresholds,pv,T,P,PS,S_sort]=permttest_norm(X1,X2,dimP,dimM,NP,TimeBar,tails) +% Normalized permutation Two-sided permutation pseudo T-test +% [alphas,thresholds,pv] = permttest_norm(X1,X2,dimP,dimM,NP,TimeBar,tails) +% +% dimP=1; +% NP=100; +% TimeBar=0; +% tails=2; +% X1=rand(15,10,12);X2=cumsum(repmat(randn(1,10), [15,1,12]),2)+rand(15,10,12); + +% actual code +[pv,T,P,PS] = permttest(X1,X2,dimP,0,+inf); % KJ customized..... +NP=size(PS,1); +S=ones(NP,1); + +for k=1:size(T,2) + MFpvalue=pvalue_fast(squeeze(PS(:,k,:))')'; + S = min([S MFpvalue]')'; +end + +S_sort = sort(S); +alphas = find(diff(S_sort)~=0)/length(S_sort); +thresholds=S_sort(find(diff(S_sort)~=0)); + +% Sth = S_sort(length(S_sort)*closest(pthres,S_sort)); + +return + + + + + +S = ones(M,1); %initialize with worst case +T_orig_pvalue = zeros(size(T_orig)); +for k = 1:K %for all channels/sources + MF = []; %MF holds all data from same channel k (MxF matrix) + for m = 1:M %for all permutations + MF = [MF; T{m}(k,:)]; + end + %convert MF into p-values + MFpvalue = pvalue_fast(MF')'; + %Update S statistic, S = minmin_kf T_kf + %we find minimum component for each channel k each time, iterate for K channels + S = min([S MFpvalue]')'; +end + +S_sort = sort(S); + +bst_message_window('Convert Perm statistics into P-values -> Done') +delete(hwait) + +%This is not completely correct +%The empirical distribution of S_sort is discrete and the left +%tail is not clearly defined +%Instead of 5% threshold, you may achieve 7.6% or something like that + +% p_steps = find(diff(S_sort)~=0)/length(S_sort); +% true_pvalue = S_sort(length(S_sort)*closest(pthres,S_sort)); + +%Sth = S_sort(length(S_sort)*0.05) + +%Significant values: +%T_orig_pvalue > Sth +return + + +function [pA] = pvalue_fast( A ) +%calculate p-values of a matrix A +%p-values are calculated row-wise + +[Y,I] = sort(-A,2); + +%fast calculation of p values ignoring common elements +for i=1:size(A,1) + if(rem(i,250)==0) + disp([num2str(i) ' out of ' num2str(size(A,1))]); + pack + end + pA(i,I(i,:)) = 1:size(A,2); +end +pA=pA/size(A,2); + + diff --git a/stat/permttest_norm2.m b/stat/permttest_norm2.m new file mode 100644 index 0000000..46a0089 --- /dev/null +++ b/stat/permttest_norm2.m @@ -0,0 +1,123 @@ +function [alphas,pThresholds,pv,pv_alpha,T,P,PS,S_sort]=permttest_norm2(X1,X2,dimP,NP,TimeBar,tails) +% Normalized permutation Two-sided permutation pseudo T-test (with memory optimization) +% [alphas,pThresholds,pv] = permttest_norm2(X1,X2,dimP,dimM,NP,TimeBar,tails) +% [alphas,pThresholds,pv,pv_alpha] = permttest_norm2(...) +% [alphas,pThresholds,pv,T,P,PS,S_sort] = permttest_norm2(...) +% +% dimP=1; +% NP=100; +% TimeBar=0; +% tails=2; +% X1=rand(15,10,12);X2=cumsum(repmat(randn(1,10), [15,1,12]),2)+rand(15,10,12); +if ~exist('dimP','var') + dimP=[]; +end +if ~isempty(dimP) & ~isequal(abs(dimP),1) + error('Data matrices X1 and X2 should be: [Subjects]x[Vertices]x[Time Samples]') +end +if ~exist('NP','var') + NP=+inf; +end +if ~exist('TimeBar','var') + TimeBar=0; +end +if ~exist('tails','var') + tails=2; +end +% try +% MEMSPACE=feature('dumpmem'); % largest contiguous block in memory +% MEMSPACE=MEMSPACE/8; % doubles are 8 bytes +% MEMSPACE=MEMSPACE/4; % we want to use only a 1/4 of it +% catch +% MEMSPACE=8e6; +% end +% +szX=[size(X1) 1]; +NV=size(X1,2); +blk=500; + +for k=1:blk:NV + kk=[k:min(k+blk-1,NV)]; + clear pv_tmp T_tmp P PS + tic + [pv_tmp,T_tmp,P,PS] = permttest(X1(:,kk,:),X2(:,kk,:),dimP,0,NP,TimeBar,tails); % KJ customized..... + toc + + if k==1 + % Those allocations cannot be done earlier as we don't know NP + NP=size(PS,1); + S=ones(NP,1); + T=zeros(szX(2:end)); + pv=zeros(szX(2:end)); + end + % Minimal p-value across channels, time etc for each perm(but not + % across perms) + S = min([S pvalue_fast(PS(:,:))]')'; + T(kk,:)=T_tmp; + pv(kk,:)=pv_tmp; +end + +S_sort = sort(S); +alphas = find(diff(S_sort)~=0)/length(S_sort); +pThresholds=S_sort(find(diff(S_sort)~=0)); +if nargout>3 + pv_alpha=alpha_threshold(alphas,pThresholds,pv); +end +return + +function [pA] = pvalue_fast( A ) +% calculate p-values of a matrix A +% p-values are calculated column-wise +A=A(:,:); +pA=zeros(size(A)); +[Y,I] = sort(-A); +n=size(A,1); +%fast calculation of p values ignoring common elements +for i=1:size(A,2) + pA(I(:,i),i) = 1:n; +end +pA=pA./n; +return + + + +%% OLDIES ========================================= + + + +S = ones(M,1); %initialize with worst case +T_orig_pvalue = zeros(size(T_orig)); +for k = 1:K %for all channels/sources + MF = []; %MF holds all data from same channel k (MxF matrix) + for m = 1:M %for all permutations + MF = [MF; T{m}(k,:)]; + end + %convert MF into p-values + MFpvalue = pvalue_fast(MF')'; + %Update S statistic, S = minmin_kf T_kf + %we find minimum component for each channel k each time, iterate for K channels + S = min([S MFpvalue]')'; +end + +S_sort = sort(S); + +bst_message_window('Convert Perm statistics into P-values -> Done') +delete(hwait) + +%This is not completely correct +%The empirical distribution of S_sort is discrete and the left +%tail is not clearly defined +%Instead of 5% threshold, you may achieve 7.6% or something like that + +% p_steps = find(diff(S_sort)~=0)/length(S_sort); +% true_pvalue = S_sort(length(S_sort)*closest(pthres,S_sort)); + +%Sth = S_sort(length(S_sort)*0.05) + +%Significant values: +%T_orig_pvalue > Sth +return + + + + diff --git a/stat/permttest_run.m b/stat/permttest_run.m new file mode 100644 index 0000000..e69de29 diff --git a/stat/phicoef.m b/stat/phicoef.m new file mode 100644 index 0000000..f5b4527 --- /dev/null +++ b/stat/phicoef.m @@ -0,0 +1,13 @@ +function [phi]=phicoef(C) +%phicoef - (Pearson's) Phi coefficient (correlation for binary data) +% +% [phi]=phicoef(C) computes phi for a contingeny matrix C +% +% KND, 2011 + +if ~isequal(size(C),[2 2]) + error +end +c1 = sum(C,1); +c2 = sum(C,2); +phi = det(C)/sqrt(prod([c1 c2'])); diff --git a/stat/posthoc.m b/stat/posthoc.m new file mode 100644 index 0000000..e25bc0f --- /dev/null +++ b/stat/posthoc.m @@ -0,0 +1,26 @@ +function p = posthoc(varargin) +%POSTHOC - Performs posthoc tests on data +% [] = posthoc(X,nf,rp) +% +% Example +% >> posthoc +% +% See also: + + +% Pb : +% Tukey pour les between-S +% Bonferroni / Dunn-Sidak pour les within +% + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-11-13 Creation +% +% ----------------------------- Script History --------------------------------- diff --git a/stat/powerStudent.m b/stat/powerStudent.m new file mode 100755 index 0000000..8f5f23f --- /dev/null +++ b/stat/powerStudent.m @@ -0,0 +1,102 @@ +function [powerStudent] = powerStudent(t,df,c,a) +%Power estimation of a performed Student's t test about mean(s). +%(Estimates the statistical power of a performed Student's t test about mean(s). +%It recalls you the statistical result of the test you should have arrived.) +% +% Syntax: function [powerStudent] = powerStudent(t,df,c,a) +% +% Inputs: +% t - Student's t statistic. +% df - degrees of freedom. +% c - specified direction testing (1 = one-tailed; 2 = two-tailed). +% a - significance level (default = 0.05). +% Outputs: +% Specified direction test. +% (Statistical result of the test you should have arrived). +% Power. +% +% Example: From the example 7.9 of Zar (1999, p.108), the estimation of power +% of a one-sample t test for a two-tailed hypothesis (c = 2) with a +% significance level = 0.05 (t = 2.7662, df = 11, c = 2). +% +% Calling on Matlab the function: +% powerStudent(2.7662,11,2) +% +% Answer is: +% +% It is a two-tailed hypothesis test. +% (The null hypothesis was statistically significative.) +% Power is: 0.7086 +% + +% Created by A. Trujillo-Ortiz and R. Hernandez-Walls +% Facultad de Ciencias Marinas +% Universidad Autonoma de Baja California +% Apdo. Postal 453 +% Ensenada, Baja California +% Mexico. +% atrujo@uabc.mx +% +% January 2, 2003. +% +% To cite this file, this would be an appropriate format: +% Trujillo-Ortiz, A. and R. Hernandez-Walls. (2003). powerStudent: Power estimation of a performed +% Student's t test about mean(s). A MATLAB file. [WWW document]. URL http://www.mathworks.com/ +% matlabcentral/fileexchange/loadFile.do?objectId=2907&objectType=file +% +% References: +% +% Zar, J. H. (1999), Biostatistical Analysis. 4th. ed. +% New-Jersey:Upper Saddle River. p. 107-108,135-136,164. + +if nargin < 4, + a = 0.05; +end + +if nargin < 3, + error('Requires at least three input arguments.'); +end + +t=abs(t); + +if c==1; + disp('It is a one-tailed hypothesis test.'); + a=a; + P=1-tcdf(t,df); + if P >= a; + disp('(The null hypothesis was not statistically significative.)'); + tp=tinv(1-a,df) - t; %Power estimation. + Power=1-tcdf(tp,df); + disp(' '); + fprintf('Power is: %2.4f\n\n', Power) + else + disp('(The null hypothesis was statistically significative.)'); + tb=t - tinv(1-a,df); %Power estimation. + Power=tcdf(tb,df); + disp(' '); + fprintf('Power is: %2.4f\n\n', Power) + end +else c==2; + disp('It is a two-tailed hypothesis test.'); + a=a/2; + P=1-tcdf(t,df); + if P >= a; + disp('(The null hypothesis was not statistically significative.)'); + tp1=tinv(1-a,df) - t; %Power estimation. + Power1=1-tcdf(tp1,df); + tp2=t + tinv(1-a,df); + Power2=1-tcdf(tp2,df); + Power=Power1 + Power2; + disp(' '); + fprintf('Power is: %2.4f\n\n', Power) + else + disp('(The null hypothesis was statistically significative.)'); + tb1=t - tinv(1-a,df); %Power estimation. + b1=1-tcdf(tb1,df); + tb2=t + tinv(1-a,df); + b2=1-tcdf(tb2,df); + Power=1 - (b1 - b2); + disp(' '); + fprintf('Power is: %2.4f\n\n', Power) + end +end diff --git a/stat/power_ttest.m b/stat/power_ttest.m new file mode 100644 index 0000000..c04d48d --- /dev/null +++ b/stat/power_ttest.m @@ -0,0 +1,39 @@ +function [beta]=power_ttest(X1,X2,alpha) +% [beta]=power_ttest(X1,X2,alpha) + + +error + +if size(X1)==2 + mX = X1(:); + if numel(X2)==1 + X2=[X2;X2]; + end + if numel(X2)~=2 + error + end + sX=X2(:); +else + mX = [ mean(X1) ; mean(X2)]; + sX = [ std(X1) ; std(X2)]; + +end + + + +function power=powerfunT(mu0,mu1,sig,alpha,tail,n) +%POWERFUNT T power calculation + S = sig ./ sqrt(n); % std dev of mean + ncp = (mu1-mu0) ./ S; % noncentrality parameter + + if tail==0 + critL = tinv(alpha/2,n-1); % note tinv() is negative + critU = -critL; + power = nctcdf(critL,n-1,ncp) + nctcdf(-critU,n-1,-ncp); % P(t < critL) + P(t > critU) + elseif tail==1 + crit = tinv(1-alpha,n-1); + power = nctcdf(-crit,n-1,-ncp); % 1-nctcdf(crit,n-1,ncp), P(t > crit) + else % tail==-1 + crit = tinv(alpha,n-1); + power = nctcdf(crit,n-1,ncp); % P(t < crit) + end \ No newline at end of file diff --git a/stat/pseudotvalue.m b/stat/pseudotvalue.m new file mode 100644 index 0000000..63804bd --- /dev/null +++ b/stat/pseudotvalue.m @@ -0,0 +1,23 @@ +% pseudotvalue - Pseudo T-value(s) between two samples (regularization of sample variance) +% +% [T] = pseudotvalue(A,B,W) +% Computes a pseudo T-value between the two samples A and B where the +% variance in the denominator is smoothed by matrix W +% INPUTS: +% A - MxK matrix (M=number of observations in the 1st sample, K=number of measures) +% B - NxK matrix (N=number of observations in the 2nd sample, K=number of measures) +% W - KxK matrix (may be sparse) applied to the variance +% OUTPUTS: +% T - 1xK vector of T-values +% +% Author: Karim(s) Jerbi & N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-06 Creation of pseudotvalue.c & its helper pseudotvalue.m +% +% ----------------------------- Script History --------------------------------- diff --git a/stat/pttest.m b/stat/pttest.m new file mode 100644 index 0000000..21d5cdb --- /dev/null +++ b/stat/pttest.m @@ -0,0 +1,41 @@ +function [p, t, df] = pttest(d1, d2) +%PTTEST Student's paired t-test. +% PTTEST(X1, X2) gives the probability that Student's t +% calculated on paired data X1 and X2 is higher than +% observed, i.e. the "significance" level. This is used +% to test whether two paired samples have significantly +% different means. +% [P, T] = PTTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works for PAIRED SAMPLES, i.e. when elements of X1 +% and X2 correspond one-on-one somehow. +% E.g. residuals of two models on the same data. +% +%See also: TTEST, UTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +if (n1 ~= n2) + error('PTTEST: paired samples must have the same number of elements !') +end +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = n1 - 1 ; +cab = (x1 - a1)' * (x2 - a2) / (n1 - 1) ; +if (a1 ~= a2) + % use abs to avoid numerical errors for very similar data + % for which v1+v2-2cab may be close to 0. + t = (a1 - a2) / sqrt(abs(v1 + v2 - 2 * cab) / n1) ; + p = betainc( df / (df + t*t), df/2, 0.5) ; +else + t = 0 ; + p = 1 ; +end diff --git a/stat/pvalue.m b/stat/pvalue.m new file mode 100644 index 0000000..6ea985a --- /dev/null +++ b/stat/pvalue.m @@ -0,0 +1,97 @@ +function = pvalue(input,varargin) +%PVALUE - One line description goes here. +% [] = pvalue(X,dist,params) +% +% Example +% >> pvalue(T,'T',dof) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-16 Creation +% +% ----------------------------- Script History --------------------------------- + + +function p = tpvalue(x,v) +%TPVALUE Compute p-value for t statistic + +normcutoff = 1e7; +if length(x)~=1 && length(v)==1 + v = repmat(v,size(x)); +end + +% Initialize P. +p = NaN(size(x)); +nans = (isnan(x) | ~(0 (0 normcutoff); +p(normal) = 0.5 * erfc(-x(normal) ./ sqrt(2)); + +% See Abramowitz and Stegun, formulas 26.5.27 and 26.7.1 +gen = ~(cauchy | normal | nans); +p(gen) = betainc(v(gen) ./ (v(gen) + x(gen).^2), v(gen)/2, 0.5)/2; + +% Adjust for x>0. Right now p<0.5, so this is numerically safe. +reflect = gen & (x > 0); +p(reflect) = 1 - p(reflect); + +% Make the result exact for the median. +p(x == 0 & ~nans) = 0.5; + + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- \ No newline at end of file diff --git a/stat/qtukey.m b/stat/qtukey.m new file mode 100644 index 0000000..a2e48a5 --- /dev/null +++ b/stat/qtukey.m @@ -0,0 +1,139 @@ +function q = qtukey(rr,cc,df,p,lowt,logp) +% Computes the quantiles of the maximum of rr studentized +% ranges, each based on cc means and with df degrees of freedom +% for the standard error, is less than q. +% +% Uses the secant method to find critical values. +% +% p = confidence level (1 - alpha) +% rr = no. of rows or groups +% cc = no. of columns or treatments +% df = degrees of freedom of error term +% +% ir(1) = error flag = 1 if wprob probability > 1 +% ir(2) = error flag = 1 if ptukey probability > 1 +% ir(3) = error flag = 1 if convergence not reached in 50 iterations +% = 2 if df < 2 +% +% qtukey = returned critical value + % +% If the difference between successive iterates is less than eps, +% the search is terminated + + % +% The algorithm is based on that of the reference. +% +% REFERENCE +% Copenhaver, Margaret Diponzio & Holland, Burt S. +% Multiple comparisons of simple effects in +% the two-way analysis of variance with fixed effects. +% Journal of Statistical Computation and Simulation, +% Vol.30, pp.1-15, 1988. + +eps = 0.0001; +maxiter = 50; + +if (df < 2 || rr < 1 || cc < 2) + error; +end + +% Initial value + +x0 = qinv(p, cc, df); + +% Find prob(value < x0) + +valx0 = ptukey(x0, rr, cc, df, 1, 0) - p; + +% Find the second iterate and prob(value < x1). +% If the first iterate has probability value +% exceeding p then second iterate is 1 less than +% first iterate; otherwise it is 1 greater. + +if (valx0 > 0.0) + x1 = fmax2(0.0, x0 - 1.0); +else + x1 = x0 + 1.0; +end + +valx1 = ptukey(x1, rr, cc, df, 1 ,0 ) - p; + +% Find new iterate +for iter=1:maxiter + q = x1 - ((valx1 * (x1 - x0)) / (valx1 - valx0)); + valx0 = valx1; + % New iterate must be >= 0 + x0 = x1; + if (q < 0.0) + q = 0.0; + valx1 = -p; + end + % Find prob(value < new iterate) + + valx1 = ptukey(ans, rr, cc, df, 1, 0) - p; + x1 = q; + + % If the difference between two successive + % iterates is less than eps, stop + + xabs = fabs(x1 - x0); + if (xabs < eps) + return + end +end + +% If the difference between two successive +% iterates is less than eps, stop + +xabs = fabs(x1 - x0); +if (xabs < eps) + return +end +error('No convergence') + + + +% qinv() : +% this function finds percentage point of the studentized range +% which is used as initial estimate for the secant method. +% function is adapted from portion of algorithm as 70 +% from applied statistics (1974) ,vol. 23, no. 1 +% by odeh, r. e. and evans, j. o. +% +% p = percentage point +% c = no. of columns or treatments +% v = degrees of freedom +% qinv = returned initial estimate +% +% vmax is cutoff above which degrees of freedom +% is treated as infinity. + +function qi = qinv(p,c,v) +p0 = 0.322232421088; +q0 = 0.993484626060e-01; +p1 = -1.0; +q1 = 0.588581570495; +p2 = -0.342242088547; +q2 = 0.531103462366; +p3 = -0.204231210125; +q3 = 0.103537752850; +p4 = -0.453642210148e-04; +q4 = 0.38560700634e-02; +c1 = 0.8832; +c2 = 0.2368; +c3 = 1.214; +c4 = 1.208; +c5 = 1.4142; +vmax = 120.0; +ps = 0.5 - 0.5 * p; +yi = sqrt (log (1.0 / (ps * ps))); +t = yi + (((( yi * p4 + p3) * yi + p2) * yi + p1) * yi + p0) / (((( yi * q4 + q3) * yi + q2) * yi + q1) * yi + q0); +if (v < vmax) + t = t + (t * t * t + t) / v / 4.0; +end +q = c1 - c2 * t; +if (v < vmax) + q = q - c3 / v + c4 * t / v; +end +qi = t * (q * log (c - 1.0) + c5); + diff --git a/stat/rau.m b/stat/rau.m new file mode 100644 index 0000000..7d17868 --- /dev/null +++ b/stat/rau.m @@ -0,0 +1,48 @@ +function rau_score = rau(p, n) +% RAU Compute rationalized arcsine transform +% +% Doing linear tests (like ANOVA or t-tests) on proportional data +% (values between 0 and 1) is difficult since the distributions of +% these values are not strictly Gaussian, especially when the +% proportions are near 0 or 1. The Rationalized Arcsine Transform +% linearizes the proportions and converts them to "rational arcsine +% units". The linear tests can then be performed on the RAU units. +% (p=0.5 roughly corresponds to a rau of 50). +% +% RAU(p) computes the rationalized arcsine transform for a proportion +% value p (0 <= p <= 1). p can also be a vector of proportion values. +% +% RAU(p,n) computes the rau-value assuming that the proportion p +% was calculated using n values. A small n tends to flatten the +% RAU values. +% +% Based on: +% Studebaker, G. A. (1985). A 'rationalized' arcsine transform. +% J. Speech Hearing Res. 28, 455-462. +% +% Example 1: +% p = 0:0.1:1; plot(100*p, rau(p), 'o-'); +% +% Example 2 (which reproduces Fig 1 in Studebaker, 1985): +% p = 0:0.01:1; plot(100*p,rau(p)-(100*p)); +% +% Gautam Vallabha, Aug-27-2007, Gautam.Vallabha@mathworks.com + +if exist('n','var') + p = p.*n; % convert to frequency count + t = asin(sqrt(p/(n+1))) + asin(sqrt((p+1)/(n+1))); +else + t = 2 * asin(sqrt(p)); +end + +if any(p < 0 | p > 1) + error('p should be between 0 and 1'); +end + +% Eq. (7) in Studebaker, 1985 +% the advantage of this scaling is that RAU is roughly +% equal to the percentage score from about 20% to 80% +% and only gets scaled beyond that. + +rau_score = (46.47324337*t) - 23; + diff --git a/stat/rep_anovan.m b/stat/rep_anovan.m new file mode 100644 index 0000000..dfd060a --- /dev/null +++ b/stat/rep_anovan.m @@ -0,0 +1,52 @@ +function [p,t,stats,terms] = rep_anovan(tit,y,group,model,sstype,gnames) +% claculates repeated measureas anova and returns both the N- factor anova +% and n-factor repeated measures anova +% subjects should be highest level i.e. first variable in group +[RP,RT,RSTATS,RTERMS]=ANOVAN(y,group,model,sstype,gnames); +[r,c]=size(group); +Rep_T=RT; + +prevjk=0; +for k=1:c + jk=factorial(c) ./(factorial(c-k)*factorial(k)); % nCr r begins from 1 + for i=1:jk + ij=i+prevjk+1; + Rep_T{ij,6}=[]; Rep_T{ij,7}=[]; + end + prevjk=prevjk+jk; +end + + +prevjk=0; +for k=1:c-1 + jk=factorial(c) ./(factorial(c-k)*factorial(k)); % nCr r begins from 1 + rs=factorial(c-1) ./(factorial(c-1-(k-1))*factorial(k-1)); % (n-1)C(r-1) + st=factorial(c-1) ./(factorial(c-1-(k))*factorial(k)); % (n-1)C(r) + for i=1+rs:jk + ij=i+prevjk+1; + Rep_T{ij,6}=RT{ij,5}/RT{ij+st,5}; % col 6 is F, col 5 is Mean Sq + Rep_T{ij,7}=1-fcdf(Rep_T{ij,6},RT{ij,3},RT{ij+st,3}); % col 7 is p val, col 3 is df + end + prevjk=prevjk+jk; +end + + +fprintf('Source\tSum Sq\tdf\tMean Sq\tF val\tp\n'); +prevjk=0; +for k=1:c + jk=factorial(c) ./(factorial(c-k)*factorial(k)); % nCr r begins from 1 + for i=1:jk + ij=i+prevjk+1; + fprintf('%s\t%f\t%d\t%f\t%f\t%f\n',Rep_T{ij,1},Rep_T{ij,2},Rep_T{ij,3}, ... + Rep_T{ij,5},Rep_T{ij,6},Rep_T{ij,7}); + end + prevjk=prevjk+jk; +end + +switch(sstype) + case 1, cap = 'Sequential (Type I) sums of squares.'; + case 2, cap = 'Hierarchical (Type II) sums of squares.'; + otherwise, cap = 'Constrained (Type III) sums of squares.'; +end +digits = [-1 -1 -1 -1 -1 2 4]; +statdisptable(Rep_T, 'N-Way ANOVA', [tit,'rep-ANOVA'], cap, digits); \ No newline at end of file diff --git a/stat/rm_anova2.m b/stat/rm_anova2.m new file mode 100644 index 0000000..997bb7f --- /dev/null +++ b/stat/rm_anova2.m @@ -0,0 +1,136 @@ +function stats = rm_anova2(Y,S,F1,F2,FACTNAMES) +% +% function stats = rm_anova2(Y,S,F1,F2,FACTNAMES) +% +% Two-factor, within-subject repeated measures ANOVA. +% For designs with two within-subject factors. +% +% Parameters: +% Y dependent variable (numeric) in a column vector +% S grouping variable for SUBJECT +% F1 grouping variable for factor #1 +% F2 grouping variable for factor #2 +% F1name name (character array) of factor #1 +% F2name name (character array) of factor #2 +% +% Y should be a 1-d column vector with all of your data (numeric). +% The grouping variables should also be 1-d numeric, each with same +% length as Y. Each entry in each of the grouping vectors indicates the +% level # (or subject #) of the corresponding entry in Y. +% +% Returns: +% stats is a cell array with the usual ANOVA table: +% Source / ss / df / ms / F / p +% +% Notes: +% Program does not do any input validation, so it is up to you to make +% sure that you have passed in the parameters in the correct form: +% +% Y, S, F1, and F2 must be numeric vectors all of the same length. +% +% There must be at least one value in Y for each possible combination +% of S, F1, and F2 (i.e. there must be at least one measurement per +% subject per condition). +% +% If there is more than one measurement per subject X condition, then +% the program will take the mean of those measurements. +% +% Aaron Schurger (2005.02.04) +% Derived from Keppel & Wickens (2004) "Design and Analysis" ch. 18 +% + +stats = cell(4,5); + +F1_lvls = unique(F1); +F2_lvls = unique(F2); +Subjs = unique(S); + +a = length(F1_lvls); % # of levels in factor 1 +b = length(F2_lvls); % # of levels in factor 2 +n = length(Subjs); % # of subjects + +INDS = cell(a,b,n); % this will hold arrays of indices +CELLS = cell(a,b,n); % this will hold the data for each subject X condition +MEANS = zeros(a,b,n); % this will hold the means for each subj X condition + +% Calculate means for each subject X condition. +% Keep data in CELLS, because in future we may want to allow options for +% how to compute the means (e.g. leaving out outliers > 3stdev, etc...). +for i=1:a % F1 + for j=1:b % F2 + for k=1:n % Subjs + INDS{i,j,k} = find(F1==F1_lvls(i) & F2==F2_lvls(j) & S==Subjs(k)); + CELLS{i,j,k} = Y(INDS{i,j,k}); + MEANS(i,j,k) = mean(CELLS{i,j,k}); + end + end +end + +% make tables (see table 18.1, p. 402) +AB = reshape(sum(MEANS,3),a,b); % across subjects +AS = reshape(sum(MEANS,2),a,n); % across factor 2 +BS = reshape(sum(MEANS,1),b,n); % across factor 1 + +A = sum(AB,2); % sum across columns, so result is ax1 column vector +B = sum(AB,1); % sum across rows, so result is 1xb row vector +S = sum(AS,1); % sum across columns, so result is 1xs row vector +T = sum(sum(A)); % could sum either A or B or S, choice is arbitrary + +% degrees of freedom +dfA = a-1; +dfB = b-1; +dfAB = (a-1)*(b-1); +dfS = n-1; +dfAS = (a-1)*(n-1); +dfBS = (b-1)*(n-1); +dfABS = (a-1)*(b-1)*(n-1); + +% bracket terms (expected value) +expA = sum(A.^2)./(b*n); +expB = sum(B.^2)./(a*n); +expAB = sum(sum(AB.^2))./n; +expS = sum(S.^2)./(a*b); +expAS = sum(sum(AS.^2))./b; +expBS = sum(sum(BS.^2))./a; +expY = sum(Y.^2); +expT = T^2 / (a*b*n); + +% sums of squares +ssA = expA - expT; +ssB = expB - expT; +ssAB = expAB - expA - expB + expT; +ssS = expS - expT; +ssAS = expAS - expA - expS + expT; +ssBS = expBS - expB - expS + expT; +ssABS = expY - expAB - expAS - expBS + expA + expB + expS - expT; +ssTot = expY - expT; + +% mean squares +msA = ssA / dfA; +msB = ssB / dfB; +msAB = ssAB / dfAB; +msS = ssS / dfS; +msAS = ssAS / dfAS; +msBS = ssBS / dfBS; +msABS = ssABS / dfABS; + +% f statistic +fA = msA / msAS; +fB = msB / msBS; +fAB = msAB / msABS; + +% p values +pA = 1-f_cdf(fA,dfA,dfAS); +pB = 1-f_cdf(fB,dfB,dfBS); +pAB = 1-f_cdf(fAB,dfAB,dfABS); + +% return values +stats = {'Source','SS','df','MS','F','p';... + FACTNAMES{1}, ssA, dfA, msA, fA, pA;... + FACTNAMES{2}, ssB, dfB, msB, fB, pB;... + [FACTNAMES{1} ' x ' FACTNAMES{2}], ssAB, dfAB, msAB, fAB, pAB;... + [FACTNAMES{1} ' x Subj'], ssAS, dfAS, msAS, [], [];... + [FACTNAMES{1} ' x Subj'], ssBS, dfBS, msBS, [], [];... + [FACTNAMES{1} ' x ' FACTNAMES{2} ' x Subj'], ssABS, dfABS, msABS, [], []}; + + return \ No newline at end of file diff --git a/stat/shapirowilktest.m b/stat/shapirowilktest.m new file mode 100644 index 0000000..b05a37f --- /dev/null +++ b/stat/shapirowilktest.m @@ -0,0 +1,260 @@ +function [H, pValue, W] = swtest(x, alpha, tail) +%SWTEST Shapiro-Wilk parametric hypothesis test of composite normality. +% [H, pValue, SWstatistic] = SWTEST(X, ALPHA, TAIL) performs +% the Shapiro-Wilk test to determine if the null hypothesis of +% composite normality is a reasonable assumption regarding the +% population distribution of a random sample X. The desired significance +% level, ALPHA, is an optional scalar input (default = 0.05). +% TAIL indicates the type of test (default = 1). +% +% The Shapiro-Wilk hypotheses are: +% Null Hypothesis: X is normal with unspecified mean and variance. +% For TAIL = 0 (2-sided test), alternative: X is not normal. +% For TAIL = 1 (1-sided test), alternative: X is upper the normal. +% For TAIL = -1 (1-sided test), alternative: X is lower the normal. +% +% This is an omnibus test, and is generally considered relatively +% powerful against a variety of alternatives. +% Shapiro-Wilk test is better than the Shapiro-Francia test for +% Platykurtic sample. Conversely, Shapiro-Francia test is better than the +% Shapiro-Wilk test for Leptokurtic samples. +% +% When the series 'X' is Leptokurtic, SWTEST performs the Shapiro-Francia +% test, else (series 'X' is Platykurtic) SWTEST performs the +% Shapiro-Wilk test. +% +% [H, pValue, SWstatistic] = SWTEST(X, ALPHA, TAIL) +% +% Inputs: +% X - a vector of deviates from an unknown distribution. The observation +% number must exceed 3 and less than 5000. +% +% Optional inputs: +% ALPHA - The significance level for the test (default = 0.05). +% +% TAIL - The type of the test (default = 1). +% +% Outputs: +% SWstatistic - The test statistic (non normalized). +% +% pValue - is the p-value, or the probability of observing the given +% result by chance given that the null hypothesis is true. Small values +% of pValue cast doubt on the validity of the null hypothesis. +% +% H = 0 => Do not reject the null hypothesis at significance level ALPHA. +% H = 1 => Reject the null hypothesis at significance level ALPHA. +% + +% +% References: Royston P. "Algorithm AS R94", Applied Statistics (1995) Vol. 44, No. 4. +% AS R94 -- calculates Shapiro-Wilk normality test and P-value +% for sample sizes 3 <= n <= 5000. Handles censored or uncensored data. +% Corrects AS 181, which was found to be inaccurate for n > 50. +% + +% +% Ensure the sample data is a VECTOR. +% + +if numel(x) == length(x) + x = x(:); % Ensure a column vector. +else + error(' Input sample ''X'' must be a vector.'); +end + +% +% Remove missing observations indicated by NaN's and check sample size. +% + +x = x(~isnan(x)); + +if length(x) < 3 + error(' Sample vector ''X'' must have at least 3 valid observations.'); +end + +if length(x) > 5000 + warning('Shapiro-Wilk test might be inaccurate due to large sample size ( > 5000).'); +end + +% +% Ensure the significance level, ALPHA, is a +% scalar, and set default if necessary. +% + +if (nargin >= 2) && ~isempty(alpha) + if numel(alpha) > 1 + error(' Significance level ''Alpha'' must be a scalar.'); + end + if (alpha <= 0 || alpha >= 1) + error(' Significance level ''Alpha'' must be between 0 and 1.'); + end +else + alpha = 0.05; +end + +% +% Ensure the type-of-test indicator, TAIL, is a scalar integer from +% the allowable set {-1 , 0 , 1}, and set default if necessary. +% + +if (nargin >= 3) && ~isempty(tail) + if numel(tail) > 1 + error('Type-of-test indicator ''Tail'' must be a scalar.'); + end + if (tail ~= -1) && (tail ~= 0) && (tail ~= 1) + error('Type-of-test indicator ''Tail'' must be -1, 0, or 1.'); + end +else + tail = 1; +end + +% First, calculate the a's for weights as a function of the m's +% See Royston (1995) for details in the approximation. + +x = sort(x); % Sort the vector X in ascending order. +n = length(x); +mtilde = norminv(((1:n)' - 3/8) / (n + 0.25)); +weights = zeros(n,1); % Preallocate the weights. + +if kurtosis(x) > 3 + + % The Shapiro-Francia test is better for leptokurtic samples. + + weights = 1/sqrt(mtilde'*mtilde) * mtilde; + + % + % The Shapiro-Francia statistic W is calculated to avoid excessive rounding + % errors for W close to 1 (a potential problem in very large samples). + % + + W = (weights' * x) ^2 / ((x - mean(x))' * (x - mean(x))); + + nu = log(n); + u1 = log(nu) - nu; + u2 = log(nu) + 2/nu; + mu = -1.2725 + (1.0521 * u1); + sigma = 1.0308 - (0.026758 * u2); + + newSFstatistic = log(1 - W); + + % + % Compute the normalized Shapiro-Francia statistic and its p-value. + % + + NormalSFstatistic = (newSFstatistic - mu) / sigma; + + % the next p-value is for the tail = 1 test. + pValue = 1 - normcdf(NormalSFstatistic, 0, 1); + +else + + % The Shapiro-Wilk test is better for platykurtic samples. + + c = 1/sqrt(mtilde'*mtilde) * mtilde; + u = 1/sqrt(n); + + PolyCoef_1 = [-2.706056 , 4.434685 , -2.071190 , -0.147981 , 0.221157 , c(n)]; + PolyCoef_2 = [-3.582633 , 5.682633 , -1.752461 , -0.293762 , 0.042981 , c(n-1)]; + + PolyCoef_3 = [-0.0006714 , 0.0250540 , -0.39978 , 0.54400]; + PolyCoef_4 = [-0.0020322 , 0.0627670 , -0.77857 , 1.38220]; + PolyCoef_5 = [0.00389150 , -0.083751 , -0.31082 , -1.5861]; + PolyCoef_6 = [0.00303020 , -0.082676 , -0.48030]; + + PolyCoef_7 = [0.459 , -2.273]; + + weights(n) = polyval(PolyCoef_1 , u); + weights(1) = -weights(n); + + % Special attention when n=3 (this is a special case). + if n == 3 + weights(1) = 0.707106781; + weights(n) = -weights(1); + end + + if n >= 6 + weights(n-1) = polyval(PolyCoef_2 , u); + weights(2) = -weights(n-1); + + count = 3; + phi = (mtilde'*mtilde - 2 * mtilde(n)^2 - 2 * mtilde(n-1)^2) / ... + (1 - 2 * weights(n)^2 - 2 * weights(n-1)^2); + else + count = 2; + phi = (mtilde'*mtilde - 2 * mtilde(n)^2) / ... + (1 - 2 * weights(n)^2); + end + + % + % The vector 'WEIGHTS' obtained next corresponds to the same coefficients + % listed by Shapiro-Wilk in their original test for small samples. + % + + weights(count : n-count+1) = mtilde(count : n-count+1) / sqrt(phi); + + % + % The Shapiro-Wilk statistic W is calculated to avoid excessive rounding + % errors for W close to 1 (a potential problem in very large samples). + % + + W = (weights' * x) ^2 / ((x - mean(x))' * (x - mean(x))); + + % + % Calculate the significance level for W (exact for n=3). + % + + newn = log(n); + + if (n > 3) && (n <= 11) + + mu = polyval(PolyCoef_3 , n); + sigma = exp(polyval(PolyCoef_4 , n)); + gam = polyval(PolyCoef_7 , n); + + newSWstatistic = -log(gam-log(1-W)); + + elseif n >= 12 + + mu = polyval(PolyCoef_5 , newn); + sigma = exp(polyval(PolyCoef_6 , newn)); + + newSWstatistic = log(1 - W); + + elseif n == 3 + mu = 0; + sigma = 1; + newSWstatistic = 0; + end + + % + % Compute the normalized Shapiro-Wilk statistic and its p-value. + % + + NormalSWstatistic = (newSWstatistic - mu) / sigma; + + % The next p-value is for the tail = 1 test. + pValue = 1 - normcdf(NormalSWstatistic, 0, 1); + + % Special attention when n=3 (this is a special case). + if n == 3 + pValue = 1.909859 * (asin(sqrt(W)) - 1.047198); + NormalSWstatistic = norminv(pValue, 0, 1); + end + +end + +% The p-value just found is for the tail = 1 test. +if tail == 0 + pValue = 2 * min(pValue, 1-pValue); +elseif tail == -1 + pValue = 1 - pValue; +end + +% +% To maintain consistency with existing Statistics Toolbox hypothesis +% tests, returning 'H = 0' implies that we 'Do not reject the null +% hypothesis at the significance level of alpha' and 'H = 1' implies +% that we 'Reject the null hypothesis at significance level of alpha.' +% + +H = (alpha >= pValue); \ No newline at end of file diff --git a/stat/spearmann.m b/stat/spearmann.m new file mode 100644 index 0000000..5d7654e --- /dev/null +++ b/stat/spearmann.m @@ -0,0 +1,23 @@ +function rho = spearmann(X,Y) +%SPEARMANN - One line description goes here. +% [rho] = spearmann(X,Y) +% +% Example +% >> spearmann +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-16 Creation +% +% ----------------------------- Script History --------------------------------- + +d=diff(tiedranks(X)); +rho = 1 - 6*sum(d.^2)./(n*(n.^2 - 1)); diff --git a/stat/ssbar.m b/stat/ssbar.m new file mode 100644 index 0000000..b84ba48 --- /dev/null +++ b/stat/ssbar.m @@ -0,0 +1,78 @@ +function [CI ,fx] = ssbar(X,nf,rp,alpha) +%SSBAR - Statistical Significance Bars +% [CI] = ssbar(X,nf,rp,fx,alpha) +% +% Example +% >> ssbar +% +% See also: +% Reference: +% Statistical significance bars (SSB): A way to make graphs +% more interpretable. Christian D. Schunn (2007) + + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2007-10-25 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<2 + nf=ndims(X)-1 +end +if nargin<3 + rp=1:nf +end +if nargin<4 + alpha=0.05; +end + +ng=size(X); +nr=ng(nf+1); +ng=ng(1:nf); +png=prod(ng); +[p,F,fx,epsilon,df,dfe,SS,SSe,SSt]=myanova(X,nf,rp); +CI=0.*p; +for i=1:length(fx) + %number of cells + k = prod(ng(fx{i})); + % number of + n = nr*png/k; + MSe = SSe(i,:)./dfe(i); + if n<120 + CI(i,:)=1/2*sqrt(MSe / n) * tukeyhsd(n,k,alpha); + else + warning('n=%d & k=%d too big for Tukey''s HSD computation',n,k) + CI(i,:)=NaN; + end +end + +return + + +% Validation data: +% One way ANOVA from Loftus & Masson, 1994 +% Exposure Duration Per Word (sec) +% 1 Sec 2 Sec 5 Sec +X= [ + 10 13 13 + 6 8 8 + 11 14 14 + 22 23 25 + 16 18 20 + 15 17 17 + 1 1 4 + 12 15 17 + 9 12 12 + 8 9 12 + ]'; +% From Schunn, 2000: +[c]=ssbar(X); % [c,fx]=ssbar(X,1,1,0.05) +k=3 ; n = 10 ; MSe = 0.615 +CI = 0.48 diff --git a/stat/stat_bar.m b/stat/stat_bar.m new file mode 100644 index 0000000..0630556 --- /dev/null +++ b/stat/stat_bar.m @@ -0,0 +1,52 @@ +function [s] = stat_bar(X,varargin) +%STAT_BAR - Bar plot with elementary statistics +% [s] = stat_bar(X,dimS,dimG) +% Display a bar plot with elementary statistics computed over +% population in dimS, grouped with dimG +% +% Example +% >> stat_bar +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-03-13 Creation +% +% ----------------------------- Script History --------------------------------- +sX=size(X); +if nargin<2 + dimS=find(sX>1); + sX(dimS)=-sX(dimS); +else + dimS=varargin{1}; +end +if nargin<3 + dimG=find(sX>1); +else + dimG=varargin{2}; +end + +paired=1; +if dimS<0 + paired=0; + dimS=-dimS; +end +X=permute2(X, [dimS dimG]); +s.mX=mean(X,1); +if paired + s.semX=stderrw(X,2,1); + [s.p,s.T]=myttest(X,2,1,'pttest'); +else + s.semX=stderr(X,1); + [s.p,s.T]=myttest(X,2,1,'ttest'); +end +s.mX=shiftdim(s.mX,1); +s.semX=shiftdim(s.semX,1); +s.h=barerrorbar(1:prod(sX)./sX(dimG)./sX(dimS),s.mX(:,:)', s.semX(:,:)') diff --git a/stat/stat_examples.m b/stat/stat_examples.m new file mode 100644 index 0000000..21877fc --- /dev/null +++ b/stat/stat_examples.m @@ -0,0 +1,67 @@ + + + +% http://www.abdn.ac.uk/~psy317/personal/files/teaching/spheric.htm +% http://www.psych.upenn.edu/~baron/rpsych.pdf +MD497= [420, 420, 480, 480, 600, 780, +420, 480, 480, 360, 480, 600, +480, 480, 540, 660, 780, 780, +420, 540, 540, 480, 780, 900, +540, 660, 540, 480, 660, 720, +360, 420, 360, 360, 480, 540, +480, 480, 600, 540, 720, 840, +480, 600, 660, 540, 720, 900, +540, 600, 540, 480, 720, 780, +480, 420, 540, 540, 660, 780]; +% SUBJECT x ANGLE x NOISE +MD497=reshape(MD497(:),10,3,2); + +H518=[ +49,47,46,47,48,47,41,46,43,47,46,45, +48,46,47,45,49,44,44,45,42,45,45,40, +49,46,47,45,49,45,41,43,44,46,45,40, +45,43,44,45,48,46,40,45,40,45,47,40 +]; +H518=H518'; +%SSUBJECT x SHAPE x COLOR +H518=reshape(H518,12,2,2); + +X=H518; + +X=MD497; + +v=cov(mean(X,3)); + +NL=size(X,2); %Nb of levels in factor ANGLE +N=10; % NB of subjects + +epsilonGG=NL^2*(mean(diag(v)) - mean(v(:))).^2/(NL-1)/(sum(v(:).^2) - 2*NL*sum(mean(v).^2) + NL^2*mean(v(:)).^2) +epsilonHF=(N*(NL-1)*epsilonGG-2)/(NL-1)/(N-1-(NL-1)*epsilonGG) + + +return + +% http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +% +X=[100 90 130 ; 90 100 100 ; 110 110 109 ; 100 90 109 ; 100 100 130]; +X=X'; +[p,F]=myanova(X,1,1) + + + + +return +% http://www.linguistics.ucla.edu/faciliti/facilities/statistics/fromoac.htm +% Example 2 +X=[ + 8 9 8 8 9 7 10 9 10; + 9 10 9 10 9 13 8 9 9; + 8 7 7 12 7 9 10 9 7; + 6 8 9 8 10 10 12 9 10; + 7 6 7 11 12 8 8 11 9]; +X=X; +X=reshape(X,5,3,3); +% COND TRIAL SUBJECT +X=permute(X,[3 2 1]); +[p,F]=myanova(X,2,1:2) + diff --git a/stat/t_cdf.m b/stat/t_cdf.m new file mode 100644 index 0000000..4540a56 --- /dev/null +++ b/stat/t_cdf.m @@ -0,0 +1,106 @@ +function p = spm_Tcdf(x,v) +% Cumulative Distribution Function (CDF) of Students t distribution +% FORMAT p = spm_Tcdf(x,v) +% +% x - T-variate (Student's t has range (-Inf,Inf) +% v - degrees of freedom (v>0, non-integer d.f. accepted) +% p - CDF of Student's t-distribution with v degrees of freedom at points x +%_______________________________________________________________________ +% +% spm_Tcdf implements the Cumulative Distribution of the Students t-distribution. +% +% Definition: +%----------------------------------------------------------------------- +% The CDF F(x) of the Student's t-distribution with v degrees of +% freedom is the probability that a realisation of a t random variable +% X has value less than x; F(x)=Pr{X0. +% +% Variate relationships: (Evans et al., Ch37 & 7) +%----------------------------------------------------------------------- +% The Student's t distribution with 1 degree of freedom is the Standard +% Cauchy distribution, which has a simple closed form CDF. +% +% Algorithm: +%----------------------------------------------------------------------- +% The CDF of the Student's t-distribution with v degrees of freedom +% is related to the incomplete beta function by: +% Pr(|X|0 +% +% See Abramowitz & Stegun, 26.5.27 & 26.7.1; Press et al., Sec6.4 for +% definitions of the incomplete beta function. The relationship is +% easily verified by substituting for v/(v+x^2) in the integral of the +% incomplete beta function. +% +% MatLab's implementation of the incomplete beta function is used. +% +% +% References: +%----------------------------------------------------------------------- +% Evans M, Hastings N, Peacock B (1993) +% "Statistical Distributions" +% 2nd Ed. Wiley, New York +% +% Abramowitz M, Stegun IA, (1964) +% "Handbook of Mathematical Functions" +% US Government Printing Office +% +% Press WH, Teukolsky SA, Vetterling AT, Flannery BP (1992) +% "Numerical Recipes in C" +% Cambridge +% +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% Andrew Holmes +% $Id: spm_Tcdf.m 112 2005-05-04 18:20:52Z john $ + + +%-Format arguments, note & check sizes +%----------------------------------------------------------------------- +if nargin<2, error('Insufficient arguments'), end + +ad = [ndims(x);ndims(v)]; +rd = max(ad); +as = [ [size(x),ones(1,rd-ad(1))];... + [size(v),ones(1,rd-ad(2))] ]; +rs = max(as); +xa = prod(as,2)>1; +if all(xa) & any(diff(as(xa,:))) + error('non-scalar args must match in size'), end + + +%-Computation +%----------------------------------------------------------------------- +%-Initialise result to zeros +p = zeros(rs); + +%-Only defined for strictly positive v. Return NaN if undefined. +md = ( ones(size(x)) & v>0 ); +if any(~md(:)), p(~md) = NaN; + warning('Returning NaN for out of range arguments'), end + +%-Special case: f is 0.5 when x=0 (where betainc involves log of zero) +p( md & x==0 ) = 0.5; + +%-Special case: Standard Cauchy distribution when v=1 +ml = ( md & v==1 ); if xa(1), mlx=ml; else, mlx=1; end +p(ml) = 0.5 + atan(x(mlx))/pi; + +%-Compute where defined & not special cases +Q = find( md & x~=0 & v~=1 ); +if isempty(Q), return, end +if xa(1), Qx=Q; else Qx=1; end +if xa(2), Qv=Q; else Qv=1; end + +%-Compute +xQxPos = x(Qx)>0; +p(Q) = xQxPos -(xQxPos*2-1).*0.5.*betainc(v(Qv)./(v(Qv)+x(Qx).^2),v(Qv)/2,1/2); diff --git a/stat/t_test.m b/stat/t_test.m new file mode 100644 index 0000000..016e0f7 --- /dev/null +++ b/stat/t_test.m @@ -0,0 +1,78 @@ +## Copyright (C) 1995, 1996, 1997 Kurt Hornik +## +## This program is free software; you can redistribute it and/or modify +## it under the terms of the GNU General Public License as published by +## the Free Software Foundation; either version 2, or (at your option) +## any later version. +## +## This program is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +## General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with this file. If not, write to the Free Software Foundation, +## 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA. + +## usage: [pval, t, df] = t_test (x, m [, alt]) +## +## For a sample x from a normal distribution with unknown mean and +## variance, perform a t-test of the null hypothesis mean(x) == m. +## Under the null, the test statistic t follows a Student distribution +## with df = length (x) - 1 degrees of freedom. +## +## With the optional argument string alt, the alternative of interest +## can be selected. +## If alt is "!=" or "!=", the null is tested against the two-sided +## alternative mean(x) != m. +## If alt is ">", the one-sided alternative mean(x) > m is considered, +## similarly for "<". +## The default is the two-sided case. +## +## pval is the p-value of the test. +## +## If no output argument is given, the p-value of the test is displayed. + +## Author: KH +## Description: Student's one-sample t test + +function [pval, t, df] = t_test (x, m, alt) + + if ((nargin < 2) || (nargin > 3)) + usage ("[pval, t, df] = t_test (x, m [, alt])"); + endif + + if !(is_vector (x)) + error ("t_test: x must be a vector."); + endif + if !(is_scalar (m)) + error ("t_test: m must be a scalar."); + endif + + n = length (x); + df = n - 1; + t = sqrt (n) * (sum (x) / n - m) / std (x); + cdf = t_cdf (t, df); + + if (nargin == 2) + alt = "!="; + endif + + if !isstr (alt) + error ("t_test: alt must be a string"); + endif + if (strcmp (alt, "!=") || strcmp (alt, "!=")) + pval = 2 * min (cdf, 1 - cdf); + elseif strcmp (alt, ">") + pval = 1 - cdf; + elseif strcmp (alt, "<") + pval = cdf; + else + error (sprintf ("t_test: option %s not recognized", alt)); + endif + + if (nargout == 0) + printf (" pval: %g\n", pval); + endif + +endfunction diff --git a/stat/test.m b/stat/test.m new file mode 100644 index 0000000..c967377 --- /dev/null +++ b/stat/test.m @@ -0,0 +1,35 @@ +function [p, s] = test(x1, x2, type) +%TEST statistical test of two samples. +% TEST(X1, X2, 'test') gives the confidence level for +% different tests of the two samples X1 and X2. +% +% 'test' Null hypothesis Assumption on distributions Type +% ----------------------------------------------------------------- +% 't' Means are equal The variances are equal t-test +% 'u' Means are equal The variances are not equal t-test +% 'p' Means are equal The data are paired t-test +% 'f' Variances are equal F-test +% +% TEST(X1, X2) performs a t-test (for equal variances) by default. +% +% [P S] = TEST(X1, X2, ['test']) returns the confidence level in P +% and the value of the statistic (t or F) in S. +% +% Ref: Press et al. 1992. Numerical recipes in C. 14.2, Cambridge. +% +%See also : TTEST, UTEST, PTEST, FTEST. +if (nargin == 2) + type = 't' ; +end + + +if (type == 't') + [p s] = ttest(x1, x2) ; +elseif (type == 'u') + [p s] = uttest(x1, x2) ; +elseif (type == 'p') + [p s] = pttest(x1, x2) ; +elseif (type == 'f') + [p s] = ftest(x1, x2) ; +end + diff --git a/stat/test_anova.m b/stat/test_anova.m new file mode 100644 index 0000000..b5934c2 --- /dev/null +++ b/stat/test_anova.m @@ -0,0 +1,26 @@ +X=[ 25.4 23.4 20 ; + 26.31 21.8 22.2; + 24.1 23.5 19.75; + 23.74 22.75 20.6; + 25.1 21.6 20.4]'; + +X=[ + 106, 110 , 95, 100 , 94, 107 , 103, 104 , 100, 102; + 110, 112 , 98, 99 , 100, 101 , 108, 112 , 105, 107; + 94, 97, 86, 87 98, 99 99, 101 94, 98]; +X=cat(3,X(:,1:2:end),X(:,2:2:end)) + + + +% http://helios.bto.ed.ac.uk/bto/statistics/tress8.html +X=cat(3, [ +9 18 36; +13 23 27; +18 27 23; +22 20 7], [ +11 20 44; +17 27 33; +22 33 27; +28 24 13]); + +% diff --git a/stat/test_perm.m b/stat/test_perm.m new file mode 100644 index 0000000..3a1b25b --- /dev/null +++ b/stat/test_perm.m @@ -0,0 +1,7 @@ +x=randn(30,2); y=randn(size(x))+[.5+rand(size(x,1),1) zeros(size(x,1),1)]; +for i=1:100 + z(1,1:4,i)=[permttest(x,y,-1,0,100,0)' permttest(x,y,-1,2,100,0)]; +end +for i=1:100 + z(2,1:4,i)=[permttest(x,y,-1,0,1000,0)' permttest(x,y,-1,2,1000,0)]; +end diff --git a/stat/testdata.m b/stat/testdata.m new file mode 100644 index 0000000..278622f --- /dev/null +++ b/stat/testdata.m @@ -0,0 +1,17 @@ +% http://www.gardenersown.co.uk/Education/Lectures/R/nonparam.htm +a = [ + 1 2 1 2004 + 2 48 1 2005 + 3 40 1 2006 + 4 3 2 2004 + 5 120 2 2005 + 6 81 2 2006 + 7 2 3 2004 + 8 16 3 2005 + 9 36 3 2006 + 10 7 4 2004 + 11 21 4 2005 + 12 17 4 2006 + 13 2 5 2004 + 14 14 5 2005 + 15 17 5 2006 ]; diff --git a/stat/ttest.m b/stat/ttest.m new file mode 100644 index 0000000..26c85cc --- /dev/null +++ b/stat/ttest.m @@ -0,0 +1,30 @@ +function [p, t] = ttest(d1, d2) +%TTEST Student's t-test for equal variances. +% TTEST(X1, X2) gives the probability that Student's t +% calculated on data X1 and X2, sampled from distributions +% with the same variance, is higher than observed, i.e. +% the "significance" level. This is used to test whether +% two sample have significantly different means. +% [P, T] = TTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works if the samples are drawn from distributions with +% the SAME VARIANCE. Otherwise, use UTTEST. +% +%See also: UTTEST, PTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = n1 + n2 - 2 ; +pvar = ((n1 - 1) * v1 + (n2 - 1) * v2) / df ; +t = (a1 - a2) / sqrt( pvar * (1/n1 + 1/n2)) ; +p = betainc( df / (df + t*t), df/2, 0.5) ; diff --git a/stat/ttest_bonf.m b/stat/ttest_bonf.m new file mode 100644 index 0000000..adfe35d --- /dev/null +++ b/stat/ttest_bonf.m @@ -0,0 +1,123 @@ +function [h,p,sigPairs] = ttest_bonf(x,pairs,alpha,tail) +%TTEST_BONF Hypothesis test: Isolate differences in +% Repeated-Measures Analysis of Variance. +% +% [H,P,SIGPAIRS] = TTEST_BONF(X,PAIRS,ALPHA,TAIL) performs a +% set of Bonferroni corrected t-tests to determine which pairs of +% treatments could have the same mean. +% +% X is a matrix of size NUMSUBJECTS rows and NUMTREATMENTS +% columns. +% +% PAIRS is a Nx2 matrix of pair-wise comparisons that should be +% tested. Example: PAIRS=[ 1 2 +% 2 3 +% 3 4 ], +% will perform 3 t-tests. The first will test the means +% of columns 1 and 2 of matrix X. The second tests the means of +% columns 2 and 3 of matrix X. The last tests the means of +% columns 3 and 4 of matrix X. +% PAIRS = nchoosek(1:NUMTREATMENTS, 2) by default. This tests all +% possible pairwise combinations of the columns of X. +% +% +% The null hypothesis is: "means of two treatments are equal". +% For TAIL = 0 the alternative hypothesis is: "means are not equal." +% For TAIL = 1, alternative: "mean of X is greater than mean of Y." +% For TAIL = -1, alternative: "mean of X is less than mean of Y." +% TAIL = 0 by default. +% +% ALPHA is desired experiment-wise significance level (ALPHA = +% 0.05 by default). The Bonferroni criteria effectively divides +% ALPHA by the number of t-tests being performed. +% +% P is the p-value, or the probability of observing the given result +% by chance given that the null hypothesis is true. Small values +% of P cast doubt on the validity of the null hypothesis. +% +% H=0 => "Do not reject null hypothesis at significance level of alpha." +% H=1 => "Reject null hypothesis at significance level of alpha." +% +% SIGPAIRS contains the rows of PAIRS which fail the t-test +% comparison. +% +% References: +% [1] S.A. Glantz, "Primer of BioStatistics", +% McGray-Hill, 1992, pp 309-310. + +% Oct 31, 2003 +% Adapted loosely from MATLAB's ttest2.m function by: +% +% Guy Shechter +% Lab of Cardiac Energetics, NHLBI, NIH, DHHS +% Bethesda, Maryland, USA +% guy at jhu dot edu + + + + if nargin < 1, + error('Requires at least one input arguments'); + end + + [m1 n1] = size(x); + + if nargin < 2, + pairs = nchoosek(1:n1,2); + elseif isempty(pairs) + pairs=nchoosek(1:n1,2); + elseif max(pairs(:))>n1 + error('PAIRS contains an illegal entry'); + end + + if (m1 == 1 & n1 == 1) + error('Requires matrix first inputs.'); + end + + if nargin < 4, + tail = 0; + end + + if nargin < 3, + alpha = 0.05; + end + + if (prod(size(alpha))>1), error('ALPHA must be a scalar.'); end + if (alpha<=0 | alpha>=1), error('ALPHA must be between 0 and 1.'); end + + df_btw_subjects = size(x,1)-1; + df_treatments = size(x,2)-1; + + df_residual = df_btw_subjects*df_treatments; + grandmean = mean(x(:)); + ss_subjects=0; + + for isub=1:m1 + ss_subjects = ss_subjects + sum( ( x(isub,:)-mean(x(isub,:))).^2); + end + ss_treatment = m1*sum( ( mean(x)-grandmean ).^2); + ssres = ss_subjects-ss_treatment; + msres = ssres/df_residual; + + + for q=1:size(pairs,1) + t(q) = ( mean(x(:,pairs(q,1))) - mean( x(:,pairs(q,2))))./ ... + sqrt(2*msres/m1); + end + + % Find the p-value for the tail = 1 test. + p = 1 - tcdf(t,df_residual); + % Adjust the p-value for other null hypotheses. + if (tail == 0) + for q=1:length(p) + p(q) = 2 * min(p(q), 1-p(q)); + end + end + + % Determine if the actual significance exceeds the desired significance + h=(p<= (alpha/size(pairs,1))); + + if (nargout>2), + sigPairs = pairs(h,:); + end + + return diff --git a/stat/tukeyhsd.m b/stat/tukeyhsd.m new file mode 100644 index 0000000..46103f8 --- /dev/null +++ b/stat/tukeyhsd.m @@ -0,0 +1,185 @@ +function [Qc,HSDc,Q,pairs,X] = tukeyhsd(varargin) +%TUKEYHSD - Performs Tukey Honnestly Significant Differences Test +% [Qc] = tukeyhsd(dfe,ng,alpha) +% Qc: critical Q of the Studentized range statistic for the number of +% freedom (df), the number of groups (ng) at the level: p> tukeyhsd +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-15 Creation +% KND 2007-10-25 Argument order changed +% +% ----------------------------- Script History --------------------------------- + +dfmax=120; +if nargin==2 + dfe=varargin{1}; + ng=varargin{2}; + alpha = 0.05; +elseif nargin==3 + dfe=varargin{1}; + ng=varargin{2}; + alpha=varargin{3}; +elseif nargin==5 + dfe=varargin{1}; + ng=varargin{2}; + alpha=varargin{3}; + ns=varargin{4}; + MSe=varargin{5}; +else + error + X=varargin{1}; + nf=varargin{2}; + fx=varargin{3}; + alpha=varargin{4}; + dfe=varargin{5}; + SSe=varargin{6}; + sx=size(X); + %number of cells in the effect + ng=prod(sx(fx)); + % number of subjects + ns=prod(sx(setdiff(1:nf+1, fx))); + MSe=SSe/dfe; +end +if dfe > dfmax; + error('Too many d.o.f.') +end +% A little math... +t = sqrt(2)*erfinv(1-alpha); +c=[0.89,0.237,1.214,1.21,1.414]; +t=t+(t^3+t)/dfe/4; +q=c(1)-c(2)*t; +q=q-c(3)/dfe+c(4)*t/dfe; +Qc=t*(q*log(ng-1)+c(5)); +if nargout<=1 + return +end +HSDc=Qc*sqrt(MSe*1/ns); +if nargout<=2 + return +end +X=permute(X,[fx setdiff(1:ndims(X), fx)]); +X=reshape(X,[ng ns nf+2:length(sx) ]); +pairs=nchoosek(1:ng,2)'; +X=reshape(mean(X(pairs(:),:,:),2),size(pairs)); +Q=diff(X)./sqrt(SSe./dfe./ns); +return + + + + +return +% Sample dataset: +% http://web.mst.edu/~psyworld/anovaexample.htm +%Problem: Susan Sound predicts that students will learn most effectively +%with a constant background sound, as opposed to an unpredictable sound or +%no sound at all. She randomly divides twenty-four students into three +%groups of eight. All students study a passage of text for 30 minutes. +%Those in group 1 study with background sound at a constant volume in the +%background. Those in group 2 study with noise that changes volume +%periodically. Those in group 3 study with no sound at all. After studying, +%all students take a 10 point multiple choice test over the material. Their +%scores follow: +% x1 x1^2 x2 x2^2 x3 x3^2 +x=[ + 7 49 5 25 2 4 + 4 16 5 25 4 16 + 6 36 3 9 7 49 + 8 64 4 16 1 1 + 6 36 4 16 2 4 + 6 36 7 49 1 1 + 2 4 2 4 5 25 + 9 81 2 4 5 25 + ]; + +% SStotal = 117.96 +% SSamong = 30.08 +% SSwithin = 117.96 - 30.08 = 87.88 +% according to the F sig/probability table with df = (2,21) F must be at +% least 3.4668 to reach p < .05, so F score is statistically significant) + +x=x(:,1:2:end); +x=transpose(x); +x=[ + 7 4 6 8 6 6 2 9 % 1) constant sound + 5 5 3 4 4 7 2 2 % 2) random sound + 2 4 7 1 2 1 5 5 % 3) no sound + ]; + +% One way between subject epsilon=1 +[p,F,fx,e,df,dfe,SS,SSe,SSt]=myanova(x,1,[],1) +% F=3.5946 -> p=0.0454 +% MSe=SSe/dfe = 4.18 +% Q= diff(mean(x))./sqrt(MSe*1/nr) +% mean(x(1,:))-mean(x(2,:))/.72=-2.7 +% mean(x(1,:))-mean(x(3,:))/.72=4.15 +% mean(x(3,:))-mean(x(2,:))/.72=1.38 +pairs=nchoosek(1:3,2)'; +diff(reshape(mean(x(pairs(:),:),2),[2 3]))./sqrt(SSe/dfe*1/size(x,2)) +qtukey(dfe,3,0.95) +% there is an error on this page! +% Mean of column 3 is 3.375 not 3! +% i wrote to the webmaster + + + +% http://facultyvassar.edu/lowry/ch14pt2.html +x =[ + 27.0000 26.2000 28.8000 33.5000 28.8000 + 22.8000 23.1000 27.7000 27.6000 24.0000 + 21.9000 23.4000 20.1000 27.8000 19.3000 + 23.5000 19.6000 23.7000 20.8000 23.9000 +]; +% Line("groups") means: +% Ma=28.86 Mb=25.04 Mc=22.50 Md=22.30 + +% Sources SS df MS F P +% between groups ("effect") 140.10 3 46.70 6.42 <.01 +% within groups ("error") 116.32 16 7.27 +% TOTAL 256.42 19 +% +% a versus b : +% Q = (28.86—25.04) / sqrt(7.27 / 5) = 3.16 +% For the present example, with k=4 and dfwg=16, you will end up with +% Q[.05] = 4.05 and Q[.01] = 5.2. + +% HSD[.05] = Q[.05] x sqrt(MSwg / Nps) +% = 4.05 * sqrt(7.275 / 5) +% = 4.88 +% HSD[.01] = 6.27 +% M[A-B] = 3.82 ; +% M[A-C] = 6.36 +% M[A-D] = 6.56 etc. +% As you can see, two of the comparisons (A·C and A·D) are significant +% beyond the .01 level, while all the others fail to achieve significance +% even at the basic .05 level + +% eta2 = SSbg / SST = 140.10 / 256.42 = 0.55 diff --git a/stat/tvalue.bak.dll b/stat/tvalue.bak.dll new file mode 100644 index 0000000000000000000000000000000000000000..20a38d2533c35295037d0ab37d087702e4a4a736 GIT binary patch literal 12288 zcmeHN4RBjkc0Q7opx8>HglzaT@JJkzK%!bdj+_uOa_pDH#ZJ7I@&jw5$o8|PL_bD) zN}Ph1%(#DEkx6!kPGMju6lRw0Wa%t~PIi|TFYzSM1_rum8^C7iG-X8Nft03Tc0E?V zbKiT?lg)Mtv$Nfu&Gnr7&i&50=broX?mh3yt@j+G3L>(B3I(E*cybDe{D035L%iVT zA1$C0^IpH@q^0HcTSC!TM(R(e`qGhv)E!ACQ>xUZNa<`+iY29{9YHCP>QP+t=U3L~ zrrTtq7Ry}v*<+bT=QTvVz~3k9EmanajVe)aXo}kw;pqg`in3GiRw9cg7XAyiA31jh ziTfogaXqdep88`iQ5(Yn^g&bP((DAKR~eOvLbIh`8F8t~fQs5tJ2Lnsp1R-CQZ~Da zo80S4_e9i)-ZlW?!vdCwP!IU`@H6L}Ya-nmwq9isI>-r57kiu9SXLM&KmBK&RXzfm} zE>z4GZVq1M!>*B|j6 z$T?nsQG0HiW9WewY?S?%Lg)qi#kYEn&f!`^qmJ;s-#E2%_}^iC=RVp;(MMpqkhSMq zt|ID$aCoBg)D#qkChV+}>vZH~`)2{+V>U4?Pv&Ijusn4{o*ZtR%4Hn6`|a#O*Ad5o zp$CrINZqh&=aK!+Lg=Wi^Ip`RH=?c@a6>DY|D!^oFf?j|bXPEclPK6xEoVELYjmK3 z9a>!W9ldzmJ#z6nwzIDg%>UOk*K_Qv%Kri*1q+6sT0e#c9hU5z{4(y}po74EA8a9u zZaL7ir|@Pv3vZ%puf5_R(KE+xbp6x(eXxcOf&cHkBKRrrm-BZE{&Mstu9%(7--+_m zb`+x30-4I+&WNpqT+UwyWN5VZX$QdEoh+JHP^l>dYPj>##aj+486)5{pxxvd@k8J!~Rv#XmC}bz{JJ<;f-P2C^IW#y)SsNzoKn{jO zvuq6yP8A!gEo7(ii@0_!J2`94K6YK zA2rK{PaXaRsW-6rpe_GbvqafzV0}UK&)DeGW+~u>CZl(mWyA6qJk@Qw&64%HSDlg1vEIcR6jqPRXLEz+a@k7@ z|2jKi`7D>cFlL)ZJysl&&slPV6YB@hJ#Y@?+o1bSc0v=bF+$z~f_`u{lV_(< z_CN!U4t;Fd{jRMBQ`|F^Q z8_bv6XT^Fn%tIodK$qV83C^GK>YDs5Vsh--+>duYo*TTB%bv&RjVYsJ*~iDLr%`qJ zkbDWFJGOrC(!z&YaasV|sBH^WSm9_O=doivO@$Rs6Tig7Uu)v4O}u2{*O>TP6Ti{K z2TXjEiElIUArrsH#CMqZy(YfL#79kh+{E{rc(urLpRc6f%n{&kFZPT>!DXv;AH_Ea ziSIH-_|xQCT~sY;j8PAJ8g1ooH6))T9#^v8k`V}9ZG07%JG>%8bdb{Jpk7iBMB-V+ z)y>6(GO#6^>{er`BsHcI{c&YL>W`$=j1=ojrqW7}i&`UUIyNBn#1cv}1HFv2Dw$1m zDQPLyD|M&h*+eq4T1sRysubxnxV zDfDMi$#HDM#baMIA2 z33~?^PL^L;dH}W_20a0K7W6!51Z1Q)z`tiIe*}ICv=n|AX&L(t+63ALY6o?IdO=Ch z0O&BtNWbnj-=xGqV_J!*N|RXG+KWQuwP4;Cl ziXT|o)%ecj!C10~R0{X@r23U4-DC;#Gn~rwMkC3dxI%wt>FtiEG791uOCk~%H%49x zcPnTGYsuOVgK96)B5OJlgW9#$jG}gBf!u7(+?R&Vt=5d1?(RQC6pwW!23$SyIN!-R zzlc~v(N&f}hiSi(PAYM)N2|CBh(V3*p{AA=7YM5r`2U5BmGHas#8i;e!ncj$iW3De z*Mn+78*!y~HPMaqZR9od81fbL1LU{TkCCsWw~()*g-eK5)2+yFBN_Sa6hXd*4kBMm zFCur*S>$fIh}=VS@X_q0<;d%33vxdx$m{7rlnTSW&6cNr$+W+1pTFd=J!)RZBZDq5u@_?Sl80a{arbO5O>)^c@W3*aQ- z8W)cWtb&=zxTWS*!Qu)_2*#x{wQwTB9Th8wb=Vf~L_~-6TDV|B`X=Z}9no}-0a=NA zeXgbHJPYpHGGqkE@-pN+kU$yo5fJ`;pw#*_koyH9>HhEWs`O$Q!Y>LIFxp7sk1>$$qvTSJFPVPn|w%*hqkba;d_z&!3BA~E=~ricb|gK_7?^=H(k(bSwR8Sg+zGt&A_sZ6Z2Nd*hKVCGPnp_%GA<&DQ6j8SP=tT4G(T zIPL;&Za;<&@j0(KkYNoDhRdO#qUr;}AvT507R(>dcp1OoTL5S&))xgm)DM>j`dlo< z`C(I(AMjE5i^KdtErp9=e!#tsW=8kC#xU6;>EHY!Jm0>#cKx5s({Kwl?qWSo92
      0f@DwxbP)6+=q%_WXbv`$<)AGf1@s{3 z3D9$()1aS%J_Z#)4je)J!(bgq2DO92pkdIXpyxp^gFXa(4q6O9TR{=fjfnkMAm(2Q zUsof>za6ptTAa0R#PVLm@P5SZcOZfeAXaYz$%xIjftnGEw}4s^i?)Hjj#zsWVr(9h zO6+@1eLij?tJvz%C34Q%P~ZzySnZIpe6Ai?Gsb16s~AIQ%^0tpB8K34DKKt_v3aGv z37R!PU_m+w?UR-?-n%-FZsS6)+WZ*e$0YZJR3@-@2LQMRKI-GnxI9dKRrbH)az z^%Ej7K6CW2n(I8NV~b{QdBWFi7*HP5g)_D&u6w^OL*1F%75uSU7h&YNF8VTS^I~~a zm&4x~JDKKhlP;gD2helLYQxXz1-5C-F;6bfgYjNgnKr?h`pcnUz zCAy7mBXRJBvytZD$*+)w@V^O24&DrnOUX(clb7I+N|yaq;3oucO*U{LuNOA6)&&$A zY?cP*-`9A7j|nBqU5uaC@DTIoG(5(J&N5Ecgs?iQ7dErxC9QBkNKWX5&GRAQ6^*aK zWIUSTA}`zur>$Qva!**A)}*|(*&s#HifHmWj8VVMdDuekg`w8n;l^zZ?crea*6niB z4Z6rmUXPPyo0~(yaGTs7Zr&cMHVGG%30rn--&&Ho*Og0y+uDnDEmXg_tZI;3U!q&C zAh*YF7yh(1>@h4>k;m=x`|7>xeEt?Yw-tsIYeMv54qWxG^V_)<#=mB^HBXpl_?n{g zbzVo)<`!VvL*b_8ttElS=h)K1HZ%cV0MS6Dsrf3r(2&AjIQ;uqGyF0(wxs%E-7zJe z`Mu_3Zz_!=D|TO2k#Jb8#T}T}BOOrEe042(Tt1gu!bM$lcPhOf|LYb}yQ7lZ<;A|L zEqs`(#0kdp$KT{UaSO2a_lgCI0ur`Yk$45nBzptQBq5HJ^AKdS{|JD7ed$DJk$K&~XPmee0 zRlR@V{l52Q@9W+Vy*A$x-!k7O-yWah%lMA^zUTXq?^WLg-?Xo~uD@|Be3@{~P{y{2%x~@lX3J>zCFqt9R9JsNYiGUVkrd8dz<71d3G` z!0*UlAND-rdEE1)=NZqlo|B%JJa2gZ(euxq4?O?j`N;E$=TpzmJ<}emcdob6%N4Jr suQ~$8@A#|sYWou2X|X@~P_74U1ew48_&zNFjFUOm(vU0pZ_^0;4-63 +#include "mex.h" + +//-------------------------------------------------------------- +// function: mexFunction - Entry point from Matlab environment +// INPUTS: +// nlhs - number of left hand side arguments (outputs) +// plhs[] - pointer to table where created matrix pointers are +// to be placed +// nrhs - number of right hand side arguments (inputs) +// prhs[] - pointer to table of input matrices +//-------------------------------------------------------------- + +// Compile trough: +// mex -v -g tvalue.c + +void mexFunction( int nlhs, mxArray *plhs[], int nrhs, const mxArray +*prhs[] ) +{ + int K; // Sizes + int k; + double *A, *B; + int nA, nB; + double *T; // Output: T-values + + if (nrhs < 1) + mexErrMsgTxt("Not enough input arguments."); + if (nrhs > 2) + mexErrMsgTxt("Too many input arguments."); + if (!mxIsDouble(prhs[0]) || ((nrhs > 1) && (!mxIsDouble(prhs[1])))) + mexErrMsgTxt("Arguments must be type double."); + K = mxGetN(prhs[0]); // Number of dimensions + if (nrhs > 1) + if (K != mxGetN(prhs[1])) + mexErrMsgTxt("Matrix dimensions (number of columns) must agree."); + if (mxIsComplex(prhs[0]) || ((nrhs > 1) && (mxIsComplex(prhs[1])))) + mexWarnMsgTxt("Complex parts ignored."); + + // edist(MxK,NxK) => MxN + A = mxGetPr(prhs[0]); + nA = mxGetM(prhs[0]); // Number of rows in A + + if (nrhs > 1) { + nB = mxGetM(prhs[1]); // Number of rows in B + B = mxGetPr(prhs[1]); + } + + K = mxGetN(prhs[0]); // Number of columns in output + + plhs[0] = mxCreateDoubleMatrix(1,K,mxREAL); + + // Outputs: + T = mxGetPr(plhs[0]); + + // Now the t-value computation + for (k=0; k 1) { + for (i=0; iRkA2tn=y7rvA;bYH773X^Pn%DF{`1EuhBxp0(Pr|( zhSzsZ*jiuT3SNIQjn$iYyg(&`4KldI8x8*$6Rhzu`>@5Tdh>3u0~(>Y5>uUiTRGYX<|8EI4jYPk&H(ft^IKal)suustiP1IS%Ym>Eqz|Q zTQK}V1<{sjx_y=Th!(%r|PeArR@{+Y)p0> z>H_3yA1Z{_V z-HggRZ~62Xm1vq@R(V&N&yVrT>88AzVARh$X#{;^%y8=1xP!=h4|R?`;VSya9o>(^ zdP7F89`Qh{L;GT}SWHbhFnXv%+o20in5m9&wTXd&6IxWR8(%o%$t>JU{R|a5v_BQ7 z9W%5^dmCB6gBhohM=HtKlyzDq%`eFiu-^e&RFD>f%ueBCx{5PM?ZPVz(KBPZkorwc zfHx!r{?FPYI-duh)7o@C7urD$m1WHX`Lq*4s6t2b+D?i%?jSj>3`lCK<}?FP-A{)$ z6y;4rq)ThjN1W<@It0)~LCyfRM-geyg~?O;SVq3PU7N#w^vEeX8!89+HC@&n>heoe zo+NrAQ@Pn>VL;^zqpvXoSd`gl{z`XlHd;{m+=Y_PVmX#^n$KY(qCEuT^klkwX<^rB z!$&BzU%soz=hDCRWZt>=!j13VnjLE_q^DcPD)yBWi1I5nnQIwq_%T&aCl`y#qSi!% zKY3|0-YUWd8PKHAN+_t)teevYdA4J99QruLN6jp zZ66L5_6{KXlVzck6sk5LHCb-XT)?jzl+u%P}4K3OovORbZ%wk+>cp?;Gm8==vn39zLFN7vjmjK zT|+bC^DDA>%Y>Io5iXj*qQ&@C6V!%qptK>Ic1lMWRbfi2rzRP*c;7O$-<;-`>GJ%c z2gvO8Z1*Mln4ypJ^pTn7=jr%DMV7y$Cg-siwtP>?+is~!Zq8AFeu|&Bsmc7Fqbdhbmxs zw>-!o|)UumuNhTdOS0RuccBvGnbVmT)^3iDy>{EsuSLDKvd;TRAWw=e@@<~xyw=t#@P4janqtv- zL>OV?0ZC4<;XyGb2|+h$3&>J>j3N>lWAODX=sD2y zpdWxTAhTTrf7K#i2cHLRLmXzSq_KlO2|55e2s#WJ0EwUx&?v}k@AaHBBs$V02?1GX z)_1&dfC#C#MMqi$xs8y$2KON1H@J3*^nv?yqI3qype`BqghWYH80iW~Vq0R+kM9e6 zsLV@JNhA@%kA&rRDb_C}666hnS$J_cEX7263_Eas#lZxsc+GZDj&zDg!eWrfq-P)) ziwh#zVe6rNPb@JI3W&joKz?Ey=#Rt_0)E?V(LhB1Vo*zZ`UT8_y=0HWp*%pyJ$5M& zhT3*}LXi6uAUo}e&q~nws68P|{qduOM8bX15qB^Wq2FX&??zNZD5;b~htd;*BnpvQ z&M>S7Vp7vVe{*ZA8-(2o{9hq+C;Wf)Y$;v6r{99;_nR6}18A-NZ&v{8eHa;fYM!nU zJ>T@a;Q68Fr=C|mS3JM--1K~atK>NDXI#8CRXbH%to7CPc}4H%yia+*?0wGrZSRZT zSG*U!m%Z1#H@pS!#`>>SACEZItLh8^x%bnm(a$n=V!9CAS za4&HexnFR<=B{ynHglzaT@JJkzK%!bdj+_uOa_pDH#ZJ7I@&jw5$o8|PL_bD) zN}Ph1%(#DEkx6!kPGMju6lRw0Wa%t~PIi|TFYzSM1_rum8^C7iG-X8Nft03Tc0E?V zbKiT?lg)Mtv$Nfu&Gnr7&i&50=broX?mh3yt@j+G3L>(B3I(E*cybDe{D035L%iVT zA1$C0^IpH@q^0HcTSC!TM(R(e`qGhv)E!ACQ>xUZNa<`+iY29{9YHCP>QP+t=U3L~ zrrTtq7Ry}v*<+bT=QTvVz~3k9EmanajVe)aXo}kw;pqg`in3GiRw9cg7XAyiA31jh ziTfogaXqdep88`iQ5(Yn^g&bP((DAKR~eOvLbIh`8F8t~fQs5tJ2Lnsp1R-CQZ~Da zo80S4_e9i)-ZlW?!vdCwP!IU`@H6L}Ya-nmwq9isI>-r57kiu9SXLM&KmBK&RXzfm} zE>z4GZVq1M!>*B|j6 z$T?nsQG0HiW9WewY?S?%Lg)qi#kYEn&f!`^qmJ;s-#E2%_}^iC=RVp;(MMpqkhSMq zt|ID$aCoBg)D#qkChV+}>vZH~`)2{+V>U4?Pv&Ijusn4{o*ZtR%4Hn6`|a#O*Ad5o zp$CrINZqh&=aK!+Lg=Wi^Ip`RH=?c@a6>DY|D!^oFf?j|bXPEclPK6xEoVELYjmK3 z9a>!W9ldzmJ#z6nwzIDg%>UOk*K_Qv%Kri*1q+6sT0e#c9hU5z{4(y}po74EA8a9u zZaL7ir|@Pv3vZ%puf5_R(KE+xbp6x(eXxcOf&cHkBKRrrm-BZE{&Mstu9%(7--+_m zb`+x30-4I+&WNpqT+UwyWN5VZX$QdEoh+JHP^l>dYPj>##aj+486)5{pxxvd@k8J!~Rv#XmC}bz{JJ<;f-P2C^IW#y)SsNzoKn{jO zvuq6yP8A!gEo7(ii@0_!J2`94K6YK zA2rK{PaXaRsW-6rpe_GbvqafzV0}UK&)DeGW+~u>CZl(mWyA6qJk@Qw&64%HSDlg1vEIcR6jqPRXLEz+a@k7@ z|2jKi`7D>cFlL)ZJysl&&slPV6YB@hJ#Y@?+o1bSc0v=bF+$z~f_`u{lV_(< z_CN!U4t;Fd{jRMBQ`|F^Q z8_bv6XT^Fn%tIodK$qV83C^GK>YDs5Vsh--+>duYo*TTB%bv&RjVYsJ*~iDLr%`qJ zkbDWFJGOrC(!z&YaasV|sBH^WSm9_O=doivO@$Rs6Tig7Uu)v4O}u2{*O>TP6Ti{K z2TXjEiElIUArrsH#CMqZy(YfL#79kh+{E{rc(urLpRc6f%n{&kFZPT>!DXv;AH_Ea ziSIH-_|xQCT~sY;j8PAJ8g1ooH6))T9#^v8k`V}9ZG07%JG>%8bdb{Jpk7iBMB-V+ z)y>6(GO#6^>{er`BsHcI{c&YL>W`$=j1=ojrqW7}i&`UUIyNBn#1cv}1HFv2Dw$1m zDQPLyD|M&h*+eq4T1sRysubxnxV zDfDMi$#HDM#baMIA2 z33~?^PL^L;dH}W_20a0K7W6!51Z1Q)z`tiIe*}ICv=n|AX&L(t+63ALY6o?IdO=Ch z0O&BtNWbnj-=xGqV_J!*N|RXG+KWQuwP4;Cl ziXT|o)%ecj!C10~R0{X@r23U4-DC;#Gn~rwMkC3dxI%wt>FtiEG791uOCk~%H%49x zcPnTGYsuOVgK96)B5OJlgW9#$jG}gBf!u7(+?R&Vt=5d1?(RQC6pwW!23$SyIN!-R zzlc~v(N&f}hiSi(PAYM)N2|CBh(V3*p{AA=7YM5r`2U5BmGHas#8i;e!ncj$iW3De z*Mn+78*!y~HPMaqZR9od81fbL1LU{TkCCsWw~()*g-eK5)2+yFBN_Sa6hXd*4kBMm zFCur*S>$fIh}=VS@X_q0<;d%33vxdx$m{7rlnTSW&6cNr$+W+1pTFd=J!)RZBZDq5u@_?Sl80a{arbO5O>)^c@W3*aQ- z8W)cWtb&=zxTWS*!Qu)_2*#x{wQwTB9Th8wb=Vf~L_~-6TDV|B`X=Z}9no}-0a=NA zeXgbHJPYpHGGqkE@-pN+kU$yo5fJ`;pw#*_koyH9>HhEWs`O$Q!Y>LIFxp7sk1>$$qvTSJFPVPn|w%*hqkba;d_z&!3BA~E=~ricb|gK_7?^=H(k(bSwR8Sg+zGt&A_sZ6Z2Nd*hKVCGPnp_%GA<&DQ6j8SP=tT4G(T zIPL;&Za;<&@j0(KkYNoDhRdO#qUr;}AvT507R(>dcp1OoTL5S&))xgm)DM>j`dlo< z`C(I(AMjE5i^KdtErp9=e!#tsW=8kC#xU6;>EHY!Jm0>#cKx5s({Kwl?qWSo92
      0f@DwxbP)6+=q%_WXbv`$<)AGf1@s{3 z3D9$()1aS%J_Z#)4je)J!(bgq2DO92pkdIXpyxp^gFXa(4q6O9TR{=fjfnkMAm(2Q zUsof>za6ptTAa0R#PVLm@P5SZcOZfeAXaYz$%xIjftnGEw}4s^i?)Hjj#zsWVr(9h zO6+@1eLij?tJvz%C34Q%P~ZzySnZIpe6Ai?Gsb16s~AIQ%^0tpB8K34DKKt_v3aGv z37R!PU_m+w?UR-?-n%-FZsS6)+WZ*e$0YZJR3@-@2LQMRKI-GnxI9dKRrbH)az z^%Ej7K6CW2n(I8NV~b{QdBWFi7*HP5g)_D&u6w^OL*1F%75uSU7h&YNF8VTS^I~~a zm&4x~JDKKhlP;gD2helLYQxXz1-5C-F;6bfgYjNgnKr?h`pcnUz zCAy7mBXRJBvytZD$*+)w@V^O24&DrnOUX(clb7I+N|yaq;3oucO*U{LuNOA6)&&$A zY?cP*-`9A7j|nBqU5uaC@DTIoG(5(J&N5Ecgs?iQ7dErxC9QBkNKWX5&GRAQ6^*aK zWIUSTA}`zur>$Qva!**A)}*|(*&s#HifHmWj8VVMdDuekg`w8n;l^zZ?crea*6niB z4Z6rmUXPPyo0~(yaGTs7Zr&cMHVGG%30rn--&&Ho*Og0y+uDnDEmXg_tZI;3U!q&C zAh*YF7yh(1>@h4>k;m=x`|7>xeEt?Yw-tsIYeMv54qWxG^V_)<#=mB^HBXpl_?n{g zbzVo)<`!VvL*b_8ttElS=h)K1HZ%cV0MS6Dsrf3r(2&AjIQ;uqGyF0(wxs%E-7zJe z`Mu_3Zz_!=D|TO2k#Jb8#T}T}BOOrEe042(Tt1gu!bM$lcPhOf|LYb}yQ7lZ<;A|L zEqs`(#0kdp$KT{UaSO2a_lgCI0ur`Yk$45nBzptQBq5HJ^AKdS{|JD7ed$DJk$K&~XPmee0 zRlR@V{l52Q@9W+Vy*A$x-!k7O-yWah%lMA^zUTXq?^WLg-?Xo~uD@|Be3@{~P{y{2%x~@lX3J>zCFqt9R9JsNYiGUVkrd8dz<71d3G` z!0*UlAND-rdEE1)=NZqlo|B%JJa2gZ(euxq4?O?j`N;E$=TpzmJ<}emcdob6%N4Jr suQ~$8@A#|sYWou2X|X@~P_74U1ew48_&zNFjFUOm(vU0pZ_^0;4-63=T))/length(pdf); +else + mu = + + mT=k*N1/2; %mean + sT=realsqrt(prod(L)/12*(N1-2*B/N/(N^2-1))); %standard deviation + zT=(abs(T-mT)-0.5)/sT; %z-value with correction for continuity + %p=1-normcdf(zT); %p-value + p = 1-(0.5 * erfc(-zT ./ sqrt(2))); +end + + +return + + + +L=[length(x1) length(x2)]; k=min(L); N=sum(L); N1=N+1; %set the basic parameter + +[A,B]=tiedrank([x1(:); x2(:)]); %compute the ranks and the ties +%Compute the Mann-Whitney-Wilcon statistic summing the ranks of the sample with +%the less number of elements. +if L(1)<=L(2) + T=sum(A(1:k)); +else + T=sum(A(k+1:end)); +end + +%There is an alternative formulation of this test that yields a statistic +%commonly denoted by U. U is related to T by the formula U=T-k*(k+1)/2, +%where k is the size of the smaller sample (or either sample if both contain +%the same number of individuals). For a presentation of the U statistic, see: +% S. Siegel and N. J. Castellan, Jr., Nonparametric Statistics for the +% Behavioral Sciences, 2d ed. McGraw-Hill, New York, 1988, Section 6.4, “The +% Wilcoxon-Mann-Whitney U Test.â€? +%For a detailed derivation and discussion of the Mann-Whitney test as developed +%here, as well as its relationship to U, see: +% F. Mosteller and R. Rourke, Sturdy Statistics: Nonparametrics and Order +% Statistics, Addison-Wesley, Reading, MA, 1973, Chapter 3, “Ranking Methods for +% Two Independent Samples.â€? +U=T-k*(k+1)/2; + + +function c = combnk(v,k) +%COMBNK All combinations of the N elements in V taken K at a time. +% C = COMBNK(V,K) produces a matrix, with K columns. Each row of C has +% K of the elements in the vector V. C has N!/K!(N-K)! rows. K must be +% a nonnegative integer. + +% Copyright 1993-2004 The MathWorks, Inc. +% $Revision: 2.12.2.2 $ $Date: 2004/12/24 20:46:48 $ + +[m, n] = size(v); + +if min(m,n) ~= 1 + error('stats:combnk:VectorRequired','First argument has to be a vector.'); +end + +if n == 1 + n = m; + flag = 1; +else + flag = 0; +end + +if n == k + c = v(:).'; +elseif n == k + 1 + tmp = v(:).'; + c = tmp(ones(n,1),:); + c(1:n+1:n*n) = []; + c = reshape(c,n,n-1); +elseif k == 1 + c = v.'; +elseif n < 17 && (k > 3 || n-k < 4) + rows = 2.^(n); + ncycles = rows; + + for count = 1:n + settings = (0:1); + ncycles = ncycles/2; + nreps = rows./(2*ncycles); + settings = settings(ones(1,nreps),:); + settings = settings(:); + settings = settings(:,ones(1,ncycles)); + x(:,n-count+1) = settings(:); + end + + idx = x(sum(x,2) == k,:); + nrows = size(idx,1); + [rows,ignore] = find(idx'); + c = reshape(v(rows),k,nrows).'; +else + P = []; + if flag == 1, + v = v.'; + end + if k < n && k > 1 + for idx = 1:n-k+1 + Q = combnk(v(idx+1:n),k-1); + P = [P; [v(ones(size(Q,1),1),idx) Q]]; + end + end + c = P; +end diff --git a/stat/uttest.m b/stat/uttest.m new file mode 100644 index 0000000..f989423 --- /dev/null +++ b/stat/uttest.m @@ -0,0 +1,30 @@ +function [p, t, df] = uttest(d1, d2) +%UTTEST Student's t-test for unequal variances. +% UTTEST(X1, X2) gives the probability that Student's t +% calculated on data X1 and X2, sampled from distributions +% with different variances, is higher than observed, i.e. +% the "significance" level. This is used to test whether +% two sample have significantly different means. +% [P, T] = UTTEST(X1, X2) gives this probability P and the +% value of Student's t in T. The smaller P is, the more +% significant the difference between the means. +% E.g. if P = 0.05 or 0.01, it is very likely that the +% two sets are sampled from distributions with different +% means. +% +% This works if the samples are drawn from distributions with +% DIFFERENT VARIANCE. Otherwise, use TTEST. +% +%See also: TTEST, PTTEST. +[l1 c1] = size(d1) ; +n1 = l1 * c1 ; +x1 = reshape(d1, l1 * c1, 1) ; +[l2 c2] = size(d2) ; +n2 = l2 * c2 ; +x2 = reshape(d2, l2 * c2, 1) ; +[a1 v1] = avevar(x1) ; +[a2 v2] = avevar(x2) ; +df = (v1 / n1 + v2 / n2) * (v1 / n1 + v2 / n2) / ... + ( (v1 / n1) * (v1 / n1) / (n1 - 1) + (v2 / n2) * (v2 / n2) / (n2 -1) ) ; +t = (a1 - a2) / sqrt( v1 / n1 + v2 / n2 ) ; +p = betainc( df / (df + t*t), df/2, 0.5) ; diff --git a/stat/winsor.m b/stat/winsor.m new file mode 100644 index 0000000..197ace7 --- /dev/null +++ b/stat/winsor.m @@ -0,0 +1,77 @@ +function [X,wtf] = winsor(X,p,dim) +% WINSOR - Winsorize data +% +% [W,wtf] = winsor(X,p) +% Replace p% (or p samples, if p>=1) in X at both ends by the p-th +% quantile values; wtf is a logical array of those elements which have +% been winsorized. +% +% [W] = winsor(X,[p_top p_bottom]) +% Remove possibly asymmetric %/samples at the top and at the bottom +% +% [W] = winsor(X,p,dim) +% Default is to work on dimension 1 +% +% See also: quantile, clipping + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-09 Creation +% +% ----------------------------- Script History --------------------------------- + +sX=size(X); +if nargin<2 + error('Missing p argument!'); +end +if nargin<3 + dim=1; + if isvector(X) + [dim,dim]=max(sX); + end +end +N = sX(dim); +if numel(p)<1 || numel(p)>2 + error('p must be a 1- or 2-element'); +end +if numel(p)==1 + p(2)=p; +end +if any(p<1) + do_warn=any(rem(N,1./p)); + p(p<1)=round(N*p(p<1)); + if do_warn + warning('Number of trimmed values rounded to: top=%d ; bottom=%d',p(1),p(2)); + end +end +if sum(p>=N) + error('Can''t trim all the data! Use a smaller p.'); +end +if dim>1 + X=permute(X, [dim setdiff(1:length(sX),dim)]); +end +X=X(:,:); +NC=size(X,2); +[j,j]=sort(X); +j = j+repmat(sX(1)*[0:NC-1],sX(1),1); +% Replace values in the upper tail +X(j(N-p(2)+1:N,:)) = repmat(X(j(N-p(2),:)),p(2),1); +% Replace values in the lower tail +X(j(1:p(1),:)) = repmat(X(j(p(1)+1,:)),p(1),1); +%X=reshape(X,N-p(1)-p(2),NC); +if dim>1 + X=ipermute(X, [dim setdiff(1:length(sX),dim)]); +end +if nargout>1 + wtf=logical(zeros(sX)); + wtf([j(1:p(1),:) j(N-p(2)+1:N,:)])=1; +end +%sX(dim)=N-p(1)-p(2); +X=reshape(X,sX); +return \ No newline at end of file diff --git a/stderr.m b/stderr.m new file mode 100644 index 0000000..2f4313f --- /dev/null +++ b/stderr.m @@ -0,0 +1,40 @@ +function y = stderr(x,dim,ci) +%stderr - Standard error (of the sample mean). +% +% y = stderr(x) +% For vectors, STDERR(X) returns the standard error around the mean. For +% ND arrays, it is computed for the first non-singleton dimension. +% The standard error is the (unbiased) standard deviation divided by the +% size of the sample: SE=SD/sqrt(N) +% +% STDERR(X,DIM) computes std err on the given dimension. +% +% See also: std + +% NOT YET: +% STDERR(X,DIM,P) computes confidence interval at P percent + +if nargin<2, + if isempty(x), y = 0/0; return; end % Empty case without dim argument + dim = min(find(size(x)~=1)); + if isempty(dim), dim = 1; end +end +if nargin<3, ci = []; end + +n=size(x,dim); + +% Avoid dividing by zero for scalar case +if n==1, y = zeros(size(x)); y(isnan(x))=NaN; return, end + +tile = ones(1,max(ndims(x),dim)); +tile(dim) = n; + +xc = x - repmat(sum(x,dim)/n,tile); % Remove mean +y = sum(conj(xc).*xc,dim)/(n-1)/n; +y=sqrt(y); +return + +% NOT YET +if not(isempty(ci)) + ci=tcdf(1); +end \ No newline at end of file diff --git a/stderr_within.m b/stderr_within.m new file mode 100644 index 0000000..ef8c4ad --- /dev/null +++ b/stderr_within.m @@ -0,0 +1,36 @@ +function y = stderr(x,dim,ci) +%stderr - Standard error (of the sample mean). +% For vectors, STDERR(X) returns the standard error around the mean. For +% ND arrays, it is computed for the first non-singleton dimension. +% The standard error is the (unbiased) standard deviation divided by the +% size of the sample: SE=SD/sqrt(N) +% +% STDERR(X,DIM) computes std err on the given dimension. + +% NOT YET: +% STDERR(X,DIM,P) computes confidence interval at P percent + +if nargin<2, + if isempty(x), y = 0/0; return; end % Empty case without dim argument + dim = min(find(size(x)~=1)); + if isempty(dim), dim = 1; end +end +if nargin<3, ci = []; end + +n=size(x,dim); + +% Avoid dividing by zero for scalar case +if n==1, y = zeros(size(x)); y(isnan(x))=NaN; return, end + +tile = ones(1,max(ndims(x),dim)); +tile(dim) = n; + +xc = x - repmat(sum(x,dim)/n,tile); % Remove mean +y = sum(conj(xc).*xc,dim)/(n-1)/n; +y=sqrt(y); +return + +% NOT YET +if not(isempty(ci)) + ci=tcdf(1); +end \ No newline at end of file diff --git a/stderrw.m b/stderrw.m new file mode 100644 index 0000000..91f0852 --- /dev/null +++ b/stderrw.m @@ -0,0 +1,45 @@ +function Y = stderrw(X,dimF,dimS) +%stderrw - Standard error for repated measure +% +% Y=stderrw(X,dimF) +% Y=stderrw(X,dimF,dimS) +% +% Computes standard error (of the sample mean) in fully repeated design. +% dimF indicates the dimension(s) of repeated factors/treatment +% dimS indicates the observations/subjects dimension +% (default: the first non-singleton dimension beside factors) +% +% Example: +% 5 different measures in 2 tasks by 3 condition for 10 subjects in a +% within subject design giving the data matrix X such as: +% size(X)==[ 2 3 5 10 ] +% >> Y=stderrw(X,1:2,4); +% Y is thus of size [2 3 5 1] + +sX=size(X); +ndX=ndims(X); +if nargin<3 + sY=sX; + sY(dimF)=0; + dimS = min(find(sY>1)); + if isempty(dimS), error('Not enough '); end +end +sY=sX; +sY(dimS)=1; +Y=zeros(sY); +sF=sX(dimF); +NL=prod(sX(dimF)); +NS=sX(dimS); +NX=[sX(setdiff(1:ndX,[dimS dimF])) 1]; + +% for each subject center X and compute stderr +pX=[dimF dimS setdiff(1:ndX,[dimS dimF])]; +X=permute(X,pX); +X=reshape(X,[NL,NS,NX]); +X=X-repmat(mean(X,1),[NL 1]); +Y=stderr(X,2); +Y=reshape(Y,[sX(dimF),1,NX]); +Y=ipermute(Y,pX); +return + + diff --git a/stdnan.m b/stdnan.m new file mode 100644 index 0000000..2090869 --- /dev/null +++ b/stdnan.m @@ -0,0 +1,82 @@ +function [y]=stdnan(x,flag,dim) +%stdnan - Standard deviation once NaN values have been removed +% +% see std() for details + +% For vectors, MEAN(X) is the mean value of the elements in X. For +% matrices, MEAN(X) is a row vector containing the mean value of +% each column. For N-D arrays, MEAN(X) is the mean value of the +% elements along the first non-singleton dimension of X. +% +% MEAN(X,DIM) takes the mean along the dimension DIM of X. +% +% Example: If X = [0 1 2 +% 3 4 5] +% +% then mean(X,1) is [1.5 2.5 3.5] and mean(X,2) is [1 +% 4] +% +% See also MEDIAN, STD, MIN, MAX, COV. + + +% Copyright 1984-2002 The MathWorks, Inc. +% $Revision: 5.17 $ $Date: 2002/06/05 17:06:39 $ + +if nargin < 2 + flag=0; +end +if nargin < 3 + dim=1; +end +x=permute(x, [dim 1:dim-1 dim+1:ndims(x)]); + +if size(x,dim)==1, + y = zeros(size(x)); + y(isnan(x))=NaN; + return +end + + +% tile = ones(1,max(ndims(x),dim)); + +t1 = [ size(x, 1) 1 ]; +t2 = [ 1 size(x, 2) ]; + +xn = x; +nn=sum(isnan(x)); +xn(isnan(xn))=0; +sx=size(x,1)-nn; + +xc = x - repmat(sum(xn),t1)./repmat((sx),t1); % Remove mean +xc(isnan(xc))=0; + +if flag, + y = sqrt(sum(conj(xn).*xc)./(sx)); +else + y = sqrt(sum(conj(xc).*xc)./(sx-1)); +end +if dim>1 + y=permute(y, [2:dim 1 dim+1:ndims(x)]); +end + +return +sx=size(x); + + + +if 0 + % Determine which dimension SUM will use + if ndims(x)>1 + error('stdnan: You have to specifiy the dimension on which stdnan operate!') + end + % dim = min(find(size(x)~=1)); + % if isempty(dim), dim = 1; end + x(find(isnan(x)))=[]; + y = sum(x)/size(x); +else + k=find(isnan(x)); + kk=zeros(size(x)); + kk(k)=1; + x(k)=0; + y = sum(x,dim)./(size(x,dim)-sum(kk,dim)); +end diff --git a/stdw.m b/stdw.m new file mode 100644 index 0000000..cda0a7c --- /dev/null +++ b/stdw.m @@ -0,0 +1,60 @@ +function Y = stdw(X,dimF,dimS) +%STDW - Standard deviation for repated measure +% +% Y=stdw(X,dimF) +% Y=stdw(X,dimF,dimS) +% Computes unbiased standard deviation in fully repeated design. +% dimF indicates the dimension(s) of repeated factors/treatment +% dimS indicates the observations/subjects dimension +% (default: the first non-singleton dimension beside factors) +% +% Example: +% 5 different measures in 2 tasks by 3 condition for 10 subjects in a +% within subject design giving the data matrix X such as: +% size(X)==[ 2 3 5 10 ] +% >> Y=stdw(X,1:2,4); +% Y is thus of size [2 3 5 1] +% +% See also: stderrw, std, stderr + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program isfree software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-05 Creation +% +% ----------------------------- Script History --------------------------------- + + +sX=size(X); +ndX=ndims(X); +if nargin<3 + sY=sX; + sY(dimF)=0; + dimS = min(find(sY>1)); + if isempty(dimS), error('Not enough '); end +end +sY=sX; +sY(dimS)=1; +Y=zeros(sY); +sF=sX(dimF); +NL=prod(sX(dimF)); +NS=sX(dimS); +NX=[sX(setdiff(1:ndX,[dimS dimF])) 1]; + +% for each subject center X and compute stderr +pX=[dimF dimS setdiff(1:ndX,[dimS dimF])]; +X=permute(X,pX); +X=reshape(X,[NL,NS,NX]); +X=X-repmat(mean(X,1),[NL 1]); +Y=std(X,[],2); +Y=reshape(Y,[sX(dimF),1,NX]); +Y=ipermute(Y,pX); +return + + + diff --git a/strcell.m b/strcell.m new file mode 100644 index 0000000..fc6246e --- /dev/null +++ b/strcell.m @@ -0,0 +1,22 @@ +function t = strcell(s) +%strcell() - Create cell array of strings from character array. +% [T] = STRCELL(S) converts S into a cell array T where every cell +% contains a character array: +% * char array are unmodified +% * empty elements or empty arrays are converted to '' +% * numbers are converted with num2str +% * non convertible elements (cell array, etc) are converted to '' +% +% See also STRINGS, CHAR, ISCELLSTR, CELLSTR. + +res = cellfun('isclass',s,'char'); +if all(res(:)); t=s; return; end +t = cell(size(s)); +t(res)=s(res); +for i=find(~res(:)') + try + t{i}=num2str(s{i}); + catch + t{i}=''; + end +end \ No newline at end of file diff --git a/strfindobj.m b/strfindobj.m new file mode 100644 index 0000000..a92db86 --- /dev/null +++ b/strfindobj.m @@ -0,0 +1,25 @@ +function [h]=strfindobj(varargin) +%strfindobj - Find obj whose property match with a given string +% h=strfindobj(S,H,P) +% String,Handles[gca],Property[Tag], + +S=varargin{1}; +switch nargin + case 1 + P='Tag'; + H=findobj(gca); + case 2 + H=varargin{2}; + P='Tag'; + case 3 + H=varargin{2}; + P=varargin{2}; +end + +r=get(H,P); +h=[]; +for i=1:length(r) + if ~isempty(strfind(lower(r{i}),lower(S))) + h=[h;H(i)]; + end +end diff --git a/strongconn.m b/strongconn.m new file mode 100644 index 0000000..b5a5ba2 --- /dev/null +++ b/strongconn.m @@ -0,0 +1,73 @@ +function [M,C] = strongconn(A,tol) +%STRONGCONN - Find strongly connected components from a graph +% [M,C] = strongconn(G) +% Finds the strongly connected sets of vertices +% in the (directed) graph matrix G +% A = 0-1 matrix displaying accessibility +% C = displays the equivalent classes +% +% See also: dmperm +% Web: http://www.nist.gov/dads/HTML/stronglyConnectedCompo.html + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-01-11 Creation +% +% ----------------------------- Script History + + + + + + +function [c,v] = dig(a,tol) +[m,n] = size(G); +if m~=n 'Not a Square Matrix', break, end +b=abs(a); o=ones(size(a)); x=zeros(1,n); +msg='The Matrix is Irreducible !'; v='Connected Directed Graph !'; +if (nargin==1) tol=n*eps*norm(a,'inf'); end + +% Create a companion matrix +b>tol*o; c=ans; if (c==o) msg, break, end + +% Compute accessibility in at most n-step paths +for k=1:n + for j=1:n + for i=1:n + % If index i accesses j, where can you go ? + if c(i,j) > 0 c(i,:) = c(i,:)+c(j,:); end + end + end +end +% Create a 0-1 matrix with the above information +c>zeros(size(a)); c=ans; if (c==o) msg, break, end + +% Identify equivalence classes +d=c.*c'+eye(size(a)); d>zeros(size(a)); d=ans; +v=zeros(size(a)); +for i=1:n find(d(i,:)); ans(n)=0; v(i,:)=ans; end + +% Eliminate displaying of identical rows +i=1; +while(i0 + h(j,:)=v(i,:); + j=j+1; + end +end +v=h; diff --git a/struct2cell2.m b/struct2cell2.m new file mode 100644 index 0000000..c9443e2 --- /dev/null +++ b/struct2cell2.m @@ -0,0 +1,12 @@ +%STRUCT2CELL2 - Recursive conversion of structure array to cell array. +% C = STRUCT2CELL2(S) converts the M-by-N structure S (with P fields) +% into a P-by-M-by-N cell array C. +% +% If S is N-D, C will have size [P SIZE(S)]. +% +% Example: +% clear s, s.category = 'tree'; s.height = 37.4; s.name = 'birch'; +% c = struct2cell(s); f = fieldnames(s); +% +% See also STRUCT2CELL, struct2list + diff --git a/struct2fv.m b/struct2fv.m new file mode 100644 index 0000000..f34a5ef --- /dev/null +++ b/struct2fv.m @@ -0,0 +1,18 @@ +function [fv]=struct2fv(s) +% struct2fv - Keep only the faces and vertices fields from a structure +% fv=struct2fv(s) +% will remove extra fields of s to keep only the "Vertices" and "Faces" ones +% Note: Upper case/lower case discrepancies are ignored. + +fv=[]; +for f={'faces', 'vertices'} + if isfield(s, f{1}) + fv=setfield(fv, f{1}, getfield(s, f{1})); + elseif isfield(s, lower(f{1})) + fv=setfield(fv, f{1}, getfield(s, lower(f{1}))); + elseif isfield(s, [upper(f{1}(1)) upper(f{1}(2:end))]) + fv=setfield(fv, f{1}, getfield(s, [upper(f{1}(1)) upper(f{1}(2:end))])); + else + warning(sprintf('No field %f in the structure', f{1})) + end +end \ No newline at end of file diff --git a/struct2list.m b/struct2list.m new file mode 100644 index 0000000..1865892 --- /dev/null +++ b/struct2list.m @@ -0,0 +1,81 @@ +function [C]=struct2list(S,depth,flat) +%struct2list - List each field and its content in an vertical cell array +% +% [C]=struct2list(S) +% Lists each fieldname and its content into a 2-column cell array. This +% is useful to pass structures as argument to function according to the +% scheme: +% function('name', value, 'name', value, ...) +% +% [C]=struct2list(S,depth) also expand the subfields which are +% themselves struct's. Down to a given depth. Use depth=Inf to explore +% the full arborescence. Default: depth=0 (i.e. no recursion) +% +% [C]=struct2list(S,depth,flat) if flat=1 (default) the structure is +% 'flattened' i.e. the field names in the first column are of the form: +% 'field.subfield' . +% +% If S is an array of struct's, C will be (N-by-2)-by-size(S) +% +% Example +% >> struct2list(ver,Inf,1) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-04-03 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<1 + error('No input!'); +end +if ~isstruct(S) + error('S should be a struct or a struct array!'); +end + +if nargin<2 + depth=0; +end +if nargin<3 + flat=1; +end +C=[]; +nS = numel(S); +f=fieldnames(S); +nf=numel(f); +for i_S=1:nS + D=[]; + c=struct2cell(S(i_S)); + for i=1:nf + fi = f(i); + x = c(i); + if depth + if isstruct(x{1}) + if flat + x = struct2list(x{1}, depth-1); + nsub=size(x,1); + if isempty(x) + fi = { fi{1} }; + x={[]}; + else + fi = [repmat([ fi{1} '.' ],nsub,1) strvcat(x(:,1))]; + fi = cellstr(fi); + x=x(:,2); + end + else + x = {struct2list(x{1}, depth-1)}; + end + end + end + D = [ D ; [fi x]]; + end + C=cat(3,C,D); +end +C=reshape(C, [ size(C,1) size(C,2) size(S)]); diff --git a/struct2minf.m b/struct2minf.m new file mode 100644 index 0000000..8724018 --- /dev/null +++ b/struct2minf.m @@ -0,0 +1,63 @@ +function [varargout]=struct2minf(x,minfname) +% struct2minf - converts a matlab struct into Brainvisa minf info +% +% [s]=struct2minf(x,minfname) +% +% Input: +% x : matlab structure +% [optional] fname: filename for output (e.g. 'toto.tex.minf') +% +% Output: +% [optional] s : character array + + +s=['attributes = {\n' ]; +ff=fieldnames(x); +nff=length(ff); +for iff=1:nff + f=getfield(x,ff{iff}); + s=[ s ' ''' ff{iff} ''' : ']; + if iscell(f) + s= [ s '[' ]; + for i=1:length(f) + if not(ischar(f{i})) + error(sprintf('%s: cannot print non character cell array!', mfilename)); + end + s=[ s '"' f{i} '" ' ]; + end + s= [ s ']' ]; + elseif ischar(f) + s=[ s '''' f '''']; + elseif isnumeric(f) + if length(f)>1 + s= [ s '[ ' ]; + for i=1:length(f) + s=[ s '''' num2str(f(i)) '''' ]; + if i1 + fid=fopen(minfname, 'wt'); + fprintf(fid,s); + fclose(fid); +end +if nargout>0 + varargout(1)={s}; +end +if nargout == 0 & nargin==1 + fprintf('%s\n', s) +end +return +% attributes = {'MinT': ['-0.256000'], 'MaxT': ['0.752000'], 'Trial': ['1']} diff --git a/struct2tab.m b/struct2tab.m new file mode 100644 index 0000000..efec51e --- /dev/null +++ b/struct2tab.m @@ -0,0 +1,155 @@ +function [s] = struct2tab(x,varargin) +% struct2tab - Print fields of structure into a text table +% [s] = struct2tab(x) +% [s] = struct2tab(x, 'headers', ['no']|'yes'|'only') + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-12 Creation +% +% ----------------------------- Script History --------------------------------- + + +% Not implemented yet: +% [s] = struct2tab(x, 'format', ['%30.5']|'no'|'only') + +options = parser(varargin{:}); + +headers=options.headers; +superfield=options.superfield; + +if headers == 1 + s=[struct2tab(x,options,'headers','only');struct2tab(x,options,'headers','no')]; + return +end + +s=[]; +fn = fieldnames(x); +for f=fn(:)' + if ~headers + if numel(x)>1 + for i=1:numel(x) + s=[s;struct2tab(x(i), varargin{:})]; + end + return + end + end + y=getfield(x(1), f{1}); + if iscell(y) + y=y{1} + end + if isstruct(y) + if headers + if ~isempty(superfield) + superfield = [superfield '.' ]; + end + t=struct2tab(y,'headers',[superfield f{1}]); + else + t=struct2tab(y,'headers','no'); + end + s=[repmat(s,size(t,1)) t]; + else + if headers + y = [f{1}]; + if ~isempty(superfield) + y = [superfield '.' y]; + end + y=y(max(1,end-29):end); + end + if isempty(y) + t = sprintf('%30.5f',0); + t = strrep(t, '0', ' '); + t = strrep(t, '.', ' '); + elseif isnumeric(y) + if numel(y)>1 + %t=[]; + %for i=1:numel(y) + %t = [t;sprintf('%30.5f',y(i));]; + %end + t = sprintf('%30s','...'); + elseif fix(y)==y + t = sprintf('%30d',y); + else + t = sprintf('%30.5f',y); + end + elseif ischar(y) + t = sprintf('% 30s',y); + elseif islogical(y) + if y + t = sprintf('% 30s','0'); + else + t = sprintf('% 30s','1'); + end + else + t = sprintf('% 30s','N/A'); + end + + + % s_fill = repmat(' ', max(0,size(t,1)-size(s,1)), size(s,2)); + % % Keeps tabs in filling + % s_fill(:,all(s==9))=9; + % t_fill = repmat(' ', max(0,size(s,1)-size(t,1)), size(t,2)) + s_fill = ''; + t_fill = ''; + s=[[s; s_fill] [t; t_fill]]; + s = [s repmat(sprintf('\t'), size(s,1),1)] ; + end +end + + +function options = parser(varargin) +% Parse options + +% default values +options.headers = 1; +options.superfield = []; +options.fieldwidth = 30; +options.fieldformat.char = []; +options.fieldformat.logical = []; +options.fieldformat.numeric = []; +options.arrays = '...'; +if nargin==0 + return +end +if isstruct(varargin{1}) + options = mergestruct(options,varargin{1}); + varargin(1)=[]; +end +na=length(varargin); +if mod(na,2) + error('Options must be specified in pairs: ''option'', value'); +end +na=na/2; +for i=1:na + va=varargin{2*i}; + switch lower(varargin{2*i-1}) + case 'headers' + if isequal(va,'yes') + options.headers = 1; + elseif isequal(va,'only') + options.headers = 2; + elseif isequal(va,'no') + options.headers = 0; + options.superfield = []; + else + options.headers = 2; + options.superfield = va; + end + case 'superfield' + options.superfield=va; + end +end + + +function s3 = mergestruct(s1,s2) +s3=s1; +f=fieldnames(s2); +for i=1:length(f) + s3=setfield(s3, f{i}, getfield(s2,f{i})); +end diff --git a/structcomparator.m b/structcomparator.m new file mode 100644 index 0000000..b69029c --- /dev/null +++ b/structcomparator.m @@ -0,0 +1,56 @@ +function h = structcomparator(A,B,varargin) +%STRUCTCOMPARATOR - One line description goes here. +% [] = structcomparator(input) +% +% Example +% >> structcomparator +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-07-28 Creation +% +% ----------------------------- Script History --------------------------------- +F=structdiff(A,B,varargin{:}); +for i=1:size(F,1) + a=[]; + b=[]; + if ~isempty(F{i,1}) + a=getfield2(A,F{i,1}); + fprintf('%s',F{i,1}) + end + fprintf(' | '); + if ~isempty(F{i,2}) + b=getfield2(B,F{i,2}); + fprintf('%s',F{i,2}) + end + fprintf('\n') + if isstruct(a) | isstruct(b) + disp(a) + disp(b) + elseif isequal(size(a,1),size(b,1)) + if isnumeric(a) & isnumeric(b) + fmt='%g '; + elseif ischar(a) & ischar(b) + fmt='%s '; + else + fmt='...'; + end + for i_row=1:size(a,1) + ta=sprintf(fmt, a(i_row,:)); + tb=sprintf(fmt, b(i_row,:)); + fprintf('%s | %s\n', ta, tb); + end + else + disp(a) + disp(b) + end + fprintf('\n'); +end \ No newline at end of file diff --git a/structdiff.m b/structdiff.m new file mode 100644 index 0000000..53f365b --- /dev/null +++ b/structdiff.m @@ -0,0 +1,139 @@ +function [varargout] = structdiff(X,Y,recursive,output) +%STRUCTDIFF - Compare structures and output differences +% [C] = structdiff(X,Y) list the fields that differ in a N-by-2 cell +% array. Fileds that are in X but not in Y appear only in the first +% column; fields of Y absent in X appear in the 2nd column; and fields +% that differ between X and Y appear in both columns +% +% Example +% >> structdiff(get(figure('name','a')),get(figure('name','b'))) +% +% [C] = structdiff(X,Y,r) +% if r== 0 (default) not recursive +% if r==Inf -> recursive +% if r==N -> max depth of recursion +% +% See also: getfield2 + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-07-17 Creation +% KND 2008-10-28 Changed format of output +% +% ----------------------------- Script History --------------------------------- +if nargin<3 + recursive=0; +end +if ~iscell(recursive) + recursive={recursive ''}; + %Internally, the 'recursive' argument is embedded in a cell, so as to + %pass the prefix (i.e. the "super.field") as the second element of it. +end +if length(X)>1 | length(Y)>1 + error('Cannot deal with struct arrays') +end + +x=fieldnames(X); +y=fieldnames(Y); +C=setdiff(x,y); +C=C(:); +n=length(C); +for i=1:n + C{i,1}=[recursive{2} C{i,1}]; + C{i,2}=[]; +end +A=setdiff(y,x); +for i=1:length(A) + C{n+i,1}=[]; + C{n+i,2}=[recursive{2} A{i}]; +end +clear A +%common fields +f=intersect(x,y); +for i=1:length(f) + x=getfield(X,f{i}); + y=getfield(Y,f{i}); + if recursive{1} && isstruct(x) && isstruct(y) + recursive{1} = recursive{1} - 1; + if length(x)== 1 && length(y)==1 + C=[C; structdiff(x,y,{1 [recursive{2} f{i} '.']})]; + elseif length(x)~= length(y) + C=[C; [recursive{2} f{i}]]; + elseif ~isequalwithequalnans(x,y) + for j=1:length(x) + if ~isequal(x(j),y(j)) + C=[C; structdiff(x(j),y(j),{recursive{1} ,[recursive{2} f{i} sprintf('(%d)', j) '.']})]; + end + end + end + else + if ~isequalwithequalnans(x,y) + C=[C; {[recursive{2} f{i}] [recursive{2} f{i}]}]; + end + end +end +if nargin>3 + for i=1:size(C,1) + a=[]; + b=[]; + if ~isempty(C{i,1}) + a=getfield2(X,C{i,1}); + fprintf('%s',C{i,1}) + end + fprintf(' | '); + if ~isempty(C{i,2}) + b=getfield2(Y,C{i,2}); + fprintf('%s',C{i,2}) + end + fprintf('\n') + if isstruct(a) | isstruct(b) + disp(a) + disp(b) + elseif isequal(size(a,1),size(b,1)) + if isnumeric(a) & isnumeric(b) %& numel(a)<100 & numel(b)<100 + fmt='%g '; + elseif ischar(a) & ischar(b) + fmt='%s '; + elseif ischar(a) & ischar(b) + + else + a=' ';b=' '; + fmt='...'; + end + for i_row=1:size(a,1) + ta=sprintf(fmt, a(i_row,:)); + tb=sprintf(fmt, b(i_row,:)); + fprintf('%s | %s\n', ta, tb); + end + else + disp(a) + disp(b) + end + fprintf('\n'); + end +end + +if nargout>1 + varargout = {C}; +else + n=size(C,1); + D=cell(n,3); + disp(C) + for j=1:n + D(j,1) = unique(C(j,~cellfun('isempty', C(j,:)))'); + if ~isempty(C{j,1}) + getfield(X, D{j,1}) + D{j,2} = getfield(X, D{j,1}); + end + if ~isempty(C{j,2}) + D{j,3} = getfield(Y, D{j,1}); + end + end + varargout = {D}; +end diff --git a/structmatch.m b/structmatch.m new file mode 100644 index 0000000..8a7de3e --- /dev/null +++ b/structmatch.m @@ -0,0 +1,143 @@ +function [V,I,MK] = structmatch(D,H,K,W) +%STRUCTMATCH - Generic lookup function for structure arrays +% +% [VALUES] = structmatch(DATA,HASHKEY,KEY) will retrieve all elements +% from the structure DATA whose field HASHKEY match the value(s) in KEY +% (according to regexp). HASKEY can also be the index in the fieldname list. +% +% [VALUES] = structmatch(DATA,HASHKEY) will retrieve all elements from +% the structure DATA whose field HASHKEY is true (will be converted to +% logical if needed) +% +% [VALUES,INDICES] = structmatch(...) also outputs the logical indices of +% the matching elements from the structure +% +% [...] = structmatch(DATA,HASHKEY,KEY,WHAT) will only retrieve from +% the matching elements, the field indexed by WHAT +% If WHAT == NaN (default), retrieves all data +% If WHAT == 0, retrieves logical indices, see just below. +% If WHAT == N, retrieves indices of N>0 first matches. +% If WHAT == Inf, retrieves indices of all matches. +% +% [TF] = structmatch(DATA,HASHKEY,KEY,0) will only retrieve logicals +% of the same size as DATA with 1's where elements match the KEY +% +% [...] = structmatch(DATA,HASKEY,FUN) uses function handle FUN to make +% the match (the result FUN is converted into a logical). +% +% [VALUES,INDICES,MATCHINGKEYS] = structmatch(...) will also output the +% names of the fields used as hashkeys (e.g., if HASHKEY was input as the +% numerical index of the field in the structure) +% +% Examples +% >> structmatch(dir(pwd),'bytes',@(X)X>10000,'name') +% will list the name of the files from the current directory whose +% size is > 100 bytes (See help on dir and function_handle) +% +% >> structmatch(dir,'date',@(D)datenum(D)>now-7,'name')' +% will list the name of the files from the current directory which +% are earlier than 7 days +% +% >> findobj('type','fig') +% >> close(ans(structmatch(get(findobj('type','fig')),'Name',@isempty,0))) +% will close all open figures whose Names are empty. +% +% See also: strmatch, structcmp, function_handle + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-28 Creation +% KND 2008-11-05 Bug with nargin=3; +% KND 2009-07-24 Bug: structmatch(dir(pwd),4,1) +% KND 2009-11-05 Logical indices & Error checking +% +% ----------------------------- Script History --------------------------------- + +%warning('bug with: structmatch(dir(pwd),4,1)') +if ~ isstruct(D) + error('Input must be a structure array') +end +if nargin<4 + %retrieve all fields of the matching elements from the structure + W=NaN; +end +if nargin<3 + %retrieve all fields of the matching elements from the structure + K=[]; +end +if ischar(H) + if isfield(D,H) + HK={D.(deblank(H))}; + else + error('Unknown hashkey: %s is not a field of the structure', H); + end +elseif isnumeric(H) + FN=fieldnames(D); + if H<1 || H > numel(FN) + error('Requiring field #%d in structure that contains only %d fields!', H, numel(FN)); + end + H=FN{H}; + HK={D.(deblank(H))}; +end +% Find indices of the elements matching the key +if isempty(K) + I=cell2mat(HK); +elseif isa(K, 'function_handle') + [I]=cell2mat(cellfun2(K,HK)); + % elseif isnumeric(K) + % [I]=ismember(cell2mat(HK),K); + % this doesn't work... + % indeed if any empty value, result is shifted... + % eg: a=dir;b=a;b(3).bytes=[];structmatch(a,3,a(4).bytes) + % +elseif ischar(K) % reg exp + %[I]=ismember(HK,K); + [I]=not(cellfun('isempty',regexp(HK,K))); +else + I=logical(zeros(size(HK))); %#ok + for i=1:numel(HK) + if isequal(K,HK{i}) + I(i)=1; + end + end + %error('STRUCTMATCH:WrongKey','Wrong input: KEY'); +end +% Output matching keys, if user wants them +if nargout>2 + MK=HK(I); +end +if isequal(W,0) + V = I; + return +end +if ~isnan(W) & isnumeric(W) + V = find(I,W); + return +end + +% Filter matching elements +V=D(I); +if ~isnan(W) + V ={V.(deblank(W))}; +else + % output the whole struct as V +end + + +function [y] = cellfun2(fun, x) +% cellfun() - Cap funtion for cellfun which accepts any function call +% +% Y = CELLFUN(FUN, C) applies function FUN to the cells of C +% +%See also: cellfun +y = cell(size(x)); +for i=1:numel(x) + y{i} = feval(fun, x{i}); +end +return; diff --git a/subarray.m b/subarray.m new file mode 100644 index 0000000..7efd89d --- /dev/null +++ b/subarray.m @@ -0,0 +1,150 @@ +function [Y,S]=subarray(X,varargin) +% subarray - Retrieves subparts from a ND-array using subscripted reference +% +% [Y,S]=subarray(X,idx,dim) +% [Y]=subarray(X,idx1,dim1,idx2,dim2,...) +% [Y]=subarray(X,{idx1,dim1,idx2,dim2,...}) or {idx{:};dim{:}} +% Retrieves Y a subpart of a N-dimension array X based on subscripted +% references specified in inputs idx and dim (see below) +% +% INPUTS: +% X: a ND-array +% idx: indices of values to retrieve in the given dimension +% If negative indices start from the end +% E.g. 0 is the last element in the dimension, -1 the one before etc. +% Indices can also be specified as logical. +% dim: dimension on which the operation is done +% Default: dim = first non-singleton. So that, if X is a vector, +% subarray(X,n) outputs the n-th element of it. +% * if dim<0: remove the subpart and output the remainder +% * if dim=+Inf or -Inf, then output the given elements after +% vertical vector reshaping (i.e. using linear indexing). +% If the same dimension is specified in multiple places only the +% last one will be taken into account. +% If other dimensions are specified along with Inf, an error will +% ensue. +% Dimensions need not to be specified in any specific ordered. +% +% OUTPUTS: +% Y: a multiple dimension array depending on the given inputs. +% S: a structure that can be used in a call with SUBSREF to +% output Y from X. However, if Inf has been used as a dimension +% specifier, S cannot be output. +% +% Examples using matrix M = magic(3) +% >> subarray(M,1) retrieves the first row of matrix M +% >> subarray(M,[3 2],2) retrieves the 3rd and 2nd columns of M (in that +% order) +% >> subarray(M,1,5) retrieves the whole matrix M since M has less than 5 +% dimensions +% >> subarray(M,1,-2) retrieves all but the first column of M +% >> subarray(M,1,-2,2,1) is equivalent to M(2,[2 3]) (but this wouldn't +% be equivalent if M had more than 2 dimensions) +% >> subarray(M,0,1) retrieves the last line of M +% >> subarray(M,2,Inf) retrieves the 2nd element of M(:) +% >> subarray(M,[-1 -2],-Inf) retrieves all but the second-to-last and +% next-to-last elements of M(:) +% >> subarray(M,[false true true],2) retrieves the 2nd and 3rd columns +% +% +% Note: This function is useful when one doesn't know the number of +% dimensions of X. E.g. to retrieve the 3rd and 4th "line" of the 2nd +% dimension of a ND array (say, X is 4-by-5-by-3-by-...) +% >> subarray(X,[3 4] ,2) +% outputs a 4-by-[2]-by-3-by-... array +% +% See also: SUBSREF + +% Author: K. N'Diaye, kndiaye01yahoo.fr +% Copyright (C) 2007 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html + +% Version 1.0 +% ----------------------------- Script History ---------------------------- +% KND 2007-05-22 Published on Matlab Central +% KND 2007-10-28 Allows logical indexing +% KND 2009-02-26 Consistent behaviour with multiple "Inf"'s used as dim +% KND 2009-11-12 Corrected bug when any dim > ndims +% ----------------------------- Script History ---------------------------- + + +sx=size(X); +if nargin<2 + Y=X; + return; %previously error('No indices given!') +elseif nargin>2 + inputs=varargin; + if rem(nargin-1,2) + error('Indices & dimensions should be given in pairs') + end +else + if iscell(varargin{1}) + % when a single cell is given as an input, + inputs=varargin{1}(:)'; + else + % when no dimension is specified use the first non-singleton + inputs=varargin(1); + dim=[find(sx>1) 1]; + inputs{2}=dim(1); + end +end +% inputs should be split in indices and dimensions +idx=inputs(1:2:end); +dim=[inputs{2:2:end}]; +%indiced in dimensions that are negative will behave as "excluders" +exclude=logical(dim<0); +dim=abs(dim); +% if length(unique(dim))1 & isinf(dim) + error('Structure S cannot be output when using Inf as dimension'); +end +return diff --git a/subdir.m b/subdir.m new file mode 100644 index 0000000..6a4e6a4 --- /dev/null +++ b/subdir.m @@ -0,0 +1,26 @@ +function [D]=subdir(DN) +% subdir() - Process DIR command across subdirectories +% [output] = subdir(directory_name) +if nargin==0 + DN=pwd; +end +[p0,n,e]=fileparts(DN); +if isempty(p0) + p0=pwd; +end +p=strread(genpath(p0), '%s', 'delimiter', ';'); +D=[]; +for i=1:length(p) + f=dir(fullfile(p{i}, [n e])); + for j=1:length(f); + f(j).name=fullfile(p{i}, f(j).name); + end + D=[D; f]; +end +if nargout==0 + if ~isempty(p0) + cd(p0) + end + D=strvcat({D.name}); +end + \ No newline at end of file diff --git a/subjectimage2spmvol.m b/subjectimage2spmvol.m new file mode 100644 index 0000000..43daf7f --- /dev/null +++ b/subjectimage2spmvol.m @@ -0,0 +1,49 @@ +function [v,y]=subjectimage2spmvol(imagefile) +% subjectimage2spmvol - converts Brainstorm subjectimage to SPM volume +% [V,Y]=subjectimage2spmvol(imagefile) +% +% See also: spm_vol, spm_read_vol +if nargin<1 + imagefile=spm_get(1,'*subjectimage.mat',... + 'Choose a subjectimage'); +end + +m=load(imagefile); + +% Create volume +v.fname=imagefile; +TYPE=2; +v.dim=[size(m.Cube) TYPE]; +% Translation (origin) +% T=[0 ; 0 ; 0]; +% v.mat=[ diag(m.Voxsize) T; zeros(1,3) 1]; + +% v.mat=m.mat; + +% Orientation in SubjecTImage is in CTF referential, thats not what we +% want: we would prefere it in the MRI referential +% Anyhow, we drop SCS info... +% if isfield(m, 'SCS') +% iSCS=strmatch('ctf', lower({m.SCS.System})); +% if isfield(m.SCS(iSCS), 'R') & isfield(m.SCS(iSCS), 'T') +% v.mat=[ m.SCS(iSCS).R m.SCS(iSCS).T ; zeros(1,3) 1 ]; +% v.mat=v.mat([2 1 3 4],:); +% end +% else +% warning('No SCS in subjectimage.') + +v.mat=diag([-1 1 1 1]); +% i.e. origin is at: v.mat(:,4) = [ 0 0 0 ]' + +% end + +v.pinfo=[1 ; 0 ; 0 ]; % Slice info: intensity scale & offset and bytes offset +v.n=1; +v.descrip='Imported from BrainStrom Image'; + +if nargout>1 + y=m.Cube; +end + + + diff --git a/subpatch.m b/subpatch.m new file mode 100644 index 0000000..41475d1 --- /dev/null +++ b/subpatch.m @@ -0,0 +1,10 @@ +function [fv2]=subpatch(fv,idx) +% subpatch - Sub part of a patch struct +% [fv2]=subpatch(fv,idx) where idx are the indices of the subpatch +fv2.vertices=fv.vertices(idx,:); +fv2.faces=[]; +for i=1:size(fv.faces,1) + if all(ismember(fv.faces(i,:), idx)) + fv2.faces=[fv2.faces; find(fv.faces(i,1)==idx) find(fv.faces(i,2)==idx) find(fv.faces(i,3)==idx) ]; + end +end diff --git a/subsasgn2.m b/subsasgn2.m new file mode 100644 index 0000000..4331af5 --- /dev/null +++ b/subsasgn2.m @@ -0,0 +1,96 @@ +function X = subsasgn2(X,v,varargin) +%SUBSASGN2 - User-friendlier subscripted assignment. +% [Y] = subsasgn2(X,v,i,dim) outputs array Y where some values in X have +% been replaced by the value given in v +% +% Example +% >> subsasgn(magic(5),0,3,2) set the 3rd column to 0 +% NaN's +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2010 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2010-04-21 Creation +% +% ----------------------------- Script History --------------------------------- + +sx=size(X); +if nargin<2 + return; %previously error('No indices given!') +elseif nargin>2 + inputs=varargin; + if rem(nargin-1,3) + error('Indices & dimensions should be given in triplets') + end +else + if iscell(varargin{1}) + % when a single cell is given as an input, + inputs=varargin{1}(:)'; + else + % when no dimension is specified use the first non-singleton + inputs=varargin(1); + dim=[find(sx>1) 1]; + inputs{2}=dim(1); + end +end +% inputs should be split in indices and dimensions +idx=inputs(1:2:end); +dim=[inputs{2:2:end}]; +%indiced in dimensions that are negative will behave as "excluders" +exclude=logical(dim<0); +dim=abs(dim); +% if length(unique(dim))1 & isinf(dim) + error('Structure S cannot be output when using Inf as dimension'); +end +return \ No newline at end of file diff --git a/sumnan.m b/sumnan.m new file mode 100644 index 0000000..3ec3906 --- /dev/null +++ b/sumnan.m @@ -0,0 +1,45 @@ +function [y,nans]=sumnan(x,dim) +%SUMNAN Sum once NaN values have been removed +% [y,nans]=sumnan(x,dim) +% +% If dim is negative +% Do not include data if any NaN found along the dimension +% +% Example: +% a = cat(3,magic(5), cumsum(ones(5)));a([3 35])=NaN +% sumnan(a,1) +% sumnan(a,-2) +% see mean() for details + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-22 Creation +% +% ----------------------------- Script History --------------------------------- + + +if nargin==1, + dim = min(find(size(x)~=1)); + if isempty(dim), dim = 1; end +end +nans=isnan(x); +if dim < 0 + dim=-dim; + otherdims = setdiff(1:ndims(x),dim); + permdims = [dim otherdims]; + nans=permute(nans,permdims); + nans(any(nans(:,:),2),:)=1; + nans=ipermute(nans,permdims); +end +x(nans)=0; +nans=double(nans); +y = sum(x,dim); +if nargin>1 + nans=logical(nans); +end \ No newline at end of file diff --git a/system1020.m b/system1020.m new file mode 100644 index 0000000..8080415 --- /dev/null +++ b/system1020.m @@ -0,0 +1,5 @@ +divch2=setdiff(divch, [9 19]) +xyz=getChannelLocs(eegch(divch2)); +mass=median(xyz) +R0 = mean(norlig(xyz - ones(62,1)*mass)); % Average distance between the center of mass and the scalp points +[SphereParams,brp] = fminsearch('dist_sph',[median(xyz) R0],[],xyz) diff --git a/tabread.m b/tabread.m new file mode 100644 index 0000000..09beeb0 --- /dev/null +++ b/tabread.m @@ -0,0 +1,61 @@ +function [A,B,N]=tabread(file,varargin) +% tabread - reads tabulated data NOT IMPLEMENTED YET + + +% [X,N]=tabread(file) +% [X,N]=tabread(file,'headerlines', ... , 'delimiter', ...) +% +% Reads tabultaed data, where the field names are in the first +% column. N is a cell of field names, X is the rest of the +% (numerical) values + +% error('NOT IMPLEMENTED YET') + +if nargin>2 + Options=struct(varargin{:}); +else + Options=[]; +end + +if not(isfield(Options, 'skiplines')) + Options.skiplines=0; +end + +if not(isfield(Options, 'headerlines')) + Options.headerlines=false; +end + +if not(isfield(Options, 'delimiters')) + Options.delimiter='\t '; +end +% Options.delimiter=[Options.delimiters{:}]; + +if not(isfield(Options, 'deblank')) + Options.deblank=1; +end + +fid=fopen(file, 'rt'); +for i=1:Options.skiplines + fgetl(fid); +end +ok = 1; +i=1; +N={}; +X=[]; +sx=0; +while not(feof(fid)) && ok + t=fgetl(fid); + if not(isempty(t)) + t=strread(t, '%s', 'delimiter', Options.delimiter); + N{i,1}=t{1}; + sx=size(X,2); + X(i,:)=str2num(strvcat(t(2:end)))'; + if sx>0 & size(X,2)>sx + warning('Zero-padding due to non rectangular data!') + + end + i=i+1; + end + +end + \ No newline at end of file diff --git a/template.m b/template.m new file mode 100644 index 0000000..4b080ca --- /dev/null +++ b/template.m @@ -0,0 +1,62 @@ +function = $filename(input,varargin) +%$FILENAME - One line description goes here. +% [] = $filename(input) +% +% Example +% >> $filename +% +% See also: + +% Author: K. N'Diaye (kndiaye01gmail.com) +% Copyright (C) $date(yyyy) +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND $date(yyyy-mm-dd) Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + error('No data!') +elseif nargin==1 || isnumeric(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + + +function [ha]=action_init(data, varargin) +% ------------------------------------------------------------------------- +% Check OPTIONS and default values when optional arguments are not +% specified +Def_OPTIONS = struct(... + 'option1',[],... + ); +if nargin < 2 + OPTIONS = Def_OPTIONS; +else + if length(varargin)>1 + OPTIONS = cell2struct(varargin(2:2:end),varargin(1:2:end),2); + % struct(varargin{:}) bugs with something like {'string1' 'string2'} in the inputs! + else + OPTIONS = varargin{1}; + end + % Check field names of passed OPTIONS and fill missing ones with default values + DefFieldNames = fieldnames(Def_OPTIONS); + for k = 1:length(DefFieldNames) + if ~isfield(OPTIONS,DefFieldNames{k}) + OPTIONS = setfield(OPTIONS,DefFieldNames{k},getfield(Def_OPTIONS,DefFieldNames{k})); + end + end + clear DefFieldNames +end +clear Def_OPTIONS +% ------------------------------------------------------------------------- diff --git a/tess2patch.m b/tess2patch.m new file mode 100644 index 0000000..a8f9f92 --- /dev/null +++ b/tess2patch.m @@ -0,0 +1,23 @@ +function [fv]=tess2patch(tess) +% tess2patch - convert Brainstorm tessellation to FV structure +% [fv]=tess2patch(tess) +% [fv]=tess2patch('xxx_tess.mat') +% NB: On FV structures, see REDUCEPATCH +if nargin<1 + [f,p]=uigetfile; + if isempty(f) + return + end + tess=fullfile(p,f) +end + +if ischar(tess) + if exist(tess, 'file') | exist([tess '.mat'], 'file') + tess=load(tess, 'Faces', 'Vertices'); + end +end + +for i=1:length(tess.Faces) + fv(i).faces=tess.Faces{i}; + fv(i).vertices=tess.Vertices{i}'; +end diff --git a/tex_clusters.m b/tex_clusters.m new file mode 100644 index 0000000..7d81514 --- /dev/null +++ b/tex_clusters.m @@ -0,0 +1,110 @@ +function [clu,clu2,tex2]=tex_clusters(tex, vc, sx, tx,VERBOSE) +% tex_clusters - find clusters of a given extant on a texture +% +% [clu]=tex_clusters(tex, vc) +% [clu,clu2,tex2]=tex_clusters(tex, vc, sx, tx) +% +% Lists clusters of a texture, given a minimal size in space and time +% (i.e. at least [sx] connected vertices must be active during at +% least [tx] time sample for the cluster to be kept +% +%INPUTS: +% tex: [M-by-T] texture of logical values (0=not active) on a N-vertices mesh during T time samples +% vc: vertex connectivity of the mesh or adjacency matrix +%OPTIONAL INPUTS: +% sx: minimum spatial extant (default: 1) +% tx: minimum temporal extant (default: 1) +%OUTPUT: +% clu: cluster list, a cell array of vertex indices matchin the criteria +% clu2: time dependent new texture with 1's +% + + +% See also: dmperm + +% http://delivery.acm.org/10.1145/100000/98287/p303-pothen.pdf?key1=98287&key2=1613996311&coll=GUIDE&dl=GUIDE&CFID=65251534&CFTOKEN=21051873 + +DEBUG=0; +if nargin<5 + VERBOSE=1; +end +if nargin<4 + tx=1; +elseif tx>0 + warning('No temporal filtering yet!'); +end +if nargin<3 + sx=1; +end +if nargin<2 + error('Not enoug arguments'); +end + +nv=size(tex,1); +nt=size(tex,2); + +if length(vc) ~= nv + error('Connectivity and number of vertices in the texture don''t match') +end + +if iscell(vc) + A=vertconn2adjacency(vc); +else + A=vc; +end + +A=(A|speye(size(A))); +if VERBOSE + h = timebar('Spatial extent','Progress'); +end +C={}; +for it=1:nt + f=double(tex(1:nv,it)); + B=A; + % NaN values + f(isnan(f))=0; + + % Remove OFF vertices + B(~f,:)=0; + B(:,~f)=0; + + % Compute clusters + [p,q,r,s] = dmperm(B); + nc=0; % number of cluster at this time sample + sr=diff(r); % compute size of clusters + [ignore,rr]=sort(-sr); % sort clusters by decreasing size + for i=1:length(r)-1 + if r(rr(i))=sx % == it passes the spatial threshold + nc=nc+1; + C{it}{nc}=p(r(rr(i)):r(rr(i)+1)-1); + end + end + if VERBOSE + try;timebar(h,(i+(it-1)*length(r))/(nt*length(r)));end; + end + end + + +end +if VERBOSE + try;close(h);end +end +% Post process for time continuity +% + +clu=C; + +if nargout>1 + clu2=sparse(nv,nt); + for it=1:nt + for i=1:length(clu{it}) + clu2(C{it}{i},it)=i; + end + end +end + +return diff --git a/textalign.m b/textalign.m new file mode 100644 index 0000000..72e8c51 --- /dev/null +++ b/textalign.m @@ -0,0 +1,38 @@ +function A = textalign(A,alignment) +%TEXTALIGN - One line description goes here. +% [B] = textalign(A, 'left'|'right'|'center') +% +% Example +% >> textalign +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-09-15 Creation +% +% ----------------------------- Script History --------------------------------- + +CharOutput = false; +szA = size(A); +if ~iscell(A) + CharOutput = true; + A = cellstr(A); +end +for i=1:numel(A) + A{i} = fliplr(A{i}); +end +A = strvcat(A); +A = fliplr(A); +if ~CharOutput + A = cellstr(A); + A = reshape(A,szA); +end +return +B=fliplr(deblank(fliplr(A))); \ No newline at end of file diff --git a/threshold.m b/threshold.m new file mode 100644 index 0000000..a7a6aed --- /dev/null +++ b/threshold.m @@ -0,0 +1,19 @@ +function [ y ] = threshold( x , thd , mode , replace ) +% threshold - thresholds an array and replace values under threshold +% [ y ] = threshold( x , thd , mode , replace ) +% x: array +% thd: value of threshold +% mode: 'value' | '%max' | '%nb' +% threshold on value (keeps x>thd) +% relative to the max (x > thd*x_max) +% percentage of number thd% most intense +if nargin < 3 + mode='value'; +end +if nargin < 4 + replace=0; +end +y=x; +switch mode + case 'value' + y(x<=thd \ No newline at end of file diff --git a/tiedrank.m b/tiedrank.m new file mode 100644 index 0000000..0d89aaf --- /dev/null +++ b/tiedrank.m @@ -0,0 +1,26 @@ +function [r,ta]=tiedrank(X,dim) +%tiedrank - Tied rank of each element in a set +% [r]=tiedrank(X,dim) +% Computes tied rank of each element of X along given dimension +% (default is to use the first non-singleton dimension) +% "Tied ranking" is such that ex-aequo elements share the same (possibly +% half) rank: +% >> tiedrank(['DABBC']) %-> 6 1 2.5 2.5 4 +if nargin<2 + dim=min(find(size(X)>1)); + if isempty(dim) + error('X is empty!') + end +end +[ignore,Y]=sort(X,dim); +[ignore,r1]=sort(Y,dim); +[ignore,Y]=sort(-X,dim); +[ignore,r2]=sort(Y,dim); +r2=size(X,dim)-r2+1; +r=(r1+r2)/2; +if nargout > 1 + warning('Tier adjustments not computed yet!'); + + % Tie adjustment... + ta=0; +end diff --git a/tiedrank2.m b/tiedrank2.m new file mode 100644 index 0000000..0d89aaf --- /dev/null +++ b/tiedrank2.m @@ -0,0 +1,26 @@ +function [r,ta]=tiedrank(X,dim) +%tiedrank - Tied rank of each element in a set +% [r]=tiedrank(X,dim) +% Computes tied rank of each element of X along given dimension +% (default is to use the first non-singleton dimension) +% "Tied ranking" is such that ex-aequo elements share the same (possibly +% half) rank: +% >> tiedrank(['DABBC']) %-> 6 1 2.5 2.5 4 +if nargin<2 + dim=min(find(size(X)>1)); + if isempty(dim) + error('X is empty!') + end +end +[ignore,Y]=sort(X,dim); +[ignore,r1]=sort(Y,dim); +[ignore,Y]=sort(-X,dim); +[ignore,r2]=sort(Y,dim); +r2=size(X,dim)-r2+1; +r=(r1+r2)/2; +if nargout > 1 + warning('Tier adjustments not computed yet!'); + + % Tie adjustment... + ta=0; +end diff --git a/tilefigs.m b/tilefigs.m new file mode 100644 index 0000000..4905bc2 --- /dev/null +++ b/tilefigs.m @@ -0,0 +1,98 @@ +function tilefigs(figs) +%TILEFIGS Tile all open figure windows around on the screen. +% +% TILEFIGS places all open figure windows around on the screen with no +% overlap. +% +% TILEFIGS(FIGS) can be used to specify which figures that should be +% tiled. Figures are not sorted when specified. +% +% See also SORTFIGS, CYCLEFIGS. + +% Author: Peter J. Acklam +% Time-stamp: 2003-10-13 15:40:11 +0200 +% E-mail: pjacklam@online.no +% URL: http://home.online.no/~pjacklam + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Get the handles to the figures to process. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if ~nargin % If no input arguments... + figs = findobj('Type', 'figure'); % ...find all figures. + figs = sort(figs); +end + +if isempty(figs) + disp('No open figures or no figures specified.'); + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% The elements in the vector specifying the position. +% 1 - Window left position +% 2 - Window bottom position +% 3 - Window horizontal size +% 4 - Window vertical size +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +%hspc = 20; % Horisontal space. +%topspc = 20; % Space above top figure. +%medspc = 20; % Space between figures. +%botspc = 40; % Space below bottom figure. +% +%units = 'pixels'; + +hspc = 0.02; % Horisontal space. +topspc = 0.02; % Space above top figure. +medspc = 0.02; % Space between figures. +botspc = 0.05; % Space below bottom figure. + +units = 'normalized'; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Set miscellaneous parameter. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +nfigs = length(figs); % Number of figures. + +nh = ceil(sqrt(nfigs)); % Number of figures horisontally. +nv = ceil(nfigs / nh); % Number of figures vertically. + +nh = max(nh, 2); +nv = max(nv, 2); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Get the screen size. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +old_root_units = get(0, 'Units'); % Get current root units. +set(0, 'Units', units); % Set root units. +scrdim = get(0, 'ScreenSize'); % Get screen size. +set(0, 'Units', old_root_units); % Reset units. +scrwid = scrdim(3); % Screen width. +scrhgt = scrdim(4); % Screen height. + +figwid = (scrwid - (nh + 1) * hspc) / nh; +fighgt = (scrhgt - (topspc + botspc) - (nv - 1) * medspc) / nv; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% Put the figures where they belong. +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +for row = 1 : nv + for col = 1 : nh + idx = (row - 1) * nh + col; + if idx <= nfigs + figlft = col * hspc + (col - 1) * figwid; + figbot = scrhgt - topspc - row * fighgt - (row - 1) * medspc; + figpos = [ figlft figbot figwid fighgt ]; % Figure position. + fighnd = figs(idx); % Figure handle. + old_fig_units = get(fighnd, 'Units'); % Get current units. + set(fighnd, 'Units', units); % Set new units. + set(fighnd, 'OuterPosition', figpos); % Set position. + set(fighnd, 'Units', old_fig_units); % Reset units. + figure(fighnd); % Raise figure. + end + end +end \ No newline at end of file diff --git a/tiles.m b/tiles.m new file mode 100644 index 0000000..1b12d1e --- /dev/null +++ b/tiles.m @@ -0,0 +1,44 @@ +function [T,idx]=tiles(A,C) +% tiles - extract subparts (a.k.a tiles or blocks) of a matrix +% [T,idx]=tiles(A,C) +% Cuts N-dimensional matrix A into pieces and extract them as a cell array of tiles +% C is a N-by-1 vector defining how each dimension of A is cut +% +%See also: tilesperm, subarray + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-04 Updated comments & help +% +% ----------------------------- Script History --------------------------------- + +S=size(A); +if ndims(A)>2 + error('Cannot process matrices with more than 2 dimensions'); +end +C=[C ones(1,max(0,length(S)-length(C)))]; +if any(C(length(S)+1:end)~=1) + error('Cuts cannot be made along those dimensions'); +end +if any(C>S) + error('Cuts cannot be made along those dimensions'); +end +%number of tiles +NT=prod(C); +T={}; +idx={}; +n1=ceil(S(1)/C(1)); +n2=ceil(S(2)/C(2)); + +for i1=1:C(1) + for i2=1:C(2) + T = [T { A( (1+(i1-1)*n1):min(S(1),i1*n1) , (1+(i2-1)*n2):min(S(2),i2*n2) )}]; + % idx = [idx { sub2ind(S, (1+(i1-1)*n1):min(S(1),i1*n1) , (1+(i2-1)*n2):min(S(2),i2*n2)) }]; + end +end \ No newline at end of file diff --git a/tilesperm.m b/tilesperm.m new file mode 100644 index 0000000..da299dd --- /dev/null +++ b/tilesperm.m @@ -0,0 +1,54 @@ +function [B,tp]=tilesperm(A,C,tp) +% Permute blocks (or tiles) of a rectangular matrix (e.g. image) +% +% B = tilesperm(A,C) will be a matrix of the same size as A but wherein +% rectangular block (tiles) have been randomly permuted +% +%INPUTS: +% A: original matrix (e.g. image) +% C = [v h]: number of tiles [vertically horizontally] +% +% [B,tp] = tilesperm(A,C[,tp]) +% tp: is the permutation table, it can be given as a 3rd argument. +% If not given or empty, a random permutation table is generated at +% runtime. +% +%See also: tiles, subarray, imgfilt + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-09-04 Updated comments & help +% +% ----------------------------- Script History --------------------------------- + +if nargin<3 + tp=[]; +end + +S=[size(A) 1]; +AA=A; +B=zeros(S,class(A)); + +for i3=1:S(3) + A=AA(:,:,i3); + [T]=tiles(A,C); + t=cellfun('prodofsize', T); + t=t==prod(size(T{1})); + if isempty(tp) + tp=randperm(sum(t)); + end + T(t)= subarray(T(t),tp,Inf); + n1=ceil(S(1)/C(1)); + n2=ceil(S(2)/C(2)); + for i1=1:C(1) + for i2=1:C(2) + B( (1+(i1-1)*n1):min(S(1),i1*n1) , (1+(i2-1)*n2):min(S(2),i2*n2) , i3 ) = T{ (i1-1)*C(2) + i2 }; + end + end +end \ No newline at end of file diff --git a/timebar.m b/timebar.m new file mode 100644 index 0000000..c07d4df --- /dev/null +++ b/timebar.m @@ -0,0 +1,215 @@ +function h = timebar(message,name,update_rate) +% TIMEBAR Progress bar with estimated time remaining +% H = TIMEBAR('message','name') creates and displays a progress +% bar with alphanumeric progress percentage and estimated time +% time remaining. A user input message ('message') is displayed, +% typically to distinguish what process is being monitored, and +% 'name' is an optional figure name. The figure handle H is +% returned. +% +% TIMEBAR(H,X) will update the length of the progress bar, the +% percentage complete, and the estimated time remaining, where +% X is a fractional progress between 0 (initial) and 1 (complete). +% (Note that the order of H,X is opposite to waitbar.) +% +% TIMEBAR(H,X,RATE) will update the progress bar and information +% at a rate given by RATE in seconds. Default is 0.1 seconds. +% +% The estimated time remaining is linear using the initial time +% (when TIMEBAR is first opened), the current time, and the percent +% complete. +% +% TIMEBAR is typically used inside a FOR loop or during numerical +% simulation. A sample for loop is shown below: +% +% h = timebar('Loop counter','Progress') +% for i = 1:100 +% % computation here % +% timebar(h,1/100) +% end +% close(h) +% +% A sample for numerical integration is shown below: +% +% % script file +% t0 = 0; +% tf = 60; +% h = timebar('Simulation integration','Progress') +% [tt,xx] = ode45('states.m',[t0 tf],initial_conditions); +% close(h) +% +% % states.m +% function xdot = states(t,x) +% xdot(1) = ...; +% xdot(2) = ...; +% ... +% timebar(h,(t-t0)/(tf-t0)) +% +% Version: 2.0 +% Version History: +% 1.0 2002-01-18 Initial release +% 2.0 2002-01-21 Added update rate option +% +% Copyright 2002, Chad English +% cenglish@myrealbox.com + +% KND: added '%' sign +% KND: no message needed + + +if nargin < 3 % If update rate is not input + update_rate = 0.1; % set it to 0.1 seconds +end +if nargin == 0 + message = [evalin('caller', 'mfilename') '@' datestr(now)]; +end +if ~ishandle(message) % If first input is not a timebar handle, + % treat as new timebar + + %%%%%%%%%% SET WINDOW SIZE AND POSITION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + winwidth = 300; % Width of timebar window + winheight = 75; % Height of timebar window + screensize = get(0,'screensize'); % User's screen size [1 1 width height] + screenwidth = screensize(3); % User's screen width + screenheight = screensize(4); % User's screen height + winpos = [0.5*(screenwidth-winwidth), ... + 0.5*(screenheight-winheight), winwidth, winheight]; % Position of timebar window origin + + %%%%%%%% END SET WINDOW SIZE AND POSITION %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%%%%%%%% OPEN FIGURE AND SET PROPERTIES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if nargin < 2 + name = ''; % If timebar name not input, set blank + end + + wincolor = 0.75*[1 1 1]; % Define window color + est_text = 'Remaining time (est.): '; % Set static estimated time text + + h = figure('menubar','none',... % Turn figure menu display off + 'numbertitle','off',... % Turn figure numbering off + 'name',name,... % Set the figure name to input name + 'position',winpos,... % Set the position of the figure as above + 'color',wincolor,... % Set the figure color + 'resize','off',... % Turn of figure resizing + 'tag','timebar'); % Tag the figure for later checking + + userdata.text(1) = uicontrol(h,'style','text',... % Prepare message text (set the style to text) + 'pos',[10 winheight-30 winwidth-20 20],... % Set the textbox position and size + 'hor','center',... % Center the text in the textbox + 'backgroundcolor',wincolor,... % Set the textbox background color + 'foregroundcolor',0*[1 1 1],... % Set the text color + 'string',message); % Set the text to the input message + + userdata.text(2) = uicontrol(h,'style','text',... % Prepare static estimated time text + 'pos',[10 5 winwidth-20 20],... % Set the textbox position and size + 'hor','left',... % Left align the text in the textbox + 'backgroundcolor',wincolor,... % Set the textbox background color + 'foregroundcolor',0*[1 1 1],... % Set the text color + 'string',est_text); % Set the static text for estimated time + + userdata.text(3) = uicontrol(h,'style','text',... % Prepare estimated time + 'pos',[135 5 winwidth-145 20],... % Set the textbox position and size + 'hor','left',... % Left align the text in the textbox + 'backgroundcolor',wincolor,... % Set the textbox background color + 'foregroundcolor',0*[1 1 1],... % Set the text color + 'string',''); % Initialize the estimated time as blank + + userdata.text(4) = uicontrol(h,'style','text',... % Prepare the percentage progress + 'pos',[winwidth-35 winheight-50 35 20],... % Set the textbox position and size + 'hor','right',... % Left align the text in the textbox + 'backgroundcolor',wincolor,... % Set the textbox background color + 'foregroundcolor',0*[1 1 1],... % Set the textbox foreground color + 'string',''); % Initialize the progress text as blank + + userdata.axes = axes('parent',h,... % Set the progress bar parent to the figure + 'units','pixels',... % Provide axes units in pixels + 'pos',[10 winheight-45 winwidth-50 15],... % Set the progress bar position and size + 'xlim',[0 1],... % Set the range from 0 to 1 + 'box','on',... % Turn on axes box (to see where 100% is) + 'color',[1 1 1],... % Set plot background color to white + 'xtick',[],'ytick',[]); % Turn off axes tick marks and labels + + userdata.bar = patch([0 0 0 0 0],[0 1 1 0 0],'r'); % Initialize progress bar to zero area + userdata.time = []; % On opening don't set time + userdata.inc = []; % + set(h, 'userdata', userdata) % Allow access to the text and axes settings + % by including them with the timebar data + %%%%%%%% END OPEN FIGURE AND SET PROPERTIES %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +else % If first input is a timebar handle, update + % the window + %%%%%%%%%% GET HANDLE AND PROGRESS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + drawnow % faster than pause ! (KND) + % pause(10e-100) % Message, bar, and static text won't display + % without arbitrary pause (don't know why) + h = message; % Set handle to first input + progress = name; % Set progress to second input + + if ~strcmp(get(h,'tag'), 'timebar') % Check object tag to see if it is a timebar + error('Handle is not to a timebar window') % If not a timebar, report error and stop + end + %%%%%%%% END GET HANGLE AND PROGRESS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%%%%%%% CALCULATE ESTIMATED TIME REMAINING %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + userdata = get(h,'userdata'); % Get the userdata included with the timebar + if isempty(userdata.time) + userdata.time = clock; % Initialize the current time + userdata.inc = clock; % Set incremental clock to current time + set(h,'userdata',userdata) + end + inc = clock-userdata.inc; % Calculate time increment since last update + inc_secs = inc(3)*3600*24 + inc(4)*3600 + ... + inc(5)*60 + inc(6); % Convert the increment to seconds + + if [inc_secs > update_rate] | [progress == 1] % Only update at update rate or 100% complete + userdata.inc = clock; % If updating, reset the increment clock + set(h,'userdata',userdata) % Update userdata with the new clock setting + tpast = clock-userdata.time; % Calculate time since timebar initialized + seconds_past = tpast(3)*3600*24 + tpast(4)*3600 + ... + tpast(5)*60 + tpast(6); % Transform passed time into seconds + estimated_seconds = seconds_past*(1/progress-1); % Estimate the time remaining in seconds + hours = floor(estimated_seconds/3600); % Calculate integer hours of estimated time + minutes = floor((estimated_seconds-3600*hours)/60); % Calculate integer minutes of estimated time + seconds = floor(estimated_seconds-3600*hours- ... + 60*minutes); % Calculate integer seconds of estimated time + tenths = floor(10*(estimated_seconds - ... + floor(estimated_seconds))); % Calculate tenths of seconds (as integer) + %%%%%%%% END CALCULATE ESTIMATED TIME REMAINING %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + %%%%%%%%%% UPDATE ESTIMATED TIME AND PROGRESS TO TIMEBAR %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + if progress > 1 % Check if input progress is > 1 + time_message = ' Error! Progress > 1!'; % If >1, print error to estimated time + time_color = 'r'; % in red + else + +time_message = sprintf('%02d:%02d''%.1f', hours,minutes,seconds); +time_message = sprintf('%s (%02d:%02d''%.1f)', time_message, tpast(3)*24+tpast(4),tpast(5), tpast(6)); + +% +% if hours < 10; h0 = '0'; else h0 = '';end % Put leading zero on hours if < 10 +% if minutes < 10; m0 = '0'; else m0 = '';end % Put leading zero on minutes if < 10 +% if seconds < 10; s0 = '0'; else s0 = '';end % Put leading zero on seconds if < 10 +% time_message = strcat(h0,num2str(hours),'h',m0,... +% num2str(minutes),'''',s0,num2str(seconds),... +% '''''',num2str(tenths),... +% '(',num2str(tpast(3)*24+tpast(4)),'h',... +% num2str(tpast(5)),'''',... +% num2str(tpast(6)),''''''); % Format estimated time as hh:mm:ss.t + time_color = 'k'; % Format estimated time text as black + end + + set(userdata.bar,'xdata',[0 0 progress progress 0]) % Update progress bar + set(userdata.text(3),'string',time_message,... + 'foregroundcolor',time_color); % Update estimated time + set(userdata.text(4),'string',... + strcat(num2str(floor(100*progress)),'%')); % Update progress percentage + set(h, 'Name', ['Progress... ' get(userdata.text(4),'string')]) + end + %%%%%%%% END UPDATE ESTIMATED TIME AND PROGRESS TO TIMEBAR %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +end + +%%%%%%%%%% TIMEBAR HANDLE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if nargout == 0 % If handle not asked for + clear h % do not output it +end +%%%%%%%% END TIMEBAR HANDLE %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \ No newline at end of file diff --git a/timeit.m b/timeit.m new file mode 100644 index 0000000..7fd6897 --- /dev/null +++ b/timeit.m @@ -0,0 +1,1139 @@ +function [t, measurement_overhead, measurement_details] = timeit(f, num_outputs) +%TIMEIT Measure time required to run function. +% T = TIMEIT(F) measures the time (in seconds) required to run F, which is a +% function handle. TIMEIT calls F with either no output arguments or one +% output argument depending on nargout(F). +% +% T = TIMEIT(F,N) calls F with N output arguments. N can be 0, 1, 2, 3, or 4. +% +% TIMEIT handles automatically the usual benchmarking procedures of "warming +% up" F, figuring out how many times to repeat F in a timing loop, etc. +% TIMEIT also compensates for the estimated time-measurement overhead +% associated with tic/toc and with calling function handles. TIMEIT returns +% the median of several repeated measurements. +% +% Examples +% -------- +% How much time does it take to compute sum(A.' .* B, 1), where A is +% 12000-by-400 and B is 400-by-12000? +% +% A = rand(12000, 400); +% B = rand(400, 12000); +% f = @() sum(A.' .* B, 1); +% timeit(f) +% +% How much time does it take to call svd with three output arguments? +% +% X = [1 2; 3 4; 5 6; 7 8]; +% f = @() svd(X); +% timeit(f, 3) +% +% How much time does it take to dilate the text.png image with +% a 25-by-25 all-ones structuring element? (This example uses Image Processing +% Toolbox functions.) +% +% bw = imread('text.png'); +% se = strel(ones(25, 25)); +% g = @() imdilate(bw, se); +% timeit(g) + +% Steve Eddins +% Copyright 2008-2010 The MathWorks, Inc. + +if nargin < 2 + num_outputs = min(numOutputs(f), 1); +else + if num_outputs > 4 + warning('MATLAB:timeit:tooManyOutputs', ... + 'Too many function output arguments specified. timeit will call your function with 4 output arguments.'); + end +end + +t_rough = roughEstimate(f, num_outputs); + +% Calculate the number of inner-loop repetitions so that the inner for-loop +% takes at least about 1ms to execute. +desired_inner_loop_time = 0.001; +num_inner_iterations = max(ceil(desired_inner_loop_time / t_rough), 1); + +% Run the outer loop enough times to give a reasonable set of inputs to median. +num_outer_iterations = 11; + +% If the estimated running time for the timing loops is too long, +% reduce the number of outer loop iterations. +estimated_running_time = num_outer_iterations * num_inner_iterations * t_rough; +long_time = 15; +min_outer_iterations = 3; +if estimated_running_time > long_time + num_outer_iterations = ceil(long_time / (num_inner_iterations * t_rough)); + num_outer_iterations = max(num_outer_iterations, min_outer_iterations); +end + +times = zeros(num_outer_iterations, 1); + +for k = 1:num_outer_iterations + % Coding note: An earlier version of this code constructed an "outputs" cell + % array, which was used in comma-separated form for the left-hand side of + % the call to f(). It turned out, though, that the comma-separated output + % argument added significant measurement overhead. Therefore, the cases + % for different numbers of output arguments are hard-coded into the switch + % statement below. + switch num_outputs + case 0 + tic(); + for p = 1:num_inner_iterations + f(); + end + times(k) = toc(); + + case 1 + tic(); + for p = 1:num_inner_iterations + output = f(); + end + times(k) = toc(); + + case 2 + tic(); + for p = 1:num_inner_iterations + [output1, output2] = f(); + end + times(k) = toc(); + + case 3 + tic(); + for p = 1:num_inner_iterations + [output1, output2, output3] = f(); + end + times(k) = toc(); + + otherwise + tic(); + for p = 1:num_inner_iterations + [output1, output2, output3, output4] = f(); + end + times(k) = toc(); + end + +end + +t = median(times) / num_inner_iterations; + +measurement_details.EmptyFunctionCallTime = emptyFunctionCallTime(); +measurement_details.SimpleFunctionHandleCallTime = simpleFunctionHandleCallTime(); +measurement_details.AnonymousFunctionHandleCallTime = anonFunctionHandleCallTime(); +measurement_details.TicTocCallTime = tictocCallTime(); +measurement_overhead = (tictocCallTime() / num_inner_iterations) + ... + functionHandleCallOverhead(f); + +t = max(t - measurement_overhead, 0); + +if t < (5 * measurement_overhead) + warning('MATLAB:timeit:HighOverhead', 'The measured time for F may be inaccurate because it is close to the estimated time-measurement overhead (%.1e seconds). Try measuring something that takes longer.', measurement_overhead); +end + +function t = roughEstimate(f, num_f_outputs) +% Return rough estimate of time required for one execution of +% f(). Basic warmups are done, but no fancy looping, medians, +% etc. + +% Warm up tic/toc. +tic(); +elapsed = toc(); +tic(); +elapsed = toc(); + +% Call f() in a loop for at least a millisecond. +times = []; +time_threshold = 3; +iter_count = 0; +while sum(times) < 0.001 + iter_count = iter_count + 1; + + switch num_f_outputs + case 0 + tic(); + f(); + times(end+1) = toc(); + + case 1 + tic(); + output1 = f(); + times(end+1) = toc(); + + case 2 + tic(); + [output1, output2] = f(); + times(end+1) = toc(); + + case 3 + tic(); + [output1, output2, output3] = f(); + times(end+1) = toc(); + + otherwise + tic(); + [output1, output2, output3, output4] = f(); + times(end+1) = toc(); + end + + if iter_count == 1 + if times > time_threshold + % If the first call to f() takes more than time_threshold to run, + % then just use the result from that call. The assumption is that + % first-time effects are negligible compared to the running time for + % f(). + break; + else + % Discard first timing. + times = []; + end + end +end + +t = median(times); + +function n = numOutputs(f) +% Return the number of output arguments to be used when calling the function +% handle f. +% * If nargout(f) > 0, return 1. +% * If nargout(f) == 0, return 0. +% * If nargout(f) < 0, use try/catch to determine whether to call f with one +% or zero output arguments. +% Note: It is not documented (as of R2008b) that nargout can return -1. +% However, it appears to do so for functions that use varargout and for +% anonymous function handles. + +n = nargout(f); +if n < 0 + try + a = f(); + % If the line above doesn't throw an error, then it's OK to call f() with + % one output argument. + n = 1; + + catch %#ok + % If we get here, assume it's because f() has zero output arguments. In + % recent versions of MATLAB we could catch the specific exception ID + % MATLAB:maxlhs, but that would limit the use of timeit to MATLAB versions + % since the introduction of MExceptions. + n = 0; + end +end + +function t = tictocCallTime +% Return the estimated time required to call tic/toc. + +persistent ttct +if ~isempty(ttct) + t = ttct; + return +end + +% Warm up tic/toc. +temp = tic(); elapsed = toc(); +temp = tic(); elapsed = toc(); +temp = tic(); elapsed = toc(); + +num_repeats = 11; +times = zeros(1, num_repeats); + +for k = 1:num_repeats + times(k) = tictocTimeExperiment(); +end + +t = min(times); +ttct = t; + +function t = tictocTimeExperiment +% Call tic/toc 100 times and return the average time required. + +elapsed = 0; +% Call tic/toc 100 times. +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); +tic(); elapsed = elapsed + toc(); + +t = elapsed / 100; + +function emptyFunction() + +function t = functionHandleCallOverhead(f) +% Return the estimated overhead, in seconds, for calling a function handle +% compared to calling a normal function. + +fcns = functions(f); +if strcmp(fcns.type, 'anonymous') + t = anonFunctionHandleCallTime(); +else + t = simpleFunctionHandleCallTime(); +end + +t = max(t - emptyFunctionCallTime(), 0); + +function t = simpleFunctionHandleCallTime +% Return the estimated time required to call a simple function handle to a +% function with an empty body. +% +% A simple function handle fh has the form @foo. + +persistent sfhct +if ~isempty(sfhct) + t = sfhct; + return +end + +num_repeats = 101; +% num_repeats chosen to take about 100 ms, assuming that +% timeFunctionHandleCall() takes about 1 ms. +times = zeros(1, num_repeats); + +fh = @emptyFunction; + +% Warm up fh(). +fh(); +fh(); +fh(); + +for k = 1:num_repeats + times(k) = functionHandleTimeExperiment(fh); +end + +t = min(times); +sfhct = t; + +function t = anonFunctionHandleCallTime +% Return the estimated time required to call an anonymous function handle that +% calls a function with an empty body. +% +% An anonymous function handle fh has the form @(arg_list) expression. For +% example: +% +% fh = @(thetad) sin(thetad * pi / 180) + +persistent afhct +if ~isempty(afhct) + t = afhct; + return +end + +num_repeats = 101; +% num_repeats chosen to take about 100 ms, assuming that timeFunctionCall() +% takes about 1 ms. +times = zeros(1, num_repeats); + +fh = @() emptyFunction(); + +% Warm up fh(). +fh(); +fh(); +fh(); + +for k = 1:num_repeats + times(k) = functionHandleTimeExperiment(fh); +end + +t = min(times); +afhct = t; + +function t = functionHandleTimeExperiment(fh) +% Call the function handle fh 2000 times and return the average time required. + +% Record starting time. +tic(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); +fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); fh(); + +t = toc() / 2000; + +function t = emptyFunctionCallTime() +% Return the estimated time required to call a function with an empty body. + +persistent efct +if ~isempty(efct) + t = efct; + return +end + +% Warm up emptyFunction. +emptyFunction(); +emptyFunction(); +emptyFunction(); + +num_repeats = 101; +% num_repeats chosen to take about 100 ms, assuming that timeFunctionCall() +% takes about 1 ms. +times = zeros(1, num_repeats); + +for k = 1:num_repeats + times(k) = emptyFunctionTimeExperiment(); +end + +t = min(times); +efct = t; + +function t = emptyFunctionTimeExperiment() +% Call emptyFunction() 2000 times and return the average time required. + +% Record starting time. +tic(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); +emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); emptyFunction(); + +t = toc() / 2000; + + diff --git a/togglestate.m b/togglestate.m new file mode 100644 index 0000000..8a17b4a --- /dev/null +++ b/togglestate.m @@ -0,0 +1,51 @@ +function [varargout] = togglestate(handles,property,togglelist,exactflag) +%togglestate - toggle a handle between states +% [newstate] = togglestate(handles,Property,[ListOfStates], [exactflag]) +% Toggle the Property of each Handle individually +% ListOfState is optional. Default is to toggle between 'on' and 'off' +% If exactflag == 'exact', string matching will be exact +% ex: +% togglestate + +if nargin<4 + exactflag=0; +else + exactflag=isequal(exactflag, 'exact'); +end + +if nargin<3 + togglelist={'on' ; 'off'}; +end +if nargin<2 + error('Handles and Property to set are mandatory') +end + +cellofchar=0; +try + char(togglelist); + cellofchar=1; +end + +% togglelist2=unique(togglelist); +% if length(togglelist2) ~= length(togglelist) +% warning('List of States has redundant elements, they will be removed!') +% [i,j]=ismember(togglelist2,togglelist) +% togglelist=togglelist(sort(j)) +% end +% togglelist(end+1)=togglelist(1); +ns=length(togglelist); + +for i=1:length(handles) + % get(handles(i), property), + newstate{i}=togglelist{1}; + for j=1:ns-1 + if (cellofchar & strmatch(togglelist{j},get(handles(i), property))) | (~cellofchar & isequal(togglelist{j},get(handles(i), property))) + newstate{i}=togglelist{j+1}; + end + end + set(handles(i), property, newstate{i}); +end +if nargout>1 + varargout=newstate; +end +return diff --git a/trim.m b/trim.m new file mode 100644 index 0000000..f32213a --- /dev/null +++ b/trim.m @@ -0,0 +1,59 @@ +function [Y] = trim(X,method,varargin) +%trim() - Trim data from its outliers (values are discarded) +% [Y] = trim(X,p) trims p% at both tails of the data +% [Y] = trim(X,[p1 p2]) trims p1% of the lower and p2% at the upper tail +% [Y] = trim(X,method) trims data from their outliers using various +% methods: +% +%INPUTS: +% X: data matrix (considered column-wise) +% p or [p1 p2]: scalars specify the percentages of data to trim. +% If p/p1/p2 are >= 1, trims an exact number of elements +% method = {'name' params }: Specify method used and the parameters +% { 'quantile'/'q' [ p ] } standard trimming (default behavior) +% { 'threshold'/'t' [ t ] } remove values above a given threshold p +% if p=[p1 p2], trimming is done between p1 (min) and p2 (max) +% Example +% >> hist([trim(randn(10000,2),'quantile',.95) randn(10000,1)],50) +% % shows the extreme 5% of (two) normal distributions getting +% % trimmed to ~2 in comparison with the unchanged 3rd one +% +% See also: quantile, stat/winsor + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-09 Creation +% KND 2008-10-13 Example in help +% KND 2010-02-18 Renamed clipping() as trim() +% ----------------------------- Script History --------------------------------- + +sX=size(X); +if prod(sX)==max(sX) + X=X(:); +else + X=X(:,:); +end +if nargin==2 && isnumeric(method) + varargin{1} = method; + method = 'quantile'; +end +switch method + case {'quantile', 'q'} + Y=quantile(abs(X),varargin{1},1); + Y=Y(:)'; + Y=repmat(Y, size(X,1),1); + Y=X.*(abs(X)=Y); + case {'threshold', 't'} + Y=X; + Y(Y>varargin{1}(end))=varargin{1}(end); + if length(varargin{1})>1 + Y(Y0, hide what is BELOW xyz(i) +% if dxyz(i)<0, hide what is ABOVE xyz(i) +% if dxyz(i)=0, depends whether xyz(i)<0 or >O (BrainStorm behavior) +% +% KND : 2005-09-18 : Created based on code from tessellation_manager + +h=[]; +xyz=[]; +dxyz=[]; + +if nargin>1 + idxargin=1; + if length(varargin{1})==1 & ishandle(varargin{1}) + h=varargin{1}; + idxargin=idxargin+1; + end + if idxargin<=nargin + xyz=varargin{idxargin}; + idxargin=idxargin+1; + end + if idxargin<=nargin + dxyz=varargin{idxargin}; + idxargin=idxargin+1; + end +end + +if isempty(h) + try + h=findTessellationHandles; + catch; + end; +end + +if isempty(xyz) + xyz = [NaN NaN NaN]; % Normalized euclidian coordinate threshold along which we want to trim out the surface view +end +if isempty(dxyz) + dxyz = [0 0 0]; % Trimming direction +end + +if ishandle(h) + vertices = get(h,'vertices'); + FaceVertexAlphaData = get(h,'FaceVertexAlphaData'); + alpha=get(h,'FaceAlpha'); + if isreal(alpha) + alpha=max(alpha); + alpha=min(alpha,1); + alpha=max(alpha,0); + else + alpha=1; + end + if isempty(FaceVertexAlphaData) + FaceVertexAlphaData = ones(size(vertices,1),1); + end + iNoModif = []; + for iCoord = 1:3 + vertx = vertices(:,iCoord)'; +% vertx = vertx-mean(vertx); +% vertx = vertx/max(abs(vertx)); + if isnan(xyz(iCoord)) + % do nothing + elseif dxyz(iCoord)==0 % native Brainstorm behavior + if xyz(iCoord) > 0 + iNoModif = [iNoModif,find(vertx < xyz(iCoord) )]; + elseif xyz(iCoord) < 0 + iNoModif = [iNoModif,find(vertx > xyz(iCoord) )]; + else + %do nothing + end + else + if dxyz(iCoord)>0 + iNoModif = [iNoModif,find(vertx > xyz(iCoord) )]; + else + iNoModif = [iNoModif,find(vertx < xyz(iCoord) )]; + end + end + + end + + if isempty(iNoModif) + set(h,'alphadatamapping','scaled',... + 'FaceVertexAlphaData',alpha*ones(size(vertices,1),1),.... + 'FaceAlpha',alpha,... + 'backfacelighting','lit') + else + + FaceVertexAlphaData(unique(iNoModif)) = alpha; + FaceVertexAlphaData(setdiff(1:end,iNoModif)) = 0; + set(h,'alphadatamapping','none',... + 'FaceVertexAlphaData',FaceVertexAlphaData,... + 'FaceAlpha','interp',... + 'backfacelighting','unlit') + end + + +end diff --git a/trimsurface_gui.m b/trimsurface_gui.m new file mode 100644 index 0000000..1441a7d --- /dev/null +++ b/trimsurface_gui.m @@ -0,0 +1,229 @@ +function []=trimsurface_gui(varargin) +% trimsurface_gui - GUI interface for trimsurface +% trimsurface(h) pops up a window for trimming surface whose handle is h + +if nargin>=1 + if ischar(varargin{1}) + action=varargin{1}; + varargin(1)=[]; + else + action='init'; + end +else + action='init'; +end +feval(sprintf('action_%s', action), varargin{:}); +return + +function action_init(varargin) +%%%%%%%%%%%%%%%%%%%%% +%%% General Info. %%% +%%%%%%%%%%%%%%%%%%%%% +Black =[0 0 0 ]/255; +LightGray =[192 192 192 ]/255; +LightGray2 =[160 160 164 ]/255; +MediumGray =[128 128 128 ]/255; +White =[255 255 255 ]/255; + +Title='Surface Trimmer'; +WindowStyle='normal'; +Interpreter='none'; +if nargin<=4, + Resize = 'off'; +end + +%%%%%%%%%%%%%%%%%%%%%%% +%%% Create TrimFig %%% +%%%%%%%%%%%%%%%%%%%%%%% +FigWidth=100;FigHeight=300; +FigPos(3:4)=[FigWidth FigHeight]; +FigColor=get(0,'Defaultuicontrolbackgroundcolor'); +TextForeground = Black; +if sum(abs(TextForeground - FigColor)) < 1 + TextForeground = White; +end + +TrimFig=dialog( ... + 'Visible' ,'on' , ... + 'Name' ,Title , ... + 'Pointer' ,'arrow' , ... + 'Units' ,'points' , ... + 'UserData' ,'' , ... + 'Tag' ,Title , ... + 'HandleVisibility','on' , ... + 'Color' ,FigColor , ... + 'NextPlot' ,'add' , ... + 'WindowStyle' ,WindowStyle, ... + 'Resize' ,Resize ... +); +Temp=get(0,'Units'); +set(0,'Units','points'); +ScreenSize=get(0,'ScreenSize'); +set(0,'Units',Temp); +FigPos(1)=(ScreenSize(3)-FigWidth)/2; +FigPos(2)=(ScreenSize(4)-FigHeight)/2; +FigPos(3)=FigWidth; +FigPos(4)=FigHeight; +set(TrimFig,'Position',FigPos); +set(TrimFig,'WindowButtonDownFcn','trimsurface_gui(''btndwn'', gcbf)'); + +tags='XYZ'; +setappdata(TrimFig, 'Tags', tags); +for i=1:3 + hui(i)=uicontrol('style', 'slider', 'unit', 'normalized', ... + 'position', [.15+(i-1)*0.3 .1 .1 .75 ],'enable', 'on',... + 'callback', 'trimsurface_gui(''btndwnslider'', gcbf, gcbo)',... + 'tag', [tags(i)]); +end +set(hui, 'max', 1) +set(hui, 'min', -1) +set(hui, 'value', 0) +for i=4:6 + hui(i)=uicontrol('style', 'checkbox', 'unit', 'normalized', ... + 'position', [.15+(i-4)*0.3 .85 .1 .05 ]); + set(hui(i), 'callback', 'trimsurface_gui(''chkbox'',gcbf, gcbo)'); + set(hui(i), 'units', 'pixels'); + set(hui(i), 'position', get(hui(i), 'position').*[1 1 0 0]+[0 0 20 20]); + set(hui(i),'units', 'normalized') + set(hui(i),'tag', ['d' tags(i-3)]) + set(hui(i),'Tooltip', 'Hide the other side of the plane'); +end +for i=7:9 + hui(i)=uicontrol('style', 'checkbox', 'unit', 'normalized', ... + 'position', [.25+(i-7)*0.3 .1 .075 .75 ], 'value',1, ... + 'callback', 'trimsurface_gui(''toggleslider'', gcbf, get(gcbo, ''UserData''))',... + 'tag', ['c' tags(i-6)], 'UserData' , hui(i-6),... + 'Tooltip', 'Activate / Deactivate this cut'); +end + + +hui(end+1)=uicontrol('style', 'edit', 'unit', 'normalized', 'enable', 'off', ... + 'position', [.1 .9 .8 .05 ], 'min', 0, 'max', 0); +if nargin>0 + hp=varargin{1}; +else + hp=findTessellationHandles; +end +hui(end+1)=uicontrol('style', 'pushbutton', 'string', 'Unhide all', ... + 'unit', 'normalized', 'position', [.15 .05 .7 .05 ], ... + 'callback', 'trimsurface_gui(''unhide'',gcbf)'); + +hui(end+1)=uicontrol('style', 'pushbutton', 'string', 'Use OpenGL', ... + 'unit', 'normalized', 'position', [.15 .00 .7 .05 ], ... + 'UserData',get(get(hp, 'Parent'), 'Parent'), 'callback', 'set(get(gcbo, ''UserData''), ''Renderer'', ''opengl'');'); + +action_selectsurface(TrimFig,hp) +action_adjustsliders(TrimFig,hp); +return + +function action_adjustsliders(varargin) +hf=varargin{1}; +hp=varargin{2}; +tags=getappdata(hf,'Tags'); +dim=get(hp, 'Vertices'); +dim=[min(dim);max(dim)]; +for i=1:3 + hui=findobj(hf, 'style', 'slider', 'tag', tags(i)); + set(hui, 'min', dim(1,i), 'max', dim(2,i), 'value', mean(dim(:,i))) + setappdata(hf, tags(i), mean(dim(:,i))); + setappdata(hf, ['d' tags(i)], 1); +end + +function action_trim(varargin) +hf=varargin{1}; +tags=getappdata(hf, 'Tags'); +if nargin<2 + for i=1:3 + xyz(i)=getappdata(hf, tags(i)); + end +else + xyz=varargin{2}; +end +if nargin<3 + for i=1:3 + dxyz(i)=getappdata(hf, ['d' tags(i)]); + end +else + dxyz=varargin{3}; +end +dxyz=2*dxyz-1; +% hui(i)=findobj(hf, 'style', 'slider', 'tag', tags(i)); +hp=getappdata(hf, 'Surface'); +trimsurface(hp,xyz,dxyz) + + +function action_selectsurface(varargin) +hf=varargin{1}; +hp=varargin{2}; +setappdata(hf, 'Surface', hp) + + +function action_btndwn(varargin) +%Right click to toggle slider +hf=varargin{1}; +if ~isequal(get(hf, 'SelectionType'),'alt') +return +end +if nargin>=2 + ho=varargin{2}; +else + ho=overobj('uicontrol') + if ~isequal(get(ho, 'style'), 'slider') + return + end +end +if isequal(get(ho, 'enable')=='on') + set(ho, 'enable','off') + setappdata(hf,get(ho, 'tag'), 'NaN') +else + set(ho, 'enable','on') + setappdata(hf,get(ho, 'tag'), 0) +end +action_update(hf) + +function action_toggleslider(varargin) +%Right click to toggle slider +hf=varargin{1}; + ho=varargin{2}; +if isequal(get(ho, 'enable'),'on') + set(ho, 'enable','off') + setappdata(hf,get(ho, 'tag'), NaN) +else + set(ho, 'enable','on') + setappdata(hf,get(ho, 'tag'),get(ho, 'Value')) +end +action_update(hf) + + +function action_btndwnslider(varargin) +hf=varargin{1}; +ho=varargin{2}; +setappdata(hf,get(ho, 'tag'), get(ho, 'Value')) +action_update(hf) + +function action_chkbox(varargin) +hf=varargin{1}; +ho=varargin{2}; +setappdata(hf,get(ho, 'tag'), get(ho, 'Value')) +action_update(hf) + + +function action_update(varargin) +hf=varargin{1}; +tags=getappdata(hf, 'Tags'); +for i=1:3 + xyz(i)=getappdata(hf, tags(i)); + if ~isnan(xyz(i)) + set(findobj(hf, 'tag', [tags(i)]), 'value', xyz(i)); + end + dxyz(i)=getappdata(hf, ['d' tags(i)]); + set(findobj(hf, 'tag', ['d' tags(i)]), 'value', dxyz(i)); +end +sxyz=[sprintf('%2.2f ', xyz)]; +set(findobj(hf, 'style', 'edit'), 'string', sxyz) +action_trim(hf, xyz, dxyz) + +function action_unhide(varargin) +hf=varargin{1}; +hp=getappdata(hf, 'Surface'); +trimsurface(hp,[NaN NaN NaN]) diff --git a/twxticklabel.m b/twxticklabel.m new file mode 100644 index 0000000..654f337 --- /dev/null +++ b/twxticklabel.m @@ -0,0 +1,75 @@ +function hh = twxticklabel(ax) +% +% TWXTICKLABEL tweaks the xtick labels of the current axis, so that fonts +% are presereved when the figure is exported to eps (e.g. for inclusion +% into LaTeX). +% +% TWXTICKLABEL(AX) applies TWXTICKLABEL to the axis with handle AX. +% +% H = TWXTICKLABEL returns in H the handles of all XTick labels so the +% user can change every property which is possible with a text object created by text command. +% Following are a few examples: +% +% h = twxticklabel; +% set(h,'fontsize',12,'fontname','courier'); % to change font namae and size +% set(h,{'string'},char('10','-3','pi','he','90','ju')); % to change ticklabels +% set(h,'rotation',90); % to change angle +% +% The two m-files TWXTICKLABEL and TWYTICKLABEL motivated by the following problems in the way Matlab handles tick labels. +%1) +% Matlab provides no handles to xtick labels and ytick labels; meaning that you can't change their +% properties separately, but only by changing axis properties. For example, the only way to change +% the fontname of xtick labels is by setting the fontname property of the axis, thus changing the fontname +% of all it object, which may not be desirable. If a user wants to rotate the tick labels, one would +% like to be able to do that with commands like set(handle, 'rotation', 90); but that is only possible if you have +% the handle. +% +%2) +% Tick labels do not interpret TeX/LaTeX character sequences; What if you want LaTeX expression $W_i(t)$. +% +%3) +% Even if you are happy with changing the properties of the whole axis, another problem arises when the Matlab +% figure is exported to eps for inclusion into LaTeX. It sometimes changes the fonts (set by the user) of the +% xticklabels in an unpredictable way (fortunately, this does not happen with xlabel, ylabel, title and other text object). +% +% +% In these two files, I have tried to create ticklabels by using text command. Handles are returned for all tick labels, +% so the user can change every property which is possible with a text object created by text command. + +if nargin == 0 + ax = gca; +end + +xtick = get(ax,'XTick')'; + +if isempty(xtick) + error('''XTick'' found empty') +end + +a = 0.5; +hxlabel = get(ax,'xlabel'); +set(hxlabel,'Units','data'); +xlabpos = get(hxlabel,'position'); +temp = get(ax,'XTickLabel'); +if iscell(temp) + xticklab = cellstr(strjust(strvcat(temp), 'center')); +elseif ischar(temp) + xticklab = strjust(temp, 'center'); +end +set(ax,'XTickLabel',[]) + +xlabpos2 = get(hxlabel,'position'); +ylims = get(ax,'ylim'); +xtickloc = a*xlabpos2(2) + (1-a)*ylims(1); + +h = text(xtick, xtickloc(ones(size(xtick))), xticklab); + +set(h, 'fontsize', get(ax,'fontsize'), ... + 'HorizontalAlignment', 'center', 'VerticalAlignment', 'top') + +xlabpos(2) = xlabpos(2) + a*(xlabpos(2)-xlabpos2(2)); +set(hxlabel, 'position',xlabpos) + +if nargout == 1 + hh = h; +end \ No newline at end of file diff --git a/uigetpathfile.m b/uigetpathfile.m new file mode 100644 index 0000000..d6ec295 --- /dev/null +++ b/uigetpathfile.m @@ -0,0 +1,10 @@ +function [ff]=uigetpathfile(varargin) +[f,p]=uigetfile(varargin{:}); +if isequal(f,0) | isequal(p,0) + ff=0; + return +end +ff=fullfile(p,f); +if length(dbstack)==1 % (evalin('caller','mfilename')) + disp(ff) +end \ No newline at end of file diff --git a/usbpath.m b/usbpath.m new file mode 100644 index 0000000..e6511df --- /dev/null +++ b/usbpath.m @@ -0,0 +1,10 @@ +function [USBDIR]=usbpath() +% USBPATH - Retrieves directory of the USB drive on the current OS +USBDIR=''; +[hostname,hostname]=system('hostname'); +switch upper(deblank(hostname)) + case 'KARIMND' + USBDIR = 'I:/'; + case 'LENA138.LENA.CHUPS.JUSSIEU.FR' + USBDIR = '/mount/usb/'; +end diff --git a/vectvec.m b/vectvec.m new file mode 100644 index 0000000..02036d8 --- /dev/null +++ b/vectvec.m @@ -0,0 +1,4 @@ +function [X]=vectvec(X) +% vectvec - make array X into one column, same as X(:) +X=X(:); +% see also: vec() in BST diff --git a/vertvec.m b/vertvec.m new file mode 100644 index 0000000..c114c43 --- /dev/null +++ b/vertvec.m @@ -0,0 +1,7 @@ +function [X]=vertvec(X) +% vertvec - make array X into one column, same as X(:) +% [Y]=vertvec(X) is equivalent to Y=X(:) + +X=X(:); + +%see: vec() in BrainStorm \ No newline at end of file diff --git a/vidal.m b/vidal.m new file mode 100644 index 0000000..7b65bb4 --- /dev/null +++ b/vidal.m @@ -0,0 +1,77 @@ +if ~ exist('fic_ds') + fic_ds='/pclxserver/home/ndiaye/DAV/rawdata/S7/aud01.ds' +end + +if ~ exist('F') +[F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] = ds2brainstorm(fic_ds,0); +end + +t=textread('ClassFile.cls','%s'); +n=strmatch('BAD',t) +n=strmatch('NUMBER',t(n:end))+n-1 + +nbad=str2num(t{n(1)+3}); +badtrials=[]; +for i=1:nbad +j=i+n(2); +badtrials=[badtrials str2num(t{j})]; +end + +MARQUEURS={'Tr22' 'Tr23' 'Tr24' 'Tr25' 'Tr26'} +for i=1:length(MARQUEURS) +t=textread('MarkerFile.mrk','%s'); +mark(i).name=MARQUEURS{i} +n=strmatch(MARQUEURS{i},t); + + + n=strmatch('SAMPLES',t(n:end))+n-1; +mark(i).nb=str2num(t{n(1)+1}) + +for j=1:mark(i).nb +k=2*j+n(2)+7; +mark(i).tr(j)=str2num(t{k}); +end + +end + + +for i=mark(5).tr+1;, + if ~ find(badtrials==i), + keep=[keep i]; +end +end + 'Essais à tester :' +keep + +selection=ieegsens; +clear G +clear allG +clear pente +j=1; +allG(:,:,j)=F{1}(selection,:); +for i=keep(2:end) + j=j+1; +% G=G + F{i}(selection,:); +allG(:,:,j)= F{i}(selection,:); + +end +% G=G/length(keep); +G=mean(allG,3); +for i=1:size(G,1) + pente(i,1)=linearfit(G(i,64:500), Time(64:500)); + pente(i,2)=linearfit(G(i,501:625), Time(501:625)); +end + + [dpente,capteur]=sort(pente(:,1)-pente(:,2)); + +subplot(3,1,1) +bar(pente(capteur(2:end),1)) +subplot(3,1,2) +bar(pente(capteur(2:end),2)) +subplot(3,1,3) +bar(dpente(2:end)) +subplot(3,1,3) +hold on +bar(std(std(allG(capteur(2:end),:,:),[],3),[],2),'r') +hold off +capteur(1:10) diff --git a/view3d.m b/view3d.m new file mode 100644 index 0000000..e7e7bc4 --- /dev/null +++ b/view3d.m @@ -0,0 +1,48 @@ +% view3d() - a simple 3D viewer +% Use: +% >> view3d(FV) +% >> view(vertices, faces) +% FV might be a structure with fields .vertices and .faces +% +% Setting options: +% >> view3d(FV, options) +% >> view(vertices, faces, options) +% e.g.: +% >> view(vertices, faces, 'FaceColorCData', rand(length(vertices),1)) +function [ p ] = view3d(v,f, varargin) +if isfield(v, 'vertices') + for i=1:length(v) + + view3d(v(i).vertices, v(i).faces, f, varargin{:}) + hold on + zoom(1/1.1) + delete(findobj(gca, 'type', 'light')) + delete(findobj(gca, 'type', 'light')) + end + axis image + if length(findobj(gca, 'type', 'light')) == 0 + light('Position',[-1 -1 1],'Style','infinite'); + light('Position',[1 1 0],'Style','infinite'); + end +else + + if isempty(varargin) + options={'FaceColor' , [0.7 .65 .65]}; + else + options=varargin; + end + + p=patch('Vertices', v, 'Faces', f,'EdgeColor','none','FaceLighting','phong','FaceAlpha','interp', options{:}); + set(p,'DiffuseStrength',.6,'SpecularStrength',0,'AmbientStrength',.4,'SpecularExponent',5) + view(3); + grid on; + lighting phong; + alpha(1); + axis on; + axis image; + if length(findobj(gca, 'type', 'light')) == 0 + light('Position',[-1 -1 1],'Style','infinite'); + light('Position',[1 1 0],'Style','infinite'); + end + zoom(1.1); +end \ No newline at end of file diff --git a/viewer3d.m b/viewer3d.m new file mode 100644 index 0000000..cdd1b10 --- /dev/null +++ b/viewer3d.m @@ -0,0 +1,48 @@ +% viewer3d() - a simple 3D viewer +% Use: +% >> viewer3d(FV) +% >> view(vertices, faces) +% FV might be a structure with fields .vertices and .faces +% +% Setting options: +% >> viewer3d(FV, options) +% >> view(vertices, faces, options) +% e.g.: +% >> view(vertices, faces, 'FaceColorCData', rand(length(vertices),1)) +function [ p ] = viewer3d(v,f, varargin) +if isfield(v, 'vertices') + for i=1:length(v) + + view3d(v(i).vertices, v(i).faces, f, varargin{:}) + hold on + zoom(1/1.1) + delete(findobj(gca, 'type', 'light')) + delete(findobj(gca, 'type', 'light')) + end + axis image + if length(findobj(gca, 'type', 'light')) == 0 + light('Position',[-1 -1 1],'Style','infinite'); + light('Position',[1 1 0],'Style','infinite'); + end +else + + if isempty(varargin) + options={'FaceColor' , [0.7 .65 .65]}; + else + options=varargin; + end + + p=patch('Vertices', v, 'Faces', f,'EdgeColor','none','FaceLighting','phong','FaceAlpha','interp', options{:}); + set(p,'DiffuseStrength',.6,'SpecularStrength',0,'AmbientStrength',.4,'SpecularExponent',5) + view(3); + grid on; + lighting phong; + alpha(1); + axis on; + axis image; + if length(findobj(gca, 'type', 'light')) == 0 + light('Position',[-1 -1 1],'Style','infinite'); + light('Position',[1 1 0],'Style','infinite'); + end + zoom(1.1); +end \ No newline at end of file diff --git a/vline.m b/vline.m new file mode 100644 index 0000000..a7f7a2f --- /dev/null +++ b/vline.m @@ -0,0 +1,66 @@ +function varargout = vline(x,varargin) +%VLINE - Create a vertical line on a plot +% [h] = vline(x) +% Adds as many vertical lines on the current plot as there are values in x. +% +% See also: line, hline + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-02 Creation +% KND 2009-10-22 Corrected bug with single argument for linestyle +% ----------------------------- Script History --------------------------------- + +%y=max(abs(get(gca, 'Ylim')))*[-1 1]; +%y=*10; +y=get(gca, 'Ylim'); +if isequal(get(gca, 'Yscale'),'log') + % not a perfect trick to deal with log scales... + yt = get(gca,'Ytick'); + y = [yt(1).^2/yt(2) y(2)]; +end +x=x(:); +x=[x*ones(1,2)]'; +y=repmat(y,size(x,2),1)'; + +holdstate=ishold; +hold on; +if nargin>1 && ischar(varargin{1}) && mod(nargin-1,2)==1 + opt=[]; + c = ismember(varargin{1}, 'bgrcmykw'); + m = ismember(varargin{1}, '.ox+*sdv^<>ph'); + if any(c) + opt=[{'Color', varargin{1}(c)} opt]; + end + if any(m) + opt=[{'Marker', varargin{1}(m)} opt]; + end + if any(~c & ~m) + opt=[{'LineStyle', varargin{1}(~c & ~m)} opt]; + end + varargin(1)=[]; + varargin = [opt varargin]; +end +h=line(x,y,varargin{:}); +if ~holdstate + hold off; +end +LineStyles={'-', ':', '--', '-.'}; +if nargin>3 + if isempty(strmatch('linestyle', lower(varargin(cellfun('isclass', varargin, 'char'))))) && ... + isempty(intersect(LineStyles,lower(varargin(cellfun('isclass', varargin, 'char'))))) + for i=1:length(h); + set(h(i), 'LineStyle', LineStyles{mod(ceil(i/size(get(gca, 'ColorOrder'),1))-1,4)+1}); + end + end +end +if nargout==0 + return +end +varargout={h}; diff --git a/wheelzoom.m b/wheelzoom.m new file mode 100644 index 0000000..88df44d --- /dev/null +++ b/wheelzoom.m @@ -0,0 +1,110 @@ +function varargout = wheelzoom(action,varargin) +%wheelzoom - Control axes zoom using mouse wheel +% wheelzoom(ha) +% wheelzoom(ha,factor) +% +% Example +% >> wheelzoom(gca) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2005 +% This program is free software; you can redistribute it and/or modify +% it under the terms of the GNU General Public License as published by +% the Free Software Foundation; either version 2 of the License, or +% (at your option) any later version. +% +% ----------------------------- Script History --------------------------------- +% KND 2005-12-15 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + action='init'; +elseif isa(varargin{1}, 'java') && isequal(get(varargin{1}, 'Type'), 'java.awt.event.MouseWheelEvent') + action='wheel'; +else + +end +'weez' +out=eval(sprintf('action_%s(varargin{:});', action)); +if nargout>0 + varargout=out; +end +return + +function [varargout]=action_init(varargin) +if nargin<1 + ha=gca; +else + ha=varargin{1}; +end +if nargin<1 + ha=gca; +else + ha=varargin{1}; +end +if nargin<2 + wz.factor=1.5; +else + wz.factor=varargin{2}; +end + +% Adapted from Nanne van der Zijpp's setMouseWheel +jobj=javax.swing.JLabel; +jobj.setOpaque(0); +[jobj,h] = javacomponent(jobj,[],get(ha,'Parent')); +% drawnow; +for i=1:100; % Number of attempts to get the RootPane + RootPane=jobj.getRootPane; + pause(.01); + if ~isempty(RootPane); break;end +end +delete(h); +% setappdata(ha,'RootPane',RootPane); +wz.RootPane=RootPane; +set(RootPane,'MouseWheelMovedCallback',[ str2func(sprintf('%s', mfilename))]); +setappdata(ha,mfilename,wz); +varargout={{}}; + +function []=action_setfactor(ha,factor) +if nargin<2 + error('Wrong number of inputs. Needs axes handle & zoom factor') +end +wz=getappdata(ha,mfilename); +if isempty(wz) + error('No WheelZoom for this axes handle!') +end +wz.factor=factor; +setappdata(ha,mfilename,wz); + +function [varargout]=action_wheel(varargin) +varargout={{}}; +ha=overobj('axes'); +if isempty(ha) + return +end +wz=getappdata(ha,mfilename); +if isempty(wz) + return +end +updown=get(varargin{1}, 'WheelRotation'); +y=get(ha, 'Ylim'); +y(3)=(y(2)+y(1))/2; +y(4:5)=wz.factor^updown*(y(2)-y(1))/2*[-1 +1]; +if strmatch('on', get(varargin{1}, 'ControlDown')) + % Control Button for pointer centered zooming + c=get(gca, 'CurrentPoint'); + y(3)=c(3); +end +if strmatch('on', get(varargin{1}, 'ShiftDown')) + % Shift Button for zero-centered zooming + c=get(gca, 'CurrentPoint'); + y(3)=0; + +end + +% y=c(3)+wz.factor^updown*(y(2)-y(1))/2*[-1 +1]; +% +set(ha, 'Ylim', y(3)+y(4:5)) diff --git a/whichLoop.m b/whichLoop.m new file mode 100644 index 0000000..c52f529 --- /dev/null +++ b/whichLoop.m @@ -0,0 +1,60 @@ +function [v]=whichLoop(x,b,n,backward) +% whichLoop - get the n-th "pseudo-bit" of a number x in pseudo-base b (little-endian) +% +% [v]=whichLoop(x,b,[n], [backward]) +% +% Ex. you fill an array using "for" loops: +% >> for i=1:3, for j=1:7, for k=1:5, x=[x, ...], end, end, end +% if you want to know at which index of "j" (the 2nd loop index) +% the, say, 12-th value in x corresponds: +% >> whichLoop(12, [3 7 5], 2) +% returns: 3 +% +% Cool, isn't it? +% +% [n] is optional, if not given, the whole list is output +% >> whichLoop(1, [3 7 5]) -> [1 1 1] that is i=1, j=1, k=1 +% >> whichLoop(51,[3 7 5]) -> [2 4 1] that is i=2, j=4, k=1 +% +% [backward] is 0 (default) or 1. In the latter case, treat b as the +% last loops of some upper unspecified loops. +% i.e. "the heaviest (pseudo)bits are discarded" +% i.e. counting starts from the most inner loops +% >> for i=1:???, ..., for j=1:7, for k=1:5 ... end,end,...,end +% >> whichLoop(12, [ 6 4 7 5 ], 2, 1) -> [3] that is: j=3 +% (whatever the number of loops in '?') +% >> whichLoop(12, [ NaN 7 5 ],1:2,1) +% returns: [k=2 j=2] +% Note that in that case, the order of the outputs is also reversed. + +if nargin<4 + backward=0; +end +if nargin<3 + n=[]; +end +if isempty(n) + n=1:length(b); +end +n=n(:); +if not(backward) + if x < 1 | x > prod(b) + error([mfilename ': impossible x input according to the loops b' ]) + end +else + % little endian + n=length(b)-n+1; +end + +k=fliplr(1./cumprod([1 b(end:-1:2)])); +x=floor((x-1)*k); +v=rem(x,b)+1; + + +if any(n>length(b)) | any(n<1) + error(sprintf('%s: asked rank (n=%d) beyond the number of loops', ... + mfilename,n)) +end +v=v(n); + +return diff --git a/whichRank.m b/whichRank.m new file mode 100644 index 0000000..cad31e3 --- /dev/null +++ b/whichRank.m @@ -0,0 +1,63 @@ +function [v]=whichRank(x,b,n,backward) +% whichRank - get the n-th "pseudo-bit" of a number x in pseudo-base b (little-endian) +% +% [v]=whichRank(x,b,[n], [backward]) +% +% Ex. +% >> for i=1:3, for j=1:7, for k=1:5, x=[x, ...], end, end, end +% if you want to know at which rank in "j" (the 2nd loop index) +% the, say, 12-th value in x corresponds: +% >> whichrank(12, [3 7 5], 2) +% returns: 3 +% +% Cool, isn't it? +% +% [n] is optional, if not given, the whole list is output +% >> whichrank(1, [3 7 5]) -> [1 1 1] that is i=1, j=1, k=1 +% >> whichrank(51,[3 7 5]) -> [2 4 1] that is i=2, j=4, k=1 +% +% [backward] is 0 [default] or 1. In the latter case, treat b as the +% last loops of some upper unspecified loops. +% i.e. "the heaviest pseudo-bits are discarded": +% >> for i=1:???, ..., for j=1:7, for k=1:5 ... end +% >> whichrank(12, [ 6 4 7 5 ], 2, 1) +% returns : 3 (whatever the loops in '?') + + +if nargin<4 + backward=0; +end +if nargin<3 + n=[]; +end + +if not(backward) + if x < 1 | x > prod(b) + error([mfilename ': impossible x input according to the loops b' ]) + end +else + n=length(b)-n+1; +end + + +k=fliplr(1./cumprod([1 b(end:-1:2)])); +x=floor((x-1)*k); +v=rem(x,b)+1; + +if not(isempty(n)) + if n>length(b) | n<1 + error(sprintf('%s: asked rank (n=%d) beyond the number of loops', ... + mfilename,n)) + end + v=v(n); +end + +return + + +v=rem(x,b(n))+1; +return +k=floor(x/k)-1 +v=rem(k,b(n))+1; +return + diff --git a/windfind.m b/windfind.m new file mode 100644 index 0000000..4c6acb2 --- /dev/null +++ b/windfind.m @@ -0,0 +1,64 @@ +function h = windfind(name); +%WINDFIND - Find or create a particular window using it's NAME property +% function h = windfind(name); +% find the first window whos 'Name' is name. +% If no such window exists, create it. +% h is the handle of the window returned. + +% ---------------------- 27-Jun-2005 10:46:04 ----------------------- +% ------ Automatically Generated Comments Block Using AUTO_COMMENTS_PRE7 ------- +% +% CATEGORY: Utility - General +% +% At Check-in: $Author: Mosher $ $Revision: 16 $ $Date: 6/27/05 9:00a $ +% +% This software is part of BrainStorm Toolbox Version 27-June-2005 +% +% Principal Investigators and Developers: +% ** Richard M. Leahy, PhD, Signal & Image Processing Institute, +% University of Southern California, Los Angeles, CA +% ** John C. Mosher, PhD, Biophysics Group, +% Los Alamos National Laboratory, Los Alamos, NM +% ** Sylvain Baillet, PhD, Cognitive Neuroscience & Brain Imaging Laboratory, +% CNRS, Hopital de la Salpetriere, Paris, France +% +% See BrainStorm website at http://neuroimage.usc.edu for further information. +% +% Copyright (c) 2005 BrainStorm by the University of Southern California +% This software distributed under the terms of the GNU General Public License +% as published by the Free Software Foundation. Further details on the GPL +% license can be found at http://www.gnu.org/copyleft/gpl.html . +% +% FOR RESEARCH PURPOSES ONLY. THE SOFTWARE IS PROVIDED "AS IS," AND THE +% UNIVERSITY OF SOUTHERN CALIFORNIA AND ITS COLLABORATORS DO NOT MAKE ANY +% WARRANTY, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO WARRANTIES OF +% MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE, NOR DO THEY ASSUME ANY +% LIABILITY OR RESPONSIBILITY FOR THE USE OF THIS SOFTWARE. +% ------------------------ 27-Jun-2005 10:46:04 ----------------------- + +% ----------------------------- Script History --------------------------------- +% Author 1994 John C. Mosher +% 3/3/94 Author +% 19-May-2004 JCM Comments Cleaning +% ----------------------------- Script History --------------------------------- + +if(~isstr(name)), + error('WINDFIND: input argument must be string'); +end + +hw = get(0,'children'); % all open windows +hw = sort(hw); % in increasing window order + +for i = 1:length(hw), + s = get(hw(i),'Name'); + if(strcmp(deblank(s),deblank(name))), + h = hw(i); + return; + end +end + +% we exited out without a match, make the window +h = figure; +set(h,'Name',name); +return + diff --git a/wwhich.m b/wwhich.m new file mode 100644 index 0000000..681dd2f --- /dev/null +++ b/wwhich.m @@ -0,0 +1,78 @@ +function out=wwhich(s1,s2) + +% WWHICH Locate m-files using wildcards +% Works exactly as WHICH, but you can +% use wild cards. +% +% out is a cell whenever 2 or more +% matches are found or if the flag +% -all was used +% +% Note: a function may be shawdowed, +% use the flag -all to locate them +% +% See WHICH for more info +% +% by Lucio Andrade + +if length(strmatch(strvcat('PCWIN'),computer)) + pathseparator=';'; +elseif length(strmatch(strvcat('SUN4','SOL2','LNX86','MAC64'),computer)) + pathseparator=':'; +else + warning('I''m not sure of the path separator for this machine.') + pathseparator=':'; + disp('I''ll use '':'' as a path separator') +end + +if nargin<1 + error('Not enough input arguments.') +end + +p=path; +out=cell(0); + +h=[0 find(p==pathseparator) length(p)+1]; +for i=length(h):-1:2 + direc= p(h(i-1)+1:h(i)-1); + a=dir([direc '/' s1 '.m']); + for j=1:length(a) + if nargin>1 + outtmp=which(a(j).name,s2); + if iscell(outtmp) + out=[out;outtmp]; + else + out=[out;{outtmp}]; + end + else + outtmp=which(a(j).name); + out=[out;{outtmp}]; + end + end +end + +%take out repetitions +todel=[]; +for i=1:length(out) + for j=i+1:length(out) + if strcmp(out{i},out{j}) todel=[todel j]; end + end +end +out(unique(todel))=[]; + +%change to string when needed +if (nargin==1) & (length(out)==1) + out=out{1}; +end + +if nargout==0 + if iscell(out) + for i=1:length(out) + disp(out{i}) + end + else + disp(out) + end + clear out +end + diff --git a/x2cell.m b/x2cell.m new file mode 100644 index 0000000..f47c964 --- /dev/null +++ b/x2cell.m @@ -0,0 +1,4 @@ +function [x]=x2cell(x) +% x2cell - make sure x is cell. DEPRECATED by: forcecell() +warning('MATLAB:x2cell is DEPRECATED') +x=forcecell(x); diff --git a/x2char.m b/x2char.m new file mode 100644 index 0000000..1fe87b4 --- /dev/null +++ b/x2char.m @@ -0,0 +1,58 @@ +function S = x2char(X) +%X2CHAR - Convert data to formatted string output +% [S] = x2char(X) +% +% Example +% >> x2char(dir) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-10-01 Creation +% +% ----------------------------- Script History --------------------------------- + +if isnumeric(X) + if isempty(X) + S = '[]'; + elseif numel(X)>10 + S = sprintf('[[%s ... %s]]',x2char(X(1)), x2char(X(end))); + elseif numel(X)>1 + if numel(X) == size(X,1) + S = sprintf('[%s\b\b\b]',sprintf('%g ; ',X)); + elseif numel(X) == size(X,2) + S = sprintf('[%s\b\b\b]',sprintf('%g , ',X)); + else + S = sprintf('[[%s\b]]',sprintf('%g ',X)); + end + else + S = sprintf('%g',X); + end +elseif ischar(X) + if isempty(X) + S = ''; + else + S = sprintf('%s',X); + end +elseif islogical(X) + if X + S = 'false'; + else + S = 'true'; + end +elseif iscell(X) + if isempty(X) + S = '{}'; + else + S = '{...}'; + end +else + S = '???'; +end \ No newline at end of file diff --git a/xjview.m b/xjview.m new file mode 100644 index 0000000..bce66ca --- /dev/null +++ b/xjview.m @@ -0,0 +1,8669 @@ +function xjview(varargin) +% xjview, version 4 +% +% usage 1: xjview (no argument) +% for displaying a result img file, or multiple image files, +% (which will be loaded later) and changing p-value or t/f-value +% usage 2: xjview(imagefilename) +% for displaying the result img file and changing p-value or +% t-value +% Example: xjView spmT_0002.img +% xjView('spmT_0002.img') +% xjView mymask.img +% usage 3: xjview(imagefilename1, imagefilename2, ...) +% for displaying the result img files and changing p-value or +% t/f-value +% Example: xjView spmT_0002.img spmT_0005.img spmT_0007.img +% xjView('spmT_0002.img', 'spmT_0003.img', 'spmT_0006.img') +% xjView myMask1.img myMask2.img myMask3.img +% usage 4: xjview(mnicoord, intensity) +% for displaying where are the mni coordinates +% mnicoord: Nx3 matrix of mni coordinates +% intensity: (optional) Nx1 matrix, usually t values of the +% corresponding voxels +% Example: xjView([20 10 1; -10 2 5],[1;2]) +% xjView([20 10 1; -10 2 5]) +% Note: to use xjview this way, you may need to modify the value +% of M and DIM in the begining of xjview.m +% +% http://people.hnl.bcm.tmc.edu/cuixu/xjView +% +% by Xu Cui and Jian Li 2/21/2005 +% last modified: 02/18/2007 (add colorbar max control) +% last modified: 11/16/2006 (keyboard shortcut for open image and open roi file) +% last modified: 06/16/2006 (spm5 compatible) +% last modified: 05/30/2006 (left/right flip, path of mask.img and templateFile.img) +% last modified: 05/08/2006 (debug CallBack_volumePush function, change handles.intensity{1} to intensity) +% last modified: 04/03/2006 (modify tr) +% last modified: 12/28/2005 (modify SPM process) +% +% Thank Sergey Pakhomov for sharing his database (MNI Space Utility). +% Thank Yuval Cohen for the maximize figure function (maximize.m) +% + +% TODO +% Send SPM to workspace + +warnstate = warning; +warning off; + +% pre-set values +% important! you need compare the display of xjview and spm. If you find +% xjview flipped the left/right, you need to set leftrightflip = 1; +% otherwise leave it to 0. +leftrightflip = 0; +% leftrightflip = 1 ; %must be on in the CMU... +% Now with spm-flip = 1; xjview-flip=1 + +% You only need to change M and DIM when you want to use xjview under +% 'usage 4'. +M = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +DIM = [41 48 35]'; +TR = 2; % you don't need to set TR is you only use the viewing part of xjview + +% system settings +try + spmdir = spm('dir'); + spm('defaults', 'fmri'); +catch + disp('Please add spm path.'); + warning(warnstate(1).state); + return +end + +if ispc + os = 'windows'; +elseif isunix + os = 'linux'; +else + warndlg('I don''t know what kind of computer you are using. I assumed it is unix.', 'What computer are you using?'); + os = 'linux'; +end +screenResolution = get(0,'ScreenSize'); + +xjviewpath = fileparts(which('xjview')); + +% pre-set values +pValue = 0.001; +intensityThreshold = 0; +clusterSizeThreshold = 5; + + +% Appearance Settings +figurePosition = [0.100, 0.050, 0.660, 0.880]; +sectionViewPosition = [0.5,0.61,0.45,0.45]; +glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +if screenResolution(3) <= 1024 + figurePosition = [0.100, 0.050, 0.700, 0.900]; + sectionViewPosition = [0.5, 0.61, 0.45, 0.46]; + glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +end + +left = 0.01; +editBoxHeight = 0.05; +editBoxWidth = 0.200; +editBoxLeft = 0.100; + +controlPanelPosition = [left, 0.080, 0.500, 0.500]; +stretchMatrix = diag([controlPanelPosition(3),controlPanelPosition(4),controlPanelPosition(3),controlPanelPosition(4)]); +controlPanelOffset = controlPanelPosition' .* [1,1,0,0]'; +heightUnit = 0.055; + +sliderPosition = stretchMatrix*[0.000, 0*heightUnit, 1.000, editBoxHeight]' + controlPanelOffset; +pValueTextPosition = stretchMatrix*[0.000, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pValueEditPosition = stretchMatrix*[0.110, 1*heightUnit, editBoxWidth*4/3, editBoxHeight]' + controlPanelOffset; +intensityThresholdTextPosition = stretchMatrix*[0.400, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +intensityThresholdEditPosition = stretchMatrix*[0.520, 1*heightUnit, editBoxWidth*3/3, editBoxHeight]' + controlPanelOffset; +dfTextPosition = stretchMatrix*[0.740, 1*heightUnit, 0.8-0.74, editBoxHeight]' + controlPanelOffset; +dfEditPosition = stretchMatrix*[0.800, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdTextPosition = stretchMatrix*[0.000, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdEditPosition = stretchMatrix*[0.150, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pickThisClusterPushPosition = stretchMatrix*[0.400, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +selectThisClusterPushPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +clearSelectedClusterPushPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +thisClusterSizeTextPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +thisClusterSizeEditPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +loadImagePushPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +imageFileEditPosition = stretchMatrix*[0.200, 3*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImagePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImageFileEditPosition = stretchMatrix*[0.200, 4*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveResultPSPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +resultPSFileEditPosition = stretchMatrix*[0.200, 5*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayIntensityTextPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth+0.1, editBoxHeight]' + controlPanelOffset; +allIntensityRadioPosition = stretchMatrix*[0.250, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +positiveIntensityRadioPosition = stretchMatrix*[0.400, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +negativeIntensityRadioPosition = stretchMatrix*[0.550, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderViewCheckPosition = stretchMatrix*[0.780, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +hideControlPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +volumePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +commonRegionPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +%knd +paramestPushPosition = stretchMatrix*[0.800, 4*heightUnit, editBoxWidth*.5, editBoxHeight]' + controlPanelOffset; +%-- +displayPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +allinonePushPosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchPushPosition = stretchMatrix*[0.000, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchContentEditPosition = stretchMatrix*[0.200, 6*heightUnit, editBoxWidth*2, editBoxHeight]' + controlPanelOffset; +searchTextPosition = stretchMatrix*[0.600, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchEnginePopPosition = stretchMatrix*[0.600, 6*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +overlayPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayEditPosition = stretchMatrix*[0.200, 5*heightUnit, 0.6-editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayPopPosition = stretchMatrix*[0.600, 5*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +helpPosition = stretchMatrix*[0.800, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +infoTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; +%xjViewPosition = stretchMatrix*[0.400, 13*heightUnit, editBoxWidth*2.5, editBoxHeight*3]' + controlPanelOffset; +%connameTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; + +sectionViewListboxPosition = [sectionViewPosition(1)+0.4, sectionViewPosition(2)+0.02, 0.1, 0.14]; +sectionViewMoreTargetPushPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.02,0.10,0.02]; +xHairCheckPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)+0.14,0.15,0.02]; +setTRangeEditPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.06,0.10,0.02]; +setTRangeTextPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.04,0.10,0.02]; + +getStructurePushPosition = [glassViewAxesPosition(1), glassViewAxesPosition(2)-0.06, editBoxWidth/2, editBoxHeight/2]; +structureEditPosition = [getStructurePushPosition(1), getStructurePushPosition(2), 1, getStructurePushPosition(4)]; +framePosition = (controlPanelPosition - controlPanelOffset')*1.05 + 0.95*controlPanelOffset'; + +%knd +setContrastNameTextPosition = [glassViewAxesPosition(1),glassViewAxesPosition(2)-0.026,0.6,0.03]; +setContrastListPosition = [setContrastNameTextPosition(1)+setContrastNameTextPosition(3)+.01,setContrastNameTextPosition(2),0.05,setContrastNameTextPosition(4)]; +setContrastListPosition = [glassViewAxesPosition(1)+.05*glassViewAxesPosition(3),glassViewAxesPosition(2)-0.026,glassViewAxesPosition(3)*.95,0.03]; +setIndivResultsListPosition = [setTRangeTextPosition(1)-0.25,setTRangeEditPosition(2),0.20,setTRangeEditPosition(4)]; +%-- knd + +% draw figure and control +figureBKcolor=[176/255 252/255 188/255]; +figureBKcolor=get(0,'Defaultuicontrolbackgroundcolor'); +f = figure('unit','normalized','position',figurePosition,'Color',figureBKcolor,'defaultuicontrolBackgroundColor', figureBKcolor,... + 'Name','xjView', 'Tag', 'xjView', 'NumberTitle','off','resize','off','CloseRequestFcn', {@CallBack_quit, warnstate(1).state}, 'visible','off'); +handles = guihandles(f); + +% databases +try + addpath g:\ndiayek\data\atlases\ + addpath ~/data/atlases + addpath /mount/usb/data/atlases +end +try + X = load('TDdatabase'); + handles.DB = X.DB; + handles.wholeMaskMNIAll = X.wholeMaskMNIAll; +catch + handles.DB = []; + handles.wholeMaskMNIAll = struct([]); + errordlg('I can''t find TDdatabase.mat','TDdatabase not found'); +end + +handles.figure = f; +handles.frame = uicontrol(handles.figure,'style','frame',... + 'unit','normalized',... + 'position',framePosition,... + 'Visible','off'); +handles.slider = uicontrol(handles.figure,'style','slider',... + 'unit','normalized',... + 'position',sliderPosition,... + 'max',1,'min',0,... + 'sliderstep',[0.01,0.10],... + 'callback',@CallBack_slider,... + 'value',0,'Visible','on'); +handles.pValueTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',pValueTextPosition,... + 'string','pValue=','horizontal','left'); +handles.pValueEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',pValueEditPosition,... + 'horizontal','left',... + 'String', num2str(pValue),... + 'BackgroundColor', 'w',... + 'callback',@CallBack_pValueEdit); +handles.intensityThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',intensityThresholdTextPosition,... + 'string',' intensity=','horizontal','left'); +handles.intensityThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',intensityThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(intensityThreshold),... + 'callback',@CallBack_intensityThresholdEdit); +handles.dfText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',dfTextPosition,... + 'string','df= ','horizontal','right'); +handles.dfEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',dfEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', '',... + 'callback',@CallBack_dfEdit); +handles.clusterSizeThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',clusterSizeThresholdTextPosition,... + 'string','cluster size >=','horizontal','left'); +handles.clusterSizeThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',clusterSizeThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(clusterSizeThreshold),... + 'callback',@CallBack_clusterSizeThresholdEdit); +handles.thisClusterSizeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',thisClusterSizeTextPosition,... + 'string','size= ','horizontal','right', 'visible', 'off'); +handles.thisClusterSizeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',thisClusterSizeEditPosition,... + 'horizontal','left',... + 'Enable', 'inactive',... + 'String', '','visible','off'); + +handles.imageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',imageFileEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_imageFileEdit,... + 'visible','off'); +handles.saveImageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',saveImageFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myMask.img',... + 'callback',@CallBack_saveImageFileEdit,... + 'visible','off'); +handles.saveResultPSEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',resultPSFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myResult.ps',... + 'callback',@CallBack_saveResultPSEdit,... + 'visible','off'); +handles.loadImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',loadImagePushPosition,... + 'string','Load Image','callback',@CallBack_loadImagePush,... + 'visible','off'); +handles.saveImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveImagePushPosition,... + 'string','Save Image','callback',@CallBack_saveImagePush,... + 'visible','off'); +handles.saveResultPSPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveResultPSPushPosition,... + 'string','Save Result','callback',@CallBack_saveResultPSPush,... + 'visible','off'); +handles.getStructurePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',getStructurePushPosition,... + 'string','Get Structure','callback',@CallBack_getStructurePush,'visible','off'); +handles.structureEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',structureEditPosition,... + 'horizontal','center',... + 'enable', 'on',... + 'UserData',struct(... + 'hReg', [],... + 'M', M,... + 'D', DIM,... + 'xyz', [0 0 0] )); +handles.pickThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',pickThisClusterPushPosition,... + 'string','Pick Cluster/Info','callback',@CallBack_pickThisClusterPush); +handles.selectThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',selectThisClusterPushPosition,... + 'string','Select Cluster','callback',@CallBack_selectThisClusterPush); +handles.clearSelectedClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',clearSelectedClusterPushPosition,... + 'string','Clear Selection','callback',@CallBack_clearSelectedClusterPush); + +handles.displayIntensityText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',displayIntensityTextPosition,... + 'string','display intensity','horizontal','left'); +handles.allIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','All',... + 'position',allIntensityRadioPosition,... + 'value', 1,... + 'callback',@CallBack_allIntensityRadio); +handles.positiveIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only +',... + 'position',positiveIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'+'}); +handles.negativeIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only -',... + 'position',negativeIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'-'}); +handles.renderViewCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','Render View' ,... + 'horizontal', 'right',... + 'position',renderViewCheckPosition,... + 'callback', @CallBack_renderViewCheck); + +handles.sectionViewListbox = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', {'single T1','avg152PD','avg152T1','avg152T2','avg305T1','ch2','ch2bet','aal','brodmann'}, ... + 'value',3,... + 'position',sectionViewListboxPosition,... + 'callback',@CallBack_sectionViewListbox); + +handles.xHairCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','XHairs Off' ,... + 'horizontal','left',... + 'position',xHairCheckPosition,... + 'callback',@CallBack_xHairCheck); +handles.sectionViewMoreTargetPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',sectionViewMoreTargetPushPosition,... + 'string','other ...','callback',@CallBack_sectionViewMoreTargetPush); +handles.setTRangeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',setTRangeEditPosition,'BackgroundColor', 'w',... + 'string','auto','callback',@CallBack_setTRangeEdit); +handles.setTRangeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setTRangeTextPosition,... + 'string','colorbar max'); +handles.hideControlPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', '<', 'position', hideControlPushPosition,... + 'visible','off'); +handles.volumePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'volume', ... + 'position', volumePushPosition,... + 'callback', @CallBack_volumePush); +handles.commonRegionPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'common region', ... + 'position', commonRegionPushPosition,... + 'callback', @CallBack_commonRegionPush); +handles.displayPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'display', ... + 'position', displayPushPosition,... + 'callback', @CallBack_displayPush,... + 'visible','off'); +handles.allinonePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'all in one', ... + 'position', allinonePushPosition,... + 'callback', @CallBack_allinonePush,... + 'visible','off'); +%knd: +handles.setContrastNameText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setContrastNameTextPosition, 'FontSize', 13,... + 'string',' ... ','callback',@CallBack_setContrastNameTextPosition); +handles.contrastListPush = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setContrastListPosition,... + 'callback', @CallBack_contrastListPush,... + 'visible','on'); + +handles.indivResultsListPush(1) = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setIndivResultsListPosition,... + 'callback', @CallBack_indivResultsListPush,... + 'visible','on'); + +handles.paramestPush(1) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Vox Betas', ... + 'position', paramestPushPosition'.*[1 1 2 1],... + 'callback', {@CallBack_paramestRegionPush, 'vox'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'vox', 0},... + 'visible','on'); +handles.paramestPush(2) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Cluster', ... + 'position', paramestPushPosition-[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'clu'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'clu', 0},... + 'visible','on'); +handles.paramestPush(3) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Sphere', ... + 'position', paramestPushPosition-2*[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'sph'},... + 'visible','on'); +%--knd + +handles.searchPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',searchPushPosition,... + 'String', 'search','callback',@CallBack_searchPush, 'ForeGroundColor',[0 0 1]); +handles.searchContentEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',searchContentEditPosition,... + 'ForeGroundColor',[0 0 1],... + 'BackgroundColor', 'w',... + 'horizontal','left','callback', @CallBack_searchContentEdit); +handles.searchText = uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',searchTextPosition,... + 'string', ' in',... + 'horizontal','left',... + 'visible','off'); +handles.searchEnginePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',searchEnginePopPosition, ... + 'String',{'Brede';'Jede';'xBrain.org';'Google Scholar';'Pubmed';'Wikipedia'}, ... + 'Style','popupmenu', ... + 'value',1); +handles.overlayPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',overlayPushPosition,... + 'String', 'overlay','callback',@CallBack_overlayPush); +handles.overlayEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',overlayEditPosition,... + 'BackgroundColor', 'w',... + 'horizontal','left',... + 'callback', @CallBack_overlayEdit); +handles.overlayPop = uicontrol(handles.figure, 'style','popupmenu',... + 'unit','normalized','position',overlayPopPosition,... + 'string', sort(fieldnames(handles.wholeMaskMNIAll)),... + 'horizontal','left',... + 'callback', @CallBack_overlayPop); + +handles.helpPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',helpPosition,... + 'String', 'help','callback','web http://people.hnl.bcm.tmc.edu/cuixu/xjView','ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.infoTextBox = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',infoTextBoxPosition,... + 'String', 'Welcome to xjView 4','ForeGroundColor','k', 'BackgroundColor', 'w',... + 'horizontal','left', ...'fontname','times',... + 'max',2, 'min',0); +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + set(handles.infoTextBox, 'String', s); +end + +handles.glassViewAxes = axes('unit','normalized','position',glassViewAxesPosition,'XTick',[],'YTick',[],'visible','off'); + + +handles.testEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',[0.1 0.4 0.2 0.05],... + 'horizontal','left',... + 'callback',@test,... + 'visible','off'); + +% menu +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +hMenuFile = findobj(get(handles.figure,'Children'),'flat','Label','&File'); +if ~isempty(hMenuFile) + hMenuFileOpen = findobj(get(handles.figure,'Children'),'Label','&Open...'); + set(hMenuFileOpen, 'label', 'Open Figure...'); + hMenuFileSave = findobj(get(handles.figure,'Children'),'Label','&Save'); + set(hMenuFileSave, 'label', 'Save Figure ...'); + hMenuFileSaveAs = findobj(get(handles.figure,'Children'),'Label','Save &As...'); + set(hMenuFileSaveAs, 'label', 'Save Figure As ...'); +else + hMenuFile = uimenu(handles.figure, 'label', '&File'); +end + +set(hMenuFile,'ForegroundColor',[0 0 1]); +set(findobj(hMenuFile,'Position',1),'Separator','on'); +%knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open SPM file (SPM.mat) ...',... + 'CallBack',@CallBack_loadSPMmat, 'Accelerator', 'o'); +%--knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open Images (*.img) ...',... + 'CallBack',@CallBack_loadImagePush, 'Accelerator', 'o'); +uimenu('Parent',hMenuFile,'Position',2,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 0}); +uimenu('Parent',hMenuFile,'Position',3,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image as Mask (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 1}); +uimenu('Parent',hMenuFile,'Position',4,'ForegroundColor',[0 0 1],... + 'Label','Save Result (*.ps/pdf) ...',... + 'CallBack',@CallBack_saveResultPSPush); + +hMenuHelp = findobj(get(handles.figure,'Children'),'flat','Label','&Help'); +if isempty(hMenuHelp) + hMenuHelp = uimenu(handles.figure, 'label', 'xjView &Help'); +end +set(hMenuHelp,'ForegroundColor',[0 0 1]); +uimenu('Parent',hMenuHelp,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','xBrain.org: brain mapping database',... + 'CallBack','web http://www.xbrain.org -browser'); +uimenu('Parent',hMenuHelp,'Position',2,... + 'Label','xjview help','ForegroundColor',[0 0 1],... + 'CallBack','web http://people.hnl.bcm.tmc.edu/cuixu/xjView'); +set(findobj(hMenuHelp,'Position',3),'Separator','on'); +set(0,'ShowHiddenHandles',cSHH) + +if exist('cuixuBOLDretrieve') + hMenuAnalyze = uimenu('label','&Analyze','ForegroundColor',[0 0 1],'visible','on'); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess); + hMenuProcess = uimenu(hMenuAnalyze,'label','Process (GLM estimation)','ForegroundColor',[0 0 1],'callback',@CallBack_process); + hMenuSPMProcess = uimenu(hMenuAnalyze,'label','SPMProcess (GLM using SPM)','ForegroundColor',[0 0 1],'callback',@CallBack_SPMProcess); + hMenuGLMPeak = uimenu(hMenuAnalyze,'label','GLM on peak BOLD','ForegroundColor',[0 0 1],'callback',@CallBack_GLMPeak); + hMenuContrast = uimenu(hMenuAnalyze,'label','Contrast','ForegroundColor',[0 0 1],'callback',@CallBack_contrast); + hMenuFDR = uimenu(hMenuAnalyze,'label','FDR','ForegroundColor',[0 0 1],'callback',@CallBack_fdr); + hMenuROI = uimenu(hMenuAnalyze,'label','ROI: retrieve signal','ForegroundColor',[0 0 1],'callback',@CallBack_timeSeries); + hMenuROIPlot = uimenu(hMenuAnalyze,'label','ROI: plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotROI, 'Accelerator', 'm'); + hMenuROIIndividualPlot = uimenu(hMenuAnalyze,'label','ROI: individual plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROI); + hMenuROIIndividualPlotWithBehavior = uimenu(hMenuAnalyze,'label','ROI: individual plot with behavior','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROIWithBehavior); + hMenuROICorrelationPlot = uimenu(hMenuAnalyze,'label','ROI: correlation plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotCorrelationROI); + %hMenuWholeBrainCorrelation = uimenu(hMenuAnalyze,'label','Whole brain correlation','ForegroundColor',[0 0 1],'callback',@CallBack_wholeBrainCorrelation); + hMenuBehaviorAnalysis = uimenu(hMenuAnalyze,'label','Behavior analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_behaviorAnalysis); + hMenuHeadMovementAnalysis = uimenu(hMenuAnalyze,'label','Head movement analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_headMovementAnalysis); + hMenuModelComparison = uimenu(hMenuAnalyze,'label','Linear model comparison','ForegroundColor',[0 0 1],'callback',@CallBack_modelComparison); + + hMenuHNLOnly = uimenu('label','For H&NL Only','ForegroundColor',[0 0 1],'visible','on'); + hMenuNew2Old = uimenu(hMenuHNLOnly,'label','Format convert','ForegroundColor',[0 0 1],'callback',@CallBack_new2old); + hMenuPreprocessCluster = uimenu(hMenuHNLOnly,'label','Preprocess (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_preprocess, 'cluster'}); + hMenuProcessCluster = uimenu(hMenuHNLOnly,'label','Process (GLM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_process, 'cluster'}); + hMenuSPMProcessCluster = uimenu(hMenuHNLOnly,'label','SPM Process (GLM using SPM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_SPMProcess, 'cluster'}); + hMenuGLMPeakCluster = uimenu(hMenuHNLOnly,'label','GLM on peak BOLD (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_GLMPeak, 'cluster'}); +end + +figurecm = uicontextmenu; +uimenu(figurecm,'label','Red','callback','set(gcf,''color'',''r'')'); +uimenu(figurecm,'label','White','callback','set(gcf,''color'',''w'')'); +uimenu(figurecm,'label','Gray','callback','set(gcf,''color'',[0.925, 0.914, 0.847])'); +%set(handles.figure,'uicontextmenu',figurecm); +set(handles.figure,'WindowButtonDownFcn',@figureMouseUpFcn); + +set(handles.figure,'visible','on'); + +% save pre-set values +handles.system = os; +handles.spmdir = spmdir; +handles.screenResolution = screenResolution; +handles.pValue = pValue; +handles.intensityThreshold = intensityThreshold; +handles.clusterSizeThreshold = clusterSizeThreshold; +handles.sectionViewPosition = sectionViewPosition; +handles.sectionViewTargetFile = getSectionViewTargetFile(spmdir, 'avg152T1'); +%knd +if exist('xjview.opt') + tmp=textread('xjview.opt','%s');eval(tmp{:}); + handles.sectionViewTargetFile = anatomy; +else + if ~isempty(findstr('gazemo', pwd)) + handles.sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean.img'); + end +end +guidata(f, handles); + +% global variables for rotation matrix M and dimension +global M_; +global DIM_; +global TR_; +global LEFTRIGHTFLIP_; +global TMAX_; % colorbar max to display in section view +M_ = M; +DIM_ = DIM; +TR_ = TR; +LEFTRIGHTFLIP_ = leftrightflip; +TMAX_ = 'auto'; + +% check input arguments +if length(varargin) == 0 + CallBack_loadSPMmat(handles.loadImagePush) + % if exist(fullfile(pwd,'SPM.mat'), 'file') + % xSPM=load(fullfile(pwd,'SPM.mat')); + % numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', length(xSPM.SPM.xCon)); + % if ~isempty(numc) + % CallBack_loadImagePush(handles.loadImagePush, [], {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)}); + % end + % end +elseif isstr(varargin{1}) + if isempty(findstr('.mat', varargin{1})) + CallBack_loadImagePush(handles.loadImagePush, [], varargin); + else + CallBack_loadSPMmat(handles.loadImagePush, [], varargin{1}); + end +else + mniCoord = varargin{1}; + if length(varargin) < 2 + intensity = ones(size(mniCoord,1),1); + else + intensity = varargin{2}; + end + thisStruct.mni = mniCoord; + thisStruct.intensity = intensity; + thisStruct.M = M; + thisStruct.DIM = DIM'; + CallBack_loadImagePush(handles.loadImagePush, [], thisStruct); +end + + + +function test(hObject, eventdata) +handles = guidata(gcbo); +set(hObject, 'String', num2str(handles.pValue)); +vars = evalin('base','who'); +vars +x = evalin('base',vars{1}); +x +handles.DIM + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdr(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); + +if get(handles.allIntensityRadio, 'Value') + positive = 1; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end +xjviewpath = fileparts(which('xjview')); +maskImageFile = fullfile(xjviewpath, 'mask.img'); +[threshold, pvalue] = fdr(handles.imageFileName{1}, q, positive, maskImageFile); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% model comparison +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_modelComparison(hObject, eventdata) +answer = getVariable({'y','x (full model)', 'x (reduced model)'}); + +if isempty(answer) + return; +end + +if ~isempty(answer{1}) + y = evalin('base',answer{1}); +else + return; +end +if ~isempty(answer{2}) + xf = evalin('base',answer{2}); % full model +else + return; +end +if ~isempty(answer{3}) + xr = evalin('base',answer{3}); % reduced model +else + xr = []; +end + +% make vector column vector +[r, c] = size(y); +if r==1; y = y'; end +[r, c] = size(xf); +if r(0.5+ii/10); +end + +K = {zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1))}; +for ii=1:size(C,1) + for jj=1:4 + K{jj}(ii) = sum(CC{jj}(ii,:)) - 1; + end +end + +x=[0:size(C,1)]; +for jj=1:4 + y{jj}=zeros(size(x)); +end + +for ii=1:length(x) + for jj=1:4 + y{jj}(ii) = sum(K{jj} == x(ii)); + end +end + +figure; +loglog(x,y{1}, x, y{2}, x, y{3}, x, y{4}); +xlabel('degree'); +ylabel('counts'); +legend('0.6', '0.7', '0.8', '0.9'); +axis equal + + +z = sum(abs(C))-1; +zx = 0:max(z); +for ii=1:length(zx)-1 + pos = find(z>zx(ii) & z<=zx(ii+1)); + zy(ii) = length(pos); +end +figure; +loglog(zx(1:length(zy)),zy); +xlabel('weighted degree'); +ylabel('counts'); +axis equal + +xjview(cor2mni(coord, handles.M{1}), z); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get/select variable names in base workspace +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function vars = getVariable(titles) +vars = evalin('base','who'); +height = 0.07; +f = dialog('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.4 0.4], 'name', 'pick variables', 'NumberTitle','off'); +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', 'Available variables', ... + 'position',[0 0.9 0.5 0.1/2]); +variableListbox = uicontrol(f,'style','listbox','tag','variableListbox',... + 'unit','normalized',... + 'String', vars, ... + 'value',1,... + 'position',[0 0 0.5 0.9]); +okPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'OK', ... + 'position',[0.55 0.05 0.2 height],... + 'callback','uiresume'); +cancelPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'Cancel', ... + 'position',[0.75 0.05 0.2 height],... + 'callback','delete(gcf)'); + +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{1}, ... + 'position',[0.5 0.9 0.5 0.1/2]); +imageDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.8 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''imageDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); +imageDataEdit = uicontrol(f,'style','edit','tag','imageDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.8 0.3 height]); + +if length(titles)>=2 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{2}, ... + 'position',[0.5 0.7 0.5 0.1/2]); + eventDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.6 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''eventDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + eventDataEdit = uicontrol(f,'style','edit','tag','eventDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.6 0.3 height]); +end +if length(titles)>=3 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{3}, ... + 'position',[0.5 0.5 0.5 0.1/2]); + correlatorDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.4 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''correlatorDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + correlatorDataEdit = uicontrol(f,'style','edit','tag','correlatorDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.4 0.3 height]); +end +if length(titles)>=4 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{4}, ... + 'position',[0.5 0.3 0.5 0.1/2]); + otherDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.2 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''otherDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + otherDataEdit = uicontrol(f,'style','edit','tag','otherDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.2 0.3 height]); +end + +uiwait(f); +try + var{1} = get(imageDataEdit,'string'); + if length(titles)>=2 + var{2} = get(eventDataEdit,'string'); + end + if length(titles)>=3 + var{3} = get(correlatorDataEdit,'string'); + end + if length(titles)>=4 + var{4} = get(otherDataEdit,'string'); + end + vars = var; + delete(f); +catch + vars = {}; + try + delete(f); + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% quit xjview +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_quit(hObject, eventdata, warnstate) +warning(warnstate) +% try +% rmdir('xjviewtmp'); +% end +delete(gcf); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mouse double click +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function figureMouseUpFcn(hObject, eventdata) +status = get(hObject, 'SelectionType'); + +% double click +if strcmp(status, 'extend') + handles = guidata(hObject); + CallBack_loadImagePush(handles.loadImagePush, eventdata); +elseif strcmp(status, 'open') + handles = guidata(hObject); + CallBack_loadSPMmat(handles.loadImagePush, eventdata); +else + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change edit image file name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_imageFileEdit(hObject, eventdata) +handles = guidata(hObject); +filename = get(hObject, 'String'); +filename = str2cell(filename); +CallBack_loadImagePush(handles.loadImagePush, eventdata, filename); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_contrastListPush(hObject, eventdata) +handles = guidata(hObject); +connum = get(handles.contrastListPush,'Value'); +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); +if ~exist(spmfile) + set(handles.contrastListPush,'Value',0); +else + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + connames=get(handles.contrastListPush,'String'); + CallBack_loadImagePush(hObject,eventdata,fullfile(img.p, cons(connum).Vspm.fname), connum) +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadImagePush(hObject, eventdata, thisfilename, ContrastName) +handles = guidata(hObject); +handles.imageFileName=[]; handles.M=[]; handles.DIM=[]; handles.TF=[]; handles.df=[]; +handles.mni=[]; handles.intensity=[]; handles.currentmni=[]; handles.currentintensity=[]; handles.currentDisplayMNI=[]; handles.currentDisplayIntensity=[]; +if nargin>3 + handles.imageContrastName=ContrastName; +else + handles.imageContrastName=[]; +end +if ~exist('thisfilename') + thisfilename = ''; +end + +if isstruct(thisfilename) + handles.imageFileName = {''}; + handles.mni = {thisfilename.mni}; + handles.intensity = {thisfilename.intensity}; + handles.M = {thisfilename.M}; + handles.DIM = {thisfilename.DIM}; + handles.TF = {'S'}; + handles.df = {1e6}; + handles.pValue = 1; + set(handles.pValueEdit, 'string', '1'); + handles.clusterSizeThreshold = 0; + set(handles.clusterSizeThresholdEdit, 'String', '0'); + handles.imageContrastName={''}; +else + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); +end + +if isempty(handles.imageFileName) + return +end + +% tries to find firts-level matching data +% knd +set(handles.indivResultsListPush(1),'String', ... + getfield2(dir(fileparts(fileparts(handles.imageFileName{1}))), 'name')); + +different = 0; % image files are same or different? +if length(handles.TF)>1 + for ii=1:length(handles.TF) + if strcmp(handles.TF{ii},handles.TF{1}) & isequal(handles.df{ii},handles.df{1}) & isequal(handles.M{ii},handles.M{1}) & isequal(handles.DIM{ii},handles.DIM{1}) + continue; + else + warndlg('Images are from different statistics or sources.', 'Warning'); + %set(handles.infoTextBox, 'string', 'Images are from different statistics or sources.'); + beep; + different = 1; + break; + end + end +end + +% reset files with empty df/TF to df=1 and TF='S'. 'S'=='T' but has a tag +% meaning it is changed. +resetTF = 0; +for ii=1:length(handles.TF) + if isempty(handles.TF{ii}) + handles.TF{ii} = 'S'; + resetTF = 1; + end + if isempty(handles.df{ii}) | isequal(handles.df{ii},0) + handles.df{ii} = 1e6; + resetTF = 1; + end +end + +handles.currentmni = handles.mni; +handles.currentintensity = handles.intensity; + +set(handles.dfEdit, 'String', cell2str(handles.df)); +set(handles.imageFileEdit, 'String', cell2str(handles.imageFileName)); % s=-log10(p) +maxs = maxcell(t2s(cellmax(handles.intensity,'abs'),handles.df, handles.TF),'abs'); +if isinf(maxs); maxs = 20; end +set(handles.slider, 'Max', maxs, 'Min', 0, 'sliderstep',[min(maxs/100,0.05),min(maxs/100,0.05)]); +if handles.TF{1}=='T' & different == 0 + str = [blanks(length(' intensit')) 'T=']; +elseif handles.TF{1}=='F' & different == 0 + str = [blanks(length(' intensit')) 'F=']; +else + str=' intensity='; +end +set(handles.intensityThresholdText, 'String', str); +set(handles.figure,'Name',['xjView: ' cell2str(handles.imageFileName)]); +try + for ii=1:length(handles.hLegend) + delete(handles.hLegend{ii}); + end +end +nimg=length(handles.TF); +if nimg>1 + colours = {'r';'g';'y';'c';'b';'m'}; + %colours = colours(mod(0:nimg-1,length(colours))+1); + %colours = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],100,1); + % read_conname = spm_input({'Retrieve contrasts names','Should I read SPM files to retrieve filenames?'},... + % 1,'bd',{'YES','NO'},[1,0]); + read_conname = 1; + for ii=1:nimg + [tmp,filename] = fileparts(handles.imageFileName{ii}); + c_names{ii} = filename ; + if read_conname & exist(fullfile(tmp, 'SPM.mat')) + tmp=load(fullfile(tmp, 'SPM.mat')); + tmp.Vspm=[tmp.SPM.xCon.Vspm]; + tmp.iCon=strmatch(filename, {tmp.Vspm.fname}); + if ~isempty(tmp.iCon) + c_names{ii} = [ [tmp.SPM.xCon(tmp.iCon).name] ' [' c_names{ii} ']']; + end + end + end + [tmp] = inputdlg({'colors' 'names'},'Loading',6,[{strvcat(c_names)};{strvcat(colours)}]); + colours = colorname2rgb(tmp{2}); + c_names = cellstr(tmp{1}); + + for ii=1:min(length(handles.TF),10) + filename = c_names{ii}; + if ii == 10; filename = '......'; end + pos0 = handles.sectionViewPosition; + pos(1) = pos0(1)+pos0(3)/2+0.03; + pos(2) = pos0(2)+ii/50-0.03; + pos(3) = 0.12; + pos(4) = 0.02; + handles.hLegend{ii}=uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',pos,... + 'string', filename,... + 'horizontal','left',... + 'fontweight','bold',... + 'ForeGroundColor',colours(ii,:)); + end + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; +end +guidata(hObject, handles); + +global M_; +global DIM_; +M_ = handles.M{1}; +DIM_ = handles.DIM{1}; + +if resetTF==1 + set(handles.pValueEdit,'string',1); +end +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% display info +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + report{1} = s; +catch + report{1} = 'Welcome to xjView 4'; +end +for jj=1:length(handles.imageFileName) + report{2+6*(jj-1)} = cell2str(handles.imageFileName(jj)); + if handles.TF{jj} == 'T' | handles.TF{jj} == 'F' + report{3+6*(jj-1)} = ['This is a ' handles.TF{jj} ' test image.']; + else + report{3+6*(jj-1)} = '';%['I don''t know what test this image came from.']; + end + report{4+6*(jj-1)} = 'mat = '; + report{5+6*(jj-1)} = num2str(handles.M{jj}); + report{6+6*(jj-1)} = 'dimension = '; + report{7+6*(jj-1)} = num2str(handles.DIM{jj}); +end +if length(handles.imageFileName)==1 + [img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); + spmfile=fullfile(img.p,'SPM.mat'); + if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); + end + end + if exist(spmfile) + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + for i=1:length(cons) + if not(isempty(cons(i).Vspm)) + consfilename{i}=cons(i).Vspm.fname; + else + consfilename{i}=''; + end + end + connum=strmatch([img.fname img.ext],consfilename); + if ~isempty(connum) + conlabel=cons(connum).name; + set(handles.figure,'Name',[get(handles.figure,'Name') ' :: ' conlabel]); + set(handles.contrastListPush,'String',{cons.name}) + set(handles.contrastListPush,'Value',connum) + set(handles.setContrastNameText,'String',[conlabel]); + report=[report(1:3) {['Contrast name in SPM.mat: (' num2str(connum) ') ' conlabel]} report(4:end)]; + else + set(handles.contrastListPush,'String',{'[none]'}) + set(handles.contrastListPush,'Value',0) + set(handles.contrastListPush,'Enable','on') + report=[report(1:3) {['Contrast has no matching name in SPM.mat']} report(4:end)]; + end + end +end +set(handles.infoTextBox, 'string', report); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pValueEdit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pValueEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +tmps = -log10(tmp); +if isnan(tmp) | tmp < 0 | tmp > 1 + errordlg('I don''t understand the input.','error'); + set(hObject, 'String', handles.pValue); + return +end + +if tmps>get(handles.slider,'max') | tmps maxcell(cellmax(handles.intensity,'abs')) + tmp = maxcell(cellmax(handles.intensity,'abs')); +end + +handles.pValue = t2p(tmp, handles.df{1}, handles.TF{1}); +handles.intensityThreshold = p2t(num2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); +set(handles.slider,'Value', -log10(handles.pValue)); +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +guidata(hObject, handles); +CallBack_slider(hObject, eventdata, -log10(handles.pValue)); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% slider bar +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_slider(hObject, eventdata, value) + +handles = guidata(hObject); + +if exist('value') + s = value; + if s > get(handles.slider,'max') + s = get(handles.slider,'max')*0.99; + end + if s < get(handles.slider,'min') + s = get(handles.slider,'min'); + end +else + s = get(hObject,'Value'); +end + +set(handles.slider, 'value', s); +pvalue = 10^(-s); +set(handles.pValueEdit,'String',num2str(pvalue)); +t = p2t(num2cell(pvalue*ones(1,length(handles.TF))), handles.df, handles.TF); +handles.intensityThreshold = t; +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +handles.pValue = pvalue; +for ii=1:length(handles.TF) + pos{ii} = find(abs(handles.intensity{ii})>=t{ii}); + handles.currentintensity{ii} = handles.intensity{ii}(pos{ii}); + handles.currentmni{ii} = handles.mni{ii}(pos{ii},:); +end + +guidata(hObject,handles); + +if get(handles.allIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.allIntensityRadio, eventdata); +elseif get(handles.positiveIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.positiveIntensityRadio, eventdata, '+'); +elseif get(handles.negativeIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.negativeIntensityRadio, eventdata, '-'); +end + +set(handles.infoTextBox, 'string', {'Don''t drag the slider bar too fast. Release your mouse button at least 1 second later.', ... + 'This sounds stupid. But there is a bug (probably MatLab bug) which I can'' fix right now.', ... + 'I suggest you confirm the correctness of the current display by press Enter in the pValue edit box.'}); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display intensity all+- radios +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allIntensityRadio(hObject, eventdata, pnall) +% pnall = '+', '-', 'a' (all) or 'c' for current (simply update drawing) +% +handles = guidata(hObject); + +currentselect = []; +if get(handles.allIntensityRadio, 'Value'); currentselect = handles.allIntensityRadio; thispnall = 'a'; end +if get(handles.positiveIntensityRadio, 'Value'); currentselect = handles.positiveIntensityRadio; thispnall = '+'; end +if get(handles.negativeIntensityRadio, 'Value'); currentselect = handles.negativeIntensityRadio; thispnall = '-'; end + +set(handles.allIntensityRadio, 'Value', 0); +set(handles.positiveIntensityRadio, 'Value', 0); +set(handles.negativeIntensityRadio, 'Value', 0); + +if exist('pnall') + if pnall=='c' + hObject = currentselect; + pnall = thispnall; + end +end + +set(hObject, 'Value', 1); + +if ~isfield(handles,'currentintensity') + return +end +for ii=1:length(handles.TF) + if exist('pnall') + if pnall == '-' + pos{ii} = find(handles.currentintensity{ii} < 0); + elseif pnall == '+' + pos{ii} = find(handles.currentintensity{ii} > 0); + elseif pnall == 'a' + pos{ii} = 1:length(handles.currentintensity{ii}); + end + else + pos{ii} = 1:length(handles.currentintensity{ii}); + end + intensity{ii} = handles.currentintensity{ii}(pos{ii}); + mni{ii} = handles.currentmni{ii}(pos{ii},:); + cor{ii} = mni2cor(mni{ii}, handles.M{ii}); + + if ~isempty(cor{ii}) + A = spm_clusters(cor{ii}'); + pos0 = []; + for kk = 1:max(A) + jj = find(A == kk); + if length(jj) >= handles.clusterSizeThreshold; pos0 = [pos0 jj]; end + end + handles.currentDisplayMNI{ii} = mni{ii}(pos0,:); + handles.currentDisplayIntensity{ii} = intensity{ii}(pos0); + else + handles.currentDisplayMNI{ii} = mni{ii}([],:); + handles.currentDisplayIntensity{ii} = intensity{ii}([]); + end +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% list of contrasts + +set(handles.contrastListPush,'String',regexprep(get(handles.contrastListPush,'String'),' \[Only [\+-a]\]$','')) +set(handles.setContrastNameText,'String',regexprep(get(handles.setContrastNameText,'String'),' \[Only [\+-a]\]$','')) + +if exist('pnall','var') + if ~isequal(pnall, 'a') + set(handles.setContrastNameText,'String',[get(handles.setContrastNameText,'String') ' [Only ' pnall ']']); + s=get(handles.contrastListPush,'String'); + s{get(handles.contrastListPush,'Value')}=[s{get(handles.contrastListPush,'Value')} ' [Only ' pnall ']']; + + set(handles.contrastListPush,'String',s); + end +end + +if get(handles.allIntensityRadio, 'Value') & max(handles.currentDisplayIntensity{1}) < 0 + warndlg('No supra-threshold positive intensity. Only negative intensity is displayed.'); +end + +try + set(handles.figure,'currentaxes', handles.glassViewAxes); + xrange = xlim; + yrange = ylim; + try + delete(handles.hGlassText) + end + if ~isempty(handles.selectedCluster,1) + %handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + end +end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% render view check? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderViewCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% which section view target file? list box +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewListbox(hObject, eventdata) +handles = guidata(hObject); +contents = get(handles.sectionViewListbox,'String'); +currentsel = contents{get(handles.sectionViewListbox,'Value')}; +handles.sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get sectionviewtargetfile +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sectionViewTargetFile = getSectionViewTargetFile(spmdir, selectedcontent) +if findstr('SPM2',spm('ver')) + fileext = 'mnc'; +elseif findstr('SPM5',spm('ver')) + fileext = 'nii'; +end +currentsel = selectedcontent; +if ~isempty(strfind(currentsel, 'single')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['single_subj_T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152PD')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152PD.' fileext]); +elseif ~isempty(strfind(currentsel, '152T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152T2')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T2.' fileext]); +elseif ~isempty(strfind(currentsel, '305T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg305T1.' fileext]); +elseif strcmp(currentsel, 'ch2') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2.img'); +elseif strcmp(currentsel, 'ch2bet') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2bet.img'); +elseif strcmp(currentsel, 'aal') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'aal.img'); +elseif strcmp(currentsel, 'brodmann') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'brodmann.img'); + %knd: +elseif ~isempty(strfind(currentsel, 'gazemo')) + sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean-no120.img'); + %sectionViewTargetFile = fullfile('D:\ndiayek\data\gazemo\group\anat', 'mean-no120.img'); +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% xhairs in section view? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_xHairCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + spm_orthviews('Xhairs','off'); +else + spm_orthviews('Xhairs','on'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% other target file for section view, push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewMoreTargetPush(hObject, eventdata) +handles = guidata(hObject); +[filename, pathname, filterindex] = uigetfile('*', 'Pick an target file'); +if isequal(filename,0) | isequal(pathname,0) + return; +end +handles.sectionViewTargetFile = fullfile(pathname, filename); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% set colorbar range +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_setTRangeEdit(hObject, eventdata) +global TMAX_; +handles = guidata(hObject); +TMAX_ = get(hObject, 'String'); +if isempty(str2num(TMAX_)) && ~strcmp(TMAX_, 'auto') + return; +end +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change degree of freedome +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_dfEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2cell(get(hObject, 'String')); +if iscellstr(tmp) + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.df); + catch + set(hObject, 'String', ''); + end + return +end +handles.df=tmp; + + +if isfield(handles,'TF') + t = p2t(mat2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); + handles.intensityThreshold = t; + set(handles.intensityThresholdEdit, 'String', cell2str(t)); +end + +guidata(hObject, handles); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get structure push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_getStructurePush(hObject, eventdata) +handles = guidata(hObject); +xyz = spm_XYZreg('GetCoords',handles.hReg); +tmp_coor = cuixuFindTDstructure(xyz', handles.DB, 0); +set(handles.structureEdit,'String', tmp_coor{1}); +handles.currentxyz = xyz'; +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% structure edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_structureEdit(action, xyz, thisfun, hReg) + +try + handles=guidata(hReg); +catch + return; +end + +handles.currentxyz = xyz'; +guidata(hReg, handles); + +try + [tmp_coor, cellstructure] = cuixuFindTDstructure(xyz', handles.DB, 0); +catch + return; +end + +set(handles.structureEdit,'String', tmp_coor{1}); + +for ii=[5 3 2 1 4] + if strfind('Unidentified', cellstructure{ii}) + continue; + else + set(handles.searchContentEdit,'string', trimStructureStr(cellstructure{ii})); + set(handles.searchContentEdit,'UserData', 'auto'); + return; + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% trim str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = trimStructureStr(str) +pos = findstr('(', str); +if ~isempty(pos) + str(pos-1:end)=[]; +end +out = str; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cluster size threshold edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clusterSizeThresholdEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +if isnan(tmp) | tmp<0 + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.clusterSizeThreshold); + catch + set(hObject, 'String', '5'); + end + return +end +handles.clusterSizeThreshold=tmp; + +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImagePush(hObject, eventdata, thisfilename, isMask) +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}); + return; + end + end + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}); + return; + end +end + +[filename, pathname] = uiputfile('*.img', 'Save image file as', get(handles.saveImageFileEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + +if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName{1}) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity'), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}, isMask); + return; + end +end + +mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, '', isMask); + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImageFileEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveImagePush(handles.saveImagePush, eventdata, get(hObject,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSPush(hObject, eventdata, thisfilename) + +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + spm_print(handles.figure); + if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); + elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); + end + return; + end +end + +[filename, pathname] = uiputfile('*.ps', 'Save result as', get(handles.saveResultPSEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +% print +H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +pos = get(H,'position'); +index = []; + +for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 & pos{ii}(2) > 0.5 + set(H(ii),'position',[pos{ii}(1), pos{ii}(2), pos{ii}(3)*3/4, pos{ii}(4)]); + index = [index ii]; + end +end + + +spm_print(handles.figure); +if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); +elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); +end + +% set the position back +set(H(index), {'position'}, pos(index)); + + +% printstr = ['print -dpsc2 -painters -noui ' '''' thisfilename '''']; +% try +% orient portrait +% eval(printstr); +% printsuccess = 1; +% catch +% errordlg('Print to ps file failed', 'print error'); +% printsuccess = 0; +% end +%set(H,{'Units'},un); +% if strcmp(handles.system, 'linux') & printsuccess == 1 +% system(['ps2pdf ' '''' thisfilename '''']); +% end + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveResultPSPush(hObject, eventdata, get(handles.saveResultPSEdit,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% select a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_selectThisClusterPush(hObject, eventdata) +handles = guidata(hObject); + +try + xyz = handles.currentxyz'; +catch + xyz = spm_XYZreg('GetCoords',handles.hReg); +end + +try + handles.selectedCluster = [handles.selectedCluster; xyz']; +catch + handles.selectedCluster = xyz'; +end + +disp('handles defines!') +assignin('base','handles',handles) + +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + delete(handles.hGlassText) +end +%handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% unselect a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clearSelectedClusterPush(hObject, eventdata) +handles = guidata(hObject); +try + handles = rmfield(handles,'selectedCluster'); +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + %delete(handles.hGlassText) + set(handles.infoTextBox, 'string', ['No clusters selected']); +end + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pick a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pickThisClusterPush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return; +end + +if ~isfield(handles, 'selectedCluster') | isempty(handles.selectedCluster) + try + xyz = handles.currentxyz'; + catch + xyz = spm_XYZreg('GetCoords',handles.hReg); + end + handles.selectedCluster = xyz'; +end + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); +xyzcor = mni2cor(handles.selectedCluster, handles.M{1}); + +pos = []; +for ii = 1:size(xyzcor,1) + pos0 = find(cor(:,1)==xyzcor(ii,1) & cor(:,2)==xyzcor(ii,2) & cor(:,3)==xyzcor(ii,3)); + if isempty(pos0) + continue; + end + pos = [pos find(A==A(pos0(1)))]; +end +if isempty(pos) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return +end + +pos = unique(pos); + +tmpmni = mni(pos,:); +tmpintensity = intensity(pos); + +[B,I,J] = unique(tmpmni, 'rows'); +handles.currentDisplayMNI = {B}; +fprintf('Cluster defined from: %s \n', handles.imageFileName{1}); +assignin('base', 'currentDisplayMNI', handles.currentDisplayMNI ); +handles.currentDisplayIntensity = {tmpintensity(I,:)}; + +handles.currentxyz = handles.selectedCluster(end,:); + +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; + +handles.selectedCluster = []; +try + delete(handles.hGlassText) +end + +guidata(hObject, handles); + +set(handles.thisClusterSizeEdit,'string', num2str(size(handles.currentDisplayMNI{1},1))); +str = get(handles.searchContentEdit, 'string'); +pos = findstr(' ', str); +str(pos) = []; +files = []; +for ii=1:length(handles.imageFileName) + [a,b,c] = fileparts(handles.imageFileName{ii}); + files = [files b]; +end +if ~isempty(files) + files = ['_from_' files]; +end + +set(handles.saveImageFileEdit, 'string', [str files '.img']); + +% list structure of voxels in this cluster +[a, b] = cuixuFindTDstructure(cell2mat(handles.currentDisplayMNI'), handles.DB, 0); +names = unique(b(:)); +index = NaN*zeros(length(b(:)),1); +for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; +end + +for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); +end +for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end +end +report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; +% format long +% disp(b) +% disp(report) +% format +report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; +for ii=2:size(report,1) + if strcmp('Unidentified', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; +end + +report2 = [report2, {'','select and Ctrl-C to copy'}]; +% f = figure('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.2 min(0.7,0.016*length(report2))], 'name', 'cluster information', 'NumberTitle','off'); +% hEdit = uicontrol(f,'style','edit',... +% 'unit','normalized','position',[0 0 1 1],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', report2,... +% 'max',2,'min',0); + +set(handles.infoTextBox, 'string', report2); +assignin('base', 'ans', handles.currentDisplayMNI) +disp('Cluster coordinates in "ans"') +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commonRegion push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_commonRegionPush(hObject, eventdata) +handles = guidata(hObject); +if ~isfield(handles,'TF') | length(handles.TF)<=1 + %msgbox('Two or more images need to be loaded to find the common region.', 'info'); + set(handles.infoTextBox, 'string', 'Two or more images need to be loaded to find the common region.'); + beep + return; +end + +common = handles.currentDisplayMNI{1}; +for ii=2:length(handles.TF) + common = intersect(common, handles.currentDisplayMNI{ii}, 'rows'); +end + +if isempty(common) + %msgbox('No common region found.', 'info'); + set(handles.infoTextBox, 'string', 'No common region found.'); + beep + return; +end + +tmpMNI = cell2mat(handles.currentDisplayMNI'); +tmpIntensity = cell2mat(handles.currentDisplayIntensity'); +intensity = zeros(size(common,1),1); + +for ii=1:size(common,1) + pos = find(abs(tmpMNI(:,1)-common(ii,1))<0.1 & abs(tmpMNI(:,2)-common(ii,2))<0.1 & abs(tmpMNI(:,3)-common(ii,3))<0.1); + intensity(ii) = prod(tmpIntensity(pos)); +end + +handles.currentDisplayMNI = {common}; +handles.currentDisplayIntensity = {intensity}; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% if isfield(handles,'hLegend') +% try +% set(cell2mat(handles.hLegend'),'visible',{'off'}); +% end +% end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_volumePush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; + + +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(intensity, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-intensity, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((intensity), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((intensity), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +elseif findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); +end + +spm_list('List',xSPM,handles.hReg); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_displayPush(hObject, eventdata) +handles = guidata(hObject); +spm_image('init', handles.imageFileName); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% all in one +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allinonePush(hObject, eventdata) +try + if findstr('SPM2',spm('ver')) + P = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P = spm_select(Inf,'image','Select image files'); + end + +catch + return; +end +if isempty(P) + return +end + +handles = guidata(hObject); +%if ~isfield(handles,'hReg') | ~isfield(handles,'hSection') | ~isfield(handles,'hcolorbar') +tmp = [0 0 0]; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(tmp([],:), [], hObject, handles); +%end + +colors=mycolourset; +for ii=1:size(P,1) + thisfilename = deblank(P(ii,:)); + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); + cor = mni2cor(handles.mni, handles.M); + spm_orthviews('addcolouredblobs',1,cor',handles.intensity',handles.M,colors(mod(ii,6)+1,:)); +end +spm_orthviews('Redraw'); + +guidata(hObject, handles); + +% contents = get(handles.sectionViewListbox,'String'); +% currentsel = contents{get(handles.sectionViewListbox,'Value')}; +% sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +% +% % spm_image('init', sectionViewTargetFile); +% % spm_image('addblobs'); +% % return + +% guidata(hObject, handles); +% load xSPM; +% VOL.XYZ = xSPM.XYZ; +% VOL.Z = xSPM.Z; +% VOL.M = handles.M; + +%addcolouredimage(handles.hSection, '333.img',[1 0 1]); +% uigetfiles +% nblobs = 4; +% for i=1:nblobs, +% %[SPM,VOL] = spm_getSPM; +% %c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); +% c = i; +% VOL.XYZ = ceil(rand(3,20)*20); +% VOL.Z = randn(1,20); +% VOL.M = handles.M; +% colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +% spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); +% end; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPush(hObject, eventdata) +handles = guidata(hObject); + +tobeoverlay = deblank(get(handles.overlayEdit, 'string')); + +if isempty(tobeoverlay) + return; +end + +tobeoverlay = str2cell(tobeoverlay, ' '); +if isnumeric(tobeoverlay{1}) + if length(tobeoverlay{1})>1 + errordlg(['Your input, ' deblank(get(handles.overlayEdit, 'string')) ', seems coincide with a matlab constant.'], 'error'); + return + end + for ii=1:length(tobeoverlay) + tobeoverlay{ii} = num2str(tobeoverlay{ii}); + end +end +fn = fieldnames(handles.wholeMaskMNIAll); +for ii=1:length(tobeoverlay) + pos{ii} = []; + for jj=1:length(fn) + x = []; + if ~isempty(str2num(tobeoverlay{ii})) + y = str2cell(fn{jj},'_'); + for kk=1:length(y) + x = isequal(tobeoverlay{ii}, y{kk}); + if x; break;end; + end + if x==0; x = []; end; + else + x = findstr(lower(tobeoverlay{ii}), lower(fn{jj})); + end + if ~isempty(x) + pos{ii} = [pos{ii} jj]; + end + end +end +common = pos{1}; +for ii=2:length(pos) + common = intersect(common, pos{ii}); +end + +if isempty(common) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return +end + +mask = []; +for ii=1:length(common) + eval(['mask = [mask; handles.wholeMaskMNIAll.' fn{common(ii)} '];']); +end + +if isempty(mask) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return; +end + +try + handles.mni; +catch + delete(gcf); + xjview(mask); + return; +end + +handles.imageFileName = [handles.imageFileName, {deblank(get(handles.overlayEdit, 'string'))}]; +handles.M = [handles.M, {handles.M{1}}]; +handles.DIM = [handles.DIM, {handles.DIM{1}}]; +handles.currentDisplayMNI = [handles.currentDisplayMNI, {mask}]; +m = max(abs(cell2mat(handles.currentDisplayIntensity'))); +if ~isempty(m) + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {-2*m*ones(size(mask,1),1)}]; +else + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {ones(size(mask,1),1)}]; +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_overlayPush(handles.overlayPush, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region popup +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPop(hObject, eventdata) +handles = guidata(hObject); +names = get(hObject, 'string'); +value = get(hObject, 'value'); +set(handles.overlayEdit, 'string', names{value}); +CallBack_overlayEdit(handles.overlayEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% search xBrain.org and other databases +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchPush(hObject, eventdata) + +try + handles = guidata(hObject); + searchContent = get(handles.searchContentEdit,'string'); + searchEngine = get(handles.searchEnginePop,'string'); + searchEngine = searchEngine{get(handles.searchEnginePop,'value')}; + + + xyz = str2num(searchContent); + searchMode=get(handles.searchContentEdit,'UserData'); + + switch searchMode + case 'auto'; + xyz = spm_XYZreg('GetCoords',handles.hReg); + handles.currentxyz = xyz'; + guidata(hObject, handles); + [a,b] = cuixuFindTDstructure(xyz', handles.DB, 0); + try + brodmann = strmatch('Brodmann',b) + brodmann = b{brodmann}; + brodmann = brodmann(1:end-4); + end; + try + region = b{3}; + region = region(1:end-4); + end + + case 'manual' + if isempty(xyz) + searchMode='text'; + elseif length(xyz)==3 + searchMode='xyz'; + end + end + + + switch searchEngine + case 'Brede' + switch searchMode + case 'auto' + searchString = sprintf(' %0.0f',xyz') + set(handles.searchContentEdit,'string',searchString); + case 'xyz' + searchString = num2str(xyz');%searchContent=sprintf('+%0.0f',searchContent) + case 'text' + end + urlstr = ['http://hendrix.imm.dtu.dk/cgi-bin/brede_loc_query.pl?q=' searchString ]; + case 'xBrain.org' + switch searchMode + case { 'auto' 'xyz'} + xbrainSearchField = 'mni or tal&mnidistance=20'; + searchString = sprintf(' %0.1f',xyz')% searchString = num2str(xyz'); + case 'text' + xbrainSearchField = 'region'; + searchString = searchContent; + end + set(handles.searchContentEdit,'string',searchString); + urlstr = ['http://people.hnl.bcm.tmc.edu/cuixu/cgi-bin/bmd/paper.pl?search_content=' searchString '&search_field=' xbrainSearchField]; + case 'Google Scholar' + if isequal(searchMode,'auto' ) + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22|',searchString{:}); + try + searchString = searchString(1:end-1); + end + %set(handles.searchContentEdit,'string',searchString); + end + urlstr = ['http://scholar.google.com/scholar?q=' searchString ]; + case 'Pubmed' + switch searchMode + case 'auto' + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22 OR ',searchString{:}); + try + searchString = searchString(1:end-4); + end + %searchString = brodmann; + case 'text' + searchString = searchContent; + end + % urlstr = ['http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=PureSearch&db=pubmed&details_term=(' searchString ')']; + urlstr = ['http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=search&db=pubmed&pubmedfilters=true&term=(' searchString ')']; + case 'Wikipedia' + if isequal(searchMode,'auto') + searchString = region; + end + urlstr = ['http://en.wikipedia.org/w/index.php?search=%22' searchString '%22']; + end + set(handles.searchContentEdit,'UserData',searchMode); +catch + urlstr = 'http://www.google.com'; +end + +try + web(urlstr,'-browser'); +catch + if exist('c:\program Files\mozilla Firefox\firefox.exe','file') + system(['"c:\program Files\mozilla Firefox\firefox.exe" "' urlstr '"']) + else + web(urlstr); + end +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% control panel on or off +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function controlHide(handles, status) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get multiple values from a string deliminated delim +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = str2cell(str, delim) +if ~exist('delim') + delim = '; '; +end + +[out{1},b] = strtok(str, delim); +ii = 2; +while ~isempty(b) + [out{ii},b] = strtok(b, delim); + ii = ii+1; +end + +for ii=1:length(out) + out2{ii} = str2num(out{ii}); + if isempty(out2{ii}) + return; + end +end + +for ii=1:length(out) + out{ii} = str2num(out{ii}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cell2str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function str = cell2str(acell, delim) +if ~exist('delim') + delim = ';'; +end + +str = []; + +if length(acell)==1 + if isstr(acell{1}) + str = acell{1}; + else + str = num2str(acell{1}); + end +else + for ii=1:length(acell) + if isstr(acell{ii}) + str = [str acell{ii}, delim ' ']; + else + str = [str num2str(acell{ii}), delim ' ']; + end + end + str(end-1:end)=[]; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cellmax, find max in each element, return a cell +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = cellmax(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end + +MAXX = []; +for ii=1:length(acell) + if strfind('abs',absolute) + MAXX = [MAXX max(abs(acell{ii}))]; + else + MAXX = [MAXX max(acell{ii})]; + end +end +MAXX = num2cell(MAXX); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% maxcell +%%% find max of all numbers in the whole cell, return a single value +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = maxcell(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end +MAXX = cellmax(acell, absolute); +MAXX = max(cell2mat(MAXX)); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% p2t +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = p2t(p, df, TF) +if ~iscell(p) + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = p2t(p{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% s2t, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = s2t(s, df, TF) + +if ~iscell(s) + p = 10^(-s); + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = s2t(s{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2p +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function p = t2p(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + end +else + for ii=1:length(t) + p{ii} = t2p(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2s, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = t2s(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + else + p = 0.1; + end + s = -log10(p); +else + for ii=1:length(t) + s{ii} = t2s(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2mask +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mask = mni2mask(coords, targetfilename, intensity, M, DIM, templateFile, isMask) +% function mask = mni2mask(coords, targetfilename, intensity, templateFile) +% make mask from coordinates +% +% coords: a Nx3 column of 3-d coordinates in MNI +% space +% targetfilename: (optional) the image files to be written +% intensity: (optional) Nx1, the values of each coordinate. +% M: rotation matrix +% DIM: dimension +% templateFile: (optional) the templateFile from which we can get the right +% dimensions. +% isMask: if this variable exist and equal to 1, then all non-zero +% intensities will be set to 1 +% +% Xu Cui +% 2004/11/18 + +if ~exist('intensity') + intensity = ones(size(coords,1),1); +end +thistemplateFile = ''; +if exist('templateFile') + if ~isempty(templateFile) + thistemplateFile = templateFile; + end +end + +if isempty(thistemplateFile) + V.mat = [... + -4 0 0 84; ... + 0 4 0 -116; ... + 0 0 4 -56; ... + 0 0 0 1]; + V.dim = [41 48 35 16]; + if exist('M') + V.mat = M; + end + if exist('DIM') + V.dim = DIM; + V.dim(4) = 16; + end + V.fname = targetfilename; + V.descrip = 'our own image'; +else + V = spm_vol(templateFile); + V.fname = targetfilename; + if isfield(V, 'descrip') + V.descrip = ['my image from ' V.descrip]; + else + V.descrip = 'my own image'; + end +end + +thisismask = 0; +if exist('isMask') + if isMask == 1 + thisismask = 1; + end +end +if thisismask + V.descrip = 'my mask'; + intensity = ones(size(intensity)); +end + +O = zeros(V.dim(1),V.dim(2),V.dim(3)); + +coords = mni2cor(coords,V.mat); + + +for ii=1:size(coords,1) + O(coords(ii,1),coords(ii,2),coords(ii,3)) = intensity(ii); +end + +if exist('targetfilename') + V = spm_write_vol(V,O); +end + +mask = O; + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get image file information +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [imageFile,M,DIM,TF,df,mni,intensity] = getImageFile(thisfilename) +% function imageFile = getImageFile(filename) +% get the information of this/these image file(s) +% +% thisfilename: (optional) if doesn't give file name, then show a open file +% dialog +% imageFile: the full name of the selected file (if user pressed cancel, +% imageFile == 0 +% M: M matrix (rotation matrix) +% DIM: dimension +% TF: t test or f test? 'T' or 'F' +% df: degree of freedome +% mni: mni coord +% intensity: intensity of each mni coord +% +% Note: The returned variables are cellarrays. +% +% Xu Cui +% last revised: 2005-05-03 + +if nargin < 1 | isempty(thisfilename) + if findstr('SPM2',spm('ver')) + P0 = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P0 = spm_select(Inf,'image','Select image files'); + end + + % try + % P0 = spm_get([0:100],'*IMAGE','Select image files'); + % catch + % P0 = []; + % [FileName,PathName] = uigetfile({'*.img';'*.IMG';'*.*'},'Select image files','MultiSelect','on'); + % if isstr(FileName) + % P0 = {fullfile(PathName, FileName)}; + % elseif iscellstr(FileName) + % for ii=1:length(FileName) + % P0{ii} = fullfile(PathName, FileName{ii}); + % end + % else + % P0 = []; + % end + % end + try + if isempty(P0) + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end + end + for ii=1:size(P0,1) + P{ii} = deblank(P0(ii,:)); + end +else + if isstr(thisfilename) + P = {thisfilename}; + elseif iscellstr(thisfilename) + P = thisfilename; + else + disp('Error: In getImageFile: I don''t understand the input.'); + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end +end + +global LEFTRIGHTFLIP_; + +for ii=1:length(P) + imageFile{ii} = P{ii}; + [cor{ii}, intensity{ii}, tmp{ii}, M{ii}, DIM{ii}, TF{ii}, df{ii}] = mask2coord(imageFile{ii}, 0); + if LEFTRIGHTFLIP_ == 1 + M{ii}(1,:) = -M{ii}(1,:); + end + mni{ii} = cor2mni(cor{ii}, M{ii}); +end + + + + + + + + + + + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuFindTDstructure +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% +% this function converts Talairach Daemon coordinate or MNI coordinate to a description of +% brain structure. +% +% pos: the coordinate (MNI or Talairach coordinate, defined by TALMNI) of the position in the brain, in mm +% DB: the database structure (see below for detailed explanation). If you don't input this argument, there +% should be a file called 'TDdatabase.mat' in the current directory +% TALMNI: 1 if pos is talairach coordinate, 0 if pos is MNI coordinate. 1 +% by default. +% +% onelinestructure: a one-line description of the returned brain +% structure +% cellarraystructure: a cell array of size 5, each cell contains a string +% describing the structure of the brain in a certain level. +% +% Example: +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48], DB, 1) +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48]) +% then +% onelinestructure = // Left Cerebrum // Frontal Lobe (L) // Middle Frontal Gyrus (L) // Gray Matter (L) // Brodmann area 8 (L) +% cellarraystructure = 'Left Cerebrum' 'Frontal Lobe (L)' [1x24 char] 'Gray Matter (L)' 'Brodmann area 8 (L)' +% +% Xu Cui +% 2004-6-28 +% + +%---------------------------------------------------------------------------------- +% DB strcture +%---------------------------------------------------------------------------------- +%------------------------------- +% Grid specification parameters: +%------------------------------- +% minX - min X (mm) +% maxX - max X (mm) +% voxX - voxel size (mm) in X direction +% minY - min Y (mm) +% maxY - max Y (mm) +% voxY - voxel size (mm) in Y direction +% minZ - min Z (mm) +% maxZ - max Z (mm) +% voxZ - voxel size (mm) in Z direction +% nVoxX - number of voxels in X direction +% nVoxY - number of voxels in Y direction +% nVoxZ - number of voxels in Z direction +%------------------------------- +% Classification parameters: +%------------------------------- +% numClass - number of classification types +% cNames - cNames{i} - cell array of class names for i-th CT +% numClassSize - numClassSize(i) - number of classes for i-th CT +% indUnidentified - indUnidentified(i) - index of "indUnidentified" class for i-th CT +% volClass - volClass{i}(j) - number of voxels in class j for i-th CT +% +% data - N x numClass matrix of referencies; let +% x y z coordinates in mm (on the grid) and +% nx = (x-minX)/voxX +% ny = (y-minY)/voxY +% nz = (z-minZ)/voxZ +% ind = nz*nVoxX*nVoxY + ny*nVoxX + nx + 1 +% data(ind, i) - index of the class for i-th CT in cNames{i} to +% which (x y z) belongs, i.e. +% cNames{i}{data(ind, i)} name of class for i-th CT +%---------------------------------------------------------------------------------- + +if nargin==1 + load('TDdatabase.mat'); + TALMNI = 1; +elseif nargin == 2 + TALMNI = 1; +end + +if(TALMNI == 1) + pos = tal2mni(pos); +elseif(TALMNI == 0) + []; +else + disp('TALMNI should be 1 or 0.'); +end + +pos(:,1) = DB.voxX*round(pos(:,1)/DB.voxX); +pos(:,2) = DB.voxY*round(pos(:,2)/DB.voxY); +pos(:,3) = DB.voxZ*round(pos(:,3)/DB.voxZ); + +min = []; +vox = []; +for(i=1:size(pos,1)) + min = [min; DB.minX DB.minY DB.minZ]; + vox = [vox; DB.voxX DB.voxY DB.voxZ]; +end +n_pos = (pos - min)./vox; + +nx = n_pos(:,1); +ny = n_pos(:,2); +nz = n_pos(:,3); +index = nz*DB.nVoxX*DB.nVoxY + ny*DB.nVoxX + nx + 1; +indMax = size(DB.data, 1); + +onelinestructuretmp = []; +onelinestructure = []; +for(j=1:size(pos,1)) + onelinestructuretmp = []; + for(i=1:DB.numClass) + + if (index(j) <= 0 | index(j) > indMax) + ind(j) = DB.indUnidentified(i); + else + ind(j) = DB.data(index(j), i); + end + + cellarraystructure{j,i} = DB.cNames{i}{ind(j)}; + onelinestructuretmp = [onelinestructuretmp ' // ' cellarraystructure{j,i}]; + end + onelinestructure{j} = onelinestructuretmp; +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mask2coord +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [cor, intensity, cor_singlecolumn,M,DIM,TF,df] = mask2coord(mask, checkdimension) +% [cor, intensity, cor_singlecolumn] = mask2coord(mask, checkdimension) +% +% This is to retrieve the coordinate of a mask file, or a matrix of 3-D +% +% mask: an image file or a matrix (3-D), with some of the elements are +% non-zeros +% checkdimension: check if the dimension is checkdimension, if not, return empty +% matrix +% cor: a N*3 matrix, which each row a coordinate in matrix +% intensity: a N*1 matrix, which encodes the intensity of each voxel. +% cor_singlecolumn: a N*1 matrix, each row is the index in the matrix +% M: rotation matrix +% DIM: dimension +% TF: t test or f test? 'T','F' or [] +% df: degree of freedome for T/F test +% +% Example: +% mask = zeros(4,3,2); +% mask(1,2,1) = 1; +% mask(3,2,2) = 1; +% mask2coord(mask) +% +% mask2coord('spmT_0002.img') +% mask2coord('spmT_0002.img',[41 48 35]) +% +% Xu Cui +% 2004-9-20 +% last revised: 2005-04-30 + +if nargin < 2 + checkdimension = 0; +end + +if ischar(mask) + V = spm_vol(mask); + mask = spm_read_vols(V); + M = V.mat; + DIM = V.dim; + TF = 'T'; + T_start = strfind(V.descrip,'SPM{T_[')+length('SPM{T_['); + if isempty(T_start); T_start = strfind(V.descrip,'SPM{F_[')+length('SPM{F_['); TF='F'; end + if isempty(T_start) + TF=[]; df=[]; + else + T_end = strfind(V.descrip,']}')-1; + df = str2num(V.descrip(T_start:T_end)); + end +else + M = []; + TF = []; + df = []; +end + +dim = size(mask); +if length(checkdimension)==3 + if dim(1)~= checkdimension(1) | dim(2)~= checkdimension(2) | dim(3)~= checkdimension(3) + y = []; + disp('dimension doesn''t match') + return + end +end + +pos = find(mask~=0); +intensity = mask(pos); + +y = zeros(length(pos),3); + +y(:,3) = ceil(pos/(dim(1)*dim(2))); +pos = pos - (y(:,3)-1)*(dim(1)*dim(2)); +y(:,2) = ceil(pos/dim(1)); +pos = pos - (y(:,2)-1)*(dim(1)); +y(:,1) = pos; + +cor = y; +cor_singlecolumn = pos; +DIM = dim; +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2cor +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function coordinate = mni2cor(mni, T) +% function coordinate = mni2cor(mni, T) +% convert mni coordinate to matrix coordinate +% +% mni: a Nx3 matrix of mni coordinate +% T: (optional) transform matrix +% coordinate is the returned coordinate in matrix +% +% caution: if T is not specified, we use: +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% + +if isempty(mni) + coordinate = []; + return; +end + +if ~exist('T') + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +coordinate = [mni(:,1) mni(:,2) mni(:,3) ones(size(mni,1),1)]*(inv(T))'; +coordinate(:,4) = []; +coordinate = round(coordinate); +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cor2mni +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mni = cor2mni(cor, T) +% function mni = cor2mni(cor, T) +% convert matrix coordinate to mni coordinate +% +% cor: an Nx3 matrix +% T: (optional) rotation matrix +% mni is the returned coordinate in mni space +% +% caution: if T is not given, the default T is +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% last revised: 2005-04-30 + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +cor = round(cor); +mni = T*[cor(:,1) cor(:,2) cor(:,3) ones(size(cor,1),1)]'; +mni = mni'; +mni(:,4) = []; +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% draw +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = Draw(mniCoord, intensity, hObject, handles) + +try + delete(handles.hcolorbar); +end +try + delete(handles.hReg); +end +try + delete(handles.hSection); +end +try + cla(handles.glassViewAxes); +end + +try + H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); + un = cellstr(get(H,'Units')); + pos = get(H,'position'); + + for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 + delete(H(ii)); + end + end +end + +sectionViewTargetFile = handles.sectionViewTargetFile; + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end + if max(intensity)*min(intensity) < 0 + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + else + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,abs(intensity),sectionViewTargetFile,hObject,handles); + end + + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end +else % multiple input? yes + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + + mniCoordtmp=[]; + intensitytmp=[]; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end + +end + +try + spm_XYZreg('SetCoords',handles.currentxyz',hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuSectionView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord, intensity, targetFile, hObject,handles) +% function h = cuixuSectionView(mniCoord, intensity) +% This is to project your coordinate to section view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% a special feature of this function is: it automatically seperate the +% negative and positive intensity and use hot and cold color to represent +% them. +% +% h: the returned handle for the axes +% +% SEE ALSO: cuixuView cuixuGlassView cuixuRenderView +% +% Xu Cui +% 2004/11/11 + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + multiple = 0; + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end +else + multiple = 1; + mniCoordtmp = []; + intensitytmp = []; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + % for multiple input + cSPM{ii}.XYZ = mni2cor(mniCoord{ii}, handles.M{ii}); + cSPM{ii}.XYZ = cSPM{ii}.XYZ'; + cSPM{ii}.Z = abs(intensity{ii}); + cSPM{ii}.M = handles.M{ii}; + cSPM{ii}.DIM = handles.DIM{ii}'; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; +end + +SPM.XYZ = mni2cor(mniCoord, handles.M); +SPM.XYZ = SPM.XYZ'; +SPM.Z = intensity; +SPM.M = handles.M; +SPM.DIM = handles.DIM'; + +%%%%%%%%%%%%%%% Reg %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +handles.colormap = colormap; + +coor = mniCoord; +xSPM = SPM; +xSPM.XYZmm = mniCoord'; +axes(handles.glassViewAxes) +WS = spm('WinScale'); +FS = spm('FontSizes'); + +Finter = gcf; +hReg = uicontrol(Finter,'Style','Frame','Position',[60 100 300 300].*WS,... + 'Visible','off'); +[hReg,xyz] = spm_XYZreg('InitReg',hReg,xSPM.M,xSPM.DIM,[0;0;0]); + +hFxyz = spm_results_ui('DrawXYZgui',xSPM.M,xSPM.DIM,xSPM,xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +hMIPax =gca ; +setcolormap('gray'); + +hMIPax = spm_mip_ui(xSPM.Z,coor',xSPM.M,xSPM.DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); + +colormap(handles.colormap); +setcolormap('gray-hot'); + +if isempty(handles.M) + spm_XYZreg('SetReg',handles.structureEdit,hReg); +else + set(handles.structureEdit, 'UserData', struct('hReg',hReg,'M',handles.M,'D', handles.DIM,'xyx',[0 0 0])); +end + +spm_XYZreg('Add2Reg',hReg,handles.structureEdit,@CallBack_structureEdit); + +%%%%%%%%%%%%%%% Reg end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if multiple == 0 + [hgraph, hSection, hcolorbar] = spm_sections(SPM,hReg,targetFile,handles.sectionViewPosition); +else + [hgraph, hSection, hcolorbar] = spm_sections(cSPM,hReg,targetFile,handles.sectionViewPosition); +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_sections +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [Fgraph, hMe, hcolorbar] = spm_sections(SPM,hReg,targetFile,sectionViewPosition) +% rendering of regional effects [SPM{Z}] on orthogonal sections +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = gcf; + +spms = fullfile(spm('dir'),'canonical', 'single_subj_T1.mnc'); +if exist('targetFile') + spms = targetFile; +end + +spm_orthviews('Reset'); +global st +st.fig = Fgraph; +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; + +spm_orthviews('Image',spms,sectionViewPosition); % position +spm_orthviews('MaxBB'); +spm_orthviews('register',hReg); +if ~iscell(SPM) + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +elseif length(SPM) == 1 + SPM = SPM{1}; + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +else + colors = mycolourset; + for ii=1:length(SPM) + spm_orthviews('addcolouredblobs',1,SPM{ii}.XYZ, SPM{ii}.Z, SPM{ii}.M, colors(ii,:)); + end +end +spm_orthviews('Redraw'); + +hMe = st.registry.hMe; +try + hcolorbar = st.vols{1}.blobs{1}.cbar; +catch + hcolorbar = 0; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuRenderView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function h = cuixuRenderView(mniCoord, intensity, varargin) +% function h = cuixuRenderView(mniCoord1, intensity1, mniCoord2, intensity2, mniCoord3, intensity3) +% This is to project your coordinate to render view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% You can input 1, 2, or 3 pairs of coordinates and intensity. +% +% h: the returned handle for the figure +% +% Xu Cui +% 2004/11/11 + +global M_; +global DIM_; + +if nargin < 3 + dat.XYZ = mni2cor(mniCoord, M_); + dat.XYZ = dat.XYZ'; + if nargin < 2 + dat.t = ones(size(mniCoord,1),1); + else + dat.t = intensity; + end + dat.mat = M_; + dat.dim = DIM_; +else + if mod(nargin,2) ~=0 + disp('You should put even number of parameters.') + return; + end + for ii=1:(2+length(varargin))/2 + if ii==1 + dat(ii).XYZ = mni2cor(mniCoord, M_); + dat(ii).t = intensity; + else + dat(ii).XYZ = mni2cor(varargin{2*(ii-1)-1}, M_); + dat(ii).t = varargin{2*(ii-1)}; + end + dat(ii).XYZ = dat(ii).XYZ'; + dat(ii).mat = M_; + dat(ii).dim = DIM_; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_render +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +h = spm_render(dat,1,fullfile(spm('dir'), 'rend', 'render_single_subj.mat')); +return + +function Fgraph = spm_render(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +% get surface +%----------------------------------------------------------------------- +if nargin < 3, + rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); +end; + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + + + +% Perform the rendering +%======================================================================= +spm('Pointer','Watch') + +load(rendfile); + +if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; +end; + +if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; +for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; +end; +if showbar, spm_progress_bar('Clear'); end; + +if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + +mx = zeros(length(rend),1)+eps; +mn = zeros(length(rend),1); + +for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; +end; + +mxmx = max(mx); +mnmn = min(mn); + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = gcf;%spm_figure('GetWin','Graphics'); +%spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +hght = 0.25; +width = 0.25; +x0 = 0.5; +y0 = 0.01; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 0.5, hght],'Visible','off'); +%ax=axes; +%image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow, width, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + X = cell(3,1); + for j=1:length(rend{i}.data), + X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + end + for j=(length(rend{i}.data)+1):3 + X{j}=zeros(size(X{1})); + end + + rgb = zeros([size(ren) 3]); + tmp = ren.*max(1-X{1}-X{2}-X{3},0); + rgb(:,:,1) = tmp + X{1}; + rgb(:,:,2) = tmp + X{2}; + rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + end; +end; + +spm('Pointer') +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_list +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function varargout = spm_list(varargin) +% Display and analysis of SPM{.} +% FORMAT TabDat = spm_list('List',SPM,hReg,[Num,Dis,Str]) +% Summary list of local maxima for entire volume of interest +% FORMAT TabDat = spm_list('ListCluster',SPM,hReg,[Num,Dis,Str]) +% List of local maxima for a single suprathreshold cluster +% +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x11 cell array) +% .fmt - fprintf format strings for table data (1x11 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (4x2 cell array) +% .dat - table data (Nx11 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%_______________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The currected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% +% Voxel-level - T/F = Statistic upon which the SPM is based +% - Ze = The eqivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qu = Expd(Prop of false positives among voxels >= Ze) +% - Pu = prob(Ze or higher at that voxel) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%_______________________________________________________________________ +% @(#)spm_list.m 2.43 Karl Friston, Andrew Holmes 02/10/31 + + +% satellite figure global variable +%----------------------------------------------------------------------- +global SatWindow + +%======================================================================= +switch lower(varargin{1}), case 'list' %-List + %======================================================================= + % FORMAT TabDat = spm_list('list',SPM,hReg) + + %-Tolerance for p-value underflow, when computing equivalent Z's + %----------------------------------------------------------------------- + tol = eps*10; + + %-Parse arguments and set maxima number and separation + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + + + %-Get current location (to highlight selected voxel in table) + %----------------------------------------------------------------------- + %xyzmm = spm_results_ui('GetCoords'); + xyzmm = [0 0 0]'; + + %-Extract data from xSPM + %----------------------------------------------------------------------- + S = varargin{2}.S; + R = varargin{2}.R; + FWHM = varargin{2}.FWHM; + VOX = varargin{2}.VOX; + n = varargin{2}.n; + STAT = varargin{2}.STAT; + df = varargin{2}.df; + u = varargin{2}.u; + M = varargin{2}.M; + v2r = 1/prod(FWHM(~isinf(FWHM))); %-voxels to resels + k = varargin{2}.k*v2r; + QPs = varargin{2}.Ps; % Needed for FDR + QPs = sort(QPs(:)); + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 3; + Dis = 8; + end + if length(varargin) > 5 + + Title = varargin{6}; + else + Title = 'p-values adjusted for search volume'; + end + + + %-Setup graphics panel + %----------------------------------------------------------------------- + spm('Pointer','Watch') + if SatWindow + Fgraph = SatWindow; + figure(Fgraph); + else + Fgraph = figure('unit','normalized','position',[0.5,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','off','MenuBar','none'); + Fgraph = gcf; + end + %spm_results_ui('Clear',Fgraph) + FS = spm('FontSizes'); %-Scaled font sizes + PF = spm_platform('fonts'); %-Font names (for this platform) + + + %-Table header & footer + %======================================================================= + + %-Table axes & Title + %---------------------------------------------------------------------- + if SatWindow, ht = 0.85; bot = .14; else, ht = 0.8; bot = 0.15; end; + + if STAT == 'P' + Title = 'Posterior Probabilities'; + end + + hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + + AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) + dy = FS(9); + y = floor(AxPos(4)) - dy; + + text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; + line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + + %-Construct table header + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + + Hc = []; + Hp = []; + h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; + h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; + h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; + h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; + text(0.22,y, 'cluster-level','FontSize',FS(9)); + line([0.15,0.41],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.16,y-9*dy/8, '\itp \rm_{corrected}'); Hp = [Hp,h]; + h = text(0.33,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.26,y-9*dy/8, '\itk \rm_E'); + + text(0.60,y, 'voxel-level','FontSize',FS(9)); + line([0.46,0.86],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.46,y-9*dy/8, '\itp \rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.55,y-9*dy/8, '\itp \rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.79,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.64,y-9*dy/8, sprintf('\\it%c',STAT)); + h = text(0.72,y-9*dy/8, '(\itZ\rm_\equiv)'); + + text(0.93,y - dy/2,['x,y,z \fontsize{',num2str(FS(8)),'}\{mm\}']); + + + %-Headers for text table... + %----------------------------------------------------------------------- + TabDat.tit = Title; + TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'voxel', 'p(FWE-cor)';... + 'voxel', 'p(FDR-cor)';... + 'voxel', STAT;... + 'voxel', 'equivZ';... + 'voxel', 'p(unc)';... + '', 'x,y,z {mm}'}';... + + TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Voxel + '%3.0f %3.0f %3.0f'}; %-XYZ + + %-Column Locations + %----------------------------------------------------------------------- + tCol = [ 0.00 0.07 ... %-Set + 0.16 0.26 0.34 ... %-Cluster + 0.46 0.55 0.62 0.71 0.80 ...%-Voxel + 0.92]; %-XYZ + + % move to next vertial postion marker + %----------------------------------------------------------------------- + y = y - 7*dy/4; + line([0 1],[y y],'LineWidth',1,'Color','r') + y = y - 5*dy/4; + y0 = y; + + + %-Table filtering note + %----------------------------------------------------------------------- + if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); + else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); + end + text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + + %-Volume, resels and smoothness (if classical inference) + %----------------------------------------------------------------------- + line([0 1],[0 0],'LineWidth',1,'Color','r') + if STAT ~= 'P' + %----------------------------------------------------------------------- + FWHMmm = FWHM.*VOX; % FWHM {mm} + Pz = spm_P(1,0,u,df,STAT,1,n,S); + Pu = spm_P(1,0,u,df,STAT,R,n,S); + Qu = spm_P_FDR(u,df,STAT,n,QPs); + [P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + + %-Footnote with SPM parameters + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) + TabDat.ftr = cell(5,2); + TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); + TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); + TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); + TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); + TabDat.ftr{5} = ... + sprintf('Expected false discovery rate, <= %0.2f',Qu); + TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); + TabDat.ftr{7} = ... + sprintf(['Smoothness FWHM = %0.1f %0.1f %0.1f {mm} ',... + ' = %0.1f %0.1f %0.1f {voxels}'],FWHMmm,FWHM); + TabDat.ftr{8} = ... + sprintf('Search vol: %0.0f cmm; %0.0f voxels; %0.1f resels',S*prod(VOX),S,R(end)); + TabDat.ftr{9} = ... + sprintf(['Voxel size: [%0.1f, %0.1f, %0.1f] mm ',... + ' (1 resel = %0.2f voxels)'],VOX,prod(FWHM)); + + text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu,Qu],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWHMmm,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + + end % Classical + + + %-Characterize excursion set in terms of maxima + % (sorted on Z values and grouped by regions) + %======================================================================= + if ~length(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,11); + varargout = {TabDat}; + spm('Pointer','Arrow') + return + end + + % Includes Darren Gitelman's code for working around + % spm_max for conjunctions with negative thresholds + %----------------------------------------------------------------------- + minz = abs(min(min(varargin{2}.Z))); + zscores = 1 + minz + varargin{2}.Z; + [N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); + Z = Z - minz - 1; + + %-Convert cluster sizes from voxels to resels + %----------------------------------------------------------------------- + if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); + else + V2R = v2r; + end + N = N.*V2R; + + %-Convert maxima locations from voxels to mm + %----------------------------------------------------------------------- + XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + + %-Table proper (& note all data in cell array) + %======================================================================= + + %-Pagination variables + %----------------------------------------------------------------------- + hPage = []; + set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + + %-Set-level p values {c} - do not display if reporting a single cluster + %----------------------------------------------------------------------- + c = max(A); %-Number of clusters + if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value + else + Pc = []; + set(Hp,'Visible','off') + end + + if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + else + set(Hc,'Visible','off') + end + + TabDat.dat = {Pc,c}; %-Table data + TabLin = 1; %-Table data line + + + %-Local maxima p-values & statistics + %----------------------------------------------------------------------- + HlistXYZ = []; + while prod(size(find(finite(Z)))) + + % Paginate if necessary + %--------------------------------------------------------------- + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %--------------------------------------------------------------- + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and voxel-level {u} p values for this cluster + %--------------------------------------------------------------- + Nv = N(i)/v2r; % extent {voxels} + + + if STAT ~= 'P' + Pz = spm_P(1,0, U,df,STAT,1,n,S);% uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S);% FWE-corrected {based on Z) + Qu = spm_P_FDR( U,df,STAT,n,QPs);% FDR-corrected {based on Z) + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S);% [un]corrected {based on k) + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum voxel-level p values {Z} + %--------------------------------------------------------------- + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %--------------------------------------------------------------------- + h = text(tCol(11),y,sprintf(TabDat.fmt{11},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %--------------------------------------------------------------- + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %----------------------------------------------- + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %----------------------------------------------- + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + if Pz < tol + Ze = Inf; + else, Ze = spm_invNcdf(1 - Pz); end + else + Pz = []; + Pu = []; + Qu = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %----------------------------------------------- + h = text(tCol(11),y,... + sprintf(TabDat.fmt{11},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) + end + + %-End: Store TabDat in UserData of axes & reset pointer + %======================================================================= + h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); + set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') + uimenu(h,'Label','Table') + uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + + %-Setup registry + %----------------------------------------------------------------------- + set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) + spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + + %-Return TabDat structure & reset pointer + %----------------------------------------------------------------------- + varargout = {TabDat}; + spm('Pointer','Arrow') + + + + + + %======================================================================= + case 'listcluster' %-List for current cluster only + %======================================================================= + % FORMAT TabDat = spm_list('listcluster',SPM,hReg) + + spm('Pointer','Watch') + + %-Parse arguments + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + SPM = varargin{2}; + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 32; + Dis = 4; + end + + + %-if there are suprathreshold voxels, filter out all but current cluster + %----------------------------------------------------------------------- + if length(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end + end + + %-Call 'list' functionality to produce table + %----------------------------------------------------------------------- + varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + + + + %======================================================================= + case 'txtlist' %-Print ASCII text table + %======================================================================= + % FORMAT spm_list('TxtList',TabDat,c) + + if nargin<2, error('Insufficient arguments'), end + if nargin<3, c=1; else, c=varargin{3}; end + TabDat = varargin{2}; + + %-Table Title + %----------------------------------------------------------------------- + fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) + fprintf('%c','='*ones(1,80)), fprintf('\n') + + %-Table header + %----------------------------------------------------------------------- + fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) + fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table data + %----------------------------------------------------------------------- + for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') + end + for i=1:max(1,11-size(TabDat.dat,1)), fprintf('\n'), end + fprintf('%s\n',TabDat.str) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table footer + %----------------------------------------------------------------------- + fprintf('%s\n',TabDat.ftr{:}) + fprintf('%c','='*ones(1,80)), fprintf('\n\n') + + + + %======================================================================= + case 'setcoords' %-Co-ordinate change + %======================================================================= + % FORMAT spm_list('SetCoords',xyz,hAx,hReg) + if nargin<3, error('Insufficient arguments'), end + hAx = varargin{3}; + xyz = varargin{2}; + UD = get(hAx,'UserData'); + HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + + %-Set all co-ord strings to black + %----------------------------------------------------------------------- + set(HlistXYZ,'Color','k') + + %-If co-ord matches a string, highlight it in red + %----------------------------------------------------------------------- + XYZ = get(HlistXYZ,'UserData'); + if iscell(XYZ), XYZ = cat(2,XYZ{:}); end + [null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); + if d=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + cm_pos; + end; + varargout{1} = H; + st.centre = mean(maxbb); + redraw_all + + case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + + case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + + case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3 + h = valid_handles(st.snap); + if ~isempty(h) + tmp=st.vols{h(1)}.mat*... + round(inv(st.vols{h(1)}.mat)*[tmp; ... + 1]); + end; + st.centre = tmp(1:3); + end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + cm_pos; + + case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + cm_pos; + + case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + bbox; + redraw_all; + else, + space(varargin{1}); + bbox; + redraw_all; + end; + + case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + + case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + + case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + + case 'delete', + my_delete(varargin{1}); + + case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + + case 'reset', + my_reset; + + case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + + case 'interp', + st.hld = varargin{1}; + redraw_all; + + case 'xhairs', + xhairs(varargin{1}); + + case 'register', + register(varargin{1}); + + case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + + case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + + case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + + case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + + case 'addtruecolourimage', + % spm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_select(1, 'image', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + + case 'addcolourbar', + addcolourbar(varargin{1}, varargin{2}); + + case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + + case 'addcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + addcontexts(handles); + + case 'rmcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + rmcontexts(handles); + + case 'context_menu', + c_menu(varargin{:}); + + case 'valid_handles', + if nargin == 1 + handles = 1:24; + else, + handles = varargin{1}; + end; + varargout{1} = valid_handles(handles); + + otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +global TMAX_ +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + mx = max([eps max(t)]); + mn = min([0 min(t)]); + if ~strcmp(TMAX_, 'auto') + mx = str2num(TMAX_); + end + %KND: + if numel(mx)==2 + mn=mx(1); + mx=mx(2); + end + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx, 'min',mn); + addcolourbar(handle,1); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx,'min',mn); + addcolourbar(handle,1); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx, ... + 'min',mn,'colour',c); + addcolourbar(handle,bset); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolourbar(vh,bh) +global st +if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); +else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); +end; +st.vols{vh}.blobs{bh}.cbar = axes('Parent',st.fig,... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on', 'YDir','normal', 'XTickLabel',[], 'XTick',[]); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'spm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['spm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''Reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +V.mapping = 'linear'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +spm_orthviews('reposition',spm_orthviews('pos')); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['spm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(finite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(finite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(finite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(finite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + imgc = max(imgc,mn); imgc = min(imgc,mx); + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(finite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgc), + tmp = imgc(finite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgs), + tmp = imgs(finite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(finite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(finite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(finite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpc(tmpc(:)>mx) = mx; + tmps(tmps(:)>mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpc = (tmpc-mn)/(mx-mn); + tmps = (tmps-mn)/(mx-mn); + tmpt(~finite(tmpt)) = 0; + tmpc(~finite(tmpc)) = 0; + tmps(~finite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_colourbar(vh,bh,interval,cdata) +global st +if isfield(st.vols{vh}.blobs{bh},'cbar') + if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); + end; + % only scale cdata if we have out-of-range truecolour values + if ndims(cdata)==3 && max(cdata(:))>1 + cdata=cdata./max(cdata(:)); + end; + image([0 1],interval,cdata,'Parent',st.vols{vh}.blobs{bh}.cbar); + set(st.vols{vh}.blobs{bh}.cbar, ... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1)... + (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'YDir','normal','XTickLabel',[],'XTick',[]); +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = []; %[ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[],'snap',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'spm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('spm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e v] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~finite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item00 = uimenu(item_parent, 'Label','unknown image', 'Separator','on'); +spm_orthviews('context_menu','image_info',item00,volhandle); +item0a = uimenu(item_parent, 'UserData','pos_mm', 'Callback','spm_orthviews(''context_menu'',''repos_mm'');','Separator','on'); +item0b = uimenu(item_parent, 'UserData','pos_vx', 'Callback','spm_orthviews(''context_menu'',''repos_vx'');'); +item0c = uimenu(item_parent, 'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','spm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +checked={'off','off'}; +checked{st.xhairs+1} = 'on'; +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''on'');','Checked',checked{2}); +item2_2 = uimenu(item2, 'Label','off', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''off'');','Checked',checked{1}); + +%contextsubmenu 3 +if st.Space == eye(4) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','spm_orthviews(''context_menu'',''orientation'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Voxel space (1st image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Voxel space (this image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',1);','Checked','off'); + +%contextsubmenu 3 +if isempty(st.snap) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Snap to Grid'); +item3_1 = uimenu(item3, 'Label','Don''t snap', 'Callback','spm_orthviews(''context_menu'',''snap'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Snap to 1st image', 'Callback','spm_orthviews(''context_menu'',''snap'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Snap to this image', 'Callback','spm_orthviews(''context_menu'',''snap'',1);','Checked','off'); + +%contextsubmenu 4 +if st.hld == 0, + checked = {'off', 'off', 'on'}; +elseif st.hld > 0, + checked = {'off', 'on', 'off'}; +else, + checked = {'on', 'off', 'off'}; +end; +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','spm_orthviews(''context_menu'',''interpolation'',3);', 'Checked',checked{3}); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','spm_orthviews(''context_menu'',''interpolation'',2);','Checked',checked{2}); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','spm_orthviews(''context_menu'',''interpolation'',1);','Checked',checked{1}); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','spm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window_gl'',1);'); +if license('test','image_toolbox') == 1 + offon = {'off', 'on'}; + checked = offon(strcmp(st.vols{volhandle}.mapping, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'})+1); + item6_2 = uimenu(item6, 'Label','Intensity mapping'); + item6_2_1 = uimenu(item6_2, 'Label','local'); + item6_2_1_1 = uimenu(item6_2_1, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''linear'');'); + item6_2_1_2 = uimenu(item6_2_1, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''histeq'');'); + item6_2_1_3 = uimenu(item6_2_1, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''loghisteq'');'); + item6_2_1_4 = uimenu(item6_2_1, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''quadhisteq'');'); + item6_2_2 = uimenu(item6_2, 'Label','global'); + item6_2_2_1 = uimenu(item6_2_2, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''linear'');'); + item6_2_2_2 = uimenu(item6_2_2, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''histeq'');'); + item6_2_2_3 = uimenu(item6_2_2, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''loghisteq'');'); + item6_2_2_4 = uimenu(item6_2_2, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''quadhisteq'');'); +end; +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add image'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_image'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_image'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored blobs','Separator','on'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_4 = uimenu(item7, 'Label','Add colored image'); +item7_4_1 = uimenu(item7_4, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_4_2 = uimenu(item7_4, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_5 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_6 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_6_1 = uimenu(item7_6, 'Label','local', 'Visible','on'); +item7_6_2 = uimenu(item7_6, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), + case 'image_info', + if nargin <3, + current_handle = get_current_handle; + else + current_handle = varargin{3}; + end; + if isfield(st.vols{current_handle},'fname'), + [p,n,e,v] = spm_fileparts(st.vols{current_handle}.fname); + if isfield(st.vols{current_handle},'n') + v = sprintf(',%d',st.vols{current_handle}.n); + end; + set(varargin{2}, 'Label',[n e v]); + end; + delete(get(varargin{2},'children')); + if exist('p','var') + item1 = uimenu(varargin{2}, 'Label', p); + end; + if isfield(st.vols{current_handle},'descrip'), + item2 = uimenu(varargin{2}, 'Label',... + st.vols{current_handle}.descrip); + end; + dt = st.vols{current_handle}.dt(1); + item3 = uimenu(varargin{2}, 'Label', sprintf('Data type: %s', spm_type(dt))); + str = 'Intensity: varied'; + if size(st.vols{current_handle}.pinfo,2) == 1, + if st.vols{current_handle}.pinfo(2), + str = sprintf('Intensity: Y = %g X + %g',... + st.vols{current_handle}.pinfo(1:2)'); + else, + str = sprintf('Intensity: Y = %g X', st.vols{current_handle}.pinfo(1)'); + end; + end; + item4 = uimenu(varargin{2}, 'Label',str); + item5 = uimenu(varargin{2}, 'Label', 'Image dims', 'Separator','on'); + item51 = uimenu(varargin{2}, 'Label',... + sprintf('%dx%dx%d', st.vols{current_handle}.dim(1:3))); + prms = spm_imatrix(st.vols{current_handle}.mat); + item6 = uimenu(varargin{2}, 'Label','Voxel size', 'Separator','on'); + item61 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', prms(7:9))); + item7 = uimenu(varargin{2}, 'Label','Origin', 'Separator','on'); + item71 = uimenu(varargin{2}, 'Label',... + sprintf('%.2f %.2f %.2f', prms(1:3))); + R = spm_matrix([0 0 0 prms(4:6)]); + item8 = uimenu(varargin{2}, 'Label','Rotations', 'Separator','on'); + item81 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(1,1:3))); + item82 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(2,1:3))); + item83 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(3,1:3))); + item9 = uimenu(varargin{2},... + 'Label','Specify other image...',... + 'Callback','spm_orthviews(''context_menu'',''swap_img'');',... + 'Separator','on'); + + case 'repos_mm', + oldpos_mm = spm_orthviews('pos'); + newpos_mm = spm_input('New Position (mm)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_mm),3); + spm_orthviews('reposition',newpos_mm); + + case 'repos_vx' + current_handle = get_current_handle; + oldpos_vx = spm_orthviews('pos', current_handle); + newpos_vx = spm_input('New Position (voxels)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_vx),3); + newpos_mm = st.vols{current_handle}.mat*[newpos_vx;1]; + spm_orthviews('reposition',newpos_mm(1:3)); + + case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + + case 'xhair', + spm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + + case 'orientation', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + spm_orthviews('Space'); + elseif varargin{2} == 2, + spm_orthviews('Space',1); + else, + spm_orthviews('Space',get_current_handle); + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Orientation'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'snap', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + st.snap = []; + elseif varargin{2} == 2, + st.snap = 1; + else, + st.snap = get_current_handle; + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Snap to Grid'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + + case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + spm_orthviews('window',current_handle); + else + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%.2f %.2f', st.vols{current_handle}.window); + else + defstr = ''; + end; + spm_orthviews('window',current_handle,spm_input('Range','+1','e',defstr,2)); + end; + + case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + current_handle = get_current_handle; + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%d %d', st.vols{current_handle}.window); + else + defstr = ''; + end; + data = spm_input('Range','+1','e',defstr,2); + + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + + case 'mapping', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', ... + 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + current_handle = get_current_handle; + cm_handles = get_cm_handles; + st.vols{current_handle}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(current_handle), ... + 'label','Intensity mapping'),'Children'); + for k = 1:numel(z_handle) + c_handle = get(z_handle(k), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + redraw_all; + + case 'mapping_gl', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + cm_handles = get_cm_handles; + for k = valid_handles(1:24), + st.vols{k}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(k), ... + 'label','Intensity mapping'),'Children'); + for l = 1:numel(z_handle) + c_handle = get(z_handle(l), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + end; + redraw_all; + + case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_select(1,'image','select new image')); + fn = fieldnames(new_info); + for k=1:numel(fn) + st.vols{current_handle}.(fn{k}) = new_info.(fn{k}); + end; + spm_orthviews('context_menu','image_info',get(gcbo, 'parent')); + redraw_all; + + case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + + case 'add_image', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + for i = 1:length(cm_handles), + addimage(cm_handles(i),fname); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Green blobs|Yellow blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;0 1 0;1 1 0;0 0 1;0 1 1;1 0 1]; + c_names = {'red';'green';'yellow';'blue';'cyan';'magenta'}; + hlabel = sprintf('%s (%s)',VOL.title,c_names{c}); + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + + case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + if isfield(st.vols{cm_handles(i)}.blobs{j},'cbar') + delete(st.vols{cm_handles(i)}.blobs{j}.cbar); + end + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + + case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',fname,c_names{c}); + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% ROI: TimeSeries +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchContentEdit(hObject, eventdata) +handles = guidata(hObject); +set(handles.searchContentEdit,'UserData', 'manual'); + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load SPM file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadSPMmat(hObject, eventdata, spmfile) +handles = guidata(hObject); +if nargin < 3 | isempty(spmfile) + %if exist(fullfile(pwd,'SPM.mat'), 'file') + if ~isempty(findstr('SPM2',spm('ver'))) & exist('spm_get')==2 + spmfile = spm_get([1],'SPM.mat','Select a SPM file'); + elseif ~isempty(findstr('SPM5',spm('ver'))) & exist('spm_select')==2 + spmfile = spm_select(1,'SPM.mat','Select a SPM file'); + else + if exist('spm')==2 + error('Check for inconsistencies in your SPM install.\nspm(''ver'') = %s\n', spm('ver')) + else + error('No SPM found'); + end + end +end +xSPM=load(spmfile); +if isfield(xSPM.SPM, 'xCon') + + if ~exist(xSPM.SPM.swd, 'dir') + nswd = fileparts(spmfile); + warning('Directory specified in SPM.swd is missing (%s).\nWill use: %s',xSPM.SPM.swd,nswd); + xSPM.SPM.swd=nswd; + end + numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', 2);%length(xSPM.SPM.xCon)); + if ~exist(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)) & ... + exist(subarray(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname),1:2,-2)) + warning('Changing path') + xSPM.SPM.swd=xSPM.SPM.swd(3:end); + end + if ~isempty(numc) + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + end +else + msgbox('No contrast in this file') +end +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_indivResultsListPush(hObject, eventdata) +handles = guidata(hObject); +if ischar(handles.imageFileName) + handles.imageFileName={handles.imageFileName}; +end +[datadir,condir,condext]=fileparts(handles.imageFileName{1}); +if datadir(2)==':' + datadir=datadir(3:end); +end +[datadir,subdir]=fileparts(datadir); +if isempty(findstr('indiv/', datadir)) +elseif isempty(findstr('rfx/', datadir)) + xSPM=load(fullfile(datadir,'SPM.mat')); + indivdir=xSPM.xY.P; +else + return +end +req = get(handles.indivResultsListPush,'String'); +req = req{get(handles.indivResultsListPush, 'value')}; + +if isequal(req,'Group') + datadir=fileparts(datadir); + condir=handles.imageContrastName{1}; + condir=strrep(condir, '>', 'vs'); + condir=strrep(condir, '<', 'vs'); + condir=strrep(condir, '+', '_'); + condir=strrep(condir, ':', ' at'); + condir=deblank(condir); + condir=fullfile(datadir,'rfx',condir); + if ~exist(condir,'dir') + return + end + xSPM=load(fullfile(condir,'SPM.mat')); + numc=2; + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + return +elseif exist('swds','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + swds(get(gcbo, 'value'),:),... + handles.imageContrastName); +else + if exist(fullfile(datadir,req,'SPM.mat')) + xSPM=load(fullfile(datadir,req,'SPM.mat')); + if ~isfield(handles,'imageContrastName') + return + end + % numc=strmatch(handles.imageContrastName{1},{xSPM.SPM.xCon.name},'exact'); + numc=get(handles.contrastListPush, 'Value'); + filename=fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname); + else + % SPM adds a comma for 4D volumes + condext = strtok(condext,','); + filename = fullfile(datadir,req,[condir condext]); + warning('Using same filename in %s: ', req, filename) + end + if filename(2)==':' + filename=filename(3:end); + end + if ~exist(filename,'file') + error('File doesn''t exist: %s',filename) + return + end + set(handles.sectionViewListbox, 'Value', [1]); + % handles.sectionViewTargetFile = + % fullfile('\ndiayek\data\gazemo\rawdata\',req,'anat','wf_0001.img'); + guidata(hObject, handles); + if exist('xSPM','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + {xSPM.SPM.xCon(numc).name}); + else + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + '???'); + end + % CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end +uicontrol(hObject) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_paramestRegionPush(hObject, eventdata, roi,readdata) +if nargin<4 + readdata=1; +end +roi=struct('type', roi); +handles = guidata(hObject); +roi.name=get(handles.structureEdit, 'String'); + +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); + +if exist(spmfile(3:end), 'file') + warning('Possible disk swapping in xjview.m'); + spmfile=spmfile(3:end); +end +if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the RFX SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the RFX SPM.mat'); + end +end +if ~exist(spmfile) + return +end +xSPM=load(spmfile, 'SPM'); +[glmpath, glmpath]=fileparts(fileparts(fileparts(xSPM.SPM.swd))); + +RetrieveRawData = 0; +status = get(gcbf, 'SelectionType') +% right click +if strcmp(status, 'alt') + RetrieveRawData = 1; +end + + + + +%[xyzmm,i] = spm_XYZreg('NearestXYZ',... +% spm_results_ui('GetCoords'),handles.currentxyz); +%spm_results_ui('SetCoords',xSPM.XYZmm(:,i)); +switch roi.type + case 'vox' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + xyz = handles.currentxyz; + case 'clu' + if not(isfield(handles,'selectedCluster')) | not(isempty(handles.selectedCluster)) + switch questdlg('Load from workspace','cluster?', 'currentDisplayMNI{1}','...','Cancel','currentDisplayMNI{1}') + case 'currentDisplayMNI{1}' + xyz=evalin('base', 'currentDisplayMNI{1}'); + case '...' + case 'Cancel' + return + end + delete(findobj('Tag', 'paramest')) + + else + delete(findobj('Tag', 'paramest')) + xyz =handles.currentDisplayMNI{1}; + end + case 'sph' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + delete(findobj('Tag', 'paramest')) + xyz = handles.currentxyz; + roi.radius=inputdlg('Radius of the sphere?'); + if isempty(roi.radius) + return + end + roi.radius=str2num(roi.radius{1}) + % XYZmm = xSPM.SPM.xVol.M(1:3,:)*[xSPM.SPM.xVol.XYZ; ones(1,size(xSPM.SPM.xVol.XYZ,2))]; + % xyz = sqrt( XYZmm-repmat(xyz,[1 size(XYZmm,2)]) ) + % xyz = XYZmm(:, xyz < roi.radius) + +end +% handles.currentDisplayMNI{1} +% ha=axes('Tag', 'paramest', 'Parent',gcf,'units','normalized','Position',[0.55, 0.05, 0.4, 0.4]); +if isequal(roi.type, 'sph') + if roi.radius > 20 + if not(spm_input({'Many many voxels may be retrieve','Radius of the sphere (in mm):',... + num2str(roi.radius),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end + end + +end +if size(xyz,1)>40 + if not(spm_input({'Many many voxels to retrieve','Number of voxel:',... + num2str(size(xyz,1)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end +end + +allbetas= []; +allcons= []; +allxyz = []; +allvxyz = []; +roi.nvox = []; +hwait = waitbar(0,'Reading 1st level data'); +lcd=cd; +handles.currentxyz +if isfield(handles, 'paramest') + handles.paramest=[]; +end + +roi.stat.TF=handles.TF; +roi.stat.pValue=handles.pValue; +roi.stat.df=handles.df; +% roi.stat.Intensity = +% handles.currentDisplayIntensity{1}(find(all(handles.currentDisplayMNI{1}==repmat(handles.currentxyz, 3,1),2))); +[i,j]=ismember(handles.mni{1}, flipud(xyz), 'rows'); +roi.stat.intensity(j(i)) = handles.intensity{1}(i); + +if isstruct(xSPM.SPM.xX.K) | ~readdata + n=1; + % Ic=strmatch('F Task',{xSPM.SPM.xCon.name}) + % + % allbetas=[] + % vcon= + % XYZ = SPM.xVol.XYZ; + % XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + % tmpallbetas= []; + % [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + % allbetas = [allbetas;(mean(tmpallbetas,1))]; + % allxyz= [allxyz;mean(tmpallxyz,1)]; + +else + n= length(xSPM.SPM.xY.P) +end + +% Is that a correlation? +PlotCorrelation = (n>1) && not(isequal(all(xSPM.SPM.xX.X==1), [1])); + +try + roi.sub2pr = str2num(subarray(strvcat(xSPM.SPM.xY.P),55:56,2)); +end + + +for sub = 1:n + + waitbar(sub/n,hwait); + if n>1 + subdir = fileparts(xSPM.SPM.xY.P{sub}); + else + subdir = xSPM.SPM.swd; + end + subdir0 =subdir; + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, '[A-Z]?\:',''); + end + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, {'^\\ndiayek', '^\\ndiaye'},'') + end + + + if ~exist(fullfile(subdir, 'SPM.mat'), 'file') & ... + exist(subarray(fullfile(subdir, 'SPM.mat'),1:2,-2),'file') + subdir = subdir(3:end); + end + if exist(fullfile(subdir, 'SPM.mat'), 'file') + load(fullfile(subdir, 'SPM.mat')); + fprintf('Retrieving betas from: %s\n', fullfile(subdir, 'SPM.mat')) + + if sub==1 + % [cn.path cn.fname cn.ext]=fileparts(char(xSPM.SPM.xY.P(sub,:))); + % consfiles=[SPM.xCon.Vcon]; + + % retrieves the f map (where all betas should be) + Ic = [... + strmatch('f anim', lower({SPM.xCon.name})) ... + strmatch('f task', lower({SPM.xCon.name})) ... + strmatch('f map', lower({SPM.xCon.name}))]; + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name},'InitialValue',Ic); + end + Ic=Ic(end); + conname=SPM.xCon(Ic).name; + end + + %------- + Ic = strmatch(conname,{SPM.xCon.name}, 'exact') ; %contrast number + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name}); + end + %------- + else + SPM = xSPM.SPM + %using raw data + Ic=NaN; + end + try + XYZ = SPM.xVol.XYZ; + XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + tmpallbetas= []; + tmpallcons= []; + tmpallxyz = []; + cd(subdir) + for cluvox = 1:size(xyz,1) + switch (roi.type) + case 'sph' + [d] = spm_XYZreg('Edist',xyz(cluvox,:),XYZmm); + i=find(d<=roi.radius); + govox = ~isempty(i); + nxyz=XYZmm(:,i); + case {'vox', 'clu'} + govox = 1; + [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=sqrt(3) %one voxel in each dimZ + govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',... + num2str(xyz(cluvox,:)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0]); + end + end + if govox==1 + vXYZ = XYZ(:,i) ; % coordinates in voxels + + %-Get parameter and hyperparameter estimates + %======================================================================= + % ResMS = spm_get_data(SPM.VResMS,vXYZ); + % Bcov = ResMS*SPM.xX.Bcov; + CI = 1.6449; % = spm_invNcdf(1 - 0.05); + % compute contrast of parameter estimates and 90% C.I. + %---------------------------------------------------------- + %---- + xSPM.SPM.xY.VY(sub).fname = strrep(xSPM.SPM.xY.VY(sub).fname, subdir0, subdir); + tmpallcons = [tmpallcons ; spm_get_data(xSPM.SPM.xY.VY(sub), vXYZ)]; + if ~isnan(Ic) + beta = spm_get_data(SPM.Vbeta, vXYZ); + tmpallbetas = [tmpallbetas; (SPM.xCon(Ic).c'*beta)']; + else + tmpallbetas = tmpallcons; + end + + if RetrieveRawData + if sub==1 + fprintf('\tRetrieving rawdata from: %s\n', fullfile(subdir, 'SPM.mat')) + tmpallcons = [ spm_get_data(xSPM.SPM.xY.VY, vXYZ)']; + end + end + tmpallxyz = [tmpallxyz; nxyz']; + end + end + allbetas = [allbetas;(mean(tmpallbetas,1))]; + allcons = [allcons;(mean(tmpallcons,1))]; + allxyz= [allxyz;mean(tmpallxyz,1)]; + allvxyz= [allvxyz mean(vXYZ,2)]; + roi.nvox = [ roi.nvox; size(tmpallbetas,1)]; + tmp = mean(tmpallxyz); + % disp(['meancluster = ' num2str(mean(tmpallxyz,1))]); + catch + warning('Error with data from: %s', subdir) + end +end +close(hwait) +cd(lcd); +% +if ~isnan(Ic) + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c )),'*bf(1)', '')'), 1:6, -2)); + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c')),'*bf(1)', '')'), 1:6, -2)); + [regnames, ireg,ireg2]=unique(regnames); + a=[ repmat(' ',length(regnames),1) strvcat(strrep(regnames, '_', ' '))]; + a=dataread('string',a', '%s'); + leg=a(isort(ireg)); +else + leg={'??'}; +end +%a=reshape(a, [],108])'; +% +% n=factor(size(allbetas,2)); +% n=sort([n(end) prod(n(1:end-1))]); +% +% prompt={'Enter the matrix size for x^2:','Enter the colormap name:'}; +% def={'20','hsv'}; +% dlgTitle='Input for Peaks function'; +% lineNo=1; +% answer=inputdlg(prompt,dlgTitle,lineNo,def); +% +% AddOpts.Resize='on'; +% AddOpts.WindowStyle='normal'; +% AddOpts.Interpreter='tex'; +% answer=inputdlg(prompt,dlgTitle,lineNo,def,AddOpts); +% +assignin('base', 'allbetas', allbetas) +% ReshapeData = []; +% xbars=[]; +% fxorder=[2 3 1]; +% switch size(allbetas,2) +% case 8 +% ReshapeData = [4 2]; +% case 4 +% if all(ismember(a,{'Neutral' 'Fearful' 'Angry' 'Happy'})) +% ReshapeData = [4 1]; +% end +% case 18 +% ReshapeData = [18 1]; +% case 16 +% % ReshapeData = [2 8]; +% % xtick=[1 3 4 5 7 8 9 11]; +% % fxorder=[3 2 1]; +% ReshapeData = [16 1]; +% end +% if isempty(ReshapeData) +% ReshapeData = [fliplr(factor(size(allbetas,2))) 1]; +% ReshapeData = [ ReshapeData(1) prod(ReshapeData(2:end))] +% end +% allbetas=reshape(allbetas, [],ReshapeData(1),ReshapeData(2)); +% allbetas = permute(allbetas,fxorder); + +% allxyz=reshape(allxyz, [], 1, 3); +% allxyz=permute(allxyz, [3 2 1]); + +%assignin('base', 'allbetas', allbetas) +%assignin('base', 'allxyz', xyz) + + +roi.allbetas=allbetas; +roi.allxyz=allxyz'; +roi.allvxyz=allvxyz; +roi.allcons=allcons'; +roi.XYZmm=xyz'; +roi.xyz=mean(allxyz,1)'; +assignin('base', 'roi', roi) +%Icc = find(xSPM.SPM.xX.X*xSPM.SPM.xCon(strmatch(handles.imageContrastName{1}, {xSPM.SPM.xCon.name})).c); +% if ~isempty(handles.imageContrastName) +% fn=handles.imageContrastName{1}; +% else +[fp,fn,fe] = fileparts(handles.imageFileName{1}); +fn=[fn fe]; +cn=[xSPM.SPM.xCon.Vspm]; + +% end +Icc = strmatch(fn, {cn.fname}) ; +roi.fname = fullfile(fp,fn); +roi.cn = cn; +roi.Icc=Icc; +roi.leg=leg; +assignin('base', 'roi', roi) + + +try + plot_betas(roi,glmpath,handles) +catch + if n>1 + try + figure;h=barerrorbar(1:(prod(size(roi.allbetas))/size(roi.allbetas,1)),mean(roi.allbetas,1)',stderrw(roi.allbetas,2:ndims(roi.allbetas),1)',NaN) + catch + end + else + figure;bar(roi.allbetas) + end + xlabel('Task') + set(gca, 'XTickLabel', leg) + set(gca, 'XTickLabel', {'Self Pos' 'Self Neg' 'Other Pos' 'Other Neg' 'Word Pos' 'Word Neg'}) + xlabel('Task') + %legend({'Positive Words' 'Negative Words'},'Location', 'Best') + delete(legend) +end +title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +setappdata(gca, 'ROI', roi) + +if ~isempty(Icc) + if ~isempty(xSPM.SPM.xCon(Icc).c) + roi.allregressors = xSPM.SPM.xX.X*xSPM.SPM.xCon(Icc).c; + else + roi.allregressors = []; + end + assignin('base', 'roi', roi) +end +if PlotCorrelation + %correlation plot + figure; + cla; + plot(roi.allregressors, roi.allcons, 'x') + %hl=legend({'test'}, 0); + [s,o,r2,sce,p]=linearfit(roi.allcons,roi.allregressors); + text(median(roi.allregressors), quantile(roi.allcons,.90), {'Correlation: ' sprintf('r2 = %g\np = %g', r2,p)}) + xlabel(xSPM.SPM.xX.name(find(xSPM.SPM.xCon(Icc).c))) + ylabel(xSPM.SPM.xY.VY(1).descrip) + [xx]=axis; + hold on + plot(xx(1:2), s*xx(1:2)+o, '--') + hold off + title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +end + +if RetrieveRawData + figure; + if n==1 + subplot(2,1,1); + plot(tmpallcons); + legend('BOLD',0) + subplot(2,1,2); + % iReg=any(SPM.xCon(handles.imageContrastName).c,2); + % plot(normalize(SPM.xX.X(:,iReg), 'unity')*diff(subarray(axis, [3 4]))/5+subarray(axis, 3)) + % legend([{'BOLD'} SPM.xX.name(iReg)],1) + Ic = handles.imageContrastName; + if isempty(Ic) || ~isnumeric(Ic) + Ic = get(handles.contrastListPush, 'Value'); + end + plot( [ + spm_FcUtil('Yc',SPM.xCon(Ic),SPM.xX.xKXs,beta) ... + SPM.xX.X*SPM.xCon(Ic).c*pinv(SPM.xCon(Ic).c)*beta ... + (1-2*get(handles.negativeIntensityRadio, 'Value'))*SPM.xX.X*SPM.xCon(Ic).c ]) + legend({ 'adjusted', 'predicted' SPM.xCon(Ic).name},0) + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [c_num, c_let, c_word]=mycolourset +c_num = [1 0 0;0 1 0;1 1 0;0 1 1;0 0 1;1 0 1]; +c_let = {'r';'g';'y';'c';'b';'m'}; +c_word= {'red';'green';'yellow';'cyan';'blue';'magenta'}; \ No newline at end of file diff --git a/xjview8p4.m b/xjview8p4.m new file mode 100644 index 0000000..6a6fed1 --- /dev/null +++ b/xjview8p4.m @@ -0,0 +1,12218 @@ +function xjview(varargin) +% xjview, version 8.4 +% +% usage 1: xjview (no argument) +% for displaying a result img file, or multiple image files, +% (which will be loaded later) and changing p-value or t/f-value +% usage 2: xjview(imagefilename) +% for displaying the result img file and changing p-value or +% t-value +% Example: xjView spmT_0002.img +% xjView('spmT_0002.img') +% xjView mymask.img +% usage 3: xjview(imagefilename1, imagefilename2, ...) +% for displaying the result img files and changing p-value or +% t/f-value +% Example: xjView spmT_0002.img spmT_0005.img spmT_0007.img +% xjView('spmT_0002.img', 'spmT_0003.img', 'spmT_0006.img') +% xjView myMask1.img myMask2.img myMask3.img +% usage 4: xjview(mnicoord, intensity) +% for displaying where are the mni coordinates +% mnicoord: Nx3 matrix of mni coordinates +% intensity: (optional) Nx1 matrix, usually t values of the +% corresponding voxels +% Example: xjView([20 10 1; -10 2 5],[1;2]) +% xjView([20 10 1; -10 2 5]) +% Note: to use xjview this way, you may need to modify the value +% of M and DIM in the begining of xjview.m +% +% http://www.alivelearn.net/xjview +% +% by Xu Cui, Jian Li and Xiaowei Song +% last modified: 10/21/2011 (compatible with MatLab 2011) +% last modified: 2/28/2011 (add small volume correction) +% last modified: 2/25/2011 (fix volume bug under SPM 8 r4010) +% last modified: 12/14/2009 (FDR and Feed) +% last modified: 06/24/2009 (fix bug in activation report) +% last modified: 05/24/2009 (slice view) +% last modified: 04/17/2009 (SPM8 compatible) +% last modified: 11/20/2007 (new database, all database from wfu_pickatlas, including aal +% last modified: 06/01/2007 (correct FDR corrected p-value list, change intensity to handles.intensity{1}) +% last modified: 02/18/2007 (add colorbar max control) +% last modified: 11/16/2006 (keyboard shortcut for open image and open roi file) +% last modified: 06/16/2006 (spm5 compatible) +% last modified: 05/30/2006 (left/right flip, path of mask.img and templateFile.img) +% last modified: 05/08/2006 (debug CallBack_volumePush function, change handles.intensity{1} to intensity) +% last modified: 04/03/2006 (modify tr) +% last modified: 12/28/2005 (modify SPM process) +% +% Thank Sergey Pakhomov for sharing his database (MNI Space Utility). +% Thank Joseph Maldjian for WFU_PickAtlas +% Thank Yuval Cohen for the maximize figure function (maximize.m) +% + +warnstate = warning; +warning off; + +% pre-set values +% important! you need compare the display of xjview and spm. If you find +% xjview flipped the left/right, you need to set leftrightflip = 1; +% otherwise leave it to 0. +leftrightflip = 0; + +% You only need to change M and DIM when you want to use xjview under +% 'usage 4'. +M = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +DIM = [41 48 35]'; + M = [ + -2 0 0 92 + 0 2 0 -128 + 0 0 2 -74 + 0 0 0 1]; + DIM = [91 109 91]'; +M = ... + [-4 0 0 82;... + 0 4 0 -116;... + 0 0 4 -54;... + 0 0 0 1]; +DIM = [40 48 34]'; + +TR = 2; % you don't need to set TR is you only use the viewing part of xjview +XJVIEWURL = 'http://www.alivelearn.net/xjview'; + +% system settings +try + spmdir = spm('dir'); + %spm('defaults', 'fmri'); +catch + disp('Please add spm path.'); + warning(warnstate(1).state); + return +end + +try + spm('defaults', 'fmri'); +catch + []; +end + + +if ispc + os = 'windows'; +elseif isunix + os = 'linux'; +else + warndlg('I don''t know what kind of computer you are using. I assumed it is unix.', 'What computer are you using?'); + os = 'linux'; +end +screenResolution = get(0,'ScreenSize'); + +xjviewpath = fileparts(which('xjview')); + +% pre-set values +pValue = 0.001; +intensityThreshold = 0; +clusterSizeThreshold = 5; + + +% Appearance Settings +figurePosition = [0.100, 0.050, 0.550, 0.880]; +sectionViewPosition = [0.5,0.61,0.45,0.45]; +glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +if screenResolution(3) <= 1024 + figurePosition = [0.100, 0.050, 0.700, 0.900]; + sectionViewPosition = [0.5, 0.61, 0.45, 0.46]; + glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +end + +left = 0.01; +editBoxHeight = 0.05; +editBoxWidth = 0.200; +editBoxLeft = 0.100; + +controlPanelPosition = [left, 0.080, 0.500, 0.500]; +stretchMatrix = diag([controlPanelPosition(3),controlPanelPosition(4),controlPanelPosition(3),controlPanelPosition(4)]); +controlPanelOffset = controlPanelPosition' .* [1,1,0,0]'; +heightUnit = 0.055; + +sliderPosition = stretchMatrix*[0.000, 0*heightUnit-0.01, 1.000, editBoxHeight]' + controlPanelOffset; +pValueTextPosition = stretchMatrix*[0.000, 0.8*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pValueEditPosition = stretchMatrix*[0.100, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +fdrTextPosition = stretchMatrix*[0.350, 0.8*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +fdrEditPosition = stretchMatrix*[0.450, 1*heightUnit, editBoxWidth/2, editBoxHeight]' + controlPanelOffset; +fdrPushPosition = stretchMatrix*[0.300, 1*heightUnit, editBoxWidth/2, editBoxHeight]' + controlPanelOffset; +intensityThresholdTextPosition = stretchMatrix*[0.55, 0.8*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +intensityThresholdEditPosition = stretchMatrix*[0.65, 1*heightUnit, editBoxWidth*3/4, editBoxHeight]' + controlPanelOffset; +dfTextPosition = stretchMatrix*[0.840, 0.8*heightUnit, 0.8-0.74, editBoxHeight]' + controlPanelOffset; +dfEditPosition = stretchMatrix*[0.900, 1*heightUnit, editBoxWidth/2, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdTextPosition = stretchMatrix*[0.000, 1.8*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdEditPosition = stretchMatrix*[0.150, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pickThisClusterPushPosition = stretchMatrix*[0.400, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +selectThisClusterPushPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +clearSelectedClusterPushPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +thisClusterSizeTextPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +thisClusterSizeEditPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +loadImagePushPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +imageFileEditPosition = stretchMatrix*[0.200, 3*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImagePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImageFileEditPosition = stretchMatrix*[0.200, 4*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveResultPSPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +resultPSFileEditPosition = stretchMatrix*[0.200, 5*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayIntensityTextPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth+0.1, editBoxHeight]' + controlPanelOffset; +allIntensityRadioPosition = stretchMatrix*[0.250, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +positiveIntensityRadioPosition = stretchMatrix*[0.400, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +negativeIntensityRadioPosition = stretchMatrix*[0.550, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderViewCheckPosition = stretchMatrix*[0.730, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderStylePopPosition = stretchMatrix*[0.90, 3*heightUnit, editBoxWidth/2, editBoxHeight]' + controlPanelOffset; +hideControlPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +reportPushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +volumePushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +smallVolumePosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +commonRegionPushPosition = stretchMatrix*[0.600, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; + +reslicePushPosition = stretchMatrix*[0.600, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +sliceViewPushPosition = stretchMatrix*[0.780, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +allinonePushPosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchPushPosition = stretchMatrix*[0.000, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchContentEditPosition = stretchMatrix*[0.200, 6*heightUnit, editBoxWidth*2, editBoxHeight]' + controlPanelOffset; +searchTextPosition = stretchMatrix*[0.600, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchEnginePopPosition = stretchMatrix*[0.600, 6*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +overlayPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayEditPosition = stretchMatrix*[0.200, 5*heightUnit, 0.6-editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayPopPosition = stretchMatrix*[0.600, 5*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +helpPosition = stretchMatrix*[0.800, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +infoTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; +%xjViewPosition = stretchMatrix*[0.400, 13*heightUnit, editBoxWidth*2.5, editBoxHeight*3]' + controlPanelOffset; + +sectionViewListboxPosition = [sectionViewPosition(1)+0.4, sectionViewPosition(2)+0.02, 0.1, 0.14]; +sectionViewMoreTargetPushPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.02,0.10,0.02]; +xHairCheckPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)+0.14,0.15,0.02]; +setTRangeEditPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.06,0.10,0.02]; +setTRangeTextPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.04,0.10,0.02]; + +getStructurePushPosition = [glassViewAxesPosition(1), glassViewAxesPosition(2)-0.06, editBoxWidth/2, editBoxHeight/2]; +structureEditPosition = [getStructurePushPosition(1), getStructurePushPosition(2), 1, getStructurePushPosition(4)]; +framePosition = (controlPanelPosition - controlPanelOffset')*1.05 + 0.95*controlPanelOffset'; + +% draw figure and control +figureBKcolor=[176/255 252/255 188/255]; +figureBKcolor=get(0,'Defaultuicontrolbackgroundcolor'); +f = figure('unit','normalized','position',figurePosition,'Color',figureBKcolor,'defaultuicontrolBackgroundColor', figureBKcolor,... + 'Name','xjView', 'NumberTitle','off','resize','off','CloseRequestFcn', {@CallBack_quit, warnstate(1).state}, 'visible','off', 'DoubleBuffer','on'); +handles = guihandles(f); + +% databases +try + X = load('TDdatabase'); + handles.DB = X.DB; + handles.wholeMaskMNIAll = X.wholeMaskMNIAll; +catch + errordlg('I can''t find TDdatabase.mat','TDdatabase not found'); +end + +handles.figure = f; +handles.frame = uicontrol(handles.figure,'style','frame',... + 'unit','normalized',... + 'position',framePosition,... + 'Visible','off'); +handles.slider = uicontrol(handles.figure,'style','slider',... + 'unit','normalized',... + 'position',sliderPosition,... + 'max',1,'min',0,... + 'sliderstep',[0.01,0.10],... + 'callback',@CallBack_slider,... + 'value',0,'Visible','on'); +handles.pValueTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',pValueTextPosition,... + 'string','pValue=','horizontal','left'); +handles.pValueEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',pValueEditPosition,... + 'horizontal','left',... + 'String', num2str(pValue),... + 'BackgroundColor', 'w',... + 'callback',@CallBack_pValueEdit); +handles.fdrTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',fdrTextPosition,... + 'string','FDR p=','horizontal','left'); +handles.fdrEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',fdrEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_fdrEdit); +handles.intensityThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',intensityThresholdTextPosition,... + 'string',' intensity=','horizontal','left'); +handles.intensityThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',intensityThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(intensityThreshold),... + 'callback',@CallBack_intensityThresholdEdit); +handles.dfText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',dfTextPosition,... + 'string','df= ','horizontal','right'); +handles.dfEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',dfEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', '',... + 'callback',@CallBack_dfEdit); +handles.clusterSizeThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',clusterSizeThresholdTextPosition,... + 'string','cluster size >=','horizontal','left'); +handles.clusterSizeThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',clusterSizeThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(clusterSizeThreshold),... + 'callback',@CallBack_clusterSizeThresholdEdit); +handles.thisClusterSizeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',thisClusterSizeTextPosition,... + 'string','size= ','horizontal','right', 'visible', 'off'); +handles.thisClusterSizeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',thisClusterSizeEditPosition,... + 'horizontal','left',... + 'Enable', 'inactive',... + 'String', '','visible','off'); + +handles.imageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',imageFileEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_imageFileEdit,... + 'visible','off'); +handles.saveImageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',saveImageFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myMask.img',... + 'callback',@CallBack_saveImageFileEdit,... + 'visible','off'); +handles.saveResultPSEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',resultPSFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myResult.ps',... + 'callback',@CallBack_saveResultPSEdit,... + 'visible','off'); +handles.loadImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',loadImagePushPosition,... + 'string','Load Image','callback',@CallBack_loadImagePush,... + 'visible','off'); +handles.saveImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveImagePushPosition,... + 'string','Save Image','callback',@CallBack_saveImagePush,... + 'visible','off'); +handles.saveResultPSPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveResultPSPushPosition,... + 'string','Save Result','callback',@CallBack_saveResultPSPush,... + 'visible','off'); +handles.getStructurePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',getStructurePushPosition,... + 'string','Get Structure','callback',@CallBack_getStructurePush,'visible','off'); +handles.structureEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',structureEditPosition,... + 'horizontal','center',... + 'enable', 'on',... + 'UserData',struct(... + 'hReg', [],... + 'M', M,... + 'D', DIM,... + 'xyz', [0 0 0] )); +handles.pickThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',pickThisClusterPushPosition,... + 'string','Pick Cluster/Info','callback',@CallBack_pickThisClusterPush); +handles.selectThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',selectThisClusterPushPosition,... + 'string','Select Cluster','callback',@CallBack_selectThisClusterPush); +handles.clearSelectedClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',clearSelectedClusterPushPosition,... + 'string','Clear Selection','callback',@CallBack_clearSelectedClusterPush); + +handles.displayIntensityText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',displayIntensityTextPosition,... + 'string','display intensity','horizontal','left'); +handles.allIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','All',... + 'position',allIntensityRadioPosition,... + 'value', 1,... + 'callback',@CallBack_allIntensityRadio); +handles.positiveIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only +',... + 'position',positiveIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'+'}); +handles.negativeIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only -',... + 'position',negativeIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'-'}); +handles.renderViewCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','Render View' ,... + 'horizontal', 'right',... + 'position',renderViewCheckPosition,... + 'callback', @CallBack_renderViewCheck); +handles.renderStylePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',renderStylePopPosition, ... + 'String',{'new';'old'}, ... + 'Style','popupmenu', ... + 'value',1,... + 'callback', @CallBack_renderStylePop); +handles.sectionViewListbox = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', {'single T1','avg152PD','avg152T1','avg152T2','avg305T1','ch2','ch2bet','aal','brodmann'}, ... + 'value',3,... + 'position',sectionViewListboxPosition,... + 'callback',@CallBack_sectionViewListbox); + +handles.xHairCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','XHairs Off' ,... + 'horizontal','left',... + 'position',xHairCheckPosition,... + 'callback',@CallBack_xHairCheck); +handles.sectionViewMoreTargetPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',sectionViewMoreTargetPushPosition,... + 'string','other ...','callback',@CallBack_sectionViewMoreTargetPush); +handles.setTRangeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',setTRangeEditPosition,'BackgroundColor', 'w',... + 'string','auto','callback',@CallBack_setTRangeEdit); +handles.setTRangeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setTRangeTextPosition,... + 'string','colorbar max'); +handles.hideControlPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', '<', 'position', hideControlPushPosition,... + 'visible','off'); +handles.reportPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'report', ... + 'position', reportPushPosition,... + 'callback', @CallBack_reportPush); +handles.volumePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'volume', ... + 'position', volumePushPosition,... + 'callback', @CallBack_volumePush); +handles.commonRegionPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'common region', ... + 'position', commonRegionPushPosition,... + 'callback', @CallBack_commonRegionPush); +% handles.fdrPush = uicontrol(handles.figure, 'style', 'push',... +% 'unit','normalized',... +% 'String', 'FDR', ... +% 'position', fdrPushPosition,... +% 'callback', @CallBack_fdrPush); +handles.reslicePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'reslice', ... + 'visible', 'off', ... + 'position', reslicePushPosition,... + 'callback', @CallBack_reslicePush); + +handles.sliceViewPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'slice view', ... + 'position', sliceViewPushPosition,... + 'callback', @CallBack_sliceViewPush); + +handles.displayPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'display', ... + 'position', displayPushPosition,... + 'callback', @CallBack_displayPush,... + 'visible','off'); +handles.allinonePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'all in one', ... + 'position', allinonePushPosition,... + 'callback', @CallBack_allinonePush,... + 'visible','off'); +handles.searchPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',searchPushPosition,... + 'String', 'search','callback',@CallBack_searchPush, 'ForeGroundColor',[0 0 1]); +handles.searchContentEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',searchContentEditPosition,... + 'ForeGroundColor',[0 0 1],... + 'BackgroundColor', 'w',... + 'horizontal','left'); +handles.searchText = uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',searchTextPosition,... + 'string', ' in',... + 'horizontal','left',... + 'visible','off'); +handles.searchEnginePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',searchEnginePopPosition, ... + 'String',{'in xBrain';'in google scholar';'in pubmed';'in wiki'}, ... + 'Style','popupmenu', ... + 'value',1); +handles.overlayPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',overlayPushPosition,... + 'String', 'overlay','callback',@CallBack_overlayPush); +handles.overlayEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',overlayEditPosition,... + 'BackgroundColor', 'w',... + 'horizontal','left',... + 'callback', @CallBack_overlayEdit); +handles.overlayPop = uicontrol(handles.figure, 'style','popupmenu',... + 'unit','normalized','position',overlayPopPosition,... + 'string', sort(fieldnames(handles.wholeMaskMNIAll)),... + 'horizontal','left',... + 'callback', @CallBack_overlayPop); + +handles.helpPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',helpPosition,... + 'String', 'help','callback',['web ' XJVIEWURL],'ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.infoTextBox = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',infoTextBoxPosition,... + 'String', 'Welcome to xjView 8','ForeGroundColor','k', 'BackgroundColor', 'w',... + 'horizontal','left', ...'fontname','times',... + 'max',2, 'min',0); +handles.getCurrentPosition = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',[0.6 0.4 0.2 0.05],... + 'String', 'get xyz','callback',@CallBack_getCurrentPosition,'ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.getCurrentPosition = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',smallVolumePosition,... + 'String', 'Small volume','callback',@CallBack_smallVolume,... + 'horizontal','left'); +try + %urlread([XJVIEWURL '/guestbook/stat.php']); + s = urlread([XJVIEWURL '/toUser.txt']); + set(handles.infoTextBox, 'String', s); +end + +% feed +try + s = urlread(['http://www.alivelearn.net/xjview8/getFeed.php']); + [feeds, links]=strread(s,'%s%s', 'delimiter','\t'); + + handles.feed = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', feeds, ... + 'userdata',links, ... + 'value',1,... + 'fontsize',12,... + 'position',[0.55 0.05 0.44 0.25]); + handles.refreshclick = uicontrol(handles.figure,'style','push',... + 'unit','normalized',... + 'String', 'Refresh', ... + 'position',[0.55 0.02 0.1 0.03],... + 'fontsize',12, ... + 'callback',@refreshFeeds); + handles.feedclick = uicontrol(handles.figure,'style','push',... + 'unit','normalized',... + 'String', 'Read', ... + 'position',[0.88 0.02 0.1 0.03],... + 'fontsize',12, ... + 'callback',@openURL); + handles.postfeedclick = uicontrol(handles.figure,'style','push',... + 'unit','normalized',... + 'String', 'Post', ... + 'position',[0.65 0.02 0.05 0.03],... + 'fontsize',12, ... + 'callback','web(''http://www.alivelearn.net/xjview8/feed.php'')'); +end + +handles.glassViewAxes = axes('unit','normalized','position',glassViewAxesPosition,'XTick',[],'YTick',[],'visible','off'); + + +handles.testEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',[0.1 0.4 0.2 0.05],... + 'horizontal','left',... + 'callback',@test,... + 'visible','off'); + +% menu +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +hMenuFile = findobj(get(handles.figure,'Children'),'flat','Label','&File'); +if ~isempty(hMenuFile) + hMenuFileOpen = findobj(get(handles.figure,'Children'),'Label','&Open...'); + set(hMenuFileOpen, 'label', 'Open Figure...'); + hMenuFileSave = findobj(get(handles.figure,'Children'),'Label','&Save'); + set(hMenuFileSave, 'label', 'Save Figure ...'); + hMenuFileSaveAs = findobj(get(handles.figure,'Children'),'Label','Save &As...'); + set(hMenuFileSaveAs, 'label', 'Save Figure As ...'); +else + hMenuFile = uimenu(handles.figure, 'label', '&File'); +end + +set(hMenuFile,'ForegroundColor',[0 0 1]); +set(findobj(hMenuFile,'Position',1),'Separator','on'); +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open Images (*.img) ...',... + 'CallBack',@CallBack_loadImagePush, 'Accelerator', 'o'); +uimenu('Parent',hMenuFile,'Position',2,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 0}); +uimenu('Parent',hMenuFile,'Position',3,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image as Mask (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 1}); +% uimenu('Parent',hMenuFile,'Position',4,'ForegroundColor',[0 0 1],... +% 'Label','Save Result (*.ps/pdf) ...',... +% 'CallBack',@CallBack_saveResultPSPush); + +hMenuHelp = findobj(get(handles.figure,'Children'),'flat','Label','&Help'); +if isempty(hMenuHelp) + hMenuHelp = uimenu(handles.figure, 'label', 'xjView &Help'); +end +set(hMenuHelp,'ForegroundColor',[0 0 1]); +uimenu('Parent',hMenuHelp,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','xBrain.org: brain mapping database',... + 'CallBack','web http://www.xbrain.org'); +uimenu('Parent',hMenuHelp,'Position',2,... + 'Label','xjview help','ForegroundColor',[0 0 1],... + 'CallBack',['web ' XJVIEWURL]); +set(findobj(hMenuHelp,'Position',3),'Separator','on'); +set(0,'ShowHiddenHandles',cSHH) + +if exist('cuixuBOLDretrieve') + hMenuAnalyze = uimenu('label','&Analyze','ForegroundColor',[0 0 1],'visible','on'); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess CIBSR','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess_cibsr); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess); + hMenuProcess = uimenu(hMenuAnalyze,'label','Process (GLM estimation)','ForegroundColor',[0 0 1],'callback',@CallBack_process); + hMenuSPMProcess = uimenu(hMenuAnalyze,'label','SPMProcess (GLM using SPM)','ForegroundColor',[0 0 1],'callback',@CallBack_SPMProcess); + hMenuGLMPeak = uimenu(hMenuAnalyze,'label','GLM on peak BOLD','ForegroundColor',[0 0 1],'callback',@CallBack_GLMPeak); + hMenuContrast = uimenu(hMenuAnalyze,'label','Contrast','ForegroundColor',[0 0 1],'callback',@CallBack_contrast); + hMenuFDR = uimenu(hMenuAnalyze,'label','FDR','ForegroundColor',[0 0 1],'callback',@CallBack_fdr); + hMenuROI = uimenu(hMenuAnalyze,'label','ROI: retrieve signal','ForegroundColor',[0 0 1],'callback',@CallBack_timeSeries); + hMenuROIPlot = uimenu(hMenuAnalyze,'label','ROI: plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotROI, 'Accelerator', 'm'); + hMenuROIIndividualPlot = uimenu(hMenuAnalyze,'label','ROI: individual plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROI); + hMenuROIIndividualPlotWithBehavior = uimenu(hMenuAnalyze,'label','ROI: individual plot with behavior','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROIWithBehavior); + hMenuROICorrelationPlot = uimenu(hMenuAnalyze,'label','ROI: correlation plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotCorrelationROI); + %hMenuWholeBrainCorrelation = uimenu(hMenuAnalyze,'label','Whole brain correlation','ForegroundColor',[0 0 1],'callback',@CallBack_wholeBrainCorrelation); + hMenuBehaviorAnalysis = uimenu(hMenuAnalyze,'label','Behavior analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_behaviorAnalysis); + hMenuHeadMovementAnalysis = uimenu(hMenuAnalyze,'label','Other analysis (head motion, gsr, physio etc)','ForegroundColor',[0 0 1],'callback',@CallBack_headMovementAnalysis); + hMenuModelComparison = uimenu(hMenuAnalyze,'label','Linear model comparison','ForegroundColor',[0 0 1],'callback',@CallBack_modelComparison); + + hMenuHNLOnly = uimenu('label','For H&NL Only','ForegroundColor',[0 0 1],'visible','on'); + hMenuNew2Old = uimenu(hMenuHNLOnly,'label','Format convert','ForegroundColor',[0 0 1],'callback',@CallBack_new2old); + hMenuPreprocessCluster = uimenu(hMenuHNLOnly,'label','Preprocess (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_preprocess, 'cluster'}); + hMenuProcessCluster = uimenu(hMenuHNLOnly,'label','Process (GLM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_process, 'cluster'}); + hMenuSPMProcessCluster = uimenu(hMenuHNLOnly,'label','SPM Process (GLM using SPM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_SPMProcess, 'cluster'}); + hMenuGLMPeakCluster = uimenu(hMenuHNLOnly,'label','GLM on peak BOLD (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_GLMPeak, 'cluster'}); + + hMenuNIRS = uimenu('label','&NIRS','ForegroundColor',[0 0 1],'visible','on'); + hMenuNIRS_SPM = uimenu(hMenuNIRS,'label','NIRS-SPM','ForegroundColor',[0 0 1],'callback', @CallBack_nirs_spm); + hMenuNIRS_TOPO = uimenu(hMenuNIRS,'label','xTOPO','ForegroundColor',[0 0 1],'callback', @CallBack_nirs_topo); + hMenuNIRS_nirs = uimenu(hMenuNIRS,'label','nirs','ForegroundColor',[0 0 1],'callback', @CallBack_nirs); + + hMenuOther = uimenu('label','&Other','ForegroundColor',[0 0 1],'visible','on'); + hMenuOther_signal = uimenu(hMenuOther,'label','Signal processing toolbox','ForegroundColor',[0 0 1],'callback', @CallBack_signal_processing); + hMenuOther_ge2sn = uimenu(hMenuOther,'label','ge2sn','ForegroundColor',[0 0 1],'callback', @CallBack_ge2sn); +end + +figurecm = uicontextmenu; +uimenu(figurecm,'label','Red','callback','set(gcf,''color'',''r'')'); +uimenu(figurecm,'label','White','callback','set(gcf,''color'',''w'')'); +uimenu(figurecm,'label','Gray','callback','set(gcf,''color'',[0.925, 0.914, 0.847])'); +%set(handles.figure,'uicontextmenu',figurecm); +set(handles.figure,'WindowButtonDownFcn',@figureMouseUpFcn); +set(handles.figure,'KeyPressFcn',@KeyPressFcn); + +set(handles.figure,'visible','on'); + +% save pre-set values +handles.system = os; +handles.spmdir = spmdir; +handles.screenResolution = screenResolution; +handles.pValue = pValue; +handles.intensityThreshold = intensityThreshold; +handles.clusterSizeThreshold = clusterSizeThreshold; +handles.sectionViewPosition = sectionViewPosition; +handles.sectionViewTargetFile = getSectionViewTargetFile(spmdir, 'avg152T1'); + +guidata(f, handles); + +% global variables for rotation matrix M and dimension +global M_; +global DIM_; +global TR_; +global LEFTRIGHTFLIP_; +global TMAX_; % colorbar max to display in section view +global XJVIEWURL_; + +M_ = M; +DIM_ = DIM; +TR_ = TR; +LEFTRIGHTFLIP_ = leftrightflip; +TMAX_ = 'auto'; +XJVIEWURL_ = XJVIEWURL; + +% check input arguments +if length(varargin) == 0 + []; +elseif isstr(varargin{1}) + CallBack_loadImagePush(handles.loadImagePush, [], varargin); +else + mniCoord = varargin{1}; + if length(varargin) < 2 + intensity = ones(size(mniCoord,1),1); + else + intensity = varargin{2}; + end + thisStruct.mni = mniCoord; + thisStruct.intensity = intensity; + thisStruct.M = M; + thisStruct.DIM = DIM'; + CallBack_loadImagePush(handles.loadImagePush, [], thisStruct); +end + + + +function test(hObject, eventdata) +handles = guidata(gcbo); +set(hObject, 'String', num2str(handles.pValue)); +vars = evalin('base','who'); +vars +x = evalin('base',vars{1}); +x +handles.DIM + +function CallBack_getCurrentPosition(hObject, eventdata) +handles = guidata(hObject); +disp(handles.currentxyz) + + +function KeyPressFcn(src,evt) +handles = guidata(src); +m = handles.M{1}; +m = abs(diag(m)); +if(strcmp(evt.Key, 'leftarrow')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(1) = xyz(1)-m(1); + spm_XYZreg('SetCoords', xyz, handles.hReg); +elseif(strcmp(evt.Key, 'rightarrow')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(1) = xyz(1)+m(1); + spm_XYZreg('SetCoords', xyz, handles.hReg); +elseif(strcmp(evt.Key, 'pageup')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(2) = xyz(2)+m(2); + spm_XYZreg('SetCoords', xyz, handles.hReg); +elseif(strcmp(evt.Key, 'pagedown')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(2) = xyz(2)-m(2); + spm_XYZreg('SetCoords', xyz, handles.hReg); +elseif(strcmp(evt.Key, 'uparrow')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(3) = xyz(3)+m(3); + spm_XYZreg('SetCoords', xyz, handles.hReg); +elseif(strcmp(evt.Key, 'downarrow')) + xyz = spm_XYZreg('GetCoords',handles.hReg); + xyz(3) = xyz(3)-m(3); + spm_XYZreg('SetCoords', xyz, handles.hReg); +end + + +function refreshFeeds(hObject, eventdata) +handles = guidata(hObject); +s = urlread(['http://www.alivelearn.net/xjview8/getFeed.php']); +[feeds, links]=strread(s,'%s%s', 'delimiter','\t'); +set(handles.feed, 'String', feeds); +set(handles.feed, 'userdata', links); + + +function openURL(hObject, eventdata) +handles = guidata(hObject); +value = get(handles.feed,'value'); +urls = get(handles.feed,'userdata'); +if(~isempty(urls{value})) + web(urls{value}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% NIRS-SPM +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_nirs_spm(hObject, eventdata) +try + nirs_spm; +catch + disp('Please add NIRS-SPM path.'); + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% NIRS-TOPO +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_nirs_topo(hObject, eventdata) +try + warndlg('You need to run xTopo in command line. Type topo and press enter.'); +catch + disp('Please add NIRS-SPM path.'); + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% NIRS +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_nirs(hObject, eventdata) +try + nirs; +catch + disp('Please add NIRS-SPM path.'); + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% NIRS +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_signal_processing(hObject, eventdata) +try + signalPreprocess; +catch + disp('Please add NIRS-SPM path.'); + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% NIRS +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_ge2sn(hObject, eventdata) +try + xge2sn; +catch + disp('Please add NIRS-SPM path.'); + return +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdrEdit(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'FDR can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.fdrEdit,'String'); +q = str2num(q); +if get(handles.allIntensityRadio, 'Value') + set(handles.infoTextBox, 'string', {'FDR only works on positive or negative direction, not both.'}); + return; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end + +VspmSv = spm_vol(handles.imageFileName{1}); +Ts = spm_read_vols(VspmSv); +Ts(Ts==0) = []; +Ts(isnan(Ts)) = []; +Ts = positive*Ts; +Ts = sort(Ts(:)); +if handles.TF{1} ~= 'P', Ts = flipud(Ts); end + +ps = t2p(Ts, handles.df{1}, handles.TF{1}); + +intensity = spm_uc_FDR(q, [1 handles.df{1}],handles.TF{1},1,ps,0); + +pvalue = t2p(intensity, handles.df{1}, handles.TF{1}); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); +%pause(1) +%CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% set(handles.intensityThresholdEdit,'string',intensity); +% pause(2) +% CallBack_intensityThresholdEdit(handles.intensityThresholdEdit, +% eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdrPush(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); +if get(handles.allIntensityRadio, 'Value') + set(handles.infoTextBox, 'string', {'FDR only works on positive or negative direction, not both.'}); + return; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end + +VspmSv = spm_vol(handles.imageFileName{1}); +Ts = spm_read_vols(VspmSv); +Ts(Ts==0) = []; +Ts(isnan(Ts)) = []; +Ts = positive*Ts; +Ts = sort(Ts(:)); +if handles.TF{1} ~= 'P', Ts = flipud(Ts); end + +ps = t2p(Ts, handles.df{1}, handles.TF{1}); + +intensity = spm_uc_FDR(q, [1 handles.df{1}],handles.TF{1},1,ps,0); + +pvalue = t2p(intensity, handles.df{1}, handles.TF{1}); +set(handles.pValueEdit,'string',pvalue); +%CallBack_pValueEdit(handles.pValueEdit, eventdata); +pause(1) +%CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% set(handles.intensityThresholdEdit,'string',intensity); +% pause(2) +% CallBack_intensityThresholdEdit(handles.intensityThresholdEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdr(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); +if get(handles.allIntensityRadio, 'Value') + positive = 1; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end +xjviewpath = fileparts(which('xjview')); +maskImageFile = fullfile(xjviewpath, 'mask.img'); +[threshold, pvalue] = fdr(handles.imageFileName{1}, q, positive, maskImageFile); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% model comparison +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_modelComparison(hObject, eventdata) +answer = getVariable({'y','x (full model)', 'x (reduced model)'}); + +if isempty(answer) + return; +end + +if ~isempty(answer{1}) + y = evalin('base',answer{1}); +else + return; +end +if ~isempty(answer{2}) + xf = evalin('base',answer{2}); % full model +else + return; +end +if ~isempty(answer{3}) + xr = evalin('base',answer{3}); % reduced model +else + xr = []; +end + +% make vector column vector +[r, c] = size(y); +if r==1; y = y'; end +[r, c] = size(xf); +if r mn + hmmin = mn; + end + if hmmax < mx + hmmax = mx; + end + end + end + + tmp = load(deblank(Pe(ii,:))); + tmp2 = fieldnames(tmp); + hm = eval(['tmp.' tmp2{1}]); + hmcell = struct2cell(hm); + hmname = fieldnames(hm); + for jj=1:length(hmname) + toplot1 = []; + toplot2 = []; + for mm = 1:length(hmcell{jj}) + toplot1 = [toplot1 hmcell{jj}(mm) hmcell{jj}(mm) nan]; + toplot2 = [toplot2 hmmin hmmax nan]; + end + plot(toplot1, toplot2, 'color', colors(jj,:)); + %ylim([0 4]) + hold on + end + legend(hmname) + title(['subject ' num2str(ii)]) + xlabel('time in s'); + + if ~isempty(P) % if there is head movement data, gsr data, eye tracking data, physio data etc + for jj=1:length(Ohmname) + plot(TRs(jj)*[0:length(Ohmcell{jj})-1],Ohmcell{jj},'color', colors(jj,:)); + hold on + end + legend([hmname; Ohmname]) + end + + %% prepare interval data for later plot + alltimes{ii} = []; + for jj=1:length(hmname) + alltimes{ii} = union(alltimes{ii}, hmcell{jj}); + end + + subplot(4,2,2*kk) + for jj=1:length(hmname) + roundhmcell{jj} = round(hmcell{jj}*1); + signal = zeros(1, max(roundhmcell{jj})+1); + signal(roundhmcell{jj}+1) = 1; + signal = signal - mean(signal); + y = fft(signal); + plotlength = round(length(y))/1; + plot([1:plotlength]/plotlength, abs(y(1:plotlength)).^2, 'color', colors(jj,:)); + hold on + end + legend(hmname) + xlabel('frequency'); + ylabel('fft power'); + title(['subject ' num2str(ii)]) + + if mod(ii,4) == 0 && ii~=size(Pe, 1) + figure; + Maximize(gcf); + end + end + + %% now I plot correlogram of intervals + figure; + kk = 1; + for ii=whichtoplot + alltimes{ii} = sort(alltimes{ii}); + intervals = diff(alltimes{ii}); + corrlag(intervals,intervals,[max(-10, -length(intervals)+2) : min(10, length(intervals)-2)], colors(ii,:)); + hold on; + legendname{kk} = ['sub ' num2str(ii)]; + kk = kk+1; + end + legend(legendname) + xlabel('lag'); + ylabel('correlation coefficient'); + title('correlogram of intervals') +end + +%% correlator + +if ~isempty(Pc) + + tmp = load(deblank(Pc(1,:))); + tmp2 = fieldnames(tmp); + hm = eval(['tmp.' tmp2{1}]); + + C = hm; + cenames = fields(C); + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [];']); + end + end + + %list all plot names in command window for selection + promt{1} = 'Please select which two correlators do you want to plot. The first one will be x and the second will be y. The two have to be of the same length.'; + promt{2} = 'index event correlator'; + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + promt{count+2} = sprintf('%d %s %s', count, cenames{jj}, correlatornames{jj}{kk}); + count = count + 1; + end + end + promt{count+2} = ''; + + if count == 1 + return + end + promt = char(promt); + name='Please select which two correlator do you want to plot. The first one will be x and the second will be y.'; + numlines=1; + if count == 1 + defaultanswer={['You don''t have more than one correlators. Click Cancel']}; + else + defaultanswer={['[1 ' num2str(count-1) ']']}; + end + + whichplot=inputdlg(promt,name,numlines,defaultanswer); + if isempty(whichplot) + return; + end + whichplot = eval(whichplot{1}); + + figure; + Maximize(gcf); + for ii=whichtoplot + tmp = load(deblank(Pc(ii,:))); + tmp2 = fieldnames(tmp); + hm = eval(['tmp.' tmp2{1}]); + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + tmp2 = eval(['hm.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + if size(tmp2,1) == 1 + tmp2 = tmp2'; + end + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [C.' cenames{jj} '.' correlatornames{jj}{kk} '; tmp2];']); + + if whichplot(1) == count + x = tmp2; + xlabeltext = [correlatornames{jj}{kk} ' at ' cenames{jj}]; + end + if whichplot(2) == count + y = tmp2; + ylabeltext = [correlatornames{jj}{kk} ' at ' cenames{jj}]; + end + count = count + 1; + end + end + + kk = mod(ii,16); + if kk == 0 + kk = 16; + end + subplot(4,4,kk) + + plot2(x,y, 'b', 1); + xlabel(xlabeltext) + ylabel(ylabeltext) + title(['subject ' num2str(ii)]) + try + % convert to colum vector + if size(x,1)==1 + x = x'; + end + if size(y,1)==1 + y = y'; + end + + % remove NaN + tmpposx = find(isnan(x) | isinf(x)); + tmpposy = find(isnan(y) | isinf(y)); + x([tmpposx; tmpposy]) = []; + y([tmpposx; tmpposy]) = []; + + b = linearregression(y,x); + + totalvar = var(y); + residvar = var(y - x*b(1) - b(2)); + modelvar = totalvar - residvar; + dfm = 1; + dft = length(x) - 1; + dfr = dft - dfm; + mmodelvar = modelvar/dfm; + mresidvar = residvar/dfr; + F = mmodelvar/mresidvar; + pvalue = 1-spm_Fcdf(F, [dfm dfr]); + + title(sprintf('sub %d, pValue=%g', ii, pvalue)) + xx=[min(x):(max(x)-min(x))/10:max(x)]; + yy=b(1) * xx + b(2); + hold on; + plot(xx,yy,'g'); + end + + if mod(ii,16) == 0 && ii~=size(Pc, 1) + figure; + Maximize(gcf); + end + end + + % plot the average + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + if whichplot(1) == count + eval(['x = C.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + xlabeltext = [correlatornames{jj}{kk} ' at ' cenames{jj}]; + end + if whichplot(2) == count + eval(['y = C.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + ylabeltext = [correlatornames{jj}{kk} ' at ' cenames{jj}]; + end + count = count + 1; + end + end + + figure + plot2(x,y, 'b', 1); + xlabel(xlabeltext) + ylabel(ylabeltext) + try + % convert to colum vector + if size(x,1)==1 + x = x'; + end + if size(y,1)==1 + y = y'; + end + + % remove NaN + tmpposx = find(isnan(x) | isinf(x)); + tmpposy = find(isnan(y) | isinf(y)); + x([tmpposx; tmpposy]) = []; + y([tmpposx; tmpposy]) = []; + + b = linearregression(y,x); + + totalvar = var(y); + residvar = var(y - x*b(1) - b(2)); + modelvar = totalvar - residvar; + dfm = 1; + dft = length(x) - 1; + dfr = dft - dfm; + mmodelvar = modelvar/dfm; + mresidvar = residvar/dfr; + F = mmodelvar/mresidvar; + pvalue = 1-spm_Fcdf(F, [dfm dfr]); + + title(sprintf('pValue=%g; slope=%g; constant=%g', pvalue, b(1), b(2))) + xx=[min(x):(max(x)-min(x))/10:max(x)]; + yy=b(1) * xx + b(2); + hold on; + plot(xx,yy,'g'); + end +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% head motion, physio, gsr, eyetracking etc analysis +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_headMovementAnalysis(hObject, eventdata) + +global TR_; +handles = guidata(hObject); + +answer = getVariable({'head motion, gsr, physio, eye tracking data', 'Event time data', 'Correlator (optional)'}); + +if isempty(answer) + return; +end +if isempty(answer{1}) + return; +end + +[filename, pathname] = uiputfile('*.mat', 'Save result to', ''); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +P = evalin('base',answer{1}); % data +try + E = evalin('base',answer{2}); % event +catch + E = []; +end +try + C = evalin('base',answer{3}); % correlator +catch + C = []; +end + +% read what data in there from the 1st dataset +tmp = load(deblank(P(1,:))); +tmp1 = fields(tmp); +eval(['M = tmp.' tmp1{1} ';']); +dataNames = fields(M); + +% prompt for TR (s) +promt = dataNames; +defaultanswer = repmat({num2str(TR_)}, 1, length(dataNames)); +name='Sampling interval (TR) in seconds'; +options.Resize = 'on'; +TRs=inputdlg(promt,name,1,defaultanswer, options); +if isempty(TRs); + return; +end +TRs = str2double(TRs); + +% % prompt for Moving Average Detrend window size (s) +% promt = dataNames; +% defaultanswer = repmat({num2str(40)}, 1, length(dataNames)); +% name='Moving average detrending window size in seconds'; +% options.Resize = 'on'; +% MWs=inputdlg(promt,name,1,defaultanswer, options); +% if isempty(MWs); +% return; +% end +% MWs = str2double(MWs); +% MWs = MWs./TRs; + +h = waitbar(0,'Please wait...'); + +for nn=1:length(dataNames) + + for ii=1:size(P,1) + tmp = load(deblank(P(ii,:))); + tmp1 = fields(tmp); + eval(['Ms = tmp.' tmp1{1} ';']); + eval(['M = Ms.' dataNames{nn} ';']); + if isnumeric(M) + M = double(M); + end + if ~isempty(E) + tmp = load(deblank(E(ii,:))); + tmp1 = fields(tmp); + eval(['event{ii} = tmp.' tmp1{1} ';']); + if ~isstruct(event{ii}) + error('I need you specify the event in a structure, not a cell array!'); + return + end + else + event = {}; + end + + [eventResponse{ii}, time{ii}, wholeOriginal{ii}] = cuixuSignalRetrieve(M, event{ii}, 50, -20, 0, TRs(nn)); + + if ~isempty(C) + tmp = load(deblank(C(ii,:))); + tmp1 = fields(tmp); + eval(['correlator{ii} = tmp.' tmp1{1} ';']); + if ~isstruct(correlator{ii}) + error('I need you specify the correlator in a structure, not a cell array!'); + return + end + + names = fields(correlator{ii}); + for kk=1:length(names) + eval(['names2 = fields(correlator{ii}.' names{kk} ');']); + for mm=1:length(names2) + eval(['correlator{ii}.' names{kk} '.' names2{mm} ' = correlator{ii}.' names{kk} '.' names2{mm} '(remainedEvent{ii}.' names{kk} ');']);; + end + end + end + waitbar(ii/size(P,1),h,[dataNames{nn} ': finished ' num2str(ii) ' of ' num2str(size(P,1))]); + disp(['finished ' num2str(ii) ' of ' num2str(size(P,1))]); + end + + + if ~exist('correlator') + correlator = {}; + end + + TR = TRs(nn); + [a,b,c] = fileparts(thisfilename); + save([fullfile(a,b) '_' dataNames{nn}], 'eventResponse', 'time', 'wholeOriginal', 'correlator', 'event', 'P', 'TR'); +end +close(h) + +%CallBack_plotROI(hObject, eventdata, thisfilename); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% contrast +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_contrast(hObject, eventdata) + +answer = getVariable({'beta files', 'contrast vector'}); + +if isempty(answer) + return; +end +if isempty(answer{1}) | isempty(answer{2}) + return; +end + +[filename, pathname] = uiputfile('*.img', 'Save t-test image as', ''); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +P1 = evalin('base',answer{1}); % beta image files +c = evalin('base',answer{2}); % contrast vector + +if iscell(P1) + []; +else + disp('format wrong'); + return; +end + + +h = waitbar(0,'Please wait...'); +V=spm_vol(deblank(P1{1}(1,:))); +M1={spm_read_vols(V)}; +contr = zeros(size(M1{1},1), size(M1{1},2), size(M1{1},3), size(P1{1},1)); + +for ii=1:size(P1{1},1) + for jj=1:length(P1) + if c(jj)~=0 + V=spm_vol(deblank(P1{jj}(ii,:))); + M1{jj}=spm_read_vols(V); + contr(:,:,:,ii) = contr(:,:,:,ii)+c(jj)*double(M1{jj}); + end + end + + waitbar(ii/size(P1{1},1),h,['finished ' num2str(ii) ' of ' num2str(size(P1{1},1))]); +end +close(h); + + +df = size(P1{1},1)-1; + +T = squeeze(t(permute(contr,[4 1 2 3]))); % return a 41*48*35 matrix +xjviewpath = fileparts(which('xjview')); +V=spm_vol(fullfile(xjviewpath, 'mask.img')); +m=spm_read_vols(V); +T = T.*m; + +targetfilename = thisfilename; +global M_; +global DIM_; +V.mat = M_; +V.dim = [DIM_(1) DIM_(2) DIM_(3) 16]; +V.fname = targetfilename; +V.descrip = ['SPM{T_[' num2str(df) '.0]} ' num2str(c)]; +V = spm_write_vol(V,T); + +handles = guidata(hObject); +[tmp,tmp,ext] = fileparts(thisfilename); +if isempty(ext) + ext = '.img'; +elseif isequal(lower(ext), '.img') + ext = ''; +end +CallBack_loadImagePush(handles.loadImagePush, [], {[thisfilename ext]}); + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% SPM process (use SPM processing) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_SPMProcess(hObject, eventdata, singleOrCluster) + +answer = getVariable({'Image files', 'Event time data', 'Modulator (optional)','Other (head motion, gsr, physio, eye track, etc, optional)'}); + +if isempty(answer) + return; +end +if isempty(answer{1}) | isempty(answer{2}) + return; +end + +P = evalin('base',answer{1}); % subject directories +E = evalin('base',answer{2}); % event time +try + Modulator = evalin('base',answer{3}); % modulator +catch + Modulator = []; +end +try + headmovement = evalin('base',answer{4}); % other regressor such as headmovement +catch + headmovement = []; +end + +if nargin < 3 + singleOrCluster = 'single'; +end + + +prompt='I will create a folder under each subject''s directory and put the SPM output files (including beta images, SPM.mat etc) for that subject into that folder. Please give a name to the folder (example: FixedEffect). No space or strange characters allowed.'; +name='Give a name to SPM output folder'; +numlines=1; +defaultanswer={'FixedEffect'}; + +wheretosave=inputdlg(prompt,name,numlines,defaultanswer); + +if isempty(wheretosave) + return +else + wheretosave = wheretosave{1}; +end + +currentdir = pwd; + +if strcmp(singleOrCluster, 'cluster') + handles = guidata(hObject); + set(handles.infoTextBox, 'string', {'This will do SPM GLM estimation using cluster.', 'Check out xjviewtmp directory'}); + + mkdir('xjviewtmp'); + cd('xjviewtmp'); + system('rm *'); + + fid = fopen('processALL.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'for ((s=1;s<=%d;s++))\n', size(P,1)); + fprintf(fid,'do\n\tsleep 3.5\n\tqsub %s/process.pbs -v "s=$s" -N SPM_$s\ndone\n', pwd); + fclose(fid); + + save P P; + save E E; + save Modulator Modulator; + save headmovement headmovement; + fid = fopen('process.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'#PBS -l nodes=1:ppn=1,walltime=04:00:00\n'); + fprintf(fid,'#PBS -N process\n'); + fprintf(fid,'#PBS -e %s\n', pwd); + fprintf(fid,'#PBS -o %s\n\n', pwd); + fprintf(fid,'sleep 3.5\n\n'); + fprintf(fid,'PATH=/usr/local/bin:$PATH\n\n'); + fprintf(fid,'matlab -nojvm -nodisplay \\\n'); + fprintf(fid,'-logfile "%s/process.$s.$PBS_JOBID.log" \\\n', pwd); + + + fprintf(fid,['-r "addpath ~/gang/xjview;'... + 'wheretosave = ''%s'';'... + 'cd %s; '... + 'load P; '... + 'load E; '... + 'load Modulator;'... + 'load headmovement;'... + 'tmp=load(deblank(P($s,:)));'... + 'fd=fields(tmp);'... + 'eval([''Pi=tmp.'' fd{1} '';'']);'... + 'N = size(Pi,1);'... + 'tmp=load(deblank(E($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''EE=tmp.'' fd{1} '';'']); '... + 'thisModulator = [];'... + 'if ~isempty(Modulator);'... + 'tmp = load(deblank(Modulator($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''thisModulator=tmp.'' fd{1} '';'']);'... + 'end;'... + '[otherregressor{1}.C, otherregressor{1}.name]=struct2matrix(N, EE, thisModulator);'... + 'if ~isempty(headmovement);'... + 'tmp = load(deblank(headmovement($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''thisheadmovement=tmp.'' fd{1} '';'']);'... + 'tmphd = struct2cell(thisheadmovement);'... + 'tmpname = fieldnames(thisheadmovement);'... + 'for kk=1:length(tmphd);'... + '[r,c] = size(tmphd{kk});'... + 'if r==1; tmphd{kk} = tmphd{kk}''; end;'... + 'otherregressor{1}.C = [otherregressor{1}.C tmphd{kk}];'... + 'otherregressor{1}.name = [otherregressor{1}.name {tmpname{kk}}];'... + 'end;'... + 'end;'... + 'subDir = fileparts(deblank(Pi(1,:))); '... + 'for kk=1:length(subDir); '... + 'if subDir(end-kk+1)==filesep;'... + 'pos=kk;'... + 'break;'... + 'end;'... + 'end; '... + 'subDir(end-pos+1:end)=[]; '... + 'cd(subDir); '... + 'try;' ... + 'rmdir(wheretosave, ''s'');'... + 'end;'... + 'mkdir(wheretosave);'... + 'cd(wheretosave);'... + 'spm_defaults;'... + 'disp(subDir);'... + 'cuixuprocess(N, [0], {}, {}, {}, [], otherregressor, Pi, 16);'... + 'disp(''done!'');'... + 'exit;"'], wheretosave, pwd); + + fclose(fid); + + system(['ssh cluster.hnl.bcm.tmc.edu PATH=$PATH:/usr/local/pbs/i686/bin bash ' pwd '/processALL.pbs']); + cd .. +elseif strcmp(singleOrCluster, 'single') + handles = guidata(hObject); + set(handles.infoTextBox, 'string', {'This will do SPM GLM estimation.'}); + for ii=1:size(P,1) + tmp=load(deblank(P(ii,:))); + fd=fields(tmp); + eval(['Pi=tmp.' fd{1} ';']); + N = size(Pi,1); + tmp=load(deblank(E(ii,:))); + fd=fields(tmp); + eval(['EE=tmp.' fd{1} ';']); + thisModulator = []; + if ~isempty(Modulator) + tmp = load(deblank(Modulator(ii,:))); + fd=fields(tmp); + eval(['thisModulator=tmp.' fd{1} ';']); + end + [otherregressor{1}.C, otherregressor{1}.name]=struct2matrix(N, EE, thisModulator); + if ~isempty(headmovement) + tmp = load(deblank(headmovement(ii,:))); + fd=fields(tmp); + eval(['thisheadmovement=tmp.' fd{1} ';']); + + tmphd = struct2cell(thisheadmovement); + tmpname = fieldnames(thisheadmovement); + for kk=1:length(tmphd) + [r,c] = size(tmphd{kk}); + if r==1; tmphd{kk} = tmphd{kk}'; end + otherregressor{1}.C = [otherregressor{1}.C tmphd{kk}]; + otherregressor{1}.name = [otherregressor{1}.name {tmpname{kk}}]; + end + end + subDir = fileparts(deblank(Pi(1,:))); + for kk=1:length(subDir); + if subDir(end-kk+1)==filesep; + pos=kk; + break; + end; + end; + subDir(end-pos+1:end)=[]; + cd(subDir); + try + rmdir(wheretosave, 's'); + end + mkdir(wheretosave); + cd(wheretosave); + + spm_defaults; + disp(subDir); + cuixuprocess(N, [0], {}, {}, {}, [], otherregressor, Pi, 16); + + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {['SPM Processing subject ' num2str(ii) ' / ' num2str(size(P,1)) ' ...']}]); + disp(['----finished ' num2str(ii) ' out of ' num2str(size(P,1)) ' subjects----']); + end + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {'Done!'}]); +end + +cd(currentdir) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% GLMPeak (only do regression on peak BOLD +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_GLMPeak(hObject, eventdata, singleOrCluster) + +answer = getVariable({'Image data', 'Event time data', 'Modulator'}); + +if isempty(answer) + return; +end +if isempty(answer{1}) | isempty(answer{2}) | isempty(answer{3}) + return; +end + +directoryname = uigetdir(pwd, 'Pick a Directory to Save Your Beta Files...'); +if isequal(directoryname, 0) + return; +end + +peakpoint = inputdlg({'What points in time do you considered as peak BOLD?'}, 'Peak point',1,{'[4 6]'}); +if isempty(peakpoint); return; end +peakpointstr = peakpoint{1}; +peakpoint = str2num(peakpoint{1}); + + +P = evalin('base',answer{1}); % subject directories +E = evalin('base',answer{2}); % event time +Modulator = evalin('base',answer{3}); % modulator + + +if nargin < 3 + singleOrCluster = 'single'; +end + +if strcmp(singleOrCluster, 'cluster') + mkdir('xjviewtmp'); + cd('xjviewtmp'); + system('rm *'); + + fid = fopen('processALL.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'for ((s=1;s<=%d;s++))\n', size(P,1)); + fprintf(fid,'do\n\tsleep 3.5\n\tqsub %s/process.pbs -v "s=$s" -N pro_$s\ndone\n', pwd); + fclose(fid); + + save P P; + save E E; + save Modulator Modulator; + fid = fopen('process.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'#PBS -l nodes=1:ppn=1,walltime=08:00:00\n'); + fprintf(fid,'#PBS -N process\n'); + fprintf(fid,'#PBS -e %s\n', pwd); + fprintf(fid,'#PBS -o %s\n\n', pwd); + fprintf(fid,'sleep 3.5\n\n'); + fprintf(fid,'PATH=/usr/local/bin:$PATH\n\n'); + fprintf(fid,'matlab -nojvm -nodisplay \\\n'); + fprintf(fid,'-logfile "%s/process.$s.$PBS_JOBID.log" \\\n', pwd); + + fprintf(fid,['-r "addpath ~/gang/xjview; '... + 'cd %s; '... + 'load P; '... + 'load E; '... + 'load Modulator; '... + 'tmp=load(deblank(P($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''SS=tmp.'' fd{1} '';'']); '... + 'tmp=load(deblank(E($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''EE=tmp.'' fd{1} '';'']); '... + 'tmp = load(deblank(Modulator($s,:))); fd=fields(tmp); eval([''MM=tmp.'' fd{1} '';'']);'... + 'names = fieldnames(EE);'... + 'for jj=1:length(names);'... + 'eval([''MM.'' names{jj} ''.time = EE.'' names{jj} '';'']);'... + 'end;'... + 'xjviewpath = fileparts(which(''xjview''));'... + 'cuixuGLMpeak(MM, SS, ''%s'', [''subject'' num2str($s)], fullfile(xjviewpath, ''mask.img''), %s, 100, 2, fullfile(xjviewpath, ''templateFile.img''));'... + 'exit;"'], pwd, directoryname, peakpointstr); + + fclose(fid); + + system(['ssh cluster.hnl.bcm.tmc.edu PATH=$PATH:/usr/local/pbs/i686/bin bash ' pwd '/processALL.pbs']); + cd .. +elseif strcmp(singleOrCluster, 'single') + xjviewpath = fileparts(which('xjview')); + handles = guidata(hObject); + set(handles.infoTextBox, 'string', {'This will do simple GLM estimation on peak BOLD.'}); + for ii = 1:size(P,1) + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {['Processing subject ' num2str(ii) ' / ' num2str(size(P,1)) ' ...']}]); + tmp=load(deblank(P(ii,:))); + fd=fields(tmp); + eval(['SS=tmp.' fd{1} ';']); + tmp=load(deblank(E(ii,:))); + fd=fields(tmp); + eval(['EE=tmp.' fd{1} ';']); + tmp=load(deblank(Modulator(ii,:))); + fd=fields(tmp); + eval(['MM=tmp.' fd{1} ';']); + % convert Modulator and E to be recognized by cuixuGLMpeak + names = fieldnames(EE); + for jj=1:length(names) + eval(['MM.' names{jj} '.time = EE.' names{jj} ';']); + end + cuixuGLMpeak(MM, SS, directoryname, ['subject' num2str(ii)], fullfile(xjviewpath, 'mask.img'), peakpoint, 100, 2, fullfile(xjviewpath, 'templateFile.img')); + disp(['----finished ' num2str(ii) ' out of ' num2str(size(P,1)) ' subjects----']); + end + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {'Done!'}]); +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% process (use my own process code, cuixuAGLM, estimation on detrended relative BOLD) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_process(hObject, eventdata, singleOrCluster) + +answer = getVariable({'Image data', 'Event time data', 'Modulator'}); + +if isempty(answer) + return; +end +if isempty(answer{1}) | isempty(answer{2}) + return; +end + +directoryname = uigetdir(pwd, 'Pick a Directory to Save Your Beta Files...'); +if isequal(directoryname, 0) + return; +end + +P = evalin('base',answer{1}); % subject directories +E = evalin('base',answer{2}); % event time +try + Modulator = evalin('base',answer{3}); % modulator +catch + Modulator = []; +end + + +if nargin < 3 + singleOrCluster = 'single'; +end + +if strcmp(singleOrCluster, 'cluster') + mkdir('xjviewtmp'); + cd('xjviewtmp'); + system('rm *'); + + fid = fopen('processALL.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'for ((s=1;s<=%d;s++))\n', size(P,1)); + fprintf(fid,'do\n\tsleep 3.5\n\tqsub %s/process.pbs -v "s=$s" -N pro_$s\ndone\n', pwd); + fclose(fid); + + save P P; + save E E; + save Modulator Modulator; + fid = fopen('process.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'#PBS -l nodes=1:ppn=1,walltime=08:00:00\n'); + fprintf(fid,'#PBS -N process\n'); + fprintf(fid,'#PBS -e %s\n', pwd); + fprintf(fid,'#PBS -o %s\n\n', pwd); + fprintf(fid,'sleep 3.5\n\n'); + fprintf(fid,'PATH=/usr/local/bin:$PATH\n\n'); + fprintf(fid,'matlab -nojvm -nodisplay \\\n'); + fprintf(fid,'-logfile "%s/process.$s.$PBS_JOBID.log" \\\n', pwd); + + fprintf(fid,['-r "addpath ~/gang/xjview; '... + 'cd %s; '... + 'load P; '... + 'load E; '... + 'load Modulator; '... + 'tmp=load(deblank(P($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''M=tmp.'' fd{1} '';'']); '... + 'if isnumeric(M); M=double(M); elseif isstr(M); V=spm_vol(M); M =spm_read_vols(V); else; error(''I don not understand the fileformat''); end;' ... + 'tmp=load(deblank(E($s,:))); '... + 'fd=fields(tmp); '... + 'eval([''EE=tmp.'' fd{1} '';'']); '... + 'if ~isempty(Modulator); tmp = load(deblank(Modulator($s,:))); fd=fields(tmp); eval([''thisModulator=tmp.'' fd{1} '';'']); else; thisModulator=[]; end;'... + 'M = permute(M,[4 1 2 3]); '... + '[tmp,tmp,M]=mAveDetrend(M,100); '... + 'M = permute(M,[2 3 4 1]); '... + '[a,b,c]=fileparts(deblank(P($s,:)));'... + 'cuixuAGLM(M,EE,{''%s'', b}, thisModulator); '... + 'exit;"'], pwd, directoryname); + + fclose(fid); + + system(['ssh cluster.hnl.bcm.tmc.edu PATH=$PATH:/usr/local/pbs/i686/bin bash ' pwd '/processALL.pbs']); + cd .. +elseif strcmp(singleOrCluster, 'single') + handles = guidata(hObject); + set(handles.infoTextBox, 'string', {'This will do simple GLM estimation.'}); + for ii=1:size(P,1) + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {['Processing subject ' num2str(ii) ' / ' num2str(size(P,1)) ' ...']}]); + tmp=load(deblank(P(ii,:))); + fd=fields(tmp); + eval(['M=tmp.' fd{1} ';']); + if isnumeric(M); M=double(M); elseif isstr(M); V=spm_vol(M); M =spm_read_vols(V); else; error('I don''t understand the fileformat'); end; + tmp=load(deblank(E(ii,:))); + fd=fields(tmp); + eval(['EE=tmp.' fd{1} ';']); + if ~isempty(Modulator); tmp = load(deblank(Modulator(ii,:))); fd=fields(tmp); eval(['thisModulator=tmp.' fd{1} ';']); else; thisModulator=[]; end; + M = permute(M,[4 1 2 3]); + [tmp,tmp,M]=mAveDetrend(M,100); + M = permute(M,[2 3 4 1]); + [a,b,c]=fileparts(deblank(P(ii,:))); + cuixuAGLM(M,EE,{directoryname, b}, thisModulator); + disp(['----finished ' num2str(ii) ' out of ' num2str(size(P,1)) ' subjects----']); + end + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {'Done!'}]); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% convert new data format to old +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_new2old(hObject, eventdata) +answer = getVariable({'subjects directories'}); +if isempty(answer) + return; +end +if isempty(answer{1}) + return; +end +P = evalin('base',answer{1}); % subject directories +new2old(P); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pre-process_cibsr +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_preprocess_cibsr(hObject, eventdata) +answer = getVariable({'subjects directories'}); +if isempty(answer) + return; +end +if isempty(answer{1}) + return; +end +P = evalin('base',answer{1}); % subject directories + +warndlg('You need to addpath ml7spm2devel2') + +cuixuPreprocessCIBSR(P); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pre-process +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_preprocess(hObject, eventdata, singleOrCluster) +answer = getVariable({'subjects directories'}); +if isempty(answer) + return; +end +if isempty(answer{1}) + return; +end +P = evalin('base',answer{1}); % subject directories + +if nargin < 3 + singleOrCluster = 'single'; +end + +if strcmp(singleOrCluster, 'cluster') + mkdir('xjviewtmp'); + cd('xjviewtmp'); + system('rm *'); + + fid = fopen('preprocessALL.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'for ((s=1;s<=%d;s++))\n', size(P,1)); + fprintf(fid,'do\n\tsleep 3.5\n\tqsub %s/preprocess.pbs -v "s=$s" -N pre_$s\ndone\n', pwd); + fclose(fid); + + save P P; + fid = fopen('preprocess.pbs','wt'); + fprintf(fid,'#!/bin/bash\n\n'); + fprintf(fid,'#PBS -l nodes=1:ppn=1,walltime=08:00:00\n'); + fprintf(fid,'#PBS -N preprocess\n'); + fprintf(fid,'#PBS -e %s\n', pwd); + fprintf(fid,'#PBS -o %s\n\n', pwd); + fprintf(fid,'sleep 3.5\n\n'); + fprintf(fid,'PATH=/usr/local/bin:$PATH\n\n'); + fprintf(fid,'matlab -nojvm -nodisplay \\\n'); + fprintf(fid,'-logfile "%s/preprocess.$s.$PBS_JOBID.log" \\\n', pwd); + fprintf(fid,['-r "addpath ~/gang/xjview; cd ' pwd '; load P; cuixuSmartPreprocess(P, $s);exit;"']); + fclose(fid); + + system(['ssh cluster.hnl.bcm.tmc.edu PATH=$PATH:/usr/local/pbs/i686/bin bash ' pwd '/preprocessALL.pbs']); + cd .. +elseif strcmp(singleOrCluster, 'single') + handles = guidata(hObject); + set(handles.infoTextBox, 'string', {'What will be done in preprocessing is:',... + '1. Converting DICOM files',... + '2. Re-align',... + '3. Coregister',... + '4. Slice timing',... + '5. Normalize',... + '6. Smooth','',... + 'This function creates a directory ''preprocessing'' under your homeDir and put all preprocessing files there. It also saves the head movement matrix in ''headmovement.mat''. The intermediate files are removed',''}); + for ii=1:size(P,1) + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {['Preprocessing subject ' num2str(ii) ' / ' num2str(size(P,1)) ' ...']}]); + cuixuSmartPreprocess(P, ii); + end + tmp = get(handles.infoTextBox, 'string'); + set(handles.infoTextBox, 'string', [tmp; {'Done!'}]); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% ROI: TimeSeries +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_timeSeries(hObject, eventdata) + +global TR_; +handles = guidata(hObject); +if ~isfield(handles,'currentDisplayMNI') | isempty(cell2mat(handles.currentDisplayMNI')) + %errordlg('No voxels found.','error'); + set(handles.infoTextBox, 'string', 'No voxels found.'); + beep + return; +end + +dimensionmatch = questdlg('The dimension of your mask image should be identical to the dimensions of the images where the time series are extracted. Are they identical?', ... + 'Dimension Match Question', ... + 'Yes', 'No', 'I Do Not Know', 'Yes'); + +switch dimensionmatch + case 'No', + msgbox('You should use spm reslice to change your mask image dimensions','warning'); + return; + case 'I Do Not Know', + msgbox('You should check the dimensions and use spm reslice to change your mask image dimensions','warning'); + return; +end % switch + + + +answer = getVariable({'Image data', 'Event time data', 'Correlator', 'Effects to be removed (e.g. headmovement)'}); +%answer=inputdlg('Input the name of the variable (in the base workspace) which contains the image file name list, or the 4-D data matrix. If you wish to select the image files directly, click cancel.', 'Variable Name?', 1, {'P'}); +if isempty(answer) + return; +end +if isempty(answer{1}) + return; +end + +searchContent = get(handles.searchContentEdit,'string'); +if isempty(searchContent) + searchContent = num2str(coord(1,3)); +end +searchContent = ['ROI_' searchContent]; +[filename, pathname] = uiputfile('*.mat', 'Save result to', searchContent); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +P = evalin('base',answer{1}); % data +try + E = evalin('base',answer{2}); % event +catch + E = []; +end +try + C = evalin('base',answer{3}); % correlator +catch + C = []; +end +try + headmovement = evalin('base',answer{4}); % headmovement +catch + headmovement = []; +end + +mni = cell2mat(handles.currentDisplayMNI'); +coord = mni2cor(mni, handles.M{1}); + + +if ischar(P) + h = waitbar(0,'Please wait...'); + for ii=1:size(P,1) + tmp = load(deblank(P(ii,:))); + tmp1 = fields(tmp); + eval(['M = tmp.' tmp1{1} ';']); + if isnumeric(M) + M = double(M); + end + if ~isempty(E) + tmp = load(deblank(E(ii,:))); + tmp1 = fields(tmp); + eval(['event{ii} = tmp.' tmp1{1} ';']); + if ~isstruct(event{ii}) + error('I need you specify the event in a structure, not a cell array!'); + return + end + else + event = {}; + end + + if ~isempty(headmovement) % if headmovement is present (or any other effects to be removed), then get rid of it first + H = []; + tmp = load(deblank(headmovement(ii,:))); + fd=fields(tmp); + eval(['thisheadmovement=tmp.' fd{1} ';']); + + tmphd = struct2cell(thisheadmovement); + for kk=1:length(tmphd) + [r,c] = size(tmphd{kk}); + if r==1; tmphd{kk} = tmphd{kk}'; end + H = [H tmphd{kk}]; + end + for kk=1:size(coord,1) + b = linearregression(squeeze(M(coord(kk,1), coord(kk,2), coord(kk,3), :)),H); + M(coord(kk,1), coord(kk,2), coord(kk,3), :) = squeeze(M(coord(kk,1), coord(kk,2), coord(kk,3), :)) - H*b(1:end-1); + end + end + + [eventResponse{ii}, time{ii}, wholeOriginal{ii}, wholeAbsolute{ii}, wholeBaseline{ii}, removedEvent{ii}, remainedEvent{ii}] = cuixuBOLDretrieve(M, coord, event{ii}, 50, -20, 100, 0, TR_); + + if ~isempty(C) + tmp = load(deblank(C(ii,:))); + tmp1 = fields(tmp); + eval(['correlator{ii} = tmp.' tmp1{1} ';']); + if ~isstruct(correlator{ii}) + error('I need you specify the correlator in a structure, not a cell array!'); + return + end + + names = fields(correlator{ii}); + for kk=1:length(names) + eval(['names2 = fields(correlator{ii}.' names{kk} ');']); + for mm=1:length(names2) + eval(['correlator{ii}.' names{kk} '.' names2{mm} ' = correlator{ii}.' names{kk} '.' names2{mm} '(remainedEvent{ii}.' names{kk} ');']);; + end + end + end + waitbar(ii/size(P,1),h,['finished ' num2str(ii) ' of ' num2str(size(P,1))]); + disp(['finished ' num2str(ii) ' of ' num2str(size(P,1))]); + end + close(h) +elseif isnumeric(P) % never used! + P = double(P); + if ~isempty(E) + tmp = load(deblank(E(ii,:))); + tmp1 = fields(tmp); + eval(['event{ii} = tmp.' tmp1{1} ';']); + else + event = {}; + end + [eventResponse{ii}, time{ii}, wholeOriginal{ii}, wholeAbsolute{ii}, wholeBaseline{ii}, removedEvent{ii}, remainedEvent{ii}] = cuixuBOLDretrieve(P, coord, event{ii}, 50, -20, 100, 0, TR_); +end + +if ~exist('correlator') + correlator = {}; +end + +mat = handles.M{1}; +save(thisfilename, 'eventResponse', 'time', 'wholeOriginal', 'wholeAbsolute', 'wholeBaseline', 'correlator', 'coord', 'mni', 'removedEvent','remainedEvent', 'event', 'mat', 'P', 'headmovement'); +CallBack_plotROI(hObject, eventdata, thisfilename); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% myerrorbar plot (change errorbar width) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function hE = myerrorbar(varargin) +hE = errorbar(varargin{:}); +xdata = get(hE, 'xdata'); +errorbarwidth = (xdata(2) - xdata(1))/4; +% adjust error bar width +hE_c = ... + get(hE , 'Children' ); +errorbarXData = ... + get(hE_c(2), 'XData' ); +errorbarXData(4:9:end) = ... + errorbarXData(1:9:end) - errorbarwidth; +errorbarXData(7:9:end) = .... + errorbarXData(1:9:end) - errorbarwidth; +errorbarXData(5:9:end) = ... + errorbarXData(1:9:end) + errorbarwidth; +errorbarXData(8:9:end) = ... + errorbarXData(1:9:end) + errorbarwidth; +set(hE_c(2), 'XData', errorbarXData); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% plot ROI +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_plotROI(hObject, eventdata, filename) +handles = guidata(hObject); + +if ~exist('filename') + if findstr('SPM2',spm('ver')) + P = spm_get([0:1],'*.mat','Select ROI result file'); + else %if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'mat','Select ROI result file'); + end +else + P = filename; +end + +if isempty(P) + return; +end +load(deblank(P)); + +if exist('mni') + delete(gcf) + xjview(mni); +end + + +% allow user to select which subject to plot +prompt=['I find you have ' num2str(length(eventResponse)) ' subjects. Please let me know which subjects you want to include to generate the plots.']; +name='Which subject(s) to plot?'; +numlines=1; +defaultanswer={['[1:' num2str(length(eventResponse)) ']']}; + +whichtoplot=inputdlg(prompt,name,numlines,defaultanswer); +if isempty(whichtoplot) + return; +end +whichtoplot = eval(whichtoplot{1}); + + +response = eventResponse{1}; + +eventisstruct = 0; +if isstruct(response) + eventisstruct = 1; + f = fieldnames(response); + response = struct2cell(response); +else + f = num2cell([1:length(response)]); + for ii=1:length(response) + f{ii} = num2str(f{ii}); + end +end +for jj=1:length(response) + response{jj} = []; +end + +if exist('correlator') & ~isempty(correlator) & eventisstruct==1 + C = correlator{1}; + cenames = fields(C); + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [];']); + end + end + for ii=whichtoplot%1:length(correlator) + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + tmp2 = eval(['correlator{ii}.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + if size(tmp2,1) == 1 + tmp2 = tmp2'; + end + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [C.' cenames{jj} '.' correlatornames{jj}{kk} '; tmp2];']); + end + end + end +end + +if eventisstruct == 1 + for ii=1:length(eventResponse) + for kk=1:length(f) + eval(['tmptmp{kk} = eventResponse{ii}.' f{kk} ';']); + end + eventResponse{ii} = tmptmp; + end +end + +for ii=whichtoplot%1:length(eventResponse) + for jj=1:length(eventResponse{1}) + response{jj} = [response{jj}; eventResponse{ii}{jj}]; + end +end + +if isempty(response) + msgbox('Nothing to plot'); + return +end + + + + +v = version; +figure; +%colors='rbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgy'; +colors=[1 0 0; + 0 0 1; + 0 0 0; + 1 0 1; + 0 1 1; + 0 1 0; + 1 1 0; + 1 0.5 0.5; + .5 .5 1; + .5 .5 .5; + 1 .5 0; + 1 0 .5; + 0 1 .5; + .5 1 0; + 0 .5 1; + .5 0 1]; +colors = repmat(colors, 10, 1); +thislabel = {}; +for ii=1:length(response) + if v(1)=='6' + ff = myerrorbar(time{1}, meannan(response{ii}), stdnan(response{ii})/sqrt(size(response{ii},1))); + set(ff,'color',colors(ii, :)); + thislabel = [thislabel {''} f(ii)]; + elseif v(1)=='7' + hE = myerrorbar(time{1}, meannan(response{ii}), stdnan(response{ii})/sqrt(size(response{ii},1)), 'color', colors(ii, :)); +% errorbarwidth = (time{1}(2) - time{1}(1))/4; +% % adjust error bar width +% hE_c = ... +% get(hE , 'Children' ); +% errorbarXData = ... +% get(hE_c(2), 'XData' ); +% errorbarXData(4:9:end) = ... +% errorbarXData(1:9:end) - errorbarwidth; +% errorbarXData(7:9:end) = .... +% errorbarXData(1:9:end) - errorbarwidth; +% errorbarXData(5:9:end) = ... +% errorbarXData(1:9:end) + errorbarwidth; +% errorbarXData(8:9:end) = ... +% errorbarXData(1:9:end) + errorbarwidth; +% set(hE_c(2), 'XData', errorbarXData); + thislabel = [thislabel f(ii)]; + end + hold on; +end +xlabel('time (s)'); +ylabel('relative signal'); +legend(thislabel) +hold off; + +[row,col] = size(response); +if row == 1; response = response'; end; +ResponseForPlot = cell2struct(response, f, 1); + +if exist('correlator') & ~isempty(correlator) + %list all plot names in command window for selection + promt{1} = 'I will plot signal amplitude vs correlator. Here are all the correlators:'; + promt{2} = 'index event correlator'; + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + promt{count+2} = sprintf('%d %s %s', count, cenames{jj}, correlatornames{jj}{kk}); + count = count + 1; + end + end + promt{count+2} = 'Which plots do you want me to show?'; + + promt = char(promt); + name='Please select which plots to show'; + numlines=1; + defaultanswer={['[1:' num2str(count-1) ']']}; + + whichplot=inputdlg(promt,name,numlines,defaultanswer); + if isempty(whichplot) + return; + end + whichplot = eval(whichplot{1}); + + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + if ~ismember(count, whichplot) + count = count + 1; + continue; + end + + eval(['x = C.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + + uniquex = unique(x); + pos = find(isnan(uniquex)); + uniquex(pos) = []; + + if(length(uniquex)<10) % only if the correlator is discrete, then plot BOLD vs time for each correlator + figure; + thislabel = {}; + for ii=1:length(uniquex) + pos = find(x==uniquex(ii)); + eval(['z = meannan(ResponseForPlot.' cenames{jj} '(pos,:));']); + eval(['stdz = stdnan(ResponseForPlot.' cenames{jj} '(pos,:))/sqrt(length(pos));']); + + if v(1)=='6' + ff = myerrorbar(time{1}, z, stdz); + set(ff,'color',colors(ii, :)); + thislabel = [thislabel {''} {(num2str(uniquex(ii)))}]; + elseif v(1)=='7' + myerrorbar(time{1}, z, stdz, 'color', colors(ii, :)); + thislabel = [thislabel {(num2str(uniquex(ii)))}]; + end + hold on; + end + legend(thislabel); + xlabel('time in second'); + ylabel('BOLD'); + title([cenames{jj} ' ' correlatornames{jj}{kk}]) + end + + count = count + 1; + end + end + + peakpoint = inputdlg({'I will plot peak signal. What points in time do you considered as peak signal?'}, 'Peak point',1,{'4 6'}); + if isempty(peakpoint); return; end + peakpoint = str2num(peakpoint{1}); + + + %list all plot names in command window for selection, effect(s) to be + %removed + clear promt; + promt{1} = 'Which effect(s) do you want me to remove first? (If none to remove, leave it blank and click OK)'; + promt{2} = 'index event correlator'; + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + promt{count+2} = sprintf('%d %s %s', count, cenames{jj}, correlatornames{jj}{kk}); + count = count + 1; + end + end + %promt{count+2} = 'Which effect(s) do you want me to remove first?'; + + promt = char(promt); + name='Please select which effect to remove'; + numlines=1; + defaultanswer={''}; + + whichremovefirst=inputdlg(promt,name,numlines,defaultanswer); + if isempty(whichremovefirst) + whichremovefirst = []; + elseif isempty(deblank(whichremovefirst{1})) + whichremovefirst = []; + else + whichremovefirst = eval(whichremovefirst{1}); + end + + +%% remove effect first + tmpResponseForPlot = ResponseForPlot; + for jj=1:length(cenames) + eval(['tmpResponseForPlot.' cenames{jj} ' = mean(tmpResponseForPlot.' cenames{jj} '(:,findind(time{1},peakpoint)), 2);']); + end + + if ~isempty(whichremovefirst) + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + eval(['y = tmpResponseForPlot.' cenames{jj} ';']); + x = []; + if size(y,1)==1 + y = y'; + end + for kk=1:length(correlatornames{jj}) + if ~ismember(count, whichremovefirst) + count = count + 1; + continue; + end + + eval(['tmpx = C.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + + % convert to colum vector + if size(tmpx,1)==1 + tmpx = tmpx'; + end + x = [x tmpx]; + + + + count = count + 1; + end + + % remove NaN + tmpposx = find(isnan(mean(x,2)) | isinf(mean(x,2))); + tmpposy = find(isnan(mean(y,2)) | isinf(mean(y,2))); + x([tmpposx; tmpposy],:) = []; + y([tmpposx; tmpposy],:) = []; + + b = linearregression(y,x); + y = y - x*b(1:end-1) - b(end); + eval(['tmpResponseForPlot.' cenames{jj} ' = y;']); + end + end + +%% now plot the residual amplitude against correlator + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + if ~ismember(count, whichplot) + count = count + 1; + continue; + end + + eval(['y = tmpResponseForPlot.' cenames{jj} ';']); + eval(['x = C.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + + + figure + plot(x,y, 'sb'); + hold on; + plot2(x,y,'r',1); + + xlabel(correlatornames{jj}{kk}) + ylabel('peak relative BOLD'); + legend(cenames{jj}) + try + % convert to colum vector + if size(x,1)==1 + x = x'; + end + if size(y,1)==1 + y = y'; + end + + % remove NaN + tmpposx = find(isnan(x) | isinf(x)); + tmpposy = find(isnan(y) | isinf(y)); + x([tmpposx; tmpposy]) = []; + y([tmpposx; tmpposy]) = []; + + b = linearregression(y,x); + + totalvar = var(y); + residvar = var(y - x*b(1) - b(2)); + modelvar = totalvar - residvar; + dfm = 1; + dft = length(x) - 1; + dfr = dft - dfm; + mmodelvar = modelvar/dfm; + mresidvar = residvar/dfr; + F = mmodelvar/mresidvar; + pvalue = 1-spm_Fcdf(F, [dfm dfr]); + + title(sprintf('pValue=%s; slope=%g; constant=%g', pvalue, b(1), b(2))) + xx=[min(x):(max(x)-min(x))/10:max(x)]; + yy=b(1) * xx + b(2); + hold on; + plot(xx,yy,'g'); + end + count = count + 1; + end + end +end + +function index = findind(vector1, vector2) +kk = 1; +for ii=1:length(vector2) + tmp = find(vector1 == vector2(ii)); + if ~isempty(tmp) + index(kk) = tmp; + kk = kk+1; + end +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% plot ROI, individual by individual, with behavior timing on it +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_plotIndividualROIWithBehavior(hObject, eventdata) +global TR_; +handles = guidata(hObject); + +if findstr('SPM2',spm('ver')) + P = spm_get([0:1],'*.mat','Select ROI result file'); +else%if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'mat','Select ROI result file'); +end + +if isempty(P) + return; +end +load(P); +if ~exist('TR') + TR = TR_; +end + +colors=[1 0 0; + 0 0 1; + 0 0 0; + 1 0 1; + 0 1 1; + 0 1 0; + 1 1 0; + 1 0.5 0.5; + .5 .5 1; + .5 .5 .5; + 1 .5 0; + 1 0 .5; + 0 1 .5; + .5 1 0; + 0 .5 1; + .5 0 1]; +colors = repmat(colors, 10, 1); + + +figure; +Maximize(gcf); +for ii=1:length(event) + kk = mod(ii,8); + if kk == 0 + kk = 8; + end + subplot(4,2,kk) + + m = mean(wholeOriginal{ii}); + s = std(wholeOriginal{ii}); + mx = max(wholeOriginal{ii}); + mn = min(wholeOriginal{ii}); + ylowerlimit = mn; + + hm = event{ii}; + hmcell = struct2cell(hm); + hmname = fieldnames(hm); + for jj=1:length(hmname) + toplot1 = []; + toplot2 = []; + for mm = 1:length(hmcell{jj}) + toplot1 = [toplot1 hmcell{jj}(mm) hmcell{jj}(mm) nan]; + toplot2 = [toplot2 m-s m+s nan]; + end + plot(toplot1, toplot2, 'color', colors(jj,:)); + hold on + end + legend(hmname) + title(['subject ' num2str(ii)]) + xlabel('time in s'); + + % plot imaging data + plot(TR*[0:length(wholeOriginal{ii})-1], wholeOriginal{ii}, 'k'); + hold on; + ylim([ylowerlimit mx]) + + if mod(ii,8) == 0 && ii~=length(event) + figure; + Maximize(gcf); + end +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% plot ROI, individual by individual +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_plotIndividualROI(hObject, eventdata, filename) +handles = guidata(hObject); + +if ~exist('filename') + if findstr('SPM2',spm('ver')) + P = spm_get([0:1],'*.mat','Select ROI result file'); + else%if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'mat','Select ROI result file'); + end +else + P = filename; +end + +if isempty(P) + return; +end +load(deblank(P)); + +if exist('mni') + delete(gcf) + xjview(mni); +end + +response = eventResponse{1}; + +eventisstruct = 0; +if isstruct(response) + eventisstruct = 1; + f = fieldnames(response); + response = struct2cell(response); +else + f = num2cell([1:length(response)]); + for ii=1:length(response) + f{ii} = num2str(f{ii}); + end +end +for jj=1:length(response) + response{jj} = []; +end + +if exist('correlator') & ~isempty(correlator) & eventisstruct==1 + C = correlator{1}; + cenames = fields(C); + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [];']); + end + end + for ii=1:length(correlator) + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + tmp2 = eval(['correlator{ii}.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + if size(tmp2,1) == 1 + tmp2 = tmp2'; + end + eval(['C.' cenames{jj} '.' correlatornames{jj}{kk} '= [C.' cenames{jj} '.' correlatornames{jj}{kk} '; tmp2];']); + end + end + end +end + +if eventisstruct == 1 + for ii=1:length(eventResponse) + for kk=1:length(f) + eval(['tmptmp{kk} = eventResponse{ii}.' f{kk} ';']); + end + eventResponse{ii} = tmptmp; + end +end + +for ii=1:length(eventResponse) + for jj=1:length(eventResponse{1}) + response{jj} = [response{jj}; eventResponse{ii}{jj}]; + end +end + +if isempty(response) + msgbox('Nothing to plot'); + return +end + + + + +v = version; +figure; +%colors='rbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgy'; +colors=[1 0 0; + 0 0 1; + 0 0 0; + 1 0 1; + 0 1 1; + 0 1 0; + 1 1 0; + 1 0.5 0.5; + .5 .5 1; + .5 .5 .5; + 1 .5 0; + 1 0 .5; + 0 1 .5; + .5 1 0; + 0 .5 1; + .5 0 1]; +colors = repmat(colors, 10, 1); +thislabel = {}; +for ii=1:length(response) + if v(1)=='6' + ff = myerrorbar(time{1}, meannan(response{ii}), stdnan(response{ii})/sqrt(size(response{ii},1))); + set(ff,'color',colors(ii, :)); + thislabel = [thislabel {''} f(ii)]; + elseif v(1)=='7' + myerrorbar(time{1}, meannan(response{ii}), stdnan(response{ii})/sqrt(size(response{ii},1)), 'color', colors(ii, :)); + thislabel = [thislabel f(ii)]; + end + hold on; +end +xlabel('time (s)'); +ylabel('relative signal'); +legend(thislabel) +hold off; + +figure; +Maximize(gcf); +for jj=1:length(eventResponse) + wheretoplot = mod(jj, 16); + if wheretoplot == 0; + wheretoplot = 16; + subplot(4,4,wheretoplot) + else + subplot(4,4,wheretoplot) + end + for ii=1:length(response) + if v(1)=='6' + ff = myerrorbar(time{1}, meannan(eventResponse{jj}{ii}), stdnan(eventResponse{jj}{ii})/sqrt(size(eventResponse{jj}{ii},1))); + set(ff,'color',colors(ii, :)); + %thislabel = [thislabel {''} f(ii)]; + elseif v(1)=='7' + myerrorbar(time{1}, meannan(eventResponse{jj}{ii}), stdnan(eventResponse{jj}{ii})/sqrt(size(eventResponse{jj}{ii},1)), 'color', colors(ii, :)); + %myerrorbar(time{1}, meannan(response{ii}), stdnan(response{ii})/sqrt(size(response{ii},1)), 'color', colors(ii, :)); + %thislabel = [thislabel f(ii)]; + end + hold on; + end + title(['subject ' num2str(jj)]) + + if mod(jj, 16)==0 && jj~=length(eventResponse) + figure; + Maximize(gcf); + end +end + + + +[row,col] = size(response); +if row == 1; response = response'; end; +for jj=1:length(eventResponse) + ResponseForPlot{jj} = cell2struct(eventResponse{jj}, f, 2); +end + +if exist('correlator') & ~isempty(correlator) + %list all plot names in command window for selection + promt{1} = 'I will plot signal amplitude vs correlator. Here are all the correlators:'; + promt{2} = 'index event correlator'; + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + promt{count+2} = sprintf('%d %s %s', count, cenames{jj}, correlatornames{jj}{kk}); + count = count + 1; + end + end + promt{count+2} = 'Which plots do you want me to show?'; + + promt = char(promt); + name='Please select which plots to show'; + numlines=1; + defaultanswer={['[1:' num2str(count-1) ']']}; + + whichplot=inputdlg(promt,name,numlines,defaultanswer); + if isempty(whichplot) + return; + end + whichplot = eval(whichplot{1}); + + peakpoint = inputdlg({'What points in time do you considered as peak signal?'}, 'Peak point',1,{'4 6'}); + if isempty(peakpoint); return; end + peakpoint = str2num(peakpoint{1}); + + count = 1; + for jj=1:length(cenames) + eval(['correlatornames{jj} = fields(C.' cenames{jj} ');']); + for kk=1:length(correlatornames{jj}) + if ~ismember(count, whichplot) + count = count + 1; + continue; + end + figure; + Maximize(gcf); + for ii=1:length(eventResponse) + wheretoplot = mod(ii, 16); + if wheretoplot == 0; + wheretoplot = 16; + subplot(4,4,wheretoplot) + else + subplot(4,4,wheretoplot) + end + + + eval(['y = mean(ResponseForPlot{ii}.' cenames{jj} '(:,findind(time{1},peakpoint)), 2);']); + eval(['x = correlator{ii}.' cenames{jj} '.' correlatornames{jj}{kk} ';']); + + %plot(x,y, 'sb'); + %hold on; + pos = find(isnan(x)); + x(pos) = []; + y(pos) = []; + pos = find(isnan(y)); + x(pos) = []; + y(pos) = []; + if length(x) < 1 + continue; + end + plot2(x,y,'r',1); + + xlabel(correlatornames{jj}{kk}) + ylabel(['peak signal at ' cenames{jj}]); + %legend(cenames{jj}) + try + % convert to colum vector + if size(x,1)==1 + x = x'; + end + if size(y,1)==1 + y = y'; + end + + % remove NaN + tmpposx = find(isnan(x) | isinf(x)); + tmpposy = find(isnan(y) | isinf(y)); + x([tmpposx; tmpposy]) = []; + y([tmpposx; tmpposy]) = []; + + b = linearregression(y,x); + + totalvar = var(y); + residvar = var(y - x*b(1) - b(2)); + modelvar = totalvar - residvar; + dfm = 1; + dft = length(x) - 1; + dfr = dft - dfm; + mmodelvar = modelvar/dfm; + mresidvar = residvar/dfr; + F = mmodelvar/mresidvar; + pvalue = 1-spm_Fcdf(F, [dfm dfr]); + + title(sprintf('subject %d, pValue=%s', ii, pvalue)) + xx=[min(x):(max(x)-min(x))/10:max(x)]; + yy=b(1) * xx + b(2); + hold on; + plot(xx,yy,'g'); + end + if mod(ii, 16)==0 && ii~=length(eventResponse) + figure; + Maximize(gcf); + end + end % end of loop subject + count = count + 1; + end + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% plot ROI: correlation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_plotCorrelationROI(hObject, eventdata) + +if findstr('SPM2',spm('ver')) + P1 = spm_get([0:100],'*.mat','Select ROI result file(s)'); +else%if findstr('SPM5',spm('ver')) + P1 = spm_select([0:100],'mat','Select ROI result file(s)'); +end + +if isempty(P1) + return; +end + +N = size(P1,1); +t = [-20:20]; + +v = version; + +if N == 1 + load(deblank(P1)); + tmp = []; + for jj=1:length(wholeAbsolute) + tmp = [tmp; corrlag(wholeAbsolute{jj},wholeAbsolute{jj},t)]; + end + figure; + myerrorbar(t, mean(tmp,1), std(tmp)/sqrt(length(wholeAbsolute))); + xlabel('lag in scan number'); + ylabel('auto correlation'); + title(deblank(P1)) + return +else + figure; + colors='rbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgyrbkmcgy'; + legendlabel = {}; + totalPermute = nchoosek([1:N],2); + for ii=1:size(totalPermute,1) + tmp = []; + s1 = load(deblank(P1(totalPermute(ii,1),:))); + s2 = load(deblank(P1(totalPermute(ii,2),:))); + for jj=1:length(s1.wholeAbsolute) + tmp = [tmp; corrlag(s1.wholeAbsolute{jj},s2.wholeAbsolute{jj},t)]; + end + myerrorbar(t, mean(tmp,1), std(tmp)/sqrt(length(s1.wholeAbsolute)), colors(ii)); + xlabel('lag in scan number'); + ylabel('cross correlation'); + hold on; + if v(1) == '6' + legendlabel = [legendlabel, {'', P(totalPermute(ii,:),:)}]; + elseif v(1) == '7' + legendlabel = [legendlabel, {P1(totalPermute(ii,:),:)}]; + end + end + legend(legendlabel); + hold off; + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% whole brain correlation analysis +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_wholeBrainCorrelation(hObject, eventdata) +% answer = getVariable({'Which data file?'}); +% if isempty(answer) +% return; +% end +% if isempty(answer{1}) +% return; +% end +% P = evalin('base',answer{1}); % subject directories +if findstr('SPM2',spm('ver')) + P = spm_get([0:1],'*.mat','Whole Brain Signal file'); +else%if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'mat','Whole Brain Signal file'); +end + +if isempty(P) + return +end + +load(deblank(P)); +M = double(M); + +N=zeros(size(M,4), size(M,1) * size(M,2) * size(M,3)); + +mm = 1; +for ii=1:2:size(M,1) + for jj=1:3:size(M,2) + for kk=1:2:size(M,3) + N(:, mm) = squeeze(M(ii,jj,kk,:)); + mm = mm + 1; + cor(mm,:) = [ii jj kk]; + end + end +end + +N(:, mm:end) = []; + +C=corrcoef(N); +C(find(isnan(C))) = 0; + +for ii=1:4 + CC{ii} = abs(C)>(0.5+ii/10); +end + +K = {zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1))}; +for ii=1:size(C,1) + for jj=1:4 + K{jj}(ii) = sum(CC{jj}(ii,:)) - 1; + end +end + +x=[0:size(C,1)]; +for jj=1:4 + y{jj}=zeros(size(x)); +end + +for ii=1:length(x) + for jj=1:4 + y{jj}(ii) = sum(K{jj} == x(ii)); + end +end + +figure; +loglog(x,y{1}, x, y{2}, x, y{3}, x, y{4}); +xlabel('degree'); +ylabel('counts'); +legend('0.6', '0.7', '0.8', '0.9'); +axis equal + + +z = sum(abs(C))-1; +zx = 0:max(z); +for ii=1:length(zx)-1 + pos = find(z>zx(ii) & z<=zx(ii+1)); + zy(ii) = length(pos); +end +figure; +loglog(zx(1:length(zy)),zy); +xlabel('weighted degree'); +ylabel('counts'); +axis equal + +xjview(cor2mni(coord, handles.M{1}), z); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get/select variable names in base workspace +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function vars = getVariable(titles) +vars = evalin('base','who'); +height = 0.07; +f = dialog('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.4 0.4], 'name', 'pick variables', 'NumberTitle','off'); +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', 'Available variables', ... + 'position',[0 0.9 0.5 0.1/2]); +variableListbox = uicontrol(f,'style','listbox','tag','variableListbox',... + 'unit','normalized',... + 'String', vars, ... + 'value',1,... + 'position',[0 0 0.5 0.9]); +okPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'OK', ... + 'position',[0.55 0.05 0.2 height],... + 'callback','uiresume'); +cancelPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'Cancel', ... + 'position',[0.75 0.05 0.2 height],... + 'callback','delete(gcf)'); + +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{1}, ... + 'position',[0.5 0.9 0.5 0.1/2]); +imageDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.8 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''imageDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); +imageDataEdit = uicontrol(f,'style','edit','tag','imageDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.8 0.3 height]); + +if length(titles)>=2 +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{2}, ... + 'position',[0.5 0.7 0.5 0.1/2]); +eventDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.6 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''eventDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + +eventDataEdit = uicontrol(f,'style','edit','tag','eventDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.6 0.3 height]); +end +if length(titles)>=3 +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{3}, ... + 'position',[0.5 0.5 0.5 0.1/2]); +correlatorDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.4 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''correlatorDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + +correlatorDataEdit = uicontrol(f,'style','edit','tag','correlatorDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.4 0.3 height]); +end +if length(titles)>=4 +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{4}, ... + 'position',[0.5 0.3 0.5 0.1/2]); +otherDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.2 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''otherDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + +otherDataEdit = uicontrol(f,'style','edit','tag','otherDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.2 0.3 height]); +end + +uiwait(f); +try + var{1} = get(imageDataEdit,'string'); + if length(titles)>=2 + var{2} = get(eventDataEdit,'string'); + end + if length(titles)>=3 + var{3} = get(correlatorDataEdit,'string'); + end + if length(titles)>=4 + var{4} = get(otherDataEdit,'string'); + end + vars = var; + delete(f); +catch + vars = {}; + try + delete(f); + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% quit xjview +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_quit(hObject, eventdata, warnstate) +warning(warnstate) +% try +% rmdir('xjviewtmp'); +% end +delete(gcf); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mouse double click +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function figureMouseUpFcn(hObject, eventdata) +status = get(hObject, 'SelectionType'); + +% double click +if strcmp(status, 'open') + handles = guidata(hObject); + CallBack_loadImagePush(handles.loadImagePush, eventdata); +else + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change edit image file name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_imageFileEdit(hObject, eventdata) +handles = guidata(hObject); +filename = get(hObject, 'String'); +filename = str2cell(filename); +CallBack_loadImagePush(handles.loadImagePush, eventdata, filename); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadImagePush(hObject, eventdata, thisfilename) +handles = guidata(hObject); + +handles.imageFileName=[]; handles.M=[]; handles.DIM=[]; handles.TF=[]; handles.df=[]; +handles.mni=[]; handles.intensity=[]; handles.currentmni=[]; handles.currentintensity=[]; handles.currentDisplayMNI=[]; handles.currentDisplayIntensity=[]; + +if ~exist('thisfilename') + thisfilename = ''; +end + +if isstruct(thisfilename) + handles.imageFileName = {''}; + handles.mni = {thisfilename.mni}; + handles.intensity = {thisfilename.intensity}; + handles.M = {thisfilename.M}; + handles.DIM = {thisfilename.DIM}; + handles.TF = {'S'}; + handles.df = {1}; + handles.pValue = 1; + set(handles.pValueEdit, 'string', '1'); + handles.clusterSizeThreshold = 0; + set(handles.clusterSizeThresholdEdit, 'String', '0'); +else + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); +end + +if isempty(handles.imageFileName) + return +end + +different = 0; % image files are same or different? +if length(handles.TF)>1 + for ii=1:length(handles.TF) + if ( strcmp(handles.TF{ii},handles.TF{1}) || isempty(handles.TF{ii}) && isempty(handles.TF{1}) ) & isequal(handles.df{ii},handles.df{1}) & isequal(handles.M{ii},handles.M{1}) & isequal(handles.DIM{ii},handles.DIM{1}) + continue; + else + warndlg('Images are from different statistics or sources.', 'Warning'); + %set(handles.infoTextBox, 'string', 'Images are from different statistics or sources.'); + beep; + different = 1; + break; + end + end +end + +% reset files with empty df/TF to df=1 and TF='S'. 'S'=='T' but has a tag +% meaning it is changed. +resetTF = 0; +for ii=1:length(handles.TF) + if isempty(handles.TF{ii}) + handles.TF{ii} = 'S'; + resetTF = 1; + end + if isempty(handles.df{ii}) | isequal(handles.df{ii},0) + handles.df{ii} = 1; + resetTF = 1; + end +end + +handles.currentmni = handles.mni; +handles.currentintensity = handles.intensity; + +set(handles.dfEdit, 'String', cell2str(handles.df)); +set(handles.imageFileEdit, 'String', cell2str(handles.imageFileName)); % s=-log10(p) +maxs = maxcell(t2s(cellmax(handles.intensity,'abs'),handles.df, handles.TF),'abs'); +if isinf(maxs); maxs = 20; end +set(handles.slider, 'Max', maxs, 'Min', 0, 'sliderstep',[min(maxs/100,0.05),min(maxs/100,0.05)]); +if handles.TF{1}=='T' & different == 0 + str = [blanks(length(' intensit')) 'T=']; +elseif handles.TF{1}=='F' & different == 0 + str = [blanks(length(' intensit')) 'F=']; +else + str=' intensity='; +end +set(handles.intensityThresholdText, 'String', str); +set(handles.figure,'Name',['xjView: ' cell2str(handles.imageFileName)]); +try + for ii=1:length(handles.hLegend) + delete(handles.hLegend{ii}); + end +end +if length(handles.TF)>1 + colours = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],100,1); + for ii=1:min(length(handles.TF),10) + [tmp,filename] = fileparts(handles.imageFileName{ii}); + if ii == 10; filename = '......'; end + pos0 = handles.sectionViewPosition; + pos(1) = pos0(1)+pos0(3)/2+0.03; + pos(2) = pos0(2)+ii/50-0.03; + pos(3) = 0.12; + pos(4) = 0.02; + handles.hLegend{ii}=uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',pos,... + 'string', filename,... + 'horizontal','left',... + 'fontweight','bold',... + 'ForeGroundColor',colours(ii,:)); + end + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; +end +guidata(hObject, handles); + +global M_; +global DIM_; +global XJVIEWURL_; +M_ = handles.M{1}; +DIM_ = handles.DIM{1}; + +if resetTF==1 + set(handles.pValueEdit,'string',1); +end +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% display info +% try +% %urlread([XJVIEWURL_ '/guestbook/stat.php']); +% s = urlread([XJVIEWURL_ '/toUser.txt']); +% report{1} = s; +% catch +% report{1} = 'Welcome to xjView 8'; +% end + +for jj=1:length(handles.imageFileName) + report{2+6*(jj-1)} = cell2str(handles.imageFileName(jj)); + if handles.TF{jj} == 'T' | handles.TF{jj} == 'F' + report{3+6*(jj-1)} = ['This is a ' handles.TF{jj} ' test image.']; + else + report{3+6*(jj-1)} = '';%['I don''t know what test this image came from.']; + end + report{4+6*(jj-1)} = 'mat = '; + report{5+6*(jj-1)} = num2str(handles.M{jj}); + report{6+6*(jj-1)} = 'dimension = '; + report{7+6*(jj-1)} = num2str(handles.DIM{jj}); +end +set(handles.infoTextBox, 'string', report); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pValueEdit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pValueEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +tmps = -log10(tmp); +if isnan(tmp) | tmp < 0 | tmp > 1 + errordlg('I don''t understand the input.','error'); + set(hObject, 'String', handles.pValue); + return +end + +if tmps>get(handles.slider,'max') | tmps maxcell(cellmax(handles.intensity,'abs')) + tmp = maxcell(cellmax(handles.intensity,'abs')); +end + +handles.pValue = t2p(tmp, handles.df{1}, handles.TF{1}); +handles.intensityThreshold = p2t(num2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); +set(handles.slider,'Value', -log10(handles.pValue)); +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +guidata(hObject, handles); +CallBack_slider(hObject, eventdata, -log10(handles.pValue)); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% slider bar +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_slider(hObject, eventdata, value) + +handles = guidata(hObject); + +if exist('value') + s = value; + if s > get(handles.slider,'max') + s = get(handles.slider,'max')*0.99; + end + if s < get(handles.slider,'min') + s = get(handles.slider,'min'); + end +else + s = get(hObject,'Value'); +end + +set(handles.slider, 'value', s); +pvalue = 10^(-s); +set(handles.pValueEdit,'String',num2str(pvalue)); +t = p2t(num2cell(pvalue*ones(1,length(handles.TF))), handles.df, handles.TF); +handles.intensityThreshold = t; +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +handles.pValue = pvalue; +for ii=1:length(handles.TF) + pos{ii} = find(abs(handles.intensity{ii})>=t{ii}); + handles.currentintensity{ii} = handles.intensity{ii}(pos{ii}); + handles.currentmni{ii} = handles.mni{ii}(pos{ii},:); +end + +guidata(hObject,handles); + +if get(handles.allIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.allIntensityRadio, eventdata); +elseif get(handles.positiveIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.positiveIntensityRadio, eventdata, '+'); +elseif get(handles.negativeIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.negativeIntensityRadio, eventdata, '-'); +end + +% set(handles.infoTextBox, 'string', {'Don''t drag the slider bar too fast. Release your mouse button at least 1 second later.', ... +% 'This sounds stupid. But there is a bug (probably MatLab bug) which I can'' fix right now.', ... +% 'I suggest you confirm the correctness of the current display by press Enter in the pValue edit box.'}); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display intensity all+- radios +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allIntensityRadio(hObject, eventdata, pnall) +% pnall = '+', '-', or 'c'. c means current (simply update drawing) +% +handles = guidata(hObject); + +currentselect = []; +if get(handles.allIntensityRadio, 'Value'); currentselect = handles.allIntensityRadio; thispnall = 'a'; end +if get(handles.positiveIntensityRadio, 'Value'); currentselect = handles.positiveIntensityRadio; thispnall = '+'; end +if get(handles.negativeIntensityRadio, 'Value'); currentselect = handles.negativeIntensityRadio; thispnall = '-'; end + +set(handles.allIntensityRadio, 'Value', 0); +set(handles.positiveIntensityRadio, 'Value', 0); +set(handles.negativeIntensityRadio, 'Value', 0); + +if exist('pnall') + if pnall=='c' + hObject = currentselect; + pnall = thispnall; + end +end + +set(hObject, 'Value', 1); + +if ~isfield(handles,'currentintensity') + return +end +for ii=1:length(handles.TF) + if exist('pnall') + if pnall == '-' + pos{ii} = find(handles.currentintensity{ii} < 0); + elseif pnall == '+' + pos{ii} = find(handles.currentintensity{ii} > 0); + elseif pnall == 'a' + pos{ii} = 1:length(handles.currentintensity{ii}); + end + else + pos{ii} = 1:length(handles.currentintensity{ii}); + end + intensity{ii} = handles.currentintensity{ii}(pos{ii}); + mni{ii} = handles.currentmni{ii}(pos{ii},:); + cor{ii} = mni2cor(mni{ii}, handles.M{ii}); + + if ~isempty(cor{ii}) + A = spm_clusters(cor{ii}'); + pos0 = []; + for kk = 1:max(A) + jj = find(A == kk); + if length(jj) >= handles.clusterSizeThreshold; pos0 = [pos0 jj]; end + end + handles.currentDisplayMNI{ii} = mni{ii}(pos0,:); + handles.currentDisplayIntensity{ii} = intensity{ii}(pos0); + else + handles.currentDisplayMNI{ii} = mni{ii}([],:); + handles.currentDisplayIntensity{ii} = intensity{ii}([]); + end +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +if get(handles.allIntensityRadio, 'Value') & max(handles.currentDisplayIntensity{1}) < 0 + warndlg('No supra-threshold positive intensity. Only negative intensity is displayed.'); + set(handles.negativeIntensityRadio, 'Value', 1); + set(handles.allIntensityRadio, 'Value', 0); + return +end +if get(handles.allIntensityRadio, 'Value') & min(handles.currentDisplayIntensity{1}) > 0 + warndlg('No supra-threshold negative intensity. Only positive intensity is displayed.'); + set(handles.positiveIntensityRadio, 'Value', 1); + set(handles.allIntensityRadio, 'Value', 0); + return +end + +try + set(handles.figure,'currentaxes', handles.glassViewAxes); + xrange = xlim; + yrange = ylim; + try + delete(handles.hGlassText) + end + if ~isempty(handles.selectedCluster,1) + %handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + end +end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% render view check? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderViewCheck(hObject, eventdata) +handles = guidata(hObject); +check = get(hObject, 'Value'); +%if check + CallBack_allIntensityRadio(hObject, eventdata, 'c'); +%end + +try +if check; % if display render, will make feed invisible + set(handles.feed,'visible','off'); + set(handles.feedclick,'visible','off'); + set(handles.postfeedclick,'visible','off'); + set(handles.refreshclick,'visible','off'); +else + set(handles.feed,'visible','on'); + set(handles.feedclick,'visible','on'); + set(handles.postfeedclick,'visible','on'); + set(handles.refreshclick,'visible','on'); +end +end +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change rend style +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderStylePop(hObject, eventdata) +CallBack_renderViewCheck(hObject, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% which section view target file? list box +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewListbox(hObject, eventdata) +handles = guidata(hObject); +contents = get(handles.sectionViewListbox,'String'); +currentsel = contents{get(handles.sectionViewListbox,'Value')}; +handles.sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get sectionviewtargetfile +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sectionViewTargetFile = getSectionViewTargetFile(spmdir, selectedcontent) +if findstr('SPM2',spm('ver')) + fileext = 'mnc'; +else%if findstr('SPM5',spm('ver')) + fileext = 'nii'; +end +currentsel = selectedcontent; +if ~isempty(strfind(currentsel, 'single')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['single_subj_T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152PD')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152PD.' fileext]); +elseif ~isempty(strfind(currentsel, '152T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152T2')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T2.' fileext]); +elseif ~isempty(strfind(currentsel, '305T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg305T1.' fileext]); +elseif strcmp(currentsel, 'ch2') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2.img'); +elseif strcmp(currentsel, 'ch2bet') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2bet.img'); +elseif strcmp(currentsel, 'aal') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'aal.img'); +elseif strcmp(currentsel, 'brodmann') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'brodmann.img'); +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% xhairs in section view? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_xHairCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + spm_orthviews('Xhairs','off'); +else + spm_orthviews('Xhairs','on'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% other target file for section view, push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewMoreTargetPush(hObject, eventdata) +handles = guidata(hObject); +[filename, pathname, filterindex] = uigetfile('*', 'Pick an target file'); +if isequal(filename,0) | isequal(pathname,0) + return; +end +handles.sectionViewTargetFile = fullfile(pathname, filename); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% set colorbar range +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_setTRangeEdit(hObject, eventdata) +global TMAX_; +handles = guidata(hObject); +TMAX_ = get(hObject, 'String'); +if isempty(str2num(TMAX_)) && ~strcmp(TMAX_, 'auto') + return; +end +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change degree of freedome +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_dfEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2cell(get(hObject, 'String')); +if iscellstr(tmp) + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.df); + catch + set(hObject, 'String', ''); + end + return +end +handles.df=tmp; + + +if isfield(handles,'TF') + t = p2t(mat2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); + handles.intensityThreshold = t; + set(handles.intensityThresholdEdit, 'String', cell2str(t)); +end + +guidata(hObject, handles); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get structure push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_getStructurePush(hObject, eventdata) +handles = guidata(hObject); +xyz = spm_XYZreg('GetCoords',handles.hReg); +tmp_coor = cuixuFindStructure(xyz', handles.DB); +set(handles.structureEdit,'String', tmp_coor{1}); +handles.currentxyz = xyz'; +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% structure edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_structureEdit(action, xyz, thisfun, hReg) + +try + handles=guidata(hReg); +catch + return; +end + +handles.currentxyz = xyz'; +handles.hReg = hReg; +guidata(hReg, handles); + +try + [tmp_coor, cellstructure] = cuixuFindStructure(xyz', handles.DB); +catch + return; +end + +set(handles.structureEdit,'String', tmp_coor{1}); + +for ii=[5 3 2 6 1 4] + if strfind('undefined', cellstructure{ii}) + continue; + else + set(handles.searchContentEdit,'string', trimStructureStr(cellstructure{ii})); + return; + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% trim str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = trimStructureStr(str) +pos = findstr('(', str); +if ~isempty(pos) + str(pos-1:end)=[]; +end +out = str; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cluster size threshold edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clusterSizeThresholdEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +if isnan(tmp) | tmp<0 + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.clusterSizeThreshold); + catch + set(hObject, 'String', '5'); + end + return +end +handles.clusterSizeThreshold=tmp; + +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImagePush(hObject, eventdata, thisfilename, isMask) +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}); + return; + end + end + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}); + return; + end +end + +[filename, pathname] = uiputfile('*.img', 'Save image file as', get(handles.saveImageFileEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + +if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName{1}) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity'), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}, isMask); + return; + end +end + +mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, '', isMask); + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImageFileEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveImagePush(handles.saveImagePush, eventdata, get(hObject,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSPush(hObject, eventdata, thisfilename) + +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + spm_print(handles.figure); + if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); + elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); + end + return; + end +end + +[filename, pathname] = uiputfile('*.ps', 'Save result as', get(handles.saveResultPSEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +% print +H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +pos = get(H,'position'); +index = []; + +for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 & pos{ii}(2) > 0.5 + set(H(ii),'position',[pos{ii}(1), pos{ii}(2), pos{ii}(3)*3/4, pos{ii}(4)]); + index = [index ii]; + end +end + + +spm_print(handles.figure); +if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); +elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); +end + +% set the position back +set(H(index), {'position'}, pos(index)); + + +% printstr = ['print -dpsc2 -painters -noui ' '''' thisfilename '''']; +% try +% orient portrait +% eval(printstr); +% printsuccess = 1; +% catch +% errordlg('Print to ps file failed', 'print error'); +% printsuccess = 0; +% end +%set(H,{'Units'},un); +% if strcmp(handles.system, 'linux') & printsuccess == 1 +% system(['ps2pdf ' '''' thisfilename '''']); +% end + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveResultPSPush(hObject, eventdata, get(handles.saveResultPSEdit,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% select a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_selectThisClusterPush(hObject, eventdata) +handles = guidata(hObject); + +try + xyz = handles.currentxyz'; +catch + xyz = spm_XYZreg('GetCoords',handles.hReg); +end +try + handles.selectedCluster = [handles.selectedCluster; xyz']; +catch + handles.selectedCluster = xyz'; +end + +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + delete(handles.hGlassText) +end +%handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% unselect a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clearSelectedClusterPush(hObject, eventdata) +handles = guidata(hObject); +try + handles = rmfield(handles,'selectedCluster'); +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + %delete(handles.hGlassText) + set(handles.infoTextBox, 'string', ['No clusters selected']); +end + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pick a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pickThisClusterPush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return; +end + +if ~isfield(handles, 'selectedCluster') | isempty(handles.selectedCluster) + try + xyz = handles.currentxyz'; + catch + xyz = spm_XYZreg('GetCoords',handles.hReg); + end + handles.selectedCluster = xyz'; +end + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); +xyzcor = mni2cor(handles.selectedCluster, handles.M{1}); + +pos = []; +for ii = 1:size(xyzcor,1) + pos0 = find(cor(:,1)==xyzcor(ii,1) & cor(:,2)==xyzcor(ii,2) & cor(:,3)==xyzcor(ii,3)); + if isempty(pos0) + continue; + end + pos = [pos find(A==A(pos0(1)))]; +end +if isempty(pos) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return +end + +pos = unique(pos); + +tmpmni = mni(pos,:); +tmpintensity = intensity(pos); + +[B,I,J] = unique(tmpmni, 'rows'); +handles.currentDisplayMNI = {B}; +handles.currentDisplayIntensity = {tmpintensity(I,:)}; + +handles.currentxyz = handles.selectedCluster(end,:); + +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; + +handles.selectedCluster = []; +try + delete(handles.hGlassText) +end + +guidata(hObject, handles); + +set(handles.thisClusterSizeEdit,'string', num2str(size(handles.currentDisplayMNI{1},1))); +str = get(handles.searchContentEdit, 'string'); +pos = findstr(' ', str); +str(pos) = []; +files = []; +for ii=1:length(handles.imageFileName) + [a,b,c] = fileparts(handles.imageFileName{ii}); + files = [files b]; +end +if ~isempty(files) + files = ['_from_' files]; +end + +set(handles.saveImageFileEdit, 'string', [str files '.img']); + +% list structure of voxels in this cluster +[a, b] = cuixuFindStructure(cell2mat(handles.currentDisplayMNI'), handles.DB); +names = unique(b(:)); +index = NaN*zeros(length(b(:)),1); +for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; +end + +for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); +end +for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end +end +report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; +% format long +% disp(b) +% disp(report) +% format +report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; +for ii=2:size(report,1) + if strcmp('undefined', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; +end + +report2 = [report2, {'','select and Ctrl-C to copy'}]; +% f = figure('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.2 min(0.7,0.016*length(report2))], 'name', 'cluster information', 'NumberTitle','off'); +% hEdit = uicontrol(f,'style','edit',... +% 'unit','normalized','position',[0 0 1 1],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', report2,... +% 'max',2,'min',0); + +set(handles.infoTextBox, 'string', report2); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% report +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_reportPush(hObject, eventdata) +handles = guidata(hObject); + +set(handles.infoTextBox, 'string', 'This function will generate a report of this functional image. Check out your MatLab command window. You may copy and past to a file for later use.'); +if(length(handles.imageFileName)~=1) + set(handles.infoTextBox, 'string', 'This function only applies to 1 functional image.'); + return; +end + +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is found. So no report will be generated.'); + beep + return; +end + +disp(handles.imageFileName{1}); +disp(['Type: ' num2str(handles.TF{1})]); +disp(['df: ' num2str(handles.df{1})]); +disp('Threshold') +disp(['-- p value = ' num2str(handles.pValue)]); +disp(['-- intensity = ' num2str(handles.intensityThreshold{1})]); +disp(['-- cluster size = ' num2str(handles.clusterSizeThreshold)]); + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); + +clusterID = unique(A); +numClusters = length(clusterID); +disp(['Number of clusters found: ' num2str(numClusters)]); + +for mm = clusterID + pos = find(A == clusterID(mm)); + numVoxels = length(pos); + tmpmni = mni(pos,:); + tmpintensity = intensity(pos); + + peakpos = find(abs(tmpintensity) == max(abs(tmpintensity))); + peakpos = peakpos(1); + peakcoord = tmpmni(peakpos,:); + peakintensity = tmpintensity(peakpos); + + % list structure of voxels in this cluster + [a, b] = cuixuFindStructure(tmpmni, handles.DB); + names = unique(b(:)); + index = NaN*zeros(length(b(:)),1); + for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; + end + + report = {}; + + for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); + end + for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end + end + report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; + + report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; + for ii=2:size(report,1) + if strcmp('undefined', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; + end + + disp(['----------------------']) + disp(['Cluster ' num2str(mm)]) + disp(['Number of voxels: ' num2str(numVoxels)]) + disp(['Peak MNI coordinate: ' num2str(peakcoord)]) + [a,b] = cuixuFindStructure(peakcoord, handles.DB); + disp(['Peak MNI coordinate region: ' a{1}]); + disp(['Peak intensity: ' num2str(peakintensity)]) + for kk=1:length(report2) + disp(report2{kk}); + end +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% sliceView push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sliceViewPush(hObject, eventdata) +if(nargin == 1) + eventdata = []; +end +handles = guidata(hObject); + + +global sliceview + +if(~isfield(sliceview, 'fig') || ~ishandle(sliceview.fig)) + sliceview.viewtype = 't'; + sliceview.row = 8; + sliceview.col = 8; + sliceview.spacing = 4; + sliceview.page = 1; + sliceview.data = {{},{},{}}; % t,s,c + sliceview.slices = {[],[],[]};% t,s,c + sliceview.colormap = ''; + sliceview.fig = figure('color','k', 'unit','normalized','position',[0.1 0.1 .6 .8],'toolbar','none', 'name', 'xjView slice view', 'NumberTitle','off'); + sliceview.ax = axes('Visible','on','DrawMode','fast','Parent',sliceview.fig,... + 'YDir','normal','Ydir','normal','XTick',[],'YTick',[], 'position', [0.15 0.05 .8 .9]); + %handles.sliceview.d = image([],'Tag','Transverse','Parent',handles.sliceview.ax); + set(sliceview.ax,'XTick',[],'YTick',[]); + axis equal + set(sliceview.ax,'color','k'); + %setcolormap(colormp) + width = 0.05; + height = 0.025; + step = 0.025; + labeloffset = step/2; + + uicontrol(sliceview.fig,'style','text',... + 'unit','normalized','position',[0 step-labeloffset width height],... + 'horizontal','left',... + 'BackGroundColor', 'k', ... + 'ForeGroundColor', [1 1 1], ... + 'String', 'row #'); + uicontrol(sliceview.fig,'style','text',... + 'unit','normalized','position',[0 step*3-labeloffset width height],... + 'horizontal','left',... + 'BackGroundColor', 'k', ... + 'ForeGroundColor', [1 1 1], ... + 'String', 'column #'); + uicontrol(sliceview.fig,'style','text',... + 'unit','normalized','position',[0 step*5-labeloffset width*2 height],... + 'horizontal','left',... + 'BackGroundColor', 'k', ... + 'ForeGroundColor', [1 1 1], ... + 'String', 'spacing (mm)'); + uicontrol(sliceview.fig,'style','text',... + 'unit','normalized','position',[0 step*7-labeloffset width height],... + 'horizontal','left',... + 'BackGroundColor', 'k', ... + 'ForeGroundColor', [1 1 1], ... + 'String', 'scroll'); + + uicontrol(sliceview.fig,'style','edit',... + 'unit','normalized','position',[0 0 width height],... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', sliceview.row,... + 'callback',@sliceViewRowChanged); + + uicontrol(sliceview.fig,'style','edit',... + 'unit','normalized','position',[0 step*2 width height],... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', sliceview.col,... + 'callback',@sliceViewColChanged); + + uicontrol(sliceview.fig,'style','edit',... + 'unit','normalized','position',[0 step*4 width height],... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', sliceview.spacing,... + 'callback',@sliceViewSpacingChanged); + +% uicontrol(sliceview.fig,'style','edit',... +% 'unit','normalized','position',[0 step*6 width height],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', sliceview.page,... +% 'callback',@sliceViewPageChanged); + uicontrol(sliceview.fig,'style','push',... + 'unit','normalized','position',[0 step*6 width height],... + 'horizontal','left',... + 'BackgroundColor', 'k',... + 'ForegroundColor', 'w', ... + 'String', 'up',... + 'callback',@sliceViewPageChangedP); + uicontrol(sliceview.fig,'style','push',... + 'unit','normalized','position',[0.05 step*6 width height],... + 'horizontal','left',... + 'BackgroundColor', 'k',... + 'ForegroundColor', 'w', ... + 'String', 'down',... + 'callback',@sliceViewPageChangedN); + uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',[0 step*8 width*2 height],... + 'String',{'transverse';'coronal';'sagittal'}, ... + 'Style','popupmenu', ... + 'value',1,... + 'callback',@sliceViewTypeChanged); + +end + +figure(sliceview.fig) + +viewtype = sliceview.viewtype; +row = sliceview.row; +col = sliceview.col; +spacing = sliceview.spacing; +page = sliceview.page; +slice_fig = sliceview.fig; +ax = sliceview.ax; +%d = handles.sliceview.d; + +[slicedata, colormp, slices] = cuixu_getSliceViewData(viewtype,row,col, spacing, page); + +if isempty(slices) + return; +end + +for ii=1:length(slices) + if(viewtype == 's') + postmp = find(slices(ii) - sliceview.slices{2} == 0); + if(isempty(postmp)) + sliceview.data{2}{end+1} = slicedata{ii}; + sliceview.slices{2}(end+1) = slices(ii); + end + elseif(viewtype == 't') + postmp = find(slices(ii) - sliceview.slices{1} == 0); + if(isempty(postmp)) + sliceview.data{1}{end+1} = slicedata{ii}; + sliceview.slices{1}(end+1) = slices(ii); + end + elseif(viewtype == 'c') + postmp = find(slices(ii) - sliceview.slices{3} == 0); + if(isempty(postmp)) + sliceview.data{3}{end+1} = slicedata{ii}; + sliceview.slices{3}(end+1) = slices(ii); + end + end + +end + + + +%slice_fig = figure('color','k', 'unit','normalized','position',[0.1 0.1 .6 .8],'toolbar','none'); + + +if(length(size(slicedata{1})) == 3) + [nx, ny, nz] = size(slicedata{1}); + slicedatafinal = zeros(nx*row, ny*col, nz ); + for ii=1:length(slicedata) + slicedatafinal(nx*(floor((ii-1)/col))+1:nx*(1+floor((ii-1)/col)), ny*(mod(ii-1,col))+1:ny*(mod(ii-1,col)+1), :) = slicedata{ii}; + end +else + [nx, ny] = size(slicedata{1}); + slicedatafinal = zeros(nx*row, ny*col ); + for ii=1:length(slicedata) + slicedatafinal(nx*(floor((ii-1)/col))+1:nx*(1+floor((ii-1)/col)), ny*(mod(ii-1,col))+1:ny*(mod(ii-1,col)+1)) = slicedata{ii}; + end +end + + +try + delete(handles.sliceview.d) +catch + []; +end + +handles.sliceview.d = image(slicedatafinal,'Tag','Transverse','Parent',sliceview.ax); + +% put slice positions +for ii=1:length(slicedata) + %text(nx*(floor((ii-1)/col))+1:nx*(1+floor((ii-1)/col)), ny*(mod(ii-1,col))+1:ny*(mod(ii-1,col)+1), num2str(slices(ii)), 'color', 'w'); + text(ny*(mod(ii-1,col))+1, nx*(floor((ii-1)/col))+1+20, num2str(slices(ii)), 'color', 'w'); +end + +set(sliceview.ax,'XTick',[],'YTick',[]); +axis(sliceview.ax, 'equal'); +set(sliceview.ax,'color','k'); +%setcolormap(colormp) +% for ii=1:length(slicedata) +% +% ax = subplot(row,col,ii); +% % ax = axes('Visible','on','DrawMode','fast','Parent',slice_fig,... +% % 'YDir','normal','Ydir','normal','XTick',[],'YTick',[]); +% set(ax,'Visible','on','DrawMode','fast','Parent',slice_fig,... +% 'YDir','normal','Ydir','normal','XTick',[],'YTick',[], 'color','k'); +% d = image(slicedata{ii},'Tag','Transverse','Parent',ax); +% set(ax,'XTick',[],'YTick',[]); +% title(pos{ii},'color','w') +% axis equal +% set(ax,'color','k'); +% +% %set(d,'Cdata',imgt); +% if mn*mx < 0 +% setcolormap('gray-hot-cold') +% elseif mx > 0 +% setcolormap('gray-hot'); +% else +% setcolormap('gray-cold') +% end +% end + +guidata(hObject, handles); + +function sliceViewRowChanged(hObject, eventdata) +global sliceview +sliceview.row = str2num(get(hObject,'string')); +CallBack_sliceViewPush(hObject, eventdata); + +function sliceViewColChanged(hObject, eventdata) +global sliceview +sliceview.col = str2num(get(hObject,'string')); +CallBack_sliceViewPush(hObject, eventdata); + +function sliceViewSpacingChanged(hObject, eventdata) +global sliceview +sliceview.spacing = str2num(get(hObject,'string')); +CallBack_sliceViewPush(hObject, eventdata); + +function sliceViewPageChangedN(hObject, eventdata) +global sliceview +sliceview.page = sliceview.page + 1; +CallBack_sliceViewPush(hObject, eventdata); + +function sliceViewPageChangedP(hObject, eventdata) +global sliceview +sliceview.page = sliceview.page - 1; +CallBack_sliceViewPush(hObject, eventdata); + +function sliceViewTypeChanged(hObject, eventdata) +global sliceview +type = get(hObject,'value'); +if(type == 1) + sliceview.viewtype = 't'; +elseif(type == 2) + sliceview.viewtype = 'c'; +else + sliceview.viewtype = 's'; +end +%sliceview.data = {{},{},{}}; +%sliceview.slices = {[],[],[]}; +sliceview.page = 0; +CallBack_sliceViewPush(hObject, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get slice view data +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [slicedata, colormp, slices] = cuixu_getSliceViewData(viewtype,row,col, spacing,page) + +global sliceview + + +slicedata = {}; +pos = {}; +slices = -80+(page-1)*spacing*col:spacing:100+(page)*spacing; + +if(isempty(slices)) + colormp = ''; + return +end + +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +kk = 1; +for slice = slices + if(kk > row*col) + slices = slices(1:kk-1); + break; + end + +if(viewtype == 's') + cent(2) = -slice; + postmp = find(slice - sliceview.slices{2} == 0); + if(~isempty(postmp)) + slicedata{kk} = sliceview.data{2}{postmp(1)}; + kk = kk+1; + continue; + end +elseif(viewtype == 't') + cent(3) = slice; + postmp = find(slice - sliceview.slices{1} == 0); + if(~isempty(postmp)) + slicedata{kk} = sliceview.data{1}{postmp(1)}; + kk = kk+1; + continue; + end +elseif(viewtype == 'c') + cent(1) = slice; + postmp = find(slice - sliceview.slices{3} == 0); + if(~isempty(postmp)) + slicedata{kk} = sliceview.data{3}{postmp(1)}; + kk = kk+1; + continue; + end +end + +if(viewtype == 's') + +for i = 1 + M = st.vols{i}.premul*st.vols{i}.mat; + + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + + + ok=1; + + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgc = max(imgc,mn); imgc = min(imgc,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + + if ~isempty(imgc), + tmp = imgc(isfinite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgc = imgc*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + + + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(isfinite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + %figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + % redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgc = scaletocmap(imgc,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wc = zeros(size(imgc)); + + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + + cimgc = zeros(size(imgc)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpc(tmpc(:)mx) = mx; + tmpc = (tmpc-mn)/(mx-mn); + tmpc(~isfinite(tmpc)) = 0; + + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + + wc = wc + tmpc; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + + imgc(imgc<0)=0; imgc(imgc>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgc = imgc*scal+dcoff; + end; + +% set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); +% set(st.vols{i}.ax{1}.lx,'HitTest','off',... +% 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{1}.ly,'HitTest','off',... +% 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); +% set(st.vols{i}.ax{2}.lx,'HitTest','off',... +% 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{2}.ly,'HitTest','off',... +% 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); +% if st.mode ==0, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); +% else, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); +% end; + + + end; +end; + +elseif(viewtype == 't') + +for i = 1 + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(isfinite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(isfinite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + %figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + % redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); +% +% redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpt(~isfinite(tmpt)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + + wt = wt + tmpt; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + %redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + end; + +% set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); +% set(st.vols{i}.ax{1}.lx,'HitTest','off',... +% 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{1}.ly,'HitTest','off',... +% 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); +% set(st.vols{i}.ax{2}.lx,'HitTest','off',... +% 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{2}.ly,'HitTest','off',... +% 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); +% if st.mode ==0, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); +% else, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); +% end; + + + end; +end; + +elseif(viewtype == 'c') + +for i = 1 + M = st.vols{i}.premul*st.vols{i}.mat; + + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgs = log(imgs-min(imgs(:))); + warning on + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + + if ~isempty(imgs), + tmp = imgs(isfinite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(isfinite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + %figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + % redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + ws = zeros(size(imgs)); + + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + + tmps(tmps(:)mx) = mx; + + tmps = (tmps-mn)/(mx-mn); + + tmps(~isfinite(tmps)) = 0; + + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgs = imgs*scal+dcoff; + end; + +% set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); +% set(st.vols{i}.ax{1}.lx,'HitTest','off',... +% 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{1}.ly,'HitTest','off',... +% 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); +% set(st.vols{i}.ax{2}.lx,'HitTest','off',... +% 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{2}.ly,'HitTest','off',... +% 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); +% +% set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); +% if st.mode ==0, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); +% else, +% set(st.vols{i}.ax{3}.lx,'HitTest','off',... +% 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); +% set(st.vols{i}.ax{3}.ly,'HitTest','off',... +% 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); +% end; + + end; +end; + +end + + + +if(viewtype == 's') + slicedata{kk} = flipdim(imgc,1); +elseif(viewtype == 't') + slicedata{kk} = flipdim(flipdim(permute(imgt,[2,1,3]),1),2); +elseif(viewtype == 'c') + slicedata{kk} = flipdim(imgs,1); +end +pos{kk} = slice; +kk = kk+1; +end +if(isempty(sliceview.colormap)) + if mn*mx < 0 + colormp = 'gray-hot-cold'; + elseif mx > 0 + colormp = 'gray-hot'; + else + colormp = 'gray-cold'; + end + sliceview.colormap = colormp; +else + colormp = sliceview.colormap; +end + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% reslice push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_reslicePush(hObject, eventdata) + +handles = guidata(hObject); + +if findstr('SPM2',spm('ver')) + p = spm_get([],'*.img','Select the image(s) you want to reslice'); +else%if findstr('SPM5',spm('ver')) + p = spm_select([0:200],'IMAGE','Select the image(s) you want to reslice'); +end +if findstr('SPM2',spm('ver')) + target = spm_get([1],'*.img','Select the space-defining image'); +else%if findstr('SPM5',spm('ver')) + target = spm_select([1],'IMAGE','Select the space-defining image'); +end + +m = size(p,2); +n = length(target); +target1 = target; +template = target1; +if m>n + target1 = [template blanks(m-n)]; +else + p = [p repmat(blanks(n-m), size(p,1),1)]; +end +P = [target1; p]; +flags = struct('interp',1,'mask',0,'mean',0,'which',1,'wrap',[0 0 0]'); +tic;spm_reslice(P, flags);toc; + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commonRegion push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_commonRegionPush(hObject, eventdata) +handles = guidata(hObject); +if ~isfield(handles,'TF') | length(handles.TF)<=1 + %msgbox('Two or more images need to be loaded to find the common region.', 'info'); + set(handles.infoTextBox, 'string', 'Two or more images need to be loaded to find the common region.'); + beep + return; +end + +common = handles.currentDisplayMNI{1}; +for ii=2:length(handles.TF) + common = intersect(common, handles.currentDisplayMNI{ii}, 'rows'); +end + +if isempty(common) + %msgbox('No common region found.', 'info'); + set(handles.infoTextBox, 'string', 'No common region found.'); + beep + return; +end + +tmpMNI = cell2mat(handles.currentDisplayMNI'); +tmpIntensity = cell2mat(handles.currentDisplayIntensity'); +intensity = zeros(size(common,1),1); + +for ii=1:size(common,1) + pos = find(abs(tmpMNI(:,1)-common(ii,1))<0.1 & abs(tmpMNI(:,2)-common(ii,2))<0.1 & abs(tmpMNI(:,3)-common(ii,3))<0.1); + intensity(ii) = 1;%max(abs(tmpIntensity(pos))); %2009/11/18 + %intensity(ii) = prod(tmpIntensity(pos)); %2009/11/18 comment +end + +common = [common; cor2mni([1 1 1], handles.M{1}); cor2mni([1 1 2], handles.M{1})]; +intensity = [intensity; 0; 1.5]; +%intensity = max(intensity) * ones(size(intensity)) + randn(size(intensity))/10; + +handles.currentDisplayMNI = {common}; +handles.currentDisplayIntensity = {intensity}; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% if isfield(handles,'hLegend') +% try +% set(cell2mat(handles.hLegend'),'visible',{'off'}); +% end +% end +guidata(hObject, handles); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% small volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_smallVolume(hObject, eventdata) +handles = guidata(hObject); + +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; +xSPM.uc = [4.7070 4.2941 338 338]; +xSPM.Pc = [0.0000 0.0000 0.0000 0.0668 0.1401 0.1723 0.1723 0.2412 0.2723 0.3092 0.5687 0.5687 0.7008 0.7008]; +xSPM.Pp = [0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0001 0.0005 0.0005 0.0015 0.0107 0.0121 0.0123 0.0383 0.0435 0.1019 0.1955 0.2257 0.2966 0.5612 0.6060 0.7725 0.9944]; + + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(handles.intensity{1}, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(handles.intensity{1}, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-handles.intensity{1}, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-handles.intensity{1}, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((handles.intensity{1}), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((handles.intensity{1}), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +else%if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + %warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); + warndlg('You must input SPM.mat.', 'SPM.mat missing'); + return; +end + +if findstr('SPM2',spm('ver')) + warndlg('Small volume correction does not work in spm 2', 'spm 2'); + return; +elseif findstr('SPM5',spm('ver')) + spm_VOI(SPM,xSPM,handles.hReg); +elseif findstr('SPM8',spm('ver')) + spm_VOI8(SPM,xSPM,handles.hReg); +end + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_VOI, for spm5, modified by Xu Cui, 2011/03/01 +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function TabDat = spm_VOI(SPM,xSPM,hReg) +% List of local maxima and adjusted p-values for a small Volume of Interest +% FORMAT TabDat = spm_VOI(SPM,xSPM,hReg) +% +% SPM - structure containing analysis details (see spm_spm) +% +% xSPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {resels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .DIM - image dimensions {voxels} - column vector +% .Vspm - Mapped statistic image(s) +% .Ps - P vlues in searched voxels (for FDR) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% TabDat - Structure containing table data +% - see spm_list for definition +% +%_______________________________________________________________________ +% +% spm_VOI is called by the SPM results section and takes variables in +% SPM to compute p-values corrected for a specified volume of interest. +% +% The volume of interest may be defined as a box or sphere centred on +% the current voxel or by a mask image. +% +% If the VOI is defined by a mask this mask must have been defined +% independently of the SPM (e.g.using a mask based on an orthogonal +% contrast) +% +% External mask images should be in the same orientation as the SPM +% (i.e. as the input used in stats estimation). The VOI is defined by +% voxels with values greater than 0. +% +% FDR computations are similarly resticted by the small search volume +% +% See also: spm_list +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% Karl Friston +% $Id: spm_VOI.m 112 2005-05-04 18:20:52Z john $ + + +%-Parse arguments +%----------------------------------------------------------------------- +if nargin < 2, error('insufficient arguments'), end +if nargin < 3, hReg = []; end + +Num = 16; % maxima per cluster +Dis = 04; % distance among maxima (mm) + +%-Title +%----------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Small Volume Correction']); + +%-Get current location {mm} +%----------------------------------------------------------------------- +%xyzmm = spm_results_ui('GetCoords'); +xyzmm = spm_XYZreg('GetCoords',hReg);% added by xu cui + +% added by xu cui, open a figure so users can input parameters +f = figure('unit','normalized','position',[0.1 0.1 0.3 0.3]); + +%-Specify search volume +%----------------------------------------------------------------------- +str = sprintf(' at [%.0f,%.0f,%.0f]',xyzmm(1),xyzmm(2),xyzmm(3)); +SPACE = spm_input('Search volume...',-1,'m',... + {['Sphere',str],['Box',str],'Image'},['S','B','I']); + +% voxels in entire search volume {mm} +%----------------------------------------------------------------------- +XYZmm = SPM.xVol.M(1:3,:)*[SPM.xVol.XYZ; ones(1, SPM.xVol.S)]; +Q = ones(1,size(xSPM.XYZmm,2)); +O = ones(1,size( XYZmm,2)); +FWHM = xSPM.FWHM; + + +switch SPACE + + case 'S' %-Sphere + %--------------------------------------------------------------- + D = spm_input('radius of VOI {mm}',-2); + str = sprintf('%0.1fmm sphere',D); + j = find(sum((xSPM.XYZmm - xyzmm*Q).^2) <= D^2); + k = find(sum(( XYZmm - xyzmm*O).^2) <= D^2); + D = D./xSPM.VOX; + + + case 'B' %-Box + %--------------------------------------------------------------- + D = spm_input('box dimensions [k l m] {mm}',-2); + str = sprintf('%0.1f x %0.1f x %0.1f mm box',D(1),D(2),D(3)); + j = find(all(abs(xSPM.XYZmm - xyzmm*Q) <= D(:)*Q/2)); + k = find(all(abs( XYZmm - xyzmm*O) <= D(:)*O/2)); + D = D./xSPM.VOX; + + + case 'I' %-Mask Image + %--------------------------------------------------------------- + Msk = spm_select(1,'image','Image defining search volume'); + D = spm_vol(Msk); + str = sprintf('image mask: %s',spm_str_manip(Msk,'a30')); + VOX = sqrt(sum(D.mat(1:3,1:3).^2)); + FWHM = FWHM.*(xSPM.VOX./VOX); + XYZ = D.mat \ [xSPM.XYZmm; ones(1, size(xSPM.XYZmm, 2))]; + j = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + XYZ = D.mat \ [ XYZmm; ones(1, size( XYZmm, 2))]; + k = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + +end + +xSPM.S = length(k); +xSPM.R = spm_resels(FWHM,D,SPACE); +xSPM.Z = xSPM.Z(j); +xSPM.XYZ = xSPM.XYZ(:,j); +xSPM.XYZmm = xSPM.XYZmm(:,j); +xSPM.Ps = xSPM.Ps(k); + +%-Tabulate p values +%----------------------------------------------------------------------- +str = sprintf('search volume: %s',str); +if any(strcmp(SPACE,{'S','B'})) + str = sprintf('%s at [%.0f,%.0f,%.0f]',str,xyzmm(1),xyzmm(2),xyzmm(3)); +end + +TabDat = spm_list('List',xSPM,hReg,Num,Dis,str); + +%-Reset title +%----------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Results']); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_VOI, for spm8, modified by Xu Cui, 2011/02/28 +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function TabDat = spm_VOI8(SPM,xSPM,hReg) +% List of local maxima and adjusted p-values for a small Volume of Interest +% FORMAT TabDat = spm_VOI(SPM,xSPM,hReg) +% +% SPM - structure containing analysis details (see spm_spm) +% +% xSPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {resels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .DIM - image dimensions {voxels} - column vector +% .Vspm - Mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for voxel FDR) +% .Pp - uncorrected P values of peaks (for peak FDR) +% .Pc - uncorrected P values of cluster extents (for cluster FDR) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% TabDat - Structure containing table data +% - see spm_list for definition +% +%__________________________________________________________________________ +% +% spm_VOI is called by the SPM results section and takes variables in +% SPM to compute p-values corrected for a specified volume of interest. +% +% The volume of interest may be defined as a box or sphere centred on +% the current voxel or by a mask image. +% +% If the VOI is defined by a mask this mask must have been defined +% independently of the SPM (e.g.using a mask based on an orthogonal +% contrast) +% +% External mask images should be in the same orientation as the SPM +% (i.e. as the input used in stats estimation). The VOI is defined by +% voxels with values greater than 0. +% +% FDR computations are similarly resticted by the small search volume +% +% See also: spm_list +%__________________________________________________________________________ +% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging + +% Karl Friston +% $Id: spm_VOI.m 2782 2009-02-24 18:53:13Z guillaume $ + + +%-Parse arguments +%-------------------------------------------------------------------------- +if nargin < 2, error('insufficient arguments'), end +if nargin < 3, hReg = []; end + +Num = 16; % maxima per cluster +Dis = 04; % distance among maxima (mm) + +%-Title +%-------------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Small Volume Correction']); + +%-Get current location {mm} +%-------------------------------------------------------------------------- +%xyzmm = spm_results_ui('GetCoords'); +xyzmm = spm_XYZreg('GetCoords',hReg);% added by xu cui + +% added by xu cui, open a figure so users can input parameters +f = figure('unit','normalized','position',[0.1 0.1 0.3 0.3]); + +%-Specify search volume +%-------------------------------------------------------------------------- +str = sprintf(' at [%.0f,%.0f,%.0f]',xyzmm(1),xyzmm(2),xyzmm(3)); +SPACE = spm_input('Search volume...',-1,'m',... + {['Sphere',str],['Box',str],'Image'},['S','B','I']); + +% voxels in entire search volume {mm} +%-------------------------------------------------------------------------- +XYZmm = SPM.xVol.M(1:3,:)*[SPM.xVol.XYZ; ones(1, SPM.xVol.S)]; +Q = ones(1,size(xSPM.XYZmm,2)); +O = ones(1,size( XYZmm,2)); +FWHM = xSPM.FWHM; + +switch SPACE + + case 'S' %-Sphere + %---------------------------------------------------------------------- + D = spm_input('radius of VOI {mm}',-2); + str = sprintf('%0.1fmm sphere',D); + j = find(sum((xSPM.XYZmm - xyzmm*Q).^2) <= D^2); + k = find(sum(( XYZmm - xyzmm*O).^2) <= D^2); + D = D./xSPM.VOX; + + + case 'B' %-Box + %---------------------------------------------------------------------- + D = spm_input('box dimensions [k l m] {mm}',-2); + if length(D)~=3, D = ones(1,3)*D(1); end + str = sprintf('%0.1f x %0.1f x %0.1f mm box',D(1),D(2),D(3)); + j = find(all(abs(xSPM.XYZmm - xyzmm*Q) <= D(:)*Q/2)); + k = find(all(abs( XYZmm - xyzmm*O) <= D(:)*O/2)); + D = D./xSPM.VOX; + + + case 'I' %-Mask Image + %---------------------------------------------------------------------- + Msk = spm_select(1,'image','Image defining search volume'); + D = spm_vol(Msk); + str = strrep(spm_str_manip(Msk,'a30'),'\','\\'); + str = strrep(str,'^','\^'); str = strrep(str,'_','\_'); + str = strrep(str,'{','\{'); str = strrep(str,'}','\}'); + str = sprintf('image mask: %s',str); + VOX = sqrt(sum(D.mat(1:3,1:3).^2)); + FWHM = FWHM.*(xSPM.VOX./VOX); + XYZ = D.mat \ [xSPM.XYZmm; ones(1, size(xSPM.XYZmm, 2))]; + j = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + XYZ = D.mat \ [ XYZmm; ones(1, size( XYZmm, 2))]; + k = find(spm_sample_vol(D, XYZ(1,:), XYZ(2,:), XYZ(3,:),0) > 0); + +end + +xSPM.S = length(k); +xSPM.R = spm_resels(FWHM,D,SPACE); +xSPM.Z = xSPM.Z(j); +xSPM.XYZ = xSPM.XYZ(:,j); +xSPM.XYZmm = xSPM.XYZmm(:,j); + +%-Restrict FDR to the search volume +%-------------------------------------------------------------------------- +df = xSPM.df; +STAT = xSPM.STAT; +DIM = xSPM.DIM; +R = xSPM.R; +n = xSPM.n; +Z = xSPM.Z; +u = xSPM.u; +S = xSPM.S; + +try, xSPM.Ps = xSPM.Ps(k); end +[up, xSPM.Pp] = spm_uc_peakFDR(0.05,df,STAT,R,n,Z,SPM.xVol.XYZ(:,k),u); +try % if STAT == 'T' + V2R = 1/prod(xSPM.FWHM(DIM>1)); + [uc, xSPM.Pc, ue] = spm_uc_clusterFDR(0.05,df,STAT,R,n,Z,SPM.xVol.XYZ(:,k),V2R,u); +catch + uc = NaN; + ue = NaN; + xSPM.Pc = []; +end +uu = spm_uc(0.05,df,STAT,R,n,S); +xSPM.uc = [uu up ue uc]; + +%-Tabulate p values +%-------------------------------------------------------------------------- +str = sprintf('search volume: %s',str); +if any(strcmp(SPACE,{'S','B'})) + str = sprintf('%s at [%.0f,%.0f,%.0f]',str,xyzmm(1),xyzmm(2),xyzmm(3)); +end + +TabDat = spm_list8('List',xSPM,hReg,Num,Dis,str); + +%-Reset title +%-------------------------------------------------------------------------- +spm('FigName',['SPM{',xSPM.STAT,'}: Results']); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_volumePush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; +xSPM.uc = [4.7070 4.2941 338 338]; +xSPM.Pc = [0.0000 0.0000 0.0000 0.0668 0.1401 0.1723 0.1723 0.2412 0.2723 0.3092 0.5687 0.5687 0.7008 0.7008]; +xSPM.Pp = [0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0001 0.0001 0.0001 0.0005 0.0005 0.0015 0.0107 0.0121 0.0123 0.0383 0.0435 0.1019 0.1955 0.2257 0.2966 0.5612 0.6060 0.7725 0.9944]; + +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(handles.intensity{1}, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(handles.intensity{1}, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-handles.intensity{1}, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-handles.intensity{1}, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((handles.intensity{1}), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((handles.intensity{1}), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +else%if findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); +end + +if findstr('SPM8',spm('ver')) + spm_list8('List',xSPM,handles.hReg); +else%if findstr('SPM5',spm('ver')) + spm_list('List',xSPM,handles.hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_displayPush(hObject, eventdata) +handles = guidata(hObject); +spm_image('init', handles.imageFileName); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% all in one +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allinonePush(hObject, eventdata) +try + if findstr('SPM2',spm('ver')) + P = spm_get([0:100],'*IMAGE','Select image files'); + else%if findstr('SPM5',spm('ver')) + P = spm_select(Inf,'image','Select image files'); + end + +catch + return; +end +if isempty(P) + return +end + +handles = guidata(hObject); +%if ~isfield(handles,'hReg') | ~isfield(handles,'hSection') | ~isfield(handles,'hcolorbar') + tmp = [0 0 0]; + [handles.hReg, handles.hSection, handles.hcolorbar] = Draw(tmp([],:), [], hObject, handles); + %end + +colors = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +for ii=1:size(P,1) + thisfilename = deblank(P(ii,:)); + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); + cor = mni2cor(handles.mni, handles.M); + spm_orthviews('addcolouredblobs',1,cor',handles.intensity',handles.M,colors(mod(ii,6)+1,:)); +end +spm_orthviews('Redraw'); + +guidata(hObject, handles); + +% contents = get(handles.sectionViewListbox,'String'); +% currentsel = contents{get(handles.sectionViewListbox,'Value')}; +% sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +% +% % spm_image('init', sectionViewTargetFile); +% % spm_image('addblobs'); +% % return + +% guidata(hObject, handles); +% load xSPM; +% VOL.XYZ = xSPM.XYZ; +% VOL.Z = xSPM.Z; +% VOL.M = handles.M; + +%addcolouredimage(handles.hSection, '333.img',[1 0 1]); +% uigetfiles +% nblobs = 4; +% for i=1:nblobs, +% %[SPM,VOL] = spm_getSPM; +% %c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); +% c = i; +% VOL.XYZ = ceil(rand(3,20)*20); +% VOL.Z = randn(1,20); +% VOL.M = handles.M; +% colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +% spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); +% end; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPush(hObject, eventdata) +handles = guidata(hObject); + +tobeoverlay = deblank(get(handles.overlayEdit, 'string')); + +if isempty(tobeoverlay) + return; +end + +tobeoverlay = str2cell(tobeoverlay, ' '); +if isnumeric(tobeoverlay{1}) + if length(tobeoverlay{1})>1 + errordlg(['Your input, ' deblank(get(handles.overlayEdit, 'string')) ', seems coincide with a matlab constant.'], 'error'); + return + end + for ii=1:length(tobeoverlay) + tobeoverlay{ii} = num2str(tobeoverlay{ii}); + end +end +fn = fieldnames(handles.wholeMaskMNIAll); +for ii=1:length(tobeoverlay) + pos{ii} = []; + for jj=1:length(fn) +% x = []; +% if ~isempty(str2num(tobeoverlay{ii})) +% y = str2cell(fn{jj},'_'); +% for kk=1:length(y) +% x = isequal(tobeoverlay{ii}, y{kk}); +% if x; break;end; +% end +% if x==0; x = []; end; +% else +% x = findstr(lower(tobeoverlay{ii}), lower(fn{jj})); +% end + if strcmp(tobeoverlay{ii}, fn{jj}) + pos{ii} = [pos{ii} jj]; + end + end +end +common = pos{1}; +for ii=2:length(pos) + common = intersect(common, pos{ii}); +end + +if isempty(common) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return +end + +mask = []; +for ii=1:length(common) + eval(['mask = [mask; handles.wholeMaskMNIAll.' fn{common(ii)} '];']); +end + +if isempty(mask) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return; +end + +try + handles.mni; +catch + delete(gcf); + xjview(mask); + return; +end + +handles.imageFileName = [handles.imageFileName, {deblank(get(handles.overlayEdit, 'string'))}]; +handles.M = [handles.M, {handles.M{1}}]; +handles.DIM = [handles.DIM, {handles.DIM{1}}]; +handles.currentDisplayMNI = [handles.currentDisplayMNI, {mask}]; +m = max(abs(cell2mat(handles.currentDisplayIntensity'))); +if ~isempty(m) + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {-2*m*ones(size(mask,1),1)}]; +else + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {ones(size(mask,1),1)}]; +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_overlayPush(handles.overlayPush, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region popup +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPop(hObject, eventdata) +handles = guidata(hObject); +names = get(hObject, 'string'); +value = get(hObject, 'value'); +set(handles.overlayEdit, 'string', names{value}); +CallBack_overlayEdit(handles.overlayEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% search xBrain.org and other databases +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchPush(hObject, eventdata) + +try + handles = guidata(hObject); + searchContent = get(handles.searchContentEdit,'string'); + searchEngine = get(handles.searchEnginePop,'value'); + xbrainSearchField = 'region'; + if isempty(deblank(searchContent)) + xyz = spm_XYZreg('GetCoords',handles.hReg); + handles.currentxyz = xyz'; + searchContent = num2str(xyz'); + set(handles.searchContentEdit,'string',searchContent); + guidata(hObject, handles); + xbrainSearchField = 'mni or tal&mnidistance=20'; + end + + if searchEngine == 1 + urlstr = ['http://people.hnl.bcm.tmc.edu/cuixu/cgi-bin/bmd/paper.pl?search_content=' searchContent '&search_field=' xbrainSearchField]; + elseif searchEngine == 2 + urlstr = ['http://scholar.google.com/scholar?q=%22' searchContent '%22']; + elseif searchEngine == 3 + urlstr = ['http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=PureSearch&db=pubmed&details_term=%22' searchContent '%22']; + elseif searchEngine == 4 + urlstr = ['http://en.wikipedia.org/w/index.php?search=%22' searchContent '%22']; + end +catch + urlstr = 'http://www.xbrain.org'; +end + +web(urlstr); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% control panel on or off +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function controlHide(handles, status) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get multiple values from a string deliminated delim +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = str2cell(str, delim) +if ~exist('delim') + delim = '; '; +end + +[out{1},b] = strtok(str, delim); +ii = 2; +while ~isempty(b) + [out{ii},b] = strtok(b, delim); + ii = ii+1; +end + +for ii=1:length(out) + out2{ii} = str2num(out{ii}); + if isempty(out2{ii}) + return; + end +end + +for ii=1:length(out) + out{ii} = str2num(out{ii}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cell2str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function str = cell2str(acell, delim) +if ~exist('delim') + delim = ';'; +end + +str = []; + +if length(acell)==1 + if isstr(acell{1}) + str = acell{1}; + else + str = num2str(acell{1}); + end +else + for ii=1:length(acell) + if isstr(acell{ii}) + str = [str acell{ii}, delim ' ']; + else + str = [str num2str(acell{ii}), delim ' ']; + end + end + str(end-1:end)=[]; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cellmax, find max in each element, return a cell +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = cellmax(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end + +MAXX = []; +for ii=1:length(acell) + if strfind('abs',absolute) + MAXX = [MAXX max(abs(acell{ii}))]; + else + MAXX = [MAXX max(acell{ii})]; + end +end +MAXX = num2cell(MAXX); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% maxcell +%%% find max of all numbers in the whole cell, return a single value +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = maxcell(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end +MAXX = cellmax(acell, absolute); +MAXX = max(cell2mat(MAXX)); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% p2t +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = p2t(p, df, TF) +if ~iscell(p) + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = p2t(p{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% s2t, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = s2t(s, df, TF) + +if ~iscell(s) + p = 10^(-s); + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = s2t(s{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2p +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function p = t2p(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + end +else + for ii=1:length(t) + p{ii} = t2p(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2s, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = t2s(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + else + p = 0.1; + end + s = -log10(p); +else + s = {10}; + for ii=1:length(t) + s{ii} = t2s(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2mask +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mask = mni2mask(coords, targetfilename, intensity, M, DIM, templateFile, isMask) +% function mask = mni2mask(coords, targetfilename, intensity, templateFile) +% make mask from coordinates +% +% coords: a Nx3 column of 3-d coordinates in MNI +% space +% targetfilename: (optional) the image files to be written +% intensity: (optional) Nx1, the values of each coordinate. +% M: rotation matrix +% DIM: dimension +% templateFile: (optional) the templateFile from which we can get the right +% dimensions. +% isMask: if this variable exist and equal to 1, then all non-zero +% intensities will be set to 1 +% +% Xu Cui +% 2004/11/18 + +if ~exist('intensity') + intensity = ones(size(coords,1),1); +end +thistemplateFile = ''; +if exist('templateFile') + if ~isempty(templateFile) + thistemplateFile = templateFile; + end +end + +if isempty(thistemplateFile) + V.mat = [... + -4 0 0 84; ... + 0 4 0 -116; ... + 0 0 4 -56; ... + 0 0 0 1]; + V.dim = [41 48 35 16]; + V.dt = [4,0]; + if exist('M') + V.mat = M; + end + if exist('DIM') + V.dim = DIM; + if findstr('SPM2',spm('ver')) + V.dim(4) = 16; + end + end + V.fname = targetfilename; + V.descrip = 'our own image'; +else + V = spm_vol(templateFile); + V.fname = targetfilename; + if isfield(V, 'descrip') + V.descrip = ['my image from ' V.descrip]; + else + V.descrip = 'my own image'; + end +end + +thisismask = 0; +if exist('isMask') + if isMask == 1 + thisismask = 1; + end +end +if thisismask + V.descrip = 'my mask'; + intensity = ones(size(intensity)); +end + +O = zeros(V.dim(1),V.dim(2),V.dim(3)); + +coords = mni2cor(coords,V.mat); + + +for ii=1:size(coords,1) + O(coords(ii,1),coords(ii,2),coords(ii,3)) = intensity(ii); +end + +if exist('targetfilename') + V = spm_write_vol(V,O); +end + +mask = O; + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get image file information +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [imageFile,M,DIM,TF,df,mni,intensity] = getImageFile(thisfilename) +% function imageFile = getImageFile(filename) +% get the information of this/these image file(s) +% +% thisfilename: (optional) if doesn't give file name, then show a open file +% dialog +% imageFile: the full name of the selected file (if user pressed cancel, +% imageFile == 0 +% M: M matrix (rotation matrix) +% DIM: dimension +% TF: t test or f test? 'T' or 'F' +% df: degree of freedome +% mni: mni coord +% intensity: intensity of each mni coord +% +% Note: The returned variables are cellarrays. +% +% Xu Cui +% last revised: 2005-05-03 + +if nargin < 1 | isempty(thisfilename) + if findstr('SPM2',spm('ver')) + P0 = spm_get([0:100],'*IMAGE','Select image files'); + else%if findstr('SPM5',spm('ver')) + P0 = spm_select(Inf,'image','Select image files'); + end + +% try +% P0 = spm_get([0:100],'*IMAGE','Select image files'); +% catch +% P0 = []; +% [FileName,PathName] = uigetfile({'*.img';'*.IMG';'*.*'},'Select image files','MultiSelect','on'); +% if isstr(FileName) +% P0 = {fullfile(PathName, FileName)}; +% elseif iscellstr(FileName) +% for ii=1:length(FileName) +% P0{ii} = fullfile(PathName, FileName{ii}); +% end +% else +% P0 = []; +% end +% end + try + if isempty(P0) + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end + end + for ii=1:size(P0,1) + P{ii} = deblank(P0(ii,:)); + end +else + if isstr(thisfilename) + P = {thisfilename}; + elseif iscellstr(thisfilename) + P = thisfilename; + else + disp('Error: In getImageFile: I don''t understand the input.'); + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end +end + +global LEFTRIGHTFLIP_; + +for ii=1:length(P) + imageFile{ii} = P{ii}; + [cor{ii}, intensity{ii}, tmp{ii}, M{ii}, DIM{ii}, TF{ii}, df{ii}] = mask2coord(imageFile{ii}, 0); + if LEFTRIGHTFLIP_ == 1 + M{ii}(1,:) = -M{ii}(1,:); + end + mni{ii} = cor2mni(cor{ii}, M{ii}); +end + + + + + + + + + + + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuFindStructure +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [onelinestructure, cellarraystructure] = cuixuFindStructure(mni, DB) +% function [onelinestructure, cellarraystructure] = cuixuFindStructure(mni, DB) +% +% this function converts MNI coordinate to a description of brain structure +% in aal +% +% mni: the coordinates (MNI) of some points, in mm. It is Nx3 matrix +% where each row is the coordinate for one point +% LDB: the database. This variable is available if you load +% TDdatabase.mat +% +% onelinestructure: description of the position, one line for each point +% cellarraystructure: description of the position, a cell array for each point +% +% Example: +% cuixuFindStructure([72 -34 -2; 50 22 0], DB) +% +% Xu Cui +% 2007-11-20 +% + +N = size(mni, 1); + +% round the coordinates +mni = round(mni/2) * 2; + +T = [... + 2 0 0 -92 + 0 2 0 -128 + 0 0 2 -74 + 0 0 0 1]; + +index = mni2cor(mni, T); + +cellarraystructure = cell(N, length(DB)); +onelinestructure = cell(N, 1); + +for ii=1:N + for jj=1:length(DB) + graylevel = DB{jj}.mnilist(index(ii, 1), index(ii, 2),index(ii, 3)); + if graylevel == 0 + thelabel = 'undefined'; + else + if jj==length(DB); tmp = ' (aal)'; else tmp = ''; end + thelabel = [DB{jj}.anatomy{graylevel} tmp]; + end + cellarraystructure{ii, jj} = thelabel; + onelinestructure{ii} = [ onelinestructure{ii} ' // ' thelabel ]; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mask2coord +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [cor, intensity, cor_singlecolumn,M,DIM,TF,df] = mask2coord(mask, checkdimension) +% [cor, intensity, cor_singlecolumn] = mask2coord(mask, checkdimension) +% +% This is to retrieve the coordinate of a mask file, or a matrix of 3-D +% +% mask: an image file or a matrix (3-D), with some of the elements are +% non-zeros +% checkdimension: check if the dimension is checkdimension, if not, return empty +% matrix +% cor: a N*3 matrix, which each row a coordinate in matrix +% intensity: a N*1 matrix, which encodes the intensity of each voxel. +% cor_singlecolumn: a N*1 matrix, each row is the index in the matrix +% M: rotation matrix +% DIM: dimension +% TF: t test or f test? 'T','F' or [] +% df: degree of freedome for T/F test +% +% Example: +% mask = zeros(4,3,2); +% mask(1,2,1) = 1; +% mask(3,2,2) = 1; +% mask2coord(mask) +% +% mask2coord('spmT_0002.img') +% mask2coord('spmT_0002.img',[41 48 35]) +% +% Xu Cui +% 2004-9-20 +% last revised: 2005-04-30 + +if nargin < 2 + checkdimension = 0; +end + +if ischar(mask) + V = spm_vol(mask); + mask = spm_read_vols(V); + M = V.mat; + DIM = V.dim; + TF = 'T'; + T_start = strfind(V.descrip,'SPM{T_[')+length('SPM{T_['); + if isempty(T_start); T_start = strfind(V.descrip,'SPM{F_[')+length('SPM{F_['); TF='F'; end + if isempty(T_start) + TF=[]; df=[]; + else + T_end = strfind(V.descrip,']}')-1; + df = str2num(V.descrip(T_start:T_end)); + end +else + M = []; + TF = []; + df = []; +end + +dim = size(mask); +if length(checkdimension)==3 + if dim(1)~= checkdimension(1) | dim(2)~= checkdimension(2) | dim(3)~= checkdimension(3) + y = []; + disp('dimension doesn''t match') + return + end +end + +pos = find(mask~=0); +intensity = mask(pos); + +y = zeros(length(pos),3); + +y(:,3) = ceil(pos/(dim(1)*dim(2))); +pos = pos - (y(:,3)-1)*(dim(1)*dim(2)); +y(:,2) = ceil(pos/dim(1)); +pos = pos - (y(:,2)-1)*(dim(1)); +y(:,1) = pos; + +cor = y; +cor_singlecolumn = pos; +DIM = dim; +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2cor +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function coordinate = mni2cor(mni, T) +% function coordinate = mni2cor(mni, T) +% convert mni coordinate to matrix coordinate +% +% mni: a Nx3 matrix of mni coordinate +% T: (optional) transform matrix +% coordinate is the returned coordinate in matrix +% +% caution: if T is not specified, we use: +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% + +if isempty(mni) + coordinate = []; + return; +end + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +coordinate = [mni(:,1) mni(:,2) mni(:,3) ones(size(mni,1),1)]*(inv(T))'; +coordinate(:,4) = []; +coordinate = round(coordinate); +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cor2mni +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mni = cor2mni(cor, T) +% function mni = cor2mni(cor, T) +% convert matrix coordinate to mni coordinate +% +% cor: an Nx3 matrix +% T: (optional) rotation matrix +% mni is the returned coordinate in mni space +% +% caution: if T is not given, the default T is +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% last revised: 2005-04-30 + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +cor = round(cor); +mni = T*[cor(:,1) cor(:,2) cor(:,3) ones(size(cor,1),1)]'; +mni = mni'; +mni(:,4) = []; +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% draw +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = Draw(mniCoord, intensity, hObject, handles) + +try + delete(handles.hcolorbar); +end +try + delete(handles.hReg); +end +try + delete(handles.hSection); +end +try + cla(handles.glassViewAxes); +end + +try + H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); + un = cellstr(get(H,'Units')); + pos = get(H,'position'); + + for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 + delete(H(ii)); + end + end +end + +sectionViewTargetFile = handles.sectionViewTargetFile; +rendStyle = get(handles.renderStylePop,'value'); +if(rendStyle == 1) + rendStyle = 'new'; +else + rendStyle = 'old'; +end + + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end + if max(intensity)*min(intensity) < 0 + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + else + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,abs(intensity),sectionViewTargetFile,hObject,handles); + end + + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(rendStyle, mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:) ); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(rendStyle, mniCoord, abs(intensity)); end + end + end +else % multiple input? yes + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + + mniCoordtmp=[]; + intensitytmp=[]; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(rendStyle, mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(rendStyle, mniCoord, abs(intensity)); end + end + end + +end + +try + spm_XYZreg('SetCoords',handles.currentxyz',hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuSectionView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord, intensity, targetFile, hObject,handles) +% function h = cuixuSectionView(mniCoord, intensity) +% This is to project your coordinate to section view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% a special feature of this function is: it automatically seperate the +% negative and positive intensity and use hot and cold color to represent +% them. +% +% h: the returned handle for the axes +% +% SEE ALSO: cuixuView cuixuGlassView cuixuRenderView +% +% Xu Cui +% 2004/11/11 + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + multiple = 0; + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end +else + multiple = 1; + mniCoordtmp = []; + intensitytmp = []; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + % for multiple input + cSPM{ii}.XYZ = mni2cor(mniCoord{ii}, handles.M{ii}); + cSPM{ii}.XYZ = cSPM{ii}.XYZ'; + cSPM{ii}.Z = abs(intensity{ii}); + cSPM{ii}.M = handles.M{ii}; + cSPM{ii}.DIM = handles.DIM{ii}'; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; +end + +SPM.XYZ = mni2cor(mniCoord, handles.M); +SPM.XYZ = SPM.XYZ'; +SPM.Z = intensity; +SPM.M = handles.M; +SPM.DIM = handles.DIM'; + +%%%%%%%%%%%%%%% Reg %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +handles.colormap = colormap; + +coor = mniCoord; +xSPM = SPM; +xSPM.XYZmm = mniCoord'; +axes(handles.glassViewAxes) +WS = spm('WinScale'); +FS = spm('FontSizes'); + +Finter = gcf; +hReg = uicontrol(Finter,'Style','Frame','Position',[60 100 300 300].*WS,... + 'Visible','off'); +[hReg,xyz] = spm_XYZreg('InitReg',hReg,xSPM.M,xSPM.DIM,[0;0;0]); + +hFxyz = spm_results_ui('DrawXYZgui',xSPM.M,xSPM.DIM,xSPM,xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +hMIPax =gca ; +setcolormap('gray'); + +hMIPax = spm_mip_ui(xSPM.Z,coor',xSPM.M,xSPM.DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); + +colormap(handles.colormap); +setcolormap('gray-hot'); + +if isempty(handles.M) + spm_XYZreg('SetReg',handles.structureEdit,hReg); +else + set(handles.structureEdit, 'UserData', struct('hReg',hReg,'M',handles.M,'D', handles.DIM,'xyx',[0 0 0])); +end + +spm_XYZreg('Add2Reg',hReg,handles.structureEdit,@CallBack_structureEdit); + +%%%%%%%%%%%%%%% Reg end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if multiple == 0 + [hgraph, hSection, hcolorbar] = spm_sections(SPM,hReg,targetFile,handles.sectionViewPosition); +else + [hgraph, hSection, hcolorbar] = spm_sections(cSPM,hReg,targetFile,handles.sectionViewPosition); +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_sections +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [Fgraph, hMe, hcolorbar] = spm_sections(SPM,hReg,targetFile,sectionViewPosition) +% rendering of regional effects [SPM{Z}] on orthogonal sections +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = gcf; + +spms = fullfile(spm('dir'),'canonical', 'single_subj_T1.mnc'); +if exist('targetFile') + spms = targetFile; +end + +spm_orthviews('Reset'); +global st +st.fig = Fgraph; +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; + +spm_orthviews('Image',spms,sectionViewPosition); % position +spm_orthviews('MaxBB'); +spm_orthviews('register',hReg); +if ~iscell(SPM)0 + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +elseif length(SPM) == 1 + SPM = SPM{1}; + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +else + colors = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],20,1); + for ii=1:length(SPM) + spm_orthviews('addcolouredblobs',1,SPM{ii}.XYZ, SPM{ii}.Z, SPM{ii}.M, colors(ii,:)); + end +end +spm_orthviews('Redraw'); + +hMe = st.registry.hMe; +try + hcolorbar = st.vols{1}.blobs{1}.cbar; +catch + hcolorbar = 0; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuRenderView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function h = cuixuRenderView(style, mniCoord, intensity, varargin) +% function h = cuixuRenderView(style, mniCoord1, intensity1, mniCoord2, intensity2, mniCoord3, intensity3) +% This is to project your coordinate to render view +% +% style: either 'new' or 'old' +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% You can input 1, 2, or 3 pairs of coordinates and intensity. +% +% h: the returned handle for the figure +% +% Xu Cui +% 2004/11/11 + +global M_; +global DIM_; + +if nargin < 4 + dat.XYZ = mni2cor(mniCoord, M_); + dat.XYZ = dat.XYZ'; + if nargin < 2 + dat.t = ones(size(mniCoord,1),1); + else + dat.t = intensity; + end + dat.mat = M_; + dat.dim = DIM_; +else + if mod(nargin+1,2) ~=0 + disp('You should put even number of parameters.') + return; + end + for ii=1:(2+length(varargin))/2 + if ii==1 + dat(ii).XYZ = mni2cor(mniCoord, M_); + dat(ii).t = intensity; + else + dat(ii).XYZ = mni2cor(varargin{2*(ii-1)-1}, M_); + dat(ii).t = varargin{2*(ii-1)}; + end + dat(ii).XYZ = dat(ii).XYZ'; + dat(ii).mat = M_; + dat(ii).dim = DIM_; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_render +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +if strcmp(style, 'old') + brt = nan; +else + brt = 1; +end +h = spm_render(dat,brt,fullfile(spm('dir'), 'rend', 'render_single_subj.mat')); + +function Fgraph = spm_render(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +% get surface +%----------------------------------------------------------------------- +if nargin < 3, + rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); +end; + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if isfinite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + + + +% Perform the rendering +%======================================================================= +spm('Pointer','Watch') + +load(rendfile); + +if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; +end; + +if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; +for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; +end; +if showbar, spm_progress_bar('Clear'); end; + +if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + +mx = zeros(length(rend),1)+eps; +mn = zeros(length(rend),1); + +for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~isfinite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~isfinite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~isfinite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if isfinite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; +end; + +mxmx = max(mx); +mnmn = min(mn); + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = gcf;%spm_figure('GetWin','Graphics'); +%spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +hght = 0.25; +width = 0.25; +x0 = 0.5; +y0 = 0.01; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 0.5, hght],'Visible','off'); +%ax=axes; +%image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~isfinite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + X = cell(3,1); + for j=1:length(rend{i}.data), + X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + end + for j=(length(rend{i}.data)+1):3 + X{j}=zeros(size(X{1})); + end + + rgb = zeros([size(ren) 3]); + tmp = ren.*max(1-X{1}-X{2}-X{3},0); + rgb(:,:,1) = tmp + X{1}; + rgb(:,:,2) = tmp + X{2}; + rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + end; +end; + +spm('Pointer') +return; + +function [P,p,Em,En,EN] = spm_P(c,k,Z,df,STAT,R,n,S) +% Returns the [un]corrected P value using unifed EC theory +% FORMAT [P p Em En EN] = spm_P(c,k,Z,df,STAT,R,n,S) +% +% c - cluster number +% k - extent {RESELS} +% Z - height {minimum over n values} +% df - [df{interest} df{error}] +% STAT - Statistical field +% 'Z' - Gaussian field +% 'T' - T - field +% 'X' - Chi squared field +% 'F' - F - field +% 'P' - Posterior probability +% R - RESEL Count {defining search volume} +% n - number of component SPMs in conjunction +% S - Voxel count +% +% P - corrected P value - P(n > kmax} +% p - uncorrected P value - P(n > k} +% Em - expected total number of maxima {m} +% En - expected total number of resels per cluster {n} +% EN - expected total number of voxels {N} +% +%__________________________________________________________________________ +% +% spm_P determines corrected and uncorrected p values, using the minimum +% of different valid methods. +% +% See the individual methods for details +% +% spm_P_RF +% spm_P_Bonf +% +%__________________________________________________________________________ +% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging + +% Thomas Nichols +% $Id: spm_P.m 2690 2009-02-04 21:44:28Z guillaume $ + + +% set global var NOBONF to 1 to turn off Bonferroni +%-------------------------------------------------------------------------- +global NOBONF; if ~isempty(NOBONF) && NOBONF, S = []; end + +if (nargin < 8), S = []; end + +[P,p,Em,En,EN] = spm_P_RF(c,k,Z,df,STAT,R,n); + +% Use lower Bonferroni P value (if possible) +%========================================================================== +if ~isempty(S) && (c == 1 && k == 0) && ~(length(R) == 1 && R == 1) + P = min(P,spm_P_Bonf(Z,df,STAT,S,n)); +end + +function [P,p,Em,En,EN] = spm_P_RF(c,k,Z,df,STAT,R,n) +% Returns the [un]corrected P value using unifed EC theory +% FORMAT [P p Em En EN] = spm_P_RF(c,k,Z,df,STAT,R,n) +% +% c - cluster number +% k - extent {RESELS} +% Z - height {minimum over n values} +% df - [df{interest} df{error}] +% STAT - Statistical field +% 'Z' - Gaussian field +% 'T' - T - field +% 'X' - Chi squared field +% 'F' - F - field +% R - RESEL Count {defining search volume} +% n - number of component SPMs in conjunction +% +% P - corrected P value - P(n > kmax} +% p - uncorrected P value - P(n > k} +% Em - expected total number of maxima {m} +% En - expected total number of resels per cluster {n} +% EN - expected total number of voxels {N} +% +%___________________________________________________________________________ +% +% spm_P_RF returns the probability of c or more clusters with more than +% k voxels in volume process of R RESELS thresholded at u. All p values +% can be considered special cases: +% +% spm_P_RF(1,0,Z,df,STAT,1,n) = uncorrected p value +% spm_P_RF(1,0,Z,df,STAT,R,n) = corrected p value {based on height Z) +% spm_P_RF(1,k,u,df,STAT,R,n) = corrected p value {based on extent k at u) +% spm_P_RF(c,k,u,df,STAT,R,n) = corrected p value {based on number c at k and u) +% spm_P_RF(c,0,u,df,STAT,R,n) = omnibus p value {based on number c at u) +% +% If n > 1 a conjunction probility over the n values of the statistic +% is returned +% +% Ref: Hasofer AM (1978) Upcrossings of random fields +% Suppl Adv Appl Prob 10:14-21 +% Ref: Friston et al (1993) Comparing functional images: Assessing +% the spatial extent of activation foci +% Ref: Worsley KJ et al 1996, Hum Brain Mapp. 4:58-73 +%___________________________________________________________________________ +% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging + +% Karl Friston +% $Id: spm_P_RF.m 2691 2009-02-04 21:46:04Z guillaume $ + + + +% get expectations +%=========================================================================== + +% get EC densities +%--------------------------------------------------------------------------- +D = find(R, 1, 'last' ); +R = R(1:D); +G = sqrt(pi)./gamma(([1:D])/2); +EC = spm_ECdensity(STAT,Z,df); +EC = EC([1:D]) + eps; + +% corrected p value +%--------------------------------------------------------------------------- +P = triu(toeplitz(EC'.*G))^n; +P = P(1,:); +EM = (R./G).*P; % over D dimensions +Em = sum(EM); % +EN = P(1)*R(D); % +En = EN/EM(D); % En = EN/EM(D); + +% get P{n > k} +%=========================================================================== + +% assume a Gaussian form for P{n > k} ~ exp(-beta*k^(2/D)) +% Appropriate for SPM{Z} and high d.f. SPM{T} +%--------------------------------------------------------------------------- +D = D - 1; +if ~k || ~D + + p = 1; + +elseif STAT == 'Z' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'T' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'X' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +elseif STAT == 'F' + + beta = (gamma(D/2 + 1)/En)^(2/D); + p = exp(-beta*(k^(2/D))); + +end + +% Poisson clumping heuristic {for multiple clusters} +%=========================================================================== +P = 1 - spm_Pcdf(c - 1,(Em + eps)*p); + + +% set P and p = [] for non-implemented cases +%+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +if k > 0 && n > 1 + P = []; p = []; +end +if k > 0 && (STAT == 'X' || STAT == 'F') + P = []; p = []; +end +%+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + + + + +% spm_ECdensity +%=========================================================================== + +function [EC] = spm_ECdensity(STAT,t,df) +% Returns the EC density +%___________________________________________________________________________ +% +% Reference : Worsley KJ et al 1996, Hum Brain Mapp. 4:58-73 +% +%--------------------------------------------------------------------------- + +% EC densities (EC} +%--------------------------------------------------------------------------- +t = t(:)'; +if STAT == 'Z' + + % Gaussian Field + %------------------------------------------------------------------- + a = 4*log(2); + b = exp(-t.^2/2); + + EC(1,:) = 1 - spm_Ncdf(t); + EC(2,:) = a^(1/2)/(2*pi)*b; + EC(3,:) = a/((2*pi)^(3/2))*b.*t; + EC(4,:) = a^(3/2)/((2*pi)^2)*b.*(t.^2 - 1); + +elseif STAT == 'T' + + % T - Field + %------------------------------------------------------------------- + v = df(2); + a = 4*log(2); + b = exp(gammaln((v+1)/2) - gammaln(v/2)); + c = (1+t.^2/v).^((1-v)/2); + + EC(1,:) = 1 - spm_Tcdf(t,v); + EC(2,:) = a^(1/2)/(2*pi)*c; + EC(3,:) = a/((2*pi)^(3/2))*c.*t/((v/2)^(1/2))*b; + EC(4,:) = a^(3/2)/((2*pi)^2)*c.*((v-1)*(t.^2)/v - 1); + +elseif STAT == 'X' + + % X - Field + %------------------------------------------------------------------- + v = df(2); + a = (4*log(2))/(2*pi); + b = t.^(1/2*(v - 1)).*exp(-t/2-gammaln(v/2))/2^((v-2)/2); + + EC(1,:) = 1 - spm_Xcdf(t,v); + EC(2,:) = a^(1/2)*b; + EC(3,:) = a*b.*(t-(v-1)); + EC(4,:) = a^(3/2)*b.*(t.^2-(2*v-1)*t+(v-1)*(v-2)); + +elseif STAT == 'F' + + % F Field + %------------------------------------------------------------------- + k = df(1); + v = df(2); + a = (4*log(2))/(2*pi); + b = gammaln(v/2) + gammaln(k/2); + + EC(1,:) = 1 - spm_Fcdf(t,df); + EC(2,:) = a^(1/2)*exp(gammaln((v+k-1)/2)-b)*2^(1/2)... + *(k*t/v).^(1/2*(k-1)).*(1+k*t/v).^(-1/2*(v+k-2)); + EC(3,:) = a*exp(gammaln((v+k-2)/2)-b)*(k*t/v).^(1/2*(k-2))... + .*(1+k*t/v).^(-1/2*(v+k-2)).*((v-1)*k*t/v-(k-1)); + EC(4,:) = a^(3/2)*exp(gammaln((v+k-3)/2)-b)... + *2^(-1/2)*(k*t/v).^(1/2*(k-3)).*(1+k*t/v).^(-1/2*(v+k-2))... + .*((v-1)*(v-2)*(k*t/v).^2-(2*v*k-v-k-1)*(k*t/v)+(k-1)*(k-2)); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_list (copied from spm 5) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function varargout = spm_list(varargin) +% Display and analysis of SPM{.} +% FORMAT TabDat = spm_list('List',SPM,hReg,[Num,Dis,Str]) +% Summary list of local maxima for entire volume of interest +% FORMAT TabDat = spm_list('ListCluster',SPM,hReg,[Num,Dis,Str]) +% List of local maxima for a single suprathreshold cluster +% +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x11 cell array) +% .fmt - fprintf format strings for table data (1x11 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (4x2 cell array) +% .dat - table data (Nx11 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%_______________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The currected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% +% Voxel-level - T/F = Statistic upon which the SPM is based +% - Ze = The eqivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qu = Expd(Prop of false positives among voxels >= Ze) +% - Pu = prob(Ze or higher at that voxel) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%_______________________________________________________________________ +% @(#)spm_list.m 2.43 Karl Friston, Andrew Holmes 02/10/31 + + +% satellite figure global variable +%----------------------------------------------------------------------- +global SatWindow + +%======================================================================= +switch lower(varargin{1}), case 'list' %-List +%======================================================================= +% FORMAT TabDat = spm_list('list',SPM,hReg) + +%-Tolerance for p-value underflow, when computing equivalent Z's +%----------------------------------------------------------------------- +tol = eps*10; + +%-Parse arguments and set maxima number and separation +%----------------------------------------------------------------------- +if nargin < 2, error('insufficient arguments'), end +if nargin < 3, hReg = []; else, hReg = varargin{3}; end + + +%-Get current location (to highlight selected voxel in table) +%----------------------------------------------------------------------- +%xyzmm = spm_results_ui('GetCoords'); +xyzmm = [0 0 0]'; + +%-Extract data from xSPM +%----------------------------------------------------------------------- +S = varargin{2}.S; +R = varargin{2}.R; +FWHM = varargin{2}.FWHM; +VOX = varargin{2}.VOX; +n = varargin{2}.n; +STAT = varargin{2}.STAT; +df = varargin{2}.df; +u = varargin{2}.u; +M = varargin{2}.M; +v2r = 1/prod(FWHM(~isinf(FWHM))); %-voxels to resels +k = varargin{2}.k*v2r; +QPs = varargin{2}.Ps; % Needed for FDR +QPs = sort(QPs(:)); + +%-get number and separation for maxima to be reported +%----------------------------------------------------------------------- +if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) +else + Num = 3; + Dis = 8; +end +if length(varargin) > 5 + + Title = varargin{6}; +else + Title = 'p-values adjusted for search volume'; +end + + +%-Setup graphics panel +%----------------------------------------------------------------------- +spm('Pointer','Watch') +if SatWindow + Fgraph = SatWindow; + figure(Fgraph); +else + Fgraph = figure('unit','normalized','position',[0.4,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','off','MenuBar','none'); + Fgraph = gcf; +end +%spm_results_ui('Clear',Fgraph) +FS = spm('FontSizes'); %-Scaled font sizes +PF = spm_platform('fonts'); %-Font names (for this platform) + + +%-Table header & footer +%======================================================================= + +%-Table axes & Title +%---------------------------------------------------------------------- +if SatWindow, ht = 0.85; bot = .14; else, ht = 0.8; bot = 0.15; end; + +if STAT == 'P' + Title = 'Posterior Probabilities'; +end + +hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + +AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) +dy = FS(9); +y = floor(AxPos(4)) - dy; + +text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; +line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + +%-Construct table header +%----------------------------------------------------------------------- +set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + +Hc = []; +Hp = []; +h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; +h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; +h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; +h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; +text(0.22,y, 'cluster-level','FontSize',FS(9)); +line([0.15,0.41],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); +h = text(0.16,y-9*dy/8, '\itp \rm_{corrected}'); Hp = [Hp,h]; +h = text(0.33,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; +h = text(0.26,y-9*dy/8, '\itk \rm_E'); + +text(0.60,y, 'voxel-level','FontSize',FS(9)); +line([0.46,0.86],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); +h = text(0.46,y-9*dy/8, '\itp \rm_{FWE-corr}'); Hp = [Hp,h]; +h = text(0.55,y-9*dy/8, '\itp \rm_{FDR-corr}'); Hp = [Hp,h]; +h = text(0.79,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; +h = text(0.64,y-9*dy/8, sprintf('\\it%c',STAT)); +h = text(0.72,y-9*dy/8, '(\itZ\rm_\equiv)'); + +text(0.93,y - dy/2,['x,y,z \fontsize{',num2str(FS(8)),'}\{mm\}']); + + +%-Headers for text table... +%----------------------------------------------------------------------- +TabDat.tit = Title; +TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'voxel', 'p(FWE-cor)';... + 'voxel', 'p(FDR-cor)';... + 'voxel', STAT;... + 'voxel', 'equivZ';... + 'voxel', 'p(unc)';... + '', 'x,y,z {mm}'}';... + +TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Voxel + '%3.0f %3.0f %3.0f'}; %-XYZ + +%-Column Locations +%----------------------------------------------------------------------- +tCol = [ 0.00 0.07 ... %-Set + 0.16 0.26 0.34 ... %-Cluster + 0.46 0.55 0.62 0.71 0.80 ...%-Voxel + 0.92]; %-XYZ + +% move to next vertial postion marker +%----------------------------------------------------------------------- +y = y - 7*dy/4; +line([0 1],[y y],'LineWidth',1,'Color','r') +y = y - 5*dy/4; +y0 = y; + + +%-Table filtering note +%----------------------------------------------------------------------- +if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); +else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); +end +text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + +%-Volume, resels and smoothness (if classical inference) +%----------------------------------------------------------------------- +line([0 1],[0 0],'LineWidth',1,'Color','r') +if STAT ~= 'P' +%----------------------------------------------------------------------- +FWHMmm = FWHM.*VOX; % FWHM {mm} +Pz = spm_P(1,0,u,df,STAT,1,n,S); +Pu = spm_P(1,0,u,df,STAT,R,n,S); +Qu = spm_P_FDR(u,df,STAT,n,QPs); +[P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + +%-Footnote with SPM parameters +%----------------------------------------------------------------------- +set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) +TabDat.ftr = cell(5,2); +TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); +TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); +TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); +TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); +TabDat.ftr{5} = ... + sprintf('Expected false discovery rate, <= %0.2f',Qu); +TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); +TabDat.ftr{7} = ... + sprintf(['Smoothness FWHM = %0.1f %0.1f %0.1f {mm} ',... + ' = %0.1f %0.1f %0.1f {voxels}'],FWHMmm,FWHM); +TabDat.ftr{8} = ... + sprintf('Search vol: %0.0f cmm; %0.0f voxels; %0.1f resels',S*prod(VOX),S,R(end)); +TabDat.ftr{9} = ... + sprintf(['Voxel size: [%0.1f, %0.1f, %0.1f] mm ',... + ' (1 resel = %0.2f voxels)'],VOX,prod(FWHM)); + +text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu,Qu],'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWHMmm,'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') +text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + +end % Classical + + +%-Characterize excursion set in terms of maxima +% (sorted on Z values and grouped by regions) +%======================================================================= +if ~length(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,11); + varargout = {TabDat}; + spm('Pointer','Arrow') + return +end + +% Includes Darren Gitelman's code for working around +% spm_max for conjunctions with negative thresholds +%----------------------------------------------------------------------- +minz = abs(min(min(varargin{2}.Z))); +zscores = 1 + minz + varargin{2}.Z; +[N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); +Z = Z - minz - 1; + +%-Convert cluster sizes from voxels to resels +%----------------------------------------------------------------------- +if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); +else + V2R = v2r; +end +N = N.*V2R; + +%-Convert maxima locations from voxels to mm +%----------------------------------------------------------------------- +XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + +%-Table proper (& note all data in cell array) +%======================================================================= + +%-Pagination variables +%----------------------------------------------------------------------- +hPage = []; +set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + +%-Set-level p values {c} - do not display if reporting a single cluster +%----------------------------------------------------------------------- +c = max(A); %-Number of clusters +if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value +else + Pc = []; + set(Hp,'Visible','off') +end + +if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; +else + set(Hc,'Visible','off') +end + +TabDat.dat = {Pc,c}; %-Table data +TabLin = 1; %-Table data line + + +%-Local maxima p-values & statistics +%----------------------------------------------------------------------- +HlistXYZ = []; +while prod(size(find(isfinite(Z)))) + + % Paginate if necessary + %--------------------------------------------------------------- + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %--------------------------------------------------------------- + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and voxel-level {u} p values for this cluster + %--------------------------------------------------------------- + Nv = N(i)/v2r; % extent {voxels} + + + if STAT ~= 'P' + Pz = spm_P(1,0, U,df,STAT,1,n,S);% uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S);% FWE-corrected {based on Z) + Qu = spm_P_FDR( U,df,STAT,n,QPs);% FDR-corrected {based on Z) + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S);% [un]corrected {based on k) + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum voxel-level p values {Z} + %--------------------------------------------------------------- + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %--------------------------------------------------------------------- + h = text(tCol(11),y,sprintf(TabDat.fmt{11},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %--------------------------------------------------------------- + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %----------------------------------------------- + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %----------------------------------------------- + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + if Pz < tol + Ze = Inf; + else, Ze = spm_invNcdf(1 - Pz); end + else + Pz = []; + Pu = []; + Qu = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %----------------------------------------------- + h = text(tCol(11),y,... + sprintf(TabDat.fmt{11},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) +end + +%-End: Store TabDat in UserData of axes & reset pointer +%======================================================================= +h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); +set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') +uimenu(h,'Label','Table') +uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); +uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); +uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + +%-Setup registry +%----------------------------------------------------------------------- +set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) +spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + +%-Return TabDat structure & reset pointer +%----------------------------------------------------------------------- +varargout = {TabDat}; +spm('Pointer','Arrow') + + + + + +%======================================================================= +case 'listcluster' %-List for current cluster only +%======================================================================= +% FORMAT TabDat = spm_list('listcluster',SPM,hReg) + +spm('Pointer','Watch') + +%-Parse arguments +%----------------------------------------------------------------------- +if nargin < 2, error('insufficient arguments'), end +if nargin < 3, hReg = []; else, hReg = varargin{3}; end +SPM = varargin{2}; + +%-get number and separation for maxima to be reported +%----------------------------------------------------------------------- +if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) +else + Num = 32; + Dis = 4; +end + + +%-if there are suprathreshold voxels, filter out all but current cluster +%----------------------------------------------------------------------- +if length(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end +end + +%-Call 'list' functionality to produce table +%----------------------------------------------------------------------- +varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + + + +%======================================================================= +case 'txtlist' %-Print ASCII text table +%======================================================================= +% FORMAT spm_list('TxtList',TabDat,c) + +if nargin<2, error('Insufficient arguments'), end +if nargin<3, c=1; else, c=varargin{3}; end +TabDat = varargin{2}; + +%-Table Title +%----------------------------------------------------------------------- +fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) +fprintf('%c','='*ones(1,80)), fprintf('\n') + +%-Table header +%----------------------------------------------------------------------- +fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) +fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) +fprintf('%c','-'*ones(1,80)), fprintf('\n') + +%-Table data +%----------------------------------------------------------------------- +for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') +end +for i=1:max(1,11-size(TabDat.dat,1)), fprintf('\n'), end +fprintf('%s\n',TabDat.str) +fprintf('%c','-'*ones(1,80)), fprintf('\n') + +%-Table footer +%----------------------------------------------------------------------- +fprintf('%s\n',TabDat.ftr{:}) +fprintf('%c','='*ones(1,80)), fprintf('\n\n') + + + +%======================================================================= +case 'setcoords' %-Co-ordinate change +%======================================================================= +% FORMAT spm_list('SetCoords',xyz,hAx,hReg) +if nargin<3, error('Insufficient arguments'), end +hAx = varargin{3}; +xyz = varargin{2}; +UD = get(hAx,'UserData'); +HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + +%-Set all co-ord strings to black +%----------------------------------------------------------------------- +set(HlistXYZ,'Color','k') + +%-If co-ord matches a string, highlight it in red +%----------------------------------------------------------------------- +XYZ = get(HlistXYZ,'UserData'); +if iscell(XYZ), XYZ = cat(2,XYZ{:}); end +[null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); +if d mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for voxel FDR) +% .Pp - uncorrected P values of peaks (for peak FDR) +% .Pc - uncorrected P values of cluster extents (for cluster FDR) +% .uc - 0.05 critical thresholds for FWEp, FDRp, FWEc, FDRc +% .thresDesc - description of height threshold (string) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x12 cell array) +% .fmt - fprintf format strings for table data (1x12 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (5x2 cell array) +% .dat - table data (Nx12 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%__________________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The corrected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% - Qc = lowest FDR bound for which this cluster would be +% declared positive +% +% Peak-level - T/F = Statistic upon which the SPM is based +% - Ze = The equivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qp = lowest FDR bound for which this peak would be +% declared positive +% - Pu = prob(Ze or higher at that voxel) +% +% Voxel-level - Qu = Expd(Prop of false positives among voxels >= Ze) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%__________________________________________________________________________ +% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging + +% Karl Friston & Andrew Holmes +% $Id: spm_list.m 2821 2009-03-03 19:54:19Z guillaume $ + + +% satellite figure global variable +%-------------------------------------------------------------------------- +global SatWindow + +% Choose between voxel-wise and topological FDR +%-------------------------------------------------------------------------- +defaults = spm('GetGlobal','defaults'); +try + topoFDR = defaults.stats.topoFDR; +catch + topoFDR = true; +end + +%========================================================================== +switch lower(varargin{1}), case 'list' %-List +%========================================================================== +% FORMAT TabDat = spm_list('list',SPM,hReg) + + %-Tolerance for p-value underflow, when computing equivalent Z's + %---------------------------------------------------------------------- + tol = eps*10; + + %-Parse arguments and set maxima number and separation + %---------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else hReg = varargin{3}; end + + + %-Get current location (to highlight selected voxel in table) + %---------------------------------------------------------------------- + %xyzmm = spm_results_ui('GetCoords'); + xyzmm = spm_XYZreg('GetCoords',hReg);% added by xu cui + + + %-Extract data from xSPM + %---------------------------------------------------------------------- + S = varargin{2}.S; + VOX = varargin{2}.VOX; + DIM = varargin{2}.DIM; + n = varargin{2}.n; + STAT = varargin{2}.STAT; + df = varargin{2}.df; + u = varargin{2}.u; + M = varargin{2}.M; + k = varargin{2}.k; + try, QPs = varargin{2}.Ps; end + try, QPp = varargin{2}.Pp; end + try, QPc = varargin{2}.Pc; end + try + thresDesc = sprintf('{%s}', varargin{2}.thresDesc); + catch + thresDesc = ''; + end + + if STAT~='P' + R = varargin{2}.R; + FWHM = varargin{2}.FWHM; + end + try + units = varargin{2}.units; + catch + units = {'mm' 'mm' 'mm'}; + end + units{1} = [units{1} ' ']; + units{2} = [units{2} ' ']; + + DIM = DIM > 1; % dimensions + VOX = VOX(DIM); % scaling + + if STAT~='P' + FWHM = FWHM(DIM); % Full width at max/2 + FWmm = FWHM.*VOX; % FWHM {units} + v2r = 1/prod(FWHM); % voxels to resels + k = k*v2r; % extent threshold in resels + R(find(~DIM) + 1) = []; % eliminate null resel counts + try, QPs = sort(QPs(:)); end % Needed for voxel FDR + try, QPp = sort(QPp(:)); end % Needed for peak FDR + try, QPc = sort(QPc(:)); end % Needed for cluster FDR + end + + %-get number and separation for maxima to be reported + %---------------------------------------------------------------------- + if length(varargin) > 3 + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 3; + Dis = 8; + end + if length(varargin) > 5 + Title = varargin{6}; + else + Title = 'p-values adjusted for search volume'; + end + + %-Setup graphics panel + %---------------------------------------------------------------------- + spm('Pointer','Watch') + if SatWindow + Fgraph = SatWindow; + figure(Fgraph); + else%edit by xu cui + Fgraph = figure('unit','normalized','position',[0.4,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','on','MenuBar','none'); + Fgraph = gcf; + %Fgraph = spm_figure('GetWin','Graphics'); + end + spm_results_ui('Clear',Fgraph) + FS = spm('FontSizes'); %-Scaled font sizes + PF = spm_platform('fonts'); %-Font names (for this platform) + + + %-Table header & footer + %====================================================================== + + %-Table axes & Title + %---------------------------------------------------------------------- + if SatWindow, ht = 0.85; bot = 0.14; else ht = 0.8; bot = 0.15; end % changed by xu cui + + if STAT == 'P' + Title = 'Posterior Probabilities'; + end + + hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + + AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) + dy = FS(9); + y = floor(AxPos(4)) - dy; + + text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; + line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + %-Construct table header + %---------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + + Hc = []; + Hp = []; + h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; + h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; + h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; + h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; + text(0.22,y, 'cluster-level','FontSize',FS(9)); + line([0.14,0.44],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.15,y-9*dy/8, '\itp\rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.24,y-9*dy/8, '\itq\rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.39,y-9*dy/8, '\itp\rm_{uncorr}'); Hp = [Hp,h]; + h = text(0.34,y-9*dy/8, '\itk\rm_E'); + + text(0.64,y, 'peak-level','FontSize',FS(9)); + line([0.48,0.88],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.49,y-9*dy/8, '\itp\rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.58,y-9*dy/8, '\itq\rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.82,y-9*dy/8, '\itp\rm_{uncorr}'); Hp = [Hp,h]; + h = text(0.67,y-9*dy/8, sprintf('\\it%c',STAT)); + h = text(0.75,y-9*dy/8, '(\itZ\rm_\equiv)'); + + text(0.92,y - dy/2,[units{:}],'Fontsize',FS(8)); + + + %-Headers for text table... + %----------------------------------------------------------------------- + TabDat.tit = Title; + TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(FWE-cor)';... + 'cluster', 'p(FDR-cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'peak', 'p(FWE-cor)';... + 'peak', 'p(FDR-cor)';... + 'peak', STAT;... + 'peak', 'equivZ';... + 'peak', 'p(unc)';... + '', 'x,y,z {mm}'}';... + + TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.3f','%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Peak + '%3.0f %3.0f %3.0f'}; %-XYZ + + %-Column Locations + %---------------------------------------------------------------------- + tCol = [ 0.01 0.08 ... %-Set + 0.15 0.24 0.33 0.39 ... %-Cluster + 0.49 0.58 0.65 0.74 0.83 ... %-Peak + 0.92]; %-XYZ + + %-Move to next vertical position marker + %---------------------------------------------------------------------- + y = y - 7*dy/4; + line([0 1],[y y],'LineWidth',1,'Color','r') + y = y - 5*dy/4; + y0 = y; + + + %-Table filtering note + %---------------------------------------------------------------------- + if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); + else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); + end + text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + + %-Volume, resels and smoothness (if classical inference) + %---------------------------------------------------------------------- + line([0 1],[0 0],'LineWidth',1,'Color','r') + if STAT ~= 'P' + %------------------------------------------------------------------ + Pz = spm_P(1,0,u,df,STAT,1,n,S); + Pu = spm_P(1,0,u,df,STAT,R,n,S); + %Qu = spm_P_FDR(u,df,STAT,n,QPs); + [P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + %-Footnote with SPM parameters + %------------------------------------------------------------------ + set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) + TabDat.ftr = cell(5,2); + TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); + TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); + TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); + TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); + if any(isnan(varargin{2}.uc)) + TabDat.ftr{5} = ... + sprintf('FWEp: %0.3f, FDRp: %0.3f',varargin{2}.uc(1:2)); + else + TabDat.ftr{5} = ... + sprintf('FWEp: %0.3f, FDRp: %0.3f, FWEc: %0.0f, FDRc: %0.0f',... + varargin{2}.uc); + end + TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); + TabDat.ftr{7} = ... + ['FWHM = ' sprintf('%0.1f ', FWmm) units{:} '; ' ... + sprintf('%0.1f ', FWHM) '{voxels}']; + TabDat.ftr{8} = ... + sprintf('Volume: %0.0f = %0.0f voxels = %0.1f resels', ... + S*prod(VOX),S,R(end)); + TabDat.ftr{9} = ... + ['Voxel size: ' sprintf('%0.1f ',VOX) units{:} '; ' ... + sprintf('(resel = %0.2f voxels)',prod(FWHM))]; + + text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',varargin{2}.uc,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWmm,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + else + TabDat.ftr = {}; + end + + + %-Characterize excursion set in terms of maxima + % (sorted on Z values and grouped by regions) + %====================================================================== + if isempty(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,12); + varargout = {TabDat}; + spm('Pointer','Arrow') + return + end + + % Includes Darren Gitelman's code for working around + % spm_max for conjunctions with negative thresholds + %---------------------------------------------------------------------- + minz = abs(min(min(varargin{2}.Z))); + zscores = 1 + minz + varargin{2}.Z; + [N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); + Z = Z - minz - 1; + + %-Convert cluster sizes from voxels to resels + %---------------------------------------------------------------------- + if STAT~='P' + if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); + else + V2R = v2r; + end + N = N.*V2R; + end + + %-Convert maxima locations from voxels to mm + %---------------------------------------------------------------------- + XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + + %-Table proper (& note all data in cell array) + %====================================================================== + + %-Pagination variables + %---------------------------------------------------------------------- + hPage = []; + set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + + %-Set-level p values {c} - do not display if reporting a single cluster + %---------------------------------------------------------------------- + c = max(A); %-Number of clusters + if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value + else + Pc = []; + set(Hp,'Visible','off') + end + + if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + else + set(Hc,'Visible','off') + end + + TabDat.dat = {Pc,c}; %-Table data + TabLin = 1; %-Table data line + + + %-Local maxima p-values & statistics + %---------------------------------------------------------------------- + HlistXYZ = []; + while numel(find(isfinite(Z))) + + % Paginate if necessary + %------------------------------------------------------------------ + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %-------------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %------------------------------------------------------------------ + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and peak-level {u} p values for this cluster + %------------------------------------------------------------------ + if STAT ~= 'P' + Nv = N(i)/v2r; % extent {voxels} + + Pz = spm_P(1,0, U,df,STAT,1,n,S); % uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S); % FWE-corrected {based on Z} + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S); % [un]corrected {based on k} + if topoFDR + Qc = spm_P_clusterFDR(N(i),df,STAT,R,n,u,QPc); % cluster FDR-corrected {based on k} + Qp = spm_P_peakFDR(U,df,STAT,R,n,u,QPp); % peak FDR-corrected {based on Z} + Qu = []; + else + Qu = spm_P_FDR( U,df,STAT,n,QPs); % voxel FDR-corrected {based on Z} + Qc = []; + Qp = []; + end + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Nv = N(i); + + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Qc = []; + Qp = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum peak-level p values {Z} + %------------------------------------------------------------------ + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Qc),'FontWeight','Bold',... + 'UserData',Qc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + if topoFDR + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Qp),'FontWeight','Bold',... + 'UserData',Qp,'ButtonDownFcn','get(gcbo,''UserData'')'); + else + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + end + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(11),y,sprintf(TabDat.fmt{11},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %------------------------------------------------------------------ + h = text(tCol(12),y,sprintf(TabDat.fmt{12},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %------------------------------------------------------------------ + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %------------------------------------------------------ + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %------------------------------------------------------ + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + if topoFDR + Qp = spm_P_peakFDR(Z(d),df,STAT,R,n,u,QPp); + Qu = []; + else + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + Qp = []; + end + if Pz < tol + Ze = Inf; + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Qp = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + if topoFDR + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Qp),... + 'UserData',Qp,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + else + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + end + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(11),y,sprintf(TabDat.fmt{11},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %------------------------------------------------------ + h = text(tCol(12),y,... + sprintf(TabDat.fmt{12},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) + end + + %-End: Store TabDat in UserData of axes & reset pointer + %====================================================================== + h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); + set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') + uimenu(h,'Label','Table') + uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + + %-Setup registry + %---------------------------------------------------------------------- + set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) + spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + + %-Return TabDat structure & reset pointer + %---------------------------------------------------------------------- + varargout = {TabDat}; + spm('Pointer','Arrow') + + + %====================================================================== + case 'listcluster' %-List for current cluster only + %====================================================================== + % FORMAT TabDat = spm_list('listcluster',SPM,hReg) + + spm('Pointer','Watch') + + %-Parse arguments + %------------------------------------------------------------------ + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else hReg = varargin{3}; end + SPM = varargin{2}; + + %-get number and separation for maxima to be reported + %------------------------------------------------------------------ + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 32; + Dis = 4; + end + + + %-if there are suprathreshold voxels, filter out all but current cluster + %------------------------------------------------------------------ + if ~isempty(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end + end + + %-Call 'list' functionality to produce table + %------------------------------------------------------------------ + varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + %====================================================================== + case 'txtlist' %-Print ASCII text table + %====================================================================== + % FORMAT spm_list('TxtList',TabDat,c) + + if nargin<2, error('Insufficient arguments'), end + if nargin<3, c=1; else c=varargin{3}; end + TabDat = varargin{2}; + + %-Table Title + %------------------------------------------------------------------ + fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) + fprintf('%c',repmat('=',1,80)), fprintf('\n') + + %-Table header + %------------------------------------------------------------------ + fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) + fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) + fprintf('%c',repmat('-',1,80)), fprintf('\n') + + %-Table data + %------------------------------------------------------------------ + for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') + end + for i=1:max(1,12-size(TabDat.dat,1)), fprintf('\n'), end + fprintf('%s\n',TabDat.str) + fprintf('%c',repmat('-',1,80)), fprintf('\n') + + %-Table footer + %------------------------------------------------------------------ + fprintf('%s\n',TabDat.ftr{:}) + fprintf('%c',repmat('=',1,80)), fprintf('\n\n') + + + + %================================================================== + case 'setcoords' %-Co-ordinate change + %================================================================== + % FORMAT spm_list('SetCoords',xyz,hAx,hReg) + if nargin<3, error('Insufficient arguments'), end + hAx = varargin{3}; + xyz = varargin{2}; + UD = get(hAx,'UserData'); + HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + + %-Set all co-ord strings to black + %------------------------------------------------------------------ + set(HlistXYZ,'Color','k') + + %-If co-ord matches a string, highlight it in red + %------------------------------------------------------------------ + XYZ = get(HlistXYZ,'UserData'); + if iscell(XYZ), XYZ = cat(2,XYZ{:}); end + [null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); + if d=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + cm_pos; + end; + varargout{1} = H; + st.centre = mean(maxbb); + redraw_all + +case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + +case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + +case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3 + h = valid_handles(st.snap); + if ~isempty(h) + tmp=st.vols{h(1)}.mat*... + round(inv(st.vols{h(1)}.mat)*[tmp; ... + 1]); + end; + st.centre = tmp(1:3); + end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + cm_pos; + +case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + cm_pos; + +case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + bbox; + redraw_all; + else, + space(varargin{1}); + bbox; + redraw_all; + end; + +case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + +case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + +case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + +case 'delete', + my_delete(varargin{1}); + +case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + +case 'reset', + my_reset; + +case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + +case 'interp', + st.hld = varargin{1}; + redraw_all; + +case 'xhairs', + xhairs(varargin{1}); + +case 'register', + register(varargin{1}); + +case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + +case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + +case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + +case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + +case 'addtruecolourimage', + % spm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_select(1, 'image', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + +case 'addcolourbar', + addcolourbar(varargin{1}, varargin{2}); + +case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + +case 'addcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + addcontexts(handles); + +case 'rmcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + rmcontexts(handles); + +case 'context_menu', + c_menu(varargin{:}); + +case 'valid_handles', + if nargin == 1 + handles = 1:24; + else, + handles = varargin{1}; + end; + varargout{1} = valid_handles(handles); + +otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +global TMAX_ +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + mx = max([eps max(t)]); + mn = min([0 min(t)]); + if ~strcmp(TMAX_, 'auto') + mx = str2num(TMAX_); + end + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx, 'min',mn); + addcolourbar(handle,1); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx,'min',mn); + addcolourbar(handle,1); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx, ... + 'min',mn,'colour',c); + addcolourbar(handle,bset); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolourbar(vh,bh) +global st +if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); +else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); +end; +st.vols{vh}.blobs{bh}.cbar = axes('Parent',st.fig,... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on', 'YDir','normal', 'XTickLabel',[], 'XTick',[]); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'spm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['spm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''Reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +V.mapping = 'linear'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +spm_orthviews('reposition',spm_orthviews('pos')); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['spm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(isfinite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(isfinite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(isfinite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(isfinite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); +% cent(1)=-40 +% cent(2)=-40 +% cent(3)=60 +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + imgc = max(imgc,mn); imgc = min(imgc,mx); + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(isfinite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgc), + tmp = imgc(isfinite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgs), + tmp = imgs(isfinite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(isfinite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(isfinite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(isfinite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); % can change this to cold color + else + setcolormap('gray-cold') + end + redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpc(tmpc(:)>mx) = mx; + tmps(tmps(:)>mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpc = (tmpc-mn)/(mx-mn); + tmps = (tmps-mn)/(mx-mn); + tmpt(~isfinite(tmpt)) = 0; + tmpc(~isfinite(tmpc)) = 0; + tmps(~isfinite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_colourbar(vh,bh,interval,cdata) +global st +if isfield(st.vols{vh}.blobs{bh},'cbar') + if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); + end; + % only scale cdata if we have out-of-range truecolour values + if ndims(cdata)==3 && max(cdata(:))>1 + cdata=cdata./max(cdata(:)); + end; + image([0 1],interval,cdata,'Parent',st.vols{vh}.blobs{bh}.cbar); + set(st.vols{vh}.blobs{bh}.cbar, ... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1)... + (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'YDir','normal','XTickLabel',[],'XTick',[]); +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = []; %[ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[],'snap',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'spm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('spm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~isfinite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item00 = uimenu(item_parent, 'Label','unknown image', 'Separator','on'); +spm_orthviews('context_menu','image_info',item00,volhandle); +item0a = uimenu(item_parent, 'UserData','pos_mm', 'Callback','spm_orthviews(''context_menu'',''repos_mm'');','Separator','on'); +item0b = uimenu(item_parent, 'UserData','pos_vx', 'Callback','spm_orthviews(''context_menu'',''repos_vx'');'); +item0c = uimenu(item_parent, 'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','spm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +checked={'off','off'}; +checked{st.xhairs+1} = 'on'; +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''on'');','Checked',checked{2}); +item2_2 = uimenu(item2, 'Label','off', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''off'');','Checked',checked{1}); + +%contextsubmenu 3 +if st.Space == eye(4) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','spm_orthviews(''context_menu'',''orientation'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Voxel space (1st image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Voxel space (this image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',1);','Checked','off'); + +%contextsubmenu 3 +if isempty(st.snap) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Snap to Grid'); +item3_1 = uimenu(item3, 'Label','Don''t snap', 'Callback','spm_orthviews(''context_menu'',''snap'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Snap to 1st image', 'Callback','spm_orthviews(''context_menu'',''snap'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Snap to this image', 'Callback','spm_orthviews(''context_menu'',''snap'',1);','Checked','off'); + +%contextsubmenu 4 +if st.hld == 0, + checked = {'off', 'off', 'on'}; +elseif st.hld > 0, + checked = {'off', 'on', 'off'}; +else, + checked = {'on', 'off', 'off'}; +end; +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','spm_orthviews(''context_menu'',''interpolation'',3);', 'Checked',checked{3}); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','spm_orthviews(''context_menu'',''interpolation'',2);','Checked',checked{2}); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','spm_orthviews(''context_menu'',''interpolation'',1);','Checked',checked{1}); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','spm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window_gl'',1);'); +if license('test','image_toolbox') == 1 + offon = {'off', 'on'}; + checked = offon(strcmp(st.vols{volhandle}.mapping, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'})+1); + item6_2 = uimenu(item6, 'Label','Intensity mapping'); + item6_2_1 = uimenu(item6_2, 'Label','local'); + item6_2_1_1 = uimenu(item6_2_1, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''linear'');'); + item6_2_1_2 = uimenu(item6_2_1, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''histeq'');'); + item6_2_1_3 = uimenu(item6_2_1, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''loghisteq'');'); + item6_2_1_4 = uimenu(item6_2_1, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''quadhisteq'');'); + item6_2_2 = uimenu(item6_2, 'Label','global'); + item6_2_2_1 = uimenu(item6_2_2, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''linear'');'); + item6_2_2_2 = uimenu(item6_2_2, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''histeq'');'); + item6_2_2_3 = uimenu(item6_2_2, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''loghisteq'');'); + item6_2_2_4 = uimenu(item6_2_2, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''quadhisteq'');'); +end; +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add image'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_image'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_image'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored blobs','Separator','on'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_4 = uimenu(item7, 'Label','Add colored image'); +item7_4_1 = uimenu(item7_4, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_4_2 = uimenu(item7_4, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_5 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_6 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_6_1 = uimenu(item7_6, 'Label','local', 'Visible','on'); +item7_6_2 = uimenu(item7_6, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), +case 'image_info', + if nargin <3, + current_handle = get_current_handle; + else + current_handle = varargin{3}; + end; + if isfield(st.vols{current_handle},'fname'), + [p,n,e,v] = spm_fileparts(st.vols{current_handle}.fname); + if isfield(st.vols{current_handle},'n') + v = sprintf(',%d',st.vols{current_handle}.n); + end; + set(varargin{2}, 'Label',[n e v]); + end; + delete(get(varargin{2},'children')); + if exist('p','var') + item1 = uimenu(varargin{2}, 'Label', p); + end; + if isfield(st.vols{current_handle},'descrip'), + item2 = uimenu(varargin{2}, 'Label',... + st.vols{current_handle}.descrip); + end; + dt = st.vols{current_handle}.dt(1); + item3 = uimenu(varargin{2}, 'Label', sprintf('Data type: %s', spm_type(dt))); + str = 'Intensity: varied'; + if size(st.vols{current_handle}.pinfo,2) == 1, + if st.vols{current_handle}.pinfo(2), + str = sprintf('Intensity: Y = %g X + %g',... + st.vols{current_handle}.pinfo(1:2)'); + else, + str = sprintf('Intensity: Y = %g X', st.vols{current_handle}.pinfo(1)'); + end; + end; + item4 = uimenu(varargin{2}, 'Label',str); + item5 = uimenu(varargin{2}, 'Label', 'Image dims', 'Separator','on'); + item51 = uimenu(varargin{2}, 'Label',... + sprintf('%dx%dx%d', st.vols{current_handle}.dim(1:3))); + prms = spm_imatrix(st.vols{current_handle}.mat); + item6 = uimenu(varargin{2}, 'Label','Voxel size', 'Separator','on'); + item61 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', prms(7:9))); + item7 = uimenu(varargin{2}, 'Label','Origin', 'Separator','on'); + item71 = uimenu(varargin{2}, 'Label',... + sprintf('%.2f %.2f %.2f', prms(1:3))); + R = spm_matrix([0 0 0 prms(4:6)]); + item8 = uimenu(varargin{2}, 'Label','Rotations', 'Separator','on'); + item81 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(1,1:3))); + item82 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(2,1:3))); + item83 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(3,1:3))); + item9 = uimenu(varargin{2},... + 'Label','Specify other image...',... + 'Callback','spm_orthviews(''context_menu'',''swap_img'');',... + 'Separator','on'); + +case 'repos_mm', + oldpos_mm = spm_orthviews('pos'); + newpos_mm = spm_input('New Position (mm)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_mm),3); + spm_orthviews('reposition',newpos_mm); + +case 'repos_vx' + current_handle = get_current_handle; + oldpos_vx = spm_orthviews('pos', current_handle); + newpos_vx = spm_input('New Position (voxels)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_vx),3); + newpos_mm = st.vols{current_handle}.mat*[newpos_vx;1]; + spm_orthviews('reposition',newpos_mm(1:3)); + +case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + +case 'xhair', + spm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + +case 'orientation', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + spm_orthviews('Space'); + elseif varargin{2} == 2, + spm_orthviews('Space',1); + else, + spm_orthviews('Space',get_current_handle); + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Orientation'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + +case 'snap', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + st.snap = []; + elseif varargin{2} == 2, + st.snap = 1; + else, + st.snap = get_current_handle; + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Snap to Grid'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + +case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + +case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + spm_orthviews('window',current_handle); + else + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%.2f %.2f', st.vols{current_handle}.window); + else + defstr = ''; + end; + spm_orthviews('window',current_handle,spm_input('Range','+1','e',defstr,2)); + end; + +case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + current_handle = get_current_handle; + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%d %d', st.vols{current_handle}.window); + else + defstr = ''; + end; + data = spm_input('Range','+1','e',defstr,2); + + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + +case 'mapping', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', ... + 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + current_handle = get_current_handle; + cm_handles = get_cm_handles; + st.vols{current_handle}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(current_handle), ... + 'label','Intensity mapping'),'Children'); + for k = 1:numel(z_handle) + c_handle = get(z_handle(k), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + redraw_all; + +case 'mapping_gl', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + cm_handles = get_cm_handles; + for k = valid_handles(1:24), + st.vols{k}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(k), ... + 'label','Intensity mapping'),'Children'); + for l = 1:numel(z_handle) + c_handle = get(z_handle(l), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + end; + redraw_all; + +case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_select(1,'image','select new image')); + fn = fieldnames(new_info); + for k=1:numel(fn) + st.vols{current_handle}.(fn{k}) = new_info.(fn{k}); + end; + spm_orthviews('context_menu','image_info',get(gcbo, 'parent')); + redraw_all; + +case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + +case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + +case 'add_image', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + for i = 1:length(cm_handles), + addimage(cm_handles(i),fname); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + +case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',VOL.title,c_names{c}); + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + +case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + if isfield(st.vols{cm_handles(i)}.blobs{j},'cbar') + delete(st.vols{cm_handles(i)}.blobs{j}.cbar); + end + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + +case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',fname,c_names{c}); + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; + + +function display_slices(imgs, colormaps, ranges) +% FORMAT display_slices(imgs, dispf) +% +% request a some parameters for slice_overlay routine +% while accepting many defaults +% SO structure contains all the parameters for display +% See slice_overlay.m for detailed comments +% +% Defaults to GUI if no arguments passed +% imgs - string or cell array of image names to display +% dispf - flag, if set, displays overlay (default = 1) +% +% Matthew Brett 5/00 V 0.3 +% revised by Xu Cui 1/4/2008 +% +% The first image file has to be a structural image + +if ischar(imgs) + imgs = cellstr(imgs); +end + +clear global SO +global SO + +% load images +nimgs = size(imgs); + +% process names +nchars = 20; +imgns = spm_str_manip(imgs, ['rck' num2str(nchars)]); + +% identify image types +cscale = []; +deftype = 1; +SO.cbar = []; +for i = 1:nimgs + SO.img(i).vol = spm_vol(imgs{i}); + options = {'Structural','Truecolour', ... + 'Blobs','Negative blobs'}; + % if there are SPM results in the workspace, add this option + if evalin('base','exist(''SPM'', ''var'')') + options = {'Structural with SPM blobs', options{:}}; + end +% itype = spm_input(sprintf('Img %d: %s - image type?', i, imgns{i}), '+1', ... +% 'm', char(options),options, deftype); + if i == 1 + itype = {'Structural'}; + else + itype = {'Blobs'}; + end + %imgns(i) = {sprintf('Img %d (%s)',i,itype{1})}; + [mx mn] = slice_overlay('volmaxmin', SO.img(i).vol); + if ~isempty(strmatch('Structural', itype)) + SO.img(i).cmap = gray; + SO.img(i).range = [mn mx]; + deftype = 2; + cscale = [cscale i]; + if strcmp(itype,'Structural with SPM blobs') + errstr = sprintf(['Cannot find SPM/VOL structs in the workspace\n'... + 'Please run SPM results GUI before' ... + ' display_slices']); + SPM = evalin('base', 'SPM', ['error(' errstr ')']); + VOL = evalin('base', 'VOL', ['error(' errstr ')']); + slice_overlay('addspm',SPM,VOL,0); + end + else + SO.cbar = [SO.cbar i]; + cprompt = ['Colormap: ' imgns{i}]; + switch itype{1} + case 'Truecolour' + dcmap = 'actc'; + drange = [mn mx]; + cscale = [cscale i]; + case 'Blobs' + dcmap = 'hot'; + drange = [0 mx]; + SO.img(i).prop = Inf; + case 'Negative blobs' + dcmap = 'winter'; + drange = [0 mn]; + SO.img(i).prop = Inf; + end + if isempty(colormaps{i}) + SO.img(i).cmap = return_cmap(cprompt, dcmap); + else + SO.img(i).cmap = colormaps{i};%return_cmap(cprompt, dcmap); + end + SO.img(i).range = ranges{i};%spm_input('Img val range for colormap','+1', 'e', drange, 2); + end +end +ncmaps=length(cscale); +if ncmaps == 1 + SO.img(cscale).prop = 1; +else + remcol=1; + for i = 1:ncmaps + ino = cscale(i); + SO.img(ino).prop = spm_input(sprintf('%s intensity',imgns{ino}),... + '+1', 'e', ... + remcol/(ncmaps-i+1),1); + remcol = remcol - SO.img(ino).prop; + end +end +% +% SO.transform = deblank(spm_input('Image orientation', '+1', ['Axial|' ... +% ' Coronal|Sagittal'], strvcat('axial','coronal','sagittal'), ... +% 1)); +SO.transform = deblank(questdlg('Image orientation?', ... + 'Image orientation', ... + 'Axial', 'Coronal', 'Sagittal', 'Axial')); + +% use SPM figure window +SO.figure = spm_figure('GetWin', 'Graphics'); + +% slices for display +slice_overlay('checkso'); +SO.slices = eval(sprintf('%0.0f:%0.0f:%0.0f',... + SO.slices(1),... + mean(diff(SO.slices)),... + SO.slices(end))); + +% and do the display + +slice_overlay + +return + +function cmap = return_cmap(prompt,defmapn) + +prompt={prompt}; +name='Input color'; +numlines=1; +defaultanswer={defmapn}; + +answer=inputdlg(prompt,name,numlines,defaultanswer); +answer = answer{1}; + +cmap = []; +while isempty(cmap) + cmap = slice_overlay('getcmap', answer); +end +return + +% slice_overlay() - Function to display + manage slice display +% +% Usage: +% >> slice_overlay(action, varargin); +% +% Inputs: +% +% Outputs: +% +% Author: Matthew Brett matthew@mrc-cbu.cam.ac.uk +% +% See also: show_2d(), show_3d() + +% $Log: slice_overlay.m,v $ +% Revision 1.1 2003/02/06 19:17:48 duann +% Initial revision +% + +function varargout = slice_overlay(action, varargin); +% Function to display + manage slice display +% Slice display works on a global structure SO +% with fields +% - img - array of images to display +% - img structs contain fields +% vol - vol struct info (see spm_vol) +% can also be vol containing image as 3d matrix +% set with slice_overlay('AddBlobs'...) call +% cmap - colormap for this image +% nancol - color for NaN. If scalar, this is an index into +% the image cmap. If 1x3 vector, it's a colour +% prop - proportion of intensity for this cmap/img +% if = Inf, gives split cmap effect where values of +% this cmap override previous image cmap values +% func - function to apply to image before scaling to cmap +% (and therefore before min/max thresholding. E.g. a func of +% 'i1(i1==0)=NaN' would convert zeros to NaNs +% range - 2x1 vector of values for image to distribute colormap across +% the first row of the colormap applies to the first +% value in 'range', and the last value to the second +% value in 'range' +% outofrange - behavior for image values to the left and +% right of image limits in 'range'. Left means +% colormap values < 1, i.e for image values < +% range(1), if (range(1) +% range(1) where (range(1)>range(2)). If missing, +% display min (for Left) and max (for Right) value from colormap. +% Otherwise should be a 2 element cell array, where +% the first element is the colour value for image values +% left of 'range', and the second is for image values +% right of 'range'. Scalar values for +% colour index the colormap, 3x1 vectors are colour +% values. An empty array attracts default settings +% appropriate to the mode - i.e. transparent colour (where +% SO.prop ~= Inf), or split colour. Empty cells +% default to 0. 0 specifies that voxels with this +% colour do not influence the image (split = +% background, true = black) +% hold - resampling order for image (see spm_sample_vol) - +% default 1 +% background - value when resampling outside image - default +% NaN +% +% - transform - either - 4x4 transformation to apply to image slice position, +% relative to mm given by slicedef, before display +% or - text string, one of axial, coronal, sagittal +% These orientations assume the image is currently +% (after its mat file has been applied) axially +% oriented +% - slicedef - 2x3 array specifying dimensions for slice images in mm +% where rows are x,and y of slice image, and cols are neg max dim, +% slice separation and pos max dim +% - slices - vector of slice positions in mm in z (of transformed image) +% - figure - figure handle for slice display figure +% - refreshf - flag - if set or empty, refresh axis info for figure +% else assume this is OK +% - clf - flag, non zero -> clear figure before display. Redundant +% if refreshf == 0 +% - area struct with fields +% position - bottom left, x size y size 1x4 vector of +% area in which to display slices +% units - one of +% inches,centimeters,normalized,points,{pixels} +% halign - one of left,{center},right +% valign - one of top,{middle},bottom +% - xslices - no of slices to display across figure (defaults to an optimum) +% - cbar - if empty, missing, no colourbar. If an array of integers, then +% indexes img array, and makes colourbar for each cmap for +% that img. Cbars specified in order of appearance L->R +% - labels - struct can be absent (-> default numerical labels) +% empty (SO.labels = []) (no labels) or contain fields +% colour - colour for label text +% size - font size in units normalized to slice axes +% format - if = cell array of strings = +% labels for each slice in Z. If is string, specifies +% sprintf format string for labelling in distance of the +% origin (Xmm=0, Ymm=0) of each slice from plane containing +% the AC, in mm, in the space of the transformed image +% - callback - callback string for button down on image panels. E.g. +% setting SO.callback to 'slice_overlay(''getpos'')' prints to +% the matlab window the equivalent position in mm of the +% position of a mouse click on one of the image slices +% - printstr - string for printing slice overlay figure window, e.g. +% 'print -dpsc -painters -noui' (the default) +% - printfile - name of file to print output to; default 'slices.ps' +% +% FORMAT slice_overlay +% Checks, fills SO struct (slice_overlay('checkso')), and +% displays slice overlay (slice_overlay('display')) +% +% FORMAT slice_overlay('checkso') +% Checks SO structure and sets defaults +% +% FORMAT cmap = slice_overlay('getcmap',cmapname) +% Gets colormap named in cmapname string +% +% FORMAT [mx mn] = slice_overlay('volmaxmin', vol) +% Returns maximum and minimum finite values from vol struct 'vol' +% +% FORMAT slice_overlay('addspm',SPM,VOL,dispf) +% Adds SPM blobs as new img to SO struct, split effect, 'hot' colormap, +% Structures SPM and VOL are generated by calls to SPM results +% if not passed, they are fetched from the workspace +% If dispf is not passed, or nonzero, displays resulting SO figure also +% +% FORMAT slice_overlay('addblobs', imgno, XYZ, vals, mat) +% adds SPM blobs to img no 'imgno', as specified in +% XYZ - 3xN voxel coordinates of N blob values +% vals - N blob intensity values +% mat - 4x4 matrix specifying voxels -> mm +% +% FORMAT vol = slice_overlay('blobs2vol', XYZ, vals, mat) +% returns (pseudo) vol struct for 3d blob volume specified +% in matrices as above +% +% FORMAT slice_overlay('addmatrix', imgno, mat3d, mat) +% adds 3d matrix image vol to img imgno. Optionally +% mat - 4x4 matrix specifying voxels -> mm +% +% FORMAT vol = slice_overlay('matrix2vol', mat3d, mat) +% returns (pseudo) vol struct for 3d matrix +% input matrices as above +% +% FORMAT mmpos = slice_overlay('getpos') +% returns equivalent position in mm of last click on current axes (gca) +% if the axes contain an image slice (empty otherwise) +% +% FORMAT vals = slice_overlay('pointvals', XYZmm, holdlist) +% returns IxN matrix with values of each image 1..I, at each +% point 1..N specified in 3xN mm coordinate matrix XYZmm +% If specified, 'holdlist' contains I values giving hold +% values for resampling for each image (see spm_sample_vol) +% +% FORMAT slice_overlay('display') +% Displays slice overlay from SO struct +% +% FORMAT slice_overlay('print', filename, printstr) +% Prints slice overlay figure, usually to file. If filename is not +% passed/empty gets filename from SO.printfile. If printstr is not +% passed/empty gets printstr from SO.printstr +% +% V 0.8 2/8/00 +% More or less beta - take care. Please report problems to +% Matthew Brett matthew@mrc-cbu.cam.ac.uk + +global SO + +if nargin < 1 + checkso; + action = 'display'; +else + action = lower(action); +end + +switch action + case 'checkso' + checkso; + case 'getcmap' + varargout = {getcmap(varargin{1})}; + case 'volmaxmin' + [mx mn] = volmaxmin(varargin{1}); + varargout = {mx, mn}; + case 'addspm' + if nargin < 2 + varargin(1) = {evalin('base', 'SPM', ['error(''Cannot find SPM' ... + ' struct'')'])}; + end + if nargin < 3 + varargin(2) = {evalin('base', 'VOL', ['error(''Cannot find VOL' ... + ' struct'')'])}; + end + if nargin < 4 + varargin{3} = 1; + end + newimg = length(SO.img)+1; + SO.img(newimg).vol = blobs2vol(varargin{1}.XYZ,varargin{1}.Z, varargin{2}.M); + SO.img(newimg).prop = Inf; + SO.img(newimg).cmap = hot; + SO.img(newimg).range = [0 max(varargin{1}.Z)]; + SO.cbar = [SO.cbar newimg]; + if varargin{3} + checkso; + slice_overlay('display'); + end + + case 'addblobs' + addblobs(varargin{1},varargin{2},varargin{3},varargin{4}); + case 'blobs2vol' + varargout = {blobs2vol(varargin{1},varargin{2},varargin{3})}; + case 'addmatrix' + if nargin<3,varargin{2}='';end + if nargin<4,varargin{3}='';end + addmatrix(varargin{1},varargin{2},varargin{3}); + case 'matrix2vol' + if nargin<3,varargin{2}=[];end + varargout = {matrix2vol(varargin{1},varargin{2})}; + case 'getpos' + varargout = {getpos}; + case 'pointvals' + varargout = {pointvals(varargin{1})}; + case 'print' + if nargin<2,varargin{1}='';end + if nargin<3,varargin{2}='';end + printfig(varargin{1}, varargin{2}); + case 'display' + +% get coordinates for plane +X=1;Y=2;Z=3; +dims = SO.slicedef; +xmm = dims(X,1):dims(X,2):dims(X,3); +ymm = dims(Y,1):dims(Y,2):dims(Y,3); +zmm = SO.slices; +[y x] = meshgrid(ymm,xmm'); +vdims = [length(xmm),length(ymm),length(zmm)]; + +% no of slices, and panels (an extra for colorbars) +nslices = vdims(Z); +minnpanels = nslices; +cbars = 0; +if is_there(SO,'cbar') + cbars = length(SO.cbar); + minnpanels = minnpanels+cbars; +end + +% get figure data +% if written to, the axes may be specified already +figno = figure(SO.figure); + +% (re)initialize axes and stuff + +% check if the figure is set up correctly +if ~SO.refreshf + axisd = flipud(findobj(SO.figure, 'Type','axes','Tag', 'slice overlay panel')); + npanels = length(axisd); + if npanels < vdims(Z)+cbars; + SO.refreshf = 1; + end +end +if SO.refreshf + % clear figure, axis store + if SO.clf, clf; end + axisd = []; + + % prevent print inversion problems + set(figno,'InvertHardCopy','off'); + + % calculate area of display in pixels + parea = SO.area.position; + if ~strcmp(SO.area.units, 'pixels') + ubu = get(SO.figure, 'units'); + set(SO.figure, 'units','pixels'); + tmp = get(SO.figure, 'Position'); + ascf = tmp(3:4); + if ~strcmp(SO.area.units, 'normalized') + set(SO.figure, 'units',SO.area.units); + tmp = get(SO.figure, 'Position'); + ascf = ascf ./ tmp(3:4); + end + set(figno, 'Units', ubu); + parea = parea .* repmat(ascf, 1, 2); + end + asz = parea(3:4); + + % by default, make most parsimonious fit to figure + yxratio = length(ymm)*dims(Y,2)/(length(xmm)*dims(X,2)); + if ~is_there(SO, 'xslices') + % iteration needed to optimize, surprisingly. Thanks to Ian NS + axlen(X,:)=asz(1):-1:1; + axlen(Y,:)=yxratio*axlen(X,:); + panels = floor(asz'*ones(1,size(axlen,2))./axlen); + estnpanels = prod(panels); + tmp = find(estnpanels >= minnpanels); + if isempty(tmp) + error('Whoops, cannot fit panels onto figure'); + end + b = tmp(1); % best fitting scaling + panels = panels(:,b); + axlen = axlen(:, b); + else + % if xslices is specified, assume X is flush with X figure dimensions + panels([X:Y],1) = [SO.xslices; 0]; + axlen([X:Y],1) = [asz(X)/panels(X); 0]; + end + + % Axis dimensions are in pixels. This prevents aspect ratio rescaling + panels(Y) = ceil(minnpanels/panels(X)); + axlen(Y) = axlen(X)*yxratio; + + % centre (etc) panels in display area as required + divs = [Inf 2 1];the_ds = [0;0]; + the_ds(X) = divs(strcmp(SO.area.halign, {'left','center','right'})); + the_ds(Y) = divs(strcmp(SO.area.valign, {'bottom','middle','top'})); + startc = parea(1:2)' + (asz'-(axlen.*panels))./the_ds; + + % make axes for panels + r=0;c=1; + npanels = prod(panels); + lastempty = npanels-cbars; + for i = 1:npanels + % panel userdata + if i<=nslices + u.type = 'slice'; + u.no = zmm(i); + elseif i > lastempty + u.type = 'cbar'; + u.no = i - lastempty; + else + u.type = 'empty'; + u.no = i - nslices; + end + axpos = [r*axlen(X)+startc(X) (panels(Y)-c)*axlen(Y)+startc(Y) axlen']; + axisd(i) = axes(... + 'Parent',figno,... + 'XTick',[],... + 'XTickLabel',[],... + 'YTick',[],... + 'YTickLabel',[],... + 'Box','on',... + 'XLim',[1 vdims(X)],... + 'YLim',[1 vdims(Y)],... + 'Units', 'pixels',... + 'Position',axpos,... + 'Tag','slice overlay panel',... + 'UserData',u); + r = r+1; + if r >= panels(X) + r = 0; + c = c+1; + end + end +end + +% sort out labels +if is_there(SO,'labels') + labels = SO.labels; + if iscell(labels.format) + if length(labels.format)~=vdims(Z) + error(... + sprintf('Oh dear, expecting %d labels, but found %d',... + vdims(Z), length(labels.contents))); + end + else + % format string for mm from AC labelling + fstr = labels.format; + labels.format = cell(vdims(Z),1); + acpt = SO.transform * [0 0 0 1]'; + for i = 1:vdims(Z) + labels.format(i) = {sprintf(fstr,zmm(i)-acpt(Z))}; + end + end +end + +% modify colormaps with any new colours +nimgs = length(SO.img); +lrn = zeros(nimgs,3); +cmaps = cell(nimgs); +for i = 1:nimgs + cmaps(i)={SO.img(i).cmap}; + lrnv = {SO.img(i).outofrange{:}, SO.img(i).nancol}; + for j = 1:length(lrnv) + if prod(size(lrnv{j}))==1 + lrn(i,j) = lrnv{j}; + else + cmaps(i) = {[cmaps{i}; lrnv{j}(1:3)]}; + lrn(i,j) = size(cmaps{i},1); + end + end +end + +% cycle through slices displaying images +nvox = prod(vdims(1:2)); +pandims = [vdims([2 1]) 3]; % NB XY transpose for display + +zimg = zeros(pandims); +for i = 1:nslices + ixyzmm = [x(:)';y(:)';ones(1,nvox)*zmm(i);ones(1,nvox)]; + img = zimg; + for j = 1:nimgs + thisimg = SO.img(j); + % to voxel space of image + vixyz = inv(SO.transform*thisimg.vol.mat)*ixyzmm; + % raw data + if is_there(thisimg.vol, 'imgdata') + V = thisimg.vol.imgdata; + else + V = thisimg.vol; + end + i1 = spm_sample_vol(V,vixyz(X,:),vixyz(Y,:),vixyz(Z,:), ... + [thisimg.hold thisimg.background]); + if is_there(thisimg, 'func') + eval(thisimg.func); + end + % transpose to reverse X and Y for figure + i1 = reshape(i1, vdims(1:2))'; + % rescale to colormap + [csdata badvals]= scaletocmap(... + i1,... + thisimg.range(1),... + thisimg.range(2),... + cmaps{j},... + lrn(j,:)); + % take indices from colormap to make true colour image + iimg = reshape(cmaps{j}(csdata(:),:),pandims); + tmp = repmat(logical(~badvals),[1 1 3]); + if thisimg.prop ~= Inf % truecolor overlay + img(tmp) = img(tmp) + iimg(tmp)*thisimg.prop; + else % split colormap effect + img(tmp) = iimg(tmp); + end + end + % threshold out of range values + img(img>1) = 1; + + image('Parent', axisd(i),... + 'ButtonDownFcn', SO.callback,... + 'CData',img); + if is_there(SO,'labels') + text('Parent',axisd(i),... + 'Color', labels.colour,... + 'FontUnits', 'normalized',... + 'VerticalAlignment','bottom',... + 'HorizontalAlignment','left',... + 'Position', [1 1],... + 'FontSize',labels.size,... + 'ButtonDownFcn', SO.callback,... + 'String', labels.format{i}); + end +end +for i = (nslices+1):npanels + set(axisd(i),'Color',[0 0 0]); +end +% add colorbar(s) +for i = 1:cbars + axno = axisd(end-cbars+i); + cbari = SO.img(SO.cbar(i)); + cml = size(cbari.cmap,1); + p = get(axno, 'Position');; % position of last axis + cw = p(3)*0.2; + ch = p(4)*0.75; + pc = p(3:4)/2; + [axlims idxs] = sort(cbari.range); + a=axes(... + 'Parent',figno,... + 'XTick',[],... + 'XTickLabel',[],... + 'Units', 'pixels',... + 'YLim', axlims,... + 'FontUnits', 'normalized',... + 'FontSize', 0.075,... + 'YColor',[1 1 1],... + 'Tag', 'cbar',... + 'Box', 'off',... + 'Position',[p(1)+pc(1)-cw/2,p(2)+pc(2)-ch/2,cw,ch]... + ); + ih = image('Parent', a,... + 'YData', axlims(idxs),... + 'CData', reshape(cbari.cmap,[cml,1,3])); + +end + + otherwise + error(sprintf('Unrecognized action string %s', action)); + +% end switch action +end + +return + +function checkso +% checks and fills SO structure +global SO + +% figure +if is_there(SO, 'figure') + try + if ~strcmp(get(SO.figure,'Type'),'figure') + error('Figure handle is not a figure') + end + catch + error('Figure handle is not a valid figure') + end +else + % no figure handle. Try spm figure, then gcf + SO.figure = spm_figure('FindWin', 'Graphics'); + if isempty(SO.figure) + SO.figure = gcf; + end +end +% set defaults for SPM figure +if strcmp(get(SO.figure, 'Tag'),'Graphics') + % position figure nicely for SPM + defstruct = struct('position', [0 0 1 0.92], 'units', 'normalized', ... + 'valign', 'top'); + SO = set_def(SO, 'area', defstruct); + SO.area = set_def(SO.area, 'position', defstruct.position); + SO.area = set_def(SO.area, 'units', defstruct.units); + SO.area = set_def(SO.area, 'valign', defstruct.valign); +end +SO = set_def(SO, 'clf', 1); + +% orientation; string or 4x4 matrix +orientn = []; +SO = set_def(SO, 'transform', 'axial'); +if ischar(SO.transform) + orientn = find(strcmpi(SO.transform, {'axial','coronal','sagittal'})); + if isempty(orientn) + error(sprintf('Unexpected orientation %s', SO.transform)); + end + ts = [0 0 0 0 0 0 1 1 1;... + 0 0 0 pi/2 0 0 1 -1 1;... + 0 0 0 pi/2 0 -pi/2 -1 1 1]; + SO.transform = spm_matrix(ts(orientn,:)); +end +% default slice size, slice matrix depends on orientation +if ~is_there(SO,'slicedef' | ~is_there(SO, 'slices')) + % take image sizes from first image + V = SO.img(1).vol; + D = V.dim(1:3); + T = SO.transform * V.mat; + vcorners = [1 1 1; D(1) 1 1; 1 D(2) 1; D(1:2) 1; ... + 1 1 D(3); D(1) 1 D(3); 1 D(2:3) ; D(1:3)]'; + corners = T * [vcorners; ones(1,8)]; + SC = sort(corners'); + vxsz = sqrt(sum(T(1:3,1:3).^2)); + + SO = set_def(SO, 'slicedef',... + [SC(1,1) vxsz(1) SC(8,1);SC(1,2) vxsz(2) SC(8,2)]); + SO = set_def(SO, 'slices',[SC(1,3):vxsz(3):SC(8,3)]); +end + +% no colourbars by default +SO = set_def(SO, 'cbars', []); + +% always refresh figure window, by default +SO = set_def(SO, 'refreshf', 1); + +% labels +defstruct = struct('colour',[1 1 1],'size',0.075,'format', '%+3.0f'); +if ~isfield(SO, 'labels') % no field, -> default + SO.labels = defstruct; +elseif ~isempty(SO.labels) % empty -> no labels + % colour for slice labels + SO.labels = set_def(SO.labels, 'colour', defstruct.colour); + % font size normalized to image axis + SO.labels = set_def(SO.labels, 'size', defstruct.size); + % format string for slice labels + SO.labels = set_def(SO.labels, 'format', defstruct.format); +end + +% callback +SO = set_def(SO, 'callback', ';'); + +% figure area stuff +defarea = struct('position',[0 0 1 1],'units','normalized'); +SO = set_def(SO, 'area', defarea); +if ~is_there(SO.area, 'position') + SO.area = defarea; +end +if ~is_there(SO.area,'units') + if (all(SO.area.position>=0 & SO.area.position<=1)) + SO.area.units = 'normalized'; + else + SO.area.units = 'pixels'; + end +end +SO.area = set_def(SO.area,'halign', 'center'); +SO.area = set_def(SO.area,'valign', 'middle'); + +% printing +SO = set_def(SO, 'printstr', 'print -dpsc -painters -noui'); +SO = set_def(SO, 'printfile', 'slices.ps'); + +% fill various img arguments +% would be nice to use set_def, but we can't + +% set colour intensities as we go +remcol = 1; +for i = 1:length(SO.img) + if ~is_there(SO.img(i),'hold') + if ~is_there(SO.img(i).vol,'imgdata') + % normal file vol struct + SO.img(i).hold = 1; + else + % 3d matrix vol struct + SO.img(i).hold = 0; + end + end + if ~is_there(SO.img(i),'background') + SO.img(i).background = NaN; + end + if ~is_there(SO.img(i),'prop') + % default is true colour + SO.img(i).prop = remcol/(length(SO.img)-i+1); + remcol = remcol - SO.img(i).prop; + end + if ~is_there(SO.img(i),'range') + [mx mn] = volmaxmin(SO.img(i).vol); + SO.img(i).range = [mn mx]; + end + if ~is_there(SO.img(i),'cmap') + if SO.img(i).prop == Inf; % split map + if SO.range(1) 1 +% img(img>=0 & img<=1)=1; +% else +% img = img*(cml-1)+1; +% end +% outvals = {img<1, img>cml, isnan(img)}; +% img= round(img); +% badvals = zeros(size(img)); +% for i = 1:length(lrn) +% if lrn(i) +% img(outvals{i}) = lrn(i); +% else +% badvals = badvals | outvals{i}; +% img(outvals{i}) = 1; +% end +% end +% return + +function st = set_def(st, fld, def) +if ~is_there(st, fld) + st = setfield(st, fld, def); +end +return + +% function addblobs(imgno, xyz,vals,mat) +% global SO +% if isempty(imgno) +% imgno = length(SO.img); +% end +% if ~isempty(xyz) +% SO.img(imgno).vol = blobs2vol(xyz,vals,mat); +% end + +function vol = blobs2vol(xyz,vals,mat) +vol = []; +if ~isempty(xyz), + rcp = round(xyz); + vol.dim = max(rcp,[],2)'; + off = rcp(1,:) + vol.dim(1)*(rcp(2,:)-1+vol.dim(2)*(rcp(3,:)-1)); + vol.imgdata = zeros(vol.dim)+NaN; + vol.imgdata(off) = vals; + vol.imgdata = reshape(vol.imgdata,vol.dim); + vol.mat = mat; +end +return + +function addmatrix(imgno,mat3d,mat) +global SO +if isempty(imgno) + imgno = length(SO.img); +end +if nargin<3 + mat = []; +end +if ~isempty(mat3d) + SO.img(imgno).vol = matrix2vol(mat3d,mat); +end + +function vol = matrix2vol(mat3d,mat) +if nargin < 2 + mat = spm_matrix([]); +end +if isempty(mat) + mat = spm_matrix([]); +end +vol = []; +if ~isempty(mat3d) + vol.imgdata = mat3d; + vol.mat = mat; + vol.dim = size(mat3d); +end +return + +function [mx,mn] = volmaxmin(vol) +if is_there(vol, 'imgdata') + tmp = vol.imgdata(isfinite(vol.imgdata)); + mx = max(tmp); + mn = min(tmp); +else + mx = -Inf;mn=Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),[0 NaN]); + tmp = tmp(find(isfinite(tmp(:)))); + if ~isempty(tmp) + mx = max([mx; tmp]); + mn = min([mn; tmp]); + end + end +end +return + +% function cmap = getcmap(acmapname) +% % get colormap of name acmapname +% if ~isempty(acmapname) +% cmap = evalin('base',acmapname,'[]'); +% if isempty(cmap) % not a matrix, is it... +% % a colour name? +% tmp = strcmp(acmapname, {'red','green','blue'}); +% if any(tmp) +% cmap = zeros(64,3); +% cmap(:,tmp) = ((0:63)/63)'; +% else +% % a .mat file? +% [p f e] = fileparts(acmapname); +% acmat = fullfile(p, [f '.mat']); +% if exist(acmat, 'file') +% s = struct2cell(load(acmat)); +% cmap = s{1}; +% end +% end +% end +% end +% if size(cmap, 2)~=3 +% warning('Colormap was not an N by 3 matrix') +% cmap = []; +% end +% return + +function mmpos = getpos +% returns point location from last click, in mm +global SO +mmpos=[]; +pos = get(gca, 'CurrentPoint'); +u = get(gca, 'UserData'); +if is_there(u, 'type') + if strcmp(u.type, 'slice') % is slice panel + mmpos = (pos(1,1:2)'-1).*SO.slicedef(:,2)+SO.slicedef(:,1); + mmpos = inv(SO.transform) * [mmpos; u.no; 1]; + mmpos = mmpos(1:3,1); + end +end +return + +function vals = pointvals(XYZmm, holdlist) +% returns values from all the images at points given in XYZmm +global SO +if nargin < 2 + holdlist = [SO.img(:).hold]; +end +X=1;Y=2;Z=3; +nimgs = length(SO.img); +nvals = size(XYZmm,2); +vals = zeros(nimgs,nvals)+NaN; +if size(XYZmm,1)~=4 + XYZmm = [XYZmm(X:Z,:); ones(1,nvals)]; +end +for i = 1:nimgs + I = SO.img(i); + XYZ = I.vol.mat\XYZmm; + if ~is_there(I.vol, 'imgdata') + vol = I.vol; + else + vol = I.vol.imgdata; + end + vals(i,:) = spm_sample_vol(vol, XYZ(X,:), XYZ(Y,:),XYZ(Z,:),[holdlist(i) ... + I.background]); +end +return + +function printfig(filename,printstr) +% print slice overlay figure +% based on spm_figure print, and including fix from thence for ps printing +global SO; +if nargin < 1 + filename = []; +end +if isempty(filename) + filename = SO.printfile; +end +if nargin < 2 + printstr = ''; +end +if isempty(printstr) + printstr = SO.printstr; +end + +%-Note current figure, & switch to figure to print +cF = get(0,'CurrentFigure'); +set(0,'CurrentFigure',SO.figure) + +%-Temporarily change all units to normalized prior to printing +% (Fixes bizzarre problem with stuff jumping around!) +%----------------------------------------------------------------------- +H = findobj(get(SO.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +set(H,'Units','normalized') + +%-Print +%----------------------------------------------------------------------- +err = 0; +try, eval([printstr ' ' filename]), catch, err=1; end +if err + errstr = lasterr; + tmp = [find(abs(errstr)==10),length(errstr)+1]; + str = {errstr(1:tmp(1)-1)}; + for i = 1:length(tmp)-1 + if tmp(i)+1 < tmp(i+1) + str = [str, {errstr(tmp(i)+1:tmp(i+1)-1)}]; + end + end + str = {str{:}, '','- print command is:',[' ',printstr ' ' filename],... + '','- current directory is:',[' ',pwd],... + '',' * nothing has been printed *'}; + for i=1:length(str) + disp(str{i});end +end + +set(H,{'Units'},un) +set(0,'CurrentFigure',cF) + +return \ No newline at end of file diff --git a/xjview_labnic.m b/xjview_labnic.m new file mode 100644 index 0000000..81aaa27 --- /dev/null +++ b/xjview_labnic.m @@ -0,0 +1,8677 @@ +function xjview(varargin) +% xjview, version 4 +% +% usage 1: xjview (no argument) +% for displaying a result img file, or multiple image files, +% (which will be loaded later) and changing p-value or t/f-value +% usage 2: xjview(imagefilename) +% for displaying the result img file and changing p-value or +% t-value +% Example: xjView spmT_0002.img +% xjView('spmT_0002.img') +% xjView mymask.img +% usage 3: xjview(imagefilename1, imagefilename2, ...) +% for displaying the result img files and changing p-value or +% t/f-value +% Example: xjView spmT_0002.img spmT_0005.img spmT_0007.img +% xjView('spmT_0002.img', 'spmT_0003.img', 'spmT_0006.img') +% xjView myMask1.img myMask2.img myMask3.img +% usage 4: xjview(mnicoord, intensity) +% for displaying where are the mni coordinates +% mnicoord: Nx3 matrix of mni coordinates +% intensity: (optional) Nx1 matrix, usually t values of the +% corresponding voxels +% Example: xjView([20 10 1; -10 2 5],[1;2]) +% xjView([20 10 1; -10 2 5]) +% Note: to use xjview this way, you may need to modify the value +% of M and DIM in the begining of xjview.m +% +% http://people.hnl.bcm.tmc.edu/cuixu/xjView +% +% by Xu Cui and Jian Li 2/21/2005 +% last modified: 02/18/2007 (add colorbar max control) +% last modified: 11/16/2006 (keyboard shortcut for open image and open roi file) +% last modified: 06/16/2006 (spm5 compatible) +% last modified: 05/30/2006 (left/right flip, path of mask.img and templateFile.img) +% last modified: 05/08/2006 (debug CallBack_volumePush function, change handles.intensity{1} to intensity) +% last modified: 04/03/2006 (modify tr) +% last modified: 12/28/2005 (modify SPM process) +% +% Thank Sergey Pakhomov for sharing his database (MNI Space Utility). +% Thank Yuval Cohen for the maximize figure function (maximize.m) +% + +% TODO +% Send SPM to workspace + +warnstate = warning; +%warning off; +clc + +% pre-set values +% important! you need compare the display of xjview and spm. If you find +% xjview flipped the left/right, you need to set leftrightflip = 1; +% otherwise leave it to 0. +leftrightflip = 0; +% leftrightflip = 1 ; %must be on in the CMU... +% Now with spm-flip = 1; xjview-flip=1 + +% You only need to change M and DIM when you want to use xjview under +% 'usage 4'. +M = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +DIM = [41 48 35]'; +TR = 2; % you don't need to set TR is you only use the viewing part of xjview + +% system settings +try + spmdir = spm('dir'); + spm('defaults', 'fmri'); +catch + disp('Please add spm path.'); + warning(warnstate(1).state); + return +end + +if ispc + os = 'windows'; +elseif isunix + os = 'linux'; +else + warndlg('I don''t know what kind of computer you are using. I assumed it is unix.', 'What computer are you using?'); + os = 'linux'; +end +screenResolution = get(0,'ScreenSize'); + +xjviewpath = fileparts(which('xjview')); + +% pre-set values +pValue = 0.001; +intensityThreshold = 0; +clusterSizeThreshold = 5; + + +% Appearance Settings +figurePosition = [0.100, 0.050, 0.660, 0.880]; +sectionViewPosition = [0.5,0.61,0.45,0.45]; +glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +if screenResolution(3) <= 1024 + figurePosition = [0.100, 0.050, 0.700, 0.900]; + sectionViewPosition = [0.5, 0.61, 0.45, 0.46]; + glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +end + +left = 0.01; +editBoxHeight = 0.05; +editBoxWidth = 0.200; +editBoxLeft = 0.100; + +controlPanelPosition = [left, 0.080, 0.500, 0.500]; +stretchMatrix = diag([controlPanelPosition(3),controlPanelPosition(4),controlPanelPosition(3),controlPanelPosition(4)]); +controlPanelOffset = controlPanelPosition' .* [1,1,0,0]'; +heightUnit = 0.055; + +sliderPosition = stretchMatrix*[0.000, 0*heightUnit, 1.000, editBoxHeight]' + controlPanelOffset; +pValueTextPosition = stretchMatrix*[0.000, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pValueEditPosition = stretchMatrix*[0.110, 1*heightUnit, editBoxWidth*4/3, editBoxHeight]' + controlPanelOffset; +intensityThresholdTextPosition = stretchMatrix*[0.400, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +intensityThresholdEditPosition = stretchMatrix*[0.520, 1*heightUnit, editBoxWidth*3/3, editBoxHeight]' + controlPanelOffset; +dfTextPosition = stretchMatrix*[0.740, 1*heightUnit, 0.8-0.74, editBoxHeight]' + controlPanelOffset; +dfEditPosition = stretchMatrix*[0.800, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdTextPosition = stretchMatrix*[0.000, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdEditPosition = stretchMatrix*[0.150, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pickThisClusterPushPosition = stretchMatrix*[0.400, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +selectThisClusterPushPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +clearSelectedClusterPushPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +thisClusterSizeTextPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +thisClusterSizeEditPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +loadImagePushPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +imageFileEditPosition = stretchMatrix*[0.200, 3*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImagePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImageFileEditPosition = stretchMatrix*[0.200, 4*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveResultPSPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +resultPSFileEditPosition = stretchMatrix*[0.200, 5*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayIntensityTextPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth+0.1, editBoxHeight]' + controlPanelOffset; +allIntensityRadioPosition = stretchMatrix*[0.250, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +positiveIntensityRadioPosition = stretchMatrix*[0.400, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +negativeIntensityRadioPosition = stretchMatrix*[0.550, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderViewCheckPosition = stretchMatrix*[0.780, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +hideControlPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +volumePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +commonRegionPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +%knd +paramestPushPosition = stretchMatrix*[0.800, 4*heightUnit, editBoxWidth*.5, editBoxHeight]' + controlPanelOffset; +%-- +displayPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +allinonePushPosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchPushPosition = stretchMatrix*[0.000, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchContentEditPosition = stretchMatrix*[0.200, 6*heightUnit, editBoxWidth*2, editBoxHeight]' + controlPanelOffset; +searchTextPosition = stretchMatrix*[0.600, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchEnginePopPosition = stretchMatrix*[0.600, 6*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +overlayPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayEditPosition = stretchMatrix*[0.200, 5*heightUnit, 0.6-editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayPopPosition = stretchMatrix*[0.600, 5*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +helpPosition = stretchMatrix*[0.800, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +infoTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; +%xjViewPosition = stretchMatrix*[0.400, 13*heightUnit, editBoxWidth*2.5, editBoxHeight*3]' + controlPanelOffset; +%connameTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; + +sectionViewListboxPosition = [sectionViewPosition(1)+0.4, sectionViewPosition(2)+0.02, 0.1, 0.14]; +sectionViewMoreTargetPushPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.02,0.10,0.02]; +xHairCheckPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)+0.14,0.15,0.02]; +setTRangeEditPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.06,0.10,0.02]; +setTRangeTextPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.04,0.10,0.02]; + +getStructurePushPosition = [glassViewAxesPosition(1), glassViewAxesPosition(2)-0.06, editBoxWidth/2, editBoxHeight/2]; +structureEditPosition = [getStructurePushPosition(1), getStructurePushPosition(2), 1, getStructurePushPosition(4)]; +framePosition = (controlPanelPosition - controlPanelOffset')*1.05 + 0.95*controlPanelOffset'; + +%knd +setContrastNameTextPosition = [glassViewAxesPosition(1),glassViewAxesPosition(2)-0.026,0.6,0.03]; +setContrastListPosition = [setContrastNameTextPosition(1)+setContrastNameTextPosition(3)+.01,setContrastNameTextPosition(2),0.05,setContrastNameTextPosition(4)]; +setContrastListPosition = [glassViewAxesPosition(1)+.05*glassViewAxesPosition(3),glassViewAxesPosition(2)-0.026,glassViewAxesPosition(3)*.95,0.03]; +setIndivResultsListPosition = [setTRangeTextPosition(1)-0.25,setTRangeEditPosition(2),0.20,setTRangeEditPosition(4)]; +%-- knd + +% draw figure and control +figureBKcolor=[176/255 252/255 188/255]; +figureBKcolor=get(0,'Defaultuicontrolbackgroundcolor'); +f = figure('unit','normalized','position',figurePosition,'Color',figureBKcolor,'defaultuicontrolBackgroundColor', figureBKcolor,... + 'Name','xjView', 'Tag', 'xjView', 'NumberTitle','off','resize','off','CloseRequestFcn', {@CallBack_quit, warnstate(1).state}, 'visible','off'); +handles = guihandles(f); + +% databases +try + addpath g:\ndiayek\data\atlases\ + addpath ~/data/atlases + addpath /mount/usb/data/atlases +end +try + X = load('TDdatabase'); + handles.DB = X.DB; + handles.wholeMaskMNIAll = X.wholeMaskMNIAll; +catch + handles.DB = []; + handles.wholeMaskMNIAll = struct([]); + errordlg('I can''t find TDdatabase.mat','TDdatabase not found'); +end + +handles.figure = f; +handles.frame = uicontrol(handles.figure,'style','frame',... + 'unit','normalized',... + 'position',framePosition,... + 'Visible','off'); +handles.slider = uicontrol(handles.figure,'style','slider',... + 'unit','normalized',... + 'position',sliderPosition,... + 'max',1,'min',0,... + 'sliderstep',[0.01,0.10],... + 'callback',@CallBack_slider,... + 'value',0,'Visible','on'); +handles.pValueTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',pValueTextPosition,... + 'string','pValue=','horizontal','left'); +handles.pValueEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',pValueEditPosition,... + 'horizontal','left',... + 'String', num2str(pValue),... + 'BackgroundColor', 'w',... + 'callback',@CallBack_pValueEdit); +handles.intensityThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',intensityThresholdTextPosition,... + 'string',' intensity=','horizontal','left'); +handles.intensityThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',intensityThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(intensityThreshold),... + 'callback',@CallBack_intensityThresholdEdit); +handles.dfText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',dfTextPosition,... + 'string','df= ','horizontal','right'); +handles.dfEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',dfEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', '',... + 'callback',@CallBack_dfEdit); +handles.clusterSizeThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',clusterSizeThresholdTextPosition,... + 'string','cluster size >=','horizontal','left'); +handles.clusterSizeThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',clusterSizeThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(clusterSizeThreshold),... + 'callback',@CallBack_clusterSizeThresholdEdit); +handles.thisClusterSizeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',thisClusterSizeTextPosition,... + 'string','size= ','horizontal','right', 'visible', 'off'); +handles.thisClusterSizeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',thisClusterSizeEditPosition,... + 'horizontal','left',... + 'Enable', 'inactive',... + 'String', '','visible','off'); + +handles.imageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',imageFileEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_imageFileEdit,... + 'visible','off'); +handles.saveImageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',saveImageFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myMask.img',... + 'callback',@CallBack_saveImageFileEdit,... + 'visible','off'); +handles.saveResultPSEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',resultPSFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myResult.ps',... + 'callback',@CallBack_saveResultPSEdit,... + 'visible','off'); +handles.loadImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',loadImagePushPosition,... + 'string','Load Image','callback',@CallBack_loadImagePush,... + 'visible','off'); +handles.saveImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveImagePushPosition,... + 'string','Save Image','callback',@CallBack_saveImagePush,... + 'visible','off'); +handles.saveResultPSPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveResultPSPushPosition,... + 'string','Save Result','callback',@CallBack_saveResultPSPush,... + 'visible','off'); +handles.getStructurePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',getStructurePushPosition,... + 'string','Get Structure','callback',@CallBack_getStructurePush,'visible','off'); +handles.structureEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',structureEditPosition,... + 'horizontal','center',... + 'enable', 'on',... + 'UserData',struct(... + 'hReg', [],... + 'M', M,... + 'D', DIM,... + 'xyz', [0 0 0] )); +handles.pickThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',pickThisClusterPushPosition,... + 'string','Pick Cluster/Info','callback',@CallBack_pickThisClusterPush); +handles.selectThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',selectThisClusterPushPosition,... + 'string','Select Cluster','callback',@CallBack_selectThisClusterPush); +handles.clearSelectedClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',clearSelectedClusterPushPosition,... + 'string','Clear Selection','callback',@CallBack_clearSelectedClusterPush); + +handles.displayIntensityText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',displayIntensityTextPosition,... + 'string','display intensity','horizontal','left'); +handles.allIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','All',... + 'position',allIntensityRadioPosition,... + 'value', 1,... + 'callback',@CallBack_allIntensityRadio); +handles.positiveIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only +',... + 'position',positiveIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'+'}); +handles.negativeIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only -',... + 'position',negativeIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'-'}); +handles.renderViewCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','Render View' ,... + 'horizontal', 'right',... + 'position',renderViewCheckPosition,... + 'callback', @CallBack_renderViewCheck); + +handles.sectionViewListbox = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', {'single T1','avg152PD','avg152T1','avg152T2','avg305T1','ch2','ch2bet','aal','brodmann'}, ... + 'value',3,... + 'position',sectionViewListboxPosition,... + 'callback',@CallBack_sectionViewListbox); + +handles.xHairCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','XHairs Off' ,... + 'horizontal','left',... + 'position',xHairCheckPosition,... + 'callback',@CallBack_xHairCheck); +handles.sectionViewMoreTargetPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',sectionViewMoreTargetPushPosition,... + 'string','other ...','callback',@CallBack_sectionViewMoreTargetPush); +handles.setTRangeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',setTRangeEditPosition,'BackgroundColor', 'w',... + 'string','auto','callback',@CallBack_setTRangeEdit); +handles.setTRangeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setTRangeTextPosition,... + 'string','colorbar max'); +handles.hideControlPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', '<', 'position', hideControlPushPosition,... + 'visible','off'); +handles.volumePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'volume', ... + 'position', volumePushPosition,... + 'callback', @CallBack_volumePush); +handles.commonRegionPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'common region', ... + 'position', commonRegionPushPosition,... + 'callback', @CallBack_commonRegionPush); +handles.displayPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'display', ... + 'position', displayPushPosition,... + 'callback', @CallBack_displayPush,... + 'visible','off'); +handles.allinonePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'all in one', ... + 'position', allinonePushPosition,... + 'callback', @CallBack_allinonePush,... + 'visible','off'); +%knd: +handles.setContrastNameText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setContrastNameTextPosition, 'FontSize', 13,... + 'string',' ... ','callback',@CallBack_setContrastNameTextPosition); +handles.contrastListPush = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setContrastListPosition,... + 'callback', @CallBack_contrastListPush,... + 'visible','on'); + +handles.indivResultsListPush(1) = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setIndivResultsListPosition,... + 'callback', @CallBack_indivResultsListPush,... + 'visible','on'); + +handles.paramestPush(1) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Vox Betas', ... + 'position', paramestPushPosition'.*[1 1 2 1],... + 'callback', {@CallBack_paramestRegionPush, 'vox'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'vox', 0},... + 'visible','on'); +handles.paramestPush(2) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Cluster', ... + 'position', paramestPushPosition-[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'clu'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'clu', 0},... + 'visible','on'); +handles.paramestPush(3) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Sphere', ... + 'position', paramestPushPosition-2*[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'sph'},... + 'visible','on'); +%--knd + +handles.searchPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',searchPushPosition,... + 'String', 'search','callback',@CallBack_searchPush, 'ForeGroundColor',[0 0 1]); +handles.searchContentEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',searchContentEditPosition,... + 'ForeGroundColor',[0 0 1],... + 'BackgroundColor', 'w',... + 'horizontal','left','callback', @CallBack_searchContentEdit); +handles.searchText = uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',searchTextPosition,... + 'string', ' in',... + 'horizontal','left',... + 'visible','off'); +handles.searchEnginePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',searchEnginePopPosition, ... + 'String',{'Brede';'Jede';'xBrain.org';'Google Scholar';'Pubmed';'Wikipedia'}, ... + 'Style','popupmenu', ... + 'value',1); +handles.overlayPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',overlayPushPosition,... + 'String', 'overlay','callback',@CallBack_overlayPush); +handles.overlayEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',overlayEditPosition,... + 'BackgroundColor', 'w',... + 'horizontal','left',... + 'callback', @CallBack_overlayEdit); +handles.overlayPop = uicontrol(handles.figure, 'style','popupmenu',... + 'unit','normalized','position',overlayPopPosition,... + 'string', sort(fieldnames(handles.wholeMaskMNIAll)),... + 'horizontal','left',... + 'callback', @CallBack_overlayPop); + +handles.helpPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',helpPosition,... + 'String', 'help','callback','web http://people.hnl.bcm.tmc.edu/cuixu/xjView','ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.infoTextBox = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',infoTextBoxPosition,... + 'String', 'Welcome to xjView 4','ForeGroundColor','k', 'BackgroundColor', 'w',... + 'horizontal','left', ...'fontname','times',... + 'max',2, 'min',0); +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + set(handles.infoTextBox, 'String', s); +end + +handles.glassViewAxes = axes('unit','normalized','position',glassViewAxesPosition,'XTick',[],'YTick',[],'visible','off'); + + +handles.testEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',[0.1 0.4 0.2 0.05],... + 'horizontal','left',... + 'callback',@test,... + 'visible','off'); + +% menu +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +hMenuFile = findobj(get(handles.figure,'Children'),'flat','Label','&File'); +if ~isempty(hMenuFile) + hMenuFileOpen = findobj(get(handles.figure,'Children'),'Label','&Open...'); + set(hMenuFileOpen, 'label', 'Open Figure...'); + hMenuFileSave = findobj(get(handles.figure,'Children'),'Label','&Save'); + set(hMenuFileSave, 'label', 'Save Figure ...'); + hMenuFileSaveAs = findobj(get(handles.figure,'Children'),'Label','Save &As...'); + set(hMenuFileSaveAs, 'label', 'Save Figure As ...'); +else + hMenuFile = uimenu(handles.figure, 'label', '&File'); +end + +set(hMenuFile,'ForegroundColor',[0 0 1]); +set(findobj(hMenuFile,'Position',1),'Separator','on'); +%knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open SPM file (SPM.mat) ...',... + 'CallBack',@CallBack_loadSPMmat, 'Accelerator', 'o'); +%--knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open Images (*.img) ...',... + 'CallBack',@CallBack_loadImagePush, 'Accelerator', 'o'); +uimenu('Parent',hMenuFile,'Position',2,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 0}); +uimenu('Parent',hMenuFile,'Position',3,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image as Mask (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 1}); +uimenu('Parent',hMenuFile,'Position',4,'ForegroundColor',[0 0 1],... + 'Label','Save Result (*.ps/pdf) ...',... + 'CallBack',@CallBack_saveResultPSPush); + +hMenuHelp = findobj(get(handles.figure,'Children'),'flat','Label','&Help'); +if isempty(hMenuHelp) + hMenuHelp = uimenu(handles.figure, 'label', 'xjView &Help'); +end +set(hMenuHelp,'ForegroundColor',[0 0 1]); +uimenu('Parent',hMenuHelp,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','xBrain.org: brain mapping database',... + 'CallBack','web http://www.xbrain.org -browser'); +uimenu('Parent',hMenuHelp,'Position',2,... + 'Label','xjview help','ForegroundColor',[0 0 1],... + 'CallBack','web http://people.hnl.bcm.tmc.edu/cuixu/xjView'); +set(findobj(hMenuHelp,'Position',3),'Separator','on'); +set(0,'ShowHiddenHandles',cSHH) + +if exist('cuixuBOLDretrieve') + hMenuAnalyze = uimenu('label','&Analyze','ForegroundColor',[0 0 1],'visible','on'); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess); + hMenuProcess = uimenu(hMenuAnalyze,'label','Process (GLM estimation)','ForegroundColor',[0 0 1],'callback',@CallBack_process); + hMenuSPMProcess = uimenu(hMenuAnalyze,'label','SPMProcess (GLM using SPM)','ForegroundColor',[0 0 1],'callback',@CallBack_SPMProcess); + hMenuGLMPeak = uimenu(hMenuAnalyze,'label','GLM on peak BOLD','ForegroundColor',[0 0 1],'callback',@CallBack_GLMPeak); + hMenuContrast = uimenu(hMenuAnalyze,'label','Contrast','ForegroundColor',[0 0 1],'callback',@CallBack_contrast); + hMenuFDR = uimenu(hMenuAnalyze,'label','FDR','ForegroundColor',[0 0 1],'callback',@CallBack_fdr); + hMenuROI = uimenu(hMenuAnalyze,'label','ROI: retrieve signal','ForegroundColor',[0 0 1],'callback',@CallBack_timeSeries); + hMenuROIPlot = uimenu(hMenuAnalyze,'label','ROI: plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotROI, 'Accelerator', 'm'); + hMenuROIIndividualPlot = uimenu(hMenuAnalyze,'label','ROI: individual plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROI); + hMenuROIIndividualPlotWithBehavior = uimenu(hMenuAnalyze,'label','ROI: individual plot with behavior','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROIWithBehavior); + hMenuROICorrelationPlot = uimenu(hMenuAnalyze,'label','ROI: correlation plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotCorrelationROI); + %hMenuWholeBrainCorrelation = uimenu(hMenuAnalyze,'label','Whole brain correlation','ForegroundColor',[0 0 1],'callback',@CallBack_wholeBrainCorrelation); + hMenuBehaviorAnalysis = uimenu(hMenuAnalyze,'label','Behavior analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_behaviorAnalysis); + hMenuHeadMovementAnalysis = uimenu(hMenuAnalyze,'label','Head movement analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_headMovementAnalysis); + hMenuModelComparison = uimenu(hMenuAnalyze,'label','Linear model comparison','ForegroundColor',[0 0 1],'callback',@CallBack_modelComparison); + + hMenuHNLOnly = uimenu('label','For H&NL Only','ForegroundColor',[0 0 1],'visible','on'); + hMenuNew2Old = uimenu(hMenuHNLOnly,'label','Format convert','ForegroundColor',[0 0 1],'callback',@CallBack_new2old); + hMenuPreprocessCluster = uimenu(hMenuHNLOnly,'label','Preprocess (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_preprocess, 'cluster'}); + hMenuProcessCluster = uimenu(hMenuHNLOnly,'label','Process (GLM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_process, 'cluster'}); + hMenuSPMProcessCluster = uimenu(hMenuHNLOnly,'label','SPM Process (GLM using SPM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_SPMProcess, 'cluster'}); + hMenuGLMPeakCluster = uimenu(hMenuHNLOnly,'label','GLM on peak BOLD (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_GLMPeak, 'cluster'}); +end + +figurecm = uicontextmenu; +uimenu(figurecm,'label','Red','callback','set(gcf,''color'',''r'')'); +uimenu(figurecm,'label','White','callback','set(gcf,''color'',''w'')'); +uimenu(figurecm,'label','Gray','callback','set(gcf,''color'',[0.925, 0.914, 0.847])'); +%set(handles.figure,'uicontextmenu',figurecm); +set(handles.figure,'WindowButtonDownFcn',@figureMouseUpFcn); + +set(handles.figure,'visible','on'); + +% save pre-set values +handles.system = os; +handles.spmdir = spmdir; +handles.screenResolution = screenResolution; +handles.pValue = pValue; +handles.intensityThreshold = intensityThreshold; +handles.clusterSizeThreshold = clusterSizeThreshold; +handles.sectionViewPosition = sectionViewPosition; +handles.sectionViewTargetFile = getSectionViewTargetFile(spmdir, 'avg152T1'); +%knd +if exist('xjview.opt') + tmp=textread('xjview.opt','%s');eval(tmp{:}); + handles.sectionViewTargetFile = anatomy; +else + if ~isempty(findstr('gazemo', pwd)) + handles.sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean.img'); + end +end +guidata(f, handles); + +% global variables for rotation matrix M and dimension +global M_; +global DIM_; +global TR_; +global LEFTRIGHTFLIP_; +global TMAX_; % colorbar max to display in section view +M_ = M; +DIM_ = DIM; +TR_ = TR; +LEFTRIGHTFLIP_ = leftrightflip; +TMAX_ = 'auto'; + +% check input arguments +if length(varargin) == 0 + CallBack_loadSPMmat(handles.loadImagePush) + % if exist(fullfile(pwd,'SPM.mat'), 'file') + % xSPM=load(fullfile(pwd,'SPM.mat')); + % numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', length(xSPM.SPM.xCon)); + % if ~isempty(numc) + % CallBack_loadImagePush(handles.loadImagePush, [], {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)}); + % end + % end +elseif isstr(varargin{1}) + if isempty(findstr('.mat', varargin{1})) + CallBack_loadImagePush(handles.loadImagePush, [], varargin); + else + CallBack_loadSPMmat(handles.loadImagePush, [], varargin{1}); + end +else + mniCoord = varargin{1}; + if length(varargin) < 2 + intensity = ones(size(mniCoord,1),1); + else + intensity = varargin{2}; + end + thisStruct.mni = mniCoord; + thisStruct.intensity = intensity; + thisStruct.M = M; + thisStruct.DIM = DIM'; + CallBack_loadImagePush(handles.loadImagePush, [], thisStruct); +end + + + +function test(hObject, eventdata) +handles = guidata(gcbo); +set(hObject, 'String', num2str(handles.pValue)); +vars = evalin('base','who'); +vars +x = evalin('base',vars{1}); +x +handles.DIM + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdr(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); + +if get(handles.allIntensityRadio, 'Value') + positive = 1; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end +xjviewpath = fileparts(which('xjview')); +maskImageFile = fullfile(xjviewpath, 'mask.img'); +[threshold, pvalue] = fdr(handles.imageFileName{1}, q, positive, maskImageFile); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% model comparison +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_modelComparison(hObject, eventdata) +answer = getVariable({'y','x (full model)', 'x (reduced model)'}); + +if isempty(answer) + return; +end + +if ~isempty(answer{1}) + y = evalin('base',answer{1}); +else + return; +end +if ~isempty(answer{2}) + xf = evalin('base',answer{2}); % full model +else + return; +end +if ~isempty(answer{3}) + xr = evalin('base',answer{3}); % reduced model +else + xr = []; +end + +% make vector column vector +[r, c] = size(y); +if r==1; y = y'; end +[r, c] = size(xf); +if r(0.5+ii/10); +end + +K = {zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1))}; +for ii=1:size(C,1) + for jj=1:4 + K{jj}(ii) = sum(CC{jj}(ii,:)) - 1; + end +end + +x=[0:size(C,1)]; +for jj=1:4 + y{jj}=zeros(size(x)); +end + +for ii=1:length(x) + for jj=1:4 + y{jj}(ii) = sum(K{jj} == x(ii)); + end +end + +figure; +loglog(x,y{1}, x, y{2}, x, y{3}, x, y{4}); +xlabel('degree'); +ylabel('counts'); +legend('0.6', '0.7', '0.8', '0.9'); +axis equal + + +z = sum(abs(C))-1; +zx = 0:max(z); +for ii=1:length(zx)-1 + pos = find(z>zx(ii) & z<=zx(ii+1)); + zy(ii) = length(pos); +end +figure; +loglog(zx(1:length(zy)),zy); +xlabel('weighted degree'); +ylabel('counts'); +axis equal + +xjview(cor2mni(coord, handles.M{1}), z); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get/select variable names in base workspace +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function vars = getVariable(titles) +vars = evalin('base','who'); +height = 0.07; +f = dialog('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.4 0.4], 'name', 'pick variables', 'NumberTitle','off'); +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', 'Available variables', ... + 'position',[0 0.9 0.5 0.1/2]); +variableListbox = uicontrol(f,'style','listbox','tag','variableListbox',... + 'unit','normalized',... + 'String', vars, ... + 'value',1,... + 'position',[0 0 0.5 0.9]); +okPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'OK', ... + 'position',[0.55 0.05 0.2 height],... + 'callback','uiresume'); +cancelPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'Cancel', ... + 'position',[0.75 0.05 0.2 height],... + 'callback','delete(gcf)'); + +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{1}, ... + 'position',[0.5 0.9 0.5 0.1/2]); +imageDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.8 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''imageDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); +imageDataEdit = uicontrol(f,'style','edit','tag','imageDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.8 0.3 height]); + +if length(titles)>=2 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{2}, ... + 'position',[0.5 0.7 0.5 0.1/2]); + eventDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.6 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''eventDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + eventDataEdit = uicontrol(f,'style','edit','tag','eventDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.6 0.3 height]); +end +if length(titles)>=3 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{3}, ... + 'position',[0.5 0.5 0.5 0.1/2]); + correlatorDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.4 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''correlatorDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + correlatorDataEdit = uicontrol(f,'style','edit','tag','correlatorDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.4 0.3 height]); +end +if length(titles)>=4 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{4}, ... + 'position',[0.5 0.3 0.5 0.1/2]); + otherDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.2 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''otherDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + otherDataEdit = uicontrol(f,'style','edit','tag','otherDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.2 0.3 height]); +end + +uiwait(f); +try + var{1} = get(imageDataEdit,'string'); + if length(titles)>=2 + var{2} = get(eventDataEdit,'string'); + end + if length(titles)>=3 + var{3} = get(correlatorDataEdit,'string'); + end + if length(titles)>=4 + var{4} = get(otherDataEdit,'string'); + end + vars = var; + delete(f); +catch + vars = {}; + try + delete(f); + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% quit xjview +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_quit(hObject, eventdata, warnstate) +warning(warnstate) +% try +% rmdir('xjviewtmp'); +% end +delete(gcf); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mouse double click +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function figureMouseUpFcn(hObject, eventdata) +status = get(hObject, 'SelectionType'); + +% double click +if strcmp(status, 'extend') + handles = guidata(hObject); + CallBack_loadImagePush(handles.loadImagePush, eventdata); +elseif strcmp(status, 'open') + handles = guidata(hObject); + CallBack_loadSPMmat(handles.loadImagePush, eventdata); +else + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change edit image file name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_imageFileEdit(hObject, eventdata) +handles = guidata(hObject); +filename = get(hObject, 'String'); +filename = str2cell(filename); +CallBack_loadImagePush(handles.loadImagePush, eventdata, filename); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_contrastListPush(hObject, eventdata) +handles = guidata(hObject); +connum = get(handles.contrastListPush,'Value'); +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); +if ~exist(spmfile) + set(handles.contrastListPush,'Value',0); +else + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + connames=get(handles.contrastListPush,'String'); + CallBack_loadImagePush(hObject,eventdata,fullfile(img.p, cons(connum).Vspm.fname), connum) +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadImagePush(hObject, eventdata, thisfilename, ContrastName) +handles = guidata(hObject); +handles.imageFileName=[]; handles.M=[]; handles.DIM=[]; handles.TF=[]; handles.df=[]; +handles.mni=[]; handles.intensity=[]; handles.currentmni=[]; handles.currentintensity=[]; handles.currentDisplayMNI=[]; handles.currentDisplayIntensity=[]; +if nargin>3 + handles.imageContrastName=ContrastName; +else + handles.imageContrastName=[]; +end +if ~exist('thisfilename') + thisfilename = ''; +end + +if isstruct(thisfilename) + handles.imageFileName = {''}; + handles.mni = {thisfilename.mni}; + handles.intensity = {thisfilename.intensity}; + handles.M = {thisfilename.M}; + handles.DIM = {thisfilename.DIM}; + handles.TF = {'S'}; + handles.df = {1e6}; + handles.pValue = 1; + set(handles.pValueEdit, 'string', '1'); + handles.clusterSizeThreshold = 0; + set(handles.clusterSizeThresholdEdit, 'String', '0'); + handles.imageContrastName={''}; +else + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); +end + +if isempty(handles.imageFileName) + return +end + +% tries to find firts-level matching data +% knd +set(handles.indivResultsListPush(1),'String', ... + getfield2(dir(fileparts(fileparts(handles.imageFileName{1}))), 'name')); + +different = 0; % image files are same or different? +if length(handles.TF)>1 + for ii=1:length(handles.TF) + if strcmp(handles.TF{ii},handles.TF{1}) & isequal(handles.df{ii},handles.df{1}) & isequal(handles.M{ii},handles.M{1}) & isequal(handles.DIM{ii},handles.DIM{1}) + continue; + else + warndlg('Images are from different statistics or sources.', 'Warning'); + %set(handles.infoTextBox, 'string', 'Images are from different statistics or sources.'); + beep; + different = 1; + break; + end + end +end + +% reset files with empty df/TF to df=1 and TF='S'. 'S'=='T' but has a tag +% meaning it is changed. +resetTF = 0; +for ii=1:length(handles.TF) + if isempty(handles.TF{ii}) + handles.TF{ii} = 'S'; + resetTF = 1; + end + if isempty(handles.df{ii}) | isequal(handles.df{ii},0) + handles.df{ii} = 1e6; + resetTF = 1; + end +end + +handles.currentmni = handles.mni; +handles.currentintensity = handles.intensity; + +set(handles.dfEdit, 'String', cell2str(handles.df)); +set(handles.imageFileEdit, 'String', cell2str(handles.imageFileName)); % s=-log10(p) +maxs = maxcell(t2s(cellmax(handles.intensity,'abs'),handles.df, handles.TF),'abs'); +if isinf(maxs); maxs = 20; end +set(handles.slider, 'Max', maxs, 'Min', 0, 'sliderstep',[min(maxs/100,0.05),min(maxs/100,0.05)]); +if handles.TF{1}=='T' & different == 0 + str = [blanks(length(' intensit')) 'T=']; +elseif handles.TF{1}=='F' & different == 0 + str = [blanks(length(' intensit')) 'F=']; +else + str=' intensity='; +end +set(handles.intensityThresholdText, 'String', str); +set(handles.figure,'Name',['xjView: ' cell2str(handles.imageFileName)]); +try + for ii=1:length(handles.hLegend) + delete(handles.hLegend{ii}); + end +end +nimg=length(handles.TF); +if nimg>1 + colours = {'r';'g';'y';'c';'b';'m'}; + %colours = colours(mod(0:nimg-1,length(colours))+1); + %colours = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],100,1); + % read_conname = spm_input({'Retrieve contrasts names','Should I read SPM files to retrieve filenames?'},... + % 1,'bd',{'YES','NO'},[1,0]); + read_conname = 1; + for ii=1:nimg + [tmp,filename] = fileparts(handles.imageFileName{ii}); + c_names{ii} = filename ; + if read_conname & exist(fullfile(tmp, 'SPM.mat')) + tmp=load(fullfile(tmp, 'SPM.mat')); + tmp.Vspm=[tmp.SPM.xCon.Vspm]; + tmp.iCon=strmatch(filename, {tmp.Vspm.fname}); + if ~isempty(tmp.iCon) + c_names{ii} = [ [tmp.SPM.xCon(tmp.iCon).name] ' [' c_names{ii} ']']; + end + end + end + [tmp] = inputdlg({'colors' 'names'},'Loading',6,[{strvcat(c_names)};{strvcat(colours)}]); + colours = colorname2rgb(tmp{2}); + c_names = cellstr(tmp{1}); + + for ii=1:min(length(handles.TF),10) + filename = c_names{ii}; + if ii == 10; filename = '......'; end + pos0 = handles.sectionViewPosition; + pos(1) = pos0(1)+pos0(3)/2+0.03; + pos(2) = pos0(2)+ii/50-0.03; + pos(3) = 0.12; + pos(4) = 0.02; + handles.hLegend{ii}=uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',pos,... + 'string', filename,... + 'horizontal','left',... + 'fontweight','bold',... + 'ForeGroundColor',colours(ii,:)); + end + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; +end +guidata(hObject, handles); + +global M_; +global DIM_; +M_ = handles.M{1}; +DIM_ = handles.DIM{1}; + +if resetTF==1 + set(handles.pValueEdit,'string',1); +end +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% display info +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + report{1} = s; +catch + report{1} = 'Welcome to xjView 4'; +end +for jj=1:length(handles.imageFileName) + report{2+6*(jj-1)} = cell2str(handles.imageFileName(jj)); + if handles.TF{jj} == 'T' | handles.TF{jj} == 'F' + report{3+6*(jj-1)} = ['This is a ' handles.TF{jj} ' test image.']; + else + report{3+6*(jj-1)} = '';%['I don''t know what test this image came from.']; + end + report{4+6*(jj-1)} = 'mat = '; + report{5+6*(jj-1)} = num2str(handles.M{jj}); + report{6+6*(jj-1)} = 'dimension = '; + report{7+6*(jj-1)} = num2str(handles.DIM{jj}); +end +if length(handles.imageFileName)==1 + [img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); + spmfile=fullfile(img.p,'SPM.mat'); + if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); + end + end + if exist(spmfile) + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + for i=1:length(cons) + if not(isempty(cons(i).Vspm)) + consfilename{i}=cons(i).Vspm.fname; + else + consfilename{i}=''; + end + end + connum=strmatch([img.fname img.ext],consfilename); + if ~isempty(connum) + conlabel=cons(connum).name; + set(handles.figure,'Name',[get(handles.figure,'Name') ' :: ' conlabel]); + set(handles.contrastListPush,'String',{cons.name}) + set(handles.contrastListPush,'Value',connum) + set(handles.setContrastNameText,'String',[conlabel]); + report=[report(1:3) {['Contrast name in SPM.mat: (' num2str(connum) ') ' conlabel]} report(4:end)]; + else + set(handles.contrastListPush,'String',{'[none]'}) + set(handles.contrastListPush,'Value',0) + set(handles.contrastListPush,'Enable','on') + report=[report(1:3) {['Contrast has no matching name in SPM.mat']} report(4:end)]; + end + end +end +set(handles.infoTextBox, 'string', report); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pValueEdit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pValueEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +tmps = -log10(tmp); +if isnan(tmp) | tmp < 0 | tmp > 1 + errordlg('I don''t understand the input.','error'); + set(hObject, 'String', handles.pValue); + return +end + +if tmps>get(handles.slider,'max') | tmps maxcell(cellmax(handles.intensity,'abs')) + tmp = maxcell(cellmax(handles.intensity,'abs')); +end + +handles.pValue = t2p(tmp, handles.df{1}, handles.TF{1}); +handles.intensityThreshold = p2t(num2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); +set(handles.slider,'Value', -log10(handles.pValue)); +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +guidata(hObject, handles); +CallBack_slider(hObject, eventdata, -log10(handles.pValue)); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% slider bar +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_slider(hObject, eventdata, value) + +handles = guidata(hObject); + +if exist('value') + s = value; + if s > get(handles.slider,'max') + s = get(handles.slider,'max')*0.99; + end + if s < get(handles.slider,'min') + s = get(handles.slider,'min'); + end +else + s = get(hObject,'Value'); +end + +set(handles.slider, 'value', s); +pvalue = 10^(-s); +set(handles.pValueEdit,'String',num2str(pvalue)); +t = p2t(num2cell(pvalue*ones(1,length(handles.TF))), handles.df, handles.TF); +handles.intensityThreshold = t; +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +handles.pValue = pvalue; +for ii=1:length(handles.TF) + pos{ii} = find(abs(handles.intensity{ii})>=t{ii}); + handles.currentintensity{ii} = handles.intensity{ii}(pos{ii}); + handles.currentmni{ii} = handles.mni{ii}(pos{ii},:); +end + +guidata(hObject,handles); + +if get(handles.allIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.allIntensityRadio, eventdata); +elseif get(handles.positiveIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.positiveIntensityRadio, eventdata, '+'); +elseif get(handles.negativeIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.negativeIntensityRadio, eventdata, '-'); +end + +set(handles.infoTextBox, 'string', {'Don''t drag the slider bar too fast. Release your mouse button at least 1 second later.', ... + 'This sounds stupid. But there is a bug (probably MatLab bug) which I can'' fix right now.', ... + 'I suggest you confirm the correctness of the current display by press Enter in the pValue edit box.'}); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display intensity all+- radios +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allIntensityRadio(hObject, eventdata, pnall) +% pnall = '+', '-', 'a' (all) or 'c' for current (simply update drawing) +% +handles = guidata(hObject); + +currentselect = []; +if get(handles.allIntensityRadio, 'Value'); currentselect = handles.allIntensityRadio; thispnall = 'a'; end +if get(handles.positiveIntensityRadio, 'Value'); currentselect = handles.positiveIntensityRadio; thispnall = '+'; end +if get(handles.negativeIntensityRadio, 'Value'); currentselect = handles.negativeIntensityRadio; thispnall = '-'; end + +set(handles.allIntensityRadio, 'Value', 0); +set(handles.positiveIntensityRadio, 'Value', 0); +set(handles.negativeIntensityRadio, 'Value', 0); + +if exist('pnall') + if pnall=='c' + hObject = currentselect; + pnall = thispnall; + end +end + +set(hObject, 'Value', 1); + +if ~isfield(handles,'currentintensity') + return +end +for ii=1:length(handles.TF) + if exist('pnall') + if pnall == '-' + pos{ii} = find(handles.currentintensity{ii} < 0); + elseif pnall == '+' + pos{ii} = find(handles.currentintensity{ii} > 0); + elseif pnall == 'a' + pos{ii} = 1:length(handles.currentintensity{ii}); + end + else + pos{ii} = 1:length(handles.currentintensity{ii}); + end + intensity{ii} = handles.currentintensity{ii}(pos{ii}); + mni{ii} = handles.currentmni{ii}(pos{ii},:); + cor{ii} = mni2cor(mni{ii}, handles.M{ii}); + + if ~isempty(cor{ii}) + A = spm_clusters(cor{ii}'); + pos0 = []; + for kk = 1:max(A) + jj = find(A == kk); + if length(jj) >= handles.clusterSizeThreshold; pos0 = [pos0 jj]; end + end + handles.currentDisplayMNI{ii} = mni{ii}(pos0,:); + handles.currentDisplayIntensity{ii} = intensity{ii}(pos0); + else + handles.currentDisplayMNI{ii} = mni{ii}([],:); + handles.currentDisplayIntensity{ii} = intensity{ii}([]); + end +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% list of contrasts + +set(handles.contrastListPush,'String',regexprep(get(handles.contrastListPush,'String'),' \[Only [\+-a]\]$','')) +set(handles.setContrastNameText,'String',regexprep(get(handles.setContrastNameText,'String'),' \[Only [\+-a]\]$','')) + +if exist('pnall','var') + if ~isequal(pnall, 'a') + set(handles.setContrastNameText,'String',[get(handles.setContrastNameText,'String') ' [Only ' pnall ']']); + s=get(handles.contrastListPush,'String'); + s{get(handles.contrastListPush,'Value')}=[s{get(handles.contrastListPush,'Value')} ' [Only ' pnall ']']; + + set(handles.contrastListPush,'String',s); + end +end + +if get(handles.allIntensityRadio, 'Value') & max(handles.currentDisplayIntensity{1}) < 0 + warndlg('No supra-threshold positive intensity. Only negative intensity is displayed.'); +end + +try + set(handles.figure,'currentaxes', handles.glassViewAxes); + xrange = xlim; + yrange = ylim; + try + delete(handles.hGlassText) + end + if ~isempty(handles.selectedCluster,1) + %handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + end +end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% render view check? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderViewCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% which section view target file? list box +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewListbox(hObject, eventdata) +handles = guidata(hObject); +contents = get(handles.sectionViewListbox,'String'); +currentsel = contents{get(handles.sectionViewListbox,'Value')}; +handles.sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get sectionviewtargetfile +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sectionViewTargetFile = getSectionViewTargetFile(spmdir, selectedcontent) +if findstr('SPM2',spm('ver')) + fileext = 'mnc'; +elseif findstr('SPM5',spm('ver')) + fileext = 'nii'; +else + fileext = 'nii'; +end +currentsel = selectedcontent; +if ~isempty(strfind(currentsel, 'single')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['single_subj_T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152PD')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152PD.' fileext]); +elseif ~isempty(strfind(currentsel, '152T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152T2')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T2.' fileext]); +elseif ~isempty(strfind(currentsel, '305T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg305T1.' fileext]); +elseif strcmp(currentsel, 'ch2') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2.img'); +elseif strcmp(currentsel, 'ch2bet') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2bet.img'); +elseif strcmp(currentsel, 'aal') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'aal.img'); +elseif strcmp(currentsel, 'brodmann') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'brodmann.img'); + %knd: +elseif ~isempty(strfind(currentsel, 'gazemo')) + sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean-no120.img'); + %sectionViewTargetFile = fullfile('D:\ndiayek\data\gazemo\group\anat', 'mean-no120.img'); +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% xhairs in section view? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_xHairCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + spm_orthviews('Xhairs','off'); +else + spm_orthviews('Xhairs','on'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% other target file for section view, push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewMoreTargetPush(hObject, eventdata) +handles = guidata(hObject); +[filename, pathname, filterindex] = uigetfile('*', 'Pick an target file'); +if isequal(filename,0) | isequal(pathname,0) + return; +end +handles.sectionViewTargetFile = fullfile(pathname, filename); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% set colorbar range +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_setTRangeEdit(hObject, eventdata) +global TMAX_; +handles = guidata(hObject); +TMAX_ = get(hObject, 'String'); +if isempty(str2num(TMAX_)) && ~strcmp(TMAX_, 'auto') + return; +end +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change degree of freedome +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_dfEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2cell(get(hObject, 'String')); +if iscellstr(tmp) + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.df); + catch + set(hObject, 'String', ''); + end + return +end +handles.df=tmp; + + +if isfield(handles,'TF') + t = p2t(mat2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); + handles.intensityThreshold = t; + set(handles.intensityThresholdEdit, 'String', cell2str(t)); +end + +guidata(hObject, handles); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get structure push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_getStructurePush(hObject, eventdata) +handles = guidata(hObject); +xyz = spm_XYZreg('GetCoords',handles.hReg); +tmp_coor = cuixuFindTDstructure(xyz', handles.DB, 0); +set(handles.structureEdit,'String', tmp_coor{1}); +handles.currentxyz = xyz'; +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% structure edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_structureEdit(action, xyz, thisfun, hReg) + +try + handles=guidata(hReg); +catch + return; +end + +handles.currentxyz = xyz'; +guidata(hReg, handles); + +try + [tmp_coor, cellstructure] = cuixuFindTDstructure(xyz', handles.DB, 0); +catch + return; +end + +set(handles.structureEdit,'String', tmp_coor{1}); + +for ii=[5 3 2 1 4] + if strfind('Unidentified', cellstructure{ii}) + continue; + else + set(handles.searchContentEdit,'string', trimStructureStr(cellstructure{ii})); + set(handles.searchContentEdit,'UserData', 'auto'); + return; + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% trim str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = trimStructureStr(str) +pos = findstr('(', str); +if ~isempty(pos) + str(pos-1:end)=[]; +end +out = str; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cluster size threshold edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clusterSizeThresholdEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +if isnan(tmp) | tmp<0 + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.clusterSizeThreshold); + catch + set(hObject, 'String', '5'); + end + return +end +handles.clusterSizeThreshold=tmp; + +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImagePush(hObject, eventdata, thisfilename, isMask) +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}); + return; + end + end + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}); + return; + end +end + +[filename, pathname] = uiputfile('*.img', 'Save image file as', get(handles.saveImageFileEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + +if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName{1}) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity'), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}, isMask); + return; + end +end + +mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, '', isMask); + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImageFileEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveImagePush(handles.saveImagePush, eventdata, get(hObject,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSPush(hObject, eventdata, thisfilename) + +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + spm_print(handles.figure); + if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); + elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); + end + return; + end +end + +[filename, pathname] = uiputfile('*.ps', 'Save result as', get(handles.saveResultPSEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +% print +H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +pos = get(H,'position'); +index = []; + +for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 & pos{ii}(2) > 0.5 + set(H(ii),'position',[pos{ii}(1), pos{ii}(2), pos{ii}(3)*3/4, pos{ii}(4)]); + index = [index ii]; + end +end + + +spm_print(handles.figure); +if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); +elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); +end + +% set the position back +set(H(index), {'position'}, pos(index)); + + +% printstr = ['print -dpsc2 -painters -noui ' '''' thisfilename '''']; +% try +% orient portrait +% eval(printstr); +% printsuccess = 1; +% catch +% errordlg('Print to ps file failed', 'print error'); +% printsuccess = 0; +% end +%set(H,{'Units'},un); +% if strcmp(handles.system, 'linux') & printsuccess == 1 +% system(['ps2pdf ' '''' thisfilename '''']); +% end + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveResultPSPush(hObject, eventdata, get(handles.saveResultPSEdit,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% select a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_selectThisClusterPush(hObject, eventdata) +handles = guidata(hObject); + +try + xyz = handles.currentxyz'; +catch + xyz = spm_XYZreg('GetCoords',handles.hReg); +end + +try + handles.selectedCluster = [handles.selectedCluster; xyz']; +catch + handles.selectedCluster = xyz'; +end + +disp('handles defines!') +assignin('base','handles',handles) + +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + delete(handles.hGlassText) +end +%handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% unselect a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clearSelectedClusterPush(hObject, eventdata) +handles = guidata(hObject); +try + handles = rmfield(handles,'selectedCluster'); +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + %delete(handles.hGlassText) + set(handles.infoTextBox, 'string', ['No clusters selected']); +end + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pick a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pickThisClusterPush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return; +end + +if ~isfield(handles, 'selectedCluster') | isempty(handles.selectedCluster) + try + xyz = handles.currentxyz'; + catch + xyz = spm_XYZreg('GetCoords',handles.hReg); + end + handles.selectedCluster = xyz'; +end + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); +xyzcor = mni2cor(handles.selectedCluster, handles.M{1}); + +pos = []; +for ii = 1:size(xyzcor,1) + pos0 = find(cor(:,1)==xyzcor(ii,1) & cor(:,2)==xyzcor(ii,2) & cor(:,3)==xyzcor(ii,3)); + if isempty(pos0) + continue; + end + pos = [pos find(A==A(pos0(1)))]; +end +if isempty(pos) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return +end + +pos = unique(pos); + +tmpmni = mni(pos,:); +tmpintensity = intensity(pos); + +[B,I,J] = unique(tmpmni, 'rows'); +handles.currentDisplayMNI = {B}; +fprintf('Cluster defined from: %s \n', handles.imageFileName{1}); +assignin('base', 'currentDisplayMNI', handles.currentDisplayMNI ); +handles.currentDisplayIntensity = {tmpintensity(I,:)}; + +handles.currentxyz = handles.selectedCluster(end,:); + +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; + +handles.selectedCluster = []; +try + delete(handles.hGlassText) +end + +guidata(hObject, handles); + +set(handles.thisClusterSizeEdit,'string', num2str(size(handles.currentDisplayMNI{1},1))); +str = get(handles.searchContentEdit, 'string'); +pos = findstr(' ', str); +str(pos) = []; +files = []; +for ii=1:length(handles.imageFileName) + [a,b,c] = fileparts(handles.imageFileName{ii}); + files = [files b]; +end +if ~isempty(files) + files = ['_from_' files]; +end + +set(handles.saveImageFileEdit, 'string', [str files '.img']); + +% list structure of voxels in this cluster +[a, b] = cuixuFindTDstructure(cell2mat(handles.currentDisplayMNI'), handles.DB, 0); +names = unique(b(:)); +index = NaN*zeros(length(b(:)),1); +for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; +end + +for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); +end +for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end +end +report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; +% format long +% disp(b) +% disp(report) +% format +report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; +for ii=2:size(report,1) + if strcmp('Unidentified', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; +end + +report2 = [report2, {'','select and Ctrl-C to copy'}]; +% f = figure('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.2 min(0.7,0.016*length(report2))], 'name', 'cluster information', 'NumberTitle','off'); +% hEdit = uicontrol(f,'style','edit',... +% 'unit','normalized','position',[0 0 1 1],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', report2,... +% 'max',2,'min',0); + +set(handles.infoTextBox, 'string', report2); +assignin('base', 'ans', handles.currentDisplayMNI) +disp('Cluster coordinates in "ans"') +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commonRegion push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_commonRegionPush(hObject, eventdata) +handles = guidata(hObject); +if ~isfield(handles,'TF') | length(handles.TF)<=1 + %msgbox('Two or more images need to be loaded to find the common region.', 'info'); + set(handles.infoTextBox, 'string', 'Two or more images need to be loaded to find the common region.'); + beep + return; +end + +common = handles.currentDisplayMNI{1}; +for ii=2:length(handles.TF) + common = intersect(common, handles.currentDisplayMNI{ii}, 'rows'); +end + +if isempty(common) + %msgbox('No common region found.', 'info'); + set(handles.infoTextBox, 'string', 'No common region found.'); + beep + return; +end + +tmpMNI = cell2mat(handles.currentDisplayMNI'); +tmpIntensity = cell2mat(handles.currentDisplayIntensity'); +intensity = zeros(size(common,1),1); + +for ii=1:size(common,1) + pos = find(abs(tmpMNI(:,1)-common(ii,1))<0.1 & abs(tmpMNI(:,2)-common(ii,2))<0.1 & abs(tmpMNI(:,3)-common(ii,3))<0.1); + intensity(ii) = prod(tmpIntensity(pos)); +end + +handles.currentDisplayMNI = {common}; +handles.currentDisplayIntensity = {intensity}; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% if isfield(handles,'hLegend') +% try +% set(cell2mat(handles.hLegend'),'visible',{'off'}); +% end +% end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_volumePush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; + + +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(intensity, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-intensity, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((intensity), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((intensity), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +elseif findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); +end + +spm_list('List',xSPM,handles.hReg); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_displayPush(hObject, eventdata) +handles = guidata(hObject); +spm_image('init', handles.imageFileName); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% all in one +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allinonePush(hObject, eventdata) +try + if findstr('SPM2',spm('ver')) + P = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P = spm_select(Inf,'image','Select image files'); + end + +catch + return; +end +if isempty(P) + return +end + +handles = guidata(hObject); +%if ~isfield(handles,'hReg') | ~isfield(handles,'hSection') | ~isfield(handles,'hcolorbar') +tmp = [0 0 0]; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(tmp([],:), [], hObject, handles); +%end + +colors=mycolourset; +for ii=1:size(P,1) + thisfilename = deblank(P(ii,:)); + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); + cor = mni2cor(handles.mni, handles.M); + spm_orthviews('addcolouredblobs',1,cor',handles.intensity',handles.M,colors(mod(ii,6)+1,:)); +end +spm_orthviews('Redraw'); + +guidata(hObject, handles); + +% contents = get(handles.sectionViewListbox,'String'); +% currentsel = contents{get(handles.sectionViewListbox,'Value')}; +% sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +% +% % spm_image('init', sectionViewTargetFile); +% % spm_image('addblobs'); +% % return + +% guidata(hObject, handles); +% load xSPM; +% VOL.XYZ = xSPM.XYZ; +% VOL.Z = xSPM.Z; +% VOL.M = handles.M; + +%addcolouredimage(handles.hSection, '333.img',[1 0 1]); +% uigetfiles +% nblobs = 4; +% for i=1:nblobs, +% %[SPM,VOL] = spm_getSPM; +% %c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); +% c = i; +% VOL.XYZ = ceil(rand(3,20)*20); +% VOL.Z = randn(1,20); +% VOL.M = handles.M; +% colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +% spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); +% end; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPush(hObject, eventdata) +handles = guidata(hObject); + +tobeoverlay = deblank(get(handles.overlayEdit, 'string')); + +if isempty(tobeoverlay) + return; +end + +tobeoverlay = str2cell(tobeoverlay, ' '); +if isnumeric(tobeoverlay{1}) + if length(tobeoverlay{1})>1 + errordlg(['Your input, ' deblank(get(handles.overlayEdit, 'string')) ', seems coincide with a matlab constant.'], 'error'); + return + end + for ii=1:length(tobeoverlay) + tobeoverlay{ii} = num2str(tobeoverlay{ii}); + end +end +fn = fieldnames(handles.wholeMaskMNIAll); +for ii=1:length(tobeoverlay) + pos{ii} = []; + for jj=1:length(fn) + x = []; + if ~isempty(str2num(tobeoverlay{ii})) + y = str2cell(fn{jj},'_'); + for kk=1:length(y) + x = isequal(tobeoverlay{ii}, y{kk}); + if x; break;end; + end + if x==0; x = []; end; + else + x = findstr(lower(tobeoverlay{ii}), lower(fn{jj})); + end + if ~isempty(x) + pos{ii} = [pos{ii} jj]; + end + end +end +common = pos{1}; +for ii=2:length(pos) + common = intersect(common, pos{ii}); +end + +if isempty(common) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return +end + +mask = []; +for ii=1:length(common) + eval(['mask = [mask; handles.wholeMaskMNIAll.' fn{common(ii)} '];']); +end + +if isempty(mask) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return; +end + +try + handles.mni; +catch + delete(gcf); + xjview(mask); + return; +end + +handles.imageFileName = [handles.imageFileName, {deblank(get(handles.overlayEdit, 'string'))}]; +handles.M = [handles.M, {handles.M{1}}]; +handles.DIM = [handles.DIM, {handles.DIM{1}}]; +handles.currentDisplayMNI = [handles.currentDisplayMNI, {mask}]; +m = max(abs(cell2mat(handles.currentDisplayIntensity'))); +if ~isempty(m) + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {-2*m*ones(size(mask,1),1)}]; +else + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {ones(size(mask,1),1)}]; +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_overlayPush(handles.overlayPush, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region popup +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPop(hObject, eventdata) +handles = guidata(hObject); +names = get(hObject, 'string'); +value = get(hObject, 'value'); +set(handles.overlayEdit, 'string', names{value}); +CallBack_overlayEdit(handles.overlayEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% search xBrain.org and other databases +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchPush(hObject, eventdata) + +try + handles = guidata(hObject); + searchContent = get(handles.searchContentEdit,'string'); + searchEngine = get(handles.searchEnginePop,'string'); + searchEngine = searchEngine{get(handles.searchEnginePop,'value')}; + + + xyz = str2num(searchContent); + searchMode=get(handles.searchContentEdit,'UserData'); + + switch searchMode + case 'auto'; + xyz = spm_XYZreg('GetCoords',handles.hReg); + handles.currentxyz = xyz'; + guidata(hObject, handles); + [a,b] = cuixuFindTDstructure(xyz', handles.DB, 0); + try + brodmann = strmatch('Brodmann',b) + brodmann = b{brodmann}; + brodmann = brodmann(1:end-4); + end; + try + region = b{3}; + region = region(1:end-4); + end + + case 'manual' + if isempty(xyz) + searchMode='text'; + elseif length(xyz)==3 + searchMode='xyz'; + end + end + + + switch searchEngine + case 'Brede' + switch searchMode + case 'auto' + searchString = sprintf(' %0.0f',xyz') + set(handles.searchContentEdit,'string',searchString); + case 'xyz' + searchString = num2str(xyz');%searchContent=sprintf('+%0.0f',searchContent) + case 'text' + end + urlstr = ['http://hendrix.imm.dtu.dk/cgi-bin/brede_loc_query.pl?q=' searchString ]; + case 'xBrain.org' + switch searchMode + case { 'auto' 'xyz'} + xbrainSearchField = 'mni or tal&mnidistance=20'; + searchString = sprintf(' %0.1f',xyz')% searchString = num2str(xyz'); + case 'text' + xbrainSearchField = 'region'; + searchString = searchContent; + end + set(handles.searchContentEdit,'string',searchString); + urlstr = ['http://people.hnl.bcm.tmc.edu/cuixu/cgi-bin/bmd/paper.pl?search_content=' searchString '&search_field=' xbrainSearchField]; + case 'Google Scholar' + if isequal(searchMode,'auto' ) + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22|',searchString{:}); + try + searchString = searchString(1:end-1); + end + %set(handles.searchContentEdit,'string',searchString); + end + urlstr = ['http://scholar.google.com/scholar?q=' searchString ]; + case 'Pubmed' + switch searchMode + case 'auto' + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22 OR ',searchString{:}); + try + searchString = searchString(1:end-4); + end + %searchString = brodmann; + case 'text' + searchString = searchContent; + end + % urlstr = ['http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=PureSearch&db=pubmed&details_term=(' searchString ')']; + urlstr = ['http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=search&db=pubmed&pubmedfilters=true&term=(' searchString ')']; + case 'Wikipedia' + if isequal(searchMode,'auto') + searchString = region; + end + urlstr = ['http://en.wikipedia.org/w/index.php?search=%22' searchString '%22']; + end + set(handles.searchContentEdit,'UserData',searchMode); +catch + urlstr = 'http://www.google.com'; +end + +try + web(urlstr,'-browser'); +catch + if exist('c:\program Files\mozilla Firefox\firefox.exe','file') + system(['"c:\program Files\mozilla Firefox\firefox.exe" "' urlstr '"']) + else + web(urlstr); + end +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% control panel on or off +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function controlHide(handles, status) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get multiple values from a string deliminated delim +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = str2cell(str, delim) +if ~exist('delim') + delim = '; '; +end + +[out{1},b] = strtok(str, delim); +ii = 2; +while ~isempty(b) + [out{ii},b] = strtok(b, delim); + ii = ii+1; +end + +for ii=1:length(out) + out2{ii} = str2num(out{ii}); + if isempty(out2{ii}) + return; + end +end + +for ii=1:length(out) + out{ii} = str2num(out{ii}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cell2str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function str = cell2str(acell, delim) +if ~exist('delim') + delim = ';'; +end + +str = []; + +if length(acell)==1 + if isstr(acell{1}) + str = acell{1}; + else + str = num2str(acell{1}); + end +else + for ii=1:length(acell) + if isstr(acell{ii}) + str = [str acell{ii}, delim ' ']; + else + str = [str num2str(acell{ii}), delim ' ']; + end + end + str(end-1:end)=[]; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cellmax, find max in each element, return a cell +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = cellmax(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end + +MAXX = []; +for ii=1:length(acell) + if strfind('abs',absolute) + MAXX = [MAXX max(abs(acell{ii}))]; + else + MAXX = [MAXX max(acell{ii})]; + end +end +MAXX = num2cell(MAXX); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% maxcell +%%% find max of all numbers in the whole cell, return a single value +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = maxcell(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end +MAXX = cellmax(acell, absolute); +MAXX = max(cell2mat(MAXX)); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% p2t +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = p2t(p, df, TF) +if ~iscell(p) + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = p2t(p{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% s2t, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = s2t(s, df, TF) + +if ~iscell(s) + p = 10^(-s); + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = s2t(s{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2p +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function p = t2p(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + end +else + for ii=1:length(t) + p{ii} = t2p(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2s, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = t2s(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + else + p = 0.1; + end + s = -log10(p); +else + for ii=1:length(t) + s{ii} = t2s(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2mask +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mask = mni2mask(coords, targetfilename, intensity, M, DIM, templateFile, isMask) +% function mask = mni2mask(coords, targetfilename, intensity, templateFile) +% make mask from coordinates +% +% coords: a Nx3 column of 3-d coordinates in MNI +% space +% targetfilename: (optional) the image files to be written +% intensity: (optional) Nx1, the values of each coordinate. +% M: rotation matrix +% DIM: dimension +% templateFile: (optional) the templateFile from which we can get the right +% dimensions. +% isMask: if this variable exist and equal to 1, then all non-zero +% intensities will be set to 1 +% +% Xu Cui +% 2004/11/18 + +if ~exist('intensity') + intensity = ones(size(coords,1),1); +end +thistemplateFile = ''; +if exist('templateFile') + if ~isempty(templateFile) + thistemplateFile = templateFile; + end +end + +if isempty(thistemplateFile) + V.mat = [... + -4 0 0 84; ... + 0 4 0 -116; ... + 0 0 4 -56; ... + 0 0 0 1]; + V.dim = [41 48 35 16]; + if exist('M') + V.mat = M; + end + if exist('DIM') + V.dim = DIM; + V.dim(4) = 16; + end + V.fname = targetfilename; + V.descrip = 'our own image'; +else + V = spm_vol(templateFile); + V.fname = targetfilename; + if isfield(V, 'descrip') + V.descrip = ['my image from ' V.descrip]; + else + V.descrip = 'my own image'; + end +end + +thisismask = 0; +if exist('isMask') + if isMask == 1 + thisismask = 1; + end +end +if thisismask + V.descrip = 'my mask'; + intensity = ones(size(intensity)); +end + +O = zeros(V.dim(1),V.dim(2),V.dim(3)); + +coords = mni2cor(coords,V.mat); + + +for ii=1:size(coords,1) + O(coords(ii,1),coords(ii,2),coords(ii,3)) = intensity(ii); +end + +if exist('targetfilename') + V = spm_write_vol(V,O); +end + +mask = O; + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get image file information +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [imageFile,M,DIM,TF,df,mni,intensity] = getImageFile(thisfilename) +% function imageFile = getImageFile(filename) +% get the information of this/these image file(s) +% +% thisfilename: (optional) if doesn't give file name, then show a open file +% dialog +% imageFile: the full name of the selected file (if user pressed cancel, +% imageFile == 0 +% M: M matrix (rotation matrix) +% DIM: dimension +% TF: t test or f test? 'T' or 'F' +% df: degree of freedome +% mni: mni coord +% intensity: intensity of each mni coord +% +% Note: The returned variables are cellarrays. +% +% Xu Cui +% last revised: 2005-05-03 + +if nargin < 1 | isempty(thisfilename) + if findstr('SPM2',spm('ver')) + P0 = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P0 = spm_select(Inf,'image','Select image files'); + end + + % try + % P0 = spm_get([0:100],'*IMAGE','Select image files'); + % catch + % P0 = []; + % [FileName,PathName] = uigetfile({'*.img';'*.IMG';'*.*'},'Select image files','MultiSelect','on'); + % if isstr(FileName) + % P0 = {fullfile(PathName, FileName)}; + % elseif iscellstr(FileName) + % for ii=1:length(FileName) + % P0{ii} = fullfile(PathName, FileName{ii}); + % end + % else + % P0 = []; + % end + % end + try + if isempty(P0) + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end + end + for ii=1:size(P0,1) + P{ii} = deblank(P0(ii,:)); + end +else + if isstr(thisfilename) + P = {thisfilename}; + elseif iscellstr(thisfilename) + P = thisfilename; + else + disp('Error: In getImageFile: I don''t understand the input.'); + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end +end + +global LEFTRIGHTFLIP_; + +for ii=1:length(P) + imageFile{ii} = P{ii}; + [cor{ii}, intensity{ii}, tmp{ii}, M{ii}, DIM{ii}, TF{ii}, df{ii}] = mask2coord(imageFile{ii}, 0); + if LEFTRIGHTFLIP_ == 1 + M{ii}(1,:) = -M{ii}(1,:); + end + mni{ii} = cor2mni(cor{ii}, M{ii}); +end + + + + + + + + + + + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuFindTDstructure +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% +% this function converts Talairach Daemon coordinate or MNI coordinate to a description of +% brain structure. +% +% pos: the coordinate (MNI or Talairach coordinate, defined by TALMNI) of the position in the brain, in mm +% DB: the database structure (see below for detailed explanation). If you don't input this argument, there +% should be a file called 'TDdatabase.mat' in the current directory +% TALMNI: 1 if pos is talairach coordinate, 0 if pos is MNI coordinate. 1 +% by default. +% +% onelinestructure: a one-line description of the returned brain +% structure +% cellarraystructure: a cell array of size 5, each cell contains a string +% describing the structure of the brain in a certain level. +% +% Example: +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48], DB, 1) +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48]) +% then +% onelinestructure = // Left Cerebrum // Frontal Lobe (L) // Middle Frontal Gyrus (L) // Gray Matter (L) // Brodmann area 8 (L) +% cellarraystructure = 'Left Cerebrum' 'Frontal Lobe (L)' [1x24 char] 'Gray Matter (L)' 'Brodmann area 8 (L)' +% +% Xu Cui +% 2004-6-28 +% + +%---------------------------------------------------------------------------------- +% DB strcture +%---------------------------------------------------------------------------------- +%------------------------------- +% Grid specification parameters: +%------------------------------- +% minX - min X (mm) +% maxX - max X (mm) +% voxX - voxel size (mm) in X direction +% minY - min Y (mm) +% maxY - max Y (mm) +% voxY - voxel size (mm) in Y direction +% minZ - min Z (mm) +% maxZ - max Z (mm) +% voxZ - voxel size (mm) in Z direction +% nVoxX - number of voxels in X direction +% nVoxY - number of voxels in Y direction +% nVoxZ - number of voxels in Z direction +%------------------------------- +% Classification parameters: +%------------------------------- +% numClass - number of classification types +% cNames - cNames{i} - cell array of class names for i-th CT +% numClassSize - numClassSize(i) - number of classes for i-th CT +% indUnidentified - indUnidentified(i) - index of "indUnidentified" class for i-th CT +% volClass - volClass{i}(j) - number of voxels in class j for i-th CT +% +% data - N x numClass matrix of referencies; let +% x y z coordinates in mm (on the grid) and +% nx = (x-minX)/voxX +% ny = (y-minY)/voxY +% nz = (z-minZ)/voxZ +% ind = nz*nVoxX*nVoxY + ny*nVoxX + nx + 1 +% data(ind, i) - index of the class for i-th CT in cNames{i} to +% which (x y z) belongs, i.e. +% cNames{i}{data(ind, i)} name of class for i-th CT +%---------------------------------------------------------------------------------- + +if nargin==1 + load('TDdatabase.mat'); + TALMNI = 1; +elseif nargin == 2 + TALMNI = 1; +end + +if(TALMNI == 1) + pos = tal2mni(pos); +elseif(TALMNI == 0) + []; +else + disp('TALMNI should be 1 or 0.'); +end + +pos(:,1) = DB.voxX*round(pos(:,1)/DB.voxX); +pos(:,2) = DB.voxY*round(pos(:,2)/DB.voxY); +pos(:,3) = DB.voxZ*round(pos(:,3)/DB.voxZ); + +min = []; +vox = []; +for(i=1:size(pos,1)) + min = [min; DB.minX DB.minY DB.minZ]; + vox = [vox; DB.voxX DB.voxY DB.voxZ]; +end +n_pos = (pos - min)./vox; + +nx = n_pos(:,1); +ny = n_pos(:,2); +nz = n_pos(:,3); +index = nz*DB.nVoxX*DB.nVoxY + ny*DB.nVoxX + nx + 1; +indMax = size(DB.data, 1); + +onelinestructuretmp = []; +onelinestructure = []; +for(j=1:size(pos,1)) + onelinestructuretmp = []; + for(i=1:DB.numClass) + + if (index(j) <= 0 | index(j) > indMax) + ind(j) = DB.indUnidentified(i); + else + ind(j) = DB.data(index(j), i); + end + + cellarraystructure{j,i} = DB.cNames{i}{ind(j)}; + onelinestructuretmp = [onelinestructuretmp ' // ' cellarraystructure{j,i}]; + end + onelinestructure{j} = onelinestructuretmp; +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mask2coord +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [cor, intensity, cor_singlecolumn,M,DIM,TF,df] = mask2coord(mask, checkdimension) +% [cor, intensity, cor_singlecolumn] = mask2coord(mask, checkdimension) +% +% This is to retrieve the coordinate of a mask file, or a matrix of 3-D +% +% mask: an image file or a matrix (3-D), with some of the elements are +% non-zeros +% checkdimension: check if the dimension is checkdimension, if not, return empty +% matrix +% cor: a N*3 matrix, which each row a coordinate in matrix +% intensity: a N*1 matrix, which encodes the intensity of each voxel. +% cor_singlecolumn: a N*1 matrix, each row is the index in the matrix +% M: rotation matrix +% DIM: dimension +% TF: t test or f test? 'T','F' or [] +% df: degree of freedome for T/F test +% +% Example: +% mask = zeros(4,3,2); +% mask(1,2,1) = 1; +% mask(3,2,2) = 1; +% mask2coord(mask) +% +% mask2coord('spmT_0002.img') +% mask2coord('spmT_0002.img',[41 48 35]) +% +% Xu Cui +% 2004-9-20 +% last revised: 2005-04-30 + +if nargin < 2 + checkdimension = 0; +end + +if ischar(mask) + V = spm_vol(mask); + mask = spm_read_vols(V); + M = V.mat; + DIM = V.dim; + TF = 'T'; + T_start = strfind(V.descrip,'SPM{T_[')+length('SPM{T_['); + if isempty(T_start); T_start = strfind(V.descrip,'SPM{F_[')+length('SPM{F_['); TF='F'; end + if isempty(T_start) + TF=[]; df=[]; + else + T_end = strfind(V.descrip,']}')-1; + df = str2num(V.descrip(T_start:T_end)); + end +else + M = []; + TF = []; + df = []; +end + +dim = size(mask); +if length(checkdimension)==3 + if dim(1)~= checkdimension(1) | dim(2)~= checkdimension(2) | dim(3)~= checkdimension(3) + y = []; + disp('dimension doesn''t match') + return + end +end + +pos = find(mask~=0); +intensity = mask(pos); + +y = zeros(length(pos),3); + +y(:,3) = ceil(pos/(dim(1)*dim(2))); +pos = pos - (y(:,3)-1)*(dim(1)*dim(2)); +y(:,2) = ceil(pos/dim(1)); +pos = pos - (y(:,2)-1)*(dim(1)); +y(:,1) = pos; + +cor = y; +cor_singlecolumn = pos; +DIM = dim; +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2cor +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function coordinate = mni2cor(mni, T) +% function coordinate = mni2cor(mni, T) +% convert mni coordinate to matrix coordinate +% +% mni: a Nx3 matrix of mni coordinate +% T: (optional) transform matrix +% coordinate is the returned coordinate in matrix +% +% caution: if T is not specified, we use: +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% + +if isempty(mni) + coordinate = []; + return; +end + +if ~exist('T') + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +coordinate = [mni(:,1) mni(:,2) mni(:,3) ones(size(mni,1),1)]*(inv(T))'; +coordinate(:,4) = []; +coordinate = round(coordinate); +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cor2mni +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mni = cor2mni(cor, T) +% function mni = cor2mni(cor, T) +% convert matrix coordinate to mni coordinate +% +% cor: an Nx3 matrix +% T: (optional) rotation matrix +% mni is the returned coordinate in mni space +% +% caution: if T is not given, the default T is +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% last revised: 2005-04-30 + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +cor = round(cor); +mni = T*[cor(:,1) cor(:,2) cor(:,3) ones(size(cor,1),1)]'; +mni = mni'; +mni(:,4) = []; +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% draw +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = Draw(mniCoord, intensity, hObject, handles) + +try + delete(handles.hcolorbar); +end +try + delete(handles.hReg); +end +try + delete(handles.hSection); +end +try + cla(handles.glassViewAxes); +end + +try + H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); + un = cellstr(get(H,'Units')); + pos = get(H,'position'); + + for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 + delete(H(ii)); + end + end +end + +sectionViewTargetFile = handles.sectionViewTargetFile; + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end + if max(intensity)*min(intensity) < 0 + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + else + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,abs(intensity),sectionViewTargetFile,hObject,handles); + end + + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end +else % multiple input? yes + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + + mniCoordtmp=[]; + intensitytmp=[]; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end + +end + +try + spm_XYZreg('SetCoords',handles.currentxyz',hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuSectionView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord, intensity, targetFile, hObject,handles) +% function h = cuixuSectionView(mniCoord, intensity) +% This is to project your coordinate to section view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% a special feature of this function is: it automatically seperate the +% negative and positive intensity and use hot and cold color to represent +% them. +% +% h: the returned handle for the axes +% +% SEE ALSO: cuixuView cuixuGlassView cuixuRenderView +% +% Xu Cui +% 2004/11/11 + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + multiple = 0; + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end +else + multiple = 1; + mniCoordtmp = []; + intensitytmp = []; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + % for multiple input + cSPM{ii}.XYZ = mni2cor(mniCoord{ii}, handles.M{ii}); + cSPM{ii}.XYZ = cSPM{ii}.XYZ'; + cSPM{ii}.Z = abs(intensity{ii}); + cSPM{ii}.M = handles.M{ii}; + cSPM{ii}.DIM = handles.DIM{ii}'; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; +end + +SPM.XYZ = mni2cor(mniCoord, handles.M); +SPM.XYZ = SPM.XYZ'; +SPM.Z = intensity; +SPM.M = handles.M; +SPM.DIM = handles.DIM'; + +%%%%%%%%%%%%%%% Reg %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +handles.colormap = colormap; + +coor = mniCoord; +xSPM = SPM; +xSPM.XYZmm = mniCoord'; +axes(handles.glassViewAxes) +WS = spm('WinScale'); +FS = spm('FontSizes'); + +Finter = gcf; +hReg = uicontrol(Finter,'Style','Frame','Position',[60 100 300 300].*WS,... + 'Visible','off'); +[hReg,xyz] = spm_XYZreg('InitReg',hReg,xSPM.M,xSPM.DIM,[0;0;0]); + +hFxyz = spm_results_ui('DrawXYZgui',xSPM.M,xSPM.DIM,xSPM,xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +hMIPax =gca ; +setcolormap('gray'); + +hMIPax = spm_mip_ui(xSPM.Z,coor',xSPM.M,xSPM.DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); + +colormap(handles.colormap); +setcolormap('gray-hot'); + +if isempty(handles.M) + spm_XYZreg('SetReg',handles.structureEdit,hReg); +else + set(handles.structureEdit, 'UserData', struct('hReg',hReg,'M',handles.M,'D', handles.DIM,'xyx',[0 0 0])); +end + +spm_XYZreg('Add2Reg',hReg,handles.structureEdit,@CallBack_structureEdit); + +%%%%%%%%%%%%%%% Reg end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if multiple == 0 + [hgraph, hSection, hcolorbar] = spm_sections(SPM,hReg,targetFile,handles.sectionViewPosition); +else + [hgraph, hSection, hcolorbar] = spm_sections(cSPM,hReg,targetFile,handles.sectionViewPosition); +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_sections +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [Fgraph, hMe, hcolorbar] = spm_sections(SPM,hReg,targetFile,sectionViewPosition) +% rendering of regional effects [SPM{Z}] on orthogonal sections +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = gcf; + +spms = fullfile(spm('dir'),'canonical', 'single_subj_T1.mnc'); +if exist('targetFile') + spms = targetFile; +end + +spm_orthviews('Reset'); +global st +st.fig = Fgraph; +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; + +spm_orthviews('Image',spms,sectionViewPosition); % position +spm_orthviews('MaxBB'); +spm_orthviews('register',hReg); +if ~iscell(SPM) + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +elseif length(SPM) == 1 + SPM = SPM{1}; + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +else + colors = mycolourset; + for ii=1:length(SPM) + spm_orthviews('addcolouredblobs',1,SPM{ii}.XYZ, SPM{ii}.Z, SPM{ii}.M, colors(ii,:)); + end +end +spm_orthviews('Redraw'); + +hMe = st.registry.hMe; +try + hcolorbar = st.vols{1}.blobs{1}.cbar; +catch + hcolorbar = 0; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuRenderView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function h = cuixuRenderView(mniCoord, intensity, varargin) +% function h = cuixuRenderView(mniCoord1, intensity1, mniCoord2, intensity2, mniCoord3, intensity3) +% This is to project your coordinate to render view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% You can input 1, 2, or 3 pairs of coordinates and intensity. +% +% h: the returned handle for the figure +% +% Xu Cui +% 2004/11/11 + +global M_; +global DIM_; + +if nargin < 3 + dat.XYZ = mni2cor(mniCoord, M_); + dat.XYZ = dat.XYZ'; + if nargin < 2 + dat.t = ones(size(mniCoord,1),1); + else + dat.t = intensity; + end + dat.mat = M_; + dat.dim = DIM_; +else + if mod(nargin,2) ~=0 + disp('You should put even number of parameters.') + return; + end + for ii=1:(2+length(varargin))/2 + if ii==1 + dat(ii).XYZ = mni2cor(mniCoord, M_); + dat(ii).t = intensity; + else + dat(ii).XYZ = mni2cor(varargin{2*(ii-1)-1}, M_); + dat(ii).t = varargin{2*(ii-1)}; + end + dat(ii).XYZ = dat(ii).XYZ'; + dat(ii).mat = M_; + dat(ii).dim = DIM_; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_render +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +h = spm_render(dat,1,fullfile(spm('dir'), 'rend', 'render_single_subj.mat')); +return + +function Fgraph = spm_render(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +% get surface +%----------------------------------------------------------------------- +if nargin < 3, + rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); +end; + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + + + +% Perform the rendering +%======================================================================= +spm('Pointer','Watch') + +load(rendfile); + +if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; +end; + +if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; +for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; +end; +if showbar, spm_progress_bar('Clear'); end; + +if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + +mx = zeros(length(rend),1)+eps; +mn = zeros(length(rend),1); + +for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; +end; + +mxmx = max(mx); +mnmn = min(mn); + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = gcf;%spm_figure('GetWin','Graphics'); +%spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +hght = 0.25; +width = 0.25; +x0 = 0.5; +y0 = 0.01; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 0.5, hght],'Visible','off'); +%ax=axes; +%image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow, width, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + X = cell(3,1); + for j=1:length(rend{i}.data), + X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + end + for j=(length(rend{i}.data)+1):3 + X{j}=zeros(size(X{1})); + end + + rgb = zeros([size(ren) 3]); + tmp = ren.*max(1-X{1}-X{2}-X{3},0); + rgb(:,:,1) = tmp + X{1}; + rgb(:,:,2) = tmp + X{2}; + rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + end; +end; + +spm('Pointer') +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_list +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function varargout = spm_list(varargin) +% Display and analysis of SPM{.} +% FORMAT TabDat = spm_list('List',SPM,hReg,[Num,Dis,Str]) +% Summary list of local maxima for entire volume of interest +% FORMAT TabDat = spm_list('ListCluster',SPM,hReg,[Num,Dis,Str]) +% List of local maxima for a single suprathreshold cluster +% +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x11 cell array) +% .fmt - fprintf format strings for table data (1x11 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (4x2 cell array) +% .dat - table data (Nx11 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%_______________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The currected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% +% Voxel-level - T/F = Statistic upon which the SPM is based +% - Ze = The eqivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qu = Expd(Prop of false positives among voxels >= Ze) +% - Pu = prob(Ze or higher at that voxel) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%_______________________________________________________________________ +% @(#)spm_list.m 2.43 Karl Friston, Andrew Holmes 02/10/31 + + +% satellite figure global variable +%----------------------------------------------------------------------- +global SatWindow + +%======================================================================= +switch lower(varargin{1}), case 'list' %-List + %======================================================================= + % FORMAT TabDat = spm_list('list',SPM,hReg) + + %-Tolerance for p-value underflow, when computing equivalent Z's + %----------------------------------------------------------------------- + tol = eps*10; + + %-Parse arguments and set maxima number and separation + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + + + %-Get current location (to highlight selected voxel in table) + %----------------------------------------------------------------------- + %xyzmm = spm_results_ui('GetCoords'); + xyzmm = [0 0 0]'; + + %-Extract data from xSPM + %----------------------------------------------------------------------- + S = varargin{2}.S; + R = varargin{2}.R; + FWHM = varargin{2}.FWHM; + VOX = varargin{2}.VOX; + n = varargin{2}.n; + STAT = varargin{2}.STAT; + df = varargin{2}.df; + u = varargin{2}.u; + M = varargin{2}.M; + v2r = 1/prod(FWHM(~isinf(FWHM))); %-voxels to resels + k = varargin{2}.k*v2r; + QPs = varargin{2}.Ps; % Needed for FDR + QPs = sort(QPs(:)); + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 3; + Dis = 8; + end + if length(varargin) > 5 + + Title = varargin{6}; + else + Title = 'p-values adjusted for search volume'; + end + + + %-Setup graphics panel + %----------------------------------------------------------------------- + spm('Pointer','Watch') + if SatWindow + Fgraph = SatWindow; + figure(Fgraph); + else + Fgraph = figure('unit','normalized','position',[0.5,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','off','MenuBar','none'); + Fgraph = gcf; + end + %spm_results_ui('Clear',Fgraph) + FS = spm('FontSizes'); %-Scaled font sizes + PF = spm_platform('fonts'); %-Font names (for this platform) + + + %-Table header & footer + %======================================================================= + + %-Table axes & Title + %---------------------------------------------------------------------- + if SatWindow, ht = 0.85; bot = .14; else, ht = 0.8; bot = 0.15; end; + + if STAT == 'P' + Title = 'Posterior Probabilities'; + end + + hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + + AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) + dy = FS(9); + y = floor(AxPos(4)) - dy; + + text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; + line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + + %-Construct table header + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + + Hc = []; + Hp = []; + h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; + h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; + h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; + h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; + text(0.22,y, 'cluster-level','FontSize',FS(9)); + line([0.15,0.41],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.16,y-9*dy/8, '\itp \rm_{corrected}'); Hp = [Hp,h]; + h = text(0.33,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.26,y-9*dy/8, '\itk \rm_E'); + + text(0.60,y, 'voxel-level','FontSize',FS(9)); + line([0.46,0.86],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.46,y-9*dy/8, '\itp \rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.55,y-9*dy/8, '\itp \rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.79,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.64,y-9*dy/8, sprintf('\\it%c',STAT)); + h = text(0.72,y-9*dy/8, '(\itZ\rm_\equiv)'); + + text(0.93,y - dy/2,['x,y,z \fontsize{',num2str(FS(8)),'}\{mm\}']); + + + %-Headers for text table... + %----------------------------------------------------------------------- + TabDat.tit = Title; + TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'voxel', 'p(FWE-cor)';... + 'voxel', 'p(FDR-cor)';... + 'voxel', STAT;... + 'voxel', 'equivZ';... + 'voxel', 'p(unc)';... + '', 'x,y,z {mm}'}';... + + TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Voxel + '%3.0f %3.0f %3.0f'}; %-XYZ + + %-Column Locations + %----------------------------------------------------------------------- + tCol = [ 0.00 0.07 ... %-Set + 0.16 0.26 0.34 ... %-Cluster + 0.46 0.55 0.62 0.71 0.80 ...%-Voxel + 0.92]; %-XYZ + + % move to next vertial postion marker + %----------------------------------------------------------------------- + y = y - 7*dy/4; + line([0 1],[y y],'LineWidth',1,'Color','r') + y = y - 5*dy/4; + y0 = y; + + + %-Table filtering note + %----------------------------------------------------------------------- + if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); + else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); + end + text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + + %-Volume, resels and smoothness (if classical inference) + %----------------------------------------------------------------------- + line([0 1],[0 0],'LineWidth',1,'Color','r') + if STAT ~= 'P' + %----------------------------------------------------------------------- + FWHMmm = FWHM.*VOX; % FWHM {mm} + Pz = spm_P(1,0,u,df,STAT,1,n,S); + Pu = spm_P(1,0,u,df,STAT,R,n,S); + Qu = spm_P_FDR(u,df,STAT,n,QPs); + [P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + + %-Footnote with SPM parameters + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) + TabDat.ftr = cell(5,2); + TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); + TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); + TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); + TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); + TabDat.ftr{5} = ... + sprintf('Expected false discovery rate, <= %0.2f',Qu); + TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); + TabDat.ftr{7} = ... + sprintf(['Smoothness FWHM = %0.1f %0.1f %0.1f {mm} ',... + ' = %0.1f %0.1f %0.1f {voxels}'],FWHMmm,FWHM); + TabDat.ftr{8} = ... + sprintf('Search vol: %0.0f cmm; %0.0f voxels; %0.1f resels',S*prod(VOX),S,R(end)); + TabDat.ftr{9} = ... + sprintf(['Voxel size: [%0.1f, %0.1f, %0.1f] mm ',... + ' (1 resel = %0.2f voxels)'],VOX,prod(FWHM)); + + text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu,Qu],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWHMmm,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + + end % Classical + + + %-Characterize excursion set in terms of maxima + % (sorted on Z values and grouped by regions) + %======================================================================= + if ~length(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,11); + varargout = {TabDat}; + spm('Pointer','Arrow') + return + end + + % Includes Darren Gitelman's code for working around + % spm_max for conjunctions with negative thresholds + %----------------------------------------------------------------------- + minz = abs(min(min(varargin{2}.Z))); + zscores = 1 + minz + varargin{2}.Z; + [N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); + Z = Z - minz - 1; + + %-Convert cluster sizes from voxels to resels + %----------------------------------------------------------------------- + if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); + else + V2R = v2r; + end + N = N.*V2R; + + %-Convert maxima locations from voxels to mm + %----------------------------------------------------------------------- + XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + + %-Table proper (& note all data in cell array) + %======================================================================= + + %-Pagination variables + %----------------------------------------------------------------------- + hPage = []; + set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + + %-Set-level p values {c} - do not display if reporting a single cluster + %----------------------------------------------------------------------- + c = max(A); %-Number of clusters + if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value + else + Pc = []; + set(Hp,'Visible','off') + end + + if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + else + set(Hc,'Visible','off') + end + + TabDat.dat = {Pc,c}; %-Table data + TabLin = 1; %-Table data line + + + %-Local maxima p-values & statistics + %----------------------------------------------------------------------- + HlistXYZ = []; + while prod(size(find(finite(Z)))) + + % Paginate if necessary + %--------------------------------------------------------------- + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %--------------------------------------------------------------- + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and voxel-level {u} p values for this cluster + %--------------------------------------------------------------- + Nv = N(i)/v2r; % extent {voxels} + + + if STAT ~= 'P' + Pz = spm_P(1,0, U,df,STAT,1,n,S);% uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S);% FWE-corrected {based on Z) + Qu = spm_P_FDR( U,df,STAT,n,QPs);% FDR-corrected {based on Z) + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S);% [un]corrected {based on k) + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum voxel-level p values {Z} + %--------------------------------------------------------------- + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %--------------------------------------------------------------------- + h = text(tCol(11),y,sprintf(TabDat.fmt{11},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %--------------------------------------------------------------- + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %----------------------------------------------- + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %----------------------------------------------- + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + if Pz < tol + Ze = Inf; + else, Ze = spm_invNcdf(1 - Pz); end + else + Pz = []; + Pu = []; + Qu = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %----------------------------------------------- + h = text(tCol(11),y,... + sprintf(TabDat.fmt{11},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) + end + + %-End: Store TabDat in UserData of axes & reset pointer + %======================================================================= + h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); + set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') + uimenu(h,'Label','Table') + uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + + %-Setup registry + %----------------------------------------------------------------------- + set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) + spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + + %-Return TabDat structure & reset pointer + %----------------------------------------------------------------------- + varargout = {TabDat}; + spm('Pointer','Arrow') + + + + + + %======================================================================= + case 'listcluster' %-List for current cluster only + %======================================================================= + % FORMAT TabDat = spm_list('listcluster',SPM,hReg) + + spm('Pointer','Watch') + + %-Parse arguments + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + SPM = varargin{2}; + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 32; + Dis = 4; + end + + + %-if there are suprathreshold voxels, filter out all but current cluster + %----------------------------------------------------------------------- + if length(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end + end + + %-Call 'list' functionality to produce table + %----------------------------------------------------------------------- + varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + + + + %======================================================================= + case 'txtlist' %-Print ASCII text table + %======================================================================= + % FORMAT spm_list('TxtList',TabDat,c) + + if nargin<2, error('Insufficient arguments'), end + if nargin<3, c=1; else, c=varargin{3}; end + TabDat = varargin{2}; + + %-Table Title + %----------------------------------------------------------------------- + fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) + fprintf('%c','='*ones(1,80)), fprintf('\n') + + %-Table header + %----------------------------------------------------------------------- + fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) + fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table data + %----------------------------------------------------------------------- + for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') + end + for i=1:max(1,11-size(TabDat.dat,1)), fprintf('\n'), end + fprintf('%s\n',TabDat.str) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table footer + %----------------------------------------------------------------------- + fprintf('%s\n',TabDat.ftr{:}) + fprintf('%c','='*ones(1,80)), fprintf('\n\n') + + + + %======================================================================= + case 'setcoords' %-Co-ordinate change + %======================================================================= + % FORMAT spm_list('SetCoords',xyz,hAx,hReg) + if nargin<3, error('Insufficient arguments'), end + hAx = varargin{3}; + xyz = varargin{2}; + UD = get(hAx,'UserData'); + HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + + %-Set all co-ord strings to black + %----------------------------------------------------------------------- + set(HlistXYZ,'Color','k') + + %-If co-ord matches a string, highlight it in red + %----------------------------------------------------------------------- + XYZ = get(HlistXYZ,'UserData'); + if iscell(XYZ), XYZ = cat(2,XYZ{:}); end + [null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); + if d=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + cm_pos; + end; + varargout{1} = H; + st.centre = mean(maxbb); + redraw_all + + case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + + case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + + case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3 + h = valid_handles(st.snap); + if ~isempty(h) + tmp=st.vols{h(1)}.mat*... + round(inv(st.vols{h(1)}.mat)*[tmp; ... + 1]); + end; + st.centre = tmp(1:3); + end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + cm_pos; + + case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + cm_pos; + + case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + bbox; + redraw_all; + else, + space(varargin{1}); + bbox; + redraw_all; + end; + + case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + + case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + + case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + + case 'delete', + my_delete(varargin{1}); + + case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + + case 'reset', + my_reset; + + case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + + case 'interp', + st.hld = varargin{1}; + redraw_all; + + case 'xhairs', + xhairs(varargin{1}); + + case 'register', + register(varargin{1}); + + case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + + case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + + case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + + case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + + case 'addtruecolourimage', + % spm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_select(1, 'image', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + + case 'addcolourbar', + addcolourbar(varargin{1}, varargin{2}); + + case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + + case 'addcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + addcontexts(handles); + + case 'rmcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + rmcontexts(handles); + + case 'context_menu', + c_menu(varargin{:}); + + case 'valid_handles', + if nargin == 1 + handles = 1:24; + else, + handles = varargin{1}; + end; + varargout{1} = valid_handles(handles); + + otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +global TMAX_ +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + mx = max([eps max(t)]); + mn = min([0 min(t)]); + if ~strcmp(TMAX_, 'auto') + mx = str2num(TMAX_); + end + %KND: + if numel(mx)==2 + mn=mx(1); + mx=mx(2); + end + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx, 'min',mn); + addcolourbar(handle,1); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx,'min',mn); + addcolourbar(handle,1); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx, ... + 'min',mn,'colour',c); + addcolourbar(handle,bset); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolourbar(vh,bh) +global st +if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); +else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); +end; +st.vols{vh}.blobs{bh}.cbar = axes('Parent',st.fig,... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on', 'YDir','normal', 'XTickLabel',[], 'XTick',[]); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'spm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['spm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''Reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +V.mapping = 'linear'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +spm_orthviews('reposition',spm_orthviews('pos')); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['spm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(finite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(finite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(finite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(finite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + imgc = max(imgc,mn); imgc = min(imgc,mx); + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(isfinite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgc), + tmp = imgc(isfinite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgs), + tmp = imgs(isfinite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(isfinite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(isfinite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(isfinite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpc(tmpc(:)>mx) = mx; + tmps(tmps(:)>mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpc = (tmpc-mn)/(mx-mn); + tmps = (tmps-mn)/(mx-mn); + tmpt(~finite(tmpt)) = 0; + tmpc(~finite(tmpc)) = 0; + tmps(~finite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_colourbar(vh,bh,interval,cdata) +global st +if isfield(st.vols{vh}.blobs{bh},'cbar') + if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); + end; + % only scale cdata if we have out-of-range truecolour values + if ndims(cdata)==3 && max(cdata(:))>1 + cdata=cdata./max(cdata(:)); + end; + image([0 1],interval,cdata,'Parent',st.vols{vh}.blobs{bh}.cbar); + set(st.vols{vh}.blobs{bh}.cbar, ... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1)... + (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'YDir','normal','XTickLabel',[],'XTick',[]); +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = []; %[ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[],'snap',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'spm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('spm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e v] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~finite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item00 = uimenu(item_parent, 'Label','unknown image', 'Separator','on'); +spm_orthviews('context_menu','image_info',item00,volhandle); +item0a = uimenu(item_parent, 'UserData','pos_mm', 'Callback','spm_orthviews(''context_menu'',''repos_mm'');','Separator','on'); +item0b = uimenu(item_parent, 'UserData','pos_vx', 'Callback','spm_orthviews(''context_menu'',''repos_vx'');'); +item0c = uimenu(item_parent, 'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','spm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +checked={'off','off'}; +checked{st.xhairs+1} = 'on'; +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''on'');','Checked',checked{2}); +item2_2 = uimenu(item2, 'Label','off', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''off'');','Checked',checked{1}); + +%contextsubmenu 3 +if st.Space == eye(4) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','spm_orthviews(''context_menu'',''orientation'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Voxel space (1st image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Voxel space (this image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',1);','Checked','off'); + +%contextsubmenu 3 +if isempty(st.snap) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Snap to Grid'); +item3_1 = uimenu(item3, 'Label','Don''t snap', 'Callback','spm_orthviews(''context_menu'',''snap'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Snap to 1st image', 'Callback','spm_orthviews(''context_menu'',''snap'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Snap to this image', 'Callback','spm_orthviews(''context_menu'',''snap'',1);','Checked','off'); + +%contextsubmenu 4 +if st.hld == 0, + checked = {'off', 'off', 'on'}; +elseif st.hld > 0, + checked = {'off', 'on', 'off'}; +else, + checked = {'on', 'off', 'off'}; +end; +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','spm_orthviews(''context_menu'',''interpolation'',3);', 'Checked',checked{3}); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','spm_orthviews(''context_menu'',''interpolation'',2);','Checked',checked{2}); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','spm_orthviews(''context_menu'',''interpolation'',1);','Checked',checked{1}); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','spm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window_gl'',1);'); +if license('test','image_toolbox') == 1 + offon = {'off', 'on'}; + checked = offon(strcmp(st.vols{volhandle}.mapping, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'})+1); + item6_2 = uimenu(item6, 'Label','Intensity mapping'); + item6_2_1 = uimenu(item6_2, 'Label','local'); + item6_2_1_1 = uimenu(item6_2_1, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''linear'');'); + item6_2_1_2 = uimenu(item6_2_1, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''histeq'');'); + item6_2_1_3 = uimenu(item6_2_1, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''loghisteq'');'); + item6_2_1_4 = uimenu(item6_2_1, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''quadhisteq'');'); + item6_2_2 = uimenu(item6_2, 'Label','global'); + item6_2_2_1 = uimenu(item6_2_2, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''linear'');'); + item6_2_2_2 = uimenu(item6_2_2, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''histeq'');'); + item6_2_2_3 = uimenu(item6_2_2, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''loghisteq'');'); + item6_2_2_4 = uimenu(item6_2_2, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''quadhisteq'');'); +end; +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add image'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_image'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_image'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored blobs','Separator','on'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_4 = uimenu(item7, 'Label','Add colored image'); +item7_4_1 = uimenu(item7_4, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_4_2 = uimenu(item7_4, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_5 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_6 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_6_1 = uimenu(item7_6, 'Label','local', 'Visible','on'); +item7_6_2 = uimenu(item7_6, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), + case 'image_info', + if nargin <3, + current_handle = get_current_handle; + else + current_handle = varargin{3}; + end; + if isfield(st.vols{current_handle},'fname'), + [p,n,e,v] = spm_fileparts(st.vols{current_handle}.fname); + if isfield(st.vols{current_handle},'n') + v = sprintf(',%d',st.vols{current_handle}.n); + end; + set(varargin{2}, 'Label',[n e v]); + end; + delete(get(varargin{2},'children')); + if exist('p','var') + item1 = uimenu(varargin{2}, 'Label', p); + end; + if isfield(st.vols{current_handle},'descrip'), + item2 = uimenu(varargin{2}, 'Label',... + st.vols{current_handle}.descrip); + end; + dt = st.vols{current_handle}.dt(1); + item3 = uimenu(varargin{2}, 'Label', sprintf('Data type: %s', spm_type(dt))); + str = 'Intensity: varied'; + if size(st.vols{current_handle}.pinfo,2) == 1, + if st.vols{current_handle}.pinfo(2), + str = sprintf('Intensity: Y = %g X + %g',... + st.vols{current_handle}.pinfo(1:2)'); + else, + str = sprintf('Intensity: Y = %g X', st.vols{current_handle}.pinfo(1)'); + end; + end; + item4 = uimenu(varargin{2}, 'Label',str); + item5 = uimenu(varargin{2}, 'Label', 'Image dims', 'Separator','on'); + item51 = uimenu(varargin{2}, 'Label',... + sprintf('%dx%dx%d', st.vols{current_handle}.dim(1:3))); + prms = spm_imatrix(st.vols{current_handle}.mat); + item6 = uimenu(varargin{2}, 'Label','Voxel size', 'Separator','on'); + item61 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', prms(7:9))); + item7 = uimenu(varargin{2}, 'Label','Origin', 'Separator','on'); + item71 = uimenu(varargin{2}, 'Label',... + sprintf('%.2f %.2f %.2f', prms(1:3))); + R = spm_matrix([0 0 0 prms(4:6)]); + item8 = uimenu(varargin{2}, 'Label','Rotations', 'Separator','on'); + item81 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(1,1:3))); + item82 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(2,1:3))); + item83 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(3,1:3))); + item9 = uimenu(varargin{2},... + 'Label','Specify other image...',... + 'Callback','spm_orthviews(''context_menu'',''swap_img'');',... + 'Separator','on'); + + case 'repos_mm', + oldpos_mm = spm_orthviews('pos'); + newpos_mm = spm_input('New Position (mm)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_mm),3); + spm_orthviews('reposition',newpos_mm); + + case 'repos_vx' + current_handle = get_current_handle; + oldpos_vx = spm_orthviews('pos', current_handle); + newpos_vx = spm_input('New Position (voxels)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_vx),3); + newpos_mm = st.vols{current_handle}.mat*[newpos_vx;1]; + spm_orthviews('reposition',newpos_mm(1:3)); + + case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + + case 'xhair', + spm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + + case 'orientation', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + spm_orthviews('Space'); + elseif varargin{2} == 2, + spm_orthviews('Space',1); + else, + spm_orthviews('Space',get_current_handle); + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Orientation'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'snap', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + st.snap = []; + elseif varargin{2} == 2, + st.snap = 1; + else, + st.snap = get_current_handle; + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Snap to Grid'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + + case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + spm_orthviews('window',current_handle); + else + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%.2f %.2f', st.vols{current_handle}.window); + else + defstr = ''; + end; + spm_orthviews('window',current_handle,spm_input('Range','+1','e',defstr,2)); + end; + + case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + current_handle = get_current_handle; + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%d %d', st.vols{current_handle}.window); + else + defstr = ''; + end; + data = spm_input('Range','+1','e',defstr,2); + + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + + case 'mapping', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', ... + 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + current_handle = get_current_handle; + cm_handles = get_cm_handles; + st.vols{current_handle}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(current_handle), ... + 'label','Intensity mapping'),'Children'); + for k = 1:numel(z_handle) + c_handle = get(z_handle(k), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + redraw_all; + + case 'mapping_gl', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + cm_handles = get_cm_handles; + for k = valid_handles(1:24), + st.vols{k}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(k), ... + 'label','Intensity mapping'),'Children'); + for l = 1:numel(z_handle) + c_handle = get(z_handle(l), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + end; + redraw_all; + + case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_select(1,'image','select new image')); + fn = fieldnames(new_info); + for k=1:numel(fn) + st.vols{current_handle}.(fn{k}) = new_info.(fn{k}); + end; + spm_orthviews('context_menu','image_info',get(gcbo, 'parent')); + redraw_all; + + case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + + case 'add_image', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + for i = 1:length(cm_handles), + addimage(cm_handles(i),fname); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Green blobs|Yellow blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;0 1 0;1 1 0;0 0 1;0 1 1;1 0 1]; + c_names = {'red';'green';'yellow';'blue';'cyan';'magenta'}; + hlabel = sprintf('%s (%s)',VOL.title,c_names{c}); + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + + case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + if isfield(st.vols{cm_handles(i)}.blobs{j},'cbar') + delete(st.vols{cm_handles(i)}.blobs{j}.cbar); + end + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + + case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',fname,c_names{c}); + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% ROI: TimeSeries +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchContentEdit(hObject, eventdata) +handles = guidata(hObject); +set(handles.searchContentEdit,'UserData', 'manual'); + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load SPM file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadSPMmat(hObject, eventdata, spmfile) +handles = guidata(hObject); +if nargin < 3 | isempty(spmfile) + %if exist(fullfile(pwd,'SPM.mat'), 'file') + if ~isempty(findstr('SPM2',spm('ver'))) & exist('spm_get')==2 + spmfile = spm_get([1],'SPM.mat','Select a SPM file'); + elseif ( ~isempty(findstr('SPM8',spm('ver'))) || ~isempty(findstr('SPM5',spm('ver')))) && exist('spm_select')==2 + spmfile = spm_select(1,'SPM.mat','Select a SPM file'); + else + if exist('spm')==2 + error('Check for inconsistencies in your SPM install.\nspm(''ver'') = %s\n', spm('ver')) + else + error('No SPM found'); + end + end +end +xSPM=load(spmfile); +if isfield(xSPM.SPM, 'xCon') + + if ~exist(xSPM.SPM.swd, 'dir') + nswd = fileparts(spmfile); + warning('Directory specified in SPM.swd is missing (%s).\nWill use: %s',xSPM.SPM.swd,nswd); + xSPM.SPM.swd=nswd; + end + numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', min(2,numel(xSPM.SPM.xCon)) );%length(xSPM.SPM.xCon)); + if ~exist(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)) & ... + exist(subarray(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname),1:2,-2)) + warning('Changing path') + xSPM.SPM.swd=xSPM.SPM.swd(3:end); + end + if ~isempty(numc) + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + end +else + msgbox('No contrast in this file') +end +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_indivResultsListPush(hObject, eventdata) +handles = guidata(hObject); +if ischar(handles.imageFileName) + handles.imageFileName={handles.imageFileName}; +end +[datadir,condir,condext]=fileparts(handles.imageFileName{1}); +if datadir(2)==':' + datadir=datadir(3:end); +end +[datadir,subdir]=fileparts(datadir); +if isempty(findstr('indiv/', datadir)) +elseif isempty(findstr('rfx/', datadir)) + xSPM=load(fullfile(datadir,'SPM.mat')); + indivdir=xSPM.xY.P; +else + return +end +req = get(handles.indivResultsListPush,'String'); +req = req{get(handles.indivResultsListPush, 'value')}; + +if isequal(req,'Group') + datadir=fileparts(datadir); + condir=handles.imageContrastName{1}; + condir=strrep(condir, '>', 'vs'); + condir=strrep(condir, '<', 'vs'); + condir=strrep(condir, '+', '_'); + condir=strrep(condir, ':', ' at'); + condir=deblank(condir); + condir=fullfile(datadir,'rfx',condir); + if ~exist(condir,'dir') + return + end + xSPM=load(fullfile(condir,'SPM.mat')); + numc=2; + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + return +elseif exist('swds','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + swds(get(gcbo, 'value'),:),... + handles.imageContrastName); +else + if exist(fullfile(datadir,req,'SPM.mat')) + xSPM=load(fullfile(datadir,req,'SPM.mat')); + if ~isfield(handles,'imageContrastName') + return + end + % numc=strmatch(handles.imageContrastName{1},{xSPM.SPM.xCon.name},'exact'); + numc=get(handles.contrastListPush, 'Value'); + filename=fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname); + else + % SPM adds a comma for 4D volumes + condext = strtok(condext,','); + filename = fullfile(datadir,req,[condir condext]); + warning('Using same filename in %s: ', req, filename) + end + if filename(2)==':' + filename=filename(3:end); + end + if ~exist(filename,'file') + error('File doesn''t exist: %s',filename) + return + end + set(handles.sectionViewListbox, 'Value', [1]); + % handles.sectionViewTargetFile = + % fullfile('\ndiayek\data\gazemo\rawdata\',req,'anat','wf_0001.img'); + guidata(hObject, handles); + if exist('xSPM','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + {xSPM.SPM.xCon(numc).name}); + else + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + '???'); + end + % CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end +uicontrol(hObject) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_paramestRegionPush(hObject, eventdata, roi,readdata) +if nargin<4 + readdata=1; +end +roi=struct('type', roi); +handles = guidata(hObject); +roi.name=get(handles.structureEdit, 'String'); + +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); + +if exist(spmfile(3:end), 'file') + warning('Possible disk swapping in xjview.m'); + spmfile=spmfile(3:end); +end +if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the RFX SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the RFX SPM.mat'); + end +end +if ~exist(spmfile) + return +end +xSPM=load(spmfile, 'SPM'); +[glmpath, glmpath]=fileparts(fileparts(fileparts(xSPM.SPM.swd))); + +RetrieveRawData = 0; +status = get(gcbf, 'SelectionType') +% right click +if strcmp(status, 'alt') + RetrieveRawData = 1; +end + +%[xyzmm,i] = spm_XYZreg('NearestXYZ',... +% spm_results_ui('GetCoords'),handles.currentxyz); +%spm_results_ui('SetCoords',xSPM.XYZmm(:,i)); +switch roi.type + case 'vox' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + xyz = handles.currentxyz; + case 'clu' + if not(isfield(handles,'selectedCluster')) | not(isempty(handles.selectedCluster)) + switch questdlg('Load from workspace','cluster?', 'currentDisplayMNI{1}','...','Cancel','currentDisplayMNI{1}') + case 'currentDisplayMNI{1}' + xyz=evalin('base', 'currentDisplayMNI{1}'); + case '...' + case 'Cancel' + return + end + delete(findobj('Tag', 'paramest')) + + else + delete(findobj('Tag', 'paramest')) + xyz =handles.currentDisplayMNI{1}; + end + case 'sph' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + delete(findobj('Tag', 'paramest')) + xyz = handles.currentxyz; + roi.radius=inputdlg('Radius of the sphere?'); + if isempty(roi.radius) + return + end + roi.radius=str2num(roi.radius{1}) + % XYZmm = xSPM.SPM.xVol.M(1:3,:)*[xSPM.SPM.xVol.XYZ; ones(1,size(xSPM.SPM.xVol.XYZ,2))]; + % xyz = sqrt( XYZmm-repmat(xyz,[1 size(XYZmm,2)]) ) + % xyz = XYZmm(:, xyz < roi.radius) + +end +% handles.currentDisplayMNI{1} +% ha=axes('Tag', 'paramest', 'Parent',gcf,'units','normalized','Position',[0.55, 0.05, 0.4, 0.4]); +if isequal(roi.type, 'sph') + if roi.radius > 20 + if not(spm_input({'Many many voxels may be retrieve','Radius of the sphere (in mm):',... + num2str(roi.radius),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end + end + +end +if size(xyz,1)>40 + if not(spm_input({'Many many voxels to retrieve','Number of voxel:',... + num2str(size(xyz,1)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end +end + +allbetas= []; +allcons= []; +allxyz = []; +allvxyz = []; +roi.nvox = []; +hwait = waitbar(0,'Reading 1st level data'); +lcd=cd; +handles.currentxyz +if isfield(handles, 'paramest') + handles.paramest=[]; +end + +roi.stat.TF=handles.TF; +roi.stat.pValue=handles.pValue; +roi.stat.df=handles.df; +% roi.stat.Intensity = +% handles.currentDisplayIntensity{1}(find(all(handles.currentDisplayMNI{1}==repmat(handles.currentxyz, 3,1),2))); +[i,j]=ismember(handles.mni{1}, flipud(xyz), 'rows'); +roi.stat.intensity(j(i)) = handles.intensity{1}(i); + +if isstruct(xSPM.SPM.xX.K) | ~readdata + n=1; + % Ic=strmatch('F Task',{xSPM.SPM.xCon.name}) + % + % allbetas=[] + % vcon= + % XYZ = SPM.xVol.XYZ; + % XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + % tmpallbetas= []; + % [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + % allbetas = [allbetas;(mean(tmpallbetas,1))]; + % allxyz= [allxyz;mean(tmpallxyz,1)]; + +else + n= length(xSPM.SPM.xY.P) +end + +% Is that a correlation? +PlotCorrelation = (n>1) && not(isequal(all(xSPM.SPM.xX.X==1), [1])); + +% try +% roi.sub2pr = str2num(subarray(strvcat(xSPM.SPM.xY.P),55:56,2)); +% end + +for sub = 1:n + + waitbar(sub/n,hwait); + + if n>1 + subdir = fileparts(xSPM.SPM.xY.P{sub}); + else + subdir = xSPM.SPM.swd; + end + subdir0 =subdir; + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, '[A-Z]?\:',''); + end + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, {'^\\ndiayek', '^\\ndiaye'},'') + end + + + if ~exist(fullfile(subdir, 'SPM.mat'), 'file') & ... + numel(dir(subarray(fullfile(subdir, 'SPM.mat'),1:2,-2)))>0 + subdir = subdir(3:end); + end + if exist(fullfile(subdir, 'SPM.mat'), 'file') + load(fullfile(subdir, 'SPM.mat')); + fprintf('Retrieving betas from: %s\n', fullfile(subdir, 'SPM.mat')) + + if sub==1 + % [cn.path cn.fname cn.ext]=fileparts(char(xSPM.SPM.xY.P(sub,:))); + % consfiles=[SPM.xCon.Vcon]; + + % retrieves the f map (where all betas should be) + Ic = [... + strmatch('f anim', lower({SPM.xCon.name})) ... + strmatch('f task', lower({SPM.xCon.name})) ... + strmatch('f map', lower({SPM.xCon.name}))]; + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name},'InitialValue',Ic); + end + Ic=Ic(end); + conname=SPM.xCon(Ic).name; + end + + %------- + Ic = strmatch(conname,{SPM.xCon.name}, 'exact') ; %contrast number + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name}); + end + %------- + else + SPM = xSPM.SPM + %using raw data + Ic=NaN; + end + try + XYZ = SPM.xVol.XYZ; + XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + tmpallbetas= []; + tmpallcons= []; + tmpallxyz = []; + cd(xSPM.SPM.swd) + cd(subdir) + for cluvox = 1:size(xyz,1) + switch (roi.type) + case 'sph' + [d] = spm_XYZreg('Edist',xyz(cluvox,:),XYZmm); + i=find(d<=roi.radius); + govox = ~isempty(i); + nxyz=XYZmm(:,i); + case {'vox', 'clu'} + govox = 1; + [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=sqrt(3) %one voxel in each dimZ + govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',... + num2str(xyz(cluvox,:)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0]); + end + end + if govox==1 + vXYZ = XYZ(:,i) ; % coordinates in voxels + + %-Get parameter and hyperparameter estimates + %======================================================================= + % ResMS = spm_get_data(SPM.VResMS,vXYZ); + % Bcov = ResMS*SPM.xX.Bcov; + CI = 1.96; % bilateral = spm_invNcdf(1 - (0.05/2)); + % compute contrast of parameter estimates and 95% C.I. + %---------------------------------------------------------- + %---- + xSPM.SPM.xY.VY(sub).fname = strrep(xSPM.SPM.xY.VY(sub).fname, subdir0, subdir); + tmpallcons = [tmpallcons ; spm_get_data(xSPM.SPM.xY.VY(sub), vXYZ)]; + if ~isnan(Ic) + beta = spm_get_data(SPM.Vbeta, vXYZ); + tmpallbetas = [tmpallbetas; (SPM.xCon(Ic).c'*beta)']; + else + tmpallbetas = tmpallcons; + end + + if RetrieveRawData + if sub==1 + fprintf('\tRetrieving rawdata from: %s\n', fullfile(subdir, 'SPM.mat')) + tmpallcons = [ spm_get_data(xSPM.SPM.xY.VY, vXYZ)']; + end + end + tmpallxyz = [tmpallxyz; nxyz']; + end + end + allbetas = [allbetas;(mean(tmpallbetas,1))]; + allcons = [allcons;(mean(tmpallcons,1))]; + allxyz= [allxyz;mean(tmpallxyz,1)]; + allvxyz= [allvxyz mean(vXYZ,2)]; + roi.nvox = [ roi.nvox; size(tmpallbetas,1)]; + tmp = mean(tmpallxyz); + % disp(['meancluster = ' num2str(mean(tmpallxyz,1))]); + catch + warning('Error with data from: %s', subdir) + roi.SPM =xSPM.SPM; + roi.xyz=xyz; + assignin('base','roi_tmp',roi) + end +end +close(hwait) +cd(lcd); +% +if ~isnan(Ic) + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c )),'*bf(1)', '')'), 1:6, -2)); + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c')),'*bf(1)', '')'), 1:6, -2)); + [regnames, ireg,ireg2]=unique(regnames); + a=[ repmat(' ',length(regnames),1) strvcat(strrep(regnames, '_', ' '))]; + a=dataread('string',a', '%s'); + leg=a(isort(ireg)); +else + leg={'??'}; +end +%a=reshape(a, [],108])'; +% +% n=factor(size(allbetas,2)); +% n=sort([n(end) prod(n(1:end-1))]); +% +% prompt={'Enter the matrix size for x^2:','Enter the colormap name:'}; +% def={'20','hsv'}; +% dlgTitle='Input for Peaks function'; +% lineNo=1; +% answer=inputdlg(prompt,dlgTitle,lineNo,def); +% +% AddOpts.Resize='on'; +% AddOpts.WindowStyle='normal'; +% AddOpts.Interpreter='tex'; +% answer=inputdlg(prompt,dlgTitle,lineNo,def,AddOpts); +% +assignin('base', 'allbetas', allbetas) +% ReshapeData = []; +% xbars=[]; +% fxorder=[2 3 1]; +% switch size(allbetas,2) +% case 8 +% ReshapeData = [4 2]; +% case 4 +% if all(ismember(a,{'Neutral' 'Fearful' 'Angry' 'Happy'})) +% ReshapeData = [4 1]; +% end +% case 18 +% ReshapeData = [18 1]; +% case 16 +% % ReshapeData = [2 8]; +% % xtick=[1 3 4 5 7 8 9 11]; +% % fxorder=[3 2 1]; +% ReshapeData = [16 1]; +% end +% if isempty(ReshapeData) +% ReshapeData = [fliplr(factor(size(allbetas,2))) 1]; +% ReshapeData = [ ReshapeData(1) prod(ReshapeData(2:end))] +% end +% allbetas=reshape(allbetas, [],ReshapeData(1),ReshapeData(2)); +% allbetas = permute(allbetas,fxorder); + +% allxyz=reshape(allxyz, [], 1, 3); +% allxyz=permute(allxyz, [3 2 1]); + +%assignin('base', 'allbetas', allbetas) +%assignin('base', 'allxyz', xyz) + + +roi.allbetas=allbetas; +roi.allxyz=allxyz'; +roi.allvxyz=allvxyz; +roi.allcons=allcons'; +roi.XYZmm=xyz'; +roi.xyz=mean(allxyz,1)'; +assignin('base', 'roi', roi) +%Icc = find(xSPM.SPM.xX.X*xSPM.SPM.xCon(strmatch(handles.imageContrastName{1}, {xSPM.SPM.xCon.name})).c); +% if ~isempty(handles.imageContrastName) +% fn=handles.imageContrastName{1}; +% else +[fp,fn,fe] = fileparts(handles.imageFileName{1}); +fn=[fn fe]; +cn=[xSPM.SPM.xCon.Vspm]; + +% end +Icc = strmatch(fn, {cn.fname}) ; +roi.fname = fullfile(fp,fn); +roi.cn = cn; +roi.Icc=Icc; +roi.leg=leg; +assignin('base', 'roi', roi) + + +try + plot_betas(roi,glmpath,handles) +catch + if n>1 + try + figure;h=barerrorbar(1:(prod(size(roi.allbetas))/size(roi.allbetas,1)),mean(roi.allbetas,1)',stderrw(roi.allbetas,2:ndims(roi.allbetas),1)',NaN) + catch + end + else + figure;bar(roi.allbetas) + end + xlabel('Task') + set(gca, 'XTickLabel', leg) + set(gca, 'XTickLabel', {'Self Pos' 'Self Neg' 'Other Pos' 'Other Neg' 'Word Pos' 'Word Neg'}) + xlabel('Task') + %legend({'Positive Words' 'Negative Words'},'Location', 'Best') + delete(legend) +end +title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +setappdata(gca, 'ROI', roi) + +if ~isempty(Icc) + if ~isempty(xSPM.SPM.xCon(Icc).c) + roi.allregressors = xSPM.SPM.xX.X*xSPM.SPM.xCon(Icc).c; + else + roi.allregressors = []; + end + assignin('base', 'roi', roi) +end +if PlotCorrelation + %correlation plot + figure; + cla; + plot(roi.allregressors, roi.allcons, 'x') + xY=strvcat(xSPM.SPM.xY.P); + xY=cellstr(xY(:,~allthesame(xY))); + text(roi.allregressors, roi.allcons,xY,'tag','Labels'); + %hl=legend({'test'}, 0); + [s,o,r2,sce,p]=linearfit(roi.allcons,roi.allregressors); + text(median(roi.allregressors), quantile(roi.allcons,.90), {'Correlation: ' sprintf('r2 = %g\np = %g', r2,p)}) + xlabel(xSPM.SPM.xX.name(find(xSPM.SPM.xCon(Icc).c))) + ylabel(xSPM.SPM.xY.VY(1).descrip) + + [xx]=axis; + hold on + plot(xx(1:2), s*xx(1:2)+o, '--') + hold off + title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +end + +if RetrieveRawData + figure; + if n==1 + subplot(2,1,1); + plot(tmpallcons); + legend('BOLD',0) + subplot(2,1,2); + % iReg=any(SPM.xCon(handles.imageContrastName).c,2); + % plot(normalize(SPM.xX.X(:,iReg), 'unity')*diff(subarray(axis, [3 4]))/5+subarray(axis, 3)) + % legend([{'BOLD'} SPM.xX.name(iReg)],1) + Ic = handles.imageContrastName; + if isempty(Ic) || ~isnumeric(Ic) + Ic = get(handles.contrastListPush, 'Value'); + end + plot( [ + spm_FcUtil('Yc',SPM.xCon(Ic),SPM.xX.xKXs,beta) ... + SPM.xX.X*SPM.xCon(Ic).c*pinv(SPM.xCon(Ic).c)*beta ... + (1-2*get(handles.negativeIntensityRadio, 'Value'))*SPM.xX.X*SPM.xCon(Ic).c ]) + legend({ 'adjusted', 'predicted' SPM.xCon(Ic).name},0) + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [c_num, c_let, c_word]=mycolourset +c_num = [1 0 0;0 1 0;1 1 0;0 1 1;0 0 1;1 0 1]; +c_let = {'r';'g';'y';'c';'b';'m'}; +c_word= {'red';'green';'yellow';'cyan';'blue';'magenta'}; \ No newline at end of file diff --git a/xjview_markus.m b/xjview_markus.m new file mode 100644 index 0000000..5b82323 --- /dev/null +++ b/xjview_markus.m @@ -0,0 +1,8547 @@ +function xjview_karim(varargin) +% PWD=pwd; eval('cd D:\Gschwind\Data\VISIONCHIM'); +% %P = genpath(pwd);rmpath(P); +% cd(PWD) +addpath('C:\Program Files\MATLAB\R2006b\work\xjview\matlab') +% xjview, version 4 +% +% usage 1: xjview (no argument) +% for displaying a result img file, or multiple image files, +% (which will be loaded later) and changing p-value or t/f-value +% usage 2: xjview(imagefilename) +% for displaying the result img file and changing p-value or +% t-value +% Example: xjView spmT_0002.img +% xjView('spmT_0002.img') +% xjView mymask.img +% usage 3: xjview(imagefilename1, imagefilename2, ...) +% for displaying the result img files and changing p-value or +% t/f-value +% Example: xjView spmT_0002.img spmT_0005.img spmT_0007.img +% xjView('spmT_0002.img', 'spmT_0003.img', 'spmT_0006.img') +% xjView myMask1.img myMask2.img myMask3.img +% usage 4: xjview(mnicoord, intensity) +% for displaying where are the mni coordinates +% mnicoord: Nx3 matrix of mni coordinates +% intensity: (optional) Nx1 matrix, usually t values of the +% corresponding voxels +% Example: xjView([20 10 1; -10 2 5],[1;2]) +% xjView([20 10 1; -10 2 5]) +% Note: to use xjview this way, you may need to modify the value +% of M and DIM in the begining of xjview.m +% +% http://people.hnl.bcm.tmc.edu/cuixu/xjView +% +% by Xu Cui and Jian Li 2/21/2005 +% last modified: 02/18/2007 (add colorbar max control) +% last modified: 11/16/2006 (keyboard shortcut for open image and open roi file) +% last modified: 06/16/2006 (spm5 compatible) +% last modified: 05/30/2006 (left/right flip, path of mask.img and templateFile.img) +% last modified: 05/08/2006 (debug CallBack_volumePush function, change handles.intensity{1} to intensity) +% last modified: 04/03/2006 (modify tr) +% last modified: 12/28/2005 (modify SPM process) +% +% Thank Sergey Pakhomov for sharing his database (MNI Space Utility). +% Thank Yuval Cohen for the maximize figure function (maximize.m) +% + +% TODO +% Send SPM to workspace + +warnstate = warning; +warning off; + +% pre-set values +% important! you need compare the display of xjview and spm. If you find +% xjview flipped the left/right, you need to set leftrightflip = 1; +% otherwise leave it to 0. +leftrightflip = 0; +% leftrightflip = 1 ; %must be on in the CMU... +% Now with spm-flip = 1; xjview-flip=1 + +% You only need to change M and DIM when you want to use xjview under +% 'usage 4'. +M = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +DIM = [41 48 35]'; +TR = 2; % you don't need to set TR is you only use the viewing part of xjview + +% system settings +try + spmdir = spm('dir'); + spm('defaults', 'fmri'); +catch + disp('Please add spm path.'); + warning(warnstate(1).state); + return +end + +if ispc + os = 'windows'; +elseif isunix + os = 'linux'; +else + warndlg('I don''t know what kind of computer you are using. I assumed it is unix.', 'What computer are you using?'); + os = 'linux'; +end +screenResolution = get(0,'ScreenSize'); + +xjviewpath = fileparts(which('xjview')); + +% pre-set values +pValue = 0.001; +intensityThreshold = 0; +clusterSizeThreshold = 5; + + +% Appearance Settings +figurePosition = [0.100, 0.050, 0.660, 0.880]; +sectionViewPosition = [0.5,0.61,0.45,0.45]; +glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +if screenResolution(3) <= 1024 + figurePosition = [0.100, 0.050, 0.700, 0.900]; + sectionViewPosition = [0.5, 0.61, 0.45, 0.46]; + glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +end + +left = 0.01; +editBoxHeight = 0.05; +editBoxWidth = 0.200; +editBoxLeft = 0.100; + +controlPanelPosition = [left, 0.080, 0.500, 0.500]; +stretchMatrix = diag([controlPanelPosition(3),controlPanelPosition(4),controlPanelPosition(3),controlPanelPosition(4)]); +controlPanelOffset = controlPanelPosition' .* [1,1,0,0]'; +heightUnit = 0.055; + +sliderPosition = stretchMatrix*[0.000, 0*heightUnit, 1.000, editBoxHeight]' + controlPanelOffset; +pValueTextPosition = stretchMatrix*[0.000, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pValueEditPosition = stretchMatrix*[0.110, 1*heightUnit, editBoxWidth*4/3, editBoxHeight]' + controlPanelOffset; +intensityThresholdTextPosition = stretchMatrix*[0.400, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +intensityThresholdEditPosition = stretchMatrix*[0.520, 1*heightUnit, editBoxWidth*3/3, editBoxHeight]' + controlPanelOffset; +dfTextPosition = stretchMatrix*[0.740, 1*heightUnit, 0.8-0.74, editBoxHeight]' + controlPanelOffset; +dfEditPosition = stretchMatrix*[0.800, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdTextPosition = stretchMatrix*[0.000, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdEditPosition = stretchMatrix*[0.150, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pickThisClusterPushPosition = stretchMatrix*[0.400, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +selectThisClusterPushPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +clearSelectedClusterPushPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +thisClusterSizeTextPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +thisClusterSizeEditPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +loadImagePushPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +imageFileEditPosition = stretchMatrix*[0.200, 3*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImagePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImageFileEditPosition = stretchMatrix*[0.200, 4*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveResultPSPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +resultPSFileEditPosition = stretchMatrix*[0.200, 5*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayIntensityTextPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth+0.1, editBoxHeight]' + controlPanelOffset; +allIntensityRadioPosition = stretchMatrix*[0.250, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +positiveIntensityRadioPosition = stretchMatrix*[0.400, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +negativeIntensityRadioPosition = stretchMatrix*[0.550, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderViewCheckPosition = stretchMatrix*[0.780, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +hideControlPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +volumePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +commonRegionPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +%knd +paramestPushPosition = stretchMatrix*[0.800, 4*heightUnit, editBoxWidth*.5, editBoxHeight]' + controlPanelOffset; +%-- +displayPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +allinonePushPosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchPushPosition = stretchMatrix*[0.000, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchContentEditPosition = stretchMatrix*[0.200, 6*heightUnit, editBoxWidth*2, editBoxHeight]' + controlPanelOffset; +searchTextPosition = stretchMatrix*[0.600, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchEnginePopPosition = stretchMatrix*[0.600, 6*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +overlayPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayEditPosition = stretchMatrix*[0.200, 5*heightUnit, 0.6-editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayPopPosition = stretchMatrix*[0.600, 5*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +helpPosition = stretchMatrix*[0.800, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +infoTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; +%xjViewPosition = stretchMatrix*[0.400, 13*heightUnit, editBoxWidth*2.5, editBoxHeight*3]' + controlPanelOffset; +%connameTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; + +sectionViewListboxPosition = [sectionViewPosition(1)+0.4, sectionViewPosition(2)+0.02, 0.1, 0.14]; +sectionViewMoreTargetPushPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.02,0.10,0.02]; +xHairCheckPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)+0.14,0.15,0.02]; +setTRangeEditPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.06,0.10,0.02]; +setTRangeTextPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.04,0.10,0.02]; + +getStructurePushPosition = [glassViewAxesPosition(1), glassViewAxesPosition(2)-0.06, editBoxWidth/2, editBoxHeight/2]; +structureEditPosition = [getStructurePushPosition(1), getStructurePushPosition(2), 1, getStructurePushPosition(4)]; +framePosition = (controlPanelPosition - controlPanelOffset')*1.05 + 0.95*controlPanelOffset'; + +%knd +setContrastNameTextPosition = [glassViewAxesPosition(1),glassViewAxesPosition(2)-0.026,0.6,0.03]; +setContrastListPosition = [setContrastNameTextPosition(1)+setContrastNameTextPosition(3)+.01,setContrastNameTextPosition(2),0.05,setContrastNameTextPosition(4)]; +setContrastListPosition = [glassViewAxesPosition(1)+.05*glassViewAxesPosition(3),glassViewAxesPosition(2)-0.026,glassViewAxesPosition(3)*.95,0.03]; +setIndivResultsListPosition = [setTRangeTextPosition(1)-0.25,setTRangeEditPosition(2),0.20,setTRangeEditPosition(4)]; +%-- knd + +% draw figure and control +figureBKcolor=[176/255 252/255 188/255]; +figureBKcolor=get(0,'Defaultuicontrolbackgroundcolor'); +f = figure('unit','normalized','position',figurePosition,'Color',figureBKcolor,'defaultuicontrolBackgroundColor', figureBKcolor,... + 'Name','xjView', 'Tag', 'xjView', 'NumberTitle','off','resize','off','CloseRequestFcn', {@CallBack_quit, warnstate(1).state}, 'visible','off'); +handles = guihandles(f); + +% databases +try + X = load('TDdatabase'); + handles.DB = X.DB; + handles.wholeMaskMNIAll = X.wholeMaskMNIAll; +catch + errordlg('I can''t find TDdatabase.mat','TDdatabase not found'); +end + +handles.figure = f; +handles.frame = uicontrol(handles.figure,'style','frame',... + 'unit','normalized',... + 'position',framePosition,... + 'Visible','off'); +handles.slider = uicontrol(handles.figure,'style','slider',... + 'unit','normalized',... + 'position',sliderPosition,... + 'max',1,'min',0,... + 'sliderstep',[0.01,0.10],... + 'callback',@CallBack_slider,... + 'value',0,'Visible','on'); +handles.pValueTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',pValueTextPosition,... + 'string','pValue=','horizontal','left'); +handles.pValueEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',pValueEditPosition,... + 'horizontal','left',... + 'String', num2str(pValue),... + 'BackgroundColor', 'w',... + 'callback',@CallBack_pValueEdit); +handles.intensityThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',intensityThresholdTextPosition,... + 'string',' intensity=','horizontal','left'); +handles.intensityThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',intensityThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(intensityThreshold),... + 'callback',@CallBack_intensityThresholdEdit); +handles.dfText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',dfTextPosition,... + 'string','df= ','horizontal','right'); +handles.dfEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',dfEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', '',... + 'callback',@CallBack_dfEdit); +handles.clusterSizeThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',clusterSizeThresholdTextPosition,... + 'string','cluster size >=','horizontal','left'); +handles.clusterSizeThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',clusterSizeThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(clusterSizeThreshold),... + 'callback',@CallBack_clusterSizeThresholdEdit); +handles.thisClusterSizeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',thisClusterSizeTextPosition,... + 'string','size= ','horizontal','right', 'visible', 'off'); +handles.thisClusterSizeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',thisClusterSizeEditPosition,... + 'horizontal','left',... + 'Enable', 'inactive',... + 'String', '','visible','off'); + +handles.imageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',imageFileEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_imageFileEdit,... + 'visible','off'); +handles.saveImageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',saveImageFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myMask.img',... + 'callback',@CallBack_saveImageFileEdit,... + 'visible','off'); +handles.saveResultPSEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',resultPSFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myResult.ps',... + 'callback',@CallBack_saveResultPSEdit,... + 'visible','off'); +handles.loadImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',loadImagePushPosition,... + 'string','Load Image','callback',@CallBack_loadImagePush,... + 'visible','off'); +handles.saveImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveImagePushPosition,... + 'string','Save Image','callback',@CallBack_saveImagePush,... + 'visible','off'); +handles.saveResultPSPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveResultPSPushPosition,... + 'string','Save Result','callback',@CallBack_saveResultPSPush,... + 'visible','off'); +handles.getStructurePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',getStructurePushPosition,... + 'string','Get Structure','callback',@CallBack_getStructurePush,'visible','off'); +handles.structureEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',structureEditPosition,... + 'horizontal','center',... + 'enable', 'on',... + 'UserData',struct(... + 'hReg', [],... + 'M', M,... + 'D', DIM,... + 'xyz', [0 0 0] )); +handles.pickThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',pickThisClusterPushPosition,... + 'string','Pick Cluster/Info','callback',@CallBack_pickThisClusterPush); +handles.selectThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',selectThisClusterPushPosition,... + 'string','Select Cluster','callback',@CallBack_selectThisClusterPush); +handles.clearSelectedClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',clearSelectedClusterPushPosition,... + 'string','Clear Selection','callback',@CallBack_clearSelectedClusterPush); + +handles.displayIntensityText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',displayIntensityTextPosition,... + 'string','display intensity','horizontal','left'); +handles.allIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','All',... + 'position',allIntensityRadioPosition,... + 'value', 1,... + 'callback',@CallBack_allIntensityRadio); +handles.positiveIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only +',... + 'position',positiveIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'+'}); +handles.negativeIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only -',... + 'position',negativeIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'-'}); +handles.renderViewCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','Render View' ,... + 'horizontal', 'right',... + 'position',renderViewCheckPosition,... + 'callback', @CallBack_renderViewCheck); + +handles.sectionViewListbox = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', {'single T1','avg152PD','avg152T1','avg152T2','avg305T1','ch2','ch2bet','aal','brodmann'}, ... + 'value',3,... + 'position',sectionViewListboxPosition,... + 'callback',@CallBack_sectionViewListbox); + +handles.xHairCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','XHairs Off' ,... + 'horizontal','left',... + 'position',xHairCheckPosition,... + 'callback',@CallBack_xHairCheck); +handles.sectionViewMoreTargetPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',sectionViewMoreTargetPushPosition,... + 'string','other ...','callback',@CallBack_sectionViewMoreTargetPush); +handles.setTRangeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',setTRangeEditPosition,'BackgroundColor', 'w',... + 'string','auto','callback',@CallBack_setTRangeEdit); +handles.setTRangeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setTRangeTextPosition,... + 'string','colorbar max'); +handles.hideControlPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', '<', 'position', hideControlPushPosition,... + 'visible','off'); +handles.volumePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'volume', ... + 'position', volumePushPosition,... + 'callback', @CallBack_volumePush); +handles.commonRegionPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'common region', ... + 'position', commonRegionPushPosition,... + 'callback', @CallBack_commonRegionPush); +handles.displayPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'display', ... + 'position', displayPushPosition,... + 'callback', @CallBack_displayPush,... + 'visible','off'); +handles.allinonePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'all in one', ... + 'position', allinonePushPosition,... + 'callback', @CallBack_allinonePush,... + 'visible','off'); +%knd: +handles.setContrastNameText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setContrastNameTextPosition, 'FontSize', 13,... + 'string',' ... ','callback',@CallBack_setContrastNameTextPosition); +handles.contrastListPush = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setContrastListPosition,... + 'callback', @CallBack_contrastListPush,... + 'visible','on'); + +handles.indivResultsListPush(1) = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setIndivResultsListPosition,... + 'callback', @CallBack_indivResultsListPush,... + 'visible','on'); + +handles.paramestPush(1) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Vox Betas', ... + 'position', paramestPushPosition'.*[1 1 2 1],... + 'callback', {@CallBack_paramestRegionPush, 'vox'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'vox', 0},... + 'visible','on'); +handles.paramestPush(2) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Cluster', ... + 'position', paramestPushPosition-[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'clu'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'clu', 0},... + 'visible','on'); +handles.paramestPush(3) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Sphere', ... + 'position', paramestPushPosition-2*[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'sph'},... + 'visible','on'); +%--knd + +handles.searchPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',searchPushPosition,... + 'String', 'search','callback',@CallBack_searchPush, 'ForeGroundColor',[0 0 1]); +handles.searchContentEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',searchContentEditPosition,... + 'ForeGroundColor',[0 0 1],... + 'BackgroundColor', 'w',... + 'horizontal','left','callback', @CallBack_searchContentEdit); +handles.searchText = uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',searchTextPosition,... + 'string', ' in',... + 'horizontal','left',... + 'visible','off'); +handles.searchEnginePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',searchEnginePopPosition, ... + 'String',{'Brede';'Jede';'xBrain.org';'Google Scholar';'Pubmed';'Wikipedia'}, ... + 'Style','popupmenu', ... + 'value',1); +handles.overlayPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',overlayPushPosition,... + 'String', 'overlay','callback',@CallBack_overlayPush); +handles.overlayEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',overlayEditPosition,... + 'BackgroundColor', 'w',... + 'horizontal','left',... + 'callback', @CallBack_overlayEdit); +handles.overlayPop = uicontrol(handles.figure, 'style','popupmenu',... + 'unit','normalized','position',overlayPopPosition,... + 'string', sort(fieldnames(handles.wholeMaskMNIAll)),... + 'horizontal','left',... + 'callback', @CallBack_overlayPop); + +handles.helpPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',helpPosition,... + 'String', 'help','callback','web http://people.hnl.bcm.tmc.edu/cuixu/xjView','ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.infoTextBox = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',infoTextBoxPosition,... + 'String', 'Welcome to xjView 4','ForeGroundColor','k', 'BackgroundColor', 'w',... + 'horizontal','left', ...'fontname','times',... + 'max',2, 'min',0); +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + set(handles.infoTextBox, 'String', s); +end + +handles.glassViewAxes = axes('unit','normalized','position',glassViewAxesPosition,'XTick',[],'YTick',[],'visible','off'); + + +handles.testEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',[0.1 0.4 0.2 0.05],... + 'horizontal','left',... + 'callback',@test,... + 'visible','off'); + +% menu +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +hMenuFile = findobj(get(handles.figure,'Children'),'flat','Label','&File'); +if ~isempty(hMenuFile) + hMenuFileOpen = findobj(get(handles.figure,'Children'),'Label','&Open...'); + set(hMenuFileOpen, 'label', 'Open Figure...'); + hMenuFileSave = findobj(get(handles.figure,'Children'),'Label','&Save'); + set(hMenuFileSave, 'label', 'Save Figure ...'); + hMenuFileSaveAs = findobj(get(handles.figure,'Children'),'Label','Save &As...'); + set(hMenuFileSaveAs, 'label', 'Save Figure As ...'); +else + hMenuFile = uimenu(handles.figure, 'label', '&File'); +end + +set(hMenuFile,'ForegroundColor',[0 0 1]); +set(findobj(hMenuFile,'Position',1),'Separator','on'); +%knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open SPM file (SPM.mat) ...',... + 'CallBack',@CallBack_loadSPMmat, 'Accelerator', 'o'); +%--knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open Images (*.img) ...',... + 'CallBack',@CallBack_loadImagePush, 'Accelerator', 'o'); +uimenu('Parent',hMenuFile,'Position',2,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 0}); +uimenu('Parent',hMenuFile,'Position',3,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image as Mask (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 1}); +uimenu('Parent',hMenuFile,'Position',4,'ForegroundColor',[0 0 1],... + 'Label','Save Result (*.ps/pdf) ...',... + 'CallBack',@CallBack_saveResultPSPush); + +hMenuHelp = findobj(get(handles.figure,'Children'),'flat','Label','&Help'); +if isempty(hMenuHelp) + hMenuHelp = uimenu(handles.figure, 'label', 'xjView &Help'); +end +set(hMenuHelp,'ForegroundColor',[0 0 1]); +uimenu('Parent',hMenuHelp,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','xBrain.org: brain mapping database',... + 'CallBack','web http://www.xbrain.org -browser'); +uimenu('Parent',hMenuHelp,'Position',2,... + 'Label','xjview help','ForegroundColor',[0 0 1],... + 'CallBack','web http://people.hnl.bcm.tmc.edu/cuixu/xjView'); +set(findobj(hMenuHelp,'Position',3),'Separator','on'); +set(0,'ShowHiddenHandles',cSHH) + +if exist('cuixuBOLDretrieve') + hMenuAnalyze = uimenu('label','&Analyze','ForegroundColor',[0 0 1],'visible','on'); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess); + hMenuProcess = uimenu(hMenuAnalyze,'label','Process (GLM estimation)','ForegroundColor',[0 0 1],'callback',@CallBack_process); + hMenuSPMProcess = uimenu(hMenuAnalyze,'label','SPMProcess (GLM using SPM)','ForegroundColor',[0 0 1],'callback',@CallBack_SPMProcess); + hMenuGLMPeak = uimenu(hMenuAnalyze,'label','GLM on peak BOLD','ForegroundColor',[0 0 1],'callback',@CallBack_GLMPeak); + hMenuContrast = uimenu(hMenuAnalyze,'label','Contrast','ForegroundColor',[0 0 1],'callback',@CallBack_contrast); + hMenuFDR = uimenu(hMenuAnalyze,'label','FDR','ForegroundColor',[0 0 1],'callback',@CallBack_fdr); + hMenuROI = uimenu(hMenuAnalyze,'label','ROI: retrieve signal','ForegroundColor',[0 0 1],'callback',@CallBack_timeSeries); + hMenuROIPlot = uimenu(hMenuAnalyze,'label','ROI: plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotROI, 'Accelerator', 'm'); + hMenuROIIndividualPlot = uimenu(hMenuAnalyze,'label','ROI: individual plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROI); + hMenuROIIndividualPlotWithBehavior = uimenu(hMenuAnalyze,'label','ROI: individual plot with behavior','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROIWithBehavior); + hMenuROICorrelationPlot = uimenu(hMenuAnalyze,'label','ROI: correlation plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotCorrelationROI); + %hMenuWholeBrainCorrelation = uimenu(hMenuAnalyze,'label','Whole brain correlation','ForegroundColor',[0 0 1],'callback',@CallBack_wholeBrainCorrelation); + hMenuBehaviorAnalysis = uimenu(hMenuAnalyze,'label','Behavior analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_behaviorAnalysis); + hMenuHeadMovementAnalysis = uimenu(hMenuAnalyze,'label','Head movement analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_headMovementAnalysis); + hMenuModelComparison = uimenu(hMenuAnalyze,'label','Linear model comparison','ForegroundColor',[0 0 1],'callback',@CallBack_modelComparison); + + hMenuHNLOnly = uimenu('label','For H&NL Only','ForegroundColor',[0 0 1],'visible','on'); + hMenuNew2Old = uimenu(hMenuHNLOnly,'label','Format convert','ForegroundColor',[0 0 1],'callback',@CallBack_new2old); + hMenuPreprocessCluster = uimenu(hMenuHNLOnly,'label','Preprocess (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_preprocess, 'cluster'}); + hMenuProcessCluster = uimenu(hMenuHNLOnly,'label','Process (GLM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_process, 'cluster'}); + hMenuSPMProcessCluster = uimenu(hMenuHNLOnly,'label','SPM Process (GLM using SPM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_SPMProcess, 'cluster'}); + hMenuGLMPeakCluster = uimenu(hMenuHNLOnly,'label','GLM on peak BOLD (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_GLMPeak, 'cluster'}); +end + +figurecm = uicontextmenu; +uimenu(figurecm,'label','Red','callback','set(gcf,''color'',''r'')'); +uimenu(figurecm,'label','White','callback','set(gcf,''color'',''w'')'); +uimenu(figurecm,'label','Gray','callback','set(gcf,''color'',[0.925, 0.914, 0.847])'); +%set(handles.figure,'uicontextmenu',figurecm); +set(handles.figure,'WindowButtonDownFcn',@figureMouseUpFcn); + +set(handles.figure,'visible','on'); + +% save pre-set values +handles.system = os; +handles.spmdir = spmdir; +handles.screenResolution = screenResolution; +handles.pValue = pValue; +handles.intensityThreshold = intensityThreshold; +handles.clusterSizeThreshold = clusterSizeThreshold; +handles.sectionViewPosition = sectionViewPosition; +handles.sectionViewTargetFile = getSectionViewTargetFile(spmdir, 'avg152T1'); +%knd +if ~isempty(findstr('gazemo', pwd)) + handles.sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean-no120.img'); +end +guidata(f, handles); + +% global variables for rotation matrix M and dimension +global M_; +global DIM_; +global TR_; +global LEFTRIGHTFLIP_; +global TMAX_; % colorbar max to display in section view +M_ = M; +DIM_ = DIM; +TR_ = TR; +LEFTRIGHTFLIP_ = leftrightflip; +TMAX_ = 'auto'; + +% check input arguments +if length(varargin) == 0 + %CallBack_loadSPMmat(handles.loadImagePush) + + if exist(fullfile(pwd,'SPM.mat'), 'file') + xSPM=load(fullfile(pwd,'SPM.mat')); + numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', length(xSPM.SPM.xCon)); + if ~isempty(numc) + %MG:02.04.2008 CallBack_loadImagePush(handles.loadImagePush, [], {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)}); + CallBack_loadImagePush(handles.loadImagePush, [], fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)); + end + end + +elseif isstr(varargin{1}) + if isempty(findstr('.mat', varargin{1})) + CallBack_loadImagePush(handles.loadImagePush, [], varargin); + else + CallBack_loadSPMmat(handles.loadImagePush, [], varargin{1}); + end +else + mniCoord = varargin{1}; + if length(varargin) < 2 + intensity = ones(size(mniCoord,1),1); + else + intensity = varargin{2}; + end + thisStruct.mni = mniCoord; + thisStruct.intensity = intensity; + thisStruct.M = M; + thisStruct.DIM = DIM'; + CallBack_loadImagePush(handles.loadImagePush, [], thisStruct); +end + + + +function test(hObject, eventdata) +handles = guidata(gcbo); +set(hObject, 'String', num2str(handles.pValue)); +vars = evalin('base','who'); +vars +x = evalin('base',vars{1}); +x +handles.DIM + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdr(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); +if get(handles.allIntensityRadio, 'Value') + positive = 1; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end +xjviewpath = fileparts(which('xjview')); +maskImageFile = fullfile(xjviewpath, 'mask.img'); +[threshold, pvalue] = fdr(handles.imageFileName{1}, q, positive, maskImageFile); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% model comparison +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_modelComparison(hObject, eventdata) +answer = getVariable({'y','x (full model)', 'x (reduced model)'}); + +if isempty(answer) + return; +end + +if ~isempty(answer{1}) + y = evalin('base',answer{1}); +else + return; +end +if ~isempty(answer{2}) + xf = evalin('base',answer{2}); % full model +else + return; +end +if ~isempty(answer{3}) + xr = evalin('base',answer{3}); % reduced model +else + xr = []; +end + +% make vector column vector +[r, c] = size(y); +if r==1; y = y'; end +[r, c] = size(xf); +if r(0.5+ii/10); +end + +K = {zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1))}; +for ii=1:size(C,1) + for jj=1:4 + K{jj}(ii) = sum(CC{jj}(ii,:)) - 1; + end +end + +x=[0:size(C,1)]; +for jj=1:4 + y{jj}=zeros(size(x)); +end + +for ii=1:length(x) + for jj=1:4 + y{jj}(ii) = sum(K{jj} == x(ii)); + end +end + +figure; +loglog(x,y{1}, x, y{2}, x, y{3}, x, y{4}); +xlabel('degree'); +ylabel('counts'); +legend('0.6', '0.7', '0.8', '0.9'); +axis equal + + +z = sum(abs(C))-1; +zx = 0:max(z); +for ii=1:length(zx)-1 + pos = find(z>zx(ii) & z<=zx(ii+1)); + zy(ii) = length(pos); +end +figure; +loglog(zx(1:length(zy)),zy); +xlabel('weighted degree'); +ylabel('counts'); +axis equal + +xjview(cor2mni(coord, handles.M{1}), z); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get/select variable names in base workspace +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function vars = getVariable(titles) +vars = evalin('base','who'); +height = 0.07; +f = dialog('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.4 0.4], 'name', 'pick variables', 'NumberTitle','off'); +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', 'Available variables', ... + 'position',[0 0.9 0.5 0.1/2]); +variableListbox = uicontrol(f,'style','listbox','tag','variableListbox',... + 'unit','normalized',... + 'String', vars, ... + 'value',1,... + 'position',[0 0 0.5 0.9]); +okPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'OK', ... + 'position',[0.55 0.05 0.2 height],... + 'callback','uiresume'); +cancelPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'Cancel', ... + 'position',[0.75 0.05 0.2 height],... + 'callback','delete(gcf)'); + +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{1}, ... + 'position',[0.5 0.9 0.5 0.1/2]); +imageDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.8 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''imageDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); +imageDataEdit = uicontrol(f,'style','edit','tag','imageDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.8 0.3 height]); + +if length(titles)>=2 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{2}, ... + 'position',[0.5 0.7 0.5 0.1/2]); + eventDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.6 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''eventDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + eventDataEdit = uicontrol(f,'style','edit','tag','eventDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.6 0.3 height]); +end +if length(titles)>=3 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{3}, ... + 'position',[0.5 0.5 0.5 0.1/2]); + correlatorDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.4 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''correlatorDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + correlatorDataEdit = uicontrol(f,'style','edit','tag','correlatorDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.4 0.3 height]); +end +if length(titles)>=4 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{4}, ... + 'position',[0.5 0.3 0.5 0.1/2]); + otherDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.2 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''otherDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + otherDataEdit = uicontrol(f,'style','edit','tag','otherDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.2 0.3 height]); +end + +uiwait(f); +try + var{1} = get(imageDataEdit,'string'); + if length(titles)>=2 + var{2} = get(eventDataEdit,'string'); + end + if length(titles)>=3 + var{3} = get(correlatorDataEdit,'string'); + end + if length(titles)>=4 + var{4} = get(otherDataEdit,'string'); + end + vars = var; + delete(f); +catch + vars = {}; + try + delete(f); + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% quit xjview +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_quit(hObject, eventdata, warnstate) +warning(warnstate) +% try +% rmdir('xjviewtmp'); +% end +delete(gcf); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mouse double click +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function figureMouseUpFcn(hObject, eventdata) +status = get(hObject, 'SelectionType'); + +% double click +if strcmp(status, 'extend') + handles = guidata(hObject); + CallBack_loadImagePush(handles.loadImagePush, eventdata); +elseif strcmp(status, 'open') + handles = guidata(hObject); + CallBack_loadSPMmat(handles.loadImagePush, eventdata); +else + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change edit image file name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_imageFileEdit(hObject, eventdata) +handles = guidata(hObject); +filename = get(hObject, 'String'); +filename = str2cell(filename); +CallBack_loadImagePush(handles.loadImagePush, eventdata, filename); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_contrastListPush(hObject, eventdata) +handles = guidata(hObject); +connum = get(handles.contrastListPush,'Value'); +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); +if ~exist(spmfile) + set(handles.contrastListPush,'Value',0); +else + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + connames=get(handles.contrastListPush,'String'); + CallBack_loadImagePush(hObject,eventdata,fullfile(img.p, cons(connum).Vspm.fname), connum) +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadImagePush(hObject, eventdata, thisfilename, ContrastName) +handles = guidata(hObject); +handles.imageFileName=[]; handles.M=[]; handles.DIM=[]; handles.TF=[]; handles.df=[]; +handles.mni=[]; handles.intensity=[]; handles.currentmni=[]; handles.currentintensity=[]; handles.currentDisplayMNI=[]; handles.currentDisplayIntensity=[]; +if nargin>3 + handles.imageContrastName=ContrastName; +else + handles.imageContrastName=[]; +end +if ~exist('thisfilename') + thisfilename = ''; +end + +if isstruct(thisfilename) + handles.imageFileName = {''}; + handles.mni = {thisfilename.mni}; + handles.intensity = {thisfilename.intensity}; + handles.M = {thisfilename.M}; + handles.DIM = {thisfilename.DIM}; + handles.TF = {'S'}; + handles.df = {1e6}; + handles.pValue = 1; + set(handles.pValueEdit, 'string', '1'); + handles.clusterSizeThreshold = 0; + set(handles.clusterSizeThresholdEdit, 'String', '0'); + handles.imageContrastName={''}; +else + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); +end + +if isempty(handles.imageFileName) + return +end + +% tries to find first-level matching data +% knd +set(handles.indivResultsListPush(1),'String', ... + getfield2(dir(fileparts(fileparts(handles.imageFileName{1}))), 'name')); + +different = 0; % image files are same or different? +if length(handles.TF)>1 + for ii=1:length(handles.TF) + if strcmp(handles.TF{ii},handles.TF{1}) & isequal(handles.df{ii},handles.df{1}) & isequal(handles.M{ii},handles.M{1}) & isequal(handles.DIM{ii},handles.DIM{1}) + continue; + else + warndlg('Images are from different statistics or sources.', 'Warning'); + %set(handles.infoTextBox, 'string', 'Images are from different statistics or sources.'); + beep; + different = 1; + break; + end + end +end + +% reset files with empty df/TF to df=1 and TF='S'. 'S'=='T' but has a tag +% meaning it is changed. +resetTF = 0; +for ii=1:length(handles.TF) + if isempty(handles.TF{ii}) + handles.TF{ii} = 'S'; + resetTF = 1; + end + if isempty(handles.df{ii}) | isequal(handles.df{ii},0) + handles.df{ii} = 1e6; + resetTF = 1; + end +end + +handles.currentmni = handles.mni; +handles.currentintensity = handles.intensity; + +set(handles.dfEdit, 'String', cell2str(handles.df)); +set(handles.imageFileEdit, 'String', cell2str(handles.imageFileName)); % s=-log10(p) +maxs = maxcell(t2s(cellmax(handles.intensity,'abs'),handles.df, handles.TF),'abs'); +if isinf(maxs); maxs = 20; end +set(handles.slider, 'Max', maxs, 'Min', 0, 'sliderstep',[min(maxs/100,0.05),min(maxs/100,0.05)]); +if handles.TF{1}=='T' & different == 0 + str = [blanks(length(' intensit')) 'T=']; +elseif handles.TF{1}=='F' & different == 0 + str = [blanks(length(' intensit')) 'F=']; +else + str=' intensity='; +end +set(handles.intensityThresholdText, 'String', str); +set(handles.figure,'Name',['xjView: ' cell2str(handles.imageFileName)]); +try + for ii=1:length(handles.hLegend) + delete(handles.hLegend{ii}); + end +end +nimg=length(handles.TF); +if nimg>1 + colours = {'r';'g';'y';'c';'b';'m'}; + %colours = colours(mod(0:nimg-1,length(colours))+1); + %colours = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],100,1); + % read_conname = spm_input({'Retrieve contrasts names','Should I read SPM files to retrieve filenames?'},... + % 1,'bd',{'YES','NO'},[1,0]); + read_conname = 1; + for ii=1:nimg + [tmp,filename] = fileparts(handles.imageFileName{ii}); + c_names{ii} = filename ; + if read_conname & exist(fullfile(tmp, 'SPM.mat')) + tmp=load(fullfile(tmp, 'SPM.mat')); + tmp.Vspm=[tmp.SPM.xCon.Vspm]; + tmp.iCon=strmatch(filename, {tmp.Vspm.fname}); + if ~isempty(tmp.iCon) + c_names{ii} = [ [tmp.SPM.xCon(tmp.iCon).name] ' [' c_names{ii} ']']; + end + end + end + [tmp] = inputdlg({'colors' 'names'},'Loading',6,[{strvcat(c_names)};{strvcat(colours)}]); + colours = colorname2rgb(tmp{2}); + c_names = cellstr(tmp{1}); + + for ii=1:min(length(handles.TF),10) + filename = c_names{ii}; + if ii == 10; filename = '......'; end + pos0 = handles.sectionViewPosition; + pos(1) = pos0(1)+pos0(3)/2+0.03; + pos(2) = pos0(2)+ii/50-0.03; + pos(3) = 0.12; + pos(4) = 0.02; + handles.hLegend{ii}=uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',pos,... + 'string', filename,... + 'horizontal','left',... + 'fontweight','bold',... + 'ForeGroundColor',colours(ii,:)); + end + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; +end +guidata(hObject, handles); + +global M_; +global DIM_; +M_ = handles.M{1}; +DIM_ = handles.DIM{1}; + +if resetTF==1 + set(handles.pValueEdit,'string',1); +end +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% display info +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + report{1} = s; +catch + report{1} = 'Welcome to xjView 4'; +end +for jj=1:length(handles.imageFileName) + report{2+6*(jj-1)} = cell2str(handles.imageFileName(jj)); + if handles.TF{jj} == 'T' | handles.TF{jj} == 'F' + report{3+6*(jj-1)} = ['This is a ' handles.TF{jj} ' test image.']; + else + report{3+6*(jj-1)} = '';%['I don''t know what test this image came from.']; + end + report{4+6*(jj-1)} = 'mat = '; + report{5+6*(jj-1)} = num2str(handles.M{jj}); + report{6+6*(jj-1)} = 'dimension = '; + report{7+6*(jj-1)} = num2str(handles.DIM{jj}); +end +if length(handles.imageFileName)==1 + [img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); + spmfile=fullfile(img.p,'SPM.mat'); + if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); + end + end + if exist(spmfile) + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + for i=1:length(cons) + if not(isempty(cons(i).Vspm)) + consfilename{i}=cons(i).Vspm.fname; + else + consfilename{i}=''; + end + end + connum=strmatch([img.fname img.ext],consfilename); + if ~isempty(connum) + conlabel=cons(connum).name; + set(handles.figure,'Name',[get(handles.figure,'Name') ' :: ' conlabel]); + set(handles.contrastListPush,'String',{cons.name}) + set(handles.contrastListPush,'Value',connum) + set(handles.setContrastNameText,'String',[conlabel]); + report=[report(1:3) {['Contrast name in SPM.mat: (' num2str(connum) ') ' conlabel]} report(4:end)]; + else + set(handles.contrastListPush,'String',{'[none]'}) + set(handles.contrastListPush,'Value',0) + set(handles.contrastListPush,'Enable','on') + report=[report(1:3) {['Contrast has no matching name in SPM.mat']} report(4:end)]; + end + end +end +set(handles.infoTextBox, 'string', report); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pValueEdit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pValueEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +tmps = -log10(tmp); +if isnan(tmp) | tmp < 0 | tmp > 1 + errordlg('I don''t understand the input.','error'); + set(hObject, 'String', handles.pValue); + return +end + +if tmps>get(handles.slider,'max') | tmps maxcell(cellmax(handles.intensity,'abs')) + tmp = maxcell(cellmax(handles.intensity,'abs')); +end + +handles.pValue = t2p(tmp, handles.df{1}, handles.TF{1}); +handles.intensityThreshold = p2t(num2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); +set(handles.slider,'Value', -log10(handles.pValue)); +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +guidata(hObject, handles); +CallBack_slider(hObject, eventdata, -log10(handles.pValue)); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% slider bar +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_slider(hObject, eventdata, value) + +handles = guidata(hObject); + +if exist('value') + s = value; + if s > get(handles.slider,'max') + s = get(handles.slider,'max')*0.99; + end + if s < get(handles.slider,'min') + s = get(handles.slider,'min'); + end +else + s = get(hObject,'Value'); +end + +set(handles.slider, 'value', s); +pvalue = 10^(-s); +set(handles.pValueEdit,'String',num2str(pvalue)); +t = p2t(num2cell(pvalue*ones(1,length(handles.TF))), handles.df, handles.TF); +handles.intensityThreshold = t; +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +handles.pValue = pvalue; +for ii=1:length(handles.TF) + pos{ii} = find(abs(handles.intensity{ii})>=t{ii}); + handles.currentintensity{ii} = handles.intensity{ii}(pos{ii}); + handles.currentmni{ii} = handles.mni{ii}(pos{ii},:); +end + +guidata(hObject,handles); + +if get(handles.allIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.allIntensityRadio, eventdata); +elseif get(handles.positiveIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.positiveIntensityRadio, eventdata, '+'); +elseif get(handles.negativeIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.negativeIntensityRadio, eventdata, '-'); +end + +set(handles.infoTextBox, 'string', {'Don''t drag the slider bar too fast. Release your mouse button at least 1 second later.', ... + 'This sounds stupid. But there is a bug (probably MatLab bug) which I can''t fix right now.', ... + 'I suggest you confirm the correctness of the current display by press Enter in the pValue edit box.'}); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display intensity all+- radios +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allIntensityRadio(hObject, eventdata, pnall) +% pnall = '+', '-', or 'c'. c means current (simply update drawing) +% +handles = guidata(hObject); + +currentselect = []; +if get(handles.allIntensityRadio, 'Value'); currentselect = handles.allIntensityRadio; thispnall = 'a'; end +if get(handles.positiveIntensityRadio, 'Value'); currentselect = handles.positiveIntensityRadio; thispnall = '+'; end +if get(handles.negativeIntensityRadio, 'Value'); currentselect = handles.negativeIntensityRadio; thispnall = '-'; end + +set(handles.allIntensityRadio, 'Value', 0); +set(handles.positiveIntensityRadio, 'Value', 0); +set(handles.negativeIntensityRadio, 'Value', 0); + +if exist('pnall') + if pnall=='c' + hObject = currentselect; + pnall = thispnall; + end +end + +set(hObject, 'Value', 1); + +if ~isfield(handles,'currentintensity') + return +end +for ii=1:length(handles.TF) + if exist('pnall') + if pnall == '-' + pos{ii} = find(handles.currentintensity{ii} < 0); + elseif pnall == '+' + pos{ii} = find(handles.currentintensity{ii} > 0); + elseif pnall == 'a' + pos{ii} = 1:length(handles.currentintensity{ii}); + end + else + pos{ii} = 1:length(handles.currentintensity{ii}); + end + intensity{ii} = handles.currentintensity{ii}(pos{ii}); + mni{ii} = handles.currentmni{ii}(pos{ii},:); + cor{ii} = mni2cor(mni{ii}, handles.M{ii}); + + if ~isempty(cor{ii}) + A = spm_clusters(cor{ii}'); + pos0 = []; + for kk = 1:max(A) + jj = find(A == kk); + if length(jj) >= handles.clusterSizeThreshold; pos0 = [pos0 jj]; end + end + handles.currentDisplayMNI{ii} = mni{ii}(pos0,:); + handles.currentDisplayIntensity{ii} = intensity{ii}(pos0); + else + handles.currentDisplayMNI{ii} = mni{ii}([],:); + handles.currentDisplayIntensity{ii} = intensity{ii}([]); + end +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.contrastListPush,'String',regexprep(get(handles.contrastListPush,'String'),' \[Only [\+-a]\]$','')) +set(handles.setContrastNameText,'String',regexprep(get(handles.setContrastNameText,'String'),' \[Only [\+-a]\]$','')) + +if exist('pnall') + if ~isequal(pnall, 'a') + set(handles.setContrastNameText,'String',[get(handles.setContrastNameText,'String') ' [Only ' pnall ']']); + s=get(handles.contrastListPush,'String'); + s{get(handles.contrastListPush,'Value')}=[s{get(handles.contrastListPush,'Value')} ' [Only ' pnall ']']; + set(handles.contrastListPush,'String',s); + end +end + +if get(handles.allIntensityRadio, 'Value') & max(handles.currentDisplayIntensity{1}) < 0 + warndlg('No supra-threshold positive intensity. Only negative intensity is displayed.'); +end + +try + set(handles.figure,'currentaxes', handles.glassViewAxes); + xrange = xlim; + yrange = ylim; + try + delete(handles.hGlassText) + end + if ~isempty(handles.selectedCluster,1) + %handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + end +end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% render view check? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderViewCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% which section view target file? list box +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewListbox(hObject, eventdata) +handles = guidata(hObject); +contents = get(handles.sectionViewListbox,'String'); +currentsel = contents{get(handles.sectionViewListbox,'Value')}; +handles.sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get sectionviewtargetfile +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sectionViewTargetFile = getSectionViewTargetFile(spmdir, selectedcontent) +if findstr('SPM2',spm('ver')) + fileext = 'mnc'; +elseif findstr('SPM5',spm('ver')) + fileext = 'nii'; +end +currentsel = selectedcontent; +if ~isempty(strfind(currentsel, 'single')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['single_subj_T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152PD')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152PD.' fileext]); +elseif ~isempty(strfind(currentsel, '152T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152T2')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T2.' fileext]); +elseif ~isempty(strfind(currentsel, '305T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg305T1.' fileext]); +elseif strcmp(currentsel, 'ch2') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2.img'); +elseif strcmp(currentsel, 'ch2bet') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2bet.img'); +elseif strcmp(currentsel, 'aal') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'aal.img'); +elseif strcmp(currentsel, 'brodmann') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'brodmann.img'); + %knd: +elseif ~isempty(strfind(currentsel, 'gazemo')) + sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean-no120.img'); + %sectionViewTargetFile = fullfile('D:\ndiayek\data\gazemo\group\anat', 'mean-no120.img'); +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% xhairs in section view? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_xHairCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + spm_orthviews('Xhairs','off'); +else + spm_orthviews('Xhairs','on'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% other target file for section view, push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewMoreTargetPush(hObject, eventdata) +handles = guidata(hObject); +[filename, pathname, filterindex] = uigetfile('*', 'Pick an target file'); +if isequal(filename,0) | isequal(pathname,0) + return; +end +handles.sectionViewTargetFile = fullfile(pathname, filename); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% set colorbar range +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_setTRangeEdit(hObject, eventdata) +global TMAX_; +handles = guidata(hObject); +TMAX_ = get(hObject, 'String'); +if isempty(str2num(TMAX_)) && ~strcmp(TMAX_, 'auto') + return; +end +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change degree of freedome +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_dfEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2cell(get(hObject, 'String')); +if iscellstr(tmp) + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.df); + catch + set(hObject, 'String', ''); + end + return +end +handles.df=tmp; + + +if isfield(handles,'TF') + t = p2t(mat2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); + handles.intensityThreshold = t; + set(handles.intensityThresholdEdit, 'String', cell2str(t)); +end + +guidata(hObject, handles); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get structure push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_getStructurePush(hObject, eventdata) +handles = guidata(hObject); +xyz = spm_XYZreg('GetCoords',handles.hReg); +tmp_coor = cuixuFindTDstructure(xyz', handles.DB, 0); +set(handles.structureEdit,'String', tmp_coor{1}); +handles.currentxyz = xyz'; +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% structure edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_structureEdit(action, xyz, thisfun, hReg) + +try + handles=guidata(hReg); +catch + return; +end + +handles.currentxyz = xyz'; +guidata(hReg, handles); + +try + [tmp_coor, cellstructure] = cuixuFindTDstructure(xyz', handles.DB, 0); +catch + return; +end + +set(handles.structureEdit,'String', tmp_coor{1}); + +for ii=[5 3 2 1 4] + if strfind('Unidentified', cellstructure{ii}) + continue; + else + set(handles.searchContentEdit,'string', trimStructureStr(cellstructure{ii})); + set(handles.searchContentEdit,'UserData', 'auto'); + return; + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% trim str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = trimStructureStr(str) +pos = findstr('(', str); +if ~isempty(pos) + str(pos-1:end)=[]; +end +out = str; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cluster size threshold edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clusterSizeThresholdEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +if isnan(tmp) | tmp<0 + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.clusterSizeThreshold); + catch + set(hObject, 'String', '5'); + end + return +end +handles.clusterSizeThreshold=tmp; + +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImagePush(hObject, eventdata, thisfilename, isMask) +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}); + return; + end + end + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}); + return; + end +end + +[filename, pathname] = uiputfile('*.img', 'Save image file as', get(handles.saveImageFileEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + +if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName{1}) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity'), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}, isMask); + return; + end +end + +mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, '', isMask); + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImageFileEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveImagePush(handles.saveImagePush, eventdata, get(hObject,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSPush(hObject, eventdata, thisfilename) + +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + spm_print(handles.figure); + if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); + elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); + end + return; + end +end + +[filename, pathname] = uiputfile('*.ps', 'Save result as', get(handles.saveResultPSEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +% print +H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +pos = get(H,'position'); +index = []; + +for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 & pos{ii}(2) > 0.5 + set(H(ii),'position',[pos{ii}(1), pos{ii}(2), pos{ii}(3)*3/4, pos{ii}(4)]); + index = [index ii]; + end +end + + +spm_print(handles.figure); +if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); +elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); +end + +% set the position back +set(H(index), {'position'}, pos(index)); + + +% printstr = ['print -dpsc2 -painters -noui ' '''' thisfilename '''']; +% try +% orient portrait +% eval(printstr); +% printsuccess = 1; +% catch +% errordlg('Print to ps file failed', 'print error'); +% printsuccess = 0; +% end +%set(H,{'Units'},un); +% if strcmp(handles.system, 'linux') & printsuccess == 1 +% system(['ps2pdf ' '''' thisfilename '''']); +% end + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveResultPSPush(hObject, eventdata, get(handles.saveResultPSEdit,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% select a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_selectThisClusterPush(hObject, eventdata) +handles = guidata(hObject); + +try + xyz = handles.currentxyz'; +catch + xyz = spm_XYZreg('GetCoords',handles.hReg); +end + +try + handles.selectedCluster = [handles.selectedCluster; xyz']; +catch + handles.selectedCluster = xyz'; +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + delete(handles.hGlassText) +end +%handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% unselect a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clearSelectedClusterPush(hObject, eventdata) +handles = guidata(hObject); +try + handles = rmfield(handles,'selectedCluster'); +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + %delete(handles.hGlassText) + set(handles.infoTextBox, 'string', ['No clusters selected']); +end + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pick a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pickThisClusterPush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return; +end + +if ~isfield(handles, 'selectedCluster') | isempty(handles.selectedCluster) + try + xyz = handles.currentxyz'; + catch + xyz = spm_XYZreg('GetCoords',handles.hReg); + end + handles.selectedCluster = xyz'; +end + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); +xyzcor = mni2cor(handles.selectedCluster, handles.M{1}); + +pos = []; +for ii = 1:size(xyzcor,1) + pos0 = find(cor(:,1)==xyzcor(ii,1) & cor(:,2)==xyzcor(ii,2) & cor(:,3)==xyzcor(ii,3)); + if isempty(pos0) + continue; + end + pos = [pos find(A==A(pos0(1)))]; +end +if isempty(pos) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return +end + +pos = unique(pos); + +tmpmni = mni(pos,:); +tmpintensity = intensity(pos); + +[B,I,J] = unique(tmpmni, 'rows'); +handles.currentDisplayMNI = {B}; +fprintf('Cluster defined from: %s \n', handles.imageFileName{1}); +assignin('base', 'currentDisplayMNI', handles.currentDisplayMNI ); +handles.currentDisplayIntensity = {tmpintensity(I,:)}; + +handles.currentxyz = handles.selectedCluster(end,:); + +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; + +handles.selectedCluster = []; +try + delete(handles.hGlassText) +end + +guidata(hObject, handles); + +set(handles.thisClusterSizeEdit,'string', num2str(size(handles.currentDisplayMNI{1},1))); +str = get(handles.searchContentEdit, 'string'); +pos = findstr(' ', str); +str(pos) = []; +files = []; +for ii=1:length(handles.imageFileName) + [a,b,c] = fileparts(handles.imageFileName{ii}); + files = [files b]; +end +if ~isempty(files) + files = ['_from_' files]; +end + +set(handles.saveImageFileEdit, 'string', [str files '.img']); + +% list structure of voxels in this cluster +[a, b] = cuixuFindTDstructure(cell2mat(handles.currentDisplayMNI'), handles.DB, 0); +names = unique(b(:)); +index = NaN*zeros(length(b(:)),1); +for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; +end + +for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); +end +for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end +end +report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; +% format long +% disp(b) +% disp(report) +% format +report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; +for ii=2:size(report,1) + if strcmp('Unidentified', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; +end + +report2 = [report2, {'','select and Ctrl-C to copy'}]; +% f = figure('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.2 min(0.7,0.016*length(report2))], 'name', 'cluster information', 'NumberTitle','off'); +% hEdit = uicontrol(f,'style','edit',... +% 'unit','normalized','position',[0 0 1 1],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', report2,... +% 'max',2,'min',0); + +set(handles.infoTextBox, 'string', report2); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commonRegion push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_commonRegionPush(hObject, eventdata) +handles = guidata(hObject); +if ~isfield(handles,'TF') | length(handles.TF)<=1 + %msgbox('Two or more images need to be loaded to find the common region.', 'info'); + set(handles.infoTextBox, 'string', 'Two or more images need to be loaded to find the common region.'); + beep + return; +end + +common = handles.currentDisplayMNI{1}; +for ii=2:length(handles.TF) + common = intersect(common, handles.currentDisplayMNI{ii}, 'rows'); +end + +if isempty(common) + %msgbox('No common region found.', 'info'); + set(handles.infoTextBox, 'string', 'No common region found.'); + beep + return; +end + +tmpMNI = cell2mat(handles.currentDisplayMNI'); +tmpIntensity = cell2mat(handles.currentDisplayIntensity'); +intensity = zeros(size(common,1),1); + +for ii=1:size(common,1) + pos = find(abs(tmpMNI(:,1)-common(ii,1))<0.1 & abs(tmpMNI(:,2)-common(ii,2))<0.1 & abs(tmpMNI(:,3)-common(ii,3))<0.1); + intensity(ii) = prod(tmpIntensity(pos)); +end + +handles.currentDisplayMNI = {common}; +handles.currentDisplayIntensity = {intensity}; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% if isfield(handles,'hLegend') +% try +% set(cell2mat(handles.hLegend'),'visible',{'off'}); +% end +% end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_volumePush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; + + +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(intensity, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-intensity, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((intensity), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((intensity), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +elseif findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); +end + +spm_list('List',xSPM,handles.hReg); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_displayPush(hObject, eventdata) +handles = guidata(hObject); +spm_image('init', handles.imageFileName); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% all in one +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allinonePush(hObject, eventdata) +try + if findstr('SPM2',spm('ver')) + P = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P = spm_select(Inf,'image','Select image files'); + end + +catch + return; +end +if isempty(P) + return +end + +handles = guidata(hObject); +%if ~isfield(handles,'hReg') | ~isfield(handles,'hSection') | ~isfield(handles,'hcolorbar') +tmp = [0 0 0]; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(tmp([],:), [], hObject, handles); +%end + +colors=mycolourset; +for ii=1:size(P,1) + thisfilename = deblank(P(ii,:)); + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); + cor = mni2cor(handles.mni, handles.M); + spm_orthviews('addcolouredblobs',1,cor',handles.intensity',handles.M,colors(mod(ii,6)+1,:)); +end +spm_orthviews('Redraw'); + +guidata(hObject, handles); + +% contents = get(handles.sectionViewListbox,'String'); +% currentsel = contents{get(handles.sectionViewListbox,'Value')}; +% sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +% +% % spm_image('init', sectionViewTargetFile); +% % spm_image('addblobs'); +% % return + +% guidata(hObject, handles); +% load xSPM; +% VOL.XYZ = xSPM.XYZ; +% VOL.Z = xSPM.Z; +% VOL.M = handles.M; + +%addcolouredimage(handles.hSection, '333.img',[1 0 1]); +% uigetfiles +% nblobs = 4; +% for i=1:nblobs, +% %[SPM,VOL] = spm_getSPM; +% %c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); +% c = i; +% VOL.XYZ = ceil(rand(3,20)*20); +% VOL.Z = randn(1,20); +% VOL.M = handles.M; +% colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +% spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); +% end; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPush(hObject, eventdata) +handles = guidata(hObject); + +tobeoverlay = deblank(get(handles.overlayEdit, 'string')); + +if isempty(tobeoverlay) + return; +end + +tobeoverlay = str2cell(tobeoverlay, ' '); +if isnumeric(tobeoverlay{1}) + if length(tobeoverlay{1})>1 + errordlg(['Your input, ' deblank(get(handles.overlayEdit, 'string')) ', seems coincide with a matlab constant.'], 'error'); + return + end + for ii=1:length(tobeoverlay) + tobeoverlay{ii} = num2str(tobeoverlay{ii}); + end +end +fn = fieldnames(handles.wholeMaskMNIAll); +for ii=1:length(tobeoverlay) + pos{ii} = []; + for jj=1:length(fn) + x = []; + if ~isempty(str2num(tobeoverlay{ii})) + y = str2cell(fn{jj},'_'); + for kk=1:length(y) + x = isequal(tobeoverlay{ii}, y{kk}); + if x; break;end; + end + if x==0; x = []; end; + else + x = findstr(lower(tobeoverlay{ii}), lower(fn{jj})); + end + if ~isempty(x) + pos{ii} = [pos{ii} jj]; + end + end +end +common = pos{1}; +for ii=2:length(pos) + common = intersect(common, pos{ii}); +end + +if isempty(common) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return +end + +mask = []; +for ii=1:length(common) + eval(['mask = [mask; handles.wholeMaskMNIAll.' fn{common(ii)} '];']); +end + +if isempty(mask) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return; +end + +try + handles.mni; +catch + delete(gcf); + xjview(mask); + return; +end + +handles.imageFileName = [handles.imageFileName, {deblank(get(handles.overlayEdit, 'string'))}]; +handles.M = [handles.M, {handles.M{1}}]; +handles.DIM = [handles.DIM, {handles.DIM{1}}]; +handles.currentDisplayMNI = [handles.currentDisplayMNI, {mask}]; +m = max(abs(cell2mat(handles.currentDisplayIntensity'))); +if ~isempty(m) + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {-2*m*ones(size(mask,1),1)}]; +else + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {ones(size(mask,1),1)}]; +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_overlayPush(handles.overlayPush, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region popup +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPop(hObject, eventdata) +handles = guidata(hObject); +names = get(hObject, 'string'); +value = get(hObject, 'value'); +set(handles.overlayEdit, 'string', names{value}); +CallBack_overlayEdit(handles.overlayEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% search xBrain.org and other databases +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchPush(hObject, eventdata) + +try + handles = guidata(hObject); + searchContent = get(handles.searchContentEdit,'string'); + searchEngine = get(handles.searchEnginePop,'string'); + searchEngine = searchEngine{get(handles.searchEnginePop,'value')}; + + + xyz = str2num(searchContent); + searchMode=get(handles.searchContentEdit,'UserData'); + + switch searchMode + case 'auto'; + xyz = spm_XYZreg('GetCoords',handles.hReg); + handles.currentxyz = xyz'; + guidata(hObject, handles); + [a,b] = cuixuFindTDstructure(xyz', handles.DB, 0); + try + brodmann = strmatch('Brodmann',b) + brodmann = b{brodmann}; + brodmann = brodmann(1:end-4); + end; + try + region = b{3}; + region = region(1:end-4); + end + + case 'manual' + if isempty(xyz) + searchMode='text'; + elseif length(xyz)==3 + searchMode='xyz'; + end + end + + + switch searchEngine + case 'Brede' + switch searchMode + case 'auto' + searchString = sprintf(' %0.0f',xyz') + set(handles.searchContentEdit,'string',searchString); + case 'xyz' + searchString = num2str(xyz');%searchContent=sprintf('+%0.0f',searchContent) + case 'text' + end + urlstr = ['http://hendrix.imm.dtu.dk/cgi-bin/brede_loc_query.pl?q=' searchString ]; + case 'xBrain.org' + switch searchMode + case { 'auto' 'xyz'} + xbrainSearchField = 'mni or tal&mnidistance=20'; + searchString = sprintf(' %0.1f',xyz')% searchString = num2str(xyz'); + case 'text' + xbrainSearchField = 'region'; + searchString = searchContent; + end + set(handles.searchContentEdit,'string',searchString); + urlstr = ['http://people.hnl.bcm.tmc.edu/cuixu/cgi-bin/bmd/paper.pl?search_content=' searchString '&search_field=' xbrainSearchField]; + case 'Google Scholar' + if isequal(searchMode,'auto' ) + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22|',searchString{:}); + try + searchString = searchString(1:end-1); + end + %set(handles.searchContentEdit,'string',searchString); + end + urlstr = ['http://scholar.google.com/scholar?q=' searchString ]; + case 'Pubmed' + switch searchMode + case 'auto' + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22 OR ',searchString{:}); + try + searchString = searchString(1:end-4); + end + %searchString = brodmann; + case 'text' + searchString = searchContent; + end + % urlstr = ['http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=PureSearch&db=pubmed&details_term=(' searchString ')']; + urlstr = ['http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=search&db=pubmed&pubmedfilters=true&term=(' searchString ')']; + case 'Wikipedia' + if isequal(searchMode,'auto') + searchString = region; + end + urlstr = ['http://en.wikipedia.org/w/index.php?search=%22' searchString '%22']; + end + set(handles.searchContentEdit,'UserData',searchMode); +catch + urlstr = 'http://www.google.com'; +end + +try + web(urlstr,'-browser'); +catch + if exist('c:\program Files\mozilla Firefox\firefox.exe','file') + system(['"c:\program Files\mozilla Firefox\firefox.exe" "' urlstr '"']) + else + web(urlstr); + end +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% control panel on or off +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function controlHide(handles, status) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get multiple values from a string deliminated delim +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = str2cell(str, delim) +if ~exist('delim') + delim = '; '; +end + +[out{1},b] = strtok(str, delim); +ii = 2; +while ~isempty(b) + [out{ii},b] = strtok(b, delim); + ii = ii+1; +end + +for ii=1:length(out) + out2{ii} = str2num(out{ii}); + if isempty(out2{ii}) + return; + end +end + +for ii=1:length(out) + out{ii} = str2num(out{ii}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cell2str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function str = cell2str(acell, delim) +if ~exist('delim') + delim = ';'; +end + +str = []; + +if length(acell)==1 + if isstr(acell{1}) + str = acell{1}; + else + str = num2str(acell{1}); + end +else + for ii=1:length(acell) + if isstr(acell{ii}) + str = [str acell{ii}, delim ' ']; + else + str = [str num2str(acell{ii}), delim ' ']; + end + end + str(end-1:end)=[]; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cellmax, find max in each element, return a cell +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = cellmax(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end + +MAXX = []; +for ii=1:length(acell) + if strfind('abs',absolute) + MAXX = [MAXX max(abs(acell{ii}))]; + else + MAXX = [MAXX max(acell{ii})]; + end +end +MAXX = num2cell(MAXX); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% maxcell +%%% find max of all numbers in the whole cell, return a single value +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = maxcell(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end +MAXX = cellmax(acell, absolute); +MAXX = max(cell2mat(MAXX)); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% p2t +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = p2t(p, df, TF) +if ~iscell(p) + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = p2t(p{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% s2t, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = s2t(s, df, TF) + +if ~iscell(s) + p = 10^(-s); + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = s2t(s{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2p +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function p = t2p(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + end +else + for ii=1:length(t) + p{ii} = t2p(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2s, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = t2s(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + else + p = 0.1; + end + s = -log10(p); +else + for ii=1:length(t) + s{ii} = t2s(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2mask +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mask = mni2mask(coords, targetfilename, intensity, M, DIM, templateFile, isMask) +% function mask = mni2mask(coords, targetfilename, intensity, templateFile) +% make mask from coordinates +% +% coords: a Nx3 column of 3-d coordinates in MNI +% space +% targetfilename: (optional) the image files to be written +% intensity: (optional) Nx1, the values of each coordinate. +% M: rotation matrix +% DIM: dimension +% templateFile: (optional) the templateFile from which we can get the right +% dimensions. +% isMask: if this variable exist and equal to 1, then all non-zero +% intensities will be set to 1 +% +% Xu Cui +% 2004/11/18 + +if ~exist('intensity') + intensity = ones(size(coords,1),1); +end +thistemplateFile = ''; +if exist('templateFile') + if ~isempty(templateFile) + thistemplateFile = templateFile; + end +end + +if isempty(thistemplateFile) + V.mat = [... + -4 0 0 84; ... + 0 4 0 -116; ... + 0 0 4 -56; ... + 0 0 0 1]; + V.dim = [41 48 35 16]; + if exist('M') + V.mat = M; + end + if exist('DIM') + V.dim = DIM; + V.dim(4) = 16; + end + V.fname = targetfilename; + V.descrip = 'our own image'; +else + V = spm_vol(templateFile); + V.fname = targetfilename; + if isfield(V, 'descrip') + V.descrip = ['my image from ' V.descrip]; + else + V.descrip = 'my own image'; + end +end + +thisismask = 0; +if exist('isMask') + if isMask == 1 + thisismask = 1; + end +end +if thisismask + V.descrip = 'my mask'; + intensity = ones(size(intensity)); +end + +O = zeros(V.dim(1),V.dim(2),V.dim(3)); + +coords = mni2cor(coords,V.mat); + + +for ii=1:size(coords,1) + O(coords(ii,1),coords(ii,2),coords(ii,3)) = intensity(ii); +end + +if exist('targetfilename') + V = spm_write_vol(V,O); +end + +mask = O; + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get image file information +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [imageFile,M,DIM,TF,df,mni,intensity] = getImageFile(thisfilename) +% function imageFile = getImageFile(filename) +% get the information of this/these image file(s) +% +% thisfilename: (optional) if doesn't give file name, then show a open file +% dialog +% imageFile: the full name of the selected file (if user pressed cancel, +% imageFile == 0 +% M: M matrix (rotation matrix) +% DIM: dimension +% TF: t test or f test? 'T' or 'F' +% df: degree of freedome +% mni: mni coord +% intensity: intensity of each mni coord +% +% Note: The returned variables are cellarrays. +% +% Xu Cui +% last revised: 2005-05-03 + +if nargin < 1 | isempty(thisfilename) + if findstr('SPM2',spm('ver')) + P0 = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P0 = spm_select(Inf,'image','Select image files'); + end + + % try + % P0 = spm_get([0:100],'*IMAGE','Select image files'); + % catch + % P0 = []; + % [FileName,PathName] = uigetfile({'*.img';'*.IMG';'*.*'},'Select image files','MultiSelect','on'); + % if isstr(FileName) + % P0 = {fullfile(PathName, FileName)}; + % elseif iscellstr(FileName) + % for ii=1:length(FileName) + % P0{ii} = fullfile(PathName, FileName{ii}); + % end + % else + % P0 = []; + % end + % end + try + if isempty(P0) + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end + end + for ii=1:size(P0,1) + P{ii} = deblank(P0(ii,:)); + end +else + if isstr(thisfilename) + P = {thisfilename}; + elseif iscellstr(thisfilename) + P = thisfilename; + else + disp('Error: In getImageFile: I don''t understand the input.'); + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end +end + +global LEFTRIGHTFLIP_; + +for ii=1:length(P) + imageFile{ii} = P{ii}; + [cor{ii}, intensity{ii}, tmp{ii}, M{ii}, DIM{ii}, TF{ii}, df{ii}] = mask2coord(imageFile{ii}, 0); + if LEFTRIGHTFLIP_ == 1 + M{ii}(1,:) = -M{ii}(1,:); + end + mni{ii} = cor2mni(cor{ii}, M{ii}); +end + + + + + + + + + + + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuFindTDstructure +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% +% this function converts Talairach Daemon coordinate or MNI coordinate to a description of +% brain structure. +% +% pos: the coordinate (MNI or Talairach coordinate, defined by TALMNI) of the position in the brain, in mm +% DB: the database structure (see below for detailed explanation). If you don't input this argument, there +% should be a file called 'TDdatabase.mat' in the current directory +% TALMNI: 1 if pos is talairach coordinate, 0 if pos is MNI coordinate. 1 +% by default. +% +% onelinestructure: a one-line description of the returned brain +% structure +% cellarraystructure: a cell array of size 5, each cell contains a string +% describing the structure of the brain in a certain level. +% +% Example: +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48], DB, 1) +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48]) +% then +% onelinestructure = // Left Cerebrum // Frontal Lobe (L) // Middle Frontal Gyrus (L) // Gray Matter (L) // Brodmann area 8 (L) +% cellarraystructure = 'Left Cerebrum' 'Frontal Lobe (L)' [1x24 char] 'Gray Matter (L)' 'Brodmann area 8 (L)' +% +% Xu Cui +% 2004-6-28 +% + +%---------------------------------------------------------------------------------- +% DB strcture +%---------------------------------------------------------------------------------- +%------------------------------- +% Grid specification parameters: +%------------------------------- +% minX - min X (mm) +% maxX - max X (mm) +% voxX - voxel size (mm) in X direction +% minY - min Y (mm) +% maxY - max Y (mm) +% voxY - voxel size (mm) in Y direction +% minZ - min Z (mm) +% maxZ - max Z (mm) +% voxZ - voxel size (mm) in Z direction +% nVoxX - number of voxels in X direction +% nVoxY - number of voxels in Y direction +% nVoxZ - number of voxels in Z direction +%------------------------------- +% Classification parameters: +%------------------------------- +% numClass - number of classification types +% cNames - cNames{i} - cell array of class names for i-th CT +% numClassSize - numClassSize(i) - number of classes for i-th CT +% indUnidentified - indUnidentified(i) - index of "indUnidentified" class for i-th CT +% volClass - volClass{i}(j) - number of voxels in class j for i-th CT +% +% data - N x numClass matrix of referencies; let +% x y z coordinates in mm (on the grid) and +% nx = (x-minX)/voxX +% ny = (y-minY)/voxY +% nz = (z-minZ)/voxZ +% ind = nz*nVoxX*nVoxY + ny*nVoxX + nx + 1 +% data(ind, i) - index of the class for i-th CT in cNames{i} to +% which (x y z) belongs, i.e. +% cNames{i}{data(ind, i)} name of class for i-th CT +%---------------------------------------------------------------------------------- + +if nargin==1 + load('TDdatabase.mat'); + TALMNI = 1; +elseif nargin == 2 + TALMNI = 1; +end + +if(TALMNI == 1) + pos = tal2mni(pos); +elseif(TALMNI == 0) + []; +else + disp('TALMNI should be 1 or 0.'); +end + +pos(:,1) = DB.voxX*round(pos(:,1)/DB.voxX); +pos(:,2) = DB.voxY*round(pos(:,2)/DB.voxY); +pos(:,3) = DB.voxZ*round(pos(:,3)/DB.voxZ); + +min = []; +vox = []; +for(i=1:size(pos,1)) + min = [min; DB.minX DB.minY DB.minZ]; + vox = [vox; DB.voxX DB.voxY DB.voxZ]; +end +n_pos = (pos - min)./vox; + +nx = n_pos(:,1); +ny = n_pos(:,2); +nz = n_pos(:,3); +index = nz*DB.nVoxX*DB.nVoxY + ny*DB.nVoxX + nx + 1; +indMax = size(DB.data, 1); + +onelinestructuretmp = []; +onelinestructure = []; +for(j=1:size(pos,1)) + onelinestructuretmp = []; + for(i=1:DB.numClass) + + if (index(j) <= 0 | index(j) > indMax) + ind(j) = DB.indUnidentified(i); + else + ind(j) = DB.data(index(j), i); + end + + cellarraystructure{j,i} = DB.cNames{i}{ind(j)}; + onelinestructuretmp = [onelinestructuretmp ' // ' cellarraystructure{j,i}]; + end + onelinestructure{j} = onelinestructuretmp; +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mask2coord +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [cor, intensity, cor_singlecolumn,M,DIM,TF,df] = mask2coord(mask, checkdimension) +% [cor, intensity, cor_singlecolumn] = mask2coord(mask, checkdimension) +% +% This is to retrieve the coordinate of a mask file, or a matrix of 3-D +% +% mask: an image file or a matrix (3-D), with some of the elements are +% non-zeros +% checkdimension: check if the dimension is checkdimension, if not, return empty +% matrix +% cor: a N*3 matrix, which each row a coordinate in matrix +% intensity: a N*1 matrix, which encodes the intensity of each voxel. +% cor_singlecolumn: a N*1 matrix, each row is the index in the matrix +% M: rotation matrix +% DIM: dimension +% TF: t test or f test? 'T','F' or [] +% df: degree of freedome for T/F test +% +% Example: +% mask = zeros(4,3,2); +% mask(1,2,1) = 1; +% mask(3,2,2) = 1; +% mask2coord(mask) +% +% mask2coord('spmT_0002.img') +% mask2coord('spmT_0002.img',[41 48 35]) +% +% Xu Cui +% 2004-9-20 +% last revised: 2005-04-30 + +if nargin < 2 + checkdimension = 0; +end + +if ischar(mask) + V = spm_vol(mask); + mask = spm_read_vols(V); + M = V.mat; + DIM = V.dim; + TF = 'T'; + T_start = strfind(V.descrip,'SPM{T_[')+length('SPM{T_['); + if isempty(T_start); T_start = strfind(V.descrip,'SPM{F_[')+length('SPM{F_['); TF='F'; end + if isempty(T_start) + TF=[]; df=[]; + else + T_end = strfind(V.descrip,']}')-1; + df = str2num(V.descrip(T_start:T_end)); + end +else + M = []; + TF = []; + df = []; +end + +dim = size(mask); +if length(checkdimension)==3 + if dim(1)~= checkdimension(1) | dim(2)~= checkdimension(2) | dim(3)~= checkdimension(3) + y = []; + disp('dimension doesn''t match') + return + end +end + +pos = find(mask~=0); +intensity = mask(pos); + +y = zeros(length(pos),3); + +y(:,3) = ceil(pos/(dim(1)*dim(2))); +pos = pos - (y(:,3)-1)*(dim(1)*dim(2)); +y(:,2) = ceil(pos/dim(1)); +pos = pos - (y(:,2)-1)*(dim(1)); +y(:,1) = pos; + +cor = y; +cor_singlecolumn = pos; +DIM = dim; +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2cor +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function coordinate = mni2cor(mni, T) +% function coordinate = mni2cor(mni, T) +% convert mni coordinate to matrix coordinate +% +% mni: a Nx3 matrix of mni coordinate +% T: (optional) transform matrix +% coordinate is the returned coordinate in matrix +% +% caution: if T is not specified, we use: +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% + +if isempty(mni) + coordinate = []; + return; +end + +if ~exist('T') + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +coordinate = [mni(:,1) mni(:,2) mni(:,3) ones(size(mni,1),1)]*(inv(T))'; +coordinate(:,4) = []; +coordinate = round(coordinate); +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cor2mni +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mni = cor2mni(cor, T) +% function mni = cor2mni(cor, T) +% convert matrix coordinate to mni coordinate +% +% cor: an Nx3 matrix +% T: (optional) rotation matrix +% mni is the returned coordinate in mni space +% +% caution: if T is not given, the default T is +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% last revised: 2005-04-30 + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +cor = round(cor); +mni = T*[cor(:,1) cor(:,2) cor(:,3) ones(size(cor,1),1)]'; +mni = mni'; +mni(:,4) = []; +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% draw +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = Draw(mniCoord, intensity, hObject, handles) + +try + delete(handles.hcolorbar); +end +try + delete(handles.hReg); +end +try + delete(handles.hSection); +end +try + cla(handles.glassViewAxes); +end + +try + H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); + un = cellstr(get(H,'Units')); + pos = get(H,'position'); + + for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 + delete(H(ii)); + end + end +end + +sectionViewTargetFile = handles.sectionViewTargetFile; + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end + if max(intensity)*min(intensity) < 0 + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + else + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,abs(intensity),sectionViewTargetFile,hObject,handles); + end + + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end +else % multiple input? yes + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + + mniCoordtmp=[]; + intensitytmp=[]; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end + +end + +try + spm_XYZreg('SetCoords',handles.currentxyz',hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuSectionView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord, intensity, targetFile, hObject,handles) +% function h = cuixuSectionView(mniCoord, intensity) +% This is to project your coordinate to section view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% a special feature of this function is: it automatically seperate the +% negative and positive intensity and use hot and cold color to represent +% them. +% +% h: the returned handle for the axes +% +% SEE ALSO: cuixuView cuixuGlassView cuixuRenderView +% +% Xu Cui +% 2004/11/11 + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + multiple = 0; + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end +else + multiple = 1; + mniCoordtmp = []; + intensitytmp = []; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + % for multiple input + cSPM{ii}.XYZ = mni2cor(mniCoord{ii}, handles.M{ii}); + cSPM{ii}.XYZ = cSPM{ii}.XYZ'; + cSPM{ii}.Z = abs(intensity{ii}); + cSPM{ii}.M = handles.M{ii}; + cSPM{ii}.DIM = handles.DIM{ii}'; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; +end + +SPM.XYZ = mni2cor(mniCoord, handles.M); +SPM.XYZ = SPM.XYZ'; +SPM.Z = intensity; +SPM.M = handles.M; +SPM.DIM = handles.DIM'; + +%%%%%%%%%%%%%%% Reg %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +handles.colormap = colormap; + +coor = mniCoord; +xSPM = SPM; +xSPM.XYZmm = mniCoord'; +axes(handles.glassViewAxes) +WS = spm('WinScale'); +FS = spm('FontSizes'); + +Finter = gcf; +hReg = uicontrol(Finter,'Style','Frame','Position',[60 100 300 300].*WS,... + 'Visible','off'); +[hReg,xyz] = spm_XYZreg('InitReg',hReg,xSPM.M,xSPM.DIM,[0;0;0]); + +hFxyz = spm_results_ui('DrawXYZgui',xSPM.M,xSPM.DIM,xSPM,xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +hMIPax =gca ; +setcolormap('gray'); + +hMIPax = spm_mip_ui(xSPM.Z,coor',xSPM.M,xSPM.DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); + +colormap(handles.colormap); +setcolormap('gray-hot'); + +if isempty(handles.M) + spm_XYZreg('SetReg',handles.structureEdit,hReg); +else + set(handles.structureEdit, 'UserData', struct('hReg',hReg,'M',handles.M,'D', handles.DIM,'xyx',[0 0 0])); +end + +spm_XYZreg('Add2Reg',hReg,handles.structureEdit,@CallBack_structureEdit); + +%%%%%%%%%%%%%%% Reg end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if multiple == 0 + [hgraph, hSection, hcolorbar] = spm_sections(SPM,hReg,targetFile,handles.sectionViewPosition); +else + [hgraph, hSection, hcolorbar] = spm_sections(cSPM,hReg,targetFile,handles.sectionViewPosition); +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_sections +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [Fgraph, hMe, hcolorbar] = spm_sections(SPM,hReg,targetFile,sectionViewPosition) +% rendering of regional effects [SPM{Z}] on orthogonal sections +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = gcf; + +spms = fullfile(spm('dir'),'canonical', 'single_subj_T1.mnc'); +if exist('targetFile') + spms = targetFile; +end + +spm_orthviews('Reset'); +global st +st.fig = Fgraph; +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; + +spm_orthviews('Image',spms,sectionViewPosition); % position +spm_orthviews('MaxBB'); +spm_orthviews('register',hReg); +if ~iscell(SPM) + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +elseif length(SPM) == 1 + SPM = SPM{1}; + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +else + colors = mycolourset; + for ii=1:length(SPM) + spm_orthviews('addcolouredblobs',1,SPM{ii}.XYZ, SPM{ii}.Z, SPM{ii}.M, colors(ii,:)); + end +end +spm_orthviews('Redraw'); + +hMe = st.registry.hMe; +try + hcolorbar = st.vols{1}.blobs{1}.cbar; +catch + hcolorbar = 0; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuRenderView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function h = cuixuRenderView(mniCoord, intensity, varargin) +% function h = cuixuRenderView(mniCoord1, intensity1, mniCoord2, intensity2, mniCoord3, intensity3) +% This is to project your coordinate to render view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% You can input 1, 2, or 3 pairs of coordinates and intensity. +% +% h: the returned handle for the figure +% +% Xu Cui +% 2004/11/11 + +global M_; +global DIM_; + +if nargin < 3 + dat.XYZ = mni2cor(mniCoord, M_); + dat.XYZ = dat.XYZ'; + if nargin < 2 + dat.t = ones(size(mniCoord,1),1); + else + dat.t = intensity; + end + dat.mat = M_; + dat.dim = DIM_; +else + if mod(nargin,2) ~=0 + disp('You should put even number of parameters.') + return; + end + for ii=1:(2+length(varargin))/2 + if ii==1 + dat(ii).XYZ = mni2cor(mniCoord, M_); + dat(ii).t = intensity; + else + dat(ii).XYZ = mni2cor(varargin{2*(ii-1)-1}, M_); + dat(ii).t = varargin{2*(ii-1)}; + end + dat(ii).XYZ = dat(ii).XYZ'; + dat(ii).mat = M_; + dat(ii).dim = DIM_; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_render +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +h = spm_render(dat,1,fullfile(spm('dir'), 'rend', 'render_single_subj.mat')); +return + +function Fgraph = spm_render(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +% get surface +%----------------------------------------------------------------------- +if nargin < 3, + rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); +end; + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + + + +% Perform the rendering +%======================================================================= +spm('Pointer','Watch') + +load(rendfile); + +if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; +end; + +if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; +for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; +end; +if showbar, spm_progress_bar('Clear'); end; + +if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + +mx = zeros(length(rend),1)+eps; +mn = zeros(length(rend),1); + +for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; +end; + +mxmx = max(mx); +mnmn = min(mn); + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = gcf;%spm_figure('GetWin','Graphics'); +%spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +hght = 0.25; +width = 0.25; +x0 = 0.5; +y0 = 0.01; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 0.5, hght],'Visible','off'); +%ax=axes; +%image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow, width, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + X = cell(3,1); + for j=1:length(rend{i}.data), + X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + end + for j=(length(rend{i}.data)+1):3 + X{j}=zeros(size(X{1})); + end + + rgb = zeros([size(ren) 3]); + tmp = ren.*max(1-X{1}-X{2}-X{3},0); + rgb(:,:,1) = tmp + X{1}; + rgb(:,:,2) = tmp + X{2}; + rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + end; +end; + +spm('Pointer') +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_list +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function varargout = spm_list(varargin) +% Display and analysis of SPM{.} +% FORMAT TabDat = spm_list('List',SPM,hReg,[Num,Dis,Str]) +% Summary list of local maxima for entire volume of interest +% FORMAT TabDat = spm_list('ListCluster',SPM,hReg,[Num,Dis,Str]) +% List of local maxima for a single suprathreshold cluster +% +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x11 cell array) +% .fmt - fprintf format strings for table data (1x11 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (4x2 cell array) +% .dat - table data (Nx11 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%_______________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The currected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% +% Voxel-level - T/F = Statistic upon which the SPM is based +% - Ze = The eqivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qu = Expd(Prop of false positives among voxels >= Ze) +% - Pu = prob(Ze or higher at that voxel) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%_______________________________________________________________________ +% @(#)spm_list.m 2.43 Karl Friston, Andrew Holmes 02/10/31 + + +% satellite figure global variable +%----------------------------------------------------------------------- +global SatWindow + +%======================================================================= +switch lower(varargin{1}), case 'list' %-List + %======================================================================= + % FORMAT TabDat = spm_list('list',SPM,hReg) + + %-Tolerance for p-value underflow, when computing equivalent Z's + %----------------------------------------------------------------------- + tol = eps*10; + + %-Parse arguments and set maxima number and separation + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + + + %-Get current location (to highlight selected voxel in table) + %----------------------------------------------------------------------- + %xyzmm = spm_results_ui('GetCoords'); + xyzmm = [0 0 0]'; + + %-Extract data from xSPM + %----------------------------------------------------------------------- + S = varargin{2}.S; + R = varargin{2}.R; + FWHM = varargin{2}.FWHM; + VOX = varargin{2}.VOX; + n = varargin{2}.n; + STAT = varargin{2}.STAT; + df = varargin{2}.df; + u = varargin{2}.u; + M = varargin{2}.M; + v2r = 1/prod(FWHM(~isinf(FWHM))); %-voxels to resels + k = varargin{2}.k*v2r; + QPs = varargin{2}.Ps; % Needed for FDR + QPs = sort(QPs(:)); + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 3; + Dis = 8; + end + if length(varargin) > 5 + + Title = varargin{6}; + else + Title = 'p-values adjusted for search volume'; + end + + + %-Setup graphics panel + %----------------------------------------------------------------------- + spm('Pointer','Watch') + if SatWindow + Fgraph = SatWindow; + figure(Fgraph); + else + Fgraph = figure('unit','normalized','position',[0.5,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','off','MenuBar','none'); + Fgraph = gcf; + end + %spm_results_ui('Clear',Fgraph) + FS = spm('FontSizes'); %-Scaled font sizes + PF = spm_platform('fonts'); %-Font names (for this platform) + + + %-Table header & footer + %======================================================================= + + %-Table axes & Title + %---------------------------------------------------------------------- + if SatWindow, ht = 0.85; bot = .14; else, ht = 0.8; bot = 0.15; end; + + if STAT == 'P' + Title = 'Posterior Probabilities'; + end + + hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + + AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) + dy = FS(9); + y = floor(AxPos(4)) - dy; + + text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; + line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + + %-Construct table header + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + + Hc = []; + Hp = []; + h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; + h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; + h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; + h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; + text(0.22,y, 'cluster-level','FontSize',FS(9)); + line([0.15,0.41],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.16,y-9*dy/8, '\itp \rm_{corrected}'); Hp = [Hp,h]; + h = text(0.33,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.26,y-9*dy/8, '\itk \rm_E'); + + text(0.60,y, 'voxel-level','FontSize',FS(9)); + line([0.46,0.86],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.46,y-9*dy/8, '\itp \rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.55,y-9*dy/8, '\itp \rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.79,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.64,y-9*dy/8, sprintf('\\it%c',STAT)); + h = text(0.72,y-9*dy/8, '(\itZ\rm_\equiv)'); + + text(0.93,y - dy/2,['x,y,z \fontsize{',num2str(FS(8)),'}\{mm\}']); + + + %-Headers for text table... + %----------------------------------------------------------------------- + TabDat.tit = Title; + TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'voxel', 'p(FWE-cor)';... + 'voxel', 'p(FDR-cor)';... + 'voxel', STAT;... + 'voxel', 'equivZ';... + 'voxel', 'p(unc)';... + '', 'x,y,z {mm}'}';... + + TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Voxel + '%3.0f %3.0f %3.0f'}; %-XYZ + + %-Column Locations + %----------------------------------------------------------------------- + tCol = [ 0.00 0.07 ... %-Set + 0.16 0.26 0.34 ... %-Cluster + 0.46 0.55 0.62 0.71 0.80 ...%-Voxel + 0.92]; %-XYZ + + % move to next vertial postion marker + %----------------------------------------------------------------------- + y = y - 7*dy/4; + line([0 1],[y y],'LineWidth',1,'Color','r') + y = y - 5*dy/4; + y0 = y; + + + %-Table filtering note + %----------------------------------------------------------------------- + if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); + else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); + end + text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + + %-Volume, resels and smoothness (if classical inference) + %----------------------------------------------------------------------- + line([0 1],[0 0],'LineWidth',1,'Color','r') + if STAT ~= 'P' + %----------------------------------------------------------------------- + FWHMmm = FWHM.*VOX; % FWHM {mm} + Pz = spm_P(1,0,u,df,STAT,1,n,S); + Pu = spm_P(1,0,u,df,STAT,R,n,S); + Qu = spm_P_FDR(u,df,STAT,n,QPs); + [P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + + %-Footnote with SPM parameters + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) + TabDat.ftr = cell(5,2); + TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); + TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); + TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); + TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); + TabDat.ftr{5} = ... + sprintf('Expected false discovery rate, <= %0.2f',Qu); + TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); + TabDat.ftr{7} = ... + sprintf(['Smoothness FWHM = %0.1f %0.1f %0.1f {mm} ',... + ' = %0.1f %0.1f %0.1f {voxels}'],FWHMmm,FWHM); + TabDat.ftr{8} = ... + sprintf('Search vol: %0.0f cmm; %0.0f voxels; %0.1f resels',S*prod(VOX),S,R(end)); + TabDat.ftr{9} = ... + sprintf(['Voxel size: [%0.1f, %0.1f, %0.1f] mm ',... + ' (1 resel = %0.2f voxels)'],VOX,prod(FWHM)); + + text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu,Qu],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWHMmm,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + + end % Classical + + + %-Characterize excursion set in terms of maxima + % (sorted on Z values and grouped by regions) + %======================================================================= + if ~length(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,11); + varargout = {TabDat}; + spm('Pointer','Arrow') + return + end + + % Includes Darren Gitelman's code for working around + % spm_max for conjunctions with negative thresholds + %----------------------------------------------------------------------- + minz = abs(min(min(varargin{2}.Z))); + zscores = 1 + minz + varargin{2}.Z; + [N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); + Z = Z - minz - 1; + + %-Convert cluster sizes from voxels to resels + %----------------------------------------------------------------------- + if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); + else + V2R = v2r; + end + N = N.*V2R; + + %-Convert maxima locations from voxels to mm + %----------------------------------------------------------------------- + XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + + %-Table proper (& note all data in cell array) + %======================================================================= + + %-Pagination variables + %----------------------------------------------------------------------- + hPage = []; + set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + + %-Set-level p values {c} - do not display if reporting a single cluster + %----------------------------------------------------------------------- + c = max(A); %-Number of clusters + if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value + else + Pc = []; + set(Hp,'Visible','off') + end + + if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + else + set(Hc,'Visible','off') + end + + TabDat.dat = {Pc,c}; %-Table data + TabLin = 1; %-Table data line + + + %-Local maxima p-values & statistics + %----------------------------------------------------------------------- + HlistXYZ = []; + while prod(size(find(finite(Z)))) + + % Paginate if necessary + %--------------------------------------------------------------- + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %--------------------------------------------------------------- + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and voxel-level {u} p values for this cluster + %--------------------------------------------------------------- + Nv = N(i)/v2r; % extent {voxels} + + + if STAT ~= 'P' + Pz = spm_P(1,0, U,df,STAT,1,n,S);% uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S);% FWE-corrected {based on Z) + Qu = spm_P_FDR( U,df,STAT,n,QPs);% FDR-corrected {based on Z) + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S);% [un]corrected {based on k) + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum voxel-level p values {Z} + %--------------------------------------------------------------- + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %--------------------------------------------------------------------- + h = text(tCol(11),y,sprintf(TabDat.fmt{11},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %--------------------------------------------------------------- + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %----------------------------------------------- + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %----------------------------------------------- + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + if Pz < tol + Ze = Inf; + else, Ze = spm_invNcdf(1 - Pz); end + else + Pz = []; + Pu = []; + Qu = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %----------------------------------------------- + h = text(tCol(11),y,... + sprintf(TabDat.fmt{11},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) + end + + %-End: Store TabDat in UserData of axes & reset pointer + %======================================================================= + h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); + set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') + uimenu(h,'Label','Table') + uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + + %-Setup registry + %----------------------------------------------------------------------- + set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) + spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + + %-Return TabDat structure & reset pointer + %----------------------------------------------------------------------- + varargout = {TabDat}; + spm('Pointer','Arrow') + + + + + + %======================================================================= + case 'listcluster' %-List for current cluster only + %======================================================================= + % FORMAT TabDat = spm_list('listcluster',SPM,hReg) + + spm('Pointer','Watch') + + %-Parse arguments + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + SPM = varargin{2}; + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 32; + Dis = 4; + end + + + %-if there are suprathreshold voxels, filter out all but current cluster + %----------------------------------------------------------------------- + if length(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end + end + + %-Call 'list' functionality to produce table + %----------------------------------------------------------------------- + varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + + + + %======================================================================= + case 'txtlist' %-Print ASCII text table + %======================================================================= + % FORMAT spm_list('TxtList',TabDat,c) + + if nargin<2, error('Insufficient arguments'), end + if nargin<3, c=1; else, c=varargin{3}; end + TabDat = varargin{2}; + + %-Table Title + %----------------------------------------------------------------------- + fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) + fprintf('%c','='*ones(1,80)), fprintf('\n') + + %-Table header + %----------------------------------------------------------------------- + fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) + fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table data + %----------------------------------------------------------------------- + for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') + end + for i=1:max(1,11-size(TabDat.dat,1)), fprintf('\n'), end + fprintf('%s\n',TabDat.str) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table footer + %----------------------------------------------------------------------- + fprintf('%s\n',TabDat.ftr{:}) + fprintf('%c','='*ones(1,80)), fprintf('\n\n') + + + + %======================================================================= + case 'setcoords' %-Co-ordinate change + %======================================================================= + % FORMAT spm_list('SetCoords',xyz,hAx,hReg) + if nargin<3, error('Insufficient arguments'), end + hAx = varargin{3}; + xyz = varargin{2}; + UD = get(hAx,'UserData'); + HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + + %-Set all co-ord strings to black + %----------------------------------------------------------------------- + set(HlistXYZ,'Color','k') + + %-If co-ord matches a string, highlight it in red + %----------------------------------------------------------------------- + XYZ = get(HlistXYZ,'UserData'); + if iscell(XYZ), XYZ = cat(2,XYZ{:}); end + [null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); + if d=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + cm_pos; + end; + varargout{1} = H; + st.centre = mean(maxbb); + redraw_all + + case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + + case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + + case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3 + h = valid_handles(st.snap); + if ~isempty(h) + tmp=st.vols{h(1)}.mat*... + round(inv(st.vols{h(1)}.mat)*[tmp; ... + 1]); + end; + st.centre = tmp(1:3); + end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + cm_pos; + + case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + cm_pos; + + case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + bbox; + redraw_all; + else, + space(varargin{1}); + bbox; + redraw_all; + end; + + case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + + case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + + case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + + case 'delete', + my_delete(varargin{1}); + + case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + + case 'reset', + my_reset; + + case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + + case 'interp', + st.hld = varargin{1}; + redraw_all; + + case 'xhairs', + xhairs(varargin{1}); + + case 'register', + register(varargin{1}); + + case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + + case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + + case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + + case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + + case 'addtruecolourimage', + % spm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_select(1, 'image', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + + case 'addcolourbar', + addcolourbar(varargin{1}, varargin{2}); + + case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + + case 'addcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + addcontexts(handles); + + case 'rmcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + rmcontexts(handles); + + case 'context_menu', + c_menu(varargin{:}); + + case 'valid_handles', + if nargin == 1 + handles = 1:24; + else, + handles = varargin{1}; + end; + varargout{1} = valid_handles(handles); + + otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +global TMAX_ +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + mx = max([eps max(t)]); + mn = min([0 min(t)]); + if ~strcmp(TMAX_, 'auto') + mx = str2num(TMAX_); + end + %KND: + if numel(mx)==2 + mn=mx(1); + mx=mx(2); + end + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx, 'min',mn); + addcolourbar(handle,1); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx,'min',mn); + addcolourbar(handle,1); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx, ... + 'min',mn,'colour',c); + addcolourbar(handle,bset); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolourbar(vh,bh) +global st +if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); +else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); +end; +st.vols{vh}.blobs{bh}.cbar = axes('Parent',st.fig,... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on', 'YDir','normal', 'XTickLabel',[], 'XTick',[]); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'spm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['spm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''Reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +V.mapping = 'linear'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +spm_orthviews('reposition',spm_orthviews('pos')); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['spm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(finite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(finite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(finite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(finite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + imgc = max(imgc,mn); imgc = min(imgc,mx); + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(finite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgc), + tmp = imgc(finite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgs), + tmp = imgs(finite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(finite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(finite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(finite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpc(tmpc(:)>mx) = mx; + tmps(tmps(:)>mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpc = (tmpc-mn)/(mx-mn); + tmps = (tmps-mn)/(mx-mn); + tmpt(~finite(tmpt)) = 0; + tmpc(~finite(tmpc)) = 0; + tmps(~finite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_colourbar(vh,bh,interval,cdata) +global st +if isfield(st.vols{vh}.blobs{bh},'cbar') + if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); + end; + % only scale cdata if we have out-of-range truecolour values + if ndims(cdata)==3 && max(cdata(:))>1 + cdata=cdata./max(cdata(:)); + end; + image([0 1],interval,cdata,'Parent',st.vols{vh}.blobs{bh}.cbar); + set(st.vols{vh}.blobs{bh}.cbar, ... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1)... + (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'YDir','normal','XTickLabel',[],'XTick',[]); +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = []; %[ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[],'snap',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'spm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('spm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e v] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~finite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item00 = uimenu(item_parent, 'Label','unknown image', 'Separator','on'); +spm_orthviews('context_menu','image_info',item00,volhandle); +item0a = uimenu(item_parent, 'UserData','pos_mm', 'Callback','spm_orthviews(''context_menu'',''repos_mm'');','Separator','on'); +item0b = uimenu(item_parent, 'UserData','pos_vx', 'Callback','spm_orthviews(''context_menu'',''repos_vx'');'); +item0c = uimenu(item_parent, 'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','spm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +checked={'off','off'}; +checked{st.xhairs+1} = 'on'; +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''on'');','Checked',checked{2}); +item2_2 = uimenu(item2, 'Label','off', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''off'');','Checked',checked{1}); + +%contextsubmenu 3 +if st.Space == eye(4) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','spm_orthviews(''context_menu'',''orientation'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Voxel space (1st image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Voxel space (this image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',1);','Checked','off'); + +%contextsubmenu 3 +if isempty(st.snap) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Snap to Grid'); +item3_1 = uimenu(item3, 'Label','Don''t snap', 'Callback','spm_orthviews(''context_menu'',''snap'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Snap to 1st image', 'Callback','spm_orthviews(''context_menu'',''snap'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Snap to this image', 'Callback','spm_orthviews(''context_menu'',''snap'',1);','Checked','off'); + +%contextsubmenu 4 +if st.hld == 0, + checked = {'off', 'off', 'on'}; +elseif st.hld > 0, + checked = {'off', 'on', 'off'}; +else, + checked = {'on', 'off', 'off'}; +end; +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','spm_orthviews(''context_menu'',''interpolation'',3);', 'Checked',checked{3}); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','spm_orthviews(''context_menu'',''interpolation'',2);','Checked',checked{2}); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','spm_orthviews(''context_menu'',''interpolation'',1);','Checked',checked{1}); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','spm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window_gl'',1);'); +if license('test','image_toolbox') == 1 + offon = {'off', 'on'}; + checked = offon(strcmp(st.vols{volhandle}.mapping, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'})+1); + item6_2 = uimenu(item6, 'Label','Intensity mapping'); + item6_2_1 = uimenu(item6_2, 'Label','local'); + item6_2_1_1 = uimenu(item6_2_1, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''linear'');'); + item6_2_1_2 = uimenu(item6_2_1, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''histeq'');'); + item6_2_1_3 = uimenu(item6_2_1, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''loghisteq'');'); + item6_2_1_4 = uimenu(item6_2_1, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''quadhisteq'');'); + item6_2_2 = uimenu(item6_2, 'Label','global'); + item6_2_2_1 = uimenu(item6_2_2, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''linear'');'); + item6_2_2_2 = uimenu(item6_2_2, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''histeq'');'); + item6_2_2_3 = uimenu(item6_2_2, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''loghisteq'');'); + item6_2_2_4 = uimenu(item6_2_2, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''quadhisteq'');'); +end; +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add image'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_image'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_image'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored blobs','Separator','on'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_4 = uimenu(item7, 'Label','Add colored image'); +item7_4_1 = uimenu(item7_4, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_4_2 = uimenu(item7_4, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_5 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_6 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_6_1 = uimenu(item7_6, 'Label','local', 'Visible','on'); +item7_6_2 = uimenu(item7_6, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), + case 'image_info', + if nargin <3, + current_handle = get_current_handle; + else + current_handle = varargin{3}; + end; + if isfield(st.vols{current_handle},'fname'), + [p,n,e,v] = spm_fileparts(st.vols{current_handle}.fname); + if isfield(st.vols{current_handle},'n') + v = sprintf(',%d',st.vols{current_handle}.n); + end; + set(varargin{2}, 'Label',[n e v]); + end; + delete(get(varargin{2},'children')); + if exist('p','var') + item1 = uimenu(varargin{2}, 'Label', p); + end; + if isfield(st.vols{current_handle},'descrip'), + item2 = uimenu(varargin{2}, 'Label',... + st.vols{current_handle}.descrip); + end; + dt = st.vols{current_handle}.dt(1); + item3 = uimenu(varargin{2}, 'Label', sprintf('Data type: %s', spm_type(dt))); + str = 'Intensity: varied'; + if size(st.vols{current_handle}.pinfo,2) == 1, + if st.vols{current_handle}.pinfo(2), + str = sprintf('Intensity: Y = %g X + %g',... + st.vols{current_handle}.pinfo(1:2)'); + else, + str = sprintf('Intensity: Y = %g X', st.vols{current_handle}.pinfo(1)'); + end; + end; + item4 = uimenu(varargin{2}, 'Label',str); + item5 = uimenu(varargin{2}, 'Label', 'Image dims', 'Separator','on'); + item51 = uimenu(varargin{2}, 'Label',... + sprintf('%dx%dx%d', st.vols{current_handle}.dim(1:3))); + prms = spm_imatrix(st.vols{current_handle}.mat); + item6 = uimenu(varargin{2}, 'Label','Voxel size', 'Separator','on'); + item61 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', prms(7:9))); + item7 = uimenu(varargin{2}, 'Label','Origin', 'Separator','on'); + item71 = uimenu(varargin{2}, 'Label',... + sprintf('%.2f %.2f %.2f', prms(1:3))); + R = spm_matrix([0 0 0 prms(4:6)]); + item8 = uimenu(varargin{2}, 'Label','Rotations', 'Separator','on'); + item81 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(1,1:3))); + item82 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(2,1:3))); + item83 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(3,1:3))); + item9 = uimenu(varargin{2},... + 'Label','Specify other image...',... + 'Callback','spm_orthviews(''context_menu'',''swap_img'');',... + 'Separator','on'); + + case 'repos_mm', + oldpos_mm = spm_orthviews('pos'); + newpos_mm = spm_input('New Position (mm)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_mm),3); + spm_orthviews('reposition',newpos_mm); + + case 'repos_vx' + current_handle = get_current_handle; + oldpos_vx = spm_orthviews('pos', current_handle); + newpos_vx = spm_input('New Position (voxels)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_vx),3); + newpos_mm = st.vols{current_handle}.mat*[newpos_vx;1]; + spm_orthviews('reposition',newpos_mm(1:3)); + + case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + + case 'xhair', + spm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + + case 'orientation', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + spm_orthviews('Space'); + elseif varargin{2} == 2, + spm_orthviews('Space',1); + else, + spm_orthviews('Space',get_current_handle); + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Orientation'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'snap', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + st.snap = []; + elseif varargin{2} == 2, + st.snap = 1; + else, + st.snap = get_current_handle; + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Snap to Grid'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + + case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + spm_orthviews('window',current_handle); + else + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%.2f %.2f', st.vols{current_handle}.window); + else + defstr = ''; + end; + spm_orthviews('window',current_handle,spm_input('Range','+1','e',defstr,2)); + end; + + case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + current_handle = get_current_handle; + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%d %d', st.vols{current_handle}.window); + else + defstr = ''; + end; + data = spm_input('Range','+1','e',defstr,2); + + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + + case 'mapping', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', ... + 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + current_handle = get_current_handle; + cm_handles = get_cm_handles; + st.vols{current_handle}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(current_handle), ... + 'label','Intensity mapping'),'Children'); + for k = 1:numel(z_handle) + c_handle = get(z_handle(k), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + redraw_all; + + case 'mapping_gl', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + cm_handles = get_cm_handles; + for k = valid_handles(1:24), + st.vols{k}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(k), ... + 'label','Intensity mapping'),'Children'); + for l = 1:numel(z_handle) + c_handle = get(z_handle(l), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + end; + redraw_all; + + case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_select(1,'image','select new image')); + fn = fieldnames(new_info); + for k=1:numel(fn) + st.vols{current_handle}.(fn{k}) = new_info.(fn{k}); + end; + spm_orthviews('context_menu','image_info',get(gcbo, 'parent')); + redraw_all; + + case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + + case 'add_image', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + for i = 1:length(cm_handles), + addimage(cm_handles(i),fname); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Green blobs|Yellow blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;0 1 0;1 1 0;0 0 1;0 1 1;1 0 1]; + c_names = {'red';'green';'yellow';'blue';'cyan';'magenta'}; + hlabel = sprintf('%s (%s)',VOL.title,c_names{c}); + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + + case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + if isfield(st.vols{cm_handles(i)}.blobs{j},'cbar') + delete(st.vols{cm_handles(i)}.blobs{j}.cbar); + end + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + + case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',fname,c_names{c}); + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% ROI: TimeSeries +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchContentEdit(hObject, eventdata) +handles = guidata(hObject); +set(handles.searchContentEdit,'UserData', 'manual'); + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load SPM file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadSPMmat(hObject, eventdata, spmfile) +handles = guidata(hObject); +if nargin < 3 | isempty(spmfile) + %if exist(fullfile(pwd,'SPM.mat'), 'file') + if findstr('SPM2',spm('ver')) + spmfile = spm_get([1],'SPM.mat','Select a SPM file'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select(1,'SPM.mat','Select a SPM file'); + end +end +xSPM=load(spmfile); +if isfield(xSPM.SPM, 'xCon') + numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', 2);%length(xSPM.SPM.xCon)); + if ~exist(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)) & ... + exist(subarray(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname),1:2,-2)) + warning('Changing path') + xSPM.SPM.swd=xSPM.SPM.swd(3:end); + end + if ~isempty(numc) + if exist(xSPM.SPM.swd, 'dir') + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + else + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(fileparts(spmfile),xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + end + end +else + msgbox('No contrast in this file') +end +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_indivResultsListPush(hObject, eventdata) +handles = guidata(hObject); +if ischar(handles.imageFileName) + handles.imageFileName={handles.imageFileName}; +end +[datadir,condir]=fileparts(handles.imageFileName{1}); + +%MG 15.09.2008 if datadir(2)==':' +% datadir=datadir(3:end); +% end +%--MG +[datadir,subdir]=fileparts(datadir); +if isempty(findstr('indiv/', datadir)) +elseif isempty(findstr('rfx/', datadir)) + xSPM=load(fullfile(datadir,'SPM.mat')); + indivdir=xSPM.xY.P; +else + return +end + +req = get(handles.indivResultsListPush,'String'); +req = req{get(handles.indivResultsListPush, 'value')}; + +if isequal(req,'Group') + datadir=fileparts(datadir); + condir=handles.imageContrastName{1}; + condir=strrep(condir, '>', 'vs'); + condir=strrep(condir, '<', 'vs'); + condir=strrep(condir, '+', '_'); + condir=strrep(condir, ':', ' at'); + condir=deblank(condir); + condir=fullfile(datadir,'rfx',condir); + if ~exist(condir,'dir') + return + end + xSPM=load(fullfile(condir,'SPM.mat')); + numc=2; + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(datadir,req,xSPM.SPM.xCon(numc).Vspm.fname)},...%MG:02.04.2008{fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + return +elseif exist('swds','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + swds(get(gcbo, 'value'),:),... + handles.imageContrastName); +else + + %MG 15.09.2008 + if strmatch('.',req,'exact')>0 + return + elseif strmatch('..', req,'exact')>0 + newdir=spm_select(1,'dir','...Select directory containing the new SPM.mat!',''); newdir=fileparts(newdir) + eval(['cd ' newdir]) + xSPM=load(spm_select('List',newdir,'SPM.mat')) + [newdatadir,newreq]=fileparts(newdir); + datadir=newdatadir; + req=newreq; + newnumc=length(xSPM.SPM.xCon); + numc=newnumc; + elseif strmatch('GROUP',req)>0 + newdir=spm_select(1,'dir','...Select directory containing the new SPM.mat!',''); newdir=fileparts(newdir) + eval(['cd ' newdir]) + xSPM=load(spm_select('List',newdir,'SPM.mat')) + [newdatadir,newreq]=fileparts(newdir); + datadir=newdatadir; + req=newreq; + newnumc=length(xSPM.SPM.xCon); + numc=newnumc; + +% xSPM=load(spm_select(1,'any','select SPM.mat!','',datadir,'SPM.mat')) +% [newdatadir,newreq]=fileparts(xSPM.SPM.swd); +% datadir=newdatadir; +% req=newreq; +% newnumc=length(xSPM.SPM.xCon); +% numc=newnumc; +% cd([datadir '\' req]) + else + cd([datadir '\' req]) + xSPM=load(fullfile(datadir,req,'SPM.mat')); + end + %--MG + + if ~isfield(handles,'imageContrastName') + return + end + % numc=strmatch(handles.imageContrastName{1},{xSPM.SPM.xCon.name},'exact'); + [datadir1,req1]=fileparts(datadir); + if strfind('GROUP',req1)>0 + numc=2; + else + numc=get(handles.contrastListPush, 'Value'); + end + %%MG 02.04.2008 filename=fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname); + filename=fullfile(datadir,req,xSPM.SPM.xCon(numc).Vspm.fname) + %--MG + + if filename(2)==':' + filename=filename(3:end); + end + set(handles.sectionViewListbox, 'Value', [1]); + % handles.sectionViewTargetFile = fullfile('\ndiayek\data\gazemo\rawdata\',req,'anat','wf_0001.img'); + guidata(hObject, handles); + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + {xSPM.SPM.xCon(numc).name}); + +% CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end + +%% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_paramestRegionPush(hObject, eventdata, roi,readdata) +if nargin<4 + readdata=1; +end +roi=struct('type', roi); +handles = guidata(hObject); +roi.name=get(handles.structureEdit, 'String'); + +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); + +if exist(spmfile(3:end), 'file') + warning('Possible disk swapping in xjview.m'); + spmfile=spmfile(3:end); +end +if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the RFX SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the RFX SPM.mat'); + end +end +if ~exist(spmfile) + return +end +xSPM=load(spmfile, 'SPM'); + + +[glmpath, glmpath]=fileparts(fileparts(fileparts(xSPM.SPM.swd))); + +%[xyzmm,i] = spm_XYZreg('NearestXYZ',... +% spm_results_ui('GetCoords'),handles.currentxyz); +%spm_results_ui('SetCoords',xSPM.XYZmm(:,i)); +switch roi.type + case 'vox' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + xyz = handles.currentxyz; + case 'clu' + if not(isfield(handles,'selectedCluster')) | not(isempty(handles.selectedCluster)) + switch questdlg('Load from workspace','cluster?', 'currentDisplayMNI{1}','...','Cancel','currentDisplayMNI{1}') + case 'currentDisplayMNI{1}' + xyz=evalin('base', 'currentDisplayMNI{1}'); + case '...' + case 'Cancel' + return + end + delete(findobj('Tag', 'paramest')) + + else + delete(findobj('Tag', 'paramest')) + xyz =handles.currentDisplayMNI{1}; + end + case 'sph' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + delete(findobj('Tag', 'paramest')) + xyz = handles.currentxyz; + roi.radius=inputdlg('Radius of the sphere?'); + if isempty(roi.radius) + return + end + roi.radius=str2num(roi.radius{1}) + % XYZmm = xSPM.SPM.xVol.M(1:3,:)*[xSPM.SPM.xVol.XYZ; ones(1,size(xSPM.SPM.xVol.XYZ,2))]; + % xyz = sqrt( XYZmm-repmat(xyz,[1 size(XYZmm,2)]) ) + % xyz = XYZmm(:, xyz < roi.radius) + +end +% handles.currentDisplayMNI{1} +% ha=axes('Tag', 'paramest', 'Parent',gcf,'units','normalized','Position',[0.55, 0.05, 0.4, 0.4]); +if isequal(roi.type, 'sph') + if roi.radius > 20 + if not(spm_input({'Many many voxels may be retrieve','Radius of the sphere (in mm):',... + num2str(roi.radius),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end + end + +end +if size(xyz,1)>20 + if not(spm_input({'Many many voxels to retrieve','Number of voxel:',... + num2str(size(xyz,1)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end +end + +allbetas= []; +allxyz = []; +roi.nvox = []; +hwait = waitbar(0,'Reading 1st level data'); +lcd=cd; +handles.currentxyz +if isfield(handles, 'paramest') + handles.paramest=[]; +end + +roi.stat.TF=handles.TF; +roi.stat.pValue=handles.pValue; +roi.stat.df=handles.df; +% roi.stat.Intensity = +% handles.currentDisplayIntensity{1}(find(all(handles.currentDisplayMNI{1}==repmat(handles.currentxyz, 3,1),2))); +[i,j]=ismember(handles.mni{1}, flipud(xyz), 'rows'); +roi.stat.intensity(j(i)) = handles.intensity{1}(i); + +if isstruct(xSPM.SPM.xX.K) | ~readdata + n=1; + % Ic=strmatch('F Task',{xSPM.SPM.xCon.name}) + % + % allbetas=[] + % vcon= + % XYZ = SPM.xVol.XYZ; + % XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + % tmpallbetas= []; + % [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + % allbetas = [allbetas;(mean(tmpallbetas,1))]; + % allxyz= [allxyz;mean(tmpallxyz,1)]; + +else + n= length(xSPM.SPM.xY.P) +end + +for sub = 1:n + + waitbar(sub/n,hwait); + if n>1 + subdir = fileparts(xSPM.SPM.xY.P{sub}); + else + subdir = xSPM.SPM.swd; + end + try + if ~exist(fullfile(subdir, 'SPM.mat'), 'file') & ... + exist(subarray(fullfile(subdir, 'SPM.mat'),1:2,-2),'file') + subdir = subdir(3:end); + end + load(fullfile(subdir, 'SPM.mat')); + fprintf('Retrieving betas from: %s\n', fullfile(subdir, 'SPM.mat')) + + if sub==1 + % [cn.path cn.fname cn.ext]=fileparts(char(xSPM.SPM.xY.P(sub,:))); + % consfiles=[SPM.xCon.Vcon]; + Ic = [strmatch('f anim', lower({SPM.xCon.name})) strmatch('f task', lower({SPM.xCon.name})) strmatch('f map', lower({SPM.xCon.name}))]; + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name},'InitialValue',Ic); + end + Ic=Ic(end); + conname=SPM.xCon(Ic).name; + end + + %------- + Ic = strmatch(conname,{SPM.xCon.name}, 'exact') ; %contrast number + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name}); + end + %------- + + XYZ = SPM.xVol.XYZ; + XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + tmpallbetas= []; + tmpallxyz = []; + cd(subdir) + for cluvox = 1:size(xyz,1) + switch (roi.type) + case 'sph' + [d] = spm_XYZreg('Edist',xyz(cluvox,:),XYZmm); + i=find(d<=roi.radius); + govox = ~isempty(i); + nxyz=XYZmm(:,i); + case {'vox', 'clu'} + govox = 1; + [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=sqrt(3) %one voxel in each dimZ + govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',... + num2str(xyz(cluvox,:)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0]); + end + end + if govox==1 + vXYZ = XYZ(:,i) ; % coordinates in voxels + %-Get parameter and hyperparameter estimates + %======================================================================= + beta = spm_get_data(SPM.Vbeta, vXYZ); + % ResMS = spm_get_data(SPM.VResMS,vXYZ); + % Bcov = ResMS*SPM.xX.Bcov; + CI = 1.6449; % = spm_invNcdf(1 - 0.05); + % compute contrast of parameter estimates and 90% C.I. + %-------------------------------------------------------------- + tmpallbetas = [tmpallbetas; (SPM.xCon(Ic).c'*beta)']; + tmpallxyz = [tmpallxyz; nxyz']; + end + end + allbetas = [allbetas;(mean(tmpallbetas,1))]; + allxyz= [allxyz;mean(tmpallxyz,1)]; + roi.nvox = [ roi.nvox; size(tmpallbetas,1)]; + tmp = mean(tmpallxyz); + % disp(['meancluster = ' num2str(mean(tmpallxyz,1))]); + catch + warning('Error with data from: %s', subdir) + end +end +close(hwait) +cd(lcd); +% +regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c )),'*bf(1)', '')'), 1:6, -2)); +regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c')),'*bf(1)', '')'), 1:6, -2)); +[regnames, ireg,ireg2]=unique(regnames); +a=[ repmat(' ',length(regnames),1) strvcat(strrep(regnames, '_', ' '))]; +a=dataread('string',a', '%s'); +leg=a(isort(ireg)); +%a=reshape(a, [],108])'; +% +% n=factor(size(allbetas,2)); +% n=sort([n(end) prod(n(1:end-1))]); +% +% prompt={'Enter the matrix size for x^2:','Enter the colormap name:'}; +% def={'20','hsv'}; +% dlgTitle='Input for Peaks function'; +% lineNo=1; +% answer=inputdlg(prompt,dlgTitle,lineNo,def); +% +% AddOpts.Resize='on'; +% AddOpts.WindowStyle='normal'; +% AddOpts.Interpreter='tex'; +% answer=inputdlg(prompt,dlgTitle,lineNo,def,AddOpts); +% +assignin('base', 'allbetas', allbetas) +ReshapeData = []; +xbars=[]; +fxorder=[2 3 1]; +switch size(allbetas,2) + case 8 + ReshapeData = [4 2]; + case 4 + if all(ismember(a,{'Neutral' 'Fearful' 'Angry' 'Happy'})) + ReshapeData = [4 1]; + end + case 18 + ReshapeData = [18 1]; + case 16 + % ReshapeData = [2 8]; + % xtick=[1 3 4 5 7 8 9 11]; + % fxorder=[3 2 1]; + ReshapeData = [16 1]; +end +if isempty(ReshapeData) + ReshapeData = [fliplr(factor(size(allbetas,2))) 1]; + ReshapeData = [ ReshapeData(1) prod(ReshapeData(2:end))] +end +allbetas=reshape(allbetas, [],ReshapeData(1),ReshapeData(2)); +allbetas = permute(allbetas,fxorder); +% allxyz=reshape(allxyz, [], 1, 3); +% allxyz=permute(allxyz, [3 2 1]); + +%assignin('base', 'allbetas', allbetas) +%assignin('base', 'allxyz', xyz) +roi.allbetas=allbetas; +roi.allxyz=allxyz'; +roi.XYZmm=xyz'; +roi.xyz=mean(allxyz,1)'; +assignin('base', 'roi', roi) + +%%%%%%%%%%%%%%%%%%%%%%%% +% Plot betas in figures >> EDIT MG: +try + plot_betas(roi,glmpath,handles) +catch + if n>1 + figure;barerrorbar(1:size(roi.allbetas,1),mean(roi.allbetas, ndims(roi.allbetas)),stderrw(roi.allbetas, 1:2, ndims(roi.allbetas)),NaN) + else + figure;bar(roi.allbetas) + end + mytitle=([roi.xyz(1,:) roi.xyz(2,:) roi.xyz(3,:)]); + title(['Coordinates (',num2str(mytitle),')']) + set(gca, 'XTickLabel', {'FULL_R' 'FULL_L' 'CHIM_b' 'CHIM_R' 'CHIM_L' 'DJ_b' 'DJ_R' 'DJ_L' 'UR' 'URx' 'UL' 'ULx' 'Rest'}) + xlabel('Condition') + ylabel('beta parameter') + legend({'Session1' 'Session2' 'Session3'},'Location', 'Best') +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [c_num, c_let, c_word]=mycolourset +c_num = [1 0 0;0 1 0;1 1 0;0 1 1;0 0 1;1 0 1]; +c_let = {'r';'g';'y';'c';'b';'m'}; +c_word= {'red';'green';'yellow';'cyan';'blue';'magenta'}; \ No newline at end of file diff --git a/xjview_v4.m b/xjview_v4.m new file mode 100644 index 0000000..bce66ca --- /dev/null +++ b/xjview_v4.m @@ -0,0 +1,8669 @@ +function xjview(varargin) +% xjview, version 4 +% +% usage 1: xjview (no argument) +% for displaying a result img file, or multiple image files, +% (which will be loaded later) and changing p-value or t/f-value +% usage 2: xjview(imagefilename) +% for displaying the result img file and changing p-value or +% t-value +% Example: xjView spmT_0002.img +% xjView('spmT_0002.img') +% xjView mymask.img +% usage 3: xjview(imagefilename1, imagefilename2, ...) +% for displaying the result img files and changing p-value or +% t/f-value +% Example: xjView spmT_0002.img spmT_0005.img spmT_0007.img +% xjView('spmT_0002.img', 'spmT_0003.img', 'spmT_0006.img') +% xjView myMask1.img myMask2.img myMask3.img +% usage 4: xjview(mnicoord, intensity) +% for displaying where are the mni coordinates +% mnicoord: Nx3 matrix of mni coordinates +% intensity: (optional) Nx1 matrix, usually t values of the +% corresponding voxels +% Example: xjView([20 10 1; -10 2 5],[1;2]) +% xjView([20 10 1; -10 2 5]) +% Note: to use xjview this way, you may need to modify the value +% of M and DIM in the begining of xjview.m +% +% http://people.hnl.bcm.tmc.edu/cuixu/xjView +% +% by Xu Cui and Jian Li 2/21/2005 +% last modified: 02/18/2007 (add colorbar max control) +% last modified: 11/16/2006 (keyboard shortcut for open image and open roi file) +% last modified: 06/16/2006 (spm5 compatible) +% last modified: 05/30/2006 (left/right flip, path of mask.img and templateFile.img) +% last modified: 05/08/2006 (debug CallBack_volumePush function, change handles.intensity{1} to intensity) +% last modified: 04/03/2006 (modify tr) +% last modified: 12/28/2005 (modify SPM process) +% +% Thank Sergey Pakhomov for sharing his database (MNI Space Utility). +% Thank Yuval Cohen for the maximize figure function (maximize.m) +% + +% TODO +% Send SPM to workspace + +warnstate = warning; +warning off; + +% pre-set values +% important! you need compare the display of xjview and spm. If you find +% xjview flipped the left/right, you need to set leftrightflip = 1; +% otherwise leave it to 0. +leftrightflip = 0; +% leftrightflip = 1 ; %must be on in the CMU... +% Now with spm-flip = 1; xjview-flip=1 + +% You only need to change M and DIM when you want to use xjview under +% 'usage 4'. +M = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +DIM = [41 48 35]'; +TR = 2; % you don't need to set TR is you only use the viewing part of xjview + +% system settings +try + spmdir = spm('dir'); + spm('defaults', 'fmri'); +catch + disp('Please add spm path.'); + warning(warnstate(1).state); + return +end + +if ispc + os = 'windows'; +elseif isunix + os = 'linux'; +else + warndlg('I don''t know what kind of computer you are using. I assumed it is unix.', 'What computer are you using?'); + os = 'linux'; +end +screenResolution = get(0,'ScreenSize'); + +xjviewpath = fileparts(which('xjview')); + +% pre-set values +pValue = 0.001; +intensityThreshold = 0; +clusterSizeThreshold = 5; + + +% Appearance Settings +figurePosition = [0.100, 0.050, 0.660, 0.880]; +sectionViewPosition = [0.5,0.61,0.45,0.45]; +glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +if screenResolution(3) <= 1024 + figurePosition = [0.100, 0.050, 0.700, 0.900]; + sectionViewPosition = [0.5, 0.61, 0.45, 0.46]; + glassViewAxesPosition = [0.000, 0.600, 0.464, 0.400]; +end + +left = 0.01; +editBoxHeight = 0.05; +editBoxWidth = 0.200; +editBoxLeft = 0.100; + +controlPanelPosition = [left, 0.080, 0.500, 0.500]; +stretchMatrix = diag([controlPanelPosition(3),controlPanelPosition(4),controlPanelPosition(3),controlPanelPosition(4)]); +controlPanelOffset = controlPanelPosition' .* [1,1,0,0]'; +heightUnit = 0.055; + +sliderPosition = stretchMatrix*[0.000, 0*heightUnit, 1.000, editBoxHeight]' + controlPanelOffset; +pValueTextPosition = stretchMatrix*[0.000, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pValueEditPosition = stretchMatrix*[0.110, 1*heightUnit, editBoxWidth*4/3, editBoxHeight]' + controlPanelOffset; +intensityThresholdTextPosition = stretchMatrix*[0.400, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +intensityThresholdEditPosition = stretchMatrix*[0.520, 1*heightUnit, editBoxWidth*3/3, editBoxHeight]' + controlPanelOffset; +dfTextPosition = stretchMatrix*[0.740, 1*heightUnit, 0.8-0.74, editBoxHeight]' + controlPanelOffset; +dfEditPosition = stretchMatrix*[0.800, 1*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdTextPosition = stretchMatrix*[0.000, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +clusterSizeThresholdEditPosition = stretchMatrix*[0.150, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +pickThisClusterPushPosition = stretchMatrix*[0.400, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +selectThisClusterPushPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +clearSelectedClusterPushPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth*1, editBoxHeight]' + controlPanelOffset; +thisClusterSizeTextPosition = stretchMatrix*[0.600, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +thisClusterSizeEditPosition = stretchMatrix*[0.800, 2*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +loadImagePushPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +imageFileEditPosition = stretchMatrix*[0.200, 3*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImagePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveImageFileEditPosition = stretchMatrix*[0.200, 4*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +saveResultPSPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +resultPSFileEditPosition = stretchMatrix*[0.200, 5*heightUnit, 1-editBoxWidth, editBoxHeight]' + controlPanelOffset; +displayIntensityTextPosition = stretchMatrix*[0.000, 3*heightUnit, editBoxWidth+0.1, editBoxHeight]' + controlPanelOffset; +allIntensityRadioPosition = stretchMatrix*[0.250, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +positiveIntensityRadioPosition = stretchMatrix*[0.400, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +negativeIntensityRadioPosition = stretchMatrix*[0.550, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +renderViewCheckPosition = stretchMatrix*[0.780, 3*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +hideControlPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +volumePushPosition = stretchMatrix*[0.000, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +commonRegionPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +%knd +paramestPushPosition = stretchMatrix*[0.800, 4*heightUnit, editBoxWidth*.5, editBoxHeight]' + controlPanelOffset; +%-- +displayPushPosition = stretchMatrix*[0.200, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +allinonePushPosition = stretchMatrix*[0.400, 4*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchPushPosition = stretchMatrix*[0.000, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchContentEditPosition = stretchMatrix*[0.200, 6*heightUnit, editBoxWidth*2, editBoxHeight]' + controlPanelOffset; +searchTextPosition = stretchMatrix*[0.600, 6*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +searchEnginePopPosition = stretchMatrix*[0.600, 6*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +overlayPushPosition = stretchMatrix*[0.000, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayEditPosition = stretchMatrix*[0.200, 5*heightUnit, 0.6-editBoxWidth, editBoxHeight]' + controlPanelOffset; +overlayPopPosition = stretchMatrix*[0.600, 5*heightUnit, 1-0.6, editBoxHeight]' + controlPanelOffset; +helpPosition = stretchMatrix*[0.800, 5*heightUnit, editBoxWidth, editBoxHeight]' + controlPanelOffset; +infoTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; +%xjViewPosition = stretchMatrix*[0.400, 13*heightUnit, editBoxWidth*2.5, editBoxHeight*3]' + controlPanelOffset; +%connameTextBoxPosition = stretchMatrix*[0.000, 8*heightUnit, 1, editBoxHeight*9]' + controlPanelOffset; + +sectionViewListboxPosition = [sectionViewPosition(1)+0.4, sectionViewPosition(2)+0.02, 0.1, 0.14]; +sectionViewMoreTargetPushPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.02,0.10,0.02]; +xHairCheckPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)+0.14,0.15,0.02]; +setTRangeEditPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.06,0.10,0.02]; +setTRangeTextPosition = [sectionViewListboxPosition(1),sectionViewListboxPosition(2)-0.04,0.10,0.02]; + +getStructurePushPosition = [glassViewAxesPosition(1), glassViewAxesPosition(2)-0.06, editBoxWidth/2, editBoxHeight/2]; +structureEditPosition = [getStructurePushPosition(1), getStructurePushPosition(2), 1, getStructurePushPosition(4)]; +framePosition = (controlPanelPosition - controlPanelOffset')*1.05 + 0.95*controlPanelOffset'; + +%knd +setContrastNameTextPosition = [glassViewAxesPosition(1),glassViewAxesPosition(2)-0.026,0.6,0.03]; +setContrastListPosition = [setContrastNameTextPosition(1)+setContrastNameTextPosition(3)+.01,setContrastNameTextPosition(2),0.05,setContrastNameTextPosition(4)]; +setContrastListPosition = [glassViewAxesPosition(1)+.05*glassViewAxesPosition(3),glassViewAxesPosition(2)-0.026,glassViewAxesPosition(3)*.95,0.03]; +setIndivResultsListPosition = [setTRangeTextPosition(1)-0.25,setTRangeEditPosition(2),0.20,setTRangeEditPosition(4)]; +%-- knd + +% draw figure and control +figureBKcolor=[176/255 252/255 188/255]; +figureBKcolor=get(0,'Defaultuicontrolbackgroundcolor'); +f = figure('unit','normalized','position',figurePosition,'Color',figureBKcolor,'defaultuicontrolBackgroundColor', figureBKcolor,... + 'Name','xjView', 'Tag', 'xjView', 'NumberTitle','off','resize','off','CloseRequestFcn', {@CallBack_quit, warnstate(1).state}, 'visible','off'); +handles = guihandles(f); + +% databases +try + addpath g:\ndiayek\data\atlases\ + addpath ~/data/atlases + addpath /mount/usb/data/atlases +end +try + X = load('TDdatabase'); + handles.DB = X.DB; + handles.wholeMaskMNIAll = X.wholeMaskMNIAll; +catch + handles.DB = []; + handles.wholeMaskMNIAll = struct([]); + errordlg('I can''t find TDdatabase.mat','TDdatabase not found'); +end + +handles.figure = f; +handles.frame = uicontrol(handles.figure,'style','frame',... + 'unit','normalized',... + 'position',framePosition,... + 'Visible','off'); +handles.slider = uicontrol(handles.figure,'style','slider',... + 'unit','normalized',... + 'position',sliderPosition,... + 'max',1,'min',0,... + 'sliderstep',[0.01,0.10],... + 'callback',@CallBack_slider,... + 'value',0,'Visible','on'); +handles.pValueTextPosition = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',pValueTextPosition,... + 'string','pValue=','horizontal','left'); +handles.pValueEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',pValueEditPosition,... + 'horizontal','left',... + 'String', num2str(pValue),... + 'BackgroundColor', 'w',... + 'callback',@CallBack_pValueEdit); +handles.intensityThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',intensityThresholdTextPosition,... + 'string',' intensity=','horizontal','left'); +handles.intensityThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',intensityThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(intensityThreshold),... + 'callback',@CallBack_intensityThresholdEdit); +handles.dfText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',dfTextPosition,... + 'string','df= ','horizontal','right'); +handles.dfEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',dfEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', '',... + 'callback',@CallBack_dfEdit); +handles.clusterSizeThresholdText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',clusterSizeThresholdTextPosition,... + 'string','cluster size >=','horizontal','left'); +handles.clusterSizeThresholdEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',clusterSizeThresholdEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', num2str(clusterSizeThreshold),... + 'callback',@CallBack_clusterSizeThresholdEdit); +handles.thisClusterSizeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',thisClusterSizeTextPosition,... + 'string','size= ','horizontal','right', 'visible', 'off'); +handles.thisClusterSizeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',thisClusterSizeEditPosition,... + 'horizontal','left',... + 'Enable', 'inactive',... + 'String', '','visible','off'); + +handles.imageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',imageFileEditPosition,... + 'horizontal','left',... + 'String', '',... + 'BackgroundColor', 'w',... + 'callback',@CallBack_imageFileEdit,... + 'visible','off'); +handles.saveImageFileEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',saveImageFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myMask.img',... + 'callback',@CallBack_saveImageFileEdit,... + 'visible','off'); +handles.saveResultPSEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',resultPSFileEditPosition,... + 'horizontal','left',... + 'BackgroundColor', 'w',... + 'String', 'myResult.ps',... + 'callback',@CallBack_saveResultPSEdit,... + 'visible','off'); +handles.loadImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',loadImagePushPosition,... + 'string','Load Image','callback',@CallBack_loadImagePush,... + 'visible','off'); +handles.saveImagePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveImagePushPosition,... + 'string','Save Image','callback',@CallBack_saveImagePush,... + 'visible','off'); +handles.saveResultPSPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',saveResultPSPushPosition,... + 'string','Save Result','callback',@CallBack_saveResultPSPush,... + 'visible','off'); +handles.getStructurePush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',getStructurePushPosition,... + 'string','Get Structure','callback',@CallBack_getStructurePush,'visible','off'); +handles.structureEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',structureEditPosition,... + 'horizontal','center',... + 'enable', 'on',... + 'UserData',struct(... + 'hReg', [],... + 'M', M,... + 'D', DIM,... + 'xyz', [0 0 0] )); +handles.pickThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',pickThisClusterPushPosition,... + 'string','Pick Cluster/Info','callback',@CallBack_pickThisClusterPush); +handles.selectThisClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',selectThisClusterPushPosition,... + 'string','Select Cluster','callback',@CallBack_selectThisClusterPush); +handles.clearSelectedClusterPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',clearSelectedClusterPushPosition,... + 'string','Clear Selection','callback',@CallBack_clearSelectedClusterPush); + +handles.displayIntensityText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',displayIntensityTextPosition,... + 'string','display intensity','horizontal','left'); +handles.allIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','All',... + 'position',allIntensityRadioPosition,... + 'value', 1,... + 'callback',@CallBack_allIntensityRadio); +handles.positiveIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only +',... + 'position',positiveIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'+'}); +handles.negativeIntensityRadio = uicontrol(handles.figure,'style','radio',... + 'unit','normalized',... + 'string','Only -',... + 'position',negativeIntensityRadioPosition,... + 'callback',{@CallBack_allIntensityRadio,'-'}); +handles.renderViewCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','Render View' ,... + 'horizontal', 'right',... + 'position',renderViewCheckPosition,... + 'callback', @CallBack_renderViewCheck); + +handles.sectionViewListbox = uicontrol(handles.figure,'style','listbox',... + 'unit','normalized',... + 'String', {'single T1','avg152PD','avg152T1','avg152T2','avg305T1','ch2','ch2bet','aal','brodmann'}, ... + 'value',3,... + 'position',sectionViewListboxPosition,... + 'callback',@CallBack_sectionViewListbox); + +handles.xHairCheck = uicontrol(handles.figure,'style','checkbox',... + 'unit','normalized',... + 'string','XHairs Off' ,... + 'horizontal','left',... + 'position',xHairCheckPosition,... + 'callback',@CallBack_xHairCheck); +handles.sectionViewMoreTargetPush = uicontrol(handles.figure,'style','push',... + 'unit','normalized','position',sectionViewMoreTargetPushPosition,... + 'string','other ...','callback',@CallBack_sectionViewMoreTargetPush); +handles.setTRangeEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',setTRangeEditPosition,'BackgroundColor', 'w',... + 'string','auto','callback',@CallBack_setTRangeEdit); +handles.setTRangeText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setTRangeTextPosition,... + 'string','colorbar max'); +handles.hideControlPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', '<', 'position', hideControlPushPosition,... + 'visible','off'); +handles.volumePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'volume', ... + 'position', volumePushPosition,... + 'callback', @CallBack_volumePush); +handles.commonRegionPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'common region', ... + 'position', commonRegionPushPosition,... + 'callback', @CallBack_commonRegionPush); +handles.displayPush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'display', ... + 'position', displayPushPosition,... + 'callback', @CallBack_displayPush,... + 'visible','off'); +handles.allinonePush = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'all in one', ... + 'position', allinonePushPosition,... + 'callback', @CallBack_allinonePush,... + 'visible','off'); +%knd: +handles.setContrastNameText = uicontrol(handles.figure,'style','text',... + 'unit','normalized','position',setContrastNameTextPosition, 'FontSize', 13,... + 'string',' ... ','callback',@CallBack_setContrastNameTextPosition); +handles.contrastListPush = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setContrastListPosition,... + 'callback', @CallBack_contrastListPush,... + 'visible','on'); + +handles.indivResultsListPush(1) = uicontrol(handles.figure, 'style', 'popup',... + 'unit','normalized',... + 'String', [ {''}'], ... % getfield(evalin('base','SS'),'sub2pr')),[],23)')], ... + 'position', setIndivResultsListPosition,... + 'callback', @CallBack_indivResultsListPush,... + 'visible','on'); + +handles.paramestPush(1) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Vox Betas', ... + 'position', paramestPushPosition'.*[1 1 2 1],... + 'callback', {@CallBack_paramestRegionPush, 'vox'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'vox', 0},... + 'visible','on'); +handles.paramestPush(2) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Cluster', ... + 'position', paramestPushPosition-[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'clu'},... + 'buttondownfcn', {@CallBack_paramestRegionPush, 'clu', 0},... + 'visible','on'); +handles.paramestPush(3) = uicontrol(handles.figure, 'style', 'push',... + 'unit','normalized',... + 'String', 'Sphere', ... + 'position', paramestPushPosition-2*[paramestPushPosition(3) 0 0 0]',... + 'callback', {@CallBack_paramestRegionPush, 'sph'},... + 'visible','on'); +%--knd + +handles.searchPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',searchPushPosition,... + 'String', 'search','callback',@CallBack_searchPush, 'ForeGroundColor',[0 0 1]); +handles.searchContentEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',searchContentEditPosition,... + 'ForeGroundColor',[0 0 1],... + 'BackgroundColor', 'w',... + 'horizontal','left','callback', @CallBack_searchContentEdit); +handles.searchText = uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',searchTextPosition,... + 'string', ' in',... + 'horizontal','left',... + 'visible','off'); +handles.searchEnginePop = uicontrol(... + 'Units','normalized', ... + 'ListboxTop',0, ... + 'Position',searchEnginePopPosition, ... + 'String',{'Brede';'Jede';'xBrain.org';'Google Scholar';'Pubmed';'Wikipedia'}, ... + 'Style','popupmenu', ... + 'value',1); +handles.overlayPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',overlayPushPosition,... + 'String', 'overlay','callback',@CallBack_overlayPush); +handles.overlayEdit = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',overlayEditPosition,... + 'BackgroundColor', 'w',... + 'horizontal','left',... + 'callback', @CallBack_overlayEdit); +handles.overlayPop = uicontrol(handles.figure, 'style','popupmenu',... + 'unit','normalized','position',overlayPopPosition,... + 'string', sort(fieldnames(handles.wholeMaskMNIAll)),... + 'horizontal','left',... + 'callback', @CallBack_overlayPop); + +handles.helpPush = uicontrol(handles.figure, 'style','push',... + 'unit','normalized','position',helpPosition,... + 'String', 'help','callback','web http://people.hnl.bcm.tmc.edu/cuixu/xjView','ForeGroundColor',[0 0 1],... + 'horizontal','left', ... + 'visible','off'); +handles.infoTextBox = uicontrol(handles.figure, 'style','edit',... + 'unit','normalized','position',infoTextBoxPosition,... + 'String', 'Welcome to xjView 4','ForeGroundColor','k', 'BackgroundColor', 'w',... + 'horizontal','left', ...'fontname','times',... + 'max',2, 'min',0); +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + set(handles.infoTextBox, 'String', s); +end + +handles.glassViewAxes = axes('unit','normalized','position',glassViewAxesPosition,'XTick',[],'YTick',[],'visible','off'); + + +handles.testEdit = uicontrol(handles.figure,'style','edit',... + 'unit','normalized','position',[0.1 0.4 0.2 0.05],... + 'horizontal','left',... + 'callback',@test,... + 'visible','off'); + +% menu +cSHH = get(0,'ShowHiddenHandles'); +set(0,'ShowHiddenHandles','on') +hMenuFile = findobj(get(handles.figure,'Children'),'flat','Label','&File'); +if ~isempty(hMenuFile) + hMenuFileOpen = findobj(get(handles.figure,'Children'),'Label','&Open...'); + set(hMenuFileOpen, 'label', 'Open Figure...'); + hMenuFileSave = findobj(get(handles.figure,'Children'),'Label','&Save'); + set(hMenuFileSave, 'label', 'Save Figure ...'); + hMenuFileSaveAs = findobj(get(handles.figure,'Children'),'Label','Save &As...'); + set(hMenuFileSaveAs, 'label', 'Save Figure As ...'); +else + hMenuFile = uimenu(handles.figure, 'label', '&File'); +end + +set(hMenuFile,'ForegroundColor',[0 0 1]); +set(findobj(hMenuFile,'Position',1),'Separator','on'); +%knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open SPM file (SPM.mat) ...',... + 'CallBack',@CallBack_loadSPMmat, 'Accelerator', 'o'); +%--knd +uimenu('Parent',hMenuFile,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','Open Images (*.img) ...',... + 'CallBack',@CallBack_loadImagePush, 'Accelerator', 'o'); +uimenu('Parent',hMenuFile,'Position',2,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 0}); +uimenu('Parent',hMenuFile,'Position',3,'ForegroundColor',[0 0 1],... + 'Label','Save Current Image as Mask (*.img) ...',... + 'CallBack',{@CallBack_saveImagePush, '', 1}); +uimenu('Parent',hMenuFile,'Position',4,'ForegroundColor',[0 0 1],... + 'Label','Save Result (*.ps/pdf) ...',... + 'CallBack',@CallBack_saveResultPSPush); + +hMenuHelp = findobj(get(handles.figure,'Children'),'flat','Label','&Help'); +if isempty(hMenuHelp) + hMenuHelp = uimenu(handles.figure, 'label', 'xjView &Help'); +end +set(hMenuHelp,'ForegroundColor',[0 0 1]); +uimenu('Parent',hMenuHelp,'Position',1,'ForegroundColor',[0 0 1],... + 'Label','xBrain.org: brain mapping database',... + 'CallBack','web http://www.xbrain.org -browser'); +uimenu('Parent',hMenuHelp,'Position',2,... + 'Label','xjview help','ForegroundColor',[0 0 1],... + 'CallBack','web http://people.hnl.bcm.tmc.edu/cuixu/xjView'); +set(findobj(hMenuHelp,'Position',3),'Separator','on'); +set(0,'ShowHiddenHandles',cSHH) + +if exist('cuixuBOLDretrieve') + hMenuAnalyze = uimenu('label','&Analyze','ForegroundColor',[0 0 1],'visible','on'); + hMenuPreprocess = uimenu(hMenuAnalyze,'label','Preprocess','ForegroundColor',[0 0 1],'callback', @CallBack_preprocess); + hMenuProcess = uimenu(hMenuAnalyze,'label','Process (GLM estimation)','ForegroundColor',[0 0 1],'callback',@CallBack_process); + hMenuSPMProcess = uimenu(hMenuAnalyze,'label','SPMProcess (GLM using SPM)','ForegroundColor',[0 0 1],'callback',@CallBack_SPMProcess); + hMenuGLMPeak = uimenu(hMenuAnalyze,'label','GLM on peak BOLD','ForegroundColor',[0 0 1],'callback',@CallBack_GLMPeak); + hMenuContrast = uimenu(hMenuAnalyze,'label','Contrast','ForegroundColor',[0 0 1],'callback',@CallBack_contrast); + hMenuFDR = uimenu(hMenuAnalyze,'label','FDR','ForegroundColor',[0 0 1],'callback',@CallBack_fdr); + hMenuROI = uimenu(hMenuAnalyze,'label','ROI: retrieve signal','ForegroundColor',[0 0 1],'callback',@CallBack_timeSeries); + hMenuROIPlot = uimenu(hMenuAnalyze,'label','ROI: plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotROI, 'Accelerator', 'm'); + hMenuROIIndividualPlot = uimenu(hMenuAnalyze,'label','ROI: individual plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROI); + hMenuROIIndividualPlotWithBehavior = uimenu(hMenuAnalyze,'label','ROI: individual plot with behavior','ForegroundColor',[0 0 1],'callback',@CallBack_plotIndividualROIWithBehavior); + hMenuROICorrelationPlot = uimenu(hMenuAnalyze,'label','ROI: correlation plot','ForegroundColor',[0 0 1],'callback',@CallBack_plotCorrelationROI); + %hMenuWholeBrainCorrelation = uimenu(hMenuAnalyze,'label','Whole brain correlation','ForegroundColor',[0 0 1],'callback',@CallBack_wholeBrainCorrelation); + hMenuBehaviorAnalysis = uimenu(hMenuAnalyze,'label','Behavior analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_behaviorAnalysis); + hMenuHeadMovementAnalysis = uimenu(hMenuAnalyze,'label','Head movement analsyis','ForegroundColor',[0 0 1],'callback',@CallBack_headMovementAnalysis); + hMenuModelComparison = uimenu(hMenuAnalyze,'label','Linear model comparison','ForegroundColor',[0 0 1],'callback',@CallBack_modelComparison); + + hMenuHNLOnly = uimenu('label','For H&NL Only','ForegroundColor',[0 0 1],'visible','on'); + hMenuNew2Old = uimenu(hMenuHNLOnly,'label','Format convert','ForegroundColor',[0 0 1],'callback',@CallBack_new2old); + hMenuPreprocessCluster = uimenu(hMenuHNLOnly,'label','Preprocess (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_preprocess, 'cluster'}); + hMenuProcessCluster = uimenu(hMenuHNLOnly,'label','Process (GLM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_process, 'cluster'}); + hMenuSPMProcessCluster = uimenu(hMenuHNLOnly,'label','SPM Process (GLM using SPM, on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_SPMProcess, 'cluster'}); + hMenuGLMPeakCluster = uimenu(hMenuHNLOnly,'label','GLM on peak BOLD (on cluster)','ForegroundColor',[0 0 1],'callback',{@CallBack_GLMPeak, 'cluster'}); +end + +figurecm = uicontextmenu; +uimenu(figurecm,'label','Red','callback','set(gcf,''color'',''r'')'); +uimenu(figurecm,'label','White','callback','set(gcf,''color'',''w'')'); +uimenu(figurecm,'label','Gray','callback','set(gcf,''color'',[0.925, 0.914, 0.847])'); +%set(handles.figure,'uicontextmenu',figurecm); +set(handles.figure,'WindowButtonDownFcn',@figureMouseUpFcn); + +set(handles.figure,'visible','on'); + +% save pre-set values +handles.system = os; +handles.spmdir = spmdir; +handles.screenResolution = screenResolution; +handles.pValue = pValue; +handles.intensityThreshold = intensityThreshold; +handles.clusterSizeThreshold = clusterSizeThreshold; +handles.sectionViewPosition = sectionViewPosition; +handles.sectionViewTargetFile = getSectionViewTargetFile(spmdir, 'avg152T1'); +%knd +if exist('xjview.opt') + tmp=textread('xjview.opt','%s');eval(tmp{:}); + handles.sectionViewTargetFile = anatomy; +else + if ~isempty(findstr('gazemo', pwd)) + handles.sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean.img'); + end +end +guidata(f, handles); + +% global variables for rotation matrix M and dimension +global M_; +global DIM_; +global TR_; +global LEFTRIGHTFLIP_; +global TMAX_; % colorbar max to display in section view +M_ = M; +DIM_ = DIM; +TR_ = TR; +LEFTRIGHTFLIP_ = leftrightflip; +TMAX_ = 'auto'; + +% check input arguments +if length(varargin) == 0 + CallBack_loadSPMmat(handles.loadImagePush) + % if exist(fullfile(pwd,'SPM.mat'), 'file') + % xSPM=load(fullfile(pwd,'SPM.mat')); + % numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', length(xSPM.SPM.xCon)); + % if ~isempty(numc) + % CallBack_loadImagePush(handles.loadImagePush, [], {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)}); + % end + % end +elseif isstr(varargin{1}) + if isempty(findstr('.mat', varargin{1})) + CallBack_loadImagePush(handles.loadImagePush, [], varargin); + else + CallBack_loadSPMmat(handles.loadImagePush, [], varargin{1}); + end +else + mniCoord = varargin{1}; + if length(varargin) < 2 + intensity = ones(size(mniCoord,1),1); + else + intensity = varargin{2}; + end + thisStruct.mni = mniCoord; + thisStruct.intensity = intensity; + thisStruct.M = M; + thisStruct.DIM = DIM'; + CallBack_loadImagePush(handles.loadImagePush, [], thisStruct); +end + + + +function test(hObject, eventdata) +handles = guidata(gcbo); +set(hObject, 'String', num2str(handles.pValue)); +vars = evalin('base','who'); +vars +x = evalin('base',vars{1}); +x +handles.DIM + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% FDR +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_fdr(hObject, eventdata) +handles = guidata(hObject); +set(handles.infoTextBox, 'string', {'Right now FDR only works for T-test image.'}); +if length(handles.imageFileName) > 1 + set(handles.infoTextBox, 'string', {'I can only work for a single image file. You opened multiple files.'}); + return +end + +q = get(handles.pValueEdit,'String'); +q = str2num(q); + +if get(handles.allIntensityRadio, 'Value') + positive = 1; +elseif get(handles.positiveIntensityRadio, 'Value') + positive = 1; +elseif get(handles.negativeIntensityRadio, 'Value') + positive = -1; +end +xjviewpath = fileparts(which('xjview')); +maskImageFile = fullfile(xjviewpath, 'mask.img'); +[threshold, pvalue] = fdr(handles.imageFileName{1}, q, positive, maskImageFile); +set(handles.pValueEdit,'string',pvalue); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% model comparison +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_modelComparison(hObject, eventdata) +answer = getVariable({'y','x (full model)', 'x (reduced model)'}); + +if isempty(answer) + return; +end + +if ~isempty(answer{1}) + y = evalin('base',answer{1}); +else + return; +end +if ~isempty(answer{2}) + xf = evalin('base',answer{2}); % full model +else + return; +end +if ~isempty(answer{3}) + xr = evalin('base',answer{3}); % reduced model +else + xr = []; +end + +% make vector column vector +[r, c] = size(y); +if r==1; y = y'; end +[r, c] = size(xf); +if r(0.5+ii/10); +end + +K = {zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1)),zeros(1, size(C,1))}; +for ii=1:size(C,1) + for jj=1:4 + K{jj}(ii) = sum(CC{jj}(ii,:)) - 1; + end +end + +x=[0:size(C,1)]; +for jj=1:4 + y{jj}=zeros(size(x)); +end + +for ii=1:length(x) + for jj=1:4 + y{jj}(ii) = sum(K{jj} == x(ii)); + end +end + +figure; +loglog(x,y{1}, x, y{2}, x, y{3}, x, y{4}); +xlabel('degree'); +ylabel('counts'); +legend('0.6', '0.7', '0.8', '0.9'); +axis equal + + +z = sum(abs(C))-1; +zx = 0:max(z); +for ii=1:length(zx)-1 + pos = find(z>zx(ii) & z<=zx(ii+1)); + zy(ii) = length(pos); +end +figure; +loglog(zx(1:length(zy)),zy); +xlabel('weighted degree'); +ylabel('counts'); +axis equal + +xjview(cor2mni(coord, handles.M{1}), z); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get/select variable names in base workspace +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function vars = getVariable(titles) +vars = evalin('base','who'); +height = 0.07; +f = dialog('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.4 0.4], 'name', 'pick variables', 'NumberTitle','off'); +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', 'Available variables', ... + 'position',[0 0.9 0.5 0.1/2]); +variableListbox = uicontrol(f,'style','listbox','tag','variableListbox',... + 'unit','normalized',... + 'String', vars, ... + 'value',1,... + 'position',[0 0 0.5 0.9]); +okPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'OK', ... + 'position',[0.55 0.05 0.2 height],... + 'callback','uiresume'); +cancelPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', 'Cancel', ... + 'position',[0.75 0.05 0.2 height],... + 'callback','delete(gcf)'); + +uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{1}, ... + 'position',[0.5 0.9 0.5 0.1/2]); +imageDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.8 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''imageDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); +imageDataEdit = uicontrol(f,'style','edit','tag','imageDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.8 0.3 height]); + +if length(titles)>=2 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{2}, ... + 'position',[0.5 0.7 0.5 0.1/2]); + eventDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.6 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''eventDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + eventDataEdit = uicontrol(f,'style','edit','tag','eventDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.6 0.3 height]); +end +if length(titles)>=3 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{3}, ... + 'position',[0.5 0.5 0.5 0.1/2]); + correlatorDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.4 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''correlatorDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + correlatorDataEdit = uicontrol(f,'style','edit','tag','correlatorDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.4 0.3 height]); +end +if length(titles)>=4 + uicontrol(f,'style','text',... + 'unit','normalized',... + 'String', titles{4}, ... + 'position',[0.5 0.3 0.5 0.1/2]); + otherDataPush = uicontrol(f,'style','push',... + 'unit','normalized',... + 'String', '->', ... + 'position',[0.5 0.2 0.1 height],... + 'callback', [... + 'xyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''otherDataEdit'');'... + 'yyouneverfindme=findobj(get(gcf,''Children''),''flat'',''tag'',''variableListbox'');'... + 'allyouneverfindme=get(yyouneverfindme,''string'');'... + 'selectedyouneverfindme=allyouneverfindme{get(yyouneverfindme,''value'')};'... + 'set(xyouneverfindme,''string'',selectedyouneverfindme);'... + 'clear allyouneverfindme selectedyouneverfindme xyouneverfindme yyouneverfindme;']); + + otherDataEdit = uicontrol(f,'style','edit','tag','otherDataEdit',... + 'unit','normalized',... + 'String', '', ... + 'BackgroundColor', 'w',... + 'position',[0.6 0.2 0.3 height]); +end + +uiwait(f); +try + var{1} = get(imageDataEdit,'string'); + if length(titles)>=2 + var{2} = get(eventDataEdit,'string'); + end + if length(titles)>=3 + var{3} = get(correlatorDataEdit,'string'); + end + if length(titles)>=4 + var{4} = get(otherDataEdit,'string'); + end + vars = var; + delete(f); +catch + vars = {}; + try + delete(f); + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% quit xjview +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_quit(hObject, eventdata, warnstate) +warning(warnstate) +% try +% rmdir('xjviewtmp'); +% end +delete(gcf); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mouse double click +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function figureMouseUpFcn(hObject, eventdata) +status = get(hObject, 'SelectionType'); + +% double click +if strcmp(status, 'extend') + handles = guidata(hObject); + CallBack_loadImagePush(handles.loadImagePush, eventdata); +elseif strcmp(status, 'open') + handles = guidata(hObject); + CallBack_loadSPMmat(handles.loadImagePush, eventdata); +else + return +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change edit image file name +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_imageFileEdit(hObject, eventdata) +handles = guidata(hObject); +filename = get(hObject, 'String'); +filename = str2cell(filename); +CallBack_loadImagePush(handles.loadImagePush, eventdata, filename); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_contrastListPush(hObject, eventdata) +handles = guidata(hObject); +connum = get(handles.contrastListPush,'Value'); +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); +if ~exist(spmfile) + set(handles.contrastListPush,'Value',0); +else + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + connames=get(handles.contrastListPush,'String'); + CallBack_loadImagePush(hObject,eventdata,fullfile(img.p, cons(connum).Vspm.fname), connum) +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load image file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadImagePush(hObject, eventdata, thisfilename, ContrastName) +handles = guidata(hObject); +handles.imageFileName=[]; handles.M=[]; handles.DIM=[]; handles.TF=[]; handles.df=[]; +handles.mni=[]; handles.intensity=[]; handles.currentmni=[]; handles.currentintensity=[]; handles.currentDisplayMNI=[]; handles.currentDisplayIntensity=[]; +if nargin>3 + handles.imageContrastName=ContrastName; +else + handles.imageContrastName=[]; +end +if ~exist('thisfilename') + thisfilename = ''; +end + +if isstruct(thisfilename) + handles.imageFileName = {''}; + handles.mni = {thisfilename.mni}; + handles.intensity = {thisfilename.intensity}; + handles.M = {thisfilename.M}; + handles.DIM = {thisfilename.DIM}; + handles.TF = {'S'}; + handles.df = {1e6}; + handles.pValue = 1; + set(handles.pValueEdit, 'string', '1'); + handles.clusterSizeThreshold = 0; + set(handles.clusterSizeThresholdEdit, 'String', '0'); + handles.imageContrastName={''}; +else + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); +end + +if isempty(handles.imageFileName) + return +end + +% tries to find firts-level matching data +% knd +set(handles.indivResultsListPush(1),'String', ... + getfield2(dir(fileparts(fileparts(handles.imageFileName{1}))), 'name')); + +different = 0; % image files are same or different? +if length(handles.TF)>1 + for ii=1:length(handles.TF) + if strcmp(handles.TF{ii},handles.TF{1}) & isequal(handles.df{ii},handles.df{1}) & isequal(handles.M{ii},handles.M{1}) & isequal(handles.DIM{ii},handles.DIM{1}) + continue; + else + warndlg('Images are from different statistics or sources.', 'Warning'); + %set(handles.infoTextBox, 'string', 'Images are from different statistics or sources.'); + beep; + different = 1; + break; + end + end +end + +% reset files with empty df/TF to df=1 and TF='S'. 'S'=='T' but has a tag +% meaning it is changed. +resetTF = 0; +for ii=1:length(handles.TF) + if isempty(handles.TF{ii}) + handles.TF{ii} = 'S'; + resetTF = 1; + end + if isempty(handles.df{ii}) | isequal(handles.df{ii},0) + handles.df{ii} = 1e6; + resetTF = 1; + end +end + +handles.currentmni = handles.mni; +handles.currentintensity = handles.intensity; + +set(handles.dfEdit, 'String', cell2str(handles.df)); +set(handles.imageFileEdit, 'String', cell2str(handles.imageFileName)); % s=-log10(p) +maxs = maxcell(t2s(cellmax(handles.intensity,'abs'),handles.df, handles.TF),'abs'); +if isinf(maxs); maxs = 20; end +set(handles.slider, 'Max', maxs, 'Min', 0, 'sliderstep',[min(maxs/100,0.05),min(maxs/100,0.05)]); +if handles.TF{1}=='T' & different == 0 + str = [blanks(length(' intensit')) 'T=']; +elseif handles.TF{1}=='F' & different == 0 + str = [blanks(length(' intensit')) 'F=']; +else + str=' intensity='; +end +set(handles.intensityThresholdText, 'String', str); +set(handles.figure,'Name',['xjView: ' cell2str(handles.imageFileName)]); +try + for ii=1:length(handles.hLegend) + delete(handles.hLegend{ii}); + end +end +nimg=length(handles.TF); +if nimg>1 + colours = {'r';'g';'y';'c';'b';'m'}; + %colours = colours(mod(0:nimg-1,length(colours))+1); + %colours = repmat([1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1],100,1); + % read_conname = spm_input({'Retrieve contrasts names','Should I read SPM files to retrieve filenames?'},... + % 1,'bd',{'YES','NO'},[1,0]); + read_conname = 1; + for ii=1:nimg + [tmp,filename] = fileparts(handles.imageFileName{ii}); + c_names{ii} = filename ; + if read_conname & exist(fullfile(tmp, 'SPM.mat')) + tmp=load(fullfile(tmp, 'SPM.mat')); + tmp.Vspm=[tmp.SPM.xCon.Vspm]; + tmp.iCon=strmatch(filename, {tmp.Vspm.fname}); + if ~isempty(tmp.iCon) + c_names{ii} = [ [tmp.SPM.xCon(tmp.iCon).name] ' [' c_names{ii} ']']; + end + end + end + [tmp] = inputdlg({'colors' 'names'},'Loading',6,[{strvcat(c_names)};{strvcat(colours)}]); + colours = colorname2rgb(tmp{2}); + c_names = cellstr(tmp{1}); + + for ii=1:min(length(handles.TF),10) + filename = c_names{ii}; + if ii == 10; filename = '......'; end + pos0 = handles.sectionViewPosition; + pos(1) = pos0(1)+pos0(3)/2+0.03; + pos(2) = pos0(2)+ii/50-0.03; + pos(3) = 0.12; + pos(4) = 0.02; + handles.hLegend{ii}=uicontrol(handles.figure, 'style','text',... + 'unit','normalized','position',pos,... + 'string', filename,... + 'horizontal','left',... + 'fontweight','bold',... + 'ForeGroundColor',colours(ii,:)); + end + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; +end +guidata(hObject, handles); + +global M_; +global DIM_; +M_ = handles.M{1}; +DIM_ = handles.DIM{1}; + +if resetTF==1 + set(handles.pValueEdit,'string',1); +end +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +% display info +try + s = urlread('http://people.hnl.bcm.tmc.edu/cuixu/xjView/toUser.txt'); + report{1} = s; +catch + report{1} = 'Welcome to xjView 4'; +end +for jj=1:length(handles.imageFileName) + report{2+6*(jj-1)} = cell2str(handles.imageFileName(jj)); + if handles.TF{jj} == 'T' | handles.TF{jj} == 'F' + report{3+6*(jj-1)} = ['This is a ' handles.TF{jj} ' test image.']; + else + report{3+6*(jj-1)} = '';%['I don''t know what test this image came from.']; + end + report{4+6*(jj-1)} = 'mat = '; + report{5+6*(jj-1)} = num2str(handles.M{jj}); + report{6+6*(jj-1)} = 'dimension = '; + report{7+6*(jj-1)} = num2str(handles.DIM{jj}); +end +if length(handles.imageFileName)==1 + [img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); + spmfile=fullfile(img.p,'SPM.mat'); + if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); + end + end + if exist(spmfile) + cons=getfield(getfield(load(spmfile, 'SPM'), 'SPM'), 'xCon'); + for i=1:length(cons) + if not(isempty(cons(i).Vspm)) + consfilename{i}=cons(i).Vspm.fname; + else + consfilename{i}=''; + end + end + connum=strmatch([img.fname img.ext],consfilename); + if ~isempty(connum) + conlabel=cons(connum).name; + set(handles.figure,'Name',[get(handles.figure,'Name') ' :: ' conlabel]); + set(handles.contrastListPush,'String',{cons.name}) + set(handles.contrastListPush,'Value',connum) + set(handles.setContrastNameText,'String',[conlabel]); + report=[report(1:3) {['Contrast name in SPM.mat: (' num2str(connum) ') ' conlabel]} report(4:end)]; + else + set(handles.contrastListPush,'String',{'[none]'}) + set(handles.contrastListPush,'Value',0) + set(handles.contrastListPush,'Enable','on') + report=[report(1:3) {['Contrast has no matching name in SPM.mat']} report(4:end)]; + end + end +end +set(handles.infoTextBox, 'string', report); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pValueEdit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pValueEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +tmps = -log10(tmp); +if isnan(tmp) | tmp < 0 | tmp > 1 + errordlg('I don''t understand the input.','error'); + set(hObject, 'String', handles.pValue); + return +end + +if tmps>get(handles.slider,'max') | tmps maxcell(cellmax(handles.intensity,'abs')) + tmp = maxcell(cellmax(handles.intensity,'abs')); +end + +handles.pValue = t2p(tmp, handles.df{1}, handles.TF{1}); +handles.intensityThreshold = p2t(num2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); +set(handles.slider,'Value', -log10(handles.pValue)); +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +guidata(hObject, handles); +CallBack_slider(hObject, eventdata, -log10(handles.pValue)); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% slider bar +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_slider(hObject, eventdata, value) + +handles = guidata(hObject); + +if exist('value') + s = value; + if s > get(handles.slider,'max') + s = get(handles.slider,'max')*0.99; + end + if s < get(handles.slider,'min') + s = get(handles.slider,'min'); + end +else + s = get(hObject,'Value'); +end + +set(handles.slider, 'value', s); +pvalue = 10^(-s); +set(handles.pValueEdit,'String',num2str(pvalue)); +t = p2t(num2cell(pvalue*ones(1,length(handles.TF))), handles.df, handles.TF); +handles.intensityThreshold = t; +set(handles.intensityThresholdEdit, 'String', cell2str(handles.intensityThreshold)); +handles.pValue = pvalue; +for ii=1:length(handles.TF) + pos{ii} = find(abs(handles.intensity{ii})>=t{ii}); + handles.currentintensity{ii} = handles.intensity{ii}(pos{ii}); + handles.currentmni{ii} = handles.mni{ii}(pos{ii},:); +end + +guidata(hObject,handles); + +if get(handles.allIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.allIntensityRadio, eventdata); +elseif get(handles.positiveIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.positiveIntensityRadio, eventdata, '+'); +elseif get(handles.negativeIntensityRadio, 'Value') + CallBack_allIntensityRadio(handles.negativeIntensityRadio, eventdata, '-'); +end + +set(handles.infoTextBox, 'string', {'Don''t drag the slider bar too fast. Release your mouse button at least 1 second later.', ... + 'This sounds stupid. But there is a bug (probably MatLab bug) which I can'' fix right now.', ... + 'I suggest you confirm the correctness of the current display by press Enter in the pValue edit box.'}); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display intensity all+- radios +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allIntensityRadio(hObject, eventdata, pnall) +% pnall = '+', '-', 'a' (all) or 'c' for current (simply update drawing) +% +handles = guidata(hObject); + +currentselect = []; +if get(handles.allIntensityRadio, 'Value'); currentselect = handles.allIntensityRadio; thispnall = 'a'; end +if get(handles.positiveIntensityRadio, 'Value'); currentselect = handles.positiveIntensityRadio; thispnall = '+'; end +if get(handles.negativeIntensityRadio, 'Value'); currentselect = handles.negativeIntensityRadio; thispnall = '-'; end + +set(handles.allIntensityRadio, 'Value', 0); +set(handles.positiveIntensityRadio, 'Value', 0); +set(handles.negativeIntensityRadio, 'Value', 0); + +if exist('pnall') + if pnall=='c' + hObject = currentselect; + pnall = thispnall; + end +end + +set(hObject, 'Value', 1); + +if ~isfield(handles,'currentintensity') + return +end +for ii=1:length(handles.TF) + if exist('pnall') + if pnall == '-' + pos{ii} = find(handles.currentintensity{ii} < 0); + elseif pnall == '+' + pos{ii} = find(handles.currentintensity{ii} > 0); + elseif pnall == 'a' + pos{ii} = 1:length(handles.currentintensity{ii}); + end + else + pos{ii} = 1:length(handles.currentintensity{ii}); + end + intensity{ii} = handles.currentintensity{ii}(pos{ii}); + mni{ii} = handles.currentmni{ii}(pos{ii},:); + cor{ii} = mni2cor(mni{ii}, handles.M{ii}); + + if ~isempty(cor{ii}) + A = spm_clusters(cor{ii}'); + pos0 = []; + for kk = 1:max(A) + jj = find(A == kk); + if length(jj) >= handles.clusterSizeThreshold; pos0 = [pos0 jj]; end + end + handles.currentDisplayMNI{ii} = mni{ii}(pos0,:); + handles.currentDisplayIntensity{ii} = intensity{ii}(pos0); + else + handles.currentDisplayMNI{ii} = mni{ii}([],:); + handles.currentDisplayIntensity{ii} = intensity{ii}([]); + end +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% list of contrasts + +set(handles.contrastListPush,'String',regexprep(get(handles.contrastListPush,'String'),' \[Only [\+-a]\]$','')) +set(handles.setContrastNameText,'String',regexprep(get(handles.setContrastNameText,'String'),' \[Only [\+-a]\]$','')) + +if exist('pnall','var') + if ~isequal(pnall, 'a') + set(handles.setContrastNameText,'String',[get(handles.setContrastNameText,'String') ' [Only ' pnall ']']); + s=get(handles.contrastListPush,'String'); + s{get(handles.contrastListPush,'Value')}=[s{get(handles.contrastListPush,'Value')} ' [Only ' pnall ']']; + + set(handles.contrastListPush,'String',s); + end +end + +if get(handles.allIntensityRadio, 'Value') & max(handles.currentDisplayIntensity{1}) < 0 + warndlg('No supra-threshold positive intensity. Only negative intensity is displayed.'); +end + +try + set(handles.figure,'currentaxes', handles.glassViewAxes); + xrange = xlim; + yrange = ylim; + try + delete(handles.hGlassText) + end + if ~isempty(handles.selectedCluster,1) + %handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); + end +end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% render view check? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_renderViewCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% which section view target file? list box +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewListbox(hObject, eventdata) +handles = guidata(hObject); +contents = get(handles.sectionViewListbox,'String'); +currentsel = contents{get(handles.sectionViewListbox,'Value')}; +handles.sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get sectionviewtargetfile +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function sectionViewTargetFile = getSectionViewTargetFile(spmdir, selectedcontent) +if findstr('SPM2',spm('ver')) + fileext = 'mnc'; +elseif findstr('SPM5',spm('ver')) + fileext = 'nii'; +end +currentsel = selectedcontent; +if ~isempty(strfind(currentsel, 'single')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['single_subj_T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152PD')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152PD.' fileext]); +elseif ~isempty(strfind(currentsel, '152T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T1.' fileext]); +elseif ~isempty(strfind(currentsel, '152T2')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg152T2.' fileext]); +elseif ~isempty(strfind(currentsel, '305T1')) + sectionViewTargetFile = fullfile(spmdir, 'canonical', ['avg305T1.' fileext]); +elseif strcmp(currentsel, 'ch2') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2.img'); +elseif strcmp(currentsel, 'ch2bet') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'ch2bet.img'); +elseif strcmp(currentsel, 'aal') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'aal.img'); +elseif strcmp(currentsel, 'brodmann') + sectionViewTargetFile = fullfile(spmdir, 'canonical', 'brodmann.img'); + %knd: +elseif ~isempty(strfind(currentsel, 'gazemo')) + sectionViewTargetFile = fullfile(fileparts(mfilename('fullpath')), 'group','anat', 'mean-no120.img'); + %sectionViewTargetFile = fullfile('D:\ndiayek\data\gazemo\group\anat', 'mean-no120.img'); +end +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% xhairs in section view? +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_xHairCheck(hObject, eventdata) +check = get(hObject, 'Value'); +if check + spm_orthviews('Xhairs','off'); +else + spm_orthviews('Xhairs','on'); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% other target file for section view, push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_sectionViewMoreTargetPush(hObject, eventdata) +handles = guidata(hObject); +[filename, pathname, filterindex] = uigetfile('*', 'Pick an target file'); +if isequal(filename,0) | isequal(pathname,0) + return; +end +handles.sectionViewTargetFile = fullfile(pathname, filename); +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% set colorbar range +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_setTRangeEdit(hObject, eventdata) +global TMAX_; +handles = guidata(hObject); +TMAX_ = get(hObject, 'String'); +if isempty(str2num(TMAX_)) && ~strcmp(TMAX_, 'auto') + return; +end +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% change degree of freedome +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_dfEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2cell(get(hObject, 'String')); +if iscellstr(tmp) + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.df); + catch + set(hObject, 'String', ''); + end + return +end +handles.df=tmp; + + +if isfield(handles,'TF') + t = p2t(mat2cell(handles.pValue*ones(1,length(handles.TF))), handles.df, handles.TF); + handles.intensityThreshold = t; + set(handles.intensityThresholdEdit, 'String', cell2str(t)); +end + +guidata(hObject, handles); +CallBack_pValueEdit(handles.pValueEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get structure push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_getStructurePush(hObject, eventdata) +handles = guidata(hObject); +xyz = spm_XYZreg('GetCoords',handles.hReg); +tmp_coor = cuixuFindTDstructure(xyz', handles.DB, 0); +set(handles.structureEdit,'String', tmp_coor{1}); +handles.currentxyz = xyz'; +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% structure edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_structureEdit(action, xyz, thisfun, hReg) + +try + handles=guidata(hReg); +catch + return; +end + +handles.currentxyz = xyz'; +guidata(hReg, handles); + +try + [tmp_coor, cellstructure] = cuixuFindTDstructure(xyz', handles.DB, 0); +catch + return; +end + +set(handles.structureEdit,'String', tmp_coor{1}); + +for ii=[5 3 2 1 4] + if strfind('Unidentified', cellstructure{ii}) + continue; + else + set(handles.searchContentEdit,'string', trimStructureStr(cellstructure{ii})); + set(handles.searchContentEdit,'UserData', 'auto'); + return; + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% trim str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = trimStructureStr(str) +pos = findstr('(', str); +if ~isempty(pos) + str(pos-1:end)=[]; +end +out = str; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cluster size threshold edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clusterSizeThresholdEdit(hObject, eventdata) +handles = guidata(hObject); +tmp = str2double(get(hObject, 'String')); +if isnan(tmp) | tmp<0 + errordlg('Please input a valid number.','error'); + try + set(hObject, 'String', handles.clusterSizeThreshold); + catch + set(hObject, 'String', '5'); + end + return +end +handles.clusterSizeThreshold=tmp; + +guidata(hObject, handles); +CallBack_allIntensityRadio(hObject, eventdata, 'c'); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image push button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImagePush(hObject, eventdata, thisfilename, isMask) +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}); + return; + end + end + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}); + return; + end +end + +[filename, pathname] = uiputfile('*.img', 'Save image file as', get(handles.saveImageFileEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + +if isfield(handles,'imageFileName') + if ~isempty(handles.imageFileName{1}) + mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity'), handles.M{1}, handles.DIM{1}, handles.imageFileName{1}, isMask); + return; + end +end + +mni2mask(cell2mat(handles.currentDisplayMNI'), thisfilename, cell2mat(handles.currentDisplayIntensity), handles.M{1}, handles.DIM{1}, '', isMask); + +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save image edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveImageFileEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveImagePush(handles.saveImagePush, eventdata, get(hObject,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSPush(hObject, eventdata, thisfilename) + +handles = guidata(hObject); + +if exist('thisfilename') + if ~strcmp(deblank(thisfilename), '') + spm_print(handles.figure); + if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); + elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); + end + return; + end +end + +[filename, pathname] = uiputfile('*.ps', 'Save result as', get(handles.saveResultPSEdit, 'string')); +if isequal(filename,0) | isequal(pathname,0) + return +else + thisfilename = fullfile(pathname, filename); +end + + +% print +H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); +un = cellstr(get(H,'Units')); +pos = get(H,'position'); +index = []; + +for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 & pos{ii}(2) > 0.5 + set(H(ii),'position',[pos{ii}(1), pos{ii}(2), pos{ii}(3)*3/4, pos{ii}(4)]); + index = [index ii]; + end +end + + +spm_print(handles.figure); +if strcmp(handles.system, 'linux') + system(['ps2pdf spm2.ps']); + system(['mv spm2.ps ' thisfilename]); + [p,f,ext]=fileparts(thisfilename); + system(['mv spm2.pdf ' fullfile(p,f) '.pdf']); +elseif strcmp(handles.system, 'windows') + system(['move spm2.ps ' '"' thisfilename '"']); +end + +% set the position back +set(H(index), {'position'}, pos(index)); + + +% printstr = ['print -dpsc2 -painters -noui ' '''' thisfilename '''']; +% try +% orient portrait +% eval(printstr); +% printsuccess = 1; +% catch +% errordlg('Print to ps file failed', 'print error'); +% printsuccess = 0; +% end +%set(H,{'Units'},un); +% if strcmp(handles.system, 'linux') & printsuccess == 1 +% system(['ps2pdf ' '''' thisfilename '''']); +% end + +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% save result edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_saveResultPSEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_saveResultPSPush(hObject, eventdata, get(handles.saveResultPSEdit,'string')); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% select a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_selectThisClusterPush(hObject, eventdata) +handles = guidata(hObject); + +try + xyz = handles.currentxyz'; +catch + xyz = spm_XYZreg('GetCoords',handles.hReg); +end + +try + handles.selectedCluster = [handles.selectedCluster; xyz']; +catch + handles.selectedCluster = xyz'; +end + +disp('handles defines!') +assignin('base','handles',handles) + +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + delete(handles.hGlassText) +end +%handles.hGlassText = text(xrange(1)+diff(xrange)*0.6, yrange(1)+diff(yrange)*0.9, [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +set(handles.infoTextBox, 'string', [num2str(size(handles.selectedCluster,1)) ' clusters selected']); +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% unselect a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_clearSelectedClusterPush(hObject, eventdata) +handles = guidata(hObject); +try + handles = rmfield(handles,'selectedCluster'); +end +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; +try + %delete(handles.hGlassText) + set(handles.infoTextBox, 'string', ['No clusters selected']); +end + +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% pick a cluster +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_pickThisClusterPush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +if isempty(mni) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return; +end + +if ~isfield(handles, 'selectedCluster') | isempty(handles.selectedCluster) + try + xyz = handles.currentxyz'; + catch + xyz = spm_XYZreg('GetCoords',handles.hReg); + end + handles.selectedCluster = xyz'; +end + +intensity = cell2mat(handles.currentDisplayIntensity'); +cor = mni2cor(mni, handles.M{1}); +A = spm_clusters(cor'); +xyzcor = mni2cor(handles.selectedCluster, handles.M{1}); + +pos = []; +for ii = 1:size(xyzcor,1) + pos0 = find(cor(:,1)==xyzcor(ii,1) & cor(:,2)==xyzcor(ii,2) & cor(:,3)==xyzcor(ii,3)); + if isempty(pos0) + continue; + end + pos = [pos find(A==A(pos0(1)))]; +end +if isempty(pos) + %errordlg('No cluster is picked up.','oops'); + set(handles.infoTextBox, 'string', 'No cluster is picked up.'); + beep + return +end + +pos = unique(pos); + +tmpmni = mni(pos,:); +tmpintensity = intensity(pos); + +[B,I,J] = unique(tmpmni, 'rows'); +handles.currentDisplayMNI = {B}; +fprintf('Cluster defined from: %s \n', handles.imageFileName{1}); +assignin('base', 'currentDisplayMNI', handles.currentDisplayMNI ); +handles.currentDisplayIntensity = {tmpintensity(I,:)}; + +handles.currentxyz = handles.selectedCluster(end,:); + +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +set(handles.figure,'currentaxes', handles.glassViewAxes); +xrange = xlim; +yrange = ylim; + +handles.selectedCluster = []; +try + delete(handles.hGlassText) +end + +guidata(hObject, handles); + +set(handles.thisClusterSizeEdit,'string', num2str(size(handles.currentDisplayMNI{1},1))); +str = get(handles.searchContentEdit, 'string'); +pos = findstr(' ', str); +str(pos) = []; +files = []; +for ii=1:length(handles.imageFileName) + [a,b,c] = fileparts(handles.imageFileName{ii}); + files = [files b]; +end +if ~isempty(files) + files = ['_from_' files]; +end + +set(handles.saveImageFileEdit, 'string', [str files '.img']); + +% list structure of voxels in this cluster +[a, b] = cuixuFindTDstructure(cell2mat(handles.currentDisplayMNI'), handles.DB, 0); +names = unique(b(:)); +index = NaN*zeros(length(b(:)),1); +for ii=1:length(names) + pos = find(strcmp(b(:),names{ii})); + index(pos) = ii; +end + +for ii=1:max(index) + report{ii,1} = names{ii}; + report{ii,2} = length(find(index==ii)); +end +for ii=1:size(report,1) + for jj=ii+1:size(report,1) + if report{ii,2} < report{jj,2} + tmp = report(ii,:); + report(ii,:) = report(jj,:); + report(jj,:) = tmp; + end + end +end +report = [{'structure','# voxels'}; {'--TOTAL # VOXELS--', length(a)}; report]; +% format long +% disp(b) +% disp(report) +% format +report2 = {sprintf('%s\t%s',report{1,2}, report{1,1}),''}; +for ii=2:size(report,1) + if strcmp('Unidentified', report{ii,1}); continue; end + report2 = [report2, {sprintf('%5d\t%s',report{ii,2}, report{ii,1})}]; +end + +report2 = [report2, {'','select and Ctrl-C to copy'}]; +% f = figure('unit','normalized', 'menubar','none', 'position', [0.3 0.2 0.2 min(0.7,0.016*length(report2))], 'name', 'cluster information', 'NumberTitle','off'); +% hEdit = uicontrol(f,'style','edit',... +% 'unit','normalized','position',[0 0 1 1],... +% 'horizontal','left',... +% 'BackgroundColor', 'w',... +% 'String', report2,... +% 'max',2,'min',0); + +set(handles.infoTextBox, 'string', report2); +assignin('base', 'ans', handles.currentDisplayMNI) +disp('Cluster coordinates in "ans"') +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% commonRegion push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_commonRegionPush(hObject, eventdata) +handles = guidata(hObject); +if ~isfield(handles,'TF') | length(handles.TF)<=1 + %msgbox('Two or more images need to be loaded to find the common region.', 'info'); + set(handles.infoTextBox, 'string', 'Two or more images need to be loaded to find the common region.'); + beep + return; +end + +common = handles.currentDisplayMNI{1}; +for ii=2:length(handles.TF) + common = intersect(common, handles.currentDisplayMNI{ii}, 'rows'); +end + +if isempty(common) + %msgbox('No common region found.', 'info'); + set(handles.infoTextBox, 'string', 'No common region found.'); + beep + return; +end + +tmpMNI = cell2mat(handles.currentDisplayMNI'); +tmpIntensity = cell2mat(handles.currentDisplayIntensity'); +intensity = zeros(size(common,1),1); + +for ii=1:size(common,1) + pos = find(abs(tmpMNI(:,1)-common(ii,1))<0.1 & abs(tmpMNI(:,2)-common(ii,2))<0.1 & abs(tmpMNI(:,3)-common(ii,3))<0.1); + intensity(ii) = prod(tmpIntensity(pos)); +end + +handles.currentDisplayMNI = {common}; +handles.currentDisplayIntensity = {intensity}; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); + +% if isfield(handles,'hLegend') +% try +% set(cell2mat(handles.hLegend'),'visible',{'off'}); +% end +% end +guidata(hObject, handles); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% volume push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_volumePush(hObject, eventdata) +handles = guidata(hObject); +mni = cell2mat(handles.currentDisplayMNI'); +intensity = cell2mat(handles.currentDisplayIntensity'); + +xSPM.XYZ = mni2cor(mni, handles.M{1}); +xSPM.XYZ = xSPM.XYZ'; +xSPM.XYZmm = mni'; +xSPM.Z = (intensity'); +xSPM.M = handles.M{1}; +xSPM.DIM = handles.DIM{1}; +xSPM.STAT = handles.TF{1}; +if xSPM.STAT == 'T' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +elseif xSPM.STAT == 'F' + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}(1)) ',' num2str(handles.df{1}(2)) '}']; + xSPM.df = [handles.df{1}]; +else + xSPM.STAT = 'T'; + xSPM.STATstr = [xSPM.STAT '_{' num2str(handles.df{1}) '}']; + xSPM.df = [1 handles.df{1}]; +end +xSPM.k = str2num(get(handles.clusterSizeThresholdEdit, 'string')); +xSPM.u = str2num(get(handles.intensityThresholdEdit, 'string')); +xSPM.u = xSPM.u(1); +xSPM.VOX = abs([xSPM.M(1,1) xSPM.M(2,2) xSPM.M(3,3)]); +xSPM.n = 1; + + +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) + +xSPM.S = length(handles.intensity{1}); +xSPM.R = [3 27.0931 276.3307 498.1985]; +xSPM.FWHM = [2.9746 3.1923 2.8600]; + +if get(handles.positiveIntensityRadio, 'Value') + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(intensity, xSPM.df)); end +end + +if get(handles.negativeIntensityRadio, 'Value'); + xSPM.Z = abs(xSPM.Z); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf(-intensity, xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf(-intensity, xSPM.df)); end +end + +if get(handles.allIntensityRadio, 'Value'); + if xSPM.STAT == 'T'; xSPM.Ps = (1-spm_Tcdf((intensity), xSPM.df(2))); end + if xSPM.STAT == 'F'; xSPM.Ps = (1-spm_Fcdf((intensity), xSPM.df)); end +end + +if findstr('SPM2',spm('ver')) + P = spm_get([0 1],'SPM.mat','locate the corresponding SPM.mat'); +elseif findstr('SPM5',spm('ver')) + P = spm_select([0:1],'SPM.mat','locate the corresponding SPM.mat'); +end + +if ~isempty(P) + load(P); + xSPM.FWHM = SPM.xVol.FWHM; + xSPM.R = SPM.xVol.R; + xSPM.S = SPM.xVol.S; +else + warndlg(['You did not input SPM.mat. The listed result may not be correct.'], 'SPM.mat missing'); +end + +spm_list('List',xSPM,handles.hReg); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% display +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_displayPush(hObject, eventdata) +handles = guidata(hObject); +spm_image('init', handles.imageFileName); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% all in one +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_allinonePush(hObject, eventdata) +try + if findstr('SPM2',spm('ver')) + P = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P = spm_select(Inf,'image','Select image files'); + end + +catch + return; +end +if isempty(P) + return +end + +handles = guidata(hObject); +%if ~isfield(handles,'hReg') | ~isfield(handles,'hSection') | ~isfield(handles,'hcolorbar') +tmp = [0 0 0]; +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(tmp([],:), [], hObject, handles); +%end + +colors=mycolourset; +for ii=1:size(P,1) + thisfilename = deblank(P(ii,:)); + [handles.imageFileName, handles.M, handles.DIM, handles.TF, handles.df, handles.mni, handles.intensity] = getImageFile(thisfilename); + cor = mni2cor(handles.mni, handles.M); + spm_orthviews('addcolouredblobs',1,cor',handles.intensity',handles.M,colors(mod(ii,6)+1,:)); +end +spm_orthviews('Redraw'); + +guidata(hObject, handles); + +% contents = get(handles.sectionViewListbox,'String'); +% currentsel = contents{get(handles.sectionViewListbox,'Value')}; +% sectionViewTargetFile = getSectionViewTargetFile(handles.spmdir, currentsel); +% +% % spm_image('init', sectionViewTargetFile); +% % spm_image('addblobs'); +% % return + +% guidata(hObject, handles); +% load xSPM; +% VOL.XYZ = xSPM.XYZ; +% VOL.Z = xSPM.Z; +% VOL.M = handles.M; + +%addcolouredimage(handles.hSection, '333.img',[1 0 1]); +% uigetfiles +% nblobs = 4; +% for i=1:nblobs, +% %[SPM,VOL] = spm_getSPM; +% %c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); +% c = i; +% VOL.XYZ = ceil(rand(3,20)*20); +% VOL.Z = randn(1,20); +% VOL.M = handles.M; +% colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; +% spm_orthviews('addcolouredblobs',1,VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); +% end; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Push +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPush(hObject, eventdata) +handles = guidata(hObject); + +tobeoverlay = deblank(get(handles.overlayEdit, 'string')); + +if isempty(tobeoverlay) + return; +end + +tobeoverlay = str2cell(tobeoverlay, ' '); +if isnumeric(tobeoverlay{1}) + if length(tobeoverlay{1})>1 + errordlg(['Your input, ' deblank(get(handles.overlayEdit, 'string')) ', seems coincide with a matlab constant.'], 'error'); + return + end + for ii=1:length(tobeoverlay) + tobeoverlay{ii} = num2str(tobeoverlay{ii}); + end +end +fn = fieldnames(handles.wholeMaskMNIAll); +for ii=1:length(tobeoverlay) + pos{ii} = []; + for jj=1:length(fn) + x = []; + if ~isempty(str2num(tobeoverlay{ii})) + y = str2cell(fn{jj},'_'); + for kk=1:length(y) + x = isequal(tobeoverlay{ii}, y{kk}); + if x; break;end; + end + if x==0; x = []; end; + else + x = findstr(lower(tobeoverlay{ii}), lower(fn{jj})); + end + if ~isempty(x) + pos{ii} = [pos{ii} jj]; + end + end +end +common = pos{1}; +for ii=2:length(pos) + common = intersect(common, pos{ii}); +end + +if isempty(common) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return +end + +mask = []; +for ii=1:length(common) + eval(['mask = [mask; handles.wholeMaskMNIAll.' fn{common(ii)} '];']); +end + +if isempty(mask) + %warndlg(['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.'], 'oops'); + set(handles.infoTextBox, 'string', ['I don'' find ' deblank(get(handles.overlayEdit, 'string')) '.']); + return; +end + +try + handles.mni; +catch + delete(gcf); + xjview(mask); + return; +end + +handles.imageFileName = [handles.imageFileName, {deblank(get(handles.overlayEdit, 'string'))}]; +handles.M = [handles.M, {handles.M{1}}]; +handles.DIM = [handles.DIM, {handles.DIM{1}}]; +handles.currentDisplayMNI = [handles.currentDisplayMNI, {mask}]; +m = max(abs(cell2mat(handles.currentDisplayIntensity'))); +if ~isempty(m) + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {-2*m*ones(size(mask,1),1)}]; +else + handles.currentDisplayIntensity = [handles.currentDisplayIntensity, {ones(size(mask,1),1)}]; +end +[handles.hReg, handles.hSection, handles.hcolorbar] = Draw(handles.currentDisplayMNI, handles.currentDisplayIntensity, hObject, handles); +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region Edit +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayEdit(hObject, eventdata) +handles = guidata(hObject); +CallBack_overlayPush(handles.overlayPush, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% overlay a brain region popup +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_overlayPop(hObject, eventdata) +handles = guidata(hObject); +names = get(hObject, 'string'); +value = get(hObject, 'value'); +set(handles.overlayEdit, 'string', names{value}); +CallBack_overlayEdit(handles.overlayEdit, eventdata); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% search xBrain.org and other databases +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchPush(hObject, eventdata) + +try + handles = guidata(hObject); + searchContent = get(handles.searchContentEdit,'string'); + searchEngine = get(handles.searchEnginePop,'string'); + searchEngine = searchEngine{get(handles.searchEnginePop,'value')}; + + + xyz = str2num(searchContent); + searchMode=get(handles.searchContentEdit,'UserData'); + + switch searchMode + case 'auto'; + xyz = spm_XYZreg('GetCoords',handles.hReg); + handles.currentxyz = xyz'; + guidata(hObject, handles); + [a,b] = cuixuFindTDstructure(xyz', handles.DB, 0); + try + brodmann = strmatch('Brodmann',b) + brodmann = b{brodmann}; + brodmann = brodmann(1:end-4); + end; + try + region = b{3}; + region = region(1:end-4); + end + + case 'manual' + if isempty(xyz) + searchMode='text'; + elseif length(xyz)==3 + searchMode='xyz'; + end + end + + + switch searchEngine + case 'Brede' + switch searchMode + case 'auto' + searchString = sprintf(' %0.0f',xyz') + set(handles.searchContentEdit,'string',searchString); + case 'xyz' + searchString = num2str(xyz');%searchContent=sprintf('+%0.0f',searchContent) + case 'text' + end + urlstr = ['http://hendrix.imm.dtu.dk/cgi-bin/brede_loc_query.pl?q=' searchString ]; + case 'xBrain.org' + switch searchMode + case { 'auto' 'xyz'} + xbrainSearchField = 'mni or tal&mnidistance=20'; + searchString = sprintf(' %0.1f',xyz')% searchString = num2str(xyz'); + case 'text' + xbrainSearchField = 'region'; + searchString = searchContent; + end + set(handles.searchContentEdit,'string',searchString); + urlstr = ['http://people.hnl.bcm.tmc.edu/cuixu/cgi-bin/bmd/paper.pl?search_content=' searchString '&search_field=' xbrainSearchField]; + case 'Google Scholar' + if isequal(searchMode,'auto' ) + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22|',searchString{:}); + try + searchString = searchString(1:end-1); + end + %set(handles.searchContentEdit,'string',searchString); + end + urlstr = ['http://scholar.google.com/scholar?q=' searchString ]; + case 'Pubmed' + switch searchMode + case 'auto' + searchString = { brodmann region }; + searchString(cellfun('isempty',searchString))=[]; + searchString = sprintf('%%22%s%%22 OR ',searchString{:}); + try + searchString = searchString(1:end-4); + end + %searchString = brodmann; + case 'text' + searchString = searchContent; + end + % urlstr = ['http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=PureSearch&db=pubmed&details_term=(' searchString ')']; + urlstr = ['http://www.ncbi.nlm.nih.gov/sites/entrez?cmd=search&db=pubmed&pubmedfilters=true&term=(' searchString ')']; + case 'Wikipedia' + if isequal(searchMode,'auto') + searchString = region; + end + urlstr = ['http://en.wikipedia.org/w/index.php?search=%22' searchString '%22']; + end + set(handles.searchContentEdit,'UserData',searchMode); +catch + urlstr = 'http://www.google.com'; +end + +try + web(urlstr,'-browser'); +catch + if exist('c:\program Files\mozilla Firefox\firefox.exe','file') + system(['"c:\program Files\mozilla Firefox\firefox.exe" "' urlstr '"']) + else + web(urlstr); + end +end + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% control panel on or off +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function controlHide(handles, status) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get multiple values from a string deliminated delim +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function out = str2cell(str, delim) +if ~exist('delim') + delim = '; '; +end + +[out{1},b] = strtok(str, delim); +ii = 2; +while ~isempty(b) + [out{ii},b] = strtok(b, delim); + ii = ii+1; +end + +for ii=1:length(out) + out2{ii} = str2num(out{ii}); + if isempty(out2{ii}) + return; + end +end + +for ii=1:length(out) + out{ii} = str2num(out{ii}); +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cell2str +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function str = cell2str(acell, delim) +if ~exist('delim') + delim = ';'; +end + +str = []; + +if length(acell)==1 + if isstr(acell{1}) + str = acell{1}; + else + str = num2str(acell{1}); + end +else + for ii=1:length(acell) + if isstr(acell{ii}) + str = [str acell{ii}, delim ' ']; + else + str = [str num2str(acell{ii}), delim ' ']; + end + end + str(end-1:end)=[]; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cellmax, find max in each element, return a cell +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = cellmax(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end + +MAXX = []; +for ii=1:length(acell) + if strfind('abs',absolute) + MAXX = [MAXX max(abs(acell{ii}))]; + else + MAXX = [MAXX max(acell{ii})]; + end +end +MAXX = num2cell(MAXX); + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% maxcell +%%% find max of all numbers in the whole cell, return a single value +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function MAXX = maxcell(acell, absolute) + +if ~exist('absolute') + absolute = ''; +end +MAXX = cellmax(acell, absolute); +MAXX = max(cell2mat(MAXX)); + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% p2t +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = p2t(p, df, TF) +if ~iscell(p) + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = p2t(p{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% s2t, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function t = s2t(s, df, TF) + +if ~iscell(s) + p = 10^(-s); + if upper(TF)=='T' | upper(TF)=='S' + t = spm_invTcdf(1-p,df); + elseif upper(TF) == 'F' + t = spm_invFcdf(1-p,df); + end +else + for ii=1:length(p) + t{ii} = s2t(s{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2p +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function p = t2p(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + end +else + for ii=1:length(t) + p{ii} = t2p(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% t2s, s is defined as -log10(p) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function s = t2s(t, df, TF) +if ~iscell(t) + if upper(TF)=='T' | upper(TF)=='S' + p = 1-spm_Tcdf(t,df); + elseif upper(TF) == 'F' + p = 1-spm_Fcdf(t,df); + else + p = 0.1; + end + s = -log10(p); +else + for ii=1:length(t) + s{ii} = t2s(t{ii},df{ii},TF{ii}); + end +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2mask +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mask = mni2mask(coords, targetfilename, intensity, M, DIM, templateFile, isMask) +% function mask = mni2mask(coords, targetfilename, intensity, templateFile) +% make mask from coordinates +% +% coords: a Nx3 column of 3-d coordinates in MNI +% space +% targetfilename: (optional) the image files to be written +% intensity: (optional) Nx1, the values of each coordinate. +% M: rotation matrix +% DIM: dimension +% templateFile: (optional) the templateFile from which we can get the right +% dimensions. +% isMask: if this variable exist and equal to 1, then all non-zero +% intensities will be set to 1 +% +% Xu Cui +% 2004/11/18 + +if ~exist('intensity') + intensity = ones(size(coords,1),1); +end +thistemplateFile = ''; +if exist('templateFile') + if ~isempty(templateFile) + thistemplateFile = templateFile; + end +end + +if isempty(thistemplateFile) + V.mat = [... + -4 0 0 84; ... + 0 4 0 -116; ... + 0 0 4 -56; ... + 0 0 0 1]; + V.dim = [41 48 35 16]; + if exist('M') + V.mat = M; + end + if exist('DIM') + V.dim = DIM; + V.dim(4) = 16; + end + V.fname = targetfilename; + V.descrip = 'our own image'; +else + V = spm_vol(templateFile); + V.fname = targetfilename; + if isfield(V, 'descrip') + V.descrip = ['my image from ' V.descrip]; + else + V.descrip = 'my own image'; + end +end + +thisismask = 0; +if exist('isMask') + if isMask == 1 + thisismask = 1; + end +end +if thisismask + V.descrip = 'my mask'; + intensity = ones(size(intensity)); +end + +O = zeros(V.dim(1),V.dim(2),V.dim(3)); + +coords = mni2cor(coords,V.mat); + + +for ii=1:size(coords,1) + O(coords(ii,1),coords(ii,2),coords(ii,3)) = intensity(ii); +end + +if exist('targetfilename') + V = spm_write_vol(V,O); +end + +mask = O; + +return; + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% get image file information +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [imageFile,M,DIM,TF,df,mni,intensity] = getImageFile(thisfilename) +% function imageFile = getImageFile(filename) +% get the information of this/these image file(s) +% +% thisfilename: (optional) if doesn't give file name, then show a open file +% dialog +% imageFile: the full name of the selected file (if user pressed cancel, +% imageFile == 0 +% M: M matrix (rotation matrix) +% DIM: dimension +% TF: t test or f test? 'T' or 'F' +% df: degree of freedome +% mni: mni coord +% intensity: intensity of each mni coord +% +% Note: The returned variables are cellarrays. +% +% Xu Cui +% last revised: 2005-05-03 + +if nargin < 1 | isempty(thisfilename) + if findstr('SPM2',spm('ver')) + P0 = spm_get([0:100],'*IMAGE','Select image files'); + elseif findstr('SPM5',spm('ver')) + P0 = spm_select(Inf,'image','Select image files'); + end + + % try + % P0 = spm_get([0:100],'*IMAGE','Select image files'); + % catch + % P0 = []; + % [FileName,PathName] = uigetfile({'*.img';'*.IMG';'*.*'},'Select image files','MultiSelect','on'); + % if isstr(FileName) + % P0 = {fullfile(PathName, FileName)}; + % elseif iscellstr(FileName) + % for ii=1:length(FileName) + % P0{ii} = fullfile(PathName, FileName{ii}); + % end + % else + % P0 = []; + % end + % end + try + if isempty(P0) + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end + end + for ii=1:size(P0,1) + P{ii} = deblank(P0(ii,:)); + end +else + if isstr(thisfilename) + P = {thisfilename}; + elseif iscellstr(thisfilename) + P = thisfilename; + else + disp('Error: In getImageFile: I don''t understand the input.'); + imageFile = '';M=[];DIM=[];TF=[];df=[];mni=[];intensity=[]; + return + end +end + +global LEFTRIGHTFLIP_; + +for ii=1:length(P) + imageFile{ii} = P{ii}; + [cor{ii}, intensity{ii}, tmp{ii}, M{ii}, DIM{ii}, TF{ii}, df{ii}] = mask2coord(imageFile{ii}, 0); + if LEFTRIGHTFLIP_ == 1 + M{ii}(1,:) = -M{ii}(1,:); + end + mni{ii} = cor2mni(cor{ii}, M{ii}); +end + + + + + + + + + + + + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuFindTDstructure +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% function [onelinestructure, cellarraystructure] = cuixuFindTDstructure(pos, DB, TALMNI) +% +% this function converts Talairach Daemon coordinate or MNI coordinate to a description of +% brain structure. +% +% pos: the coordinate (MNI or Talairach coordinate, defined by TALMNI) of the position in the brain, in mm +% DB: the database structure (see below for detailed explanation). If you don't input this argument, there +% should be a file called 'TDdatabase.mat' in the current directory +% TALMNI: 1 if pos is talairach coordinate, 0 if pos is MNI coordinate. 1 +% by default. +% +% onelinestructure: a one-line description of the returned brain +% structure +% cellarraystructure: a cell array of size 5, each cell contains a string +% describing the structure of the brain in a certain level. +% +% Example: +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48], DB, 1) +% [onelinestructure, cellarraystructure] = cuixuFindTDstructure([-24 24 48]) +% then +% onelinestructure = // Left Cerebrum // Frontal Lobe (L) // Middle Frontal Gyrus (L) // Gray Matter (L) // Brodmann area 8 (L) +% cellarraystructure = 'Left Cerebrum' 'Frontal Lobe (L)' [1x24 char] 'Gray Matter (L)' 'Brodmann area 8 (L)' +% +% Xu Cui +% 2004-6-28 +% + +%---------------------------------------------------------------------------------- +% DB strcture +%---------------------------------------------------------------------------------- +%------------------------------- +% Grid specification parameters: +%------------------------------- +% minX - min X (mm) +% maxX - max X (mm) +% voxX - voxel size (mm) in X direction +% minY - min Y (mm) +% maxY - max Y (mm) +% voxY - voxel size (mm) in Y direction +% minZ - min Z (mm) +% maxZ - max Z (mm) +% voxZ - voxel size (mm) in Z direction +% nVoxX - number of voxels in X direction +% nVoxY - number of voxels in Y direction +% nVoxZ - number of voxels in Z direction +%------------------------------- +% Classification parameters: +%------------------------------- +% numClass - number of classification types +% cNames - cNames{i} - cell array of class names for i-th CT +% numClassSize - numClassSize(i) - number of classes for i-th CT +% indUnidentified - indUnidentified(i) - index of "indUnidentified" class for i-th CT +% volClass - volClass{i}(j) - number of voxels in class j for i-th CT +% +% data - N x numClass matrix of referencies; let +% x y z coordinates in mm (on the grid) and +% nx = (x-minX)/voxX +% ny = (y-minY)/voxY +% nz = (z-minZ)/voxZ +% ind = nz*nVoxX*nVoxY + ny*nVoxX + nx + 1 +% data(ind, i) - index of the class for i-th CT in cNames{i} to +% which (x y z) belongs, i.e. +% cNames{i}{data(ind, i)} name of class for i-th CT +%---------------------------------------------------------------------------------- + +if nargin==1 + load('TDdatabase.mat'); + TALMNI = 1; +elseif nargin == 2 + TALMNI = 1; +end + +if(TALMNI == 1) + pos = tal2mni(pos); +elseif(TALMNI == 0) + []; +else + disp('TALMNI should be 1 or 0.'); +end + +pos(:,1) = DB.voxX*round(pos(:,1)/DB.voxX); +pos(:,2) = DB.voxY*round(pos(:,2)/DB.voxY); +pos(:,3) = DB.voxZ*round(pos(:,3)/DB.voxZ); + +min = []; +vox = []; +for(i=1:size(pos,1)) + min = [min; DB.minX DB.minY DB.minZ]; + vox = [vox; DB.voxX DB.voxY DB.voxZ]; +end +n_pos = (pos - min)./vox; + +nx = n_pos(:,1); +ny = n_pos(:,2); +nz = n_pos(:,3); +index = nz*DB.nVoxX*DB.nVoxY + ny*DB.nVoxX + nx + 1; +indMax = size(DB.data, 1); + +onelinestructuretmp = []; +onelinestructure = []; +for(j=1:size(pos,1)) + onelinestructuretmp = []; + for(i=1:DB.numClass) + + if (index(j) <= 0 | index(j) > indMax) + ind(j) = DB.indUnidentified(i); + else + ind(j) = DB.data(index(j), i); + end + + cellarraystructure{j,i} = DB.cNames{i}{ind(j)}; + onelinestructuretmp = [onelinestructuretmp ' // ' cellarraystructure{j,i}]; + end + onelinestructure{j} = onelinestructuretmp; +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mask2coord +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [cor, intensity, cor_singlecolumn,M,DIM,TF,df] = mask2coord(mask, checkdimension) +% [cor, intensity, cor_singlecolumn] = mask2coord(mask, checkdimension) +% +% This is to retrieve the coordinate of a mask file, or a matrix of 3-D +% +% mask: an image file or a matrix (3-D), with some of the elements are +% non-zeros +% checkdimension: check if the dimension is checkdimension, if not, return empty +% matrix +% cor: a N*3 matrix, which each row a coordinate in matrix +% intensity: a N*1 matrix, which encodes the intensity of each voxel. +% cor_singlecolumn: a N*1 matrix, each row is the index in the matrix +% M: rotation matrix +% DIM: dimension +% TF: t test or f test? 'T','F' or [] +% df: degree of freedome for T/F test +% +% Example: +% mask = zeros(4,3,2); +% mask(1,2,1) = 1; +% mask(3,2,2) = 1; +% mask2coord(mask) +% +% mask2coord('spmT_0002.img') +% mask2coord('spmT_0002.img',[41 48 35]) +% +% Xu Cui +% 2004-9-20 +% last revised: 2005-04-30 + +if nargin < 2 + checkdimension = 0; +end + +if ischar(mask) + V = spm_vol(mask); + mask = spm_read_vols(V); + M = V.mat; + DIM = V.dim; + TF = 'T'; + T_start = strfind(V.descrip,'SPM{T_[')+length('SPM{T_['); + if isempty(T_start); T_start = strfind(V.descrip,'SPM{F_[')+length('SPM{F_['); TF='F'; end + if isempty(T_start) + TF=[]; df=[]; + else + T_end = strfind(V.descrip,']}')-1; + df = str2num(V.descrip(T_start:T_end)); + end +else + M = []; + TF = []; + df = []; +end + +dim = size(mask); +if length(checkdimension)==3 + if dim(1)~= checkdimension(1) | dim(2)~= checkdimension(2) | dim(3)~= checkdimension(3) + y = []; + disp('dimension doesn''t match') + return + end +end + +pos = find(mask~=0); +intensity = mask(pos); + +y = zeros(length(pos),3); + +y(:,3) = ceil(pos/(dim(1)*dim(2))); +pos = pos - (y(:,3)-1)*(dim(1)*dim(2)); +y(:,2) = ceil(pos/dim(1)); +pos = pos - (y(:,2)-1)*(dim(1)); +y(:,1) = pos; + +cor = y; +cor_singlecolumn = pos; +DIM = dim; +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% mni2cor +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function coordinate = mni2cor(mni, T) +% function coordinate = mni2cor(mni, T) +% convert mni coordinate to matrix coordinate +% +% mni: a Nx3 matrix of mni coordinate +% T: (optional) transform matrix +% coordinate is the returned coordinate in matrix +% +% caution: if T is not specified, we use: +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% + +if isempty(mni) + coordinate = []; + return; +end + +if ~exist('T') + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +coordinate = [mni(:,1) mni(:,2) mni(:,3) ones(size(mni,1),1)]*(inv(T))'; +coordinate(:,4) = []; +coordinate = round(coordinate); +return; + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cor2mni +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function mni = cor2mni(cor, T) +% function mni = cor2mni(cor, T) +% convert matrix coordinate to mni coordinate +% +% cor: an Nx3 matrix +% T: (optional) rotation matrix +% mni is the returned coordinate in mni space +% +% caution: if T is not given, the default T is +% T = ... +% [-4 0 0 84;... +% 0 4 0 -116;... +% 0 0 4 -56;... +% 0 0 0 1]; +% +% xu cui +% 2004-8-18 +% last revised: 2005-04-30 + +if nargin == 1 + T = ... + [-4 0 0 84;... + 0 4 0 -116;... + 0 0 4 -56;... + 0 0 0 1]; +end + +cor = round(cor); +mni = T*[cor(:,1) cor(:,2) cor(:,3) ones(size(cor,1),1)]'; +mni = mni'; +mni(:,4) = []; +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% draw +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = Draw(mniCoord, intensity, hObject, handles) + +try + delete(handles.hcolorbar); +end +try + delete(handles.hReg); +end +try + delete(handles.hSection); +end +try + cla(handles.glassViewAxes); +end + +try + H = findobj(get(handles.figure,'Children'),'flat','Type','axes'); + un = cellstr(get(H,'Units')); + pos = get(H,'position'); + + for ii=1:length(H) + if findstr('pixels', un{ii}) + continue; + end + if pos{ii}(1)>0.4 + delete(H(ii)); + end + end +end + +sectionViewTargetFile = handles.sectionViewTargetFile; + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end + if max(intensity)*min(intensity) < 0 + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + else + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,abs(intensity),sectionViewTargetFile,hObject,handles); + end + + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end +else % multiple input? yes + [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord,intensity,sectionViewTargetFile,hObject,handles); + + mniCoordtmp=[]; + intensitytmp=[]; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + if size(mniCoord,1)>1 + pos1 = find(intensity>=0); + pos2 = find(intensity<0); + if ~isempty(pos1) & ~isempty(pos2) + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord(pos1,:),intensity(pos1,:),mniCoord(pos2,:),-intensity(pos2,:)); end + else + if get(handles.renderViewCheck, 'Value'); cuixuRenderView(mniCoord, abs(intensity)); end + end + end + +end + +try + spm_XYZreg('SetCoords',handles.currentxyz',hReg); +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuSectionView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [hReg, hSection, hcolorbar] = cuixuSectionView(mniCoord, intensity, targetFile, hObject,handles) +% function h = cuixuSectionView(mniCoord, intensity) +% This is to project your coordinate to section view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% a special feature of this function is: it automatically seperate the +% negative and positive intensity and use hot and cold color to represent +% them. +% +% h: the returned handle for the axes +% +% SEE ALSO: cuixuView cuixuGlassView cuixuRenderView +% +% Xu Cui +% 2004/11/11 + +if ~iscell(mniCoord) | (iscell(mniCoord) & length(mniCoord)==1)% multiple input? no + multiple = 0; + if (iscell(mniCoord) & length(mniCoord)==1) + mniCoord = mniCoord{1}; + intensity = intensity{1}; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; + end +else + multiple = 1; + mniCoordtmp = []; + intensitytmp = []; + for ii=1:length(mniCoord) + mniCoordtmp = [mniCoordtmp; mniCoord{ii}]; + intensitytmp = [intensitytmp; intensity{ii}]; + % for multiple input + cSPM{ii}.XYZ = mni2cor(mniCoord{ii}, handles.M{ii}); + cSPM{ii}.XYZ = cSPM{ii}.XYZ'; + cSPM{ii}.Z = abs(intensity{ii}); + cSPM{ii}.M = handles.M{ii}; + cSPM{ii}.DIM = handles.DIM{ii}'; + end + mniCoord = mniCoordtmp; + intensity = intensitytmp; + handles.M = handles.M{1}; + handles.DIM = handles.DIM{1}; +end + +SPM.XYZ = mni2cor(mniCoord, handles.M); +SPM.XYZ = SPM.XYZ'; +SPM.Z = intensity; +SPM.M = handles.M; +SPM.DIM = handles.DIM'; + +%%%%%%%%%%%%%%% Reg %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +handles.colormap = colormap; + +coor = mniCoord; +xSPM = SPM; +xSPM.XYZmm = mniCoord'; +axes(handles.glassViewAxes) +WS = spm('WinScale'); +FS = spm('FontSizes'); + +Finter = gcf; +hReg = uicontrol(Finter,'Style','Frame','Position',[60 100 300 300].*WS,... + 'Visible','off'); +[hReg,xyz] = spm_XYZreg('InitReg',hReg,xSPM.M,xSPM.DIM,[0;0;0]); + +hFxyz = spm_results_ui('DrawXYZgui',xSPM.M,xSPM.DIM,xSPM,xyz,Finter); +spm_XYZreg('XReg',hReg,hFxyz,'spm_results_ui'); + +hMIPax =gca ; +setcolormap('gray'); + +hMIPax = spm_mip_ui(xSPM.Z,coor',xSPM.M,xSPM.DIM,hMIPax); +spm_XYZreg('XReg',hReg,hMIPax,'spm_mip_ui'); + +colormap(handles.colormap); +setcolormap('gray-hot'); + +if isempty(handles.M) + spm_XYZreg('SetReg',handles.structureEdit,hReg); +else + set(handles.structureEdit, 'UserData', struct('hReg',hReg,'M',handles.M,'D', handles.DIM,'xyx',[0 0 0])); +end + +spm_XYZreg('Add2Reg',hReg,handles.structureEdit,@CallBack_structureEdit); + +%%%%%%%%%%%%%%% Reg end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +if multiple == 0 + [hgraph, hSection, hcolorbar] = spm_sections(SPM,hReg,targetFile,handles.sectionViewPosition); +else + [hgraph, hSection, hcolorbar] = spm_sections(cSPM,hReg,targetFile,handles.sectionViewPosition); +end + +return + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_sections +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [Fgraph, hMe, hcolorbar] = spm_sections(SPM,hReg,targetFile,sectionViewPosition) +% rendering of regional effects [SPM{Z}] on orthogonal sections +% FORMAT spm_sections(SPM,hReg) +% +% SPM - xSPM structure containing details of excursion set +% hReg - handle of MIP register +% +% see spm_getSPM for details +%_______________________________________________________________________ +% +% spm_sections is called by spm_results and uses variables in SPM and +% VOL to create three orthogonal sections though a background image. +% Regional foci from the selected SPM are rendered on this image. +% +%_______________________________________________________________________ +% @(#)spm_sections.m 2.14 John Ashburner 02/09/05 + +Fgraph = gcf; + +spms = fullfile(spm('dir'),'canonical', 'single_subj_T1.mnc'); +if exist('targetFile') + spms = targetFile; +end + +spm_orthviews('Reset'); +global st +st.fig = Fgraph; +st.Space = spm_matrix([0 0 0 0 0 -pi/2])*st.Space; + +spm_orthviews('Image',spms,sectionViewPosition); % position +spm_orthviews('MaxBB'); +spm_orthviews('register',hReg); +if ~iscell(SPM) + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +elseif length(SPM) == 1 + SPM = SPM{1}; + spm_orthviews('addblobs',1,SPM.XYZ,SPM.Z,SPM.M); +else + colors = mycolourset; + for ii=1:length(SPM) + spm_orthviews('addcolouredblobs',1,SPM{ii}.XYZ, SPM{ii}.Z, SPM{ii}.M, colors(ii,:)); + end +end +spm_orthviews('Redraw'); + +hMe = st.registry.hMe; +try + hcolorbar = st.vols{1}.blobs{1}.cbar; +catch + hcolorbar = 0; +end + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% cuixuRenderView +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function h = cuixuRenderView(mniCoord, intensity, varargin) +% function h = cuixuRenderView(mniCoord1, intensity1, mniCoord2, intensity2, mniCoord3, intensity3) +% This is to project your coordinate to render view +% +% mniCoord: the mni coordinate, N*3 matrix +% intensity: the plot intensity of the spots, 1*N matrix. The intensity +% could be t value, for example. +% +% You can input 1, 2, or 3 pairs of coordinates and intensity. +% +% h: the returned handle for the figure +% +% Xu Cui +% 2004/11/11 + +global M_; +global DIM_; + +if nargin < 3 + dat.XYZ = mni2cor(mniCoord, M_); + dat.XYZ = dat.XYZ'; + if nargin < 2 + dat.t = ones(size(mniCoord,1),1); + else + dat.t = intensity; + end + dat.mat = M_; + dat.dim = DIM_; +else + if mod(nargin,2) ~=0 + disp('You should put even number of parameters.') + return; + end + for ii=1:(2+length(varargin))/2 + if ii==1 + dat(ii).XYZ = mni2cor(mniCoord, M_); + dat(ii).t = intensity; + else + dat(ii).XYZ = mni2cor(varargin{2*(ii-1)-1}, M_); + dat(ii).t = varargin{2*(ii-1)}; + end + dat(ii).XYZ = dat(ii).XYZ'; + dat(ii).mat = M_; + dat(ii).dim = DIM_; + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_render +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +h = spm_render(dat,1,fullfile(spm('dir'), 'rend', 'render_single_subj.mat')); +return + +function Fgraph = spm_render(dat,brt,rendfile) +% Render blobs on surface of a 'standard' brain +% FORMAT spm_render(dat,brt,rendfile) +% +% dat - a vertical cell array of length 1 to 3 +% - each element is a structure containing: +% - XYZ - the x, y & z coordinates of the transformed t values. +% in units of voxels. +% - t - the SPM{.} values +% - mat - affine matrix mapping from XYZ voxels to Talairach. +% - dim - dimensions of volume from which XYZ is drawn. +% brt - brightness control: +% If NaN, then displays using the old style with hot +% metal for the blobs, and grey for the brain. +% Otherwise, it is used as a ``gamma correction'' to +% optionally brighten the blobs up a little. +% rendfile - the file containing the images to render on to. See also +% spm_xbrain.m. +% +% Without arguments, spm_render acts as its own UI. +%_______________________________________________________________________ +% +% spm_render prompts for details of up to three SPM{Z}s or SPM{t}s that +% are then displayed superimposed on the surface of a standard brain. +% +% The first is shown in red, then green then blue. +% +% The blobs which are displayed are the integral of all transformed t +% values, exponentially decayed according to their depth. Voxels that +% are 10mm behind the surface have half the intensity of ones at the +% surface. +%_______________________________________________________________________ +% @(#)spm_render.m 2.19 John Ashburner FIL 02/10/29 + +%-Parse arguments, get data if not passed as parameters +%======================================================================= +if nargin < 1 + SPMid = spm('FnBanner',mfilename,'2.19'); + [Finter,Fgraph,CmdLine] = spm('FnUIsetup','Results: render',0); + + num = spm_input('Number of sets',1,'1 set|2 sets|3 sets',[1 2 3]); + + for i = 1:num, + [SPM,VOL] = spm_getSPM; + dat(i) = struct( 'XYZ', VOL.XYZ,... + 't', VOL.Z',... + 'mat', VOL.M,... + 'dim', VOL.DIM); + end; + showbar = 1; +else, + num = length(dat); + showbar = 0; +end; + +% get surface +%----------------------------------------------------------------------- +if nargin < 3, + rendfile = spm_get(1,'render*.mat','Render file',fullfile(spm('Dir'),'rend')); +end; + +% get brightness +%----------------------------------------------------------------------- +if nargin < 2, + brt = 1; + if num==1, + brt = spm_input('Style',1,'new|old',[1 NaN], 1); + end; + if finite(brt), + brt = spm_input('Brighten blobs',1,'none|slightly|more|lots',[1 0.75 0.5 0.25], 1); + end; +end; + + + +% Perform the rendering +%======================================================================= +spm('Pointer','Watch') + +load(rendfile); + +if (exist('rend') ~= 1), % Assume old format... + rend = cell(size(Matrixes,1),1); + for i=1:size(Matrixes,1), + rend{i}=struct('M',eval(Matrixes(i,:)),... + 'ren',eval(Rens(i,:)),... + 'dep',eval(Depths(i,:))); + rend{i}.ren = rend{i}.ren/max(max(rend{i}.ren)); + end; +end; + +if showbar, spm_progress_bar('Init', size(dat,1)*length(rend),... + 'Formatting Renderings', 'Number completed'); end; +for i=1:length(rend), + rend{i}.max=0; + rend{i}.data = cell(size(dat,1),1); + if issparse(rend{i}.ren), + % Assume that images have been DCT compressed + % - the SPM99 distribution was originally too big. + d = size(rend{i}.ren); + B1 = spm_dctmtx(d(1),d(1)); + B2 = spm_dctmtx(d(2),d(2)); + rend{i}.ren = B1*rend{i}.ren*B2'; + % the depths did not compress so well with + % a straight DCT - therefore it was modified slightly + rend{i}.dep = exp(B1*rend{i}.dep*B2')-1; + end; + msk = find(rend{i}.ren>1);rend{i}.ren(msk)=1; + msk = find(rend{i}.ren<0);rend{i}.ren(msk)=0; + if showbar, spm_progress_bar('Set', i); end; +end; +if showbar, spm_progress_bar('Clear'); end; + +if showbar, spm_progress_bar('Init', length(dat)*length(rend),... + 'Making pictures', 'Number completed'); end; + +mx = zeros(length(rend),1)+eps; +mn = zeros(length(rend),1); + +for j=1:length(dat), + XYZ = dat(j).XYZ; + t = dat(j).t; + dim = dat(j).dim; + mat = dat(j).mat; + + for i=1:length(rend), + + % transform from Taliarach space to space of the rendered image + %------------------------------------------------------- + M1 = rend{i}.M*dat(j).mat; + zm = sum(M1(1:2,1:3).^2,2).^(-1/2); + M2 = diag([zm' 1 1]); + M = M2*M1; + cor = [1 1 1 ; dim(1) 1 1 ; 1 dim(2) 1; dim(1) dim(2) 1 ; + 1 1 dim(3) ; dim(1) 1 dim(3) ; 1 dim(2) dim(3); dim(1) dim(2) dim(3)]'; + tcor= M(1:3,1:3)*cor + M(1:3,4)*ones(1,8); + off = min(tcor(1:2,:)'); + M2 = spm_matrix(-off+1)*M2; + M = M2*M1; + xyz = (M(1:3,1:3)*XYZ + M(1:3,4)*ones(1,size(XYZ,2))); + d2 = ceil(max(xyz(1:2,:)')); + + % calculate 'depth' of values + %------------------------------------------------------- + dep = spm_slice_vol(rend{i}.dep,spm_matrix([0 0 1])*inv(M2),d2,1); + z1 = dep(round(xyz(1,:))+round(xyz(2,:)-1)*size(dep,1)); + + if ~finite(brt), msk = find(xyz(3,:) < (z1+20) & xyz(3,:) > (z1-5)); + else, msk = find(xyz(3,:) < (z1+60) & xyz(3,:) > (z1-5)); end; + + if ~isempty(msk), + + % generate an image of the integral of the blob values. + %----------------------------------------------- + xyz = xyz(:,msk); + if ~finite(brt), t0 = t(msk); + else, dst = xyz(3,:) - z1(msk); + dst = max(dst,0); + t0 = t(msk).*exp((log(0.5)/10)*dst)'; + end; + X0 = full(sparse(round(xyz(1,:)), round(xyz(2,:)), t0, d2(1), d2(2))); + hld = 1; if ~finite(brt), hld = 0; end; + X = spm_slice_vol(X0,spm_matrix([0 0 1])*M2,size(rend{i}.dep),hld); + msk = find(X<0); + X(msk) = 0; + else, + X = zeros(size(rend{i}.dep)); + end; + + % Brighten the blobs + if finite(brt), X = X.^brt; end; + + mx(j) = max([mx(j) max(max(X))]); + mn(j) = min([mn(j) min(min(X))]); + + rend{i}.data{j} = X; + + if showbar, spm_progress_bar('Set', i+(j-1)*length(rend)); end; + end; +end; + +mxmx = max(mx); +mnmn = min(mn); + +if showbar, spm_progress_bar('Clear'); end; +Fgraph = gcf;%spm_figure('GetWin','Graphics'); +%spm_results_ui('Clear',Fgraph); + +nrow = ceil(length(rend)/2); +hght = 0.25; +width = 0.25; +x0 = 0.5; +y0 = 0.01; +% subplot('Position',[0, 0, 1, hght]); +ax=axes('Parent',Fgraph,'units','normalized','Position',[0, 0, 0.5, hght],'Visible','off'); +%ax=axes; +%image(0,'Parent',ax); +set(ax,'YTick',[],'XTick',[]); + +if ~finite(brt), + % Old style split colourmap display. + %--------------------------------------------------------------- + load Split; + colormap(split); + for i=1:length(rend), + ren = rend{i}.ren; + X = (rend{i}.data{1}-mnmn)/(mxmx-mnmn); + msk = find(X); + ren(msk) = X(msk)+(1+1.51/64); + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow, width, hght/nrow],... + 'Visible','off'); + image(ren*64,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],'XDir','normal','YDir','normal'); + end; +else, + % Combine the brain surface renderings with the blobs, and display using + % 24 bit colour. + %--------------------------------------------------------------- + for i=1:length(rend), + ren = rend{i}.ren; + X = cell(3,1); + for j=1:length(rend{i}.data), + X{j} = rend{i}.data{j}/(mxmx-mnmn)-mnmn; + end + for j=(length(rend{i}.data)+1):3 + X{j}=zeros(size(X{1})); + end + + rgb = zeros([size(ren) 3]); + tmp = ren.*max(1-X{1}-X{2}-X{3},0); + rgb(:,:,1) = tmp + X{1}; + rgb(:,:,2) = tmp + X{2}; + rgb(:,:,3) = tmp + X{3}; + + ax=axes('Parent',Fgraph,'units','normalized',... + 'Position',[x0+rem(i-1,2)*width, y0+floor((i-1)/2)*hght/nrow*2, width, hght/nrow*2],... + 'Visible','off'); + image(rgb,'Parent',ax); + set(ax,'DataAspectRatio',[1 1 1], ... + 'PlotBoxAspectRatioMode','auto',... + 'YTick',[],'XTick',[],... + 'XDir','normal','YDir','normal'); + end; +end; + +spm('Pointer') +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% spm_list +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function varargout = spm_list(varargin) +% Display and analysis of SPM{.} +% FORMAT TabDat = spm_list('List',SPM,hReg,[Num,Dis,Str]) +% Summary list of local maxima for entire volume of interest +% FORMAT TabDat = spm_list('ListCluster',SPM,hReg,[Num,Dis,Str]) +% List of local maxima for a single suprathreshold cluster +% +% SPM - structure containing SPM, distribution & filtering details +% - required fields are: +% .swd - SPM working directory - directory containing current SPM.mat +% .Z - minimum of n Statistics {filtered on u and k} +% .n - number of conjoint tests +% .STAT - distribution {Z, T, X or F} +% .df - degrees of freedom [df{interest}, df{residual}] +% .u - height threshold +% .k - extent threshold {voxels} +% .XYZ - location of voxels {voxel coords} +% .XYZmm - location of voxels {mm} +% .S - search Volume {voxels} +% .R - search Volume {resels} +% .FWHM - smoothness {voxels} +% .M - voxels - > mm matrix +% .VOX - voxel dimensions {mm} +% .Vspm - mapped statistic image(s) +% .Ps - uncorrected P values in searched volume (for FDR) +% +% (see spm_getSPM for further details of xSPM structures) +% +% hReg - Handle of results section XYZ registry (see spm_results_ui.m) +% +% Num - number of maxima per cluster +% Dis - distance among clusters (mm) +% Str - header string +% +% TabDat - Structure containing table data +% - fields are +% .tit - table Title (string) +% .hdr - table header (2x11 cell array) +% .fmt - fprintf format strings for table data (1x11 cell array) +% .str - table filtering note (string) +% .ftr - table footnote information (4x2 cell array) +% .dat - table data (Nx11 cell array) +% +% ---------------- +% +% FORMAT spm_list('TxtList',TabDat,c) +% Prints a tab-delimited text version of the table +% TabDat - Structure containing table data (format as above) +% c - Column of table data to start text table at +% (E.g. c=3 doesn't print set-level results contained in columns 1 & 2) +% ---------------- +% +% FORMAT spm_list('SetCoords',xyz,hAx,hC) +% Highlighting of table co-ordinates (used by results section registry) +% xyz - 3-vector of new co-ordinate +% hAx - table axis (the registry object for tables) +% hReg - Handle of caller (not used) +%_______________________________________________________________________ +% +% spm_list characterizes SPMs (thresholded at u and k) in terms of +% excursion sets (a collection of face, edge and vertex connected +% subsets or clusters). The currected significance of the results are +% based on set, cluster and voxel-level inferences using distributional +% approximations from the Theory of Gaussian Fields. These +% distributions assume that the SPM is a reasonable lattice +% approximation of a continuous random field with known component field +% smoothness. +% +% The p values are based on the probability of obtaining c, or more, +% clusters of k, or more, resels above u, in the volume S analysed = +% P(u,k,c). For specified thresholds u, k, the set-level inference is +% based on the observed number of clusters C, = P(u,k,C). For each +% cluster of size K the cluster-level inference is based on P(u,K,1) +% and for each voxel (or selected maxima) of height U, in that cluster, +% the voxel-level inference is based on P(U,0,1). All three levels of +% inference are supported with a tabular presentation of the p values +% and the underlying statistic: +% +% Set-level - c = number of suprathreshold clusters +% - P = prob(c or more clusters in the search volume) +% +% Cluster-level - k = number of voxels in this cluster +% - Pc = prob(k or more voxels in the search volume) +% - Pu = prob(k or more voxels in a cluster) +% +% Voxel-level - T/F = Statistic upon which the SPM is based +% - Ze = The eqivalent Z score - prob(Z > Ze) = prob(t > T) +% - Pc = prob(Ze or higher in the search volume) +% - Qu = Expd(Prop of false positives among voxels >= Ze) +% - Pu = prob(Ze or higher at that voxel) +% +% x,y,z (mm) - Coordinates of the voxel +% +% The table is grouped by regions and sorted on the Ze-variate of the +% primary maxima. Ze-variates (based on the uncorrected p value) are the +% Z score equivalent of the statistic. Volumes are expressed in voxels. +% +% Clicking on values in the table returns the value to the Matlab +% workspace. In addition, clicking on the co-ordinates jumps the +% results section cursor to that location. The table has a context menu +% (obtained by right-clicking in the background of the table), +% providing options to print the current table as a text table, or to +% extract the table data to the Matlab workspace. +% +%_______________________________________________________________________ +% @(#)spm_list.m 2.43 Karl Friston, Andrew Holmes 02/10/31 + + +% satellite figure global variable +%----------------------------------------------------------------------- +global SatWindow + +%======================================================================= +switch lower(varargin{1}), case 'list' %-List + %======================================================================= + % FORMAT TabDat = spm_list('list',SPM,hReg) + + %-Tolerance for p-value underflow, when computing equivalent Z's + %----------------------------------------------------------------------- + tol = eps*10; + + %-Parse arguments and set maxima number and separation + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + + + %-Get current location (to highlight selected voxel in table) + %----------------------------------------------------------------------- + %xyzmm = spm_results_ui('GetCoords'); + xyzmm = [0 0 0]'; + + %-Extract data from xSPM + %----------------------------------------------------------------------- + S = varargin{2}.S; + R = varargin{2}.R; + FWHM = varargin{2}.FWHM; + VOX = varargin{2}.VOX; + n = varargin{2}.n; + STAT = varargin{2}.STAT; + df = varargin{2}.df; + u = varargin{2}.u; + M = varargin{2}.M; + v2r = 1/prod(FWHM(~isinf(FWHM))); %-voxels to resels + k = varargin{2}.k*v2r; + QPs = varargin{2}.Ps; % Needed for FDR + QPs = sort(QPs(:)); + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 3; + Dis = 8; + end + if length(varargin) > 5 + + Title = varargin{6}; + else + Title = 'p-values adjusted for search volume'; + end + + + %-Setup graphics panel + %----------------------------------------------------------------------- + spm('Pointer','Watch') + if SatWindow + Fgraph = SatWindow; + figure(Fgraph); + else + Fgraph = figure('unit','normalized','position',[0.5,0.1,0.55,0.5],'Color','w',... + 'Name','volume', 'NumberTitle','off','resize','off','MenuBar','none'); + Fgraph = gcf; + end + %spm_results_ui('Clear',Fgraph) + FS = spm('FontSizes'); %-Scaled font sizes + PF = spm_platform('fonts'); %-Font names (for this platform) + + + %-Table header & footer + %======================================================================= + + %-Table axes & Title + %---------------------------------------------------------------------- + if SatWindow, ht = 0.85; bot = .14; else, ht = 0.8; bot = 0.15; end; + + if STAT == 'P' + Title = 'Posterior Probabilities'; + end + + hAx = axes('Position',[0.025 bot 0.9 ht],... + 'DefaultTextFontSize',FS(8),... + 'DefaultTextInterpreter','Tex',... + 'DefaultTextVerticalAlignment','Baseline',... + 'Units','points',... + 'Visible','off'); + + AxPos = get(hAx,'Position'); set(hAx,'YLim',[0,AxPos(4)]) + dy = FS(9); + y = floor(AxPos(4)) - dy; + + text(0,y,['Statistics: \it\fontsize{',num2str(FS(9)),'}',Title],... + 'FontSize',FS(11),'FontWeight','Bold'); y = y - dy/2; + line([0 1],[y y],'LineWidth',3,'Color','r'), y = y - 9*dy/8; + + + %-Construct table header + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,'DefaultTextFontSize',FS(8)) + + Hc = []; + Hp = []; + h = text(0.01,y, 'set-level','FontSize',FS(9)); Hc = [Hc,h]; + h = line([0,0.11],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); Hc = [Hc,h]; + h = text(0.08,y-9*dy/8, '\itc '); Hc = [Hc,h]; + h = text(0.02,y-9*dy/8, '\itp '); Hc = [Hc,h]; + Hp = [Hp,h]; + text(0.22,y, 'cluster-level','FontSize',FS(9)); + line([0.15,0.41],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.16,y-9*dy/8, '\itp \rm_{corrected}'); Hp = [Hp,h]; + h = text(0.33,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.26,y-9*dy/8, '\itk \rm_E'); + + text(0.60,y, 'voxel-level','FontSize',FS(9)); + line([0.46,0.86],[1,1]*(y-dy/4),'LineWidth',0.5,'Color','r'); + h = text(0.46,y-9*dy/8, '\itp \rm_{FWE-corr}'); Hp = [Hp,h]; + h = text(0.55,y-9*dy/8, '\itp \rm_{FDR-corr}'); Hp = [Hp,h]; + h = text(0.79,y-9*dy/8, '\itp \rm_{uncorrected}'); Hp = [Hp,h]; + h = text(0.64,y-9*dy/8, sprintf('\\it%c',STAT)); + h = text(0.72,y-9*dy/8, '(\itZ\rm_\equiv)'); + + text(0.93,y - dy/2,['x,y,z \fontsize{',num2str(FS(8)),'}\{mm\}']); + + + %-Headers for text table... + %----------------------------------------------------------------------- + TabDat.tit = Title; + TabDat.hdr = { 'set', 'c';... + 'set', 'p';... + 'cluster', 'p(cor)';... + 'cluster', 'equivk';... + 'cluster', 'p(unc)';... + 'voxel', 'p(FWE-cor)';... + 'voxel', 'p(FDR-cor)';... + 'voxel', STAT;... + 'voxel', 'equivZ';... + 'voxel', 'p(unc)';... + '', 'x,y,z {mm}'}';... + + TabDat.fmt = { '%-0.3f','%g',... %-Set + '%0.3f', '%0.0f', '%0.3f',... %-Cluster + '%0.3f', '%0.3f', '%6.2f', '%5.2f', '%0.3f',... %-Voxel + '%3.0f %3.0f %3.0f'}; %-XYZ + + %-Column Locations + %----------------------------------------------------------------------- + tCol = [ 0.00 0.07 ... %-Set + 0.16 0.26 0.34 ... %-Cluster + 0.46 0.55 0.62 0.71 0.80 ...%-Voxel + 0.92]; %-XYZ + + % move to next vertial postion marker + %----------------------------------------------------------------------- + y = y - 7*dy/4; + line([0 1],[y y],'LineWidth',1,'Color','r') + y = y - 5*dy/4; + y0 = y; + + + %-Table filtering note + %----------------------------------------------------------------------- + if isinf(Num) + TabDat.str = sprintf('table shows all local maxima > %.1fmm apart',Dis); + else + TabDat.str = sprintf(['table shows %d local maxima ',... + 'more than %.1fmm apart'],Num,Dis); + end + text(0.5,4,TabDat.str,'HorizontalAlignment','Center','FontName',PF.helvetica,... + 'FontSize',FS(8),'FontAngle','Italic') + + + %-Volume, resels and smoothness (if classical inference) + %----------------------------------------------------------------------- + line([0 1],[0 0],'LineWidth',1,'Color','r') + if STAT ~= 'P' + %----------------------------------------------------------------------- + FWHMmm = FWHM.*VOX; % FWHM {mm} + Pz = spm_P(1,0,u,df,STAT,1,n,S); + Pu = spm_P(1,0,u,df,STAT,R,n,S); + Qu = spm_P_FDR(u,df,STAT,n,QPs); + [P Pn Em En EN] = spm_P(1,k,u,df,STAT,R,n,S); + + + %-Footnote with SPM parameters + %----------------------------------------------------------------------- + set(gca,'DefaultTextFontName',PF.helvetica,... + 'DefaultTextInterpreter','None','DefaultTextFontSize',FS(8)) + TabDat.ftr = cell(5,2); + TabDat.ftr{1} = ... + sprintf('Height threshold: %c = %0.2f, p = %0.3f (%0.3f)',... + STAT,u,Pz,Pu); + TabDat.ftr{2} = ... + sprintf('Extent threshold: k = %0.0f voxels, p = %0.3f (%0.3f)',... + k/v2r,Pn,P); + TabDat.ftr{3} = ... + sprintf('Expected voxels per cluster, = %0.3f',En/v2r); + TabDat.ftr{4} = ... + sprintf('Expected number of clusters, = %0.2f',Em*Pn); + TabDat.ftr{5} = ... + sprintf('Expected false discovery rate, <= %0.2f',Qu); + TabDat.ftr{6} = ... + sprintf('Degrees of freedom = [%0.1f, %0.1f]',df); + TabDat.ftr{7} = ... + sprintf(['Smoothness FWHM = %0.1f %0.1f %0.1f {mm} ',... + ' = %0.1f %0.1f %0.1f {voxels}'],FWHMmm,FWHM); + TabDat.ftr{8} = ... + sprintf('Search vol: %0.0f cmm; %0.0f voxels; %0.1f resels',S*prod(VOX),S,R(end)); + TabDat.ftr{9} = ... + sprintf(['Voxel size: [%0.1f, %0.1f, %0.1f] mm ',... + ' (1 resel = %0.2f voxels)'],VOX,prod(FWHM)); + + text(0.0,-1*dy,TabDat.ftr{1},... + 'UserData',[u,Pz,Pu,Qu],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-2*dy,TabDat.ftr{2},... + 'UserData',[k/v2r,Pn,P],'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-3*dy,TabDat.ftr{3},... + 'UserData',En/v2r,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-4*dy,TabDat.ftr{4},... + 'UserData',Em*Pn,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.0,-5*dy,TabDat.ftr{5},... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-1*dy,TabDat.ftr{6},... + 'UserData',df,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-2*dy,TabDat.ftr{7},... + 'UserData',FWHMmm,'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-3*dy,TabDat.ftr{8},... + 'UserData',[S*prod(VOX),S,R(end)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + text(0.5,-4*dy,TabDat.ftr{9},... + 'UserData',[VOX,prod(FWHM)],... + 'ButtonDownFcn','get(gcbo,''UserData'')') + + end % Classical + + + %-Characterize excursion set in terms of maxima + % (sorted on Z values and grouped by regions) + %======================================================================= + if ~length(varargin{2}.Z) + text(0.5,y-6*dy,'no suprathreshold clusters',... + 'HorizontalAlignment','Center',... + 'FontAngle','Italic','FontWeight','Bold',... + 'FontSize',FS(16),'Color',[1,1,1]*.5); + TabDat.dat = cell(0,11); + varargout = {TabDat}; + spm('Pointer','Arrow') + return + end + + % Includes Darren Gitelman's code for working around + % spm_max for conjunctions with negative thresholds + %----------------------------------------------------------------------- + minz = abs(min(min(varargin{2}.Z))); + zscores = 1 + minz + varargin{2}.Z; + [N Z XYZ A] = spm_max(zscores,varargin{2}.XYZ); + Z = Z - minz - 1; + + %-Convert cluster sizes from voxels to resels + %----------------------------------------------------------------------- + if isfield(varargin{2},'VRvp') + V2R = spm_get_data(varargin{2}.VRvp,XYZ); + else + V2R = v2r; + end + N = N.*V2R; + + %-Convert maxima locations from voxels to mm + %----------------------------------------------------------------------- + XYZmm = M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + + + + %-Table proper (& note all data in cell array) + %======================================================================= + + %-Pagination variables + %----------------------------------------------------------------------- + hPage = []; + set(gca,'DefaultTextFontName',PF.courier,'DefaultTextFontSize',FS(7)) + + + %-Set-level p values {c} - do not display if reporting a single cluster + %----------------------------------------------------------------------- + c = max(A); %-Number of clusters + if STAT ~= 'P' + Pc = spm_P(c,k,u,df,STAT,R,n,S); %-Set-level p-value + else + Pc = []; + set(Hp,'Visible','off') + end + + if c > 1; + h = text(tCol(1),y,sprintf(TabDat.fmt{1},Pc),'FontWeight','Bold',... + 'UserData',Pc,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(2),y,sprintf(TabDat.fmt{2},c),'FontWeight','Bold',... + 'UserData',c,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + else + set(Hc,'Visible','off') + end + + TabDat.dat = {Pc,c}; %-Table data + TabLin = 1; %-Table data line + + + %-Local maxima p-values & statistics + %----------------------------------------------------------------------- + HlistXYZ = []; + while prod(size(find(finite(Z)))) + + % Paginate if necessary + %--------------------------------------------------------------- + if y < min(Num + 1,3)*dy + + % added Fgraph term to paginate on Satellite window + %------------------------------------------------------- + h = text(0.5,-5*dy,... + sprintf('Page %d',spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + %-Find largest remaining local maximum + %--------------------------------------------------------------- + [U,i] = max(Z); % largest maxima + j = find(A == A(i)); % maxima in cluster + + + %-Compute cluster {k} and voxel-level {u} p values for this cluster + %--------------------------------------------------------------- + Nv = N(i)/v2r; % extent {voxels} + + + if STAT ~= 'P' + Pz = spm_P(1,0, U,df,STAT,1,n,S);% uncorrected p value + Pu = spm_P(1,0, U,df,STAT,R,n,S);% FWE-corrected {based on Z) + Qu = spm_P_FDR( U,df,STAT,n,QPs);% FDR-corrected {based on Z) + [Pk Pn] = spm_P(1,N(i),u,df,STAT,R,n,S);% [un]corrected {based on k) + + if Pz < tol % Equivalent Z-variate + Ze = Inf; % (underflow => can't compute) + else + Ze = spm_invNcdf(1 - Pz); + end + else + Pz = []; + Pu = []; + Qu = []; + Pk = []; + Pn = []; + Ze = spm_invNcdf(U); + end + + + %-Print cluster and maximum voxel-level p values {Z} + %--------------------------------------------------------------- + h = text(tCol(3),y,sprintf(TabDat.fmt{3},Pk),'FontWeight','Bold',... + 'UserData',Pk,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(4),y,sprintf(TabDat.fmt{4},Nv),'FontWeight','Bold',... + 'UserData',Nv,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(5),y,sprintf(TabDat.fmt{5},Pn),'FontWeight','Bold',... + 'UserData',Pn,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),'FontWeight','Bold',... + 'UserData',Pu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),'FontWeight','Bold',... + 'UserData',Qu,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},U),'FontWeight','Bold',... + 'UserData',U,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),'FontWeight','Bold',... + 'UserData',Ze,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = ... + text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),'FontWeight','Bold',... + 'UserData',Pz,'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % Specifically changed so it properly finds hMIPax + %--------------------------------------------------------------------- + h = text(tCol(11),y,sprintf(TabDat.fmt{11},XYZmm(:,i)),... + 'FontWeight','Bold',... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,i)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,i)) Dis mm apart) + %--------------------------------------------------------------- + [l q] = sort(-Z(j)); % sort on Z value + D = i; + for i = 1:length(q) + d = j(q(i)); + if min(sqrt(sum((XYZmm(:,D)-XYZmm(:,d)*ones(1,size(D,2))).^2)))>Dis; + + if length(D) < Num + + % Paginate if necessary + %----------------------------------------------- + if y < dy + h = text(0.5,-5*dy,sprintf('Page %d',... + spm_figure('#page',Fgraph)),... + 'FontName',PF.helvetica,... + 'FontAngle','Italic',... + 'FontSize',FS(8)); + + spm_figure('NewPage',[hPage,h]) + hPage = []; + y = y0; + end + + % voxel-level p values {Z} + %----------------------------------------------- + if STAT ~= 'P' + Pz = spm_P(1,0,Z(d),df,STAT,1,n,S); + Pu = spm_P(1,0,Z(d),df,STAT,R,n,S); + Qu = spm_P_FDR(Z(d),df,STAT,n,QPs); + if Pz < tol + Ze = Inf; + else, Ze = spm_invNcdf(1 - Pz); end + else + Pz = []; + Pu = []; + Qu = []; + Ze = spm_invNcdf(Z(d)); + end + + h = text(tCol(6),y,sprintf(TabDat.fmt{6},Pu),... + 'UserData',Pu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + h = text(tCol(7),y,sprintf(TabDat.fmt{7},Qu),... + 'UserData',Qu,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(8),y,sprintf(TabDat.fmt{8},Z(d)),... + 'UserData',Z(d),... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(9),y,sprintf(TabDat.fmt{9},Ze),... + 'UserData',Ze,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + h = text(tCol(10),y,sprintf(TabDat.fmt{10},Pz),... + 'UserData',Pz,... + 'ButtonDownFcn','get(gcbo,''UserData'')'); + hPage = [hPage, h]; + + % specifically modified line to use hMIPax + %----------------------------------------------- + h = text(tCol(11),y,... + sprintf(TabDat.fmt{11},XYZmm(:,d)),... + 'Tag','ListXYZ',... + 'ButtonDownFcn',[... + 'hMIPax = findobj(''tag'',''hMIPax'');',... + 'spm_mip_ui(''SetCoords'',',... + 'get(gcbo,''UserData''),hMIPax);'],... + 'Interruptible','off','BusyAction','Cancel',... + 'UserData',XYZmm(:,d)); + + HlistXYZ = [HlistXYZ, h]; + if spm_XYZreg('Edist',xyzmm,XYZmm(:,d))1 + h = text(0.5,-5*dy,sprintf('Page %d/%d',spm_figure('#page',Fgraph)*[1,1]),... + 'FontName',PF.helvetica,'FontSize',FS(8),'FontAngle','Italic'); + spm_figure('NewPage',[hPage,h]) + end + + %-End: Store TabDat in UserData of axes & reset pointer + %======================================================================= + h = uicontextmenu('Tag','TabDat',... + 'UserData',TabDat); + set(gca,'UIContextMenu',h,... + 'Visible','on',... + 'XColor','w','YColor','w') + uimenu(h,'Label','Table') + uimenu(h,'Separator','on','Label','Print text table',... + 'Tag','TD_TxtTab',... + 'CallBack',... + 'spm_list(''txtlist'',get(get(gcbo,''Parent''),''UserData''),3)',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','off','Label','Extract table data structure',... + 'Tag','TD_Xdat',... + 'CallBack','get(get(gcbo,''Parent''),''UserData'')',... + 'Interruptible','off','BusyAction','Cancel'); + uimenu(h,'Separator','on','Label','help',... + 'Tag','TD_Xdat',... + 'CallBack','spm_help(''spm_list'')',... + 'Interruptible','off','BusyAction','Cancel'); + + %-Setup registry + %----------------------------------------------------------------------- + set(hAx,'UserData',struct('hReg',hReg,'HlistXYZ',HlistXYZ)) + spm_XYZreg('Add2Reg',hReg,hAx,'spm_list'); + + %-Return TabDat structure & reset pointer + %----------------------------------------------------------------------- + varargout = {TabDat}; + spm('Pointer','Arrow') + + + + + + %======================================================================= + case 'listcluster' %-List for current cluster only + %======================================================================= + % FORMAT TabDat = spm_list('listcluster',SPM,hReg) + + spm('Pointer','Watch') + + %-Parse arguments + %----------------------------------------------------------------------- + if nargin < 2, error('insufficient arguments'), end + if nargin < 3, hReg = []; else, hReg = varargin{3}; end + SPM = varargin{2}; + + %-get number and separation for maxima to be reported + %----------------------------------------------------------------------- + if length(varargin) > 3 + + Num = varargin{4}; % number of maxima per cluster + Dis = varargin{5}; % distance among clusters (mm) + else + Num = 32; + Dis = 4; + end + + + %-if there are suprathreshold voxels, filter out all but current cluster + %----------------------------------------------------------------------- + if length(SPM.Z) + + %-Jump to voxel nearest current location + %-------------------------------------------------------------- + [xyzmm,i] = spm_XYZreg('NearestXYZ',... + spm_results_ui('GetCoords'),SPM.XYZmm); + spm_results_ui('SetCoords',SPM.XYZmm(:,i)); + + %-Find selected cluster + %-------------------------------------------------------------- + A = spm_clusters(SPM.XYZ); + j = find(A == A(i)); + SPM.Z = SPM.Z(j); + SPM.XYZ = SPM.XYZ(:,j); + SPM.XYZmm = SPM.XYZmm(:,j); + if isfield(SPM,'Rd'), SPM.Rd = SPM.Rd(:,j); end + end + + %-Call 'list' functionality to produce table + %----------------------------------------------------------------------- + varargout = {spm_list('list',SPM,hReg,Num,Dis)}; + + + + + + %======================================================================= + case 'txtlist' %-Print ASCII text table + %======================================================================= + % FORMAT spm_list('TxtList',TabDat,c) + + if nargin<2, error('Insufficient arguments'), end + if nargin<3, c=1; else, c=varargin{3}; end + TabDat = varargin{2}; + + %-Table Title + %----------------------------------------------------------------------- + fprintf('\n\nSTATISTICS: %s\n',TabDat.tit) + fprintf('%c','='*ones(1,80)), fprintf('\n') + + %-Table header + %----------------------------------------------------------------------- + fprintf('%s\t',TabDat.hdr{1,c:end-1}), fprintf('%s\n',TabDat.hdr{1,end}) + fprintf('%s\t',TabDat.hdr{2,c:end-1}), fprintf('%s\n',TabDat.hdr{2,end}) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table data + %----------------------------------------------------------------------- + for i = 1:size(TabDat.dat,1) + for j=c:size(TabDat.dat,2) + fprintf(TabDat.fmt{j},TabDat.dat{i,j}) + fprintf('\t') + end + fprintf('\n') + end + for i=1:max(1,11-size(TabDat.dat,1)), fprintf('\n'), end + fprintf('%s\n',TabDat.str) + fprintf('%c','-'*ones(1,80)), fprintf('\n') + + %-Table footer + %----------------------------------------------------------------------- + fprintf('%s\n',TabDat.ftr{:}) + fprintf('%c','='*ones(1,80)), fprintf('\n\n') + + + + %======================================================================= + case 'setcoords' %-Co-ordinate change + %======================================================================= + % FORMAT spm_list('SetCoords',xyz,hAx,hReg) + if nargin<3, error('Insufficient arguments'), end + hAx = varargin{3}; + xyz = varargin{2}; + UD = get(hAx,'UserData'); + HlistXYZ = UD.HlistXYZ(ishandle(UD.HlistXYZ)); + + %-Set all co-ord strings to black + %----------------------------------------------------------------------- + set(HlistXYZ,'Color','k') + + %-If co-ord matches a string, highlight it in red + %----------------------------------------------------------------------- + XYZ = get(HlistXYZ,'UserData'); + if iscell(XYZ), XYZ = cat(2,XYZ{:}); end + [null,i,d] = spm_XYZreg('NearestXYZ',xyz,XYZ); + if d=2, st.vols{H}.area = varargin{2}; end; + if isempty(st.bb), st.bb = maxbb; end; + bbox; + cm_pos; + end; + varargout{1} = H; + st.centre = mean(maxbb); + redraw_all + + case 'bb', + if length(varargin)> 0 & all(size(varargin{1})==[2 3]), st.bb = varargin{1}; end; + bbox; + redraw_all; + + case 'redraw', + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + + case 'reposition', + if length(varargin)<1, tmp = findcent; + else, tmp = varargin{1}; end; + if length(tmp)==3 + h = valid_handles(st.snap); + if ~isempty(h) + tmp=st.vols{h(1)}.mat*... + round(inv(st.vols{h(1)}.mat)*[tmp; ... + 1]); + end; + st.centre = tmp(1:3); + end; + redraw_all; + eval(st.callback); + if isfield(st,'registry'), + spm_XYZreg('SetCoords',st.centre,st.registry.hReg,st.registry.hMe); + end; + cm_pos; + + case 'setcoords', + st.centre = varargin{1}; + st.centre = st.centre(:); + redraw_all; + eval(st.callback); + cm_pos; + + case 'space', + if length(varargin)<1, + st.Space = eye(4); + st.bb = maxbb; + bbox; + redraw_all; + else, + space(varargin{1}); + bbox; + redraw_all; + end; + + case 'maxbb', + st.bb = maxbb; + bbox; + redraw_all; + + case 'resolution', + resolution(varargin{1}); + bbox; + redraw_all; + + case 'window', + if length(varargin)<2, + win = 'auto'; + elseif length(varargin{2})==2, + win = varargin{2}; + end; + for i=valid_handles(varargin{1}), + st.vols{i}.window = win; + end; + redraw(varargin{1}); + + case 'delete', + my_delete(varargin{1}); + + case 'move', + move(varargin{1},varargin{2}); + % redraw_all; + + case 'reset', + my_reset; + + case 'pos', + if isempty(varargin), + H = st.centre(:); + else, + H = pos(varargin{1}); + end; + varargout{1} = H; + + case 'interp', + st.hld = varargin{1}; + redraw_all; + + case 'xhairs', + xhairs(varargin{1}); + + case 'register', + register(varargin{1}); + + case 'addblobs', + addblobs(varargin{1}, varargin{2},varargin{3},varargin{4}); + % redraw(varargin{1}); + + case 'addcolouredblobs', + addcolouredblobs(varargin{1}, varargin{2},varargin{3},varargin{4},varargin{5}); + % redraw(varargin{1}); + + case 'addimage', + addimage(varargin{1}, varargin{2}); + % redraw(varargin{1}); + + case 'addcolouredimage', + addcolouredimage(varargin{1}, varargin{2},varargin{3}); + % redraw(varargin{1}); + + case 'addtruecolourimage', + % spm_orthviews('Addtruecolourimage',handle,filename,colourmap,prop,mx,mn) + % Adds blobs from an image in true colour + % handle - image number to add blobs to [default 1] + % filename of image containing blob data [default - request via GUI] + % colourmap - colormap to display blobs in [GUI input] + % prop - intensity proportion of activation cf grayscale [0.4] + % mx - maximum intensity to scale to [maximum value in activation image] + % mn - minimum intensity to scale to [minimum value in activation image] + % + if nargin < 2 + varargin(1) = {1}; + end + if nargin < 3 + varargin(2) = {spm_select(1, 'image', 'Image with activation signal')}; + end + if nargin < 4 + actc = []; + while isempty(actc) + actc = getcmap(spm_input('Colourmap for activation image', '+1','s')); + end + varargin(3) = {actc}; + end + if nargin < 5 + varargin(4) = {0.4}; + end + if nargin < 6 + actv = spm_vol(varargin{2}); + varargin(5) = {max([eps maxval(actv)])}; + end + if nargin < 7 + varargin(6) = {min([0 minval(actv)])}; + end + + addtruecolourimage(varargin{1}, varargin{2},varargin{3}, varargin{4}, ... + varargin{5}, varargin{6}); + % redraw(varargin{1}); + + case 'addcolourbar', + addcolourbar(varargin{1}, varargin{2}); + + case 'rmblobs', + rmblobs(varargin{1}); + % redraw(varargin{1}); + + case 'addcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + addcontexts(handles); + + case 'rmcontext', + if nargin == 1, + handles = 1:24; + else, + handles = varargin{1}; + end; + rmcontexts(handles); + + case 'context_menu', + c_menu(varargin{:}); + + case 'valid_handles', + if nargin == 1 + handles = 1:24; + else, + handles = varargin{1}; + end; + varargout{1} = valid_handles(handles); + + otherwise, + addonaction = strcmp(st.plugins,action); + if any(addonaction) + feval(['spm_ov_' st.plugins{addonaction}],varargin{:}); + else + warning('Unknown action string') + end; +end; + +spm('Pointer'); +return; + + +%_______________________________________________________________________ +%_______________________________________________________________________ +function addblobs(handle, xyz, t, mat) +global st +global TMAX_ +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + st.vols{i}.blobs=cell(1,1); + if st.mode == 0, + axpos = get(st.vols{i}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{i}.ax{1}.ax,'Position'); + end; + mx = max([eps max(t)]); + mn = min([0 min(t)]); + if ~strcmp(TMAX_, 'auto') + mx = str2num(TMAX_); + end + %KND: + if numel(mx)==2 + mn=mx(1); + mx=mx(2); + end + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx, 'min',mn); + addcolourbar(handle,1); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addimage(handle, fname) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + st.vols{i}.blobs=cell(1,1); + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{1} = struct('vol',vol,'mat',mat,'max',mx,'min',mn); + addcolourbar(handle,1); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredblobs(handle, xyz, t, mat,colour) +global st +for i=valid_handles(handle), + if ~isempty(xyz), + rcp = round(xyz); + dim = max(rcp,[],2)'; + off = rcp(1,:) + dim(1)*(rcp(2,:)-1 + dim(2)*(rcp(3,:)-1)); + vol = zeros(dim)+NaN; + vol(off) = t; + vol = reshape(vol,dim); + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolouredimage(handle, fname,colour) +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + mx = max([eps maxval(vol)]); + mn = min([0 minval(vol)]); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx,'min',mn,'colour',colour); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addtruecolourimage(handle,fname,colourmap,prop,mx,mn) +% adds true colour image to current displayed image +global st +for i=valid_handles(handle), + if isstruct(fname), + vol = fname(1); + else, + vol = spm_vol(fname); + end; + mat = vol.mat; + if ~isfield(st.vols{i},'blobs'), + st.vols{i}.blobs=cell(1,1); + bset = 1; + else, + bset = length(st.vols{i}.blobs)+1; + end; + c = struct('cmap', colourmap,'prop',prop); + st.vols{i}.blobs{bset} = struct('vol',vol,'mat',mat,'max',mx, ... + 'min',mn,'colour',c); + addcolourbar(handle,bset); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcolourbar(vh,bh) +global st +if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); +else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); +end; +st.vols{vh}.blobs{bh}.cbar = axes('Parent',st.fig,... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1) (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'Box','on', 'YDir','normal', 'XTickLabel',[], 'XTick',[]); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmblobs(handle) +global st +for i=valid_handles(handle), + if isfield(st.vols{i},'blobs'), + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'cbar') & ishandle(st.vols{i}.blobs{j}.cbar), + delete(st.vols{i}.blobs{j}.cbar); + end; + end; + st.vols{i} = rmfield(st.vols{i},'blobs'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function register(hreg) +global st +tmp = uicontrol('Position',[0 0 1 1],'Visible','off','Parent',st.fig); +h = valid_handles(1:24); +if ~isempty(h), + tmp = st.vols{h(1)}.ax{1}.ax; + st.registry = struct('hReg',hreg,'hMe', tmp); + spm_XYZreg('Add2Reg',st.registry.hReg,st.registry.hMe, 'spm_orthviews'); +else, + warning('Nothing to register with'); +end; +st.centre = spm_XYZreg('GetCoords',st.registry.hReg); +st.centre = st.centre(:); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function xhairs(arg1), +global st +st.xhairs = 0; +opt = 'on'; +if ~strcmp(arg1,'on'), + opt = 'off'; +else, + st.xhairs = 1; +end; +for i=valid_handles(1:24), + for j=1:3, + set(st.vols{i}.ax{j}.lx,'Visible',opt); + set(st.vols{i}.ax{j}.ly,'Visible',opt); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = pos(arg1) +global st +H = []; +for arg1=valid_handles(arg1), + is = inv(st.vols{arg1}.premul*st.vols{arg1}.mat); + H = is(1:3,1:3)*st.centre(:) + is(1:3,4); +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_reset +global st +if ~isempty(st) & isfield(st,'registry') & ishandle(st.registry.hMe), + delete(st.registry.hMe); st = rmfield(st,'registry'); +end; +my_delete(1:24); +reset_st; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function my_delete(arg1) +global st +for i=valid_handles(arg1), + kids = get(st.fig,'Children'); + for j=1:3, + if any(kids == st.vols{i}.ax{j}.ax), + set(get(st.vols{i}.ax{j}.ax,'Children'),'DeleteFcn',''); + delete(st.vols{i}.ax{j}.ax); + end; + end; + st.vols{i} = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function resolution(arg1) +global st +res = arg1/mean(svd(st.Space(1:3,1:3))); +Mat = diag([res res res 1]); +st.Space = st.Space*Mat; +st.bb = st.bb/res; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function move(handle,pos) +global st +for handle = valid_handles(handle), + st.vols{handle}.area = pos; +end; +bbox; +% redraw(valid_handles(handle)); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bb = maxbb +global st +mn = [Inf Inf Inf]; +mx = -mn; +for i=valid_handles(1:24), + bb = [[1 1 1];st.vols{i}.dim(1:3)]; + c = [ bb(1,1) bb(1,2) bb(1,3) 1 + bb(1,1) bb(1,2) bb(2,3) 1 + bb(1,1) bb(2,2) bb(1,3) 1 + bb(1,1) bb(2,2) bb(2,3) 1 + bb(2,1) bb(1,2) bb(1,3) 1 + bb(2,1) bb(1,2) bb(2,3) 1 + bb(2,1) bb(2,2) bb(1,3) 1 + bb(2,1) bb(2,2) bb(2,3) 1]'; + tc = st.Space\(st.vols{i}.premul*st.vols{i}.mat)*c; + tc = tc(1:3,:)'; + mx = max([tc ; mx]); + mn = min([tc ; mn]); +end; +bb = [mn ; mx]; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function space(arg1) +global st +if ~isempty(st.vols{arg1}) + num = arg1; + Mat = st.vols{num}.premul(1:3,1:3)*st.vols{num}.mat(1:3,1:3); + vox = sqrt(sum(Mat.^2)); + if det(Mat(1:3,1:3))<0, vox(1) = -vox(1); end; + Mat = diag([vox 1]); + Space = (st.vols{num}.mat)/Mat; + bb = [1 1 1;st.vols{num}.dim(1:3)]; + bb = [bb [1;1]]; + bb=bb*Mat'; + bb=bb(:,1:3); + bb=sort(bb); + st.Space = Space; + st.bb = bb; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function H = specify_image(arg1, arg2) +global st +H=[]; +ok = 1; +if isstruct(arg1), + V = arg1(1); +else, + try, + V = spm_vol(arg1); + catch, + fprintf('Can not use image "%s"\n', arg1); + return; + end; +end; + +ii = 1; +while ~isempty(st.vols{ii}), ii = ii + 1; end; + +DeleteFcn = ['spm_orthviews(''Delete'',' num2str(ii) ');']; +V.ax = cell(3,1); +for i=1:3, + ax = axes('Visible','off','DrawMode','fast','Parent',st.fig,'DeleteFcn',DeleteFcn,... + 'YDir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''Reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + d = image(0,'Tag','Transverse','Parent',ax,... + 'DeleteFcn',DeleteFcn); + set(ax,'Ydir','normal','ButtonDownFcn',... + ['if strcmp(get(gcf,''SelectionType''),''normal''),spm_orthviews(''Reposition'');',... + 'elseif strcmp(get(gcf,''SelectionType''),''extend''),spm_orthviews(''reposition'');',... + 'spm_orthviews(''context_menu'',''ts'',1);end;']); + + lx = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + ly = line(0,0,'Parent',ax,'DeleteFcn',DeleteFcn); + if ~st.xhairs, + set(lx,'Visible','off'); + set(ly,'Visible','off'); + end; + V.ax{i} = struct('ax',ax,'d',d,'lx',lx,'ly',ly); +end; +V.premul = eye(4); +V.window = 'auto'; +V.mapping = 'linear'; +st.vols{ii} = V; + +H = ii; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function addcontexts(handles) +global st +for ii = valid_handles(handles), + cm_handle = addcontext(ii); + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',cm_handle); + st.vols{ii}.ax{i}.cm = cm_handle; + end; +end; +spm_orthviews('reposition',spm_orthviews('pos')); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function rmcontexts(handles) +global st +for ii = valid_handles(handles), + for i=1:3, + set(st.vols{ii}.ax{i}.ax,'UIcontextmenu',[]); + st.vols{ii}.ax{i} = rmfield(st.vols{ii}.ax{i},'cm'); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function bbox +global st +Dims = diff(st.bb)'+1; + +TD = Dims([1 2])'; +CD = Dims([1 3])'; +if st.mode == 0, SD = Dims([3 2])'; else, SD = Dims([2 3])'; end; + +un = get(st.fig,'Units');set(st.fig,'Units','Pixels'); +sz = get(st.fig,'Position');set(st.fig,'Units',un); +sz = sz(3:4); +sz(2) = sz(2)-40; + +for i=valid_handles(1:24), + area = st.vols{i}.area(:); + area = [area(1)*sz(1) area(2)*sz(2) area(3)*sz(1) area(4)*sz(2)]; + if st.mode == 0, + sx = area(3)/(Dims(1)+Dims(3))/1.02; + else, + sx = area(3)/(Dims(1)+Dims(2))/1.02; + end; + sy = area(4)/(Dims(2)+Dims(3))/1.02; + s = min([sx sy]); + + offy = (area(4)-(Dims(2)+Dims(3))*1.02*s)/2 + area(2); + sky = s*(Dims(2)+Dims(3))*0.02; + if st.mode == 0, + offx = (area(3)-(Dims(1)+Dims(3))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(3))*0.02; + else, + offx = (area(3)-(Dims(1)+Dims(2))*1.02*s)/2 + area(1); + skx = s*(Dims(1)+Dims(2))*0.02; + end; + + DeleteFcn = ['spm_orthviews(''Delete'',' num2str(i) ');']; + + % Transverse + set(st.vols{i}.ax{1}.ax,'Units','pixels', ... + 'Position',[offx offy s*Dims(1) s*Dims(2)],... + 'Units','normalized','Xlim',[0 TD(1)]+0.5,'Ylim',[0 TD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Coronal + set(st.vols{i}.ax{2}.ax,'Units','Pixels',... + 'Position',[offx offy+s*Dims(2)+sky s*Dims(1) s*Dims(3)],... + 'Units','normalized','Xlim',[0 CD(1)]+0.5,'Ylim',[0 CD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + + % Sagittal + if st.mode == 0, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy s*Dims(3) s*Dims(2)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + else, + set(st.vols{i}.ax{3}.ax,'Units','Pixels', 'Box','on',... + 'Position',[offx+s*Dims(1)+skx offy+s*Dims(2)+sky s*Dims(2) s*Dims(3)],... + 'Units','normalized','Xlim',[0 SD(1)]+0.5,'Ylim',[0 SD(2)]+0.5,... + 'Visible','on','XTick',[],'YTick',[]); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_all +global st +redraw(1:24); +return; +%_______________________________________________________________________ +function mx = maxval(vol) +if isstruct(vol), + mx = -Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imx = max(tmp(find(finite(tmp)))); + if ~isempty(imx),mx = max(mx,imx);end + end; +else, + mx = max(vol(find(finite(vol)))); +end; +%_______________________________________________________________________ +function mn = minval(vol) +if isstruct(vol), + mn = Inf; + for i=1:vol.dim(3), + tmp = spm_slice_vol(vol,spm_matrix([0 0 i]),vol.dim(1:2),0); + imn = min(tmp(find(finite(tmp)))); + if ~isempty(imn),mn = min(mn,imn);end + end; +else, + mn = min(vol(find(finite(vol)))); +end; + +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw(arg1) +global st +bb = st.bb; +Dims = round(diff(bb)'+1); +is = inv(st.Space); +cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + +for i = valid_handles(arg1), + M = st.vols{i}.premul*st.vols{i}.mat; + TM0 = [ 1 0 0 -bb(1,1)+1 + 0 1 0 -bb(1,2)+1 + 0 0 1 -cent(3) + 0 0 0 1]; + TM = inv(TM0*(st.Space\M)); + TD = Dims([1 2]); + + CM0 = [ 1 0 0 -bb(1,1)+1 + 0 0 1 -bb(1,3)+1 + 0 1 0 -cent(2) + 0 0 0 1]; + CM = inv(CM0*(st.Space\M)); + CD = Dims([1 3]); + + if st.mode ==0, + SM0 = [ 0 0 1 -bb(1,3)+1 + 0 1 0 -bb(1,2)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); SD = Dims([3 2]); + else, + SM0 = [ 0 1 0 -bb(1,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM0 = [ 0 -1 0 +bb(2,2)+1 + 0 0 1 -bb(1,3)+1 + 1 0 0 -cent(1) + 0 0 0 1]; + SM = inv(SM0*(st.Space\M)); + SD = Dims([2 3]); + end; + + ok=1; + eval('imgt = (spm_slice_vol(st.vols{i},TM,TD,st.hld))'';','ok=0;'); + eval('imgc = (spm_slice_vol(st.vols{i},CM,CD,st.hld))'';','ok=0;'); + eval('imgs = (spm_slice_vol(st.vols{i},SM,SD,st.hld))'';','ok=0;'); + if (ok==0), fprintf('Image "%s" can not be resampled\n', st.vols{i}.fname); + else, + % get min/max threshold + if strcmp(st.vols{i}.window,'auto') + mn = -Inf; + mx = Inf; + else + mn = min(st.vols{i}.window); + mx = max(st.vols{i}.window); + end; + % threshold images + imgt = max(imgt,mn); imgt = min(imgt,mx); + imgc = max(imgc,mn); imgc = min(imgc,mx); + imgs = max(imgs,mn); imgs = min(imgs,mx); + % compute intensity mapping, if histeq is available + if license('test','image_toolbox') == 0 + st.vols{i}.mapping = 'linear'; + end; + switch st.vols{i}.mapping, + case 'linear', + case 'histeq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'quadhisteq', + % scale images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:).^2; imgc1(:).^2; imgs1(:).^2],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + case 'loghisteq', + warning off % messy - but it may avoid extra queries + imgt = log(imgt-min(imgt(:))); + imgc = log(imgc-min(imgc(:))); + imgs = log(imgs-min(imgs(:))); + warning on + imgt(~isfinite(imgt)) = 0; + imgc(~isfinite(imgc)) = 0; + imgs(~isfinite(imgs)) = 0; + % scale log images to a range between 0 and 1 + imgt1=(imgt-min(imgt(:)))/(max(imgt(:)-min(imgt(:)))+eps); + imgc1=(imgc-min(imgc(:)))/(max(imgc(:)-min(imgc(:)))+eps); + imgs1=(imgs-min(imgs(:)))/(max(imgs(:)-min(imgs(:)))+eps); + img = histeq([imgt1(:); imgc1(:); imgs1(:)],1024); + imgt = reshape(img(1:numel(imgt1)),size(imgt1)); + imgc = reshape(img(numel(imgt1)+[1:numel(imgc1)]),size(imgc1)); + imgs = reshape(img(numel(imgt1)+numel(imgc1)+[1:numel(imgs1)]),size(imgs1)); + mn = 0; + mx = 1; + end; + % recompute min/max for display + if strcmp(st.vols{i}.window,'auto') + mx = -inf; mn = inf; + end; + if ~isempty(imgt), + tmp = imgt(finite(imgt)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgc), + tmp = imgc(finite(imgc)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if ~isempty(imgs), + tmp = imgs(finite(imgs)); + mx = max([mx max(max(tmp))]); + mn = min([mn min(min(tmp))]); + end; + if mx==mn, mx=mn+eps; end; + + if isfield(st.vols{i},'blobs'), + if ~isfield(st.vols{i}.blobs{1},'colour'), + % Add blobs for display using the split colourmap + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + + if isfield(st.vols{i}.blobs{1},'max'), + mx = st.vols{i}.blobs{1}.max; + else, + mx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.max = mx; + end; + if isfield(st.vols{i}.blobs{1},'min'), + mn = st.vols{i}.blobs{1}.min; + else, + mn = min([0 minval(st.vols{i}.blobs{1}.vol)]); + st.vols{i}.blobs{1}.min = mn; + end; + + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + %tmpt_z = find(tmpt==0);tmpt(tmpt_z) = NaN; + %tmpc_z = find(tmpc==0);tmpc(tmpc_z) = NaN; + %tmps_z = find(tmps==0);tmps(tmps_z) = NaN; + + sc = 64/(mx-mn); + off = 65.51-mn*sc; + msk = find(finite(tmpt)); imgt(msk) = off+tmpt(msk)*sc; + msk = find(finite(tmpc)); imgc(msk) = off+tmpc(msk)*sc; + msk = find(finite(tmps)); imgs(msk) = off+tmps(msk)*sc; + + cmap = get(st.fig,'Colormap'); + + figure(st.fig) + if mn*mx < 0 + setcolormap('gray-hot-cold') + elseif mx > 0 + setcolormap('gray-hot'); + else + setcolormap('gray-cold') + end + redraw_colourbar(i,1,[mn mx],[1:64]'+64); + elseif isstruct(st.vols{i}.blobs{1}.colour), + % Add blobs for display using a defined + % colourmap + + % colourmaps + gryc = [0:63]'*ones(1,3)/63; + actc = ... + st.vols{1}.blobs{1}.colour.cmap; + actp = ... + st.vols{1}.blobs{1}.colour.prop; + + % scale grayscale image, not finite -> black + imgt = scaletocmap(imgt,mn,mx,gryc,65); + imgc = scaletocmap(imgc,mn,mx,gryc,65); + imgs = scaletocmap(imgs,mn,mx,gryc,65); + gryc = [gryc; 0 0 0]; + + % get max for blob image + vol = st.vols{i}.blobs{1}.vol; + mat = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + if isfield(st.vols{i}.blobs{1},'max'), + cmx = st.vols{i}.blobs{1}.max; + else, + cmx = max([eps maxval(st.vols{i}.blobs{1}.vol)]); + end; + if isfield(st.vols{i}.blobs{1},'min'), + cmn = st.vols{i}.blobs{1}.min; + else, + cmn = -cmx; + end; + + % get blob data + vol = st.vols{i}.blobs{1}.vol; + M = st.vols{i}.premul*st.vols{i}.blobs{1}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*(st.Space\M)),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*(st.Space\M)),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*(st.Space\M)),SD,[0 NaN])'; + + % actimg scaled round 0, black NaNs + topc = size(actc,1)+1; + tmpt = scaletocmap(tmpt,cmn,cmx,actc,topc); + tmpc = scaletocmap(tmpc,cmn,cmx,actc,topc); + tmps = scaletocmap(tmps,cmn,cmx,actc,topc); + actc = [actc; 0 0 0]; + + % combine gray and blob data to + % truecolour + imgt = reshape(actc(tmpt(:),:)*actp+ ... + gryc(imgt(:),:)*(1-actp), ... + [size(imgt) 3]); + imgc = reshape(actc(tmpc(:),:)*actp+ ... + gryc(imgc(:),:)*(1-actp), ... + [size(imgc) 3]); + imgs = reshape(actc(tmps(:),:)*actp+ ... + gryc(imgs(:),:)*(1-actp), ... + [size(imgs) 3]); + + redraw_colourbar(i,1,[cmn cmx],[1:64]'+64); + + else, + % Add full colour blobs - several sets at once + scal = 1/(mx-mn); + dcoff = -mn*scal; + + wt = zeros(size(imgt)); + wc = zeros(size(imgc)); + ws = zeros(size(imgs)); + + imgt = repmat(imgt*scal+dcoff,[1,1,3]); + imgc = repmat(imgc*scal+dcoff,[1,1,3]); + imgs = repmat(imgs*scal+dcoff,[1,1,3]); + + cimgt = zeros(size(imgt)); + cimgc = zeros(size(imgc)); + cimgs = zeros(size(imgs)); + + for j=1:length(st.vols{i}.blobs), % get colours of all images first + if isfield(st.vols{i}.blobs{j},'colour'), + colour(j,:) = reshape(st.vols{i}.blobs{j}.colour, [1 3]); + else, + colour(j,:) = [1 0 0]; + end; + end; + %colour = colour/max(sum(colour)); + + for j=1:length(st.vols{i}.blobs), + if isfield(st.vols{i}.blobs{j},'max'), + mx = st.vols{i}.blobs{j}.max; + else, + mx = max([eps max(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.max = mx; + end; + if isfield(st.vols{i}.blobs{j},'min'), + mn = st.vols{i}.blobs{j}.min; + else, + mn = min([0 min(st.vols{i}.blobs{j}.vol(:))]); + st.vols{i}.blobs{j}.min = mn; + end; + + vol = st.vols{i}.blobs{j}.vol; + M = st.Space\st.vols{i}.premul*st.vols{i}.blobs{j}.mat; + tmpt = spm_slice_vol(vol,inv(TM0*M),TD,[0 NaN])'; + tmpc = spm_slice_vol(vol,inv(CM0*M),CD,[0 NaN])'; + tmps = spm_slice_vol(vol,inv(SM0*M),SD,[0 NaN])'; + % check min/max of sampled image + % against mn/mx as given in st + tmpt(tmpt(:)mx) = mx; + tmpc(tmpc(:)>mx) = mx; + tmps(tmps(:)>mx) = mx; + tmpt = (tmpt-mn)/(mx-mn); + tmpc = (tmpc-mn)/(mx-mn); + tmps = (tmps-mn)/(mx-mn); + tmpt(~finite(tmpt)) = 0; + tmpc(~finite(tmpc)) = 0; + tmps(~finite(tmps)) = 0; + + cimgt = cimgt + cat(3,tmpt*colour(j,1),tmpt*colour(j,2),tmpt*colour(j,3)); + cimgc = cimgc + cat(3,tmpc*colour(j,1),tmpc*colour(j,2),tmpc*colour(j,3)); + cimgs = cimgs + cat(3,tmps*colour(j,1),tmps*colour(j,2),tmps*colour(j,3)); + + wt = wt + tmpt; + wc = wc + tmpc; + ws = ws + tmps; + cdata=permute(shiftdim([1/64:1/64:1]'* ... + colour(j,:),-1),[2 1 3]); + redraw_colourbar(i,j,[mn mx],cdata); + end; + + imgt = repmat(1-wt,[1 1 3]).*imgt+cimgt; + imgc = repmat(1-wc,[1 1 3]).*imgc+cimgc; + imgs = repmat(1-ws,[1 1 3]).*imgs+cimgs; + + imgt(imgt<0)=0; imgt(imgt>1)=1; + imgc(imgc<0)=0; imgc(imgc>1)=1; + imgs(imgs<0)=0; imgs(imgs>1)=1; + end; + else, + scal = 64/(mx-mn); + dcoff = -mn*scal; + imgt = imgt*scal+dcoff; + imgc = imgc*scal+dcoff; + imgs = imgs*scal+dcoff; + end; + + set(st.vols{i}.ax{1}.d,'HitTest','off', 'Cdata',imgt); + set(st.vols{i}.ax{1}.lx,'HitTest','off',... + 'Xdata',[0 TD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{1}.ly,'HitTest','off',... + 'Ydata',[0 TD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{2}.d,'HitTest','off', 'Cdata',imgc); + set(st.vols{i}.ax{2}.lx,'HitTest','off',... + 'Xdata',[0 CD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{2}.ly,'HitTest','off',... + 'Ydata',[0 CD(2)]+0.5,'Xdata',[1 1]*(cent(1)-bb(1,1)+1)); + + set(st.vols{i}.ax{3}.d,'HitTest','off','Cdata',imgs); + if st.mode ==0, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(2)-bb(1,2)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(cent(3)-bb(1,3)+1)); + else, + set(st.vols{i}.ax{3}.lx,'HitTest','off',... + 'Xdata',[0 SD(1)]+0.5,'Ydata',[1 1]*(cent(3)-bb(1,3)+1)); + set(st.vols{i}.ax{3}.ly,'HitTest','off',... + 'Ydata',[0 SD(2)]+0.5,'Xdata',[1 1]*(bb(2,2)+1-cent(2))); + end; + + if ~isempty(st.plugins) % process any addons + for k = 1:prod(size(st.plugins)) + if isfield(st.vols{i},st.plugins{k}) + feval(['spm_ov_', st.plugins{k}], ... + 'redraw', i, TM0, TD, CM0, CD, SM0, SD); + end; + end; + end; + end; +end; +drawnow; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function redraw_colourbar(vh,bh,interval,cdata) +global st +if isfield(st.vols{vh}.blobs{bh},'cbar') + if st.mode == 0, + axpos = get(st.vols{vh}.ax{2}.ax,'Position'); + else, + axpos = get(st.vols{vh}.ax{1}.ax,'Position'); + end; + % only scale cdata if we have out-of-range truecolour values + if ndims(cdata)==3 && max(cdata(:))>1 + cdata=cdata./max(cdata(:)); + end; + image([0 1],interval,cdata,'Parent',st.vols{vh}.blobs{bh}.cbar); + set(st.vols{vh}.blobs{bh}.cbar, ... + 'Position',[(axpos(1)+axpos(3)+0.05+(bh-1)*.1)... + (axpos(2)+0.005) 0.05 (axpos(4)-0.01)],... + 'YDir','normal','XTickLabel',[],'XTick',[]); +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function centre = findcent +global st +obj = get(st.fig,'CurrentObject'); +centre = []; +cent = []; +cp = []; +for i=valid_handles(1:24), + for j=1:3, + if ~isempty(obj), + if (st.vols{i}.ax{j}.ax == obj), + cp = get(obj,'CurrentPoint'); + end; + end; + if ~isempty(cp), + cp = cp(1,1:2); + is = inv(st.Space); + cent = is(1:3,1:3)*st.centre(:) + is(1:3,4); + switch j, + case 1, + cent([1 2])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,2)-1]; + case 2, + cent([1 3])=[cp(1)+st.bb(1,1)-1 cp(2)+st.bb(1,3)-1]; + case 3, + if st.mode ==0, + cent([3 2])=[cp(1)+st.bb(1,3)-1 cp(2)+st.bb(1,2)-1]; + else, + cent([2 3])=[st.bb(2,2)+1-cp(1) cp(2)+st.bb(1,3)-1]; + end; + end; + break; + end; + end; + if ~isempty(cent), break; end; +end; +if ~isempty(cent), centre = st.Space(1:3,1:3)*cent(:) + st.Space(1:3,4); end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function handles = valid_handles(handles) +global st; +handles = handles(:)'; +handles = handles(find(handles<=24 & handles>=1 & ~rem(handles,1))); +for h=handles, + if isempty(st.vols{h}), handles(find(handles==h))=[]; end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function reset_st +global st +fig = spm_figure('FindWin','Graphics'); +bb = []; %[ [-78 78]' [-112 76]' [-50 85]' ]; +st = struct('n', 0, 'vols',[], 'bb',bb,'Space',eye(4),'centre',[0 0 0],'callback',';','xhairs',1,'hld',1,'fig',fig,'mode',1,'plugins',[],'snap',[]); +st.vols = cell(24,1); + +pluginpath = fullfile(spm('Dir'),'spm_orthviews'); +if isdir(pluginpath) + pluginfiles = dir(fullfile(pluginpath,'spm_ov_*.m')); + if ~isempty(pluginfiles) + addpath(pluginpath); + % fprintf('spm_orthviews: Using Plugins in %s\n', pluginpath); + for k = 1:length(pluginfiles) + [p pluginname e v] = fileparts(pluginfiles(k).name); + st.plugins{k} = strrep(pluginname, 'spm_ov_',''); + % fprintf('%s\n',st.plugins{k}); + end; + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function img = scaletocmap(inpimg,mn,mx,cmap,miscol) +if nargin < 5, miscol=1;end +cml = size(cmap,1); +scf = (cml-1)/(mx-mn); +img = round((inpimg-mn)*scf)+1; +img(find(img<1)) = 1; +img(find(img>cml)) = cml; +img(~finite(img)) = miscol; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cmap = getcmap(acmapname) +% get colormap of name acmapname +if ~isempty(acmapname), + cmap = evalin('base',acmapname,'[]'); + if isempty(cmap), % not a matrix, is .mat file? + [p f e] = fileparts(acmapname); + acmat = fullfile(p, [f '.mat']); + if exist(acmat, 'file'), + s = struct2cell(load(acmat)); + cmap = s{1}; + end; + end; +end; +if size(cmap, 2)~=3, + warning('Colormap was not an N by 3 matrix') + cmap = []; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function item_parent = addcontext(volhandle) +global st; +%create context menu +fg = spm_figure('Findwin','Graphics');set(0,'CurrentFigure',fg); +%contextmenu +item_parent = uicontextmenu; + +%contextsubmenu 0 +item00 = uimenu(item_parent, 'Label','unknown image', 'Separator','on'); +spm_orthviews('context_menu','image_info',item00,volhandle); +item0a = uimenu(item_parent, 'UserData','pos_mm', 'Callback','spm_orthviews(''context_menu'',''repos_mm'');','Separator','on'); +item0b = uimenu(item_parent, 'UserData','pos_vx', 'Callback','spm_orthviews(''context_menu'',''repos_vx'');'); +item0c = uimenu(item_parent, 'UserData','v_value'); + +%contextsubmenu 1 +item1 = uimenu(item_parent,'Label','Zoom'); +item1_1 = uimenu(item1, 'Label','Full Volume', 'Callback','spm_orthviews(''context_menu'',''zoom'',6);', 'Checked','on'); +item1_2 = uimenu(item1, 'Label','160x160x160mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',5);'); +item1_3 = uimenu(item1, 'Label','80x80x80mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',4);'); +item1_4 = uimenu(item1, 'Label','40x40x40mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',3);'); +item1_5 = uimenu(item1, 'Label','20x20x20mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',2);'); +item1_6 = uimenu(item1, 'Label','10x10x10mm', 'Callback','spm_orthviews(''context_menu'',''zoom'',1);'); + +%contextsubmenu 2 +checked={'off','off'}; +checked{st.xhairs+1} = 'on'; +item2 = uimenu(item_parent,'Label','Crosshairs'); +item2_1 = uimenu(item2, 'Label','on', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''on'');','Checked',checked{2}); +item2_2 = uimenu(item2, 'Label','off', 'Callback','spm_orthviews(''context_menu'',''Xhair'',''off'');','Checked',checked{1}); + +%contextsubmenu 3 +if st.Space == eye(4) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Orientation'); +item3_1 = uimenu(item3, 'Label','World space', 'Callback','spm_orthviews(''context_menu'',''orientation'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Voxel space (1st image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Voxel space (this image)', 'Callback','spm_orthviews(''context_menu'',''orientation'',1);','Checked','off'); + +%contextsubmenu 3 +if isempty(st.snap) + checked = {'off', 'on'}; +else + checked = {'on', 'off'}; +end; +item3 = uimenu(item_parent,'Label','Snap to Grid'); +item3_1 = uimenu(item3, 'Label','Don''t snap', 'Callback','spm_orthviews(''context_menu'',''snap'',3);','Checked',checked{2}); +item3_2 = uimenu(item3, 'Label','Snap to 1st image', 'Callback','spm_orthviews(''context_menu'',''snap'',2);','Checked',checked{1}); +item3_3 = uimenu(item3, 'Label','Snap to this image', 'Callback','spm_orthviews(''context_menu'',''snap'',1);','Checked','off'); + +%contextsubmenu 4 +if st.hld == 0, + checked = {'off', 'off', 'on'}; +elseif st.hld > 0, + checked = {'off', 'on', 'off'}; +else, + checked = {'on', 'off', 'off'}; +end; +item4 = uimenu(item_parent,'Label','Interpolation'); +item4_1 = uimenu(item4, 'Label','NN', 'Callback','spm_orthviews(''context_menu'',''interpolation'',3);', 'Checked',checked{3}); +item4_2 = uimenu(item4, 'Label','Bilin', 'Callback','spm_orthviews(''context_menu'',''interpolation'',2);','Checked',checked{2}); +item4_3 = uimenu(item4, 'Label','Sinc', 'Callback','spm_orthviews(''context_menu'',''interpolation'',1);','Checked',checked{1}); + +%contextsubmenu 5 +% item5 = uimenu(item_parent,'Label','Position', 'Callback','spm_orthviews(''context_menu'',''position'');'); + +%contextsubmenu 6 +item6 = uimenu(item_parent,'Label','Image','Separator','on'); +item6_1 = uimenu(item6, 'Label','Window'); +item6_1_1 = uimenu(item6_1, 'Label','local'); +item6_1_1_1 = uimenu(item6_1_1, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window'',2);'); +item6_1_1_2 = uimenu(item6_1_1, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window'',1);'); +item6_1_2 = uimenu(item6_1, 'Label','global'); +item6_1_2_1 = uimenu(item6_1_2, 'Label','auto', 'Callback','spm_orthviews(''context_menu'',''window_gl'',2);'); +item6_1_2_2 = uimenu(item6_1_2, 'Label','manual', 'Callback','spm_orthviews(''context_menu'',''window_gl'',1);'); +if license('test','image_toolbox') == 1 + offon = {'off', 'on'}; + checked = offon(strcmp(st.vols{volhandle}.mapping, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'})+1); + item6_2 = uimenu(item6, 'Label','Intensity mapping'); + item6_2_1 = uimenu(item6_2, 'Label','local'); + item6_2_1_1 = uimenu(item6_2_1, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''linear'');'); + item6_2_1_2 = uimenu(item6_2_1, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''histeq'');'); + item6_2_1_3 = uimenu(item6_2_1, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''loghisteq'');'); + item6_2_1_4 = uimenu(item6_2_1, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping'',''quadhisteq'');'); + item6_2_2 = uimenu(item6_2, 'Label','global'); + item6_2_2_1 = uimenu(item6_2_2, 'Label','Linear', 'Checked',checked{1}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''linear'');'); + item6_2_2_2 = uimenu(item6_2_2, 'Label','Equalised histogram', 'Checked',checked{2}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''histeq'');'); + item6_2_2_3 = uimenu(item6_2_2, 'Label','Equalised log-histogram', 'Checked',checked{3}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''loghisteq'');'); + item6_2_2_4 = uimenu(item6_2_2, 'Label','Equalised squared-histogram', 'Checked',checked{4}, ... + 'Callback','spm_orthviews(''context_menu'',''mapping_gl'',''quadhisteq'');'); +end; +%contextsubmenu 7 +item7 = uimenu(item_parent,'Label','Blobs'); +item7_1 = uimenu(item7, 'Label','Add blobs'); +item7_1_1 = uimenu(item7_1, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',2);'); +item7_1_2 = uimenu(item7_1, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_blobs'',1);'); +item7_2 = uimenu(item7, 'Label','Add image'); +item7_2_1 = uimenu(item7_2, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_image'',2);'); +item7_2_2 = uimenu(item7_2, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_image'',1);'); +item7_3 = uimenu(item7, 'Label','Add colored blobs','Separator','on'); +item7_3_1 = uimenu(item7_3, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',2);'); +item7_3_2 = uimenu(item7_3, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_blobs'',1);'); +item7_4 = uimenu(item7, 'Label','Add colored image'); +item7_4_1 = uimenu(item7_4, 'Label','local', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',2);'); +item7_4_2 = uimenu(item7_4, 'Label','global', 'Callback','spm_orthviews(''context_menu'',''add_c_image'',1);'); +item7_5 = uimenu(item7, 'Label','Remove blobs', 'Visible','off','Separator','on'); +item7_6 = uimenu(item7, 'Label','Remove colored blobs','Visible','off'); +item7_6_1 = uimenu(item7_6, 'Label','local', 'Visible','on'); +item7_6_2 = uimenu(item7_6, 'Label','global','Visible','on'); + +if ~isempty(st.plugins) % process any plugins + for k = 1:prod(size(st.plugins)), + feval(['spm_ov_', st.plugins{k}], ... + 'context_menu', volhandle, item_parent); + end; +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function c_menu(varargin) +global st + +switch lower(varargin{1}), + case 'image_info', + if nargin <3, + current_handle = get_current_handle; + else + current_handle = varargin{3}; + end; + if isfield(st.vols{current_handle},'fname'), + [p,n,e,v] = spm_fileparts(st.vols{current_handle}.fname); + if isfield(st.vols{current_handle},'n') + v = sprintf(',%d',st.vols{current_handle}.n); + end; + set(varargin{2}, 'Label',[n e v]); + end; + delete(get(varargin{2},'children')); + if exist('p','var') + item1 = uimenu(varargin{2}, 'Label', p); + end; + if isfield(st.vols{current_handle},'descrip'), + item2 = uimenu(varargin{2}, 'Label',... + st.vols{current_handle}.descrip); + end; + dt = st.vols{current_handle}.dt(1); + item3 = uimenu(varargin{2}, 'Label', sprintf('Data type: %s', spm_type(dt))); + str = 'Intensity: varied'; + if size(st.vols{current_handle}.pinfo,2) == 1, + if st.vols{current_handle}.pinfo(2), + str = sprintf('Intensity: Y = %g X + %g',... + st.vols{current_handle}.pinfo(1:2)'); + else, + str = sprintf('Intensity: Y = %g X', st.vols{current_handle}.pinfo(1)'); + end; + end; + item4 = uimenu(varargin{2}, 'Label',str); + item5 = uimenu(varargin{2}, 'Label', 'Image dims', 'Separator','on'); + item51 = uimenu(varargin{2}, 'Label',... + sprintf('%dx%dx%d', st.vols{current_handle}.dim(1:3))); + prms = spm_imatrix(st.vols{current_handle}.mat); + item6 = uimenu(varargin{2}, 'Label','Voxel size', 'Separator','on'); + item61 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', prms(7:9))); + item7 = uimenu(varargin{2}, 'Label','Origin', 'Separator','on'); + item71 = uimenu(varargin{2}, 'Label',... + sprintf('%.2f %.2f %.2f', prms(1:3))); + R = spm_matrix([0 0 0 prms(4:6)]); + item8 = uimenu(varargin{2}, 'Label','Rotations', 'Separator','on'); + item81 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(1,1:3))); + item82 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(2,1:3))); + item83 = uimenu(varargin{2}, 'Label', sprintf('%.2f %.2f %.2f', R(3,1:3))); + item9 = uimenu(varargin{2},... + 'Label','Specify other image...',... + 'Callback','spm_orthviews(''context_menu'',''swap_img'');',... + 'Separator','on'); + + case 'repos_mm', + oldpos_mm = spm_orthviews('pos'); + newpos_mm = spm_input('New Position (mm)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_mm),3); + spm_orthviews('reposition',newpos_mm); + + case 'repos_vx' + current_handle = get_current_handle; + oldpos_vx = spm_orthviews('pos', current_handle); + newpos_vx = spm_input('New Position (voxels)','+1','r',sprintf('%.2f %.2f %.2f',oldpos_vx),3); + newpos_mm = st.vols{current_handle}.mat*[newpos_vx;1]; + spm_orthviews('reposition',newpos_mm(1:3)); + + case 'zoom' + zoom_all(varargin{2}); + bbox; + redraw_all; + + case 'xhair', + spm_orthviews('Xhairs',varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Crosshairs'),'Children'); + set(z_handle,'Checked','off'); %reset check + if strcmp(varargin{2},'off'), op = 1; else op = 2; end + set(z_handle(op),'Checked','on'); + end; + + case 'orientation', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + spm_orthviews('Space'); + elseif varargin{2} == 2, + spm_orthviews('Space',1); + else, + spm_orthviews('Space',get_current_handle); + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Orientation'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Orientation'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'snap', + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle,'Checked','off'); + end; + if varargin{2} == 3, + st.snap = []; + elseif varargin{2} == 2, + st.snap = 1; + else, + st.snap = get_current_handle; + z_handle = get(findobj(st.vols{get_current_handle}.ax{1}.cm,'label','Snap to Grid'),'Children'); + set(z_handle(1),'Checked','on'); + return; + end; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Snap to Grid'),'Children'); + set(z_handle(varargin{2}),'Checked','on'); + end; + + case 'interpolation', + tmp = [-4 1 0]; + st.hld = tmp(varargin{2}); + cm_handles = get_cm_handles; + for i = 1:length(cm_handles), + z_handle = get(findobj(cm_handles(i),'label','Interpolation'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(varargin{2}),'Checked','on'); + end; + redraw_all; + + case 'window', + current_handle = get_current_handle; + if varargin{2} == 2, + spm_orthviews('window',current_handle); + else + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%.2f %.2f', st.vols{current_handle}.window); + else + defstr = ''; + end; + spm_orthviews('window',current_handle,spm_input('Range','+1','e',defstr,2)); + end; + + case 'window_gl', + if varargin{2} == 2, + for i = 1:length(get_cm_handles), + st.vols{i}.window = 'auto'; + end; + else, + current_handle = get_current_handle; + if isnumeric(st.vols{current_handle}.window) + defstr = sprintf('%d %d', st.vols{current_handle}.window); + else + defstr = ''; + end; + data = spm_input('Range','+1','e',defstr,2); + + for i = 1:length(get_cm_handles), + st.vols{i}.window = data; + end; + end; + redraw_all; + + case 'mapping', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', ... + 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + current_handle = get_current_handle; + cm_handles = get_cm_handles; + st.vols{current_handle}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(current_handle), ... + 'label','Intensity mapping'),'Children'); + for k = 1:numel(z_handle) + c_handle = get(z_handle(k), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + redraw_all; + + case 'mapping_gl', + checked = strcmp(varargin{2}, ... + {'linear', 'histeq', 'loghisteq', 'quadhisteq'}); + checked = checked(end:-1:1); % Handles are stored in inverse order + cm_handles = get_cm_handles; + for k = valid_handles(1:24), + st.vols{k}.mapping = varargin{2}; + z_handle = get(findobj(cm_handles(k), ... + 'label','Intensity mapping'),'Children'); + for l = 1:numel(z_handle) + c_handle = get(z_handle(l), 'Children'); + set(c_handle, 'checked', 'off'); + set(c_handle(checked), 'checked', 'on'); + end; + end; + redraw_all; + + case 'swap_img', + current_handle = get_current_handle; + new_info = spm_vol(spm_select(1,'image','select new image')); + fn = fieldnames(new_info); + for k=1:numel(fn) + st.vols{current_handle}.(fn{k}) = new_info.(fn{k}); + end; + spm_orthviews('context_menu','image_info',get(gcbo, 'parent')); + redraw_all; + + case 'add_blobs', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + for i = 1:length(cm_handles), + addblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'remove_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + for i = 1:length(cm_handles), + rmblobs(cm_handles(i)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + delete(get(c_handle,'Children')); + set(c_handle,'Visible','off'); + end; + redraw_all; + + case 'add_image', + % Add blobs to the image - in split colortable + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + for i = 1:length(cm_handles), + addimage(cm_handles(i),fname); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove blobs'); + set(c_handle,'Visible','on'); + delete(get(c_handle,'Children')); + item7_3_1 = uimenu(c_handle,'Label','local','Callback','spm_orthviews(''context_menu'',''remove_blobs'',2);'); + if varargin{2} == 1, + item7_3_2 = uimenu(c_handle,'Label','global','Callback','spm_orthviews(''context_menu'',''remove_blobs'',1);'); + end; + end; + redraw_all; + + case 'add_c_blobs', + % Add blobs to the image - in full colour + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + spm_figure('Clear','Interactive'); + [SPM,VOL] = spm_getSPM; + c = spm_input('Colour','+1','m',... + 'Red blobs|Green blobs|Yellow blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;0 1 0;1 1 0;0 0 1;0 1 1;1 0 1]; + c_names = {'red';'green';'yellow';'blue';'cyan';'magenta'}; + hlabel = sprintf('%s (%s)',VOL.title,c_names{c}); + for i = 1:length(cm_handles), + addcolouredblobs(cm_handles(i),VOL.XYZ,VOL.Z,VOL.M,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);',... + 'UserData',c); + if varargin{2} == 1, + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end; + end; + redraw_all; + + case 'remove_c_blobs', + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle; end; + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + for i = 1:length(cm_handles), + if isfield(st.vols{cm_handles(i)},'blobs'), + for j = 1:length(st.vols{cm_handles(i)}.blobs), + if st.vols{cm_handles(i)}.blobs{j}.colour == colours(varargin{3},:); + if isfield(st.vols{cm_handles(i)}.blobs{j},'cbar') + delete(st.vols{cm_handles(i)}.blobs{j}.cbar); + end + st.vols{cm_handles(i)}.blobs(j) = []; + break; + end; + end; + rm_c_menu = findobj(st.vols{cm_handles(i)}.ax{1}.cm,'Label','Remove colored blobs'); + delete(findobj(rm_c_menu,'Label',c_names{varargin{3}})); + if isempty(st.vols{cm_handles(i)}.blobs), + st.vols{cm_handles(i)} = rmfield(st.vols{cm_handles(i)},'blobs'); + set(rm_c_menu, 'Visible', 'off'); + end; + end; + end; + redraw_all; + + case 'add_c_image', + % Add truecolored image + cm_handles = valid_handles(1:24); + if varargin{2} == 2, cm_handles = get_current_handle;end; + spm_figure('Clear','Interactive'); + fname = spm_select(1,'image','select image'); + c = spm_input('Colour','+1','m','Red blobs|Yellow blobs|Green blobs|Cyan blobs|Blue blobs|Magenta blobs',[1 2 3 4 5 6],1); + colours = [1 0 0;1 1 0;0 1 0;0 1 1;0 0 1;1 0 1]; + c_names = {'red';'yellow';'green';'cyan';'blue';'magenta'}; + hlabel = sprintf('%s (%s)',fname,c_names{c}); + for i = 1:length(cm_handles), + addcolouredimage(cm_handles(i),fname,colours(c,:)); + addcolourbar(cm_handles(i),numel(st.vols{cm_handles(i)}.blobs)); + c_handle = findobj(findobj(st.vols{cm_handles(i)}.ax{1}.cm,'label','Blobs'),'Label','Remove colored blobs'); + ch_c_handle = get(c_handle,'Children'); + set(c_handle,'Visible','on'); + %set(ch_c_handle,'Visible',on'); + item7_4_1 = uimenu(ch_c_handle(2),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',2,c);','UserData',c); + if varargin{2} == 1 + item7_4_2 = uimenu(ch_c_handle(1),'Label',hlabel,'ForegroundColor',colours(c,:),... + 'Callback','c = get(gcbo,''UserData'');spm_orthviews(''context_menu'',''remove_c_blobs'',1,c);',... + 'UserData',c); + end + end + redraw_all; +end; +%_______________________________________________________________________ +%_______________________________________________________________________ +function current_handle = get_current_handle +global st +cm_handle = get(gca,'UIContextMenu'); +cm_handles = get_cm_handles; +current_handle = find(cm_handles==cm_handle); +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_pos +global st +for i = 1:length(valid_handles(1:24)), + if isfield(st.vols{i}.ax{1},'cm') + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_mm'),... + 'Label',sprintf('mm: %.1f %.1f %.1f',spm_orthviews('pos'))); + pos = spm_orthviews('pos',i); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','pos_vx'),... + 'Label',sprintf('vx: %.1f %.1f %.1f',pos)); + set(findobj(st.vols{i}.ax{1}.cm,'UserData','v_value'),... + 'Label',sprintf('Y = %g',spm_sample_vol(st.vols{i},pos(1),pos(2),pos(3),st.hld))); + end +end; +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function cm_handles = get_cm_handles +global st +cm_handles = []; +for i=valid_handles(1:24), + cm_handles = [cm_handles st.vols{i}.ax{1}.cm]; +end +return; +%_______________________________________________________________________ +%_______________________________________________________________________ +function zoom_all(op) +global st +cm_handles = get_cm_handles; +res = [.125 .125 .25 .5 1 1]; +if op==6, + st.bb = maxbb; +else, + vx = sqrt(sum(st.Space(1:3,1:3).^2)); + vx = vx.^(-1); + pos = spm_orthviews('pos'); + pos = st.Space\[pos ; 1]; + pos = pos(1:3)'; + if op == 5, st.bb = [pos-80*vx ; pos+80*vx] ; + elseif op == 4, st.bb = [pos-40*vx ; pos+40*vx] ; + elseif op == 3, st.bb = [pos-20*vx ; pos+20*vx] ; + elseif op == 2, st.bb = [pos-10*vx ; pos+10*vx] ; + elseif op == 1; st.bb = [pos- 5*vx ; pos+ 5*vx] ; + else disp('no Zoom possible'); + end; +end +resolution(res(op)); +redraw_all; +for i = 1:length(cm_handles) + z_handle = get(findobj(cm_handles(i),'label','Zoom'),'Children'); + set(z_handle,'Checked','off'); + set(z_handle(op),'Checked','on'); +end +return; + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% ROI: TimeSeries +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_searchContentEdit(hObject, eventdata) +handles = guidata(hObject); +set(handles.searchContentEdit,'UserData', 'manual'); + + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% click load SPM file button +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_loadSPMmat(hObject, eventdata, spmfile) +handles = guidata(hObject); +if nargin < 3 | isempty(spmfile) + %if exist(fullfile(pwd,'SPM.mat'), 'file') + if ~isempty(findstr('SPM2',spm('ver'))) & exist('spm_get')==2 + spmfile = spm_get([1],'SPM.mat','Select a SPM file'); + elseif ~isempty(findstr('SPM5',spm('ver'))) & exist('spm_select')==2 + spmfile = spm_select(1,'SPM.mat','Select a SPM file'); + else + if exist('spm')==2 + error('Check for inconsistencies in your SPM install.\nspm(''ver'') = %s\n', spm('ver')) + else + error('No SPM found'); + end + end +end +xSPM=load(spmfile); +if isfield(xSPM.SPM, 'xCon') + + if ~exist(xSPM.SPM.swd, 'dir') + nswd = fileparts(spmfile); + warning('Directory specified in SPM.swd is missing (%s).\nWill use: %s',xSPM.SPM.swd,nswd); + xSPM.SPM.swd=nswd; + end + numc=listdlg('ListString' , {xSPM.SPM.xCon.name}, 'SelectionMode' , 'single', 'InitialValue', 2);%length(xSPM.SPM.xCon)); + if ~exist(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)) & ... + exist(subarray(fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname),1:2,-2)) + warning('Changing path') + xSPM.SPM.swd=xSPM.SPM.swd(3:end); + end + if ~isempty(numc) + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + end +else + msgbox('No contrast in this file') +end +return + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_indivResultsListPush(hObject, eventdata) +handles = guidata(hObject); +if ischar(handles.imageFileName) + handles.imageFileName={handles.imageFileName}; +end +[datadir,condir,condext]=fileparts(handles.imageFileName{1}); +if datadir(2)==':' + datadir=datadir(3:end); +end +[datadir,subdir]=fileparts(datadir); +if isempty(findstr('indiv/', datadir)) +elseif isempty(findstr('rfx/', datadir)) + xSPM=load(fullfile(datadir,'SPM.mat')); + indivdir=xSPM.xY.P; +else + return +end +req = get(handles.indivResultsListPush,'String'); +req = req{get(handles.indivResultsListPush, 'value')}; + +if isequal(req,'Group') + datadir=fileparts(datadir); + condir=handles.imageContrastName{1}; + condir=strrep(condir, '>', 'vs'); + condir=strrep(condir, '<', 'vs'); + condir=strrep(condir, '+', '_'); + condir=strrep(condir, ':', ' at'); + condir=deblank(condir); + condir=fullfile(datadir,'rfx',condir); + if ~exist(condir,'dir') + return + end + xSPM=load(fullfile(condir,'SPM.mat')); + numc=2; + CallBack_loadImagePush(handles.loadImagePush, [],... + {fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname)},... + {xSPM.SPM.xCon(numc).name}); + return +elseif exist('swds','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + swds(get(gcbo, 'value'),:),... + handles.imageContrastName); +else + if exist(fullfile(datadir,req,'SPM.mat')) + xSPM=load(fullfile(datadir,req,'SPM.mat')); + if ~isfield(handles,'imageContrastName') + return + end + % numc=strmatch(handles.imageContrastName{1},{xSPM.SPM.xCon.name},'exact'); + numc=get(handles.contrastListPush, 'Value'); + filename=fullfile(xSPM.SPM.swd,xSPM.SPM.xCon(numc).Vspm.fname); + else + % SPM adds a comma for 4D volumes + condext = strtok(condext,','); + filename = fullfile(datadir,req,[condir condext]); + warning('Using same filename in %s: ', req, filename) + end + if filename(2)==':' + filename=filename(3:end); + end + if ~exist(filename,'file') + error('File doesn''t exist: %s',filename) + return + end + set(handles.sectionViewListbox, 'Value', [1]); + % handles.sectionViewTargetFile = + % fullfile('\ndiayek\data\gazemo\rawdata\',req,'anat','wf_0001.img'); + guidata(hObject, handles); + if exist('xSPM','var') + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + {xSPM.SPM.xCon(numc).name}); + else + CallBack_loadImagePush(handles.loadImagePush, [],... + {filename},... + '???'); + end + % CallBack_allIntensityRadio(hObject, eventdata, 'c'); +end +uicontrol(hObject) + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function CallBack_paramestRegionPush(hObject, eventdata, roi,readdata) +if nargin<4 + readdata=1; +end +roi=struct('type', roi); +handles = guidata(hObject); +roi.name=get(handles.structureEdit, 'String'); + +[img.p, img.fname, img.ext]=fileparts(handles.imageFileName{1}); +spmfile=fullfile(img.p,'SPM.mat'); + +if exist(spmfile(3:end), 'file') + warning('Possible disk swapping in xjview.m'); + spmfile=spmfile(3:end); +end +if ~exist(spmfile) + if findstr('SPM2',spm('ver')) + spmfile = spm_get([0 1],'SPM.mat','locate the RFX SPM.mat'); + elseif findstr('SPM5',spm('ver')) + spmfile = spm_select([0:1],'SPM.mat','locate the RFX SPM.mat'); + end +end +if ~exist(spmfile) + return +end +xSPM=load(spmfile, 'SPM'); +[glmpath, glmpath]=fileparts(fileparts(fileparts(xSPM.SPM.swd))); + +RetrieveRawData = 0; +status = get(gcbf, 'SelectionType') +% right click +if strcmp(status, 'alt') + RetrieveRawData = 1; +end + + + + +%[xyzmm,i] = spm_XYZreg('NearestXYZ',... +% spm_results_ui('GetCoords'),handles.currentxyz); +%spm_results_ui('SetCoords',xSPM.XYZmm(:,i)); +switch roi.type + case 'vox' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + xyz = handles.currentxyz; + case 'clu' + if not(isfield(handles,'selectedCluster')) | not(isempty(handles.selectedCluster)) + switch questdlg('Load from workspace','cluster?', 'currentDisplayMNI{1}','...','Cancel','currentDisplayMNI{1}') + case 'currentDisplayMNI{1}' + xyz=evalin('base', 'currentDisplayMNI{1}'); + case '...' + case 'Cancel' + return + end + delete(findobj('Tag', 'paramest')) + + else + delete(findobj('Tag', 'paramest')) + xyz =handles.currentDisplayMNI{1}; + end + case 'sph' + if not(isfield(handles,'currentxyz')) %%% + error('Wrong selection') + return + end + delete(findobj('Tag', 'paramest')) + xyz = handles.currentxyz; + roi.radius=inputdlg('Radius of the sphere?'); + if isempty(roi.radius) + return + end + roi.radius=str2num(roi.radius{1}) + % XYZmm = xSPM.SPM.xVol.M(1:3,:)*[xSPM.SPM.xVol.XYZ; ones(1,size(xSPM.SPM.xVol.XYZ,2))]; + % xyz = sqrt( XYZmm-repmat(xyz,[1 size(XYZmm,2)]) ) + % xyz = XYZmm(:, xyz < roi.radius) + +end +% handles.currentDisplayMNI{1} +% ha=axes('Tag', 'paramest', 'Parent',gcf,'units','normalized','Position',[0.55, 0.05, 0.4, 0.4]); +if isequal(roi.type, 'sph') + if roi.radius > 20 + if not(spm_input({'Many many voxels may be retrieve','Radius of the sphere (in mm):',... + num2str(roi.radius),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end + end + +end +if size(xyz,1)>40 + if not(spm_input({'Many many voxels to retrieve','Number of voxel:',... + num2str(size(xyz,1)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0])) + return + end +end + +allbetas= []; +allcons= []; +allxyz = []; +allvxyz = []; +roi.nvox = []; +hwait = waitbar(0,'Reading 1st level data'); +lcd=cd; +handles.currentxyz +if isfield(handles, 'paramest') + handles.paramest=[]; +end + +roi.stat.TF=handles.TF; +roi.stat.pValue=handles.pValue; +roi.stat.df=handles.df; +% roi.stat.Intensity = +% handles.currentDisplayIntensity{1}(find(all(handles.currentDisplayMNI{1}==repmat(handles.currentxyz, 3,1),2))); +[i,j]=ismember(handles.mni{1}, flipud(xyz), 'rows'); +roi.stat.intensity(j(i)) = handles.intensity{1}(i); + +if isstruct(xSPM.SPM.xX.K) | ~readdata + n=1; + % Ic=strmatch('F Task',{xSPM.SPM.xCon.name}) + % + % allbetas=[] + % vcon= + % XYZ = SPM.xVol.XYZ; + % XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + % tmpallbetas= []; + % [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + % allbetas = [allbetas;(mean(tmpallbetas,1))]; + % allxyz= [allxyz;mean(tmpallxyz,1)]; + +else + n= length(xSPM.SPM.xY.P) +end + +% Is that a correlation? +PlotCorrelation = (n>1) && not(isequal(all(xSPM.SPM.xX.X==1), [1])); + +try + roi.sub2pr = str2num(subarray(strvcat(xSPM.SPM.xY.P),55:56,2)); +end + + +for sub = 1:n + + waitbar(sub/n,hwait); + if n>1 + subdir = fileparts(xSPM.SPM.xY.P{sub}); + else + subdir = xSPM.SPM.swd; + end + subdir0 =subdir; + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, '[A-Z]?\:',''); + end + if ~exist(subdir, 'dir') + subdir = regexprep(subdir, {'^\\ndiayek', '^\\ndiaye'},'') + end + + + if ~exist(fullfile(subdir, 'SPM.mat'), 'file') & ... + exist(subarray(fullfile(subdir, 'SPM.mat'),1:2,-2),'file') + subdir = subdir(3:end); + end + if exist(fullfile(subdir, 'SPM.mat'), 'file') + load(fullfile(subdir, 'SPM.mat')); + fprintf('Retrieving betas from: %s\n', fullfile(subdir, 'SPM.mat')) + + if sub==1 + % [cn.path cn.fname cn.ext]=fileparts(char(xSPM.SPM.xY.P(sub,:))); + % consfiles=[SPM.xCon.Vcon]; + + % retrieves the f map (where all betas should be) + Ic = [... + strmatch('f anim', lower({SPM.xCon.name})) ... + strmatch('f task', lower({SPM.xCon.name})) ... + strmatch('f map', lower({SPM.xCon.name}))]; + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name},'InitialValue',Ic); + end + Ic=Ic(end); + conname=SPM.xCon(Ic).name; + end + + %------- + Ic = strmatch(conname,{SPM.xCon.name}, 'exact') ; %contrast number + if isempty(Ic) + Ic = listdlg('ListString',{SPM.xCon.name}); + end + %------- + else + SPM = xSPM.SPM + %using raw data + Ic=NaN; + end + try + XYZ = SPM.xVol.XYZ; + XYZmm = SPM.xVol.M(1:3,:)*[XYZ; ones(1,size(XYZ,2))]; + tmpallbetas= []; + tmpallcons= []; + tmpallxyz = []; + cd(subdir) + for cluvox = 1:size(xyz,1) + switch (roi.type) + case 'sph' + [d] = spm_XYZreg('Edist',xyz(cluvox,:),XYZmm); + i=find(d<=roi.radius); + govox = ~isempty(i); + nxyz=XYZmm(:,i); + case {'vox', 'clu'} + govox = 1; + [nxyz,i] = spm_XYZreg('NearestXYZ',xyz(cluvox,:),XYZmm); + if sqrt(sum((nxyz'-xyz(cluvox,:)).^2))>=sqrt(3) %one voxel in each dimZ + govox= spm_input({'No data stored for this voxel','Closest voxels with data are:',... + num2str(xyz(cluvox,:)),... + 'Continue anyway?'},... + 1,'bd',{'OK','NO'},[1,0]); + end + end + if govox==1 + vXYZ = XYZ(:,i) ; % coordinates in voxels + + %-Get parameter and hyperparameter estimates + %======================================================================= + % ResMS = spm_get_data(SPM.VResMS,vXYZ); + % Bcov = ResMS*SPM.xX.Bcov; + CI = 1.6449; % = spm_invNcdf(1 - 0.05); + % compute contrast of parameter estimates and 90% C.I. + %---------------------------------------------------------- + %---- + xSPM.SPM.xY.VY(sub).fname = strrep(xSPM.SPM.xY.VY(sub).fname, subdir0, subdir); + tmpallcons = [tmpallcons ; spm_get_data(xSPM.SPM.xY.VY(sub), vXYZ)]; + if ~isnan(Ic) + beta = spm_get_data(SPM.Vbeta, vXYZ); + tmpallbetas = [tmpallbetas; (SPM.xCon(Ic).c'*beta)']; + else + tmpallbetas = tmpallcons; + end + + if RetrieveRawData + if sub==1 + fprintf('\tRetrieving rawdata from: %s\n', fullfile(subdir, 'SPM.mat')) + tmpallcons = [ spm_get_data(xSPM.SPM.xY.VY, vXYZ)']; + end + end + tmpallxyz = [tmpallxyz; nxyz']; + end + end + allbetas = [allbetas;(mean(tmpallbetas,1))]; + allcons = [allcons;(mean(tmpallcons,1))]; + allxyz= [allxyz;mean(tmpallxyz,1)]; + allvxyz= [allvxyz mean(vXYZ,2)]; + roi.nvox = [ roi.nvox; size(tmpallbetas,1)]; + tmp = mean(tmpallxyz); + % disp(['meancluster = ' num2str(mean(tmpallxyz,1))]); + catch + warning('Error with data from: %s', subdir) + end +end +close(hwait) +cd(lcd); +% +if ~isnan(Ic) + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c )),'*bf(1)', '')'), 1:6, -2)); + regnames=cellstr(subarray(strvcat(strrep(SPM.xX.name(any(SPM.xCon(Ic).c')),'*bf(1)', '')'), 1:6, -2)); + [regnames, ireg,ireg2]=unique(regnames); + a=[ repmat(' ',length(regnames),1) strvcat(strrep(regnames, '_', ' '))]; + a=dataread('string',a', '%s'); + leg=a(isort(ireg)); +else + leg={'??'}; +end +%a=reshape(a, [],108])'; +% +% n=factor(size(allbetas,2)); +% n=sort([n(end) prod(n(1:end-1))]); +% +% prompt={'Enter the matrix size for x^2:','Enter the colormap name:'}; +% def={'20','hsv'}; +% dlgTitle='Input for Peaks function'; +% lineNo=1; +% answer=inputdlg(prompt,dlgTitle,lineNo,def); +% +% AddOpts.Resize='on'; +% AddOpts.WindowStyle='normal'; +% AddOpts.Interpreter='tex'; +% answer=inputdlg(prompt,dlgTitle,lineNo,def,AddOpts); +% +assignin('base', 'allbetas', allbetas) +% ReshapeData = []; +% xbars=[]; +% fxorder=[2 3 1]; +% switch size(allbetas,2) +% case 8 +% ReshapeData = [4 2]; +% case 4 +% if all(ismember(a,{'Neutral' 'Fearful' 'Angry' 'Happy'})) +% ReshapeData = [4 1]; +% end +% case 18 +% ReshapeData = [18 1]; +% case 16 +% % ReshapeData = [2 8]; +% % xtick=[1 3 4 5 7 8 9 11]; +% % fxorder=[3 2 1]; +% ReshapeData = [16 1]; +% end +% if isempty(ReshapeData) +% ReshapeData = [fliplr(factor(size(allbetas,2))) 1]; +% ReshapeData = [ ReshapeData(1) prod(ReshapeData(2:end))] +% end +% allbetas=reshape(allbetas, [],ReshapeData(1),ReshapeData(2)); +% allbetas = permute(allbetas,fxorder); + +% allxyz=reshape(allxyz, [], 1, 3); +% allxyz=permute(allxyz, [3 2 1]); + +%assignin('base', 'allbetas', allbetas) +%assignin('base', 'allxyz', xyz) + + +roi.allbetas=allbetas; +roi.allxyz=allxyz'; +roi.allvxyz=allvxyz; +roi.allcons=allcons'; +roi.XYZmm=xyz'; +roi.xyz=mean(allxyz,1)'; +assignin('base', 'roi', roi) +%Icc = find(xSPM.SPM.xX.X*xSPM.SPM.xCon(strmatch(handles.imageContrastName{1}, {xSPM.SPM.xCon.name})).c); +% if ~isempty(handles.imageContrastName) +% fn=handles.imageContrastName{1}; +% else +[fp,fn,fe] = fileparts(handles.imageFileName{1}); +fn=[fn fe]; +cn=[xSPM.SPM.xCon.Vspm]; + +% end +Icc = strmatch(fn, {cn.fname}) ; +roi.fname = fullfile(fp,fn); +roi.cn = cn; +roi.Icc=Icc; +roi.leg=leg; +assignin('base', 'roi', roi) + + +try + plot_betas(roi,glmpath,handles) +catch + if n>1 + try + figure;h=barerrorbar(1:(prod(size(roi.allbetas))/size(roi.allbetas,1)),mean(roi.allbetas,1)',stderrw(roi.allbetas,2:ndims(roi.allbetas),1)',NaN) + catch + end + else + figure;bar(roi.allbetas) + end + xlabel('Task') + set(gca, 'XTickLabel', leg) + set(gca, 'XTickLabel', {'Self Pos' 'Self Neg' 'Other Pos' 'Other Neg' 'Word Pos' 'Word Neg'}) + xlabel('Task') + %legend({'Positive Words' 'Negative Words'},'Location', 'Best') + delete(legend) +end +title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +setappdata(gca, 'ROI', roi) + +if ~isempty(Icc) + if ~isempty(xSPM.SPM.xCon(Icc).c) + roi.allregressors = xSPM.SPM.xX.X*xSPM.SPM.xCon(Icc).c; + else + roi.allregressors = []; + end + assignin('base', 'roi', roi) +end +if PlotCorrelation + %correlation plot + figure; + cla; + plot(roi.allregressors, roi.allcons, 'x') + %hl=legend({'test'}, 0); + [s,o,r2,sce,p]=linearfit(roi.allcons,roi.allregressors); + text(median(roi.allregressors), quantile(roi.allcons,.90), {'Correlation: ' sprintf('r2 = %g\np = %g', r2,p)}) + xlabel(xSPM.SPM.xX.name(find(xSPM.SPM.xCon(Icc).c))) + ylabel(xSPM.SPM.xY.VY(1).descrip) + [xx]=axis; + hold on + plot(xx(1:2), s*xx(1:2)+o, '--') + hold off + title(sprintf('XYZ = %+0.1f %+0.1f %+0.1f', roi.XYZmm(1:3))); +end + +if RetrieveRawData + figure; + if n==1 + subplot(2,1,1); + plot(tmpallcons); + legend('BOLD',0) + subplot(2,1,2); + % iReg=any(SPM.xCon(handles.imageContrastName).c,2); + % plot(normalize(SPM.xX.X(:,iReg), 'unity')*diff(subarray(axis, [3 4]))/5+subarray(axis, 3)) + % legend([{'BOLD'} SPM.xX.name(iReg)],1) + Ic = handles.imageContrastName; + if isempty(Ic) || ~isnumeric(Ic) + Ic = get(handles.contrastListPush, 'Value'); + end + plot( [ + spm_FcUtil('Yc',SPM.xCon(Ic),SPM.xX.xKXs,beta) ... + SPM.xX.X*SPM.xCon(Ic).c*pinv(SPM.xCon(Ic).c)*beta ... + (1-2*get(handles.negativeIntensityRadio, 'Value'))*SPM.xX.X*SPM.xCon(Ic).c ]) + legend({ 'adjusted', 'predicted' SPM.xCon(Ic).name},0) + end +end + + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +%%% paramest push (Parameter estimates) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [c_num, c_let, c_word]=mycolourset +c_num = [1 0 0;0 1 0;1 1 0;0 1 1;0 0 1;1 0 1]; +c_let = {'r';'g';'y';'c';'b';'m'}; +c_word= {'red';'green';'yellow';'cyan';'blue';'magenta'}; \ No newline at end of file diff --git a/xline.m b/xline.m new file mode 100644 index 0000000..1701b00 --- /dev/null +++ b/xline.m @@ -0,0 +1,39 @@ +function varargout = hline(y,varargin) +%HLINE - Create a horizontal line on a plot +% [h] = hline(y) +% Adds as many horizontal lines on the current plot as there are values in y. +% +% See also: line, vline + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-02 Creation +% +% ----------------------------- Script History --------------------------------- + +x=max(abs(get(gca, 'Xlim')))*[-1 1]; +%x=x*10; +y=y(:); +y=[y*ones(1,2)]'; +x=repmat(x,size(y,2),1)'; + +holdstate=ishold; +hold on; +h=line(x,y); +if ~holdstate + hold off; +end +LineStyles={'-', ':', '--', '-.'}; +for i=1:length(h); + set(h(i), 'LineStyle', LineStyles{ceil(i/size(get(gca, 'ColorOrder'),1))}); +end +if nargout==0 + return +end +varargout={h}; diff --git a/xml2struct.m b/xml2struct.m new file mode 100644 index 0000000..fccd4cc --- /dev/null +++ b/xml2struct.m @@ -0,0 +1,47 @@ +function out = xml2struct(xmlfile) +%XML2STRUCT Read XML file into a structure. + +% Douglas M. Schwarz + +xml = xmlread(xmlfile); + +children = xml.getChildNodes; +for i = 1:children.getLength + out(i) = node2struct(children.item(i-1)); +end + +function s = node2struct(node) + +s.name = char(node.getNodeName); + +if node.hasAttributes + attributes = node.getAttributes; + nattr = attributes.getLength; + s.attributes = struct('name',cell(1,nattr),'value',cell(1,nattr)); + for i = 1:nattr + attr = attributes.item(i-1); + s.attributes(i).name = char(attr.getName); + s.attributes(i).value = char(attr.getValue); + end +else + s.attributes = []; +end + +try + s.data = char(node.getData); +catch + s.data = ''; +end + +if node.hasChildNodes + children = node.getChildNodes; + nchildren = children.getLength; + c = cell(1,nchildren); + s.children = struct('name',c,'attributes',c,'data',c,'children',c); + for i = 1:nchildren + child = children.item(i-1); + s.children(i) = node2struct(child); + end +else + s.children = []; +end diff --git a/xticklabel_rotate.m b/xticklabel_rotate.m new file mode 100644 index 0000000..f01eadc --- /dev/null +++ b/xticklabel_rotate.m @@ -0,0 +1,212 @@ +function hText = xticklabel_rotate(XTick,rot,varargin) +%hText = xticklabel_rotate(XTick,rot,XTickLabel,varargin) Rotate XTickLabel +% +% Syntax: xticklabel_rotate +% +% Input: +% {opt} XTick - vector array of XTick positions & values (numeric) +% uses current XTick values or XTickLabel cell array by +% default (if empty) +% {opt} rot - angle of rotation in degrees, 90° by default +% {opt} XTickLabel - cell array of label strings +% {opt} [var] - "Property-value" pairs passed to text generator +% ex: 'interpreter','none' +% 'Color','m','Fontweight','bold' +% +% Output: hText - handle vector to text labels +% +% Example 1: Rotate existing XTickLabels at their current position by 90° +% xticklabel_rotate +% +% Example 2: Rotate existing XTickLabels at their current position by 45° and change +% font size +% xticklabel_rotate([],45,[],'Fontsize',14) +% +% Example 3: Set the positions of the XTicks and rotate them 90° +% figure; plot([1960:2004],randn(45,1)); xlim([1960 2004]); +% xticklabel_rotate([1960:2:2004]); +% +% Example 4: Use text labels at XTick positions rotated 45° without tex interpreter +% xticklabel_rotate(XTick,45,NameFields,'interpreter','none'); +% +% Example 5: Use text labels rotated 90° at current positions +% xticklabel_rotate([],90,NameFields); +% +% Note : you can not re-run xticklabel_rotate on the same graph. +% +% + + +% This is a modified version of xticklabel_rotate90 by Denis Gilbert +% Modifications include Text labels (in the form of cell array) +% Arbitrary angle rotation +% Output of text handles +% Resizing of axes and title/xlabel/ylabel positions to maintain same overall size +% and keep text on plot +% (handles small window resizing after, but not well due to proportional placement with +% fixed font size. To fix this would require a serious resize function) +% Uses current XTick by default +% Uses current XTickLabel is different from XTick values (meaning has been already defined) + +% Brian FG Katz +% bfgkatz@hotmail.com +% 23-05-03 +% Modified 03-11-06 after user comment +% Allow for exisiting XTickLabel cell array + +% Other m-files required: cell2mat +% Subfunctions: none +% MAT-files required: none +% +% See also: xticklabel_rotate90, TEXT, SET + +% Based on xticklabel_rotate90 +% Author: Denis Gilbert, Ph.D., physical oceanography +% Maurice Lamontagne Institute, Dept. of Fisheries and Oceans Canada +% email: gilbertd@dfo-mpo.gc.ca Web: http://www.qc.dfo-mpo.gc.ca/iml/ +% February 1998; Last revision: 24-Mar-2003 + +% check to see if xticklabel_rotate has already been here (no other reason for this to happen) +if isempty(get(gca,'XTickLabel')), + error('xticklabel_rotate : can not process, either xticklabel_rotate has already been run or XTickLabel field has been erased') ; +end + +% if no XTickLabel AND no XTick are defined use the current XTickLabel +%if nargin < 3 & (~exist('XTick') | isempty(XTick)), +if (nargin < 3 || isempty(varargin{1})) & (~exist('XTick') | isempty(XTick)), + xTickLabels = get(gca,'XTickLabel') ; % use current XTickLabel + if ~iscell(xTickLabels) + % remove trailing spaces if exist (typical with auto generated XTickLabel) + temp1 = num2cell(xTickLabels,2) ; + for loop = 1:length(temp1), + temp1{loop} = deblank(temp1{loop}) ; + end + xTickLabels = temp1 ; + end +varargin = varargin(2:length(varargin)); +end + +% if no XTick is defined use the current XTick +if (~exist('XTick') | isempty(XTick)), + XTick = get(gca,'XTick') ; % use current XTick +end + +%Make XTick a column vector +XTick = XTick(:); + +if ~exist('xTickLabels'), + % Define the xtickLabels + % If XtickLabel is passed as a cell array then use the text + if (length(varargin)>0) & (iscell(varargin{1})), + xTickLabels = varargin{1}; + varargin = varargin(2:length(varargin)); + else + xTickLabels = num2str(XTick); + end +end + +if length(XTick) ~= length(xTickLabels), + error('xticklabel_rotate : must have same number of elements in "XTick" and "XTickLabel"') ; +end + +%Set the Xtick locations and set XTicklabel to an empty string +set(gca,'XTick',XTick,'XTickLabel','') + +if nargin < 2, + rot = 90 ; +end + +% Determine the location of the labels based on the position +% of the xlabel +hxLabel = get(gca,'XLabel'); % Handle to xlabel +xLabelString = get(hxLabel,'String'); + +% if ~isempty(xLabelString) +% warning('You may need to manually reset the XLABEL vertical position') +% end + +set(hxLabel,'Units','data'); +xLabelPosition = get(hxLabel,'Position'); +y = xLabelPosition(2); + +%CODE below was modified following suggestions from Urs Schwarz +y=repmat(y,size(XTick,1),1); +% retrieve current axis' fontsize +fs = get(gca,'fontsize'); + +% Place the new xTickLabels by creating TEXT objects +hText = text(XTick, y, xTickLabels,'fontsize',fs); + +% Rotate the text objects by ROT degrees +set(hText,'Rotation',rot,'HorizontalAlignment','right',varargin{:}) + +% Adjust the size of the axis to accomodate for longest label (like if they are text ones) +% This approach keeps the top of the graph at the same place and tries to keep xlabel at the same place +% This approach keeps the right side of the graph at the same place + +set(get(gca,'xlabel'),'units','data') ; + labxorigpos_data = get(get(gca,'xlabel'),'position') ; +set(get(gca,'ylabel'),'units','data') ; + labyorigpos_data = get(get(gca,'ylabel'),'position') ; +set(get(gca,'title'),'units','data') ; + labtorigpos_data = get(get(gca,'title'),'position') ; + +set(gca,'units','pixel') ; +set(hText,'units','pixel') ; +set(get(gca,'xlabel'),'units','pixel') ; +set(get(gca,'ylabel'),'units','pixel') ; + +origpos = get(gca,'position') ; +textsizes = cell2mat(get(hText,'extent')) ; +longest = max(textsizes(:,4)) ; + +laborigext = get(get(gca,'xlabel'),'extent') ; +laborigpos = get(get(gca,'xlabel'),'position') ; + + +labyorigext = get(get(gca,'ylabel'),'extent') ; +labyorigpos = get(get(gca,'ylabel'),'position') ; +leftlabdist = labyorigpos(1) + labyorigext(1) ; + +% assume first entry is the farthest left +leftpos = get(hText(1),'position') ; +leftext = get(hText(1),'extent') ; +leftdist = leftpos(1) + leftext(1) ; +if leftdist > 0, leftdist = 0 ; end % only correct for off screen problems + +botdist = origpos(2) + laborigpos(2) ; +newpos = [origpos(1)-leftdist longest+botdist origpos(3)+leftdist origpos(4)-longest+origpos(2)-botdist] ; +set(gca,'position',newpos) ; + +% readjust position of nex labels after resize of plot +set(hText,'units','data') ; +for loop= 1:length(hText), + set(hText(loop),'position',[XTick(loop), y(loop)]) ; +end + + +% adjust position of xlabel and ylabel +laborigpos = get(get(gca,'xlabel'),'position') ; +set(get(gca,'xlabel'),'position',[laborigpos(1) laborigpos(2)-longest 0]) ; + +% switch to data coord and fix it all +set(get(gca,'ylabel'),'units','data') ; +set(get(gca,'ylabel'),'position',labyorigpos_data) ; +set(get(gca,'title'),'position',labtorigpos_data) ; + +set(get(gca,'xlabel'),'units','data') ; + labxorigpos_data_new = get(get(gca,'xlabel'),'position') ; +set(get(gca,'xlabel'),'position',[labxorigpos_data(1) labxorigpos_data_new(2)]) ; + + +% Reset all units to normalized to allow future resizing +set(get(gca,'xlabel'),'units','normalized') ; +set(get(gca,'ylabel'),'units','normalized') ; +set(get(gca,'title'),'units','normalized') ; +set(hText,'units','normalized') ; +set(gca,'units','normalized') ; + +if nargout < 1, + clear hText +end + diff --git a/xyz2channel.m b/xyz2channel.m new file mode 100644 index 0000000..3109540 --- /dev/null +++ b/xyz2channel.m @@ -0,0 +1,5 @@ +function [Channel]=xyz2channel(x) +Channel=[]; +for i=1:size(x,1); + Channel(i).Loc=x(i,:)'; +end diff --git a/xyz2channels.m b/xyz2channels.m new file mode 100644 index 0000000..3109540 --- /dev/null +++ b/xyz2channels.m @@ -0,0 +1,5 @@ +function [Channel]=xyz2channel(x) +Channel=[]; +for i=1:size(x,1); + Channel(i).Loc=x(i,:)'; +end diff --git a/xyzlabels.m b/xyzlabels.m new file mode 100644 index 0000000..5238072 --- /dev/null +++ b/xyzlabels.m @@ -0,0 +1,15 @@ +function []=xyzlabels(xl,yl,zl) +% xyzlabels - add labels to each axis +if nargin<3 + zl='z axis'; +end +if nargin<2 + yl='y axis' +end +if nargin<3 + xl='x axis' +end +axis on +xlabel(xl) +ylabel(yl) +zlabel(zl) diff --git a/yline.m b/yline.m new file mode 100644 index 0000000..39448a7 --- /dev/null +++ b/yline.m @@ -0,0 +1,39 @@ +function varargout = yline(x,varargin) +%YLINE - Create a vertical line on a plot +% [h] = yline(x) +% Adds as many vertical lines on the current plot as there are values in x. +% +% See also: line, xline + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-02 Creation +% +% ----------------------------- Script History --------------------------------- + +y=max(abs(get(gca, 'Ylim')))*[-1 1]; +%y=*10; +x=x(:); +x=[x*ones(1,2)]'; +y=repmat(y,size(x,2),1)'; + +holdstate=ishold; +hold on; +h=line(x,y,varargin{:}); +if ~holdstate + hold off; +end +LineStyles={'-', ':', '--', '-.'}; +for i=1:length(h); + set(h(i), 'LineStyle', LineStyles{ceil(i/size(get(gca, 'ColorOrder'),1))}); +end +if nargout==0 + return +end +varargout={h}; diff --git a/yprime.dll b/yprime.dll new file mode 100644 index 0000000000000000000000000000000000000000..fd4b620f371bd112697a15312ff38e9cd700e754 GIT binary patch literal 6144 zcmeHLZEPFm9e?Z`#RI2z?a~q?rd^9uEw8bE^_GTu^|#NgW~aY#Zo{Oh z?c9d0L!pEiS7Sq}91(+ZG#b;yfFi2Ns2GZhExY%Mk=TG@udThyRu0|K%2=D}PF6gA zrKOVXW48MKyG`b;%mRrOU}kJ;EwBI(0YniEIn`|f5H?mCI~ea~X7pt^kS#eFxQsd& z+ezYn#?B(nm##QtN552g>k7N3q%^pvS7D>NsMi}!fW{J0oqa&oWY9+G5Kzy?On@rO zi}Bdil3|*J4glG$Cg$eyVl4JRB0&<7h6ceGtu)0`O7V;tb-;?^8AaUm@KU@`$E$=3BKd0B(^tbZs!RRyD9h}bD^8bXx=#=)&GW%zPSmXCrg@B%@HpwA5Q zjb{sd?;T8JLV@o&U*HeaT1xa3_*wANfZrDQJ&S|klNHBuX0;zG6$sxdRd9eRI0twa*0|%Xr5!URuUCF5_*>c<(a4WeJb_ zn3=Di5WP&$aZ@IQ62VO{B5*tYg~~GX*4de3FH?=M$L+0q4QI%*t=4S2CEG1z7ERh= z^`6Y4nIHW**)P^;P5Osf|Fzj^E7QAd7Q{Ag^)E;}ZylS`XSBaeILbMmhxFAVmR?Ju zOK+0PBz;X*{E|e^!1G4bW2ZMk#`Ib$bdt*X8Pz^Hz7}<_EB9mM>>(Y+_3~pwNaFlx zuAg!t#~Cw)=(2H_o-M~if3tJjQ(T_$*RBZUXzxuqoC%uSV8cNo0^og<1 z;5Jfdza=wo!5ng}RqVvI&;~+2dK?H@zcrh*jD5t9egMCmk2?kAoO<=R!C5}V zFmgWYI*OS|)1DnQG@Ik=nUM22QUz2f)kx*Y1O!UgSeG^E3U;W9+5|@$$UE| z(Dg(NuV(S2Cd%qiGNMGags3WyCqt?-U`Ihc9i2PdTPvc3s2!3uv4>vjWKj}RqEkGq z1htrIXDy+_p+qPa6$8WK5k-w{xQlhgVq!#&4vVp*wj>2bHr7-bub|sFfy%qL3-5XO zGQ0te;5P#t0DAX(fG``5tD%Tu9|(t8L`iK=MuQqooir=!|8D|E`)}494={$`YV224 zvNUA)24}BV$xcCrw*q#dO7=Qr_+@{~s|~)rfJ1;M0poxZfK!0efXbSxqCWsV4_E|n z$S+V`fXZ@EO;!BYonyPHFBFL<(3_FuP4V6s@W6HRG}B?DolUDnhPetT~*MN(u<^VwFScM-j#M0ZflGU%NNUn~+2EA(@H z(BMmP$aX7z=v!5_Ju%cpe_$C8f&H=?tqA&I^c7H=g41|>)WPo2*3Mn6ZElw#fNLXU zUj*S$Ad)H@HNl2}WJ*N{-<5R>6Tox*DBSLK$c~pBZ#b?yHaWlRj5$v_Uvw6oYh4>% zE?2Xw(-m;3uBTkjxK6lUaMij+cc;78ExU)@DfhJdy!)zqk90ullLn+8N>53;G%h_O zosgcFekr{q{a*TmbV2%?)a=>m>F{)W0-onQFL++_ocDa> zoom_axes +% +% See also: axes + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-09-09 Creation +% +% ----------------------------- Script History --------------------------------- + +if nargin<1 + help(mfilename) + return +end +if nargin<2 + hAxesVector = gca; +end +if numel(zoom_factor) == 1 + zoom_factor(2) = zoom_factor(1); +end +if numel(zoom_factor) == 2 + zoom_factor(3) = 1; +end + +if nargin<3 + zoomPoint = []; +end + +m = 1-2.*(zoom_factor < 0); + +currLim = axis(hAxesVector); +currXLim = get(hAxesVector,'XLim'); +currYLim = get(hAxesVector,'YLim'); +if ~iscell(currLim) + currLim = {currLim}; + currXLim = {currXLim}; + currYLim = {currYLim}; +end +newXLim = cell(size(currXLim)); +newYLim = cell(size(currYLim)); +newLim = cell(size(currLim)); + +for i=1:numel(hAxesVector) + + hAxes = hAxesVector(i); + limits = getappdata(hAxes,'zoom_zoomOrigAxesLimits'); + if isempty(limits) + axis(hAxes, 'tight'); + limits = axis(hAxes); + end + maxbounds = objbounds(hAxes); + % Use current bounds, g161225, 163055 + if isempty(maxbounds) + maxbounds = axis(hAxes); + end + boundXLim = maxbounds(1:2); + boundYLim = maxbounds(3:4); + isXLog = strcmpi(get(hAxes,'XScale'),'log'); + isYLog = strcmpi(get(hAxes,'YScale'),'log'); + if isXLog + currXLim{i} = log10(currXLim{i}); + end + if isYLog + currYLim{i} = log10(currYLim{i}); + end + newXLim{i} = currXLim{i}; + newYLim{i} = currYLim{i}; + dx = diff(currXLim{i}); + dy = diff(currYLim{i}); + if isempty(zoomPoint) + center_x = currXLim{i}(1)+dx/2; + center_y = currYLim{i}(1)+dy/2; + else + center_x = zoomPoint(i,1); + center_y = zoomPoint(i,2); + end + zoomConstraint = 'none'; + + if ~any(isinf(currXLim{i})) && (strcmpi(zoomConstraint,'horizontal') || strcmp(zoomConstraint,'none')) + xmin = limits(1); + xmax = limits(2); + newdx = dx *m(:,1).*(1/zoom_factor(:,1)); + newdx = min(newdx,xmax-xmin); + % Limit zoom. + center_x = max(center_x,xmin + newdx/2); + center_x = min(center_x,xmax - newdx/2); + newXLim{i} = [max(xmin,center_x-newdx/2) min(xmax,center_x+newdx/2)]; + + % Check for log axes and return to linear values. + if isXLog + newXLim{i} = 10.^newXLim{i}(1:2); + end + end + + % Calculate new y-limits + if ~any(isinf(currYLim{i})) && (strcmpi(zoomConstraint,'vertical') || strcmp(zoomConstraint,'none')) + ymin = limits(3); + ymax = limits(4); + % newdy = dy * (1/zoom_factor(:,2).^(m(:,2)+1)); + newdy = dy *m(:,2).*(1/zoom_factor(:,2)); + newdy = min(newdy,ymax-ymin); + % Limit zoom. + center_y = max(center_y,ymin + newdy/2); + center_y = min(center_y,ymax - newdy/2); + newYLim{i} = [max(ymin,center_y-newdy/2) min(ymax,center_y+newdy/2)]; + + % Check for log axes and return to linear values. + if isYLog + newYLim{i} = 10.^newYLim{i}(1:2); + end + end + + %Check for strangeness in the limits: + if newXLim{i}(1) >= newXLim{i}(2) + newXLim{i} = currXLim{i}; + end + if newYLim{i}(1) >= newYLim{i}(2) + newYLim{i} = currYLim{i}; + end + newLim{i} = [newXLim{i},newYLim{i}]; + + axis(hAxes,newLim{i}); +end +return +% [ '[ cell2mat(x2cell(argouts('... +% ' ''ind2sub( size(getappdata(gca, ''''Traces'''')),nonzeros(idxmember(findobj(gca, ''''Visible'''', ''''off'''') , getappdata(gca,''''Traces''''))))'' ,'... +% ' ndims(getappdata(gca,''Traces''))))) ]' ]); diff --git a/zscore.m b/zscore.m new file mode 100644 index 0000000..d693072 --- /dev/null +++ b/zscore.m @@ -0,0 +1,41 @@ +function [z]=zscore(a,t,dim) +% zscore - compute z-score +% [z]=zscore(a, t ,[dim]) +if nargin<3 + dim=2; +end +sz=size(a); +if nargin<2 + t=1:sz(dim) +end +if length(t)==1 + t=1:t; +end +z = normalize(a,'baseline',dim,t,'z'); +return + + +% +% [z]=zscore(a, t ,[dim]) +% +% a: N-by-T matrix +% t: baseline samples: single value=nb of samples (t> z=zscore(F, 100) -> 100 first samples +% >> z=zscore(F, 1:100) -> idem +if nargin<3 + dim=2; +end +sz=size(a); +if nargin<2 + t=1:sz(dim) +end +if length(t)==1 + t=1:t; +end +nd=ndims(a); +a=permute(a, [dim setdiff(1:nd,dim)]); +z=a(:,:)./(repmat(std(a(t,:)),sz(dim),1) + eps); +z=reshape(z,sz([dim setdiff(1:nd,dim)])); +z=ipermute(z, [dim setdiff(1:nd,dim)]); + diff --git a/ztransform.m b/ztransform.m new file mode 100644 index 0000000..bec3373 --- /dev/null +++ b/ztransform.m @@ -0,0 +1,30 @@ +function [W,Z,P]=ztransform(X,N) +% ztransform - compute the Fisher's Z-transfom +% [W] = ztransform(X) +% [W,Z,P] = ztransform(X,N) may use Hotelling correction for small +% (N<=25) samples and also compute the corresponding Z-value and +% probability. +% +% +% Example +% >> load carsmall +% >> [w,z]=ztransform(corrcoef(Horsepower(1:30), Weight(1:30)),30); +% Since z > 1.96 we can conclude that the correlation is significant +% +% See also: zscore(), tcdf() +% Ref: http://fedc.wiwi.hu-berlin.de/xplore/tutorials/mvahtmlnode23.html + +W = log((1+X)./(1-X))./2; +if nargin<2 + return +end + +if N <= 25 + %Apply Hotelling correction + W= W - ((3*W)+tanh(W))/4/(N-1); + iV=sqrt(N-1); +else + iV=sqrt(N-3); +end +Z=iV*W; +P = 0.5 * erfc(Z ./ sqrt(2)); \ No newline at end of file

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x N(nf) x N(subjects) x [ ... ] +% nf is the number of factors (leading to nfx effects) +% Note: Subject MUST BE on dimension nf+1 +%OUTPUT: +% eGG: Greenhouse-Geisser epsilon: (nfx)-by-[...] matrix +% eHF: Huynh-Feldt epsilon: (nfx)-by-[...] matrix +% eLB: Lower-bound estimate = 1/(#levels-1) +% fx: cell list of effect (see myanova) +% +% See also: myanova +% Ref: http://www.psych.upenn.edu/~baron/rpsych.pdf + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-14 Creation +% +% ----------------------------- Script History --------------------------------- + +sx=size(X); +nX=ndims(X); +NM=prod(sx(nf+2:nX)); +N=sx(nf+1); % NB of subjects +NC=prod(sx(1:nf)); % NB of Cells +X=permute(X,[nf+1 1:nf nf+2:nX]); +fx={}; +for i=1:nf + fx=[fx ; num2cell(nchoosek(1:nf,i),2)]; +end +nfx=length(fx); +eGG=zeros([nfx,sx(nf+2:nX) 1]); +if nargout>1 + eHF=zeros([nfx,sx(nf+2:nX) 1]); +end +if nargout>2 + eLB=zeros([nfx,sx(nf+2:nX) 1]); +end + +for i=1:nfx + Y=permute(X,[1 fx{i}+1 setdiff(2:nf+1,[1+fx{i}]) nf+2:nX]); + NL=prod(sx(fx{i})); % Number of levels + Y=reshape(Y,N,NL,NC/NL,NM); + v=cov2(mean(Y,3)); + eGG(i,:)=NL^2*(mean(diag2(v)) - squeeze(mean(mean(v,2),1))').^2/(NL-1)./... + (squeeze(sum(sum(v.^2,1),2))' - 2*NL*squeeze(sum(mean(v,1).^2,2))' + NL^2*squeeze(mean(mean(v,1),2))'.^2); + clear v; + if nargout>1 + eHF(i,:)=(N*(NL-1)*eGG(i,:)-2)./((NL-1)*(N-1-(NL-1)*eGG(i,:))); + end + if nargout>2 + eLB(i,:)=1./(NL-1); + end +end + +return + + +function [y]=diag2(x) +% Diagonal of the first 2D plan of N-by-N-by-[...] multidimensional array X +sx=[size(x) 1]; +n=sx(1); +nm=prod(sx(3:end)); +y=x(repmat((1:n+1:n^2)',1,nm) +repmat(n^2*[0:nm-1],n,1)); +y=reshape(y,[sx(1),sx(3:end)]); + +function V = cov2(X,varargin) +%COV2 - Multidimensional Covariance +% [V] = cov2(X) +% Computes the M-by-M-by-[...] covariance matrix of data X, which are +% given as N-by-M-by-[...] matrix, N observations and M variables. +sX=[size(X) 1]; +X=reshape(X,sX(1),sX(2),prod(sX(3:end))); +X=X-repmat(sum(X,1)/sX(1),sX(1),1); 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a/spm/myspm_defaults.m b/spm/myspm_defaults.m new file mode 100644 index 0000000..0b3b75d --- /dev/null +++ b/spm/myspm_defaults.m @@ -0,0 +1,126 @@ + +% Sets the defaults which are used by SPM +% +% FORMAT spm_defaults +%_______________________________________________________________________ +% +% This file is intended to be customised for the site. +% Individual users can make copies which can be stored in their own +% matlab subdirectories. If ~/matlab is ahead of the SPM directory +% in the MATLABPATH, then the users own personal defaults are used. +% +% Care must be taken when modifying this file +%_______________________________________________________________________ +% @(#)spm_defaults.m 2.23 John Ashburner, Andrew Holmes 03/04/16 + +global defaults + +% Misc +%======================================================================= +defaults.grid = 0.4; +defaults.cmdline = 0; +defaults.logfile = ''; +defaults.printstr = [];%spm_figure('DefPrintCmd'),'spm2.ps']; + +% File format specific +%======================================================================= +defaults.analyze.multivol = 0; +defaults.analyze.flip = 1; % <<= Very important. Relates to L/R +% Changed by KND: +% defaults.analyze.flip = 0; % <<= Very important. Relates to L/R +% but now in the CMU it's 1... + +% Stats defaults +%======================================================================= +defaults.stats.maxmem = 2^20; +defaults.stats.maxres = 64; +defaults.stats.fmri.ufp = 0.001; +defaults.stats.fmri.t = 16; +defaults.stats.fmri.t0 = 8; +defaults.stats.pet.ufp = 0.05; + +defaults.stats.fmri.t0 = 1; + +defaults.modality = 'FMRI'; + + +% Mask defaults +%======================================================================= +defaults.mask.thresh = 0.8; + +% Realignment defaults +%======================================================================= +defaults.realign.estimate.quality = 0.75; +defaults.realign.estimate.weight = 0; +defaults.realign.estimate.interp = 2; +defaults.realign.estimate.wrap = [0 0 0]; +defaults.realign.write.mask = 1; +defaults.realign.write.interp = 4; +defaults.realign.write.wrap = [0 0 0]; + +% Unwarp defaults +%======================================================================= +defaults.unwarp.estimate.fwhm = 4; +defaults.unwarp.estimate.basfcn = [10 10]; +defaults.unwarp.estimate.regorder= 1; +defaults.unwarp.estimate.regwgt = 1e5; +defaults.unwarp.estimate.soe = 1; +defaults.unwarp.estimate.rem = 1; +defaults.unwarp.estimate.jm = 0; +defaults.unwarp.estimate.noi = 5; +defaults.unwarp.estimate.expround= 'Average'; +% +% Unwarp uses defaults.realign.write +% defaults for writing. +% + +% Coregistration defaults +%======================================================================= +defaults.coreg.estimate.cost_fun = 'nmi'; +defaults.coreg.estimate.sep = [4 2]; +defaults.coreg.estimate.tol = [0.02 0.02 0.02 0.001 0.001 0.001 0.01 0.01 0.01 0.001 0.001 0.001]; +defaults.coreg.estimate.fwhm = [7 7]; +defaults.coreg.write.interp = 1; +defaults.coreg.write.wrap = [0 0 0]; +defaults.coreg.write.mask = 0; + +% Spatial Normalisation defaults +%======================================================================= +defaults.normalise.estimate.smosrc = 8; +defaults.normalise.estimate.smoref = 0; +defaults.normalise.estimate.regtype = 'mni'; +defaults.normalise.estimate.weight = ''; +defaults.normalise.estimate.cutoff = 25; +defaults.normalise.estimate.nits = 16; +defaults.normalise.estimate.reg = 1; +defaults.normalise.estimate.wtsrc = 0; +defaults.normalise.write.preserve = 0; +defaults.normalise.write.bb = [[-78 -112 -50];[78 76 85]]; +%defaults.normalise.write.vox = [2 2 2]; +defaults.normalise.write.vox = [3 3 3]; +defaults.normalise.write.interp = 1; +defaults.normalise.write.wrap = [0 0 0]; + +% Segmentation defaults +%======================================================================= +defaults.segment.estimate.priors = str2mat(... + fullfile(spm('Dir'),'apriori','gray.mnc'),... + fullfile(spm('Dir'),'apriori','white.mnc'),... + fullfile(spm('Dir'),'apriori','csf.mnc')); +defaults.segment.estimate.reg = 0.01; +defaults.segment.estimate.cutoff = 30; +defaults.segment.estimate.samp = 3; +defaults.segment.estimate.bb = [[-88 88]' [-122 86]' [-60 95]']; +defaults.segment.estimate.affreg.smosrc = 8; +defaults.segment.estimate.affreg.regtype = 'mni'; +%defaults.segment.estimate.affreg.weight = fullfile(spm('Dir'),'apriori','brainmask.mnc'); +defaults.segment.estimate.affreg.weight = ''; +defaults.segment.write.cleanup = 1; +defaults.segment.write.wrt_cor = 1; + +% Bias field estimation defaults +%======================================================================= +defaults.bias.nbins = 256; % Number of histogram bins +defaults.bias.reg = 0.01; % Regularisation +defaults.bias.cutoff = 30; % DCT frequency cutoff (mm) + diff --git a/spm/myspm_get_data_xyz.m b/spm/myspm_get_data_xyz.m new file mode 100644 index 0000000..9e9009a --- /dev/null +++ b/spm/myspm_get_data_xyz.m @@ -0,0 +1,128 @@ +function [K,XYZvox,rXYZmm] = myspm_get_data_xyz(V,XYZmm,approx) +%MYSPM_GET_DATA_XYZ - gets data from image files at locations given in mm +% FORMAT [K,XYZvox,rXYZmm] = myspm_get_data(V,XYZmm,approx); +% +%INPUTS +% V: (cell) array of M filenames or volume structures from sspm_vol +% XYZmm: 3-by-N voxels locations to read in millimeters +% approx: Approximation mode. if approx==NaN (default) returns NaN for +% voxels out of the image else approximates see spm_sample_vol() +% +%OUPUTS +% K: M-by-N values read in the files +% XYZvox: 3-by-M-by-N matrix of voxels locations read in voxel space +% rXYZmm: 3-by-M-by-N matrix of actual coordinates of the voxels read +% +% Example +% >> spm_get_data_xyz(P,[45 -50 +50]) retrieves voxel intensity in +% the VMPFC of the MNI template... +% +% See also: spm_get_data + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-22 Creation +% +% ----------------------------- Script History --------------------------------- +if isstruct(V) +% output of a dir + if isfield(V,'name') + V={V.name}; + end +end + +if ~isstruct(V) + V = spm_vol(V); + try + V = cat(2,V{:}); + end +end + +if nargin<3 + approx=NaN; +end +if isempty(approx) + approx=NaN; +end +if numel(approx)==1 + approx(1:length(V))=approx; +end +if nargin<2 + XYZmm = 'all'; +end +if ~ischar(XYZmm) + if ~isequal(size(XYZmm,1),3) + error('XYZ input should be 3-by-N') + end + % number of voxels to retrieve + %--------------------------------------------------------------- + n=size(XYZmm,2); + % preallocate outputs + %--------------------------------------------------------------- + K = zeros( length(V),n); + XYZvox= zeros(3,length(V),n); + % expand approximation mode to match size of inputs + %--------------------------------------------------------------- + if prod(size(approx))==1 + approx=repmat(approx,length(V),1); + end + xyz = [XYZmm; ones(1,n)]; + xyz(isinf(xyz)) = 1e10*sign(xyz(isinf(xyz))); +else + switch (XYZmm) + case 'all' + + case 'roi' + % To do: retrieve a region from a given atlas: + % aal:sup front gyrus:Right; + % brodmannn:4:Left etc. + end +end +for i = 1:length(V) + if exist('xyz', 'var') + % trick from spm_XYZreg + vox = round(inv(V(i).mat)*xyz); + j = all(vox(1:3,:)<=repmat(V(i).dim(1:3)',1,n)) & all(vox(1:3,:)>zeros(3,n)); + elseif i==1 + % retrieve all voxels + h=spm_vol(V(i)); + [vox(1,:),vox(2,:),vox(3,:)] = ind2sub(h.dim, 1:prod(h.dim)); + j=logical(ones(size(vox(1,:)))); + n=length(j); + % preallocate outputs + %--------------------------------------------------------------- + K = zeros( length(V),n); + XYZvox= zeros(3,length(V),n); + end + if any(j) + %-Load mask image within current mask & update mask + %------------------------------------------------------- + K(i,j) = spm_sample_vol(V(i),vox(1,j),vox(2,j),vox(3,j),0); + end + if isnan(approx(i)) + K(i,~j)=NaN; + else + K(i,~j) = spm_sample_vol(V(i),vox(1,~j),vox(2,~j),vox(3,~j),approx(i)); + end + XYZvox(1:3,i,1:n) = vox(1:3,:); + if nargout > 2 + if i==1 + % pre-allocation might be useless if later on, a V(i) volume is + % bigger than the first one and all voxels are retrieved) + rXYZmm= zeros(3,length(V),n); + end + if ~exist('xyz', 'var') + rXYZmm(1:4,i,:) = NaN; + rXYZmm(1:4,i,1:n)=V(i).mat*[vox(:,:) ; ones(1,n)]; + rXYZmm(4,:) = NaN; + else + rXYZmm(1:3,i,1:n) = V(i).mat(1:3,:)*xyz; + end + end +end diff --git a/spm/myspm_hierarchy.m b/spm/myspm_hierarchy.m new file mode 100644 index 0000000..e69de29 diff --git a/spm/myspm_struct_info.m b/spm/myspm_struct_info.m new file mode 100644 index 0000000..23488f1 --- /dev/null +++ b/spm/myspm_struct_info.m @@ -0,0 +1,172 @@ +% Short Explanation of the Fields of SPM struct +% ============================================= +% SPM.xY Data +% --------------------------------------------------------------------- +% xY.P filenames of images (with path) +% xY.VY handle to images (from spm_vol) +% VY.fname filename +% VY.dim image dimensions +% VY.mat transformation matrix +% VY.pinfo plane info (scale factor for every image) +% VY.descrip description string +% VY.n ? +% VY.private.hdr analyze header +% VY.userdata user data (usually not used) +% SPM.xX Design Matrix +% --------------------------------------------------------------------- +% xX.X Design Matrix (raw values) +% xX.iH column indices for condition effects partition +% xX.iC column indices for covariates of interest partition +% xX.iB column indices for constants +% xX.iG colunn indices for nuisances covariates partition +% xX.name regressor names (cell array) +% xX.I indicator for factor levels +% xX.sF factor names +% xX.K filter for design matrix +% xX.W pre-whitening matrix (WY = WX*b + We) +% xX.xKXs struct for filtered and pre-whitened design matrix (K*W*X) +% xKXs.X the filtered and whitened design matrix +% xKXs.tol tolerance [max(size(xKXs.X))*max(abs(xKXs.ds))*eps] +% xKXs.ds vector of singular values [diag(s) from [u,s,v]=svd(xKXs.X,0)] +% xKXs.u u as in X = u*diag(ds)*v' [taken from [u,s,v]=svd(xKXs.X,0)] +% xKXs.v v as in X = u*diag(ds)*v' [taken from [u,s,v]=svd(xKXs.X,0)] +% xKXS.rk rank = sum(xKXs.ds > xKXs.tol) +% xKXs.oP orthogonal projector on X +% xKXs.oPp orthogonal projector on X' +% xKXs.ups space in which this one is embedded +% xKXs.sus subspace +% xX.pKX pseudo-inverse of filtered and pre-whitened design +% matrix +% xX.Bcov covariance matrix of parameter estimates +% [diag(Bcov) = variance of parameter estimates] +% xX.V filtered and pre-whitened error covariance matrix +% (K*W*xVi.Vi*W'*K') +% xX.trRV trace of R*V (necessary for effective df) +% xX.trRVRV trace of RVRV (necessary of effective df) +% xX.erdf effective residual df (trRV^2/trRVRV) +% xX.nKX filtered design matrix scaled for display +% SPM.xC Covariate details +% --------------------------------------------------------------------- +% xC.rc raw (as entered) i-th covariate +% xC.rcname name of this covariate +% xC.c covariate as appears in design matrix +% xC.cname cellstr containing names corresponding to xC(i).c +% xC.iCC covariate contering option +% xC.iCFT covariate by factor interaction option +% xC.type covariate type (1=interest,2=nuisance,3=global) +% xC.cols columns of design matrix corresponding to xC(i).c +% xC.descrip description of covariate +% SPM.xGX Global options and values +% --------------------------------------------------------------------- +% xGX.iGXcalc global calculation option used +% xGX.sGCcalc string describing global calculations used +% xGX.rg raw globals (before scaling) +% [mean image intensity, not session-specific] +% xGX.gSF global scaling factor (applied to xGX.rg) +% [global mean, session-specific] +% xGX.GM global mean (gSF*rg = GM) +% xGX.iGMsca grand mean scaling option +% xGX.sGMsca string describing grand mean (/proportional) +% scaling option +% xGX.iGC global covariate centering option +% xGX.sGC string describing global covariate centering option +% xGX.gc center for global covariate +% xGX.iGloNorm global normalization option +% xGX.sGloNorm string describing global normalization option +% SPM.xVi Non-spericity options +% --------------------------------------------------------------------- +% xVi.iid independent and identical errors (0/1) +% xVi.I see SPM.xX.I +% xVi.sF see SPM.xX.sF +% xVi.var factor to correct for inhomogenous variance (?) +% xVi.dep factor to correct of non-identical errors (?) +% xVi.Vi cell array with model components for error GLM +% (design matrices for error) +% xVi.h hyperparameter estimates for xVi.Vi +% (usually called lambda's) +% xVi.Cy spatially whitened covariance matrix of data (Y*Y') +% [used by ReML to estimate h)] +% xVi.CY fitted covariance matrix of data (Y-)*(Y-') +% [used by spm_Bayes] +% SPM.xM Masking options +% --------------------------------------------------------------------- +% xM.T threshold masking values (-Inf = 'none') +% xM.TH nScan x 1 vector of analysis thresholds +% xM.I implicit masking (0 = 'none'; 1 = zero/NaN) +% xM.VM handle to explicit masking image (see SPM.xY.VY) +% xM.xs struture describing masking options +% SPM.xVol information about image dimensions etc. +% --------------------------------------------------------------------- +% xVol.M transformation matrix vox2mm +% xVol.iM transformation matrix mm2vox +% xVol.DIM images dimensions +% xVol.FWHM smoothing filter width (in voxels) +% xVol.R vector of resel counts (in resels) +% xVol.S Lebelgue measure of volume (in voxels) +% xVol.VRpv handle to Resels/voxel images (RPV.img) +% (see SPM.xY.VY) +% SPM.Vbeta parameter estimates +% --------------------------------------------------------------------- +% handle to beta images (see SPM.xY.VY) +% SPM.VResMS residual sum of squares +% --------------------------------------------------------------------- +% handle to images of residuals (ResMS.img) +% SPM.VM mask image +% --------------------------------------------------------------------- +% handle to mask images of analysis voxels +% (mask.img) +% SPM.xCon structure holding contrast information +% --------------------------------------------------------------------- +% xCon.name contrast name +% xCon.STAT type of statistic (T/F) +% xCon.c contrast vector/matrix +% xCon.X0 reduced design matrix (spans design space under Ho) +% xCon.iX0 indicates how contrast was specified +% if by "columns for reduces design" then column +% indices, otherwise either 'c', 'c+', or 'X0' +% see spm_FcUtil +% xCon.X1o remaining design space (orthogonal to X0) +% xCon.eidf effective interest df (numerator df) +% xCon.Vcon handle to contrast image +% (con_xxxx.img,ess_xxxx.img) +% xCon.Vspm handle to statistical image +% (spmT_xxxx.img/spmF_xxxx.img) +% SPM.Sess regressors in design matrix (session-specific) +% --------------------------------------------------------------------- +% Sess.U experimental regressors +% U.name name of regressors +% U.ons onset vector +% U.dur duration (0 = events) +% U.P parametric modulations +% P.name name of parametric modulator +% P.h order of expansion +% P.i +% U.dt internal temporal resolution RT/T +% U.pst peri-stimulus time (specifies occurence of +% scans in relation to events) +% C covariates +% C.C nScan x number of covariates matrix +% C.name cell array with names of covariates +% row indices of rows of design matrix belonging to +% the session +% col indices of columns of design matrix belongin to +% the session +% Fc structrue holding information on F-contrasts +% Fc.i index of F-contrast (?) +% FC.name name of F-contrast +% SPM.xBF structure with information if basis functions +% --------------------------------------------------------------------- +% xBF.name name of basis function of set of bassi functions +% xBF.T time bins +% xBF.T0 reference bin +% xBF.UNITS onsets in scans or seconds +% xBF.Volterra (1 = linear, normal HRF, 2 = trial interactions) +% xBF.dt internal temporal resolution (RT/T) +% xBF.length length of basis functions (in sec) +% xBF.order ? (1 = HRD no order) +% xBF.bf vector with basis functions +% SPM.xsDes structure describing design +% SPM.SPMid version information of SPM +% SPM.swd analysis directory (holding SPM.mat) +% SPM.nscan number of images +help(mfilename) \ No newline at end of file diff --git a/spm/myspm_updatepath.m b/spm/myspm_updatepath.m new file mode 100644 index 0000000..746beb7 --- /dev/null +++ b/spm/myspm_updatepath.m @@ -0,0 +1,89 @@ +function Q = myspm_updatepath(P,varargin) +%MYSPM_UPDATEPATH - Update SPM path/working directory. +% [Q] = myspm_updatepath(P) +% [SPM] = myspm_updatepath(spmfilename) +% [Q] = myspm_updatepath(P,nwd) +% [SPM] = myspm_updatepath(spmfilename,nwd,save?) +% +% Example +% >> myspm_updatepath +% +% See also: spm_vol + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-07-22 Creation +% +% ----------------------------- Script History --------------------------------- + +spmfilename=[]; +imgfilename=[]; +persistent pwd +persistent nwd +Q=P; +if nargin>1 + nwd=varargin{2}; + if ~exist(nwd, 'dir') + warning('myspm_updatepath:NotADirectory','Updated directory doesn''t exist: %s',nwd); + end +end +if nargin<3 + dosave=NaN; +else + dosave=varargin{3}; +end + +if iscell(P) + Q=cell(size(P)); + for i=1:numel(P) + Q{i}=myspm_updatepath(P{i},varargin{:}); + return + end +end + +if isstruct(P) + SPM=P; + clear P; + swd = SPM.swd; +elseif ischar(P) + try + % test if it's an SPM file + clear SPM + load(P) + swd = SPM.swd; + spmfilename = P; + clear P; + catch ME + [swd,imgfilename,imgfileext] = fileparts(P); + end +else + error('Wrong input P must be an image/SPM filename or a SPM struct.') +end +if isempty(pwd) || ~strmatch(pwd,swd,'exact') + if ~isempty(spmfilename) + pwd=fileparts(spmfilename); + end + nwd=uigetdir(pwd,sprintf('Pick a new SPM folder instead of:\n%s',swd)); + if isequal(nwd,0) + return + end +end +fprintf(1,'Updating former path: %s\ninto: %s\n', pwd,nwd); +pwd=swd; +if exist('SPM', 'var') + SPM.swd=nwd; + if dosave && ~isempty(spmfilename) + save(spmfilename, '-APPEND', 'SPM'); + end + Q=SPM; +end +if ~isempty(imgfilename) + Q=fullfile(nwd,[imgfilename,imgfileext]); +end +return diff --git a/spm/nii_for_spm2/@file_array/Contents.m b/spm/nii_for_spm2/@file_array/Contents.m new file mode 100644 index 0000000..b8c7a8d --- /dev/null +++ b/spm/nii_for_spm2/@file_array/Contents.m @@ -0,0 +1,51 @@ +% +% File Array Object +% +% file_array - create a file_array +% horzcat - horizontal concatenation +% vertcat - vertical concatenation +% size - size of array +% length - length of longest dimension +% subsref - subscripted reference +% end - last index in an indexing expression +% resize - resize (but only of simple file_array structures) +% +% other operations are unlikely to work. +% +% Example usage. +% +% % Create a file array object by mapping test_le.img +% % to a 256x256x100 array, of datatype float32, stored +% % in a little-endian way starting at byte 0. +% fa0 = file_array('test_le.img',[256 256 100], 'FLOAT32-LE',0) +% +% % Creating an object from test_be.img, but skipping +% % the first plane of data. Data stored as big-endian +% fa1 = file_array('test_be.img',[256 256 99], 'FLOAT32-BE',4*256*256) +% +% % Reshape procedure +% fa2 = reshape(fa1,[128 2 256 99]) +% +% % Concatenation +% fa3 = [[fa0 fa0]; [fa0 fa0]] +% fa4 = cat(3,fa0,fa1) +% +% % Note that reshape will not work on the above +% % concatenated objects +% +% % Accessing values from the objects +% img = fa1(:,:,40); +% pixval = fa4(50,50,:); +% small = fa1(1:2:end,1:2:end,40); +% +% % Determining dimensions +% size(fa4) +% size(fa2) +% length(fa0) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: Contents.m 1601 2008-05-12 14:11:02Z guillaume $ + + diff --git a/spm/nii_for_spm2/@file_array/cat.m b/spm/nii_for_spm2/@file_array/cat.m new file mode 100755 index 0000000..0698818 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/cat.m @@ -0,0 +1,40 @@ +function o = cat(dr,varargin) +% Concatenate file_array objects. The result is a non-simple object +% that can no longer be reshaped. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: cat.m 253 2005-10-13 15:31:34Z guillaume $ + + +if dr>32 || dr<0, error('Unknown command option.'); end; +dr = max(round(dr),1); +d = ones(nargin-1,16); +tmp = {}; +dpos = 0; +for i=1:nargin-1, + vi = varargin{i}; + if strcmp(class(vi),'file_array') + sz = size(vi); + d(i,1:length(sz)) = sz; + svi = struct(vi); + svi = svi(:); + for j=1:length(svi(:)), + if length(svi(j).pos)1, + fprintf(' %s object: ', class(obj)); + sz = size(obj); + if length(sz)>4, + fprintf('%d-D\n',length(sz)); + else + for i=1:(length(sz)-1), + fprintf('%d-by-',sz(i)); + end; + fprintf('%d\n',sz(end)); + end; +else + display(mystruct(obj)) +end; +return; +%======================================================================= + +%======================================================================= +function t = mystruct(obj) +fn = fieldnames(obj); +for i=1:length(fn) + t.(fn{i}) = subsref(obj,struct('type','.','subs',fn{i})); +end; +return; +%======================================================================= diff --git a/spm/nii_for_spm2/@file_array/display.m b/spm/nii_for_spm2/@file_array/display.m new file mode 100755 index 0000000..b8136de --- /dev/null +++ b/spm/nii_for_spm2/@file_array/display.m @@ -0,0 +1,14 @@ +function display(obj) +% Display a file_array object +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: display.m 253 2005-10-13 15:31:34Z guillaume $ + + +disp(' '); +disp([inputname(1),' = ']) +disp(' '); +disp(obj) +disp(' ') diff --git a/spm/nii_for_spm2/@file_array/double.m b/spm/nii_for_spm2/@file_array/double.m new file mode 100755 index 0000000..93ccb69 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/double.m @@ -0,0 +1,12 @@ +function out = double(fa) +% Convert to double precision +% FORMAT double(fa) +% fa - a file_array +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: double.m 253 2005-10-13 15:31:34Z guillaume $ + +out = double(numeric(fa)); + diff --git a/spm/nii_for_spm2/@file_array/end.m b/spm/nii_for_spm2/@file_array/end.m new file mode 100755 index 0000000..a7cff36 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/end.m @@ -0,0 +1,17 @@ +function en = end(a,k,n) +% Overloaded end function for file_array objects. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: end.m 253 2005-10-13 15:31:34Z guillaume $ + +dim = size(a); +if k>length(dim) + en = 1; +else + if n=1, a = fname(a,varargin{1}); end; +if nargin>=2, a = dim(a,varargin{2}); end; +if nargin>=3, a = dtype(a,varargin{3}); end; +if nargin>=4, a = offset(a,varargin{4}); end; +if nargin>=5, a = scl_slope(a,varargin{5}); end; +if nargin>=6, a = scl_inter(a,varargin{6}); end; + +a.pos = ones(size(a.dim)); +a = class(a,'file_array'); diff --git a/spm/nii_for_spm2/@file_array/horzcat.m b/spm/nii_for_spm2/@file_array/horzcat.m new file mode 100755 index 0000000..dcada1c --- /dev/null +++ b/spm/nii_for_spm2/@file_array/horzcat.m @@ -0,0 +1,11 @@ +function o = horzcat(varargin) +% Horizontal concatenation of file_array objects +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: horzcat.m 253 2005-10-13 15:31:34Z guillaume $ + +o = cat(2,varargin{:}); +return; + diff --git a/spm/nii_for_spm2/@file_array/length.m b/spm/nii_for_spm2/@file_array/length.m new file mode 100755 index 0000000..acb7689 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/length.m @@ -0,0 +1,11 @@ +function l = length(x) +% Overloaded length function for file_array objects +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: length.m 253 2005-10-13 15:31:34Z guillaume $ + + +l = max(size(x)); + diff --git a/spm/nii_for_spm2/@file_array/loadobj.m b/spm/nii_for_spm2/@file_array/loadobj.m new file mode 100644 index 0000000..06de737 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/loadobj.m @@ -0,0 +1,14 @@ +function b = loadobj(a) +% loadobj for file_array class +% _______________________________________________________________________ +% Copyright (C) 2008 Wellcome Trust Centre for Neuroimaging + +% +% $Id: loadobj.m 1746 2008-05-28 17:43:42Z guillaume $ + +if isa(a,'file_array') + b = a; +else + a = rmfield(a, 'permission'); + b = file_array(a); +end diff --git a/spm/nii_for_spm2/@file_array/mystruct.m b/spm/nii_for_spm2/@file_array/mystruct.m new file mode 100755 index 0000000..3dd255d --- /dev/null +++ b/spm/nii_for_spm2/@file_array/mystruct.m @@ -0,0 +1,16 @@ +function t = mystruct(obj) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: mystruct.m 253 2005-10-13 15:31:34Z guillaume $ + + +if numel(obj)~=1, + error('Too many elements to convert'); +end; +fn = fieldnames(obj); +for i=1:length(fn) + t.(fn{i}) = subsref(obj,struct('type','.','subs',fn{i})); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/ndims.m b/spm/nii_for_spm2/@file_array/ndims.m new file mode 100755 index 0000000..43ecabe --- /dev/null +++ b/spm/nii_for_spm2/@file_array/ndims.m @@ -0,0 +1,12 @@ +function out = ndims(fa) +% Number of dimensions +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: ndims.m 253 2005-10-13 15:31:34Z guillaume $ + + +out = size(fa); +out = length(out); + diff --git a/spm/nii_for_spm2/@file_array/numel.m b/spm/nii_for_spm2/@file_array/numel.m new file mode 100755 index 0000000..f561385 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/numel.m @@ -0,0 +1,14 @@ +function t = numel(obj) +% Number of simple file arrays involved. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: numel.m 253 2005-10-13 15:31:34Z guillaume $ + + +% Should be this, but it causes problems when accessing +% obj as a structure. +%t = prod(size(obj)); + +t = numel(struct(obj)); diff --git a/spm/nii_for_spm2/@file_array/numeric.m b/spm/nii_for_spm2/@file_array/numeric.m new file mode 100755 index 0000000..5b4acdf --- /dev/null +++ b/spm/nii_for_spm2/@file_array/numeric.m @@ -0,0 +1,14 @@ +function out = numeric(fa) +% Convert to numeric form +% FORMAT numeric(fa) +% fa - a file_array +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: numeric.m 253 2005-10-13 15:31:34Z guillaume $ + + +[vo{1:ndims(fa)}] = deal(':'); +out = subsref(fa,struct('type','()','subs',{vo})); + diff --git a/spm/nii_for_spm2/@file_array/permute.m b/spm/nii_for_spm2/@file_array/permute.m new file mode 100755 index 0000000..a6c79b6 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/permute.m @@ -0,0 +1,10 @@ +function varargout = permute(varargin) +% Can not be permuted. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: permute.m 253 2005-10-13 15:31:34Z guillaume $ + + +error('file_array objects can not be permuted.'); diff --git a/spm/nii_for_spm2/@file_array/private/datatypes.m b/spm/nii_for_spm2/@file_array/private/datatypes.m new file mode 100755 index 0000000..f6e6ca5 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/datatypes.m @@ -0,0 +1,56 @@ +function dt = datatypes +% Datatype +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: datatypes.m 253 2005-10-13 15:31:34Z guillaume $ + + +persistent dtype +if isempty(dtype), + t = true; + f = false; + table = {... + 0 ,'UNKNOWN' ,'uint8' ,@uint8 ,1,1 ,t,t,f + 1 ,'BINARY' ,'uint1' ,@logical,1,1/8,t,t,f + 256 ,'INT8' ,'int8' ,@int8 ,1,1 ,t,f,t + 2 ,'UINT8' ,'uint8' ,@uint8 ,1,1 ,t,t,t + 4 ,'INT16' ,'int16' ,@int16 ,1,2 ,t,f,t + 512 ,'UINT16' ,'uint16' ,@uint16 ,1,2 ,t,t,t + 8 ,'INT32' ,'int32' ,@int32 ,1,4 ,t,f,t + 768 ,'UINT32' ,'uint32' ,@uint32 ,1,4 ,t,t,t + 1024,'INT64' ,'int64' ,@int64 ,1,8 ,t,f,f + 1280,'UINT64' ,'uint64' ,@uint64 ,1,8 ,t,t,f + 16 ,'FLOAT32' ,'float32' ,@single ,1,4 ,f,f,t + 64 ,'FLOAT64' ,'double' ,@double ,1,8 ,f,f,t + 1536,'FLOAT128' ,'float128',@crash ,1,16 ,f,f,f + 32 ,'COMPLEX64' ,'float32' ,@single ,2,4 ,f,f,f + 1792,'COMPLEX128','double' ,@double ,2,8 ,f,f,f + 2048,'COMPLEX256','float128',@crash ,2,16 ,f,f,f + 128 ,'RGB24' ,'uint8' ,@uint8 ,3,1 ,t,t,f}; + dtype = struct(... + 'code' ,table(:,1),... + 'label' ,table(:,2),... + 'prec' ,table(:,3),... + 'conv' ,table(:,4),... + 'nelem' ,table(:,5),... + 'size' ,table(:,6),... + 'isint' ,table(:,7),... + 'unsigned' ,table(:,8),... + 'min',-Inf,'max',Inf',... + 'supported',table(:,9)); + for i=1:length(dtype), + if dtype(i).isint + if dtype(i).unsigned + dtype(i).min = 0; + dtype(i).max = 2^(8*dtype(i).size)-1; + else + dtype(i).min = -2^(8*dtype(i).size-1); + dtype(i).max = 2^(8*dtype(i).size-1)-1; + end; + end; + end; +end; + +dt = dtype; diff --git a/spm/nii_for_spm2/@file_array/private/dim.m b/spm/nii_for_spm2/@file_array/private/dim.m new file mode 100755 index 0000000..cf6a6c1 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/dim.m @@ -0,0 +1,37 @@ +function varargout = dim(varargin) +% Format +% For getting the value +% dat = dim(obj) +% +% For setting the value +% obj = dim(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: dim.m 253 2005-10-13 15:31:34Z guillaume $ + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wrong number of arguments.'); +end; +return; + +function dat = ref(obj) +dat = obj.dim; +return; + +function obj = asgn(obj,dat) +if isnumeric(dat) && all(dat>=0) && all(rem(dat,1)==0), + dat = [double(dat(:)') 1 1]; + lim = max([2 find(dat~=1)]); + dat = dat(1:lim); + obj.dim = dat; +else + error('"dim" must be a vector of positive integers.'); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/private/dtype.m b/spm/nii_for_spm2/@file_array/private/dtype.m new file mode 100755 index 0000000..5ca51a4 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/dtype.m @@ -0,0 +1,86 @@ +function varargout = dtype(varargin) +% Format +% For getting the value +% dat = dtype(obj) +% +% For setting the value +% obj = dtype(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: dtype.m 466 2006-03-01 15:14:22Z john $ + + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wring number of arguments.'); +end; +return; + +function t = ref(obj) +d = datatypes; +mch = find(cat(1,d.code)==obj.dtype); +if isempty(mch), t = 'UNKNOWN'; else t = d(mch).label; end; +if obj.be, t = [t '-BE']; else t = [t '-LE']; end; +return; + +function obj = asgn(obj,dat) +d = datatypes; +if isnumeric(dat) + if numel(dat)>=1, + mch = find(cat(1,d.code)==dat(1)); + if isempty(mch) || mch==0, + fprintf('Invalid datatype (%d).', dat(1)); + disp('First part of datatype should be of one of the following'); + disp(sortrows([num2str(cat(1,d.code)) ... + repmat(' ',numel(d),2) strvcat(d.label)])); + %error(['Invalid datatype (' num2str(dat(1)) ').']); + return; + end; + obj.dtype = double(dat(1)); + end; + if numel(dat)>=2, + obj.be = double(dat(2)~=0); + end; + if numel(dat)>2, + error('Too many elements in numeric datatype.'); + end; +elseif ischar(dat), + dat1 = lower(dat); + sep = find(dat1=='-' | dat1=='/'); + sep = sep(sep~=1); + if ~isempty(sep), + c1 = dat1(1:(sep(1)-1)); + c2 = dat1((sep(1)+1):end); + else + c1 = dat1; + c2 = ''; + end; + mch = find(strcmpi(c1,lower({d.label}))); + if isempty(mch), + disp('First part of datatype should be of one of the following'); + disp(sortrows([num2str(cat(1,d.code)) ... + repmat(' ',numel(d),2) strvcat(d.label)])); + %error(['Invalid datatype (' c1 ').']); + return; + else + obj.dtype = double(d(mch(1)).code); + end; + if any(c2=='b'), + if any(c2=='l'), + error('Cannot be both big and little endian.'); + end; + obj.be = 1; + elseif any(c2=='l'), + obj.be = 0; + end; +else + error('Invalid datatype.'); +end; +return; + diff --git a/spm/nii_for_spm2/@file_array/private/fname.m b/spm/nii_for_spm2/@file_array/private/fname.m new file mode 100755 index 0000000..065a02c --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/fname.m @@ -0,0 +1,35 @@ +function varargout = fname(varargin) +% Format +% For getting the value +% dat = fname(obj) +% +% For setting the value +% obj = fname(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: fname.m 253 2005-10-13 15:31:34Z guillaume $ + + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wrong number of arguments.'); +end; +return; + +function dat = ref(obj) +dat = obj.fname; +return; + +function obj = asgn(obj,dat) +if ischar(dat) + obj.fname = deblank(dat(:)'); +else + error('"fname" must be a character string.'); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/private/mystruct.m b/spm/nii_for_spm2/@file_array/private/mystruct.m new file mode 100755 index 0000000..614ed7d --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/mystruct.m @@ -0,0 +1,16 @@ +function t = mystruct(obj) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: mystruct.m 488 2006-03-30 11:59:54Z john $ + + +if numel(obj)~=1, + error('Too many elements to convert'); +end; +fn = fieldnames(obj); +for i=1:length(fn) + t.(fn{i}) = subsref(obj,struct('type','.','subs',fn{i})); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/private/offset.m b/spm/nii_for_spm2/@file_array/private/offset.m new file mode 100755 index 0000000..128b3ee --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/offset.m @@ -0,0 +1,35 @@ +function varargout = offset(varargin) +% Format +% For getting the value +% dat = offset(obj) +% +% For setting the value +% obj = offset(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: offset.m 253 2005-10-13 15:31:34Z guillaume $ + + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wrong number of arguments.'); +end; +return; + +function dat = ref(obj) +dat = obj.offset; +return; + +function obj = asgn(obj,dat) +if isnumeric(dat) && numel(dat)==1 && dat>=0 && rem(dat,1)==0, + obj.offset = double(dat); +else + error('"offset" must be a positive integer.'); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/private/resize_scales.m b/spm/nii_for_spm2/@file_array/private/resize_scales.m new file mode 100755 index 0000000..0149d23 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/resize_scales.m @@ -0,0 +1,24 @@ +function s1 = resize_scales(s0,dim,args) +% Resize scalefactors +% _________________________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: resize_scales.m 315 2005-11-28 16:48:59Z john $ + +dim = [dim ones(1,max(numel(args)-numel(dim),0))]; +args1 = cell(1,numel(args)); +for i=1:numel(args), + if max(args{i})>dim(i) || min(args{i})<1, + error('Index exceeds matrix dimensions (1).'); + end; + + if size(s0,i)==1, + args1{i} = ones(size(args{i})); + else + args1{i} = args{i}; + end; +end; + +s1 = s0(args1{:}); + diff --git a/spm/nii_for_spm2/@file_array/private/scl_inter.m b/spm/nii_for_spm2/@file_array/private/scl_inter.m new file mode 100755 index 0000000..9ad7b9a --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/scl_inter.m @@ -0,0 +1,36 @@ +function varargout = scl_inter(varargin) +% Format +% For getting the value +% dat = scl_inter(obj) +% +% For setting the value +% obj = scl_inter(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: scl_inter.m 253 2005-10-13 15:31:34Z guillaume $ + + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wrong number of arguments.'); +end; +return; + +function dat = ref(obj) +dat = obj.scl_inter; +return; + +function obj = asgn(obj,dat) +if isnumeric(dat), % && numel(dat)<=1, + obj.scl_inter = double(dat); +else + error('"scl_inter" must be numeric.'); +end; +return; + diff --git a/spm/nii_for_spm2/@file_array/private/scl_slope.m b/spm/nii_for_spm2/@file_array/private/scl_slope.m new file mode 100755 index 0000000..c68a71c --- /dev/null +++ b/spm/nii_for_spm2/@file_array/private/scl_slope.m @@ -0,0 +1,35 @@ +function varargout = scl_slope(varargin) +% Format +% For getting the value +% dat = scl_slope(obj) +% +% For setting the value +% obj = scl_slope(obj,dat) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: scl_slope.m 253 2005-10-13 15:31:34Z guillaume $ + + + +if nargin==2, + varargout{1} = asgn(varargin{:}); +elseif nargin==1, + varargout{1} = ref(varargin{:}); +else + error('Wrong number of arguments.'); +end; +return; + +function dat = ref(obj) +dat = obj.scl_slope; +return; + +function obj = asgn(obj,dat) +if isnumeric(dat), % && numel(dat)<=1, + obj.scl_slope = double(dat); +else + error('"scl_slope" must be numeric.'); +end; +return; diff --git a/spm/nii_for_spm2/@file_array/reshape.m b/spm/nii_for_spm2/@file_array/reshape.m new file mode 100755 index 0000000..0a5d1d2 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/reshape.m @@ -0,0 +1,21 @@ +function a = reshape(b,varargin) +% Overloaded reshape function for file_array objects +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: reshape.m 253 2005-10-13 15:31:34Z guillaume $ + + +if length(struct(b))~=1, error('Can only reshape simple file_array objects.'); end; + +args = []; +for i=1:length(varargin), + args = [args varargin{i}(:)']; +end; +if prod(args)~=prod(b.dim), + error('To RESHAPE the number of elements must not change.'); +end; +a = b; +a.dim = args; + diff --git a/spm/nii_for_spm2/@file_array/size.m b/spm/nii_for_spm2/@file_array/size.m new file mode 100644 index 0000000..c116250 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/size.m @@ -0,0 +1,43 @@ +function d = size(a,varargin) +% overloaded size function for file_array objects. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: size.m 1037 2007-12-21 13:02:53Z john $ + + +sa = struct(a); +nd = 0; +for i=1:numel(sa), + nd = max(nd,numel(sa(i).dim)); +end +nd = nd+1; + +dim = ones(length(sa),nd); +pos = ones(length(sa),nd); + +for i=1:length(sa) + sz = sa(i).dim; + dim(i,1:length(sz)) = sz; + ps = sa(i).pos; + pos(i,1:length(ps)) = ps; +end + +tmp = pos==1; +d = zeros(1,nd); +for i=1:nd, + ind = all(tmp(:,[1:(i-1) (i+1):nd]),2); + d(i) = sum(dim(ind,i)); +end; +lim = max(max(find(d~=1)),2); +d = d(1:lim); + +if nargin>1, + if varargin{1}<=length(d), + d = d(varargin{1}); + else + d = 1; + end; +end; + diff --git a/spm/nii_for_spm2/@file_array/subsasgn.m b/spm/nii_for_spm2/@file_array/subsasgn.m new file mode 100644 index 0000000..89cd6e3 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/subsasgn.m @@ -0,0 +1,146 @@ +function obj = subsasgn(obj,subs,dat) +% Overloaded subsasgn function for file_array objects. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: subsasgn.m 945 2007-10-14 18:08:46Z volkmar $ + + +if isempty(subs) + return; +end; +if ~strcmp(subs(1).type,'()'), + if strcmp(subs(1).type,'.'), + %error('Attempt to reference field of non-structure array.'); + if numel(struct(obj))~=1, + error('Can only change the fields of simple file_array objects.'); + end; + switch(subs(1).subs) + case 'fname', obj = asgn(obj,@fname, subs(2:end),dat); %fname(obj,dat); + case 'dtype', obj = asgn(obj,@dtype, subs(2:end),dat); %dtype(obj,dat); + case 'offset', obj = asgn(obj,@offset, subs(2:end),dat); %offset(obj,dat); + case 'dim', obj = asgn(obj,@dim, subs(2:end),dat); %obj = dim(obj,dat); + case 'scl_slope', obj = asgn(obj,@scl_slope,subs(2:end),dat); %scl_slope(obj,dat); + case 'scl_inter', obj = asgn(obj,@scl_inter,subs(2:end),dat); %scl_inter(obj,dat); + otherwise, error(['Reference to non-existent field "' subs.subs '".']); + end; + return; + end; + if strcmp(subs(1).type,'{}'), error('Cell contents reference from a non-cell array object.'); end; +end; + +if numel(subs)~=1, error('Expression too complicated');end; +dm = size(obj); +sobj = struct(obj); + +if length(subs.subs) < length(dm), + l = length(subs.subs); + dm = [dm(1:(l-1)) prod(dm(l:end))]; + if numel(sobj) ~= 1, + error('Can only reshape simple file_array objects.'); + end; + if numel(sobj.scl_slope)>1 || numel(sobj.scl_inter)>1, + error('Can not reshape file_array objects with multiple slopes and intercepts.'); + end; +end; + +dm = [dm ones(1,16)]; +do = ones(1,16); +args = {}; +for i=1:length(subs.subs), + if ischar(subs.subs{i}), + if ~strcmp(subs.subs{i},':'), error('This shouldn''t happen....'); end; + args{i} = int32(1:dm(i)); + else + args{i} = int32(subs.subs{i}); + end; + do(i) = length(args{i}); +end; +if length(sobj)==1 + sobj.dim = dm; + if numel(dat)~=1, + subfun(sobj,double(dat),args{:}); + else + dat1 = double(dat) + zeros(do); + subfun(sobj,dat1,args{:}); + end; +else + for j=1:length(sobj), + ps = [sobj(j).pos ones(1,length(args))]; + dm = [sobj(j).dim ones(1,length(args))]; + siz = ones(1,16); + for i=1:length(args), + msk = args{i}>=ps(i) & args{i}<(ps(i)+dm(i)); + args2{i} = find(msk); + args3{i} = int32(double(args{i}(msk))-ps(i)+1); + siz(i) = numel(args2{i}); + end; + if numel(dat)~=1, + dat1 = double(subsref(dat,struct('type','()','subs',{args2}))); + else + dat1 = double(dat) + zeros(siz); + end; + subfun(sobj(j),dat1,args3{:}); + end +end +return + +function sobj = subfun(sobj,dat,varargin) +va = varargin; + +dt = datatypes; +ind = find(cat(1,dt.code)==sobj.dtype); +if isempty(ind), error('Unknown datatype'); end; +if dt(ind).isint, dat(~isfinite(dat)) = 0; end; + +if ~isempty(sobj.scl_inter), + inter = sobj.scl_inter; + if numel(inter)>1, + inter = resize_scales(inter,sobj.dim,varargin); + end; + dat = double(dat) - inter; +end; + +if ~isempty(sobj.scl_slope), + slope = sobj.scl_slope; + if numel(slope)>1, + slope = resize_scales(slope,sobj.dim,varargin); + dat = double(dat)./slope; + else + dat = double(dat)/slope; + end; +end; + +if dt(ind).isint, dat = round(dat); end; + +% Avoid warning messages in R14 SP3 +wrn = warning; +warning('off'); +dat = feval(dt(ind).conv,dat); +warning(wrn); + +nelem = dt(ind).nelem; +if nelem==1, + mat2file(sobj,dat,va{:}); +elseif nelem==2, + sobj1 = sobj; + sobj1.dim = [2 sobj.dim]; + sobj1.dtype = dt(find(strcmp(dt(ind).prec,{dt.prec}) & (cat(2,dt.nelem)==1))).code; + dat = reshape(dat,[1 size(dat)]); + dat = [real(dat) ; imag(dat)]; + mat2file(sobj1,dat,int32([1 2]),va{:}); +else + error('Inappropriate number of elements per voxel.'); +end; +return + +function obj = asgn(obj,fun,subs,dat) +if ~isempty(subs), + tmp = feval(fun,obj); + tmp = subsasgn(tmp,subs,dat); + obj = feval(fun,obj,tmp); +else + obj = feval(fun,obj,dat); +end; + diff --git a/spm/nii_for_spm2/@file_array/subsref.m b/spm/nii_for_spm2/@file_array/subsref.m new file mode 100755 index 0000000..813aa58 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/subsref.m @@ -0,0 +1,124 @@ +function varargout=subsref(obj,subs) +% SUBSREF Subscripted reference +% An overloaded function... +% _________________________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: subsref.m 315 2005-11-28 16:48:59Z john $ + + +if isempty(subs) + return; +end; + +if ~strcmp(subs(1).type,'()'), + if strcmp(subs(1).type,'.'), + %error('Attempt to reference field of non-structure array.'); + %if numel(struct(obj))~=1, + % error('Can only access the fields of simple file_array objects.'); + %end; + + varargout = access_fields(obj,subs); + return; + end; + if strcmp(subs.type,'{}'), error('Cell contents reference from a non-cell array object.'); end; +end; + +if numel(subs)~=1, error('Expression too complicated');end; + +dim = [size(obj) ones(1,16)]; +nd = max(find(dim>1))-1; +sobj = struct(obj); + +if length(subs.subs) < nd, + l = length(subs.subs); + dim = [dim(1:(l-1)) prod(dim(l:end))]; + if numel(sobj) ~= 1, + error('Can only reshape simple file_array objects.'); + else + if numel(sobj.scl_slope)>1 || numel(sobj.scl_inter)>1, + error('Can not reshape file_array objects with multiple slopes and intercepts.'); + end; + sobj.dim = dim; + end; +end; + +do = ones(16,1); +args = {}; +for i=1:length(subs.subs), + if ischar(subs.subs{i}), + if ~strcmp(subs.subs{i},':'), error('This shouldn''t happen....'); end; + args{i} = int32(1:dim(i)); + else + args{i} = int32(subs.subs{i}); + end; + do(i) = length(args{i}); +end; + +if length(sobj)==1, + t = subfun(sobj,args{:}); +else + t = zeros(do'); + for j=1:length(sobj), + ps = [sobj(j).pos ones(1,length(args))]; + dm = [sobj(j).dim ones(1,length(args))]; + for i=1:length(args), + msk = find(args{i}>=ps(i) & args{i}<(ps(i)+dm(i))); + args2{i} = msk; + args3{i} = int32(double(args{i}(msk))-ps(i)+1); + end; + + t = subsasgn(t,struct('type','()','subs',{args2}),subfun(sobj(j),args3{:})); + end +end +varargout = {t}; +return; + +function t = subfun(sobj,varargin) +%sobj.dim = [sobj.dim ones(1,16)]; +t = file2mat(sobj,varargin{:}); +if ~isempty(sobj.scl_slope) || ~isempty(sobj.scl_inter) + slope = 1; + inter = 0; + if ~isempty(sobj.scl_slope), slope = sobj.scl_slope; end; + if ~isempty(sobj.scl_inter), inter = sobj.scl_inter; end; + if numel(slope)>1, + slope = resize_scales(slope,sobj.dim,varargin); + t = double(t).*slope; + else + t = double(t)*slope; + end; + if numel(inter)>1, + inter = resize_scales(inter,sobj.dim,varargin); + end; + t = t + inter; +end; +return; + +function c = access_fields(obj,subs) +%error('Attempt to reference field of non-structure array.'); +%if numel(struct(obj))~=1, +% error('Can only access the fields of simple file_array objects.'); +%end; +c = {}; +sobj = struct(obj); +for i=1:numel(sobj), + %obj = class(sobj(i),'file_array'); + obj = sobj(i); + switch(subs(1).subs) + case 'fname', t = fname(obj); + case 'dtype', t = dtype(obj); + case 'offset', t = offset(obj); + case 'dim', t = dim(obj); + case 'scl_slope', t = scl_slope(obj); + case 'scl_inter', t = scl_inter(obj); + otherwise, error(['Reference to non-existent field "' subs(1).type '".']); + end; + if numel(subs)>1, + t = subsref(t,subs(2:end)); + end; + c{i} = t; +end; +return; + diff --git a/spm/nii_for_spm2/@file_array/transpose.m b/spm/nii_for_spm2/@file_array/transpose.m new file mode 100755 index 0000000..0f6aaa1 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/transpose.m @@ -0,0 +1,10 @@ +function varargout = transpose(varargin) +% Transposing is not allowed. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: transpose.m 253 2005-10-13 15:31:34Z guillaume $ + + +error('file_array objects can not be transposed.'); diff --git a/spm/nii_for_spm2/@file_array/vertcat.m b/spm/nii_for_spm2/@file_array/vertcat.m new file mode 100755 index 0000000..4e67694 --- /dev/null +++ b/spm/nii_for_spm2/@file_array/vertcat.m @@ -0,0 +1,11 @@ +function o = vertcat(varargin) +% Vertical concatenation of file_array objects. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: vertcat.m 253 2005-10-13 15:31:34Z guillaume $ + + +o = cat(1,varargin{:}); +return; diff --git a/spm/nii_for_spm2/@nifti/Contents.m b/spm/nii_for_spm2/@nifti/Contents.m new file mode 100755 index 0000000..d531861 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/Contents.m @@ -0,0 +1,82 @@ +% +% NIFTI Object +% +% create - Create a NIFTI-1 file +% disp - Disp a NIFTI-1 object +% display - Display a NIFTI-1 object +% fieldnames - Fieldnames of a NIFTI-1 object +% nifti - Create a NIFTI-1 object +% subsasgn - Subscript assignment +% subsref - Subscript referencing +% +% other operations are unlikely to work. +% +% Example usage. +% +% % Example of creating a simulated .nii file. +% dat = file_array; +% dat.fname = 'junk.nii'; +% dat.dim = [64 64 32]; +% dat.dtype = 'FLOAT64-BE'; +% dat.offset = ceil(348/8)*8; +% +% % alternatively: +% % dat = file_array( 'junk.nii',dim,dtype,off,scale,inter) +% +% disp(dat) +% +% % Create an empty NIFTI structure +% N = nifti; +% +% fieldnames(N) % Dump fieldnames +% +% % Creating all the NIFTI header stuff +% N.dat = dat; +% N.mat = [2 0 0 -110 ; 0 2 0 -110; 0 0 -2 92; 0 0 0 1]; +% N.mat_intent = 'xxx'; % dump possibilities +% N.mat_intent = 'Scanner'; +% N.mat0 = N.mat; +% N.mat0_intent = 'Aligned'; +% +% N.diminfo.slice = 3; +% N.diminfo.phase = 2; +% N.diminfo.frequency = 2; +% N.diminfo.slice_time.code='xxx'; % dump possibilities +% N.diminfo.slice_time.code = 'sequential_increasing'; +% N.diminfo.slice_time.start = 1; +% N.diminfo.slice_time.end = 32; +% N.diminfo.slice_time.duration = 3/32; +% +% N.intent.code='xxx' ; % dump possibilities +% N.intent.code='FTEST'; % or N.intent.code=4; +% N.intent.param = [4 8]; +% +% N.timing.toffset = 28800; +% N.timing.tspace=3; +% N.descrip = 'This is a NIFTI-1 file'; +% N.aux_file='aux-file-name.txt'; +% N.cal = [0 1]; +% +% create(N); % Writes hdr info +% +% dat(:,:,:)=0; % Write out the data as all zeros +% +% [i,j,k] = ndgrid(1:64,1:64,1:32); +% dat(find((i-32).^2+(j-32).^2+(k*2-32).^2 < 30^2))=1; % Write some ones in the file +% dat(find((i-32).^2+(j-32).^2+(k*2-32).^2 < 15^2))=2; +% +% +% % displaying a slice +% imagesc(dat(:,:,12));colorbar +% +% % get a handle to 'junk.nii'; +% M=nifti('junk.nii'); +% +% imagesc(M.dat(:,:,12)); +% +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id$ + diff --git a/spm/nii_for_spm2/@nifti/create.m b/spm/nii_for_spm2/@nifti/create.m new file mode 100755 index 0000000..6f486d8 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/create.m @@ -0,0 +1,74 @@ +function create(obj,wrt) +% Create a NIFTI-1 file +% FORMAT create(obj) +% This writes out the header information for the nifti object +% +% create(obj,wrt) +% This also writes out an empty image volume if wrt==1 +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: create.m 433 2006-02-09 11:45:02Z john $ + +for i=1:numel(obj) + create_each(obj(i)); +end; + +function create_each(obj) +if ~isa(obj.dat,'file_array'), + error('Data must be a file-array'); +end; +fname = obj.dat.fname; +if isempty(fname), + error('No filename to write to.'); +end; +dt = obj.dat.dtype; +ok = write_hdr_raw(fname,obj.hdr,dt(end-1)=='B'); +if ~ok, + error(['Unable to write header for "' fname '".']); +end; + +write_extras(fname,obj.extras); + +if nargin>2 && any(wrt==1), + % Create an empty image file if necessary + d = findindict(obj.hdr.datatype, 'dtype'); + dim = double(obj.hdr.dim(2:end)); + dim((double(obj.hdr.dim(1))+1):end) = 1; + nbytes = ceil(d.size*d.nelem*prod(dim(1:2)))*prod(dim(3:end))+double(obj.hdr.vox_offset); + [pth,nam,ext] = fileparts(obj.dat.fname); + + if any(strcmp(deblank(obj.hdr.magic),{'n+1','nx1'})), + ext = '.nii'; + else + ext = '.img'; + end; + iname = fullfile(pth,[nam ext]); + fp = fopen(iname,'a+'); + if fp==-1, + error(['Unable to create image for "' fname '".']); + end; + + fseek(fp,0,'eof'); + pos = ftell(fp); + if pos0) + if nbytes4, + fprintf('%d-D\n',length(sz)); +else + for i=1:(length(sz)-1), + fprintf('%d-by-',sz(i)); + end; + fprintf('%d\n',sz(end)); +end; +if prod(sz)==1, + display(structn(obj)) +end; +return; diff --git a/spm/nii_for_spm2/@nifti/display.m b/spm/nii_for_spm2/@nifti/display.m new file mode 100755 index 0000000..78fef0d --- /dev/null +++ b/spm/nii_for_spm2/@nifti/display.m @@ -0,0 +1,14 @@ +function display(obj) +% Display a NIFTI-1 object +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: display.m 253 2005-10-13 15:31:34Z guillaume $ + + +disp(' '); +disp([inputname(1),' = ']) +disp(' '); +disp(obj) +disp(' ') diff --git a/spm/nii_for_spm2/@nifti/fieldnames.m b/spm/nii_for_spm2/@nifti/fieldnames.m new file mode 100755 index 0000000..b49f427 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/fieldnames.m @@ -0,0 +1,26 @@ +function t = fieldnames(obj) +% Fieldnames of a NIFTI-1 object +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: fieldnames.m 253 2005-10-13 15:31:34Z guillaume $ + + +if isfield(obj.hdr,'magic') + t = {... + 'dat' + 'mat' + 'mat_intent' + 'mat0' + 'mat0_intent' + 'intent' + 'diminfo' + 'timing' + 'descrip' + 'cal' + 'aux_file' + }; +else + error('This should not happen.'); +end; diff --git a/spm/nii_for_spm2/@nifti/nifti.m b/spm/nii_for_spm2/@nifti/nifti.m new file mode 100755 index 0000000..037140e --- /dev/null +++ b/spm/nii_for_spm2/@nifti/nifti.m @@ -0,0 +1,91 @@ +function h = nifti(varargin) +% Create a NIFTI-1 object +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: nifti.m 253 2005-10-13 15:31:34Z guillaume $ + + +switch nargin +case 0, + org = niftistruc; + hdr = []; + for i=1:length(org), + hdr.(org(i).label) = feval(org(i).dtype.conv,org(i).def); + end; + h = struct('hdr',hdr,'dat',[],'extras',struct); + h = class(h,'nifti'); + +case 1 + if ischar(varargin{1}) + if size(varargin{1},1)>1, + h = nifti(cellstr(varargin{1})); + return; + end; + fname = deblank(varargin{1}); + vol = read_hdr(fname); + extras = read_extras(fname); + + if ~isfield(vol.hdr,'magic'), + vol.hdr = mayo2nifti1(vol.hdr); + + % For SPM99 compatibility + if isfield(extras,'M') && ~isfield(extras,'mat'), + extras.mat = extras.M; + if spm_flip_analyze_images, + extras.mat = diag([-1 1 1 1])*extras.mat; + end; + end; + + % Over-ride sform if a .mat file exists + if isfield(extras,'mat') && size(extras.mat,3)>=1, + mat = extras.mat(:,:,1); + mat1 = mat*[eye(4,3) [1 1 1 1]']; + vol.hdr.srow_x = mat1(1,:); + vol.hdr.srow_y = mat1(2,:); + vol.hdr.srow_z = mat1(3,:); + vol.hdr.sform_code = 2; + vol.hdr.qform_code = 2; + vol.hdr = encode_qform0(mat,vol.hdr); + end; + end; + + if isfield(extras,'M'), extras = rmfield(extras,'M'); end; + if isfield(extras,'mat') && size(extras.mat,3)<=1, + extras = rmfield(extras,'mat'); + end; + + dim = double(vol.hdr.dim); + dim = dim(2:(dim(1)+1)); + dt = double(vol.hdr.datatype); + offs = double(vol.hdr.vox_offset); + + if ~vol.hdr.scl_slope && ~vol.hdr.scl_inter, + vol.hdr.scl_slope = 1; + end; + slope = double(vol.hdr.scl_slope); + inter = double(vol.hdr.scl_inter); + + dat = file_array(vol.iname,dim,[dt,vol.be],offs,slope,inter); + h = struct('hdr',vol.hdr,'dat',dat,'extras',extras); + h = class(h,'nifti'); + + elseif isstruct(varargin{1}) + h = class(varargin{1},'nifti'); + + elseif iscell(varargin{1}) + fnames = varargin{1}; + h(numel(fnames)) = struct('hdr',[],'dat',[],'extras',struct); + h = class(h,'nifti'); + for i=1:numel(fnames), + h(i) = nifti(fnames{i}); + end; + + else + error('Dont know what to do yet.'); + end; +otherwise + error('Dont know what to do yet'); +end; +return; diff --git a/spm/nii_for_spm2/@nifti/private/M2Q.m b/spm/nii_for_spm2/@nifti/private/M2Q.m new file mode 100755 index 0000000..b87eee8 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/M2Q.m @@ -0,0 +1,33 @@ +function Q = M2Q(M) +% Convert from rotation matrix to quaternion form +% See: http://skal.planet-d.net/demo/matrixfaq.htm +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: M2Q.m 253 2005-10-13 15:31:34Z guillaume $ + + +d = diag(M(1:3,1:3)); +t = sum(d) + 1; +if t>0.5, + s = sqrt(t)*2; + Q = [(M(3,2)-M(2,3))/s (M(1,3)-M(3,1))/s (M(2,1)-M(1,2))/s 0.25*s]'; +else + t = find(d==max(d)); + t = t(1); + switch(t), + case 1, + s = 2*sqrt(1 + M(1,1) - M(2,2) - M(3,3)); + Q = [0.25*s (M(1,2)+M(2,1))/s (M(3,1)+M(1,3))/s (M(3,2)-M(2,3))/s]'; + case 2, + s = 2*sqrt(1 + M(2,2) - M(1,1) - M(3,3)); + Q = [(M(1,2)+M(2,1))/s 0.25*s (M(2,3)+M(3,2))/s (M(1,3)-M(3,1))/s ]'; + case 3, + s = 2*sqrt(1 + M(3,3) - M(1,1) - M(2,2)); + Q = [(M(3,1)+M(1,3))/s (M(2,3)+M(3,2))/s 0.25*s (M(2,1)-M(1,2))/s]'; + end; +end; +if Q(4)<0, Q = -Q; end; % w must be +ve +return; + diff --git a/spm/nii_for_spm2/@nifti/private/Q2M.m b/spm/nii_for_spm2/@nifti/private/Q2M.m new file mode 100755 index 0000000..1f684ce --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/Q2M.m @@ -0,0 +1,31 @@ +function M = Q2M(Q) +% Generate a rotation matrix from a quaternion xi+yj+zk+w, +% where Q = [x y z], and w = 1-x^2-y^2-z^2. +% See: http://skal.planet-d.net/demo/matrixfaq.htm +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: Q2M.m 253 2005-10-13 15:31:34Z guillaume $ + + +Q = Q(1:3); % Assume rigid body +w = sqrt(1 - sum(Q.^2)); +x = Q(1); y = Q(2); z = Q(3); +if w<1e-7, + w = 1/sqrt(x*x+y*y+z*z); + x = x*w; + y = y*w; + z = z*w; + w = 0; +end; +xx = x*x; yy = y*y; zz = z*z; ww = w*w; +xy = x*y; xz = x*z; xw = x*w; +yz = y*z; yw = y*w; zw = z*w; +M = [... +(xx-yy-zz+ww) 2*(xy-zw) 2*(xz+yw) 0 + 2*(xy+zw) (-xx+yy-zz+ww) 2*(yz-xw) 0 + 2*(xz-yw) 2*(yz+xw) (-xx-yy+zz+ww) 0 + 0 0 0 1]; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/decode_qform0.m b/spm/nii_for_spm2/@nifti/private/decode_qform0.m new file mode 100755 index 0000000..6bd8ee2 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/decode_qform0.m @@ -0,0 +1,61 @@ +function M = decode_qform0(hdr) +% Decode qform info from NIFTI-1 headers. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: decode_qform0.m 253 2005-10-13 15:31:34Z guillaume $ + + +dim = double(hdr.dim); +pixdim = double(hdr.pixdim); +if ~isfield(hdr,'magic') || hdr.qform_code <= 0, + flp = spm_flip_analyze_images; + %disp('------------------------------------------------------'); + %disp('The images are in a form whereby it is not possible to'); + %disp('tell the left and right sides of the brain apart.'); + %if flp, + % disp('They are assumed to be stored right-handed.'); + %else + % disp('They are assumed to be stored left-handed.'); + %end; + %disp('------------------------------------------------------'); + + %R = eye(4); + n = min(dim(1),3); + vox = [pixdim(2:(n+1)) ones(1,3-n)]; + + if ~isfield(hdr,'origin') || ~any(hdr.origin(1:3)), + origin = (dim(2:4)+1)/2; + else + origin = double(hdr.origin(1:3)); + end; + off = -vox.*origin; + M = [vox(1) 0 0 off(1) ; 0 vox(2) 0 off(2) ; 0 0 vox(3) off(3) ; 0 0 0 1]; + + % Stuff for default orientations + if flp, M = diag([-1 1 1 1])*M; end; +else + + % Rotations from quaternions + R = Q2M(double([hdr.quatern_b hdr.quatern_c hdr.quatern_d])); + + % Translations + T = [eye(4,3) double([hdr.qoffset_x hdr.qoffset_y hdr.qoffset_z 1]')]; + + % Zooms. Note that flips are derived from the first + % element of pixdim, which is normally unused. + n = min(dim(1),3); + Z = [pixdim(2:(n+1)) ones(1,4-n)]; + Z(Z<0) = 1; + if pixdim(1)<0, Z(3) = -Z(3); end; + Z = diag(Z); + + M = T*R*Z; + + % Convert from first voxel at [1,1,1] + % to first voxel at [0,0,0] + M = M * [eye(4,3) [-1 -1 -1 1]']; +end; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/empty_hdr.m b/spm/nii_for_spm2/@nifti/private/empty_hdr.m new file mode 100755 index 0000000..0f80b60 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/empty_hdr.m @@ -0,0 +1,15 @@ +function hdr = empty_hdr +% Create an empty NIFTI-1 header +% FORMAT hdr = empty_hdr +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: empty_hdr.m 253 2005-10-13 15:31:34Z guillaume $ + + +org = niftistruc; +for i=1:length(org), + hdr.(org(i).label) = org(i).def; +end; + diff --git a/spm/nii_for_spm2/@nifti/private/encode_qform0.m b/spm/nii_for_spm2/@nifti/private/encode_qform0.m new file mode 100755 index 0000000..df296db --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/encode_qform0.m @@ -0,0 +1,45 @@ +function hdr = encode_qform0(M,hdr) +% Encode an affine transform into qform +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: encode_qform0.m 253 2005-10-13 15:31:34Z guillaume $ + + +% Convert from first voxel at [1,1,1] to first voxel at [0,0,0] +M = M * [eye(4,3) [1 1 1 1]']; + +% Translations +hdr.qoffset_x = M(1,4); +hdr.qoffset_y = M(2,4); +hdr.qoffset_z = M(3,4); + +% Rotations and zooms +R = M(1:3,1:3); +vx = sqrt(sum(M(1:3,1:3).^2)); +vx(vx==0) = 1; +R = R * diag(1./vx); + +% Ensure that R is O(3) +[U,S,V] = svd(R); +R = U*V'; +if any(abs(diag(S)-1)>1e-3), warning('QFORM0 representation has been rounded.'); end; + +% Ensure that R is SO(3) +if det(R)>0 + hdr.pixdim(1:4) = [ 1 vx]; +else + R = R*diag([1 1 -1]); + hdr.pixdim(1:4) = [-1 vx]; +end; + +% Convert to quaternions +Q = M2Q(R); +hdr.quatern_b = Q(1); +hdr.quatern_c = Q(2); +hdr.quatern_d = Q(3); + +if hdr.qform_code == 0, hdr.qform_code = 2; end; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/findindict.m b/spm/nii_for_spm2/@nifti/private/findindict.m new file mode 100755 index 0000000..5ad7fc2 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/findindict.m @@ -0,0 +1,37 @@ +function entry = findindict(c,dcode) +% Look up an entry in the dictionary +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: findindict.m 253 2005-10-13 15:31:34Z guillaume $ + + +entry = []; +d = getdict; +d = d.(dcode); +if ischar(c) + for i=1:length(d), + if strcmpi(d(i).label,c), + entry = d(i); + break; + end; + end; +elseif isnumeric(c) && numel(c)==1 + for i=1:length(d), + if d(i).code==c, + entry = d(i); + break; + end; + end; +else + error(['Inappropriate code for ' dcode '.']); +end; +if isempty(entry) + fprintf('\nThis is not an option. Try one of these:\n'); + for i=1:length(d) + fprintf('%5d) %s\n', d(i).code, d(i).label); + end; + %fprintf('\nNO CHANGES MADE\n'); +end; + diff --git a/spm/nii_for_spm2/@nifti/private/getdict.m b/spm/nii_for_spm2/@nifti/private/getdict.m new file mode 100755 index 0000000..58f7d67 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/getdict.m @@ -0,0 +1,153 @@ +function d = getdict +% Dictionary of NIFTI stuff +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: getdict.m 253 2005-10-13 15:31:34Z guillaume $ + + +persistent dict; +if ~isempty(dict), + d = dict; + return; +end; + +% Datatype +t = true; +f = false; +table = {... + 0 ,'UNKNOWN' ,'uint8' ,@uint8 ,1,1 ,t,t,f + 1 ,'BINARY' ,'uint1' ,@logical,1,1/8,t,t,f + 256 ,'INT8' ,'int8' ,@int8 ,1,1 ,t,f,t + 2 ,'UINT8' ,'uint8' ,@uint8 ,1,1 ,t,t,t + 4 ,'INT16' ,'int16' ,@int16 ,1,2 ,t,f,t + 512 ,'UINT16' ,'uint16' ,@uint16 ,1,2 ,t,t,t + 8 ,'INT32' ,'int32' ,@int32 ,1,4 ,t,f,t + 768 ,'UINT32' ,'uint32' ,@uint32 ,1,4 ,t,t,t + 1024,'INT64' ,'int64' ,@int64 ,1,8 ,t,f,f + 1280,'UINT64' ,'uint64' ,@uint64 ,1,8 ,t,t,f + 16 ,'FLOAT32' ,'float32' ,@single ,1,4 ,f,f,t + 64 ,'FLOAT64' ,'double' ,@double ,1,8 ,f,f,t + 1536,'FLOAT128' ,'float128',@crash ,1,16 ,f,f,f + 32 ,'COMPLEX64' ,'float32' ,@single ,2,4 ,f,f,f + 1792,'COMPLEX128','double' ,@double ,2,8 ,f,f,f + 2048,'COMPLEX256','float128',@crash ,2,16 ,f,f,f + 128 ,'RGB24' ,'uint8' ,@uint8 ,3,1 ,t,t,f}; + +dtype = struct(... + 'code' ,table(:,1),... + 'label' ,table(:,2),... + 'prec' ,table(:,3),... + 'conv' ,table(:,4),... + 'nelem' ,table(:,5),... + 'size' ,table(:,6),... + 'isint' ,table(:,7),... + 'unsigned' ,table(:,8),... + 'min',-Inf,'max',Inf',... + 'supported',table(:,9)); +for i=1:length(dtype), + if dtype(i).isint + if dtype(i).unsigned + dtype(i).min = 0; + dtype(i).max = 2^(8*dtype(i).size)-1; + else + dtype(i).min = -2^(8*dtype(i).size-1); + dtype(i).max = 2^(8*dtype(i).size-1)-1; + end; + end; +end; +% Intent +table = {... + 0 ,'NONE' ,'None',{} + 2 ,'CORREL' ,'Correlation statistic',{'DOF'} + 3 ,'TTEST' ,'T-statistic',{'DOF'} + 4 ,'FTEST' ,'F-statistic',{'numerator DOF','denominator DOF'} + 5 ,'ZSCORE' ,'Z-score',{} + 6 ,'CHISQ' ,'Chi-squared distribution',{'DOF'} + 7 ,'BETA' ,'Beta distribution',{'a','b'} + 8 ,'BINOM' ,'Binomial distribution',... + {'number of trials','probability per trial'} + 9 ,'GAMMA' ,'Gamma distribution',{'shape','scale'} + 10 ,'POISSON' ,'Poisson distribution',{'mean'} + 11 ,'NORMAL' ,'Normal distribution',{'mean','standard deviation'} + 12 ,'FTEST_NONC' ,'F-statistic noncentral',... + {'numerator DOF','denominator DOF','numerator noncentrality parameter'} + 13 ,'CHISQ_NONC' ,'Chi-squared noncentral',{'DOF','noncentrality parameter'} + 14 ,'LOGISTIC' ,'Logistic distribution',{'location','scale'} + 15 ,'LAPLACE' ,'Laplace distribution',{'location','scale'} + 16 ,'UNIFORM' ,'Uniform distribition',{'lower end','upper end'} + 17 ,'TTEST_NONC' ,'T-statistic noncentral',{'DOF','noncentrality parameter'} + 18 ,'WEIBULL' ,'Weibull distribution',{'location','scale','power'} + 19 ,'CHI' ,'Chi distribution',{'DOF'} + 20 ,'INVGAUSS' ,'Inverse Gaussian distribution',{'mu','lambda'} + 21 ,'EXTVAL' ,'Extreme Value distribution',{'location','scale'} + 22 ,'PVAL' ,'P-value',{} + 23 ,'LOGPVAL' ,'Log P-value',{} + 24 ,'LOG10PVAL' ,'Log_10 P-value',{} + 1001,'ESTIMATE' ,'Estimate',{} + 1002,'LABEL' ,'Label index',{} + 1003,'NEURONAMES' ,'NeuroNames index',{} + 1004,'MATRIX' ,'General matrix',{'M','N'} + 1005,'MATRIX_SYM' ,'Symmetric matrix',{} + 1006,'DISPLACEMENT' ,'Displacement vector',{} + 1007,'VECTOR' ,'Vector',{} + 1008,'POINTS' ,'Pointset',{} + 1009,'TRIANGLE' ,'Triangle',{} + 1010,'QUATERNION' ,'Quaternion',{} + 1011,'DIMLESS' ,'Dimensionless',{} +}; +intent = struct('code',table(:,1),'label',table(:,2),... + 'fullname',table(:,3),'param',table(:,4)); + +% Units +table = {... + 0, 1,'UNKNOWN' + 1,1000,'m' + 2, 1,'mm' + 3,1e-3,'um' + 8, 1,'s' + 16,1e-3,'ms' + 24,1e-6,'us' + 32, 1,'Hz' + 40, 1,'ppm' + 48, 1,'rads'}; +units = struct('code',table(:,1),'label',table(:,3),'rescale',table(:,2)); + +% Reference space +% code = {0,1,2,3,4}; +table = {... + 0,'UNKNOWN' + 1,'Scanner Anat' + 2,'Aligned Anat' + 3,'Talairach' + 4,'MNI_152'}; +anat = struct('code',table(:,1),'label',table(:,2)); + +% Slice Ordering +table = {... + 0,'UNKNOWN' + 1,'sequential_increasing' + 2,'sequential_decreasing' + 3,'alternating_increasing' + 4,'alternating_decreasing'}; +sliceorder = struct('code',table(:,1),'label',table(:,2)); + +% Q/S Form Interpretation +table = {... + 0,'UNKNOWN' + 1,'Scanner' + 2,'Aligned' + 3,'Talairach' + 4,'MNI152'}; +xform = struct('code',table(:,1),'label',table(:,2)); + +dict = struct('dtype',dtype,'intent',intent,'units',units,... + 'space',anat,'sliceorder',sliceorder,'xform',xform); + +d = dict; +return; + +function varargout = crash(varargin) +error('There is a NIFTI-1 data format problem (an invalid datatype).'); + diff --git a/spm/nii_for_spm2/@nifti/private/mayo2nifti1.m b/spm/nii_for_spm2/@nifti/private/mayo2nifti1.m new file mode 100755 index 0000000..8aac923 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/mayo2nifti1.m @@ -0,0 +1,67 @@ +function hdr = mayo2nifti1(ohdr,mat) +% Convert from an ANALYZE to a NIFTI-1 header +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: mayo2nifti1.m 594 2006-08-16 16:22:34Z john $ + + +if isfield(ohdr,'magic'), + hdr = ohdr; + return; +end; +hdr = empty_hdr; +hdr.dim = ohdr.dim; +hdr.datatype = ohdr.datatype; +hdr.bitpix = ohdr.bitpix; +hdr.pixdim = ohdr.pixdim; +hdr.vox_offset = ohdr.vox_offset; +hdr.scl_slope = ohdr.roi_scale; +hdr.scl_inter = ohdr.funused1; +hdr.descrip = ohdr.descrip; +hdr.aux_file = ohdr.aux_file; +hdr.glmax = ohdr.glmax; +hdr.glmin = ohdr.glmin; +hdr.cal_max = ohdr.cal_max; +hdr.cal_min = ohdr.cal_min; +hdr.magic = 'ni1'; + +switch hdr.datatype, +case 130, hdr.datatype = 256; % int8 +case 132, hdr.datatype = 512; % uint16 +case 136, hdr.datatype = 768; % uint32 +end; + +if nargin<2, + % No mat, so create the equivalent from the hdr... + if any(ohdr.origin(1:3)), origin = double(ohdr.origin(1:3)); + else origin = (double(ohdr.dim(2:4))+1)/2; end; + vox = double(ohdr.pixdim(2:4)); + if vox(1)<0, + % Assume FSL orientation + flp = 0; + else + % Assume SPM or proper Analyze + flp = spm_flip_analyze_images; + end; + if all(vox == 0), vox = [1 1 1]; end; + off = -vox.*origin; + mat = [vox(1) 0 0 off(1) ; 0 vox(2) 0 off(2) ; 0 0 vox(3) off(3) ; 0 0 0 1]; + if flp, + %disp(['Assuming that image is stored left-handed']); + mat = diag([-1 1 1 1])*mat; + else + %disp(['Assuming that image is stored right-handed']); + end; +end; + +hdr = encode_qform0(mat,hdr); +mat = mat*[eye(4,3) [1 1 1 1]']; +hdr.srow_x = mat(1,:); +hdr.srow_y = mat(2,:); +hdr.srow_z = mat(3,:); +hdr.qform_code = 2; +hdr.sform_code = 2; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/mayostruc.m b/spm/nii_for_spm2/@nifti/private/mayostruc.m new file mode 100755 index 0000000..ec818af --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/mayostruc.m @@ -0,0 +1,80 @@ +function o = mayostruc +% Create a data structure describing Analyze headers +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: mayostruc.m 253 2005-10-13 15:31:34Z guillaume $ + + +persistent org; +if ~isempty(org), + o = org; + return; +end; +t = struct('conv',{ @char, @int16, @int32, @single },... + 'prec',{'uint8','int16','int32','single'},... + 'size',{ 1, 2, 4, 4}); +c = t(1); +s = t(2); +i = t(3); +f = t(4); +table = {... + i, 1,'sizeof_hdr',348 + c,10,'data_type',[] + c,18,'db_name',[] + i, 1,'extents',[] + s, 1,'session_error',[] + c, 1,'regular','r' + c, 1,'hkey_un0',[] + s, 8,'dim',[3 1 1 1 1 1 1 1 1] + c, 4,'vox_units',[] + c, 8,'cal_units',[] + s, 1,'unused1',[] + s, 1,'datatype',[] + s, 1,'bitpix',[] + s, 1,'dim_un0',[] + f, 8,'pixdim',[] + f, 1,'vox_offset',0 + f, 1,'roi_scale',1 + f, 1,'funused1',0 + f, 1,'funused2',[] + f, 1,'cal_max',[] + f, 1,'cal_min',[] + i, 1,'compressed',[] + i, 1,'verified',[] + i, 1,'glmax',[] + i, 1,'glmin',[] + c,80,'descrip','Analyze Image' + c,24,'aux_file','' + c, 1,'orient',[] +% c,10,'originator',[] + s, 5,'origin',[] % SPM version + c,10,'generated',[] + c,10,'scannum',[] + c,10,'patient_id',[] + c,10,'exp_date',[] + c,10,'exp_time',[] + c, 3,'hist_un0',[] + i, 1,'views',[] + i, 1,'vols_added',[] + i, 1,'start_field',[] + i, 1,'field_skip',[] + i, 1,'omax',[] + i, 1,'omin',[] + i, 1,'smax',[] + i, 1,'smin',[]}; +org = struct('label',table(:,3),'dtype',table(:,1),'len',table(:,2),... + 'offset',0,'def',table(:,4)); +os = 0; +for j=1:length(org) + os = os + org(j).dtype.size*ceil(os/org(j).dtype.size); + fun = org(j).dtype.conv; + def = [org(j).def zeros(1,org(j).len-length(org(j).def))]; + org(j).def = feval(fun,def); + org(j).offset = os; + os = os + org(j).len*org(j).dtype.size; +end; +o = org; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/nifti1.h b/spm/nii_for_spm2/@nifti/private/nifti1.h new file mode 100755 index 0000000..98fed70 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/nifti1.h @@ -0,0 +1,1222 @@ +#ifndef _NIFTI_HEADER_ +#define _NIFTI_HEADER_ + +/***************************************************************************** + ** This file defines the "NIFTI-1" header format. ** + ** It is derived from 2 meetings at the NIH (31 Mar 2003 and ** + ** 02 Sep 2003) of the Data Format Working Group (DFWG), ** + ** chartered by the NIfTI (Neuroimaging Informatics Technology ** + ** Initiative) at the National Institutes of Health (NIH). ** + **--------------------------------------------------------------** + ** Neither the National Institutes of Health (NIH), the DFWG, ** + ** nor any of the members or employees of these institutions ** + ** imply any warranty of usefulness of this material for any ** + ** purpose, and do not assume any liability for damages, ** + ** incidental or otherwise, caused by any use of this document. ** + ** If these conditions are not acceptable, do not use this! ** + **--------------------------------------------------------------** + ** Author: Robert W Cox (NIMH, Bethesda) ** + ** Advisors: John Ashburner (FIL, London), ** + ** Stephen Smith (FMRIB, Oxford), ** + ** Mark Jenkinson (FMRIB, Oxford) ** +******************************************************************************/ + +/*---------------------------------------------------------------------------*/ +/* Note that the ANALYZE 7.5 file header (dbh.h) is + (c) Copyright 1986-1995 + Biomedical Imaging Resource + Mayo Foundation + Incorporation of components of dbh.h are by permission of the + Mayo Foundation. + + Changes from the ANALYZE 7.5 file header in this file are released to the + public domain, including the functional comments and any amusing asides. +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/*! INTRODUCTION TO NIFTI-1: + ------------------------ + The twin (and somewhat conflicting) goals of this modified ANALYZE 7.5 + format are: + (a) To add information to the header that will be useful for functional + neuroimaging data analysis and display. These additions include: + - More basic data types. + - Two affine transformations to specify voxel coordinates. + - "Intent" codes and parameters to describe the meaning of the data. + - Affine scaling of the stored data values to their "true" values. + - Optional storage of the header and image data in one file (.nii). + (b) To maintain compatibility with non-NIFTI-aware ANALYZE 7.5 compatible + software (i.e., such a program should be able to do something useful + with a NIFTI-1 dataset -- at least, with one stored in a traditional + .img/.hdr file pair). + + Most of the unused fields in the ANALYZE 7.5 header have been taken, + and some of the lesser-used fields have been co-opted for other purposes. + Notably, most of the data_history substructure has been co-opted for + other purposes, since the ANALYZE 7.5 format describes this substructure + as "not required". + + NIFTI-1 FLAG (MAGIC STRINGS): + ---------------------------- + To flag such a struct as being conformant to the NIFTI-1 spec, the last 4 + bytes of the header must be either the C String "ni1" or "n+1"; + in hexadecimal, the 4 bytes + 6E 69 31 00 or 6E 2B 31 00 + (in any future version of this format, the '1' will be upgraded to '2', + etc.). Normally, such a "magic number" or flag goes at the start of the + file, but trying to avoid clobbering widely-used ANALYZE 7.5 fields led to + putting this marker last. However, recall that "the last shall be first" + (Matthew 20:16). + + If a NIFTI-aware program reads a header file that is NOT marked with a + NIFTI magic string, then it should treat the header as an ANALYZE 7.5 + structure. + + NIFTI-1 FILE STORAGE: + -------------------- + "ni1" means that the image data is stored in the ".img" file corresponding + to the header file (starting at file offset 0). + + "n+1" means that the image data is stored in the same file as the header + information. We recommend that the combined header+data filename suffix + be ".nii". When the dataset is stored in one file, the first byte of image + data is stored at byte location (int)vox_offset in this combined file. + + GRACE UNDER FIRE: + ---------------- + Most NIFTI-aware programs will only be able to handle a subset of the full + range of datasets possible with this format. All NIFTI-aware programs + should take care to check if an input dataset conforms to the program's + needs and expectations (e.g., check datatype, intent_code, etc.). If the + input dataset can't be handled by the program, the program should fail + gracefully (e.g., print a useful warning; not crash). + + SAMPLE CODES: + ------------ + The associated files nifti1_io.h and nifti1_io.c provide a sample + implementation in C of a set of functions to read, write, and manipulate + NIFTI-1 files. The file nifti1_test.c is a sample program that uses + the nifti1_io.c functions. +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* HEADER STRUCT DECLARATION: + ------------------------- + In the comments below for each field, only NIFTI-1 specific requirements + or changes from the ANALYZE 7.5 format are described. For convenience, + the 348 byte header is described as a single struct, rather than as the + ANALYZE 7.5 group of 3 substructs. + + Further comments about the interpretation of various elements of this + header are after the data type definition itself. Fields that are + marked as ++UNUSED++ have no particular interpretation in this standard. + (Also see the UNUSED FIELDS comment section, far below.) + + The presumption below is that the various C types have particular sizes: + sizeof(int) = sizeof(float) = 4 ; sizeof(short) = 2 +-----------------------------------------------------------------------------*/ + +/*=================*/ +#ifdef __cplusplus +extern "C" { +#endif +/*=================*/ + /*************************/ /************************/ +struct nifti_1_header { /* NIFTI-1 usage */ /* ANALYZE 7.5 field(s) */ + /*************************/ /************************/ + + /*--- was header_key substruct ---*/ + int sizeof_hdr; /*!< MUST be 348 */ /* int sizeof_hdr; */ + char data_type[10]; /*!< ++UNUSED++ */ /* char data_type[10]; */ + char db_name[18]; /*!< ++UNUSED++ */ /* char db_name[18]; */ + int extents; /*!< ++UNUSED++ */ /* int extents; */ + short session_error; /*!< ++UNUSED++ */ /* short session_error; */ + char regular; /*!< ++UNUSED++ */ /* char regular; */ + char dim_info; /*!< MRI slice ordering. */ /* char hkey_un0; */ + + /*--- was image_dimension substruct ---*/ + short dim[8]; /*!< Data array dimensions.*/ /* short dim[8]; */ + float intent_p1 ; /*!< 1st intent parameter. */ /* short unused8; */ + /* short unused9; */ + float intent_p2 ; /*!< 2nd intent parameter. */ /* short unused10; */ + /* short unused11; */ + float intent_p3 ; /*!< 3rd intent parameter. */ /* short unused12; */ + /* short unused13; */ + short intent_code ; /*!< NIFTI_INTENT_* code. */ /* short unused14; */ + short datatype; /*!< Defines data type! */ /* short datatype; */ + short bitpix; /*!< Number bits/voxel. */ /* short bitpix; */ + short slice_start; /*!< First slice index. */ /* short dim_un0; */ + float pixdim[8]; /*!< Grid spacings. */ /* float pixdim[8]; */ + float vox_offset; /*!< Offset into .nii file */ /* float vox_offset; */ + float scl_slope ; /*!< Data scaling: slope. */ /* float funused1; */ + float scl_inter ; /*!< Data scaling: offset. */ /* float funused2; */ + short slice_end; /*!< Last slice index. */ /* float funused3; */ + char slice_code ; /*!< Slice timing order. */ + char xyzt_units ; /*!< Units of pixdim[1..4] */ + float cal_max; /*!< Max display intensity */ /* float cal_max; */ + float cal_min; /*!< Min display intensity */ /* float cal_min; */ + float slice_duration;/*!< Time for 1 slice. */ /* float compressed; */ + float toffset; /*!< Time axis shift. */ /* float verified; */ + int glmax; /*!< ++UNUSED++ */ /* int glmax; */ + int glmin; /*!< ++UNUSED++ */ /* int glmin; */ + + /*--- was data_history substruct ---*/ + char descrip[80]; /*!< any text you like. */ /* char descrip[80]; */ + char aux_file[24]; /*!< auxiliary filename. */ /* char aux_file[24]; */ + + short qform_code ; /*!< NIFTI_XFORM_* code. */ /*-- all ANALYZE 7.5 ---*/ + short sform_code ; /*!< NIFTI_XFORM_* code. */ /* fields below here */ + /* are replaced */ + float quatern_b ; /*!< Quaternion b param. */ + float quatern_c ; /*!< Quaternion c param. */ + float quatern_d ; /*!< Quaternion d param. */ + float qoffset_x ; /*!< Quaternion x shift. */ + float qoffset_y ; /*!< Quaternion y shift. */ + float qoffset_z ; /*!< Quaternion z shift. */ + + float srow_x[4] ; /*!< 1st row affine transform. */ + float srow_y[4] ; /*!< 2nd row affine transform. */ + float srow_z[4] ; /*!< 3rd row affine transform. */ + + char intent_name[16];/*!< 'name' or meaning of data. */ + + char magic[4] ; /*!< MUST be "ni1\0" or "n+1\0". */ + +} ; /**** 348 bytes total ****/ + +typedef struct nifti_1_header nifti_1_header ; + +/*---------------------------------------------------------------------------*/ +/* DATA DIMENSIONALITY (as in ANALYZE 7.5): + --------------------------------------- + dim[0] = number of dimensions; + - if dim[0] is outside range 1..7, then the header information + needs to be byte swapped appropriately + - ANALYZE supports dim[0] up to 7, but NIFTI-1 reserves + dimensions 1,2,3 for space (x,y,z), 4 for time (t), and + 5,6,7 for anything else needed. + + dim[i] = length of dimension #i, for i=1..dim[0] (must be positive) + - also see the discussion of intent_code, far below + + pixdim[i] = voxel width along dimension #i, i=1..dim[0] (positive) + - cf. ORIENTATION section below for use of pixdim[0] + - the units of pixdim can be specified with the xyzt_units + field (also described far below). + + Number of bits per voxel value is in bitpix, which MUST correspond with + the datatype field. The total number of bytes in the image data is + dim[1] * ... * dim[dim[0]] * bitpix / 8 + + In NIFTI-1 files, dimensions 1,2,3 are for space, dimension 4 is for time, + and dimension 5 is for storing multiple values at each spatiotemporal + voxel. Some examples: + - A typical whole-brain FMRI experiment's time series: + - dim[0] = 4 + - dim[1] = 64 pixdim[1] = 3.75 xyzt_units = NIFTI_UNITS_MM + - dim[2] = 64 pixdim[2] = 3.75 | NIFTI_UNITS_SEC + - dim[3] = 20 pixdim[3] = 5.0 + - dim[4] = 120 pixdim[4] = 2.0 + - A typical T1-weighted anatomical volume: + - dim[0] = 3 + - dim[1] = 256 pixdim[1] = 1.0 xyzt_units = NIFTI_UNITS_MM + - dim[2] = 256 pixdim[2] = 1.0 + - dim[3] = 128 pixdim[3] = 1.1 + - A single slice EPI time series: + - dim[0] = 4 + - dim[1] = 64 pixdim[1] = 3.75 xyzt_units = NIFTI_UNITS_MM + - dim[2] = 64 pixdim[2] = 3.75 | NIFTI_UNITS_SEC + - dim[3] = 1 pixdim[3] = 5.0 + - dim[4] = 1200 pixdim[4] = 0.2 + - A 3-vector stored at each point in a 3D volume: + - dim[0] = 5 + - dim[1] = 256 pixdim[1] = 1.0 xyzt_units = NIFTI_UNITS_MM + - dim[2] = 256 pixdim[2] = 1.0 + - dim[3] = 128 pixdim[3] = 1.1 + - dim[4] = 1 pixdim[4] = 0.0 + - dim[5] = 3 intent_code = NIFTI_INTENT_VECTOR + - A single time series with a 3x3 matrix at each point: + - dim[0] = 5 + - dim[1] = 1 xyzt_units = NIFTI_UNITS_SEC + - dim[2] = 1 + - dim[3] = 1 + - dim[4] = 1200 pixdim[4] = 0.2 + - dim[5] = 9 intent_code = NIFTI_INTENT_GENMATRIX + - intent_p1 = intent_p2 = 3.0 (indicates matrix dimensions) +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* DATA STORAGE: + ------------ + If the magic field is "n+1", then the voxel data is stored in the + same file as the header. In this case, the voxel data starts at offset + (int)vox_offset into the header file. Thus, vox_offset=348.0 means that + the data starts immediately after the NIFTI-1 header. If vox_offset is + greater than 348, the NIFTI-1 format does not say anything about the + contents of the dataset file between the end of the header and the + start of the data. + + FILES: + ----- + If the magic field is "ni1", then the voxel data is stored in the + associated ".img" file, starting at offset 0 (i.e., vox_offset is not + used in this case, and should be set to 0.0). + + When storing NIFTI-1 datasets in pairs of files, it is customary to name + the files in the pattern "name.hdr" and "name.img", as in ANALYZE 7.5. + When storing in a single file ("n+1"), the file name should be in + the form "name.nii" (the ".nft" and ".nif" suffixes are already taken; + cf. http://www.icdatamaster.com/n.html ). + + BYTE ORDERING: + ------------- + The byte order of the data arrays is presumed to be the same as the byte + order of the header (which is determined by examining dim[0]). + + Floating point types are presumed to be stored in IEEE-754 format. +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* DATA SCALING: + ------------ + If the scl_slope field is nonzero, then each voxel value in the dataset + should be scaled as + y = scl_slope * x + scl_inter + where x = voxel value stored + y = "true" voxel value + Normally, we would expect this scaling to be used to store "true" floating + values in a smaller integer datatype, but that is not required. That is, + it is legal to use scaling even if the datatype is a float type (crazy, + perhaps, but legal). + - However, the scaling is to be ignored if datatype is DT_RGB24. + - If datatype is a complex type, then the scaling is to be + applied to both the real and imaginary parts. + + The cal_min and cal_max fields (if nonzero) are used for mapping (possibly + scaled) dataset values to display colors: + - Minimum display intensity (black) corresponds to dataset value cal_min. + - Maximum display intensity (white) corresponds to dataset value cal_max. + - Dataset values below cal_min should display as black also, and values + above cal_max as white. + - Colors "black" and "white", of course, may refer to any scalar display + scheme (e.g., a color lookup table specified via aux_file). + - cal_min and cal_max only make sense when applied to scalar-valued + datasets (i.e., dim[0] < 5 or dim[5] = 1). +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* TYPE OF DATA (acceptable values for datatype field): + --------------------------------------------------- + Values of datatype smaller than 256 are ANALYZE 7.5 compatible. + Larger values are NIFTI-1 additions. These are all multiples of 256, so + that no bits below position 8 are set in datatype. But there is no need + to use only powers-of-2, as the original ANALYZE 7.5 datatype codes do. + + The additional codes are intended to include a complete list of basic + scalar types, including signed and unsigned integers from 8 to 64 bits, + floats from 32 to 128 bits, and complex (float pairs) from 64 to 256 bits. + + Note that most programs will support only a few of these datatypes! + A NIFTI-1 program should fail gracefully (e.g., print a warning message) + when it encounters a dataset with a type it doesn't like. +-----------------------------------------------------------------------------*/ + +#undef DT_UNKNOWN /* defined in dirent.h on some Unix systems */ + + /*--- the original ANALYZE 7.5 type codes ---*/ +#define DT_NONE 0 +#define DT_UNKNOWN 0 /* what it says, dude */ +#define DT_BINARY 1 /* binary (1 bit/voxel) */ +#define DT_UNSIGNED_CHAR 2 /* unsigned char (8 bits/voxel) */ +#define DT_SIGNED_SHORT 4 /* signed short (16 bits/voxel) */ +#define DT_SIGNED_INT 8 /* signed int (32 bits/voxel) */ +#define DT_FLOAT 16 /* float (32 bits/voxel) */ +#define DT_COMPLEX 32 /* complex (64 bits/voxel) */ +#define DT_DOUBLE 64 /* double (64 bits/voxel) */ +#define DT_RGB 128 /* RGB triple (24 bits/voxel) */ +#define DT_ALL 255 /* not very useful (?) */ + + /*----- another set of names for the same ---*/ +#define DT_UINT8 2 +#define DT_INT16 4 +#define DT_INT32 8 +#define DT_FLOAT32 16 +#define DT_COMPLEX64 32 +#define DT_FLOAT64 64 +#define DT_RGB24 128 + + /*------------------- new codes for NIFTI ---*/ +#define DT_INT8 256 /* signed char (8 bits) */ +#define DT_UINT16 512 /* unsigned short (16 bits) */ +#define DT_UINT32 768 /* unsigned int (32 bits) */ +#define DT_INT64 1024 /* long long (64 bits) */ +#define DT_UINT64 1280 /* unsigned long long (64 bits) */ +#define DT_FLOAT128 1536 /* long double (128 bits) */ +#define DT_COMPLEX128 1792 /* double pair (128 bits) */ +#define DT_COMPLEX256 2048 /* long double pair (256 bits) */ + + /*------- aliases for all the above codes ---*/ + + /*! unsigned char. */ +#define NIFTI_TYPE_UINT8 2 + /*! signed short. */ +#define NIFTI_TYPE_INT16 4 + /*! signed int. */ +#define NIFTI_TYPE_INT32 8 + /*! 32 bit float. */ +#define NIFTI_TYPE_FLOAT32 16 + /*! 64 bit complex = 2 32 bit floats. */ +#define NIFTI_TYPE_COMPLEX64 32 + /*! 64 bit float = double. */ +#define NIFTI_TYPE_FLOAT64 64 + /*! 3 8 bit bytes. */ +#define NIFTI_TYPE_RGB24 128 + /*! signed char. */ +#define NIFTI_TYPE_INT8 256 + /*! unsigned short. */ +#define NIFTI_TYPE_UINT16 512 + /*! unsigned int. */ +#define NIFTI_TYPE_UINT32 768 + /*! signed long long. */ +#define NIFTI_TYPE_INT64 1024 + /*! unsigned long long. */ +#define NIFTI_TYPE_UINT64 1280 + /*! 128 bit float = long double. */ +#define NIFTI_TYPE_FLOAT128 1536 + /*! 128 bit complex = 2 64 bit floats. */ +#define NIFTI_TYPE_COMPLEX128 1792 + /*! 256 bit complex = 2 128 bit floats */ +#define NIFTI_TYPE_COMPLEX256 2048 + + /*-------- sample typedefs for complicated types ---*/ +#if 0 +typedef struct { float r,i; } complex_float ; +typedef struct { double r,i; } complex_double ; +typedef struct { long double r,i; } complex_longdouble ; +typedef struct { unsigned char r,g,b; } rgb_byte ; +#endif + +/*---------------------------------------------------------------------------*/ +/* INTERPRETATION OF VOXEL DATA: + ---------------------------- + The intent_code field can be used to indicate that the voxel data has + some particular meaning. In particular, a large number of codes is + given to indicate that the the voxel data should be interpreted as + being drawn from a given probability distribution. + + VECTOR-VALUED DATASETS: + ---------------------- + The 5th dimension of the dataset, if present (i.e., dim[0]=5 and + dim[5] > 1), contains multiple values (e.g., a vector) to be stored + at each spatiotemporal location. For example, the header values + - dim[0] = 5 + - dim[1] = 64 + - dim[2] = 64 + - dim[3] = 20 + - dim[4] = 1 (indicates no time axis) + - dim[5] = 3 + - datatype = DT_FLOAT + - intent_code = NIFTI_INTENT_VECTOR + mean that this dataset should be interpreted as a 3D volume (64x64x20), + with a 3-vector of floats defined at each point in the 3D grid. + + A program reading a dataset with a 5th dimension may want to reformat + the image data to store each voxels' set of values together in a struct + or array. This programming detail, however, is beyond the scope of the + NIFTI-1 file specification! Uses of dimensions 6 and 7 are also not + specified here. + + STATISTICAL PARAMETRIC DATASETS (i.e., SPMs): + -------------------------------------------- + Values of intent_code from NIFTI_FIRST_STATCODE to NIFTI_LAST_STATCODE + (inclusive) indicate that the numbers in the dataset should be interpreted + as being drawn from a given distribution. Most such distributions have + auxiliary parameters (e.g., NIFTI_INTENT_TTEST has 1 DOF parameter). + + If the dataset DOES NOT have a 5th dimension, then the auxiliary parameters + are the same for each voxel, and are given in header fields intent_p1, + intent_p2, and intent_p3. + + If the dataset DOES have a 5th dimension, then the auxiliary parameters + are different for each voxel. For example, the header values + - dim[0] = 5 + - dim[1] = 128 + - dim[2] = 128 + - dim[3] = 1 (indicates a single slice) + - dim[4] = 1 (indicates no time axis) + - dim[5] = 2 + - datatype = DT_FLOAT + - intent_code = NIFTI_INTENT_TTEST + mean that this is a 2D dataset (128x128) of t-statistics, with the + t-statistic being in the first "plane" of data and the degrees-of-freedom + parameter being in the second "plane" of data. + + If the dataset 5th dimension is used to store the voxel-wise statistical + parameters, then dim[5] must be 1 plus the number of parameters required + by that distribution (e.g., intent_code=NIFTI_INTENT_TTEST implies dim[5] + must be 2, as in the example just above). + + Note: intent_code values 2..10 are compatible with AFNI 1.5x (which is + why there is no code with value=1, which is obsolescent in AFNI). + + OTHER INTENTIONS: + ---------------- + The purpose of the intent_* fields is to help interpret the values + stored in the dataset. Some non-statistical values for intent_code + and conventions are provided for storing other complex data types. + + The intent_name field provides space for a 15 character (plus 0 byte) + 'name' string for the type of data stored. Examples: + - intent_code = NIFTI_INTENT_ESTIMATE; intent_name = "T1"; + could be used to signify that the voxel values are estimates of the + NMR parameter T1. + - intent_code = NIFTI_INTENT_TTEST; intent_name = "House"; + could be used to signify that the voxel values are t-statistics + for the significance of 'activation' response to a House stimulus. + - intent_code = NIFTI_INTENT_DISPVECT; intent_name = "ToMNI152"; + could be used to signify that the voxel values are a displacement + vector that transforms each voxel (x,y,z) location to the + corresponding location in the MNI152 standard brain. + - intent_code = NIFTI_INTENT_SYMMATRIX; intent_name = "DTI"; + could be used to signify that the voxel values comprise a diffusion + tensor image. + + If no data name is implied or needed, intent_name[0] should be set to 0. +-----------------------------------------------------------------------------*/ + + /*! default: no intention is indicated in the header. */ + +#define NIFTI_INTENT_NONE 0 + + /*-------- These codes are for probability distributions ---------------*/ + /* Most distributions have a number of parameters, + below denoted by p1, p2, and p3, and stored in + - intent_p1, intent_p2, intent_p3 if dataset doesn't have 5th dimension + - image data array if dataset does have 5th dimension + + Functions to compute with many of the distributions below can be found + in the CDF library from U Texas. + + Formulas for and discussions of these distributions can be found in the + following books: + + [U] Univariate Discrete Distributions, + NL Johnson, S Kotz, AW Kemp. + + [C1] Continuous Univariate Distributions, vol. 1, + NL Johnson, S Kotz, N Balakrishnan. + + [C2] Continuous Univariate Distributions, vol. 2, + NL Johnson, S Kotz, N Balakrishnan. */ + /*----------------------------------------------------------------------*/ + + /*! [C2, chap 32] Correlation coefficient R (1 param): + p1 = degrees of freedom + R/sqrt(1-R*R) is t-distributed with p1 DOF. */ + +#define NIFTI_INTENT_CORREL 2 + + /*! [C2, chap 28] Student t statistic (1 param): p1 = DOF. */ + +#define NIFTI_INTENT_TTEST 3 + + /*! [C2, chap 27] Fisher F statistic (2 params): + p1 = numerator DOF, p2 = denominator DOF. */ + +#define NIFTI_INTENT_FTEST 4 + + /*! [C1, chap 13] Standard normal (0 params): Density = N(0,1). */ + +#define NIFTI_INTENT_ZSCORE 5 + + /*! [C1, chap 18] Chi-squared (1 param): p1 = DOF. + Density(x) proportional to exp(-x/2) * x^(p1/2-1). */ + +#define NIFTI_INTENT_CHISQ 6 + + /*! [C2, chap 25] Beta distribution (2 params): p1=a, p2=b. + Density(x) proportional to x^(a-1) * (1-x)^(b-1). */ + +#define NIFTI_INTENT_BETA 7 + + /*! [U, chap 3] Binomial distribution (2 params): + p1 = number of trials, p2 = probability per trial. + Prob(x) = (p1 choose x) * p2^x * (1-p2)^(p1-x), for x=0,1,...,p1. */ + +#define NIFTI_INTENT_BINOM 8 + + /*! [C1, chap 17] Gamma distribution (2 params): + p1 = shape, p2 = scale. + Density(x) proportional to x^(p1-1) * exp(-p2*x). */ + +#define NIFTI_INTENT_GAMMA 9 + + /*! [U, chap 4] Poisson distribution (1 param): p1 = mean. + Prob(x) = exp(-p1) * p1^x / x! , for x=0,1,2,.... */ + +#define NIFTI_INTENT_POISSON 10 + + /*! [C1, chap 13] Normal distribution (2 params): + p1 = mean, p2 = standard deviation. */ + +#define NIFTI_INTENT_NORMAL 11 + + /*! [C2, chap 30] Noncentral F statistic (3 params): + p1 = numerator DOF, p2 = denominator DOF, + p3 = numerator noncentrality parameter. */ + +#define NIFTI_INTENT_FTEST_NONC 12 + + /*! [C2, chap 29] Noncentral chi-squared statistic (2 params): + p1 = DOF, p2 = noncentrality parameter. */ + +#define NIFTI_INTENT_CHISQ_NONC 13 + + /*! [C2, chap 23] Logistic distribution (2 params): + p1 = location, p2 = scale. + Density(x) proportional to sech^2((x-p1)/(2*p2)). */ + +#define NIFTI_INTENT_LOGISTIC 14 + + /*! [C2, chap 24] Laplace distribution (2 params): + p1 = location, p2 = scale. + Density(x) proportional to exp(-abs(x-p1)/p2). */ + +#define NIFTI_INTENT_LAPLACE 15 + + /*! [C2, chap 26] Uniform distribution: p1 = lower end, p2 = upper end. */ + +#define NIFTI_INTENT_UNIFORM 16 + + /*! [C2, chap 31] Noncentral t statistic (2 params): + p1 = DOF, p2 = noncentrality parameter. */ + +#define NIFTI_INTENT_TTEST_NONC 17 + + /*! [C1, chap 21] Weibull distribution (3 params): + p1 = location, p2 = scale, p3 = power. + Density(x) proportional to + ((x-p1)/p2)^(p3-1) * exp(-((x-p1)/p2)^p3) for x > p1. */ + +#define NIFTI_INTENT_WEIBULL 18 + + /*! [C1, chap 18] Chi distribution (1 param): p1 = DOF. + Density(x) proportional to x^(p1-1) * exp(-x^2/2) for x > 0. + p1 = 1 = 'half normal' distribution + p1 = 2 = Rayleigh distribution + p1 = 3 = Maxwell-Boltzmann distribution. */ + +#define NIFTI_INTENT_CHI 19 + + /*! [C1, chap 15] Inverse Gaussian (2 params): + p1 = mu, p2 = lambda + Density(x) proportional to + exp(-p2*(x-p1)^2/(2*p1^2*x)) / x^3 for x > 0. */ + +#define NIFTI_INTENT_INVGAUSS 20 + + /*! [C2, chap 22] Extreme value type I (2 params): + p1 = location, p2 = scale + cdf(x) = exp(-exp(-(x-p1)/p2)). */ + +#define NIFTI_INTENT_EXTVAL 21 + + /*! Data is a 'p-value' (no params). */ + +#define NIFTI_INTENT_PVAL 22 + + /*! Smallest intent_code that indicates a statistic. */ + +#define NIFTI_FIRST_STATCODE 2 + + /*! Largest intent_code that indicates a statistic. */ + +#define NIFTI_LAST_STATCODE 22 + + /*---------- these values for intent_code aren't for statistics ----------*/ + + /*! To signify that the value at each voxel is an estimate + of some parameter, set intent_code = NIFTI_INTENT_ESTIMATE. + The name of the parameter may be stored in intent_name. */ + +#define NIFTI_INTENT_ESTIMATE 1001 + + /*! To signify that the value at each voxel is an index into + some set of labels, set intent_code = NIFTI_INTENT_LABEL. + The filename with the labels may stored in aux_file. */ + +#define NIFTI_INTENT_LABEL 1002 + + /*! To signify that the value at each voxel is an index into the + NeuroNames labels set, set intent_code = NIFTI_INTENT_NEURONAME. */ + +#define NIFTI_INTENT_NEURONAME 1003 + + /*! To store an M x N matrix at each voxel: + - dataset must have a 5th dimension (dim[0]=5 and dim[5]>1) + - intent_code must be NIFTI_INTENT_GENMATRIX + - dim[5] must be M*N + - intent_p1 must be M (in float format) + - intent_p2 must be N (ditto) + - the matrix values A[i][[j] are stored in row-order: + - A[0][0] A[0][1] ... A[0][N-1] + - A[1][0] A[1][1] ... A[1][N-1] + - etc., until + - A[M-1][0] A[M-1][1] ... A[M-1][N-1] */ + +#define NIFTI_INTENT_GENMATRIX 1004 + + /*! To store an NxN symmetric matrix at each voxel: + - dataset must have a 5th dimension + - intent_code must be NIFTI_INTENT_SYMMATRIX + - dim[5] must be N*(N+1)/2 + - intent_p1 must be N (in float format) + - the matrix values A[i][[j] are stored in row-order: + - A[0][0] + - A[1][0] A[1][1] + - A[2][0] A[2][1] A[2][2] + - etc.: row-by-row */ + +#define NIFTI_INTENT_SYMMATRIX 1005 + + /*! To signify that the vector value at each voxel is to be taken + as a displacement field or vector: + - dataset must have a 5th dimension + - intent_code must be NIFTI_INTENT_DISPVECT + - dim[5] must be the dimensionality of the displacment + vector (e.g., 3 for spatial displacement, 2 for in-plane) */ + +#define NIFTI_INTENT_DISPVECT 1006 /* specifically for displacements */ +#define NIFTI_INTENT_VECTOR 1007 /* for any other type of vector */ + + /*! To signify that the vector value at each voxel is really a + spatial coordinate (e.g., the vertices or nodes of a surface mesh): + - dataset must have a 5th dimension + - intent_code must be NIFTI_INTENT_POINTSET + - dim[0] = 5 + - dim[1] = number of points + - dim[2] = dim[3] = dim[4] = 1 + - dim[5] must be the dimensionality of space (e.g., 3 => 3D space). + - intent_name may describe the object these points come from + (e.g., "pial", "gray/white" , "EEG", "MEG"). */ + +#define NIFTI_INTENT_POINTSET 1008 + + /*! To signify that the vector value at each voxel is really a triple + of indexes (e.g., forming a triangle) from a pointset dataset: + - dataset must have a 5th dimension + - intent_code must be NIFTI_INTENT_TRIANGLE + - dim[0] = 5 + - dim[1] = number of triangles + - dim[2] = dim[3] = dim[4] = 1 + - dim[5] = 3 + - datatype should be an integer type (preferably DT_INT32) + - the data values are indexes (0,1,...) into a pointset dataset. */ + +#define NIFTI_INTENT_TRIANGLE 1009 + + /*! To signify that the vector value at each voxel is a quaternion: + - dataset must have a 5th dimension + - intent_code must be NIFTI_INTENT_QUATERNION + - dim[0] = 5 + - dim[5] = 4 + - datatype should be a floating point type */ + +#define NIFTI_INTENT_QUATERNION 1010 + +/*---------------------------------------------------------------------------*/ +/* 3D IMAGE (VOLUME) ORIENTATION AND LOCATION IN SPACE: + --------------------------------------------------- + There are 3 different methods by which continuous coordinates can + attached to voxels. The discussion below emphasizes 3D volumes, and + the continuous coordinates are referred to as (x,y,z). The voxel + index coordinates (i.e., the array indexes) are referred to as (i,j,k), + with valid ranges: + i = 0 .. dim[1]-1 + j = 0 .. dim[2]-1 (if dim[0] >= 2) + k = 0 .. dim[3]-1 (if dim[0] >= 3) + The (x,y,z) coordinates refer to the CENTER of a voxel. In methods + 2 and 3, the (x,y,z) axes refer to a subject-based coordinate system, + with + +x = Right +y = Anterior +z = Superior. + This is a right-handed coordinate system. However, the exact direction + these axes point with respect to the subject depends on qform_code + (Method 2) and sform_code (Method 3). + + N.B.: The i index varies most rapidly, j index next, k index slowest. + Thus, voxel (i,j,k) is stored starting at location + (i + j*dim[1] + k*dim[1]*dim[2]) * (bitpix/8) + into the dataset array. + + N.B.: The ANALYZE 7.5 coordinate system is + +x = Left +y = Anterior +z = Superior + which is a left-handed coordinate system. This backwardness is + too difficult to tolerate, so this NIFTI-1 standard specifies the + coordinate order which is most common in functional neuroimaging. + + N.B.: The 3 methods below all give the locations of the voxel centers + in the (x,y,z) coordinate system. In many cases, programs will wish + to display image data on some other grid. In such a case, the program + will need to convert its desired (x,y,z) values into (i,j,k) values + in order to extract (or interpolate) the image data. This operation + would be done with the inverse transformation to those described below. + + N.B.: Method 2 uses a factor 'qfac' which is either -1 or 1; qfac is + stored in the otherwise unused pixdim[0]. If pixdim[0]=0.0 (which + should not occur), we take qfac=1. Of course, pixdim[0] is only used + when reading a NIFTI-1 header, not when reading an ANALYZE 7.5 header. + + N.B.: The units of (x,y,z) can be specified using the xyzt_units field. + + METHOD 1 (the "old" way, used only when qform_code = 0): + ------------------------------------------------------- + The coordinate mapping from (i,j,k) to (x,y,z) is the ANALYZE + 7.5 way. This is a simple scaling relationship: + + x = pixdim[1] * i + y = pixdim[2] * j + z = pixdim[3] * k + + No particular spatial orientation is attached to these (x,y,z) + coordinates. (NIFTI-1 does not have the ANALYZE 7.5 orient field, + which is not general and is often not set properly.) This method + is not recommended, and is present mainly for compatibility with + ANALYZE 7.5 files. + + METHOD 2 (used when qform_code > 0, which should be the "normal case): + --------------------------------------------------------------------- + The (x,y,z) coordinates are given by the pixdim[] scales, a rotation + matrix, and a shift. This method is intended to represent + "scanner-anatomical" coordinates, which are often embedded in the + image header (e.g., DICOM fields (0020,0032), (0020,0037), (0028,0030), + and (0018,0050)), and represent the nominal orientation and location of + the data. This method can also be used to represent "aligned" + coordinates, which would typically result from some post-acquisition + alignment of the volume to a standard orientation (e.g., the same + subject on another day, or a rigid rotation to true anatomical + orientation from the tilted position of the subject in the scanner). + The formula for (x,y,z) in terms of header parameters and (i,j,k) is: + + [ x ] [ R11 R12 R13 ] [ pixdim[1] * i ] [ qoffset_x ] + [ y ] = [ R21 R22 R23 ] [ pixdim[2] * j ] + [ qoffset_y ] + [ z ] [ R31 R32 R33 ] [ qfac * pixdim[3] * k ] [ qoffset_z ] + + The qoffset_* shifts are in the NIFTI-1 header. Note that the center + of the (i,j,k)=(0,0,0) voxel (first value in the dataset array) is + just (x,y,z)=(qoffset_x,qoffset_y,qoffset_z). + + The rotation matrix R is calculated from the quatern_* parameters. + This calculation is described below. + + The scaling factor qfac is either 1 or -1. The rotation matrix R + defined by the quaternion parameters is "proper" (has determinant 1). + This may not fit the needs of the data; for example, if the image + grid is + i increases from Left-to-Right + j increases from Anterior-to-Posterior + k increases from Inferior-to-Superior + Then (i,j,k) is a left-handed triple. In this example, if qfac=1, + the R matrix would have to be + + [ 1 0 0 ] + [ 0 -1 0 ] which is "improper" (determinant = -1). + [ 0 0 1 ] + + If we set qfac=-1, then the R matrix would be + + [ 1 0 0 ] + [ 0 -1 0 ] which is proper. + [ 0 0 -1 ] + + This R matrix is represented by quaternion [a,b,c,d] = [0,1,0,0] + (which encodes a 180 degree rotation about the x-axis). + + METHOD 3 (used when sform_code > 0): + ----------------------------------- + The (x,y,z) coordinates are given by a general affine transformation + of the (i,j,k) indexes: + + x = srow_x[0] * i + srow_x[1] * j + srow_x[2] * k + srow_x[3] + y = srow_y[0] * i + srow_y[1] * j + srow_y[2] * k + srow_y[3] + z = srow_z[0] * i + srow_z[1] * j + srow_z[2] * k + srow_z[3] + + The srow_* vectors are in the NIFTI_1 header. Note that no use is + made of pixdim[] in this method. + + WHY 3 METHODS? + -------------- + Method 1 is provided only for backwards compatibility. The intention + is that Method 2 (qform_code > 0) represents the nominal voxel locations + as reported by the scanner, or as rotated to some fiducial orientation and + location. Method 3, if present (sform_code > 0), is to be used to give + the location of the voxels in some standard space. The sform_code + indicates which standard space is present. Both methods 2 and 3 can be + present, and be useful in different contexts (method 2 for displaying the + data on its original grid; method 3 for displaying it on a standard grid). + + In this scheme, a dataset would originally be set up so that the + Method 2 coordinates represent what the scanner reported. Later, + a registration to some standard space can be computed and inserted + in the header. Image display software can use either transform, + depending on its purposes and needs. + + In Method 2, the origin of coordinates would generally be whatever + the scanner origin is; for example, in MRI, (0,0,0) is the center + of the gradient coil. + + In Method 3, the origin of coordinates would depend on the value + of sform_code; for example, for the Talairach coordinate system, + (0,0,0) corresponds to the Anterior Commissure. + + QUATERNION REPRESENTATION OF ROTATION MATRIX (METHOD 2) + ------------------------------------------------------- + The orientation of the (x,y,z) axes relative to the (i,j,k) axes + in 3D space is specified using a unit quaternion [a,b,c,d], where + a*a+b*b+c*c+d*d=1. The (b,c,d) values are all that is needed, since + we require that a = sqrt(1.0-b*b+c*c+d*d) be nonnegative. The (b,c,d) + values are stored in the (quatern_b,quatern_c,quatern_d) fields. + + The quaternion representation is chosen for its compactness in + representing rotations. The (proper) 3x3 rotation matrix that + corresponds to [a,b,c,d] is + + [ a*a+b*b-c*c-d*d 2*b*c-2*a*d 2*b*d+2*a*c ] + R = [ 2*b*c+2*a*d a*a+c*c-b*b-d*d 2*c*d-2*a*b ] + [ 2*b*d-2*a*c 2*c*d+2*a*b a*a+d*d-c*c-b*b ] + + [ R11 R12 R13 ] + = [ R21 R22 R23 ] + [ R31 R32 R33 ] + + If (p,q,r) is a unit 3-vector, then rotation of angle h about that + direction is represented by the quaternion + + [a,b,c,d] = [cos(h/2), p*sin(h/2), q*sin(h/2), r*sin(h/2)]. + + Requiring a >= 0 is equivalent to requiring -Pi <= h <= Pi. (Note that + [-a,-b,-c,-d] represents the same rotation as [a,b,c,d]; there are 2 + quaternions that can be used to represent a given rotation matrix R.) + To rotate a 3-vector (x,y,z) using quaternions, we compute the + quaternion product + + [0,x',y',z'] = [a,b,c,d] * [0,x,y,z] * [a,-b,-c,-d] + + which is equivalent to the matrix-vector multiply + + [ x' ] [ x ] + [ y' ] = R [ y ] (equivalence depends on a*a+b*b+c*c+d*d=1) + [ z' ] [ z ] + + Multiplication of 2 quaternions is defined by the following: + + [a,b,c,d] = a*1 + b*I + c*J + d*K + where + I*I = J*J = K*K = -1 (I,J,K are square roots of -1) + I*J = K J*K = I K*I = J + J*I = -K K*J = -I I*K = -J (not commutative!) + For example + [a,b,0,0] * [0,0,0,1] = [0,-b,0,a] + since this expands to + (a+b*I)*(K) = (a*K+b*I*K) = (a*K-b*J). + + The above formula shows how to go from quaternion (b,c,d) to + rotation matrix and direction cosines. Conversely, given R, + we can compute the fields for the NIFTI-1 header by + + a = 0.5 * sqrt(1+R11+R22+R33) (not stored) + b = 0.25 * (R32-R23) / a => quatern_b + c = 0.25 * (R13-R31) / a => quatern_c + d = 0.25 * (R21-R12) / a => quatern_d + + If a=0 (a 180 degree rotation), alternative formulas are needed. + See the nifti1_io.c function mat44_to_quatern() for an implementation + of the various cases in converting R to [a,b,c,d]. + + Note that R-transpose (= R-inverse) would lead to the quaternion + [a,-b,-c,-d]. + + The choice to specify the qoffset_x (etc.) values in the final + coordinate system is partly to make it easy to convert DICOM images to + this format. The DICOM attribute "Image Position (Patient)" (0020,0032) + stores the (Xd,Yd,Zd) coordinates of the center of the first voxel. + Here, (Xd,Yd,Zd) refer to DICOM coordinates, and Xd=-x, Yd=-y, Zd=z, + where (x,y,z) refers to the NIFTI coordinate system discussed above. + (i.e., DICOM +Xd is Left, +Yd is Posterior, +Zd is Superior, + whereas +x is Right, +y is Anterior , +z is Superior. ) + Thus, if the (0020,0032) DICOM attribute is extracted into (px,py,pz), then + qoffset_x = -px qoffset_y = -py qoffset_z = pz + is a reasonable setting when qform_code=NIFTI_XFORM_SCANNER_ANAT. + + That is, DICOM's coordinate system is 180 degrees rotated about the z-axis + from the neuroscience/NIFTI coordinate system. To transform between DICOM + and NIFTI, you just have to negate the x- and y-coordinates. + + The DICOM attribute (0020,0037) "Image Orientation (Patient)" gives the + orientation of the x- and y-axes of the image data in terms of 2 3-vectors. + The first vector is a unit vector along the x-axis, and the second is + along the y-axis. If the (0020,0037) attribute is extracted into the + value (xa,xb,xc,ya,yb,yc), then the first two columns of the R matrix + would be + [ -xa -ya ] + [ -xb -yb ] + [ xc yc ] + The negations are because DICOM's x- and y-axes are reversed relative + to NIFTI's. The third column of the R matrix gives the direction of + displacement (relative to the subject) along the slice-wise direction. + This orientation is not encoded in the DICOM standard in a simple way; + DICOM is mostly concerned with 2D images. The third column of R will be + either the cross-product of the first 2 columns or its negative. It is + possible to infer the sign of the 3rd column by examining the coordinates + in DICOM attribute (0020,0032) "Image Position (Patient)" for successive + slices. However, this method occasionally fails for reasons that I + (RW Cox) do not understand. +-----------------------------------------------------------------------------*/ + + /* [qs]form_code value: */ /* x,y,z coordinate system refers to: */ + /*-----------------------*/ /*---------------------------------------*/ + + /*! Arbitrary coordinates (Method 1). */ + +#define NIFTI_XFORM_UNKNOWN 0 + + /*! Scanner-based anatomical coordinates */ + +#define NIFTI_XFORM_SCANNER_ANAT 1 + + /*! Coordinates aligned to another file's, + or to anatomical "truth". */ + +#define NIFTI_XFORM_ALIGNED_ANAT 2 + + /*! Coordinates aligned to Talairach- + Tournoux Atlas; (0,0,0)=AC, etc. */ + +#define NIFTI_XFORM_TALAIRACH 3 + + /*! MNI 152 normalized coordinates. */ + +#define NIFTI_XFORM_MNI_152 4 + +/*---------------------------------------------------------------------------*/ +/* UNITS OF SPATIAL AND TEMPORAL DIMENSIONS: + ---------------------------------------- + The codes below can be used in xyzt_units to indicate the units of pixdim. + As noted earlier, dimensions 1,2,3 are for x,y,z; dimension 4 is for + time (t). + - If dim[4]=1 or dim[0] < 4, there is no time axis. + - A single time series (no space) would be specified with + - dim[0] = 4 (for scalar data) or dim[0] = 5 (for vector data) + - dim[1] = dim[2] = dim[3] = 1 + - dim[4] = number of time points + - pixdim[4] = time step + - xyzt_units indicates units of pixdim[4] + - dim[5] = number of values stored at each time point + + Bits 0..2 of xyzt_units specify the units of pixdim[1..3] + (e.g., spatial units are values 1..7). + Bits 3..5 of xyzt_units specify the units of pixdim[4] + (e.g., temporal units are multiples of 8). + + This compression of 2 distinct concepts into 1 byte is due to the + limited space available in the 348 byte ANALYZE 7.5 header. The + macros XYZT_TO_SPACE and XYZT_TO_TIME can be used to mask off the + undesired bits from the xyzt_units fields, leaving "pure" space + and time codes. Inversely, the macro SPACE_TIME_TO_XYZT can be + used to assemble a space code (0,1,2,...,7) with a time code + (0,8,16,32,...,56) into the combined value for xyzt_units. + + Note that codes are provided to indicate the "time" axis units are + actually frequency in Hertz (_HZ) or in part-per-million (_PPM). + + The toffset field can be used to indicate a nonzero start point for + the time axis. That is, time point #m is at t=toffset+m*pixdim[4] + for m=0..dim[4]-1. +-----------------------------------------------------------------------------*/ + + /*! NIFTI code for unspecified units. */ +#define NIFTI_UNITS_UNKNOWN 0 + + /** Space codes are multiples of 1. **/ + /*! NIFTI code for meters. */ +#define NIFTI_UNITS_METER 1 + /*! NIFTI code for millimeters. */ +#define NIFTI_UNITS_MM 2 + /*! NIFTI code for micrometers. */ +#define NIFTI_UNITS_MICRON 3 + + /** Time codes are multiples of 8. **/ + /*! NIFTI code for seconds. */ +#define NIFTI_UNITS_SEC 8 + /*! NIFTI code for milliseconds. */ +#define NIFTI_UNITS_MSEC 16 + /*! NIFTI code for microseconds. */ +#define NIFTI_UNITS_USEC 24 + + /*** These units are for spectral data: ***/ + /*! NIFTI code for Hertz. */ +#define NIFTI_UNITS_HZ 32 + /*! NIFTI code for ppm. */ +#define NIFTI_UNITS_PPM 40 + +#undef XYZT_TO_SPACE +#undef XYZT_TO_TIME +#define XYZT_TO_SPACE(xyzt) ( (xyzt) & 0x07 ) +#define XYZT_TO_TIME(xyzt) ( (xyzt) & 0x38 ) + +#undef SPACE_TIME_TO_XYZT +#define SPACE_TIME_TO_XYZT(ss,tt) ( (((char)(ss)) & 0x07) \ + | (((char)(tt)) & 0x38) ) + +/*---------------------------------------------------------------------------*/ +/* MRI-SPECIFIC SPATIAL AND TEMPORAL INFORMATION: + --------------------------------------------- + A few fields are provided to store some extra information + that is sometimes important when storing the image data + from an FMRI time series experiment. (After processing such + data into statistical images, these fields are not likely + to be useful.) + + { freq_dim } = These fields encode which spatial dimension (1,2, or 3) + { phase_dim } = corresponds to which acquisition dimension for MRI data. + { slice_dim } = + Examples: + Rectangular scan multi-slice EPI: + freq_dim = 1 phase_dim = 2 slice_dim = 3 (or some permutation) + Spiral scan multi-slice EPI: + freq_dim = phase_dim = 0 slice_dim = 3 + since the concepts of frequency- and phase-encoding directions + don't apply to spiral scan + + slice_duration = If this is positive, AND if slice_dim is nonzero, + indicates the amount of time used to acquire 1 slice. + slice_duration*dim[slice_dim] can be less than pixdim[4] + with a clustered acquisition method, for example. + + slice_code = If this is nonzero, AND if slice_dim is nonzero, AND + if slice_duration is positive, indicates the timing + pattern of the slice acquisition. The following codes + are defined: + NIFTI_SLICE_SEQ_INC + NIFTI_SLICE_SEQ_DEC + NIFTI_SLICE_ALT_INC + NIFTI_SLICE_ALT_DEC + { slice_start } = Indicates the start and end of the slice acquisition + { slice_end } = pattern, when slice_code is nonzero. These values + are present to allow for the possible addition of + "padded" slices at either end of the volume, which + don't fit into the slice timing pattern. If there + are no padding slices, then slice_start=0 and + slice_end=dim[slice_dim]-1 are the correct values. + For these values to be meaningful, slice_start must + be non-negative and slice_end must be greater than + slice_start. + + The following table indicates the slice timing pattern, relative to + time=0 for the first slice acquired, for some sample cases. Here, + dim[slice_dim]=7 (there are 7 slices, labeled 0..6), slice_duration=0.1, + and slice_start=1, slice_end=5 (1 padded slice on each end). + + slice + index SEQ_INC SEQ_DEC ALT_INC ALT_DEC + 6 -- n/a n/a n/a n/a n/a = not applicable + 5 -- 0.4 0.0 0.2 0.0 (slice time offset + 4 -- 0.3 0.1 0.4 0.3 doesn't apply to + 3 -- 0.2 0.2 0.1 0.1 slices outside range + 2 -- 0.1 0.3 0.3 0.4 slice_start..slice_end) + 1 -- 0.0 0.4 0.0 0.2 + 0 -- n/a n/a n/a n/a + + The fields freq_dim, phase_dim, slice_dim are all squished into the single + byte field dim_info (2 bits each, since the values for each field are + limited to the range 0..3). This unpleasantness is due to lack of space + in the 348 byte allowance. + + The macros DIM_INFO_TO_FREQ_DIM, DIM_INFO_TO_PHASE_DIM, and + DIM_INFO_TO_SLICE_DIM can be used to extract these values from the + dim_info byte. + + The macro FPS_INTO_DIM_INFO can be used to put these 3 values + into the dim_info byte. +-----------------------------------------------------------------------------*/ + +#undef DIM_INFO_TO_FREQ_DIM +#undef DIM_INFO_TO_PHASE_DIM +#undef DIM_INFO_TO_SLICE_DIM + +#define DIM_INFO_TO_FREQ_DIM(di) ( ((di) ) & 0x03 ) +#define DIM_INFO_TO_PHASE_DIM(di) ( ((di) >> 2) & 0x03 ) +#define DIM_INFO_TO_SLICE_DIM(di) ( ((di) >> 4) & 0x03 ) + +#undef FPS_INTO_DIM_INFO +#define FPS_INTO_DIM_INFO(fd,pd,sd) ( ( ( ((char)(fd)) & 0x03) ) | \ + ( ( ((char)(pd)) & 0x03) << 2 ) | \ + ( ( ((char)(sd)) & 0x03) << 4 ) ) + +#define NIFTI_SLICE_SEQ_INC 1 +#define NIFTI_SLICE_SEQ_DEC 2 +#define NIFTI_SLICE_ALT_INC 3 +#define NIFTI_SLICE_ALT_DEC 4 + +/*---------------------------------------------------------------------------*/ +/* UNUSED FIELDS: + ------------- + Some of the ANALYZE 7.5 fields marked as ++UNUSED++ may need to be set + to particular values for compatibility with other programs. The issue + of interoperability of ANALYZE 7.5 files is a murky one -- not all + programs require exactly the same set of fields. (Unobscuring this + murkiness is a principal motivation behind NIFTI-1.) + + Some of the fields that may need to be set for other (non-NIFTI aware) + software to be happy are: + + extents dbh.h says this should be 16384 + regular dbh.h says this should be the character 'r' + glmin, } dbh.h says these values should be the min and max voxel + glmax } values for the entire dataset + + It is best to initialize ALL fields in the NIFTI-1 header to 0 + (e.g., with calloc()), then fill in what is needed. +-----------------------------------------------------------------------------*/ + +/*---------------------------------------------------------------------------*/ +/* MISCELLANEOUS C MACROS +-----------------------------------------------------------------------------*/ + +/*.................*/ +/*! Given a nifti_1_header struct, check if it has a good magic number. + Returns NIFTI version number (1..9) if magic is good, 0 if it is not. */ + +#define NIFTI_VERSION(h) \ + ( ( (h).magic[0]=='n' && (h).magic[3]=='\0' && \ + ( (h).magic[1]=='i' || (h).magic[1]=='+' ) && \ + ( (h).magic[2]>='1' && (h).magic[2]<='9' ) ) \ + ? (h).magic[2]-'0' : 0 ) + +/*.................*/ +/*! Check if a nifti_1_header struct says if the data is stored in the + same file or in a separate file. Returns 1 if the data is in the same + file as the header, 0 if it is not. */ + +#define NIFTI_ONEFILE(h) ( (h).magic[1] == '+' ) + +/*.................*/ +/*! Check if a nifti_1_header struct needs to be byte swapped. + Returns 1 if it needs to be swapped, 0 if it does not. */ + +#define NIFTI_NEEDS_SWAP(h) ( (h).dim[0] < 0 || (h).dim[0] > 7 ) + +/*.................*/ +/*! Check if a nifti_1_header struct contains a 5th (vector) dimension. + Returns size of 5th dimension if > 1, returns 0 otherwise. */ + +#define NIFTI_5TH_DIM(h) ( ((h).dim[0]>4 && (h).dim[5]>1) ? (h).dim[5] : 0 ) + +/*****************************************************************************/ + +/*=================*/ +#ifdef __cplusplus +} +#endif +/*=================*/ + +#endif /* _NIFTI_HEADER_ */ diff --git a/spm/nii_for_spm2/@nifti/private/nifti_stats.c b/spm/nii_for_spm2/@nifti/private/nifti_stats.c new file mode 100755 index 0000000..c561c1a --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/nifti_stats.c @@ -0,0 +1,11277 @@ +#ifndef lint +static char sccsid[] = "%W% R.W. Cox %E%"; +#endif + /************************************************************************/ + /** Functions to compute cumulative distributions and their inverses **/ + /** for the NIfTI-1 statistical types. Much of this code is taken **/ + /** from other sources. In particular, the cdflib functions by **/ + /** Brown and Lovato make up the bulk of this file. That code **/ + /** was placed in the public domain. The code by K. Krishnamoorthy **/ + /** is also released for unrestricted use. Finally, the other parts **/ + /** of this file (by RW Cox) are released to the public domain. **/ + /** **/ + /** Most of this file comprises a set of "static" functions, to be **/ + /** called by the user-level functions at the very end of the file. **/ + /** At the end of the file is a simple main program to drive these **/ + /** functions. **/ + /** **/ + /** To find the user-level functions, search forward for the string **/ + /** "nifti_", which will be at about line 11000. **/ + /************************************************************************/ + /*****==============================================================*****/ + /***** Neither the National Institutes of Health (NIH), the DFWG, *****/ + /***** nor any of the members or employees of these institutions *****/ + /***** imply any warranty of usefulness of this material for any *****/ + /***** purpose, and do not assume any liability for damages, *****/ + /***** incidental or otherwise, caused by any use of this document. *****/ + /***** If these conditions are not acceptable, do not use this! *****/ + /*****==============================================================*****/ + /************************************************************************/ + + /*....................................................................... + To compile with gcc, for example: + + gcc -O3 -ffast-math -o nifti_stats nifti_stats.c -lm + ........................................................................*/ + +#include "nifti1.h" /* for the NIFTI_INTENT_* constants */ +#include +#include +#include + + /************************************************************************/ + /************ Include all the cdflib functions here and now *************/ + /************ [about 9900 lines of code below here] *************/ + /************************************************************************/ + +/** Prototypes for cdflib functions **/ + +static double algdiv(double*,double*); +static double alngam(double*); +static double alnrel(double*); +static double apser(double*,double*,double*,double*); +static double basym(double*,double*,double*,double*); +static double bcorr(double*,double*); +static double betaln(double*,double*); +static double bfrac(double*,double*,double*,double*,double*,double*); +static void bgrat(double*,double*,double*,double*,double*,double*,int*i); +static double bpser(double*,double*,double*,double*); +static void bratio(double*,double*,double*,double*,double*,double*,int*); +static double brcmp1(int*,double*,double*,double*,double*); +static double brcomp(double*,double*,double*,double*); +static double bup(double*,double*,double*,double*,int*,double*); +static void cdfbet(int*,double*,double*,double*,double*,double*,double*, + int*,double*); +static void cdfbin(int*,double*,double*,double*,double*,double*,double*, + int*,double*); +static void cdfchi(int*,double*,double*,double*,double*,int*,double*); +static void cdfchn(int*,double*,double*,double*,double*,double*,int*,double*); +static void cdff(int*,double*,double*,double*,double*,double*,int*,double*); +static void cdffnc(int*,double*,double*,double*,double*,double*,double*, + int*s,double*); +static void cdfgam(int*,double*,double*,double*,double*,double*,int*,double*); +static void cdfnbn(int*,double*,double*,double*,double*,double*,double*, + int*,double*); +static void cdfnor(int*,double*,double*,double*,double*,double*,int*,double*); +static void cdfpoi(int*,double*,double*,double*,double*,int*,double*); +static void cdft(int*,double*,double*,double*,double*,int*,double*); +static void cumbet(double*,double*,double*,double*,double*,double*); +static void cumbin(double*,double*,double*,double*,double*,double*); +static void cumchi(double*,double*,double*,double*); +static void cumchn(double*,double*,double*,double*,double*); +static void cumf(double*,double*,double*,double*,double*); +static void cumfnc(double*,double*,double*,double*,double*,double*); +static void cumgam(double*,double*,double*,double*); +static void cumnbn(double*,double*,double*,double*,double*,double*); +static void cumnor(double*,double*,double*); +static void cumpoi(double*,double*,double*,double*); +static void cumt(double*,double*,double*,double*); +static double dbetrm(double*,double*); +static double devlpl(double [],int*,double*); +static double dexpm1(double*); +static double dinvnr(double *p,double *q); +static void E0000(int,int*,double*,double*,unsigned long*, + unsigned long*,double*,double*,double*, + double*,double*,double*,double*); +static void dinvr(int*,double*,double*,unsigned long*,unsigned long*); +static void dstinv(double*,double*,double*,double*,double*,double*, + double*); +static double dlanor(double*); +static double dln1mx(double*); +static double dln1px(double*); +static double dlnbet(double*,double*); +static double dlngam(double*); +static double dstrem(double*); +static double dt1(double*,double*,double*); +static void E0001(int,int*,double*,double*,double*,double*, + unsigned long*,unsigned long*,double*,double*, + double*,double*); +static void dzror(int*,double*,double*,double*,double *, + unsigned long*,unsigned long*); +static void dstzr(double *zxlo,double *zxhi,double *zabstl,double *zreltl); +static double erf1(double*); +static double erfc1(int*,double*); +static double esum(int*,double*); +static double exparg(int*); +static double fpser(double*,double*,double*,double*); +static double gam1(double*); +static void gaminv(double*,double*,double*,double*,double*,int*); +static double gamln(double*); +static double gamln1(double*); +static double Xgamm(double*); +static void grat1(double*,double*,double*,double*,double*,double*); +static void gratio(double*,double*,double*,double*,int*); +static double gsumln(double*,double*); +static double psi(double*); +static double rcomp(double*,double*); +static double rexp(double*); +static double rlog(double*); +static double rlog1(double*); +static double spmpar(int*); +static double stvaln(double*); +static double fifdint(double); +static double fifdmax1(double,double); +static double fifdmin1(double,double); +static double fifdsign(double,double); +static long fifidint(double); +static long fifmod(long,long); +static void ftnstop(char*); +static int ipmpar(int*); + +/***=====================================================================***/ +static double algdiv(double *a,double *b) +/* +----------------------------------------------------------------------- + + COMPUTATION OF LN(GAMMA(B)/GAMMA(A+B)) WHEN B .GE. 8 + + -------- + + IN THIS ALGORITHM, DEL(X) IS THE FUNCTION DEFINED BY + LN(GAMMA(X)) = (X - 0.5)*LN(X) - X + 0.5*LN(2*PI) + DEL(X). + +----------------------------------------------------------------------- +*/ +{ +static double c0 = .833333333333333e-01; +static double c1 = -.277777777760991e-02; +static double c2 = .793650666825390e-03; +static double c3 = -.595202931351870e-03; +static double c4 = .837308034031215e-03; +static double c5 = -.165322962780713e-02; +static double algdiv,c,d,h,s11,s3,s5,s7,s9,t,u,v,w,x,x2,T1; +/* + .. + .. Executable Statements .. +*/ + if(*a <= *b) goto S10; + h = *b/ *a; + c = 1.0e0/(1.0e0+h); + x = h/(1.0e0+h); + d = *a+(*b-0.5e0); + goto S20; +S10: + h = *a/ *b; + c = h/(1.0e0+h); + x = 1.0e0/(1.0e0+h); + d = *b+(*a-0.5e0); +S20: +/* + SET SN = (1 - X**N)/(1 - X) +*/ + x2 = x*x; + s3 = 1.0e0+(x+x2); + s5 = 1.0e0+(x+x2*s3); + s7 = 1.0e0+(x+x2*s5); + s9 = 1.0e0+(x+x2*s7); + s11 = 1.0e0+(x+x2*s9); +/* + SET W = DEL(B) - DEL(A + B) +*/ + t = pow(1.0e0/ *b,2.0); + w = ((((c5*s11*t+c4*s9)*t+c3*s7)*t+c2*s5)*t+c1*s3)*t+c0; + w *= (c/ *b); +/* + COMBINE THE RESULTS +*/ + T1 = *a/ *b; + u = d*alnrel(&T1); + v = *a*(log(*b)-1.0e0); + if(u <= v) goto S30; + algdiv = w-v-u; + return algdiv; +S30: + algdiv = w-u-v; + return algdiv; +} /* END */ + +/***=====================================================================***/ +static double alngam(double *x) +/* +********************************************************************** + + double alngam(double *x) + double precision LN of the GAMma function + + + Function + + + Returns the natural logarithm of GAMMA(X). + + + Arguments + + + X --> value at which scaled log gamma is to be returned + X is DOUBLE PRECISION + + + Method + + + If X .le. 6.0, then use recursion to get X below 3 + then apply rational approximation number 5236 of + Hart et al, Computer Approximations, John Wiley and + Sons, NY, 1968. + + If X .gt. 6.0, then use recursion to get X to at least 12 and + then use formula 5423 of the same source. + +********************************************************************** +*/ +{ +#define hln2pi 0.91893853320467274178e0 +static double coef[5] = { + 0.83333333333333023564e-1,-0.27777777768818808e-2,0.79365006754279e-3, + -0.594997310889e-3,0.8065880899e-3 +}; +static double scoefd[4] = { + 0.62003838007126989331e2,0.9822521104713994894e1,-0.8906016659497461257e1, + 0.1000000000000000000e1 +}; +static double scoefn[9] = { + 0.62003838007127258804e2,0.36036772530024836321e2,0.20782472531792126786e2, + 0.6338067999387272343e1,0.215994312846059073e1,0.3980671310203570498e0, + 0.1093115956710439502e0,0.92381945590275995e-2,0.29737866448101651e-2 +}; +static int K1 = 9; +static int K3 = 4; +static int K5 = 5; +static double alngam,offset,prod,xx; +static int i,n; +static double T2,T4,T6; +/* + .. + .. Executable Statements .. +*/ + if(!(*x <= 6.0e0)) goto S70; + prod = 1.0e0; + xx = *x; + if(!(*x > 3.0e0)) goto S30; +S10: + if(!(xx > 3.0e0)) goto S20; + xx -= 1.0e0; + prod *= xx; + goto S10; +S30: +S20: + if(!(*x < 2.0e0)) goto S60; +S40: + if(!(xx < 2.0e0)) goto S50; + prod /= xx; + xx += 1.0e0; + goto S40; +S60: +S50: + T2 = xx-2.0e0; + T4 = xx-2.0e0; + alngam = devlpl(scoefn,&K1,&T2)/devlpl(scoefd,&K3,&T4); +/* + COMPUTE RATIONAL APPROXIMATION TO GAMMA(X) +*/ + alngam *= prod; + alngam = log(alngam); + goto S110; +S70: + offset = hln2pi; +/* + IF NECESSARY MAKE X AT LEAST 12 AND CARRY CORRECTION IN OFFSET +*/ + n = fifidint(12.0e0-*x); + if(!(n > 0)) goto S90; + prod = 1.0e0; + for(i=1; i<=n; i++) prod *= (*x+(double)(i-1)); + offset -= log(prod); + xx = *x+(double)n; + goto S100; +S90: + xx = *x; +S100: +/* + COMPUTE POWER SERIES +*/ + T6 = 1.0e0/pow(xx,2.0); + alngam = devlpl(coef,&K5,&T6)/xx; + alngam += (offset+(xx-0.5e0)*log(xx)-xx); +S110: + return alngam; +#undef hln2pi +} /* END */ + +/***=====================================================================***/ +static double alnrel(double *a) +/* +----------------------------------------------------------------------- + EVALUATION OF THE FUNCTION LN(1 + A) +----------------------------------------------------------------------- +*/ +{ +static double p1 = -.129418923021993e+01; +static double p2 = .405303492862024e+00; +static double p3 = -.178874546012214e-01; +static double q1 = -.162752256355323e+01; +static double q2 = .747811014037616e+00; +static double q3 = -.845104217945565e-01; +static double alnrel,t,t2,w,x; +/* + .. + .. Executable Statements .. +*/ + if(fabs(*a) > 0.375e0) goto S10; + t = *a/(*a+2.0e0); + t2 = t*t; + w = (((p3*t2+p2)*t2+p1)*t2+1.0e0)/(((q3*t2+q2)*t2+q1)*t2+1.0e0); + alnrel = 2.0e0*t*w; + return alnrel; +S10: + x = 1.e0+*a; + alnrel = log(x); + return alnrel; +} /* END */ + +/***=====================================================================***/ +static double apser(double *a,double *b,double *x,double *eps) +/* +----------------------------------------------------------------------- + APSER YIELDS THE INCOMPLETE BETA RATIO I(SUB(1-X))(B,A) FOR + A .LE. MIN(EPS,EPS*B), B*X .LE. 1, AND X .LE. 0.5. USED WHEN + A IS VERY SMALL. USE ONLY IF ABOVE INEQUALITIES ARE SATISFIED. +----------------------------------------------------------------------- +*/ +{ +static double g = .577215664901533e0; +static double apser,aj,bx,c,j,s,t,tol; +/* + .. + .. Executable Statements .. +*/ + bx = *b**x; + t = *x-bx; + if(*b**eps > 2.e-2) goto S10; + c = log(*x)+psi(b)+g+t; + goto S20; +S10: + c = log(bx)+g+t; +S20: + tol = 5.0e0**eps*fabs(c); + j = 1.0e0; + s = 0.0e0; +S30: + j += 1.0e0; + t *= (*x-bx/j); + aj = t/j; + s += aj; + if(fabs(aj) > tol) goto S30; + apser = -(*a*(c+s)); + return apser; +} /* END */ + +/***=====================================================================***/ +static double basym(double *a,double *b,double *lambda,double *eps) +/* +----------------------------------------------------------------------- + ASYMPTOTIC EXPANSION FOR IX(A,B) FOR LARGE A AND B. + LAMBDA = (A + B)*Y - B AND EPS IS THE TOLERANCE USED. + IT IS ASSUMED THAT LAMBDA IS NONNEGATIVE AND THAT + A AND B ARE GREATER THAN OR EQUAL TO 15. +----------------------------------------------------------------------- +*/ +{ +static double e0 = 1.12837916709551e0; +static double e1 = .353553390593274e0; +static int num = 20; +/* +------------------------ + ****** NUM IS THE MAXIMUM VALUE THAT N CAN TAKE IN THE DO LOOP + ENDING AT STATEMENT 50. IT IS REQUIRED THAT NUM BE EVEN. + THE ARRAYS A0, B0, C, D HAVE DIMENSION NUM + 1. +------------------------ + E0 = 2/SQRT(PI) + E1 = 2**(-3/2) +------------------------ +*/ +static int K3 = 1; +static double basym,bsum,dsum,f,h,h2,hn,j0,j1,r,r0,r1,s,sum,t,t0,t1,u,w,w0,z,z0, + z2,zn,znm1; +static int i,im1,imj,j,m,mm1,mmj,n,np1; +static double a0[21],b0[21],c[21],d[21],T1,T2; +/* + .. + .. Executable Statements .. +*/ + basym = 0.0e0; + if(*a >= *b) goto S10; + h = *a/ *b; + r0 = 1.0e0/(1.0e0+h); + r1 = (*b-*a)/ *b; + w0 = 1.0e0/sqrt(*a*(1.0e0+h)); + goto S20; +S10: + h = *b/ *a; + r0 = 1.0e0/(1.0e0+h); + r1 = (*b-*a)/ *a; + w0 = 1.0e0/sqrt(*b*(1.0e0+h)); +S20: + T1 = -(*lambda/ *a); + T2 = *lambda/ *b; + f = *a*rlog1(&T1)+*b*rlog1(&T2); + t = exp(-f); + if(t == 0.0e0) return basym; + z0 = sqrt(f); + z = 0.5e0*(z0/e1); + z2 = f+f; + a0[0] = 2.0e0/3.0e0*r1; + c[0] = -(0.5e0*a0[0]); + d[0] = -c[0]; + j0 = 0.5e0/e0*erfc1(&K3,&z0); + j1 = e1; + sum = j0+d[0]*w0*j1; + s = 1.0e0; + h2 = h*h; + hn = 1.0e0; + w = w0; + znm1 = z; + zn = z2; + for(n=2; n<=num; n+=2) { + hn = h2*hn; + a0[n-1] = 2.0e0*r0*(1.0e0+h*hn)/((double)n+2.0e0); + np1 = n+1; + s += hn; + a0[np1-1] = 2.0e0*r1*s/((double)n+3.0e0); + for(i=n; i<=np1; i++) { + r = -(0.5e0*((double)i+1.0e0)); + b0[0] = r*a0[0]; + for(m=2; m<=i; m++) { + bsum = 0.0e0; + mm1 = m-1; + for(j=1; j<=mm1; j++) { + mmj = m-j; + bsum += (((double)j*r-(double)mmj)*a0[j-1]*b0[mmj-1]); + } + b0[m-1] = r*a0[m-1]+bsum/(double)m; + } + c[i-1] = b0[i-1]/((double)i+1.0e0); + dsum = 0.0e0; + im1 = i-1; + for(j=1; j<=im1; j++) { + imj = i-j; + dsum += (d[imj-1]*c[j-1]); + } + d[i-1] = -(dsum+c[i-1]); + } + j0 = e1*znm1+((double)n-1.0e0)*j0; + j1 = e1*zn+(double)n*j1; + znm1 = z2*znm1; + zn = z2*zn; + w = w0*w; + t0 = d[n-1]*w*j0; + w = w0*w; + t1 = d[np1-1]*w*j1; + sum += (t0+t1); + if(fabs(t0)+fabs(t1) <= *eps*sum) goto S80; + } +S80: + u = exp(-bcorr(a,b)); + basym = e0*t*u*sum; + return basym; +} /* END */ + +/***=====================================================================***/ +static double bcorr(double *a0,double *b0) +/* +----------------------------------------------------------------------- + + EVALUATION OF DEL(A0) + DEL(B0) - DEL(A0 + B0) WHERE + LN(GAMMA(A)) = (A - 0.5)*LN(A) - A + 0.5*LN(2*PI) + DEL(A). + IT IS ASSUMED THAT A0 .GE. 8 AND B0 .GE. 8. + +----------------------------------------------------------------------- +*/ +{ +static double c0 = .833333333333333e-01; +static double c1 = -.277777777760991e-02; +static double c2 = .793650666825390e-03; +static double c3 = -.595202931351870e-03; +static double c4 = .837308034031215e-03; +static double c5 = -.165322962780713e-02; +static double bcorr,a,b,c,h,s11,s3,s5,s7,s9,t,w,x,x2; +/* + .. + .. Executable Statements .. +*/ + a = fifdmin1(*a0,*b0); + b = fifdmax1(*a0,*b0); + h = a/b; + c = h/(1.0e0+h); + x = 1.0e0/(1.0e0+h); + x2 = x*x; +/* + SET SN = (1 - X**N)/(1 - X) +*/ + s3 = 1.0e0+(x+x2); + s5 = 1.0e0+(x+x2*s3); + s7 = 1.0e0+(x+x2*s5); + s9 = 1.0e0+(x+x2*s7); + s11 = 1.0e0+(x+x2*s9); +/* + SET W = DEL(B) - DEL(A + B) +*/ + t = pow(1.0e0/b,2.0); + w = ((((c5*s11*t+c4*s9)*t+c3*s7)*t+c2*s5)*t+c1*s3)*t+c0; + w *= (c/b); +/* + COMPUTE DEL(A) + W +*/ + t = pow(1.0e0/a,2.0); + bcorr = (((((c5*t+c4)*t+c3)*t+c2)*t+c1)*t+c0)/a+w; + return bcorr; +} /* END */ + +/***=====================================================================***/ +static double betaln(double *a0,double *b0) +/* +----------------------------------------------------------------------- + EVALUATION OF THE LOGARITHM OF THE BETA FUNCTION +----------------------------------------------------------------------- + E = 0.5*LN(2*PI) +-------------------------- +*/ +{ +static double e = .918938533204673e0; +static double betaln,a,b,c,h,u,v,w,z; +static int i,n; +static double T1; +/* + .. + .. Executable Statements .. +*/ + a = fifdmin1(*a0,*b0); + b = fifdmax1(*a0,*b0); + if(a >= 8.0e0) goto S100; + if(a >= 1.0e0) goto S20; +/* +----------------------------------------------------------------------- + PROCEDURE WHEN A .LT. 1 +----------------------------------------------------------------------- +*/ + if(b >= 8.0e0) goto S10; + T1 = a+b; + betaln = gamln(&a)+(gamln(&b)-gamln(&T1)); + return betaln; +S10: + betaln = gamln(&a)+algdiv(&a,&b); + return betaln; +S20: +/* +----------------------------------------------------------------------- + PROCEDURE WHEN 1 .LE. A .LT. 8 +----------------------------------------------------------------------- +*/ + if(a > 2.0e0) goto S40; + if(b > 2.0e0) goto S30; + betaln = gamln(&a)+gamln(&b)-gsumln(&a,&b); + return betaln; +S30: + w = 0.0e0; + if(b < 8.0e0) goto S60; + betaln = gamln(&a)+algdiv(&a,&b); + return betaln; +S40: +/* + REDUCTION OF A WHEN B .LE. 1000 +*/ + if(b > 1000.0e0) goto S80; + n = a-1.0e0; + w = 1.0e0; + for(i=1; i<=n; i++) { + a -= 1.0e0; + h = a/b; + w *= (h/(1.0e0+h)); + } + w = log(w); + if(b < 8.0e0) goto S60; + betaln = w+gamln(&a)+algdiv(&a,&b); + return betaln; +S60: +/* + REDUCTION OF B WHEN B .LT. 8 +*/ + n = b-1.0e0; + z = 1.0e0; + for(i=1; i<=n; i++) { + b -= 1.0e0; + z *= (b/(a+b)); + } + betaln = w+log(z)+(gamln(&a)+(gamln(&b)-gsumln(&a,&b))); + return betaln; +S80: +/* + REDUCTION OF A WHEN B .GT. 1000 +*/ + n = a-1.0e0; + w = 1.0e0; + for(i=1; i<=n; i++) { + a -= 1.0e0; + w *= (a/(1.0e0+a/b)); + } + betaln = log(w)-(double)n*log(b)+(gamln(&a)+algdiv(&a,&b)); + return betaln; +S100: +/* +----------------------------------------------------------------------- + PROCEDURE WHEN A .GE. 8 +----------------------------------------------------------------------- +*/ + w = bcorr(&a,&b); + h = a/b; + c = h/(1.0e0+h); + u = -((a-0.5e0)*log(c)); + v = b*alnrel(&h); + if(u <= v) goto S110; + betaln = -(0.5e0*log(b))+e+w-v-u; + return betaln; +S110: + betaln = -(0.5e0*log(b))+e+w-u-v; + return betaln; +} /* END */ + +/***=====================================================================***/ +static double bfrac(double *a,double *b,double *x,double *y,double *lambda, + double *eps) +/* +----------------------------------------------------------------------- + CONTINUED FRACTION EXPANSION FOR IX(A,B) WHEN A,B .GT. 1. + IT IS ASSUMED THAT LAMBDA = (A + B)*Y - B. +----------------------------------------------------------------------- +*/ +{ +static double bfrac,alpha,an,anp1,beta,bn,bnp1,c,c0,c1,e,n,p,r,r0,s,t,w,yp1; +/* + .. + .. Executable Statements .. +*/ + bfrac = brcomp(a,b,x,y); + if(bfrac == 0.0e0) return bfrac; + c = 1.0e0+*lambda; + c0 = *b/ *a; + c1 = 1.0e0+1.0e0/ *a; + yp1 = *y+1.0e0; + n = 0.0e0; + p = 1.0e0; + s = *a+1.0e0; + an = 0.0e0; + bn = anp1 = 1.0e0; + bnp1 = c/c1; + r = c1/c; +S10: +/* + CONTINUED FRACTION CALCULATION +*/ + n += 1.0e0; + t = n/ *a; + w = n*(*b-n)**x; + e = *a/s; + alpha = p*(p+c0)*e*e*(w**x); + e = (1.0e0+t)/(c1+t+t); + beta = n+w/s+e*(c+n*yp1); + p = 1.0e0+t; + s += 2.0e0; +/* + UPDATE AN, BN, ANP1, AND BNP1 +*/ + t = alpha*an+beta*anp1; + an = anp1; + anp1 = t; + t = alpha*bn+beta*bnp1; + bn = bnp1; + bnp1 = t; + r0 = r; + r = anp1/bnp1; + if(fabs(r-r0) <= *eps*r) goto S20; +/* + RESCALE AN, BN, ANP1, AND BNP1 +*/ + an /= bnp1; + bn /= bnp1; + anp1 = r; + bnp1 = 1.0e0; + goto S10; +S20: +/* + TERMINATION +*/ + bfrac *= r; + return bfrac; +} /* END */ + +/***=====================================================================***/ +static void bgrat(double *a,double *b,double *x,double *y,double *w, + double *eps,int *ierr) +/* +----------------------------------------------------------------------- + ASYMPTOTIC EXPANSION FOR IX(A,B) WHEN A IS LARGER THAN B. + THE RESULT OF THE EXPANSION IS ADDED TO W. IT IS ASSUMED + THAT A .GE. 15 AND B .LE. 1. EPS IS THE TOLERANCE USED. + IERR IS A VARIABLE THAT REPORTS THE STATUS OF THE RESULTS. +----------------------------------------------------------------------- +*/ +{ +static double bm1,bp2n,cn,coef,dj,j,l,lnx,n2,nu,p,q,r,s,sum,t,t2,u,v,z; +static int i,n,nm1; +static double c[30],d[30],T1; +/* + .. + .. Executable Statements .. +*/ + bm1 = *b-0.5e0-0.5e0; + nu = *a+0.5e0*bm1; + if(*y > 0.375e0) goto S10; + T1 = -*y; + lnx = alnrel(&T1); + goto S20; +S10: + lnx = log(*x); +S20: + z = -(nu*lnx); + if(*b*z == 0.0e0) goto S70; +/* + COMPUTATION OF THE EXPANSION + SET R = EXP(-Z)*Z**B/GAMMA(B) +*/ + r = *b*(1.0e0+gam1(b))*exp(*b*log(z)); + r *= (exp(*a*lnx)*exp(0.5e0*bm1*lnx)); + u = algdiv(b,a)+*b*log(nu); + u = r*exp(-u); + if(u == 0.0e0) goto S70; + grat1(b,&z,&r,&p,&q,eps); + v = 0.25e0*pow(1.0e0/nu,2.0); + t2 = 0.25e0*lnx*lnx; + l = *w/u; + j = q/r; + sum = j; + t = cn = 1.0e0; + n2 = 0.0e0; + for(n=1; n<=30; n++) { + bp2n = *b+n2; + j = (bp2n*(bp2n+1.0e0)*j+(z+bp2n+1.0e0)*t)*v; + n2 += 2.0e0; + t *= t2; + cn /= (n2*(n2+1.0e0)); + c[n-1] = cn; + s = 0.0e0; + if(n == 1) goto S40; + nm1 = n-1; + coef = *b-(double)n; + for(i=1; i<=nm1; i++) { + s += (coef*c[i-1]*d[n-i-1]); + coef += *b; + } +S40: + d[n-1] = bm1*cn+s/(double)n; + dj = d[n-1]*j; + sum += dj; + if(sum <= 0.0e0) goto S70; + if(fabs(dj) <= *eps*(sum+l)) goto S60; + } +S60: +/* + ADD THE RESULTS TO W +*/ + *ierr = 0; + *w += (u*sum); + return; +S70: +/* + THE EXPANSION CANNOT BE COMPUTED +*/ + *ierr = 1; + return; +} /* END */ + +/***=====================================================================***/ +static double bpser(double *a,double *b,double *x,double *eps) +/* +----------------------------------------------------------------------- + POWER SERIES EXPANSION FOR EVALUATING IX(A,B) WHEN B .LE. 1 + OR B*X .LE. 0.7. EPS IS THE TOLERANCE USED. +----------------------------------------------------------------------- +*/ +{ +static double bpser,a0,apb,b0,c,n,sum,t,tol,u,w,z; +static int i,m; +/* + .. + .. Executable Statements .. +*/ + bpser = 0.0e0; + if(*x == 0.0e0) return bpser; +/* +----------------------------------------------------------------------- + COMPUTE THE FACTOR X**A/(A*BETA(A,B)) +----------------------------------------------------------------------- +*/ + a0 = fifdmin1(*a,*b); + if(a0 < 1.0e0) goto S10; + z = *a*log(*x)-betaln(a,b); + bpser = exp(z)/ *a; + goto S100; +S10: + b0 = fifdmax1(*a,*b); + if(b0 >= 8.0e0) goto S90; + if(b0 > 1.0e0) goto S40; +/* + PROCEDURE FOR A0 .LT. 1 AND B0 .LE. 1 +*/ + bpser = pow(*x,*a); + if(bpser == 0.0e0) return bpser; + apb = *a+*b; + if(apb > 1.0e0) goto S20; + z = 1.0e0+gam1(&apb); + goto S30; +S20: + u = *a+*b-1.e0; + z = (1.0e0+gam1(&u))/apb; +S30: + c = (1.0e0+gam1(a))*(1.0e0+gam1(b))/z; + bpser *= (c*(*b/apb)); + goto S100; +S40: +/* + PROCEDURE FOR A0 .LT. 1 AND 1 .LT. B0 .LT. 8 +*/ + u = gamln1(&a0); + m = b0-1.0e0; + if(m < 1) goto S60; + c = 1.0e0; + for(i=1; i<=m; i++) { + b0 -= 1.0e0; + c *= (b0/(a0+b0)); + } + u = log(c)+u; +S60: + z = *a*log(*x)-u; + b0 -= 1.0e0; + apb = a0+b0; + if(apb > 1.0e0) goto S70; + t = 1.0e0+gam1(&apb); + goto S80; +S70: + u = a0+b0-1.e0; + t = (1.0e0+gam1(&u))/apb; +S80: + bpser = exp(z)*(a0/ *a)*(1.0e0+gam1(&b0))/t; + goto S100; +S90: +/* + PROCEDURE FOR A0 .LT. 1 AND B0 .GE. 8 +*/ + u = gamln1(&a0)+algdiv(&a0,&b0); + z = *a*log(*x)-u; + bpser = a0/ *a*exp(z); +S100: + if(bpser == 0.0e0 || *a <= 0.1e0**eps) return bpser; +/* +----------------------------------------------------------------------- + COMPUTE THE SERIES +----------------------------------------------------------------------- +*/ + sum = n = 0.0e0; + c = 1.0e0; + tol = *eps/ *a; +S110: + n += 1.0e0; + c *= ((0.5e0+(0.5e0-*b/n))**x); + w = c/(*a+n); + sum += w; + if(fabs(w) > tol) goto S110; + bpser *= (1.0e0+*a*sum); + return bpser; +} /* END */ + +/***=====================================================================***/ +static void bratio(double *a,double *b,double *x,double *y,double *w, + double *w1,int *ierr) +/* +----------------------------------------------------------------------- + + EVALUATION OF THE INCOMPLETE BETA FUNCTION IX(A,B) + + -------------------- + + IT IS ASSUMED THAT A AND B ARE NONNEGATIVE, AND THAT X .LE. 1 + AND Y = 1 - X. BRATIO ASSIGNS W AND W1 THE VALUES + + W = IX(A,B) + W1 = 1 - IX(A,B) + + IERR IS A VARIABLE THAT REPORTS THE STATUS OF THE RESULTS. + IF NO INPUT ERRORS ARE DETECTED THEN IERR IS SET TO 0 AND + W AND W1 ARE COMPUTED. OTHERWISE, IF AN ERROR IS DETECTED, + THEN W AND W1 ARE ASSIGNED THE VALUE 0 AND IERR IS SET TO + ONE OF THE FOLLOWING VALUES ... + + IERR = 1 IF A OR B IS NEGATIVE + IERR = 2 IF A = B = 0 + IERR = 3 IF X .LT. 0 OR X .GT. 1 + IERR = 4 IF Y .LT. 0 OR Y .GT. 1 + IERR = 5 IF X + Y .NE. 1 + IERR = 6 IF X = A = 0 + IERR = 7 IF Y = B = 0 + +-------------------- + WRITTEN BY ALFRED H. MORRIS, JR. + NAVAL SURFACE WARFARE CENTER + DAHLGREN, VIRGINIA + REVISED ... NOV 1991 +----------------------------------------------------------------------- +*/ +{ +static int K1 = 1; +static double a0,b0,eps,lambda,t,x0,y0,z; +static int ierr1,ind,n; +static double T2,T3,T4,T5; +/* + .. + .. Executable Statements .. +*/ +/* + ****** EPS IS A MACHINE DEPENDENT CONSTANT. EPS IS THE SMALLEST + FLOATING POINT NUMBER FOR WHICH 1.0 + EPS .GT. 1.0 +*/ + eps = spmpar(&K1); + *w = *w1 = 0.0e0; + if(*a < 0.0e0 || *b < 0.0e0) goto S270; + if(*a == 0.0e0 && *b == 0.0e0) goto S280; + if(*x < 0.0e0 || *x > 1.0e0) goto S290; + if(*y < 0.0e0 || *y > 1.0e0) goto S300; + z = *x+*y-0.5e0-0.5e0; + if(fabs(z) > 3.0e0*eps) goto S310; + *ierr = 0; + if(*x == 0.0e0) goto S210; + if(*y == 0.0e0) goto S230; + if(*a == 0.0e0) goto S240; + if(*b == 0.0e0) goto S220; + eps = fifdmax1(eps,1.e-15); + if(fifdmax1(*a,*b) < 1.e-3*eps) goto S260; + ind = 0; + a0 = *a; + b0 = *b; + x0 = *x; + y0 = *y; + if(fifdmin1(a0,b0) > 1.0e0) goto S40; +/* + PROCEDURE FOR A0 .LE. 1 OR B0 .LE. 1 +*/ + if(*x <= 0.5e0) goto S10; + ind = 1; + a0 = *b; + b0 = *a; + x0 = *y; + y0 = *x; +S10: + if(b0 < fifdmin1(eps,eps*a0)) goto S90; + if(a0 < fifdmin1(eps,eps*b0) && b0*x0 <= 1.0e0) goto S100; + if(fifdmax1(a0,b0) > 1.0e0) goto S20; + if(a0 >= fifdmin1(0.2e0,b0)) goto S110; + if(pow(x0,a0) <= 0.9e0) goto S110; + if(x0 >= 0.3e0) goto S120; + n = 20; + goto S140; +S20: + if(b0 <= 1.0e0) goto S110; + if(x0 >= 0.3e0) goto S120; + if(x0 >= 0.1e0) goto S30; + if(pow(x0*b0,a0) <= 0.7e0) goto S110; +S30: + if(b0 > 15.0e0) goto S150; + n = 20; + goto S140; +S40: +/* + PROCEDURE FOR A0 .GT. 1 AND B0 .GT. 1 +*/ + if(*a > *b) goto S50; + lambda = *a-(*a+*b)**x; + goto S60; +S50: + lambda = (*a+*b)**y-*b; +S60: + if(lambda >= 0.0e0) goto S70; + ind = 1; + a0 = *b; + b0 = *a; + x0 = *y; + y0 = *x; + lambda = fabs(lambda); +S70: + if(b0 < 40.0e0 && b0*x0 <= 0.7e0) goto S110; + if(b0 < 40.0e0) goto S160; + if(a0 > b0) goto S80; + if(a0 <= 100.0e0) goto S130; + if(lambda > 0.03e0*a0) goto S130; + goto S200; +S80: + if(b0 <= 100.0e0) goto S130; + if(lambda > 0.03e0*b0) goto S130; + goto S200; +S90: +/* + EVALUATION OF THE APPROPRIATE ALGORITHM +*/ + *w = fpser(&a0,&b0,&x0,&eps); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S100: + *w1 = apser(&a0,&b0,&x0,&eps); + *w = 0.5e0+(0.5e0-*w1); + goto S250; +S110: + *w = bpser(&a0,&b0,&x0,&eps); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S120: + *w1 = bpser(&b0,&a0,&y0,&eps); + *w = 0.5e0+(0.5e0-*w1); + goto S250; +S130: + T2 = 15.0e0*eps; + *w = bfrac(&a0,&b0,&x0,&y0,&lambda,&T2); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S140: + *w1 = bup(&b0,&a0,&y0,&x0,&n,&eps); + b0 += (double)n; +S150: + T3 = 15.0e0*eps; + bgrat(&b0,&a0,&y0,&x0,w1,&T3,&ierr1); + *w = 0.5e0+(0.5e0-*w1); + goto S250; +S160: + n = b0; + b0 -= (double)n; + if(b0 != 0.0e0) goto S170; + n -= 1; + b0 = 1.0e0; +S170: + *w = bup(&b0,&a0,&y0,&x0,&n,&eps); + if(x0 > 0.7e0) goto S180; + *w += bpser(&a0,&b0,&x0,&eps); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S180: + if(a0 > 15.0e0) goto S190; + n = 20; + *w += bup(&a0,&b0,&x0,&y0,&n,&eps); + a0 += (double)n; +S190: + T4 = 15.0e0*eps; + bgrat(&a0,&b0,&x0,&y0,w,&T4,&ierr1); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S200: + T5 = 100.0e0*eps; + *w = basym(&a0,&b0,&lambda,&T5); + *w1 = 0.5e0+(0.5e0-*w); + goto S250; +S210: +/* + TERMINATION OF THE PROCEDURE +*/ + if(*a == 0.0e0) goto S320; +S220: + *w = 0.0e0; + *w1 = 1.0e0; + return; +S230: + if(*b == 0.0e0) goto S330; +S240: + *w = 1.0e0; + *w1 = 0.0e0; + return; +S250: + if(ind == 0) return; + t = *w; + *w = *w1; + *w1 = t; + return; +S260: +/* + PROCEDURE FOR A AND B .LT. 1.E-3*EPS +*/ + *w = *b/(*a+*b); + *w1 = *a/(*a+*b); + return; +S270: +/* + ERROR RETURN +*/ + *ierr = 1; + return; +S280: + *ierr = 2; + return; +S290: + *ierr = 3; + return; +S300: + *ierr = 4; + return; +S310: + *ierr = 5; + return; +S320: + *ierr = 6; + return; +S330: + *ierr = 7; + return; +} /* END */ + +/***=====================================================================***/ +static double brcmp1(int *mu,double *a,double *b,double *x,double *y) +/* +----------------------------------------------------------------------- + EVALUATION OF EXP(MU) * (X**A*Y**B/BETA(A,B)) +----------------------------------------------------------------------- +*/ +{ +static double Const = .398942280401433e0; +static double brcmp1,a0,apb,b0,c,e,h,lambda,lnx,lny,t,u,v,x0,y0,z; +static int i,n; +/* +----------------- + CONST = 1/SQRT(2*PI) +----------------- +*/ +static double T1,T2,T3,T4; +/* + .. + .. Executable Statements .. +*/ + a0 = fifdmin1(*a,*b); + if(a0 >= 8.0e0) goto S130; + if(*x > 0.375e0) goto S10; + lnx = log(*x); + T1 = -*x; + lny = alnrel(&T1); + goto S30; +S10: + if(*y > 0.375e0) goto S20; + T2 = -*y; + lnx = alnrel(&T2); + lny = log(*y); + goto S30; +S20: + lnx = log(*x); + lny = log(*y); +S30: + z = *a*lnx+*b*lny; + if(a0 < 1.0e0) goto S40; + z -= betaln(a,b); + brcmp1 = esum(mu,&z); + return brcmp1; +S40: +/* +----------------------------------------------------------------------- + PROCEDURE FOR A .LT. 1 OR B .LT. 1 +----------------------------------------------------------------------- +*/ + b0 = fifdmax1(*a,*b); + if(b0 >= 8.0e0) goto S120; + if(b0 > 1.0e0) goto S70; +/* + ALGORITHM FOR B0 .LE. 1 +*/ + brcmp1 = esum(mu,&z); + if(brcmp1 == 0.0e0) return brcmp1; + apb = *a+*b; + if(apb > 1.0e0) goto S50; + z = 1.0e0+gam1(&apb); + goto S60; +S50: + u = *a+*b-1.e0; + z = (1.0e0+gam1(&u))/apb; +S60: + c = (1.0e0+gam1(a))*(1.0e0+gam1(b))/z; + brcmp1 = brcmp1*(a0*c)/(1.0e0+a0/b0); + return brcmp1; +S70: +/* + ALGORITHM FOR 1 .LT. B0 .LT. 8 +*/ + u = gamln1(&a0); + n = b0-1.0e0; + if(n < 1) goto S90; + c = 1.0e0; + for(i=1; i<=n; i++) { + b0 -= 1.0e0; + c *= (b0/(a0+b0)); + } + u = log(c)+u; +S90: + z -= u; + b0 -= 1.0e0; + apb = a0+b0; + if(apb > 1.0e0) goto S100; + t = 1.0e0+gam1(&apb); + goto S110; +S100: + u = a0+b0-1.e0; + t = (1.0e0+gam1(&u))/apb; +S110: + brcmp1 = a0*esum(mu,&z)*(1.0e0+gam1(&b0))/t; + return brcmp1; +S120: +/* + ALGORITHM FOR B0 .GE. 8 +*/ + u = gamln1(&a0)+algdiv(&a0,&b0); + T3 = z-u; + brcmp1 = a0*esum(mu,&T3); + return brcmp1; +S130: +/* +----------------------------------------------------------------------- + PROCEDURE FOR A .GE. 8 AND B .GE. 8 +----------------------------------------------------------------------- +*/ + if(*a > *b) goto S140; + h = *a/ *b; + x0 = h/(1.0e0+h); + y0 = 1.0e0/(1.0e0+h); + lambda = *a-(*a+*b)**x; + goto S150; +S140: + h = *b/ *a; + x0 = 1.0e0/(1.0e0+h); + y0 = h/(1.0e0+h); + lambda = (*a+*b)**y-*b; +S150: + e = -(lambda/ *a); + if(fabs(e) > 0.6e0) goto S160; + u = rlog1(&e); + goto S170; +S160: + u = e-log(*x/x0); +S170: + e = lambda/ *b; + if(fabs(e) > 0.6e0) goto S180; + v = rlog1(&e); + goto S190; +S180: + v = e-log(*y/y0); +S190: + T4 = -(*a*u+*b*v); + z = esum(mu,&T4); + brcmp1 = Const*sqrt(*b*x0)*z*exp(-bcorr(a,b)); + return brcmp1; +} /* END */ + +/***=====================================================================***/ +static double brcomp(double *a,double *b,double *x,double *y) +/* +----------------------------------------------------------------------- + EVALUATION OF X**A*Y**B/BETA(A,B) +----------------------------------------------------------------------- +*/ +{ +static double Const = .398942280401433e0; +static double brcomp,a0,apb,b0,c,e,h,lambda,lnx,lny,t,u,v,x0,y0,z; +static int i,n; +/* +----------------- + CONST = 1/SQRT(2*PI) +----------------- +*/ +static double T1,T2; +/* + .. + .. Executable Statements .. +*/ + brcomp = 0.0e0; + if(*x == 0.0e0 || *y == 0.0e0) return brcomp; + a0 = fifdmin1(*a,*b); + if(a0 >= 8.0e0) goto S130; + if(*x > 0.375e0) goto S10; + lnx = log(*x); + T1 = -*x; + lny = alnrel(&T1); + goto S30; +S10: + if(*y > 0.375e0) goto S20; + T2 = -*y; + lnx = alnrel(&T2); + lny = log(*y); + goto S30; +S20: + lnx = log(*x); + lny = log(*y); +S30: + z = *a*lnx+*b*lny; + if(a0 < 1.0e0) goto S40; + z -= betaln(a,b); + brcomp = exp(z); + return brcomp; +S40: +/* +----------------------------------------------------------------------- + PROCEDURE FOR A .LT. 1 OR B .LT. 1 +----------------------------------------------------------------------- +*/ + b0 = fifdmax1(*a,*b); + if(b0 >= 8.0e0) goto S120; + if(b0 > 1.0e0) goto S70; +/* + ALGORITHM FOR B0 .LE. 1 +*/ + brcomp = exp(z); + if(brcomp == 0.0e0) return brcomp; + apb = *a+*b; + if(apb > 1.0e0) goto S50; + z = 1.0e0+gam1(&apb); + goto S60; +S50: + u = *a+*b-1.e0; + z = (1.0e0+gam1(&u))/apb; +S60: + c = (1.0e0+gam1(a))*(1.0e0+gam1(b))/z; + brcomp = brcomp*(a0*c)/(1.0e0+a0/b0); + return brcomp; +S70: +/* + ALGORITHM FOR 1 .LT. B0 .LT. 8 +*/ + u = gamln1(&a0); + n = b0-1.0e0; + if(n < 1) goto S90; + c = 1.0e0; + for(i=1; i<=n; i++) { + b0 -= 1.0e0; + c *= (b0/(a0+b0)); + } + u = log(c)+u; +S90: + z -= u; + b0 -= 1.0e0; + apb = a0+b0; + if(apb > 1.0e0) goto S100; + t = 1.0e0+gam1(&apb); + goto S110; +S100: + u = a0+b0-1.e0; + t = (1.0e0+gam1(&u))/apb; +S110: + brcomp = a0*exp(z)*(1.0e0+gam1(&b0))/t; + return brcomp; +S120: +/* + ALGORITHM FOR B0 .GE. 8 +*/ + u = gamln1(&a0)+algdiv(&a0,&b0); + brcomp = a0*exp(z-u); + return brcomp; +S130: +/* +----------------------------------------------------------------------- + PROCEDURE FOR A .GE. 8 AND B .GE. 8 +----------------------------------------------------------------------- +*/ + if(*a > *b) goto S140; + h = *a/ *b; + x0 = h/(1.0e0+h); + y0 = 1.0e0/(1.0e0+h); + lambda = *a-(*a+*b)**x; + goto S150; +S140: + h = *b/ *a; + x0 = 1.0e0/(1.0e0+h); + y0 = h/(1.0e0+h); + lambda = (*a+*b)**y-*b; +S150: + e = -(lambda/ *a); + if(fabs(e) > 0.6e0) goto S160; + u = rlog1(&e); + goto S170; +S160: + u = e-log(*x/x0); +S170: + e = lambda/ *b; + if(fabs(e) > 0.6e0) goto S180; + v = rlog1(&e); + goto S190; +S180: + v = e-log(*y/y0); +S190: + z = exp(-(*a*u+*b*v)); + brcomp = Const*sqrt(*b*x0)*z*exp(-bcorr(a,b)); + return brcomp; +} /* END */ + +/***=====================================================================***/ +static double bup(double *a,double *b,double *x,double *y,int *n,double *eps) +/* +----------------------------------------------------------------------- + EVALUATION OF IX(A,B) - IX(A+N,B) WHERE N IS A POSITIVE INTEGER. + EPS IS THE TOLERANCE USED. +----------------------------------------------------------------------- +*/ +{ +static int K1 = 1; +static int K2 = 0; +static double bup,ap1,apb,d,l,r,t,w; +static int i,k,kp1,mu,nm1; +/* + .. + .. Executable Statements .. +*/ +/* + OBTAIN THE SCALING FACTOR EXP(-MU) AND + EXP(MU)*(X**A*Y**B/BETA(A,B))/A +*/ + apb = *a+*b; + ap1 = *a+1.0e0; + mu = 0; + d = 1.0e0; + if(*n == 1 || *a < 1.0e0) goto S10; + if(apb < 1.1e0*ap1) goto S10; + mu = fabs(exparg(&K1)); + k = exparg(&K2); + if(k < mu) mu = k; + t = mu; + d = exp(-t); +S10: + bup = brcmp1(&mu,a,b,x,y)/ *a; + if(*n == 1 || bup == 0.0e0) return bup; + nm1 = *n-1; + w = d; +/* + LET K BE THE INDEX OF THE MAXIMUM TERM +*/ + k = 0; + if(*b <= 1.0e0) goto S50; + if(*y > 1.e-4) goto S20; + k = nm1; + goto S30; +S20: + r = (*b-1.0e0)**x/ *y-*a; + if(r < 1.0e0) goto S50; + k = t = nm1; + if(r < t) k = r; +S30: +/* + ADD THE INCREASING TERMS OF THE SERIES +*/ + for(i=1; i<=k; i++) { + l = i-1; + d = (apb+l)/(ap1+l)**x*d; + w += d; + } + if(k == nm1) goto S70; +S50: +/* + ADD THE REMAINING TERMS OF THE SERIES +*/ + kp1 = k+1; + for(i=kp1; i<=nm1; i++) { + l = i-1; + d = (apb+l)/(ap1+l)**x*d; + w += d; + if(d <= *eps*w) goto S70; + } +S70: +/* + TERMINATE THE PROCEDURE +*/ + bup *= w; + return bup; +} /* END */ + +/***=====================================================================***/ +static void cdfbet(int *which,double *p,double *q,double *x,double *y, + double *a,double *b,int *status,double *bound) +/********************************************************************** + + void cdfbet(int *which,double *p,double *q,double *x,double *y, + double *a,double *b,int *status,double *bound) + + Cumulative Distribution Function + BETa Distribution + + + Function + + + Calculates any one parameter of the beta distribution given + values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next four argument + values is to be calculated from the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from X,Y,A and B + iwhich = 2 : Calculate X and Y from P,Q,A and B + iwhich = 3 : Calculate A from P,Q,X,Y and B + iwhich = 4 : Calculate B from P,Q,X,Y and A + + P <--> The integral from 0 to X of the chi-square + distribution. + Input range: [0, 1]. + + Q <--> 1-P. + Input range: [0, 1]. + P + Q = 1.0. + + X <--> Upper limit of integration of beta density. + Input range: [0,1]. + Search range: [0,1] + + Y <--> 1-X. + Input range: [0,1]. + Search range: [0,1] + X + Y = 1.0. + + A <--> The first parameter of the beta density. + Input range: (0, +infinity). + Search range: [1D-300,1D300] + + B <--> The second parameter of the beta density. + Input range: (0, +infinity). + Search range: [1D-300,1D300] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + 4 if X + Y .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Cumulative distribution function (P) is calculated directly by + code associated with the following reference. + + DiDinato, A. R. and Morris, A. H. Algorithm 708: Significant + Digit Computation of the Incomplete Beta Function Ratios. ACM + Trans. Math. Softw. 18 (1993), 360-373. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + + Note + + + The beta density is proportional to + t^(A-1) * (1-t)^(B-1) + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define inf 1.0e300 +#define one 1.0e0 +static int K1 = 1; +static double K2 = 0.0e0; +static double K3 = 1.0e0; +static double K8 = 0.5e0; +static double K9 = 5.0e0; +static double fx,xhi,xlo,cum,ccum,xy,pq; +static unsigned long qhi,qleft,qporq; +static double T4,T5,T6,T7,T10,T11,T12,T13,T14,T15; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q < 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q < 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S150; +/* + X +*/ + if(!(*x < 0.0e0 || *x > 1.0e0)) goto S140; + if(!(*x < 0.0e0)) goto S120; + *bound = 0.0e0; + goto S130; +S120: + *bound = 1.0e0; +S130: + *status = -4; + return; +S150: +S140: + if(*which == 2) goto S190; +/* + Y +*/ + if(!(*y < 0.0e0 || *y > 1.0e0)) goto S180; + if(!(*y < 0.0e0)) goto S160; + *bound = 0.0e0; + goto S170; +S160: + *bound = 1.0e0; +S170: + *status = -5; + return; +S190: +S180: + if(*which == 3) goto S210; +/* + A +*/ + if(!(*a <= 0.0e0)) goto S200; + *bound = 0.0e0; + *status = -6; + return; +S210: +S200: + if(*which == 4) goto S230; +/* + B +*/ + if(!(*b <= 0.0e0)) goto S220; + *bound = 0.0e0; + *status = -7; + return; +S230: +S220: + if(*which == 1) goto S270; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S260; + if(!(pq < 0.0e0)) goto S240; + *bound = 0.0e0; + goto S250; +S240: + *bound = 1.0e0; +S250: + *status = 3; + return; +S270: +S260: + if(*which == 2) goto S310; +/* + X + Y +*/ + xy = *x+*y; + if(!(fabs(xy-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S300; + if(!(xy < 0.0e0)) goto S280; + *bound = 0.0e0; + goto S290; +S280: + *bound = 1.0e0; +S290: + *status = 4; + return; +S310: +S300: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P and Q +*/ + cumbet(x,y,a,b,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating X and Y +*/ + T4 = atol; + T5 = tol; + dstzr(&K2,&K3,&T4,&T5); + if(!qporq) goto S340; + *status = 0; + dzror(status,x,&fx,&xlo,&xhi,&qleft,&qhi); + *y = one-*x; +S320: + if(!(*status == 1)) goto S330; + cumbet(x,y,a,b,&cum,&ccum); + fx = cum-*p; + dzror(status,x,&fx,&xlo,&xhi,&qleft,&qhi); + *y = one-*x; + goto S320; +S330: + goto S370; +S340: + *status = 0; + dzror(status,y,&fx,&xlo,&xhi,&qleft,&qhi); + *x = one-*y; +S350: + if(!(*status == 1)) goto S360; + cumbet(x,y,a,b,&cum,&ccum); + fx = ccum-*q; + dzror(status,y,&fx,&xlo,&xhi,&qleft,&qhi); + *x = one-*y; + goto S350; +S370: +S360: + if(!(*status == -1)) goto S400; + if(!qleft) goto S380; + *status = 1; + *bound = 0.0e0; + goto S390; +S380: + *status = 2; + *bound = 1.0e0; +S400: +S390: + ; + } + else if(3 == *which) { +/* + Computing A +*/ + *a = 5.0e0; + T6 = zero; + T7 = inf; + T10 = atol; + T11 = tol; + dstinv(&T6,&T7,&K8,&K8,&K9,&T10,&T11); + *status = 0; + dinvr(status,a,&fx,&qleft,&qhi); +S410: + if(!(*status == 1)) goto S440; + cumbet(x,y,a,b,&cum,&ccum); + if(!qporq) goto S420; + fx = cum-*p; + goto S430; +S420: + fx = ccum-*q; +S430: + dinvr(status,a,&fx,&qleft,&qhi); + goto S410; +S440: + if(!(*status == -1)) goto S470; + if(!qleft) goto S450; + *status = 1; + *bound = zero; + goto S460; +S450: + *status = 2; + *bound = inf; +S470: +S460: + ; + } + else if(4 == *which) { +/* + Computing B +*/ + *b = 5.0e0; + T12 = zero; + T13 = inf; + T14 = atol; + T15 = tol; + dstinv(&T12,&T13,&K8,&K8,&K9,&T14,&T15); + *status = 0; + dinvr(status,b,&fx,&qleft,&qhi); +S480: + if(!(*status == 1)) goto S510; + cumbet(x,y,a,b,&cum,&ccum); + if(!qporq) goto S490; + fx = cum-*p; + goto S500; +S490: + fx = ccum-*q; +S500: + dinvr(status,b,&fx,&qleft,&qhi); + goto S480; +S510: + if(!(*status == -1)) goto S540; + if(!qleft) goto S520; + *status = 1; + *bound = zero; + goto S530; +S520: + *status = 2; + *bound = inf; +S530: + ; + } +S540: + return; +#undef tol +#undef atol +#undef zero +#undef inf +#undef one +} /* END */ + +/***=====================================================================***/ +static void cdfbin(int *which,double *p,double *q,double *s,double *xn, + double *pr,double *ompr,int *status,double *bound) +/********************************************************************** + + void cdfbin(int *which,double *p,double *q,double *s,double *xn, + double *pr,double *ompr,int *status,double *bound) + + Cumulative Distribution Function + BINomial distribution + + + Function + + + Calculates any one parameter of the binomial + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next four argument + values is to be calculated from the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from S,XN,PR and OMPR + iwhich = 2 : Calculate S from P,Q,XN,PR and OMPR + iwhich = 3 : Calculate XN from P,Q,S,PR and OMPR + iwhich = 4 : Calculate PR and OMPR from P,Q,S and XN + + P <--> The cumulation from 0 to S of the binomial distribution. + (Probablility of S or fewer successes in XN trials each + with probability of success PR.) + Input range: [0,1]. + + Q <--> 1-P. + Input range: [0, 1]. + P + Q = 1.0. + + S <--> The number of successes observed. + Input range: [0, XN] + Search range: [0, XN] + + XN <--> The number of binomial trials. + Input range: (0, +infinity). + Search range: [1E-300, 1E300] + + PR <--> The probability of success in each binomial trial. + Input range: [0,1]. + Search range: [0,1] + + OMPR <--> 1-PR + Input range: [0,1]. + Search range: [0,1] + PR + OMPR = 1.0 + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + 4 if PR + OMPR .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.5.24 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the binomial + distribution to the cumulative incomplete beta distribution. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + +**********************************************************************/ +{ +#define atol (1.0e-50) +#define tol (1.0e-8) +#define zero (1.0e-300) +#define inf 1.0e300 +#define one 1.0e0 +static int K1 = 1; +static double K2 = 0.0e0; +static double K3 = 0.5e0; +static double K4 = 5.0e0; +static double K11 = 1.0e0; +static double fx,xhi,xlo,cum,ccum,pq,prompr; +static unsigned long qhi,qleft,qporq; +static double T5,T6,T7,T8,T9,T10,T12,T13; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 && *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q < 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q < 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 3) goto S130; +/* + XN +*/ + if(!(*xn <= 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -5; + return; +S130: +S120: + if(*which == 2) goto S170; +/* + S +*/ + if(!(*s < 0.0e0 || *which != 3 && *s > *xn)) goto S160; + if(!(*s < 0.0e0)) goto S140; + *bound = 0.0e0; + goto S150; +S140: + *bound = *xn; +S150: + *status = -4; + return; +S170: +S160: + if(*which == 4) goto S210; +/* + PR +*/ + if(!(*pr < 0.0e0 || *pr > 1.0e0)) goto S200; + if(!(*pr < 0.0e0)) goto S180; + *bound = 0.0e0; + goto S190; +S180: + *bound = 1.0e0; +S190: + *status = -6; + return; +S210: +S200: + if(*which == 4) goto S250; +/* + OMPR +*/ + if(!(*ompr < 0.0e0 || *ompr > 1.0e0)) goto S240; + if(!(*ompr < 0.0e0)) goto S220; + *bound = 0.0e0; + goto S230; +S220: + *bound = 1.0e0; +S230: + *status = -7; + return; +S250: +S240: + if(*which == 1) goto S290; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S280; + if(!(pq < 0.0e0)) goto S260; + *bound = 0.0e0; + goto S270; +S260: + *bound = 1.0e0; +S270: + *status = 3; + return; +S290: +S280: + if(*which == 4) goto S330; +/* + PR + OMPR +*/ + prompr = *pr+*ompr; + if(!(fabs(prompr-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S320; + if(!(prompr < 0.0e0)) goto S300; + *bound = 0.0e0; + goto S310; +S300: + *bound = 1.0e0; +S310: + *status = 4; + return; +S330: +S320: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + cumbin(s,xn,pr,ompr,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating S +*/ + *s = 5.0e0; + T5 = atol; + T6 = tol; + dstinv(&K2,xn,&K3,&K3,&K4,&T5,&T6); + *status = 0; + dinvr(status,s,&fx,&qleft,&qhi); +S340: + if(!(*status == 1)) goto S370; + cumbin(s,xn,pr,ompr,&cum,&ccum); + if(!qporq) goto S350; + fx = cum-*p; + goto S360; +S350: + fx = ccum-*q; +S360: + dinvr(status,s,&fx,&qleft,&qhi); + goto S340; +S370: + if(!(*status == -1)) goto S400; + if(!qleft) goto S380; + *status = 1; + *bound = 0.0e0; + goto S390; +S380: + *status = 2; + *bound = *xn; +S400: +S390: + ; + } + else if(3 == *which) { +/* + Calculating XN +*/ + *xn = 5.0e0; + T7 = zero; + T8 = inf; + T9 = atol; + T10 = tol; + dstinv(&T7,&T8,&K3,&K3,&K4,&T9,&T10); + *status = 0; + dinvr(status,xn,&fx,&qleft,&qhi); +S410: + if(!(*status == 1)) goto S440; + cumbin(s,xn,pr,ompr,&cum,&ccum); + if(!qporq) goto S420; + fx = cum-*p; + goto S430; +S420: + fx = ccum-*q; +S430: + dinvr(status,xn,&fx,&qleft,&qhi); + goto S410; +S440: + if(!(*status == -1)) goto S470; + if(!qleft) goto S450; + *status = 1; + *bound = zero; + goto S460; +S450: + *status = 2; + *bound = inf; +S470: +S460: + ; + } + else if(4 == *which) { +/* + Calculating PR and OMPR +*/ + T12 = atol; + T13 = tol; + dstzr(&K2,&K11,&T12,&T13); + if(!qporq) goto S500; + *status = 0; + dzror(status,pr,&fx,&xlo,&xhi,&qleft,&qhi); + *ompr = one-*pr; +S480: + if(!(*status == 1)) goto S490; + cumbin(s,xn,pr,ompr,&cum,&ccum); + fx = cum-*p; + dzror(status,pr,&fx,&xlo,&xhi,&qleft,&qhi); + *ompr = one-*pr; + goto S480; +S490: + goto S530; +S500: + *status = 0; + dzror(status,ompr,&fx,&xlo,&xhi,&qleft,&qhi); + *pr = one-*ompr; +S510: + if(!(*status == 1)) goto S520; + cumbin(s,xn,pr,ompr,&cum,&ccum); + fx = ccum-*q; + dzror(status,ompr,&fx,&xlo,&xhi,&qleft,&qhi); + *pr = one-*ompr; + goto S510; +S530: +S520: + if(!(*status == -1)) goto S560; + if(!qleft) goto S540; + *status = 1; + *bound = 0.0e0; + goto S550; +S540: + *status = 2; + *bound = 1.0e0; +S550: + ; + } +S560: + return; +#undef atol +#undef tol +#undef zero +#undef inf +#undef one +} /* END */ + +/***=====================================================================***/ +static void cdfchi(int *which,double *p,double *q,double *x,double *df, + int *status,double *bound) +/********************************************************************** + + void cdfchi(int *which,double *p,double *q,double *x,double *df, + int *status,double *bound) + + Cumulative Distribution Function + CHI-Square distribution + + + Function + + + Calculates any one parameter of the chi-square + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next three argument + values is to be calculated from the others. + Legal range: 1..3 + iwhich = 1 : Calculate P and Q from X and DF + iwhich = 2 : Calculate X from P,Q and DF + iwhich = 3 : Calculate DF from P,Q and X + + P <--> The integral from 0 to X of the chi-square + distribution. + Input range: [0, 1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + X <--> Upper limit of integration of the non-central + chi-square distribution. + Input range: [0, +infinity). + Search range: [0,1E300] + + DF <--> Degrees of freedom of the + chi-square distribution. + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + 10 indicates error returned from cumgam. See + references in cdfgam + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.4.19 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the chisqure + distribution to the incomplete distribution. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define inf 1.0e300 +static int K1 = 1; +static double K2 = 0.0e0; +static double K4 = 0.5e0; +static double K5 = 5.0e0; +static double fx,cum,ccum,pq,porq; +static unsigned long qhi,qleft,qporq; +static double T3,T6,T7,T8,T9,T10,T11; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 3)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 3.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S130; +/* + X +*/ + if(!(*x < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -4; + return; +S130: +S120: + if(*which == 3) goto S150; +/* + DF +*/ + if(!(*df <= 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -5; + return; +S150: +S140: + if(*which == 1) goto S190; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S180; + if(!(pq < 0.0e0)) goto S160; + *bound = 0.0e0; + goto S170; +S160: + *bound = 1.0e0; +S170: + *status = 3; + return; +S190: +S180: + if(*which == 1) goto S220; +/* + Select the minimum of P or Q +*/ + qporq = *p <= *q; + if(!qporq) goto S200; + porq = *p; + goto S210; +S200: + porq = *q; +S220: +S210: +/* + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P and Q +*/ + *status = 0; + cumchi(x,df,p,q); + if(porq > 1.5e0) { + *status = 10; + return; + } + } + else if(2 == *which) { +/* + Calculating X +*/ + *x = 5.0e0; + T3 = inf; + T6 = atol; + T7 = tol; + dstinv(&K2,&T3,&K4,&K4,&K5,&T6,&T7); + *status = 0; + dinvr(status,x,&fx,&qleft,&qhi); +S230: + if(!(*status == 1)) goto S270; + cumchi(x,df,&cum,&ccum); + if(!qporq) goto S240; + fx = cum-*p; + goto S250; +S240: + fx = ccum-*q; +S250: + if(!(fx+porq > 1.5e0)) goto S260; + *status = 10; + return; +S260: + dinvr(status,x,&fx,&qleft,&qhi); + goto S230; +S270: + if(!(*status == -1)) goto S300; + if(!qleft) goto S280; + *status = 1; + *bound = 0.0e0; + goto S290; +S280: + *status = 2; + *bound = inf; +S300: +S290: + ; + } + else if(3 == *which) { +/* + Calculating DF +*/ + *df = 5.0e0; + T8 = zero; + T9 = inf; + T10 = atol; + T11 = tol; + dstinv(&T8,&T9,&K4,&K4,&K5,&T10,&T11); + *status = 0; + dinvr(status,df,&fx,&qleft,&qhi); +S310: + if(!(*status == 1)) goto S350; + cumchi(x,df,&cum,&ccum); + if(!qporq) goto S320; + fx = cum-*p; + goto S330; +S320: + fx = ccum-*q; +S330: + if(!(fx+porq > 1.5e0)) goto S340; + *status = 10; + return; +S340: + dinvr(status,df,&fx,&qleft,&qhi); + goto S310; +S350: + if(!(*status == -1)) goto S380; + if(!qleft) goto S360; + *status = 1; + *bound = zero; + goto S370; +S360: + *status = 2; + *bound = inf; +S370: + ; + } +S380: + return; +#undef tol +#undef atol +#undef zero +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdfchn(int *which,double *p,double *q,double *x,double *df, + double *pnonc,int *status,double *bound) +/********************************************************************** + + void cdfchn(int *which,double *p,double *q,double *x,double *df, + double *pnonc,int *status,double *bound) + + Cumulative Distribution Function + Non-central Chi-Square + + + Function + + + Calculates any one parameter of the non-central chi-square + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next three argument + values is to be calculated from the others. + Input range: 1..4 + iwhich = 1 : Calculate P and Q from X and DF + iwhich = 2 : Calculate X from P,DF and PNONC + iwhich = 3 : Calculate DF from P,X and PNONC + iwhich = 3 : Calculate PNONC from P,X and DF + + P <--> The integral from 0 to X of the non-central chi-square + distribution. + Input range: [0, 1-1E-16). + + Q <--> 1-P. + Q is not used by this subroutine and is only included + for similarity with other cdf* routines. + + X <--> Upper limit of integration of the non-central + chi-square distribution. + Input range: [0, +infinity). + Search range: [0,1E300] + + DF <--> Degrees of freedom of the non-central + chi-square distribution. + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + PNONC <--> Non-centrality parameter of the non-central + chi-square distribution. + Input range: [0, +infinity). + Search range: [0,1E4] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.4.25 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to compute the cumulative + distribution function. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + + WARNING + + The computation time required for this routine is proportional + to the noncentrality parameter (PNONC). Very large values of + this parameter can consume immense computer resources. This is + why the search range is bounded by 10,000. + +**********************************************************************/ +{ +#define tent4 1.0e4 +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define one (1.0e0-1.0e-16) +#define inf 1.0e300 +static double K1 = 0.0e0; +static double K3 = 0.5e0; +static double K4 = 5.0e0; +static double fx,cum,ccum; +static unsigned long qhi,qleft; +static double T2,T5,T6,T7,T8,T9,T10,T11,T12,T13; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > one)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = one; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 2) goto S90; +/* + X +*/ + if(!(*x < 0.0e0)) goto S80; + *bound = 0.0e0; + *status = -4; + return; +S90: +S80: + if(*which == 3) goto S110; +/* + DF +*/ + if(!(*df <= 0.0e0)) goto S100; + *bound = 0.0e0; + *status = -5; + return; +S110: +S100: + if(*which == 4) goto S130; +/* + PNONC +*/ + if(!(*pnonc < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -6; + return; +S130: +S120: +/* + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P and Q +*/ + cumchn(x,df,pnonc,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating X +*/ + *x = 5.0e0; + T2 = inf; + T5 = atol; + T6 = tol; + dstinv(&K1,&T2,&K3,&K3,&K4,&T5,&T6); + *status = 0; + dinvr(status,x,&fx,&qleft,&qhi); +S140: + if(!(*status == 1)) goto S150; + cumchn(x,df,pnonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,x,&fx,&qleft,&qhi); + goto S140; +S150: + if(!(*status == -1)) goto S180; + if(!qleft) goto S160; + *status = 1; + *bound = 0.0e0; + goto S170; +S160: + *status = 2; + *bound = inf; +S180: +S170: + ; + } + else if(3 == *which) { +/* + Calculating DF +*/ + *df = 5.0e0; + T7 = zero; + T8 = inf; + T9 = atol; + T10 = tol; + dstinv(&T7,&T8,&K3,&K3,&K4,&T9,&T10); + *status = 0; + dinvr(status,df,&fx,&qleft,&qhi); +S190: + if(!(*status == 1)) goto S200; + cumchn(x,df,pnonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,df,&fx,&qleft,&qhi); + goto S190; +S200: + if(!(*status == -1)) goto S230; + if(!qleft) goto S210; + *status = 1; + *bound = zero; + goto S220; +S210: + *status = 2; + *bound = inf; +S230: +S220: + ; + } + else if(4 == *which) { +/* + Calculating PNONC +*/ + *pnonc = 5.0e0; + T11 = tent4; + T12 = atol; + T13 = tol; + dstinv(&K1,&T11,&K3,&K3,&K4,&T12,&T13); + *status = 0; + dinvr(status,pnonc,&fx,&qleft,&qhi); +S240: + if(!(*status == 1)) goto S250; + cumchn(x,df,pnonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,pnonc,&fx,&qleft,&qhi); + goto S240; +S250: + if(!(*status == -1)) goto S280; + if(!qleft) goto S260; + *status = 1; + *bound = zero; + goto S270; +S260: + *status = 2; + *bound = tent4; +S270: + ; + } +S280: + return; +#undef tent4 +#undef tol +#undef atol +#undef zero +#undef one +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdff(int *which,double *p,double *q,double *f,double *dfn, + double *dfd,int *status,double *bound) +/********************************************************************** + + void cdff(int *which,double *p,double *q,double *f,double *dfn, + double *dfd,int *status,double *bound) + + Cumulative Distribution Function + F distribution + + + Function + + + Calculates any one parameter of the F distribution + given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next four argument + values is to be calculated from the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from F,DFN and DFD + iwhich = 2 : Calculate F from P,Q,DFN and DFD + iwhich = 3 : Calculate DFN from P,Q,F and DFD + iwhich = 4 : Calculate DFD from P,Q,F and DFN + + P <--> The integral from 0 to F of the f-density. + Input range: [0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + F <--> Upper limit of integration of the f-density. + Input range: [0, +infinity). + Search range: [0,1E300] + + DFN < --> Degrees of freedom of the numerator sum of squares. + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + DFD < --> Degrees of freedom of the denominator sum of squares. + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.6.2 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the computation + of the cumulative distribution function for the F variate to + that of an incomplete beta. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + WARNING + + The value of the cumulative F distribution is not necessarily + monotone in either degrees of freedom. There thus may be two + values that provide a given CDF value. This routine assumes + monotonicity and will find an arbitrary one of the two values. + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define inf 1.0e300 +static int K1 = 1; +static double K2 = 0.0e0; +static double K4 = 0.5e0; +static double K5 = 5.0e0; +static double pq,fx,cum,ccum; +static unsigned long qhi,qleft,qporq; +static double T3,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S130; +/* + F +*/ + if(!(*f < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -4; + return; +S130: +S120: + if(*which == 3) goto S150; +/* + DFN +*/ + if(!(*dfn <= 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -5; + return; +S150: +S140: + if(*which == 4) goto S170; +/* + DFD +*/ + if(!(*dfd <= 0.0e0)) goto S160; + *bound = 0.0e0; + *status = -6; + return; +S170: +S160: + if(*which == 1) goto S210; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S200; + if(!(pq < 0.0e0)) goto S180; + *bound = 0.0e0; + goto S190; +S180: + *bound = 1.0e0; +S190: + *status = 3; + return; +S210: +S200: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + cumf(f,dfn,dfd,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating F +*/ + *f = 5.0e0; + T3 = inf; + T6 = atol; + T7 = tol; + dstinv(&K2,&T3,&K4,&K4,&K5,&T6,&T7); + *status = 0; + dinvr(status,f,&fx,&qleft,&qhi); +S220: + if(!(*status == 1)) goto S250; + cumf(f,dfn,dfd,&cum,&ccum); + if(!qporq) goto S230; + fx = cum-*p; + goto S240; +S230: + fx = ccum-*q; +S240: + dinvr(status,f,&fx,&qleft,&qhi); + goto S220; +S250: + if(!(*status == -1)) goto S280; + if(!qleft) goto S260; + *status = 1; + *bound = 0.0e0; + goto S270; +S260: + *status = 2; + *bound = inf; +S280: +S270: + ; + } + else if(3 == *which) { +/* + Calculating DFN +*/ + *dfn = 5.0e0; + T8 = zero; + T9 = inf; + T10 = atol; + T11 = tol; + dstinv(&T8,&T9,&K4,&K4,&K5,&T10,&T11); + *status = 0; + dinvr(status,dfn,&fx,&qleft,&qhi); +S290: + if(!(*status == 1)) goto S320; + cumf(f,dfn,dfd,&cum,&ccum); + if(!qporq) goto S300; + fx = cum-*p; + goto S310; +S300: + fx = ccum-*q; +S310: + dinvr(status,dfn,&fx,&qleft,&qhi); + goto S290; +S320: + if(!(*status == -1)) goto S350; + if(!qleft) goto S330; + *status = 1; + *bound = zero; + goto S340; +S330: + *status = 2; + *bound = inf; +S350: +S340: + ; + } + else if(4 == *which) { +/* + Calculating DFD +*/ + *dfd = 5.0e0; + T12 = zero; + T13 = inf; + T14 = atol; + T15 = tol; + dstinv(&T12,&T13,&K4,&K4,&K5,&T14,&T15); + *status = 0; + dinvr(status,dfd,&fx,&qleft,&qhi); +S360: + if(!(*status == 1)) goto S390; + cumf(f,dfn,dfd,&cum,&ccum); + if(!qporq) goto S370; + fx = cum-*p; + goto S380; +S370: + fx = ccum-*q; +S380: + dinvr(status,dfd,&fx,&qleft,&qhi); + goto S360; +S390: + if(!(*status == -1)) goto S420; + if(!qleft) goto S400; + *status = 1; + *bound = zero; + goto S410; +S400: + *status = 2; + *bound = inf; +S410: + ; + } +S420: + return; +#undef tol +#undef atol +#undef zero +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdffnc(int *which,double *p,double *q,double *f,double *dfn, + double *dfd,double *phonc,int *status,double *bound) +/********************************************************************** + + void cdffnc(int *which,double *p,double *q,double *f,double *dfn, + double *dfd,double *phonc,int *status,double *bound) + + Cumulative Distribution Function + Non-central F distribution + + + Function + + + Calculates any one parameter of the Non-central F + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next five argument + values is to be calculated from the others. + Legal range: 1..5 + iwhich = 1 : Calculate P and Q from F,DFN,DFD and PNONC + iwhich = 2 : Calculate F from P,Q,DFN,DFD and PNONC + iwhich = 3 : Calculate DFN from P,Q,F,DFD and PNONC + iwhich = 4 : Calculate DFD from P,Q,F,DFN and PNONC + iwhich = 5 : Calculate PNONC from P,Q,F,DFN and DFD + + P <--> The integral from 0 to F of the non-central f-density. + Input range: [0,1-1E-16). + + Q <--> 1-P. + Q is not used by this subroutine and is only included + for similarity with other cdf* routines. + + F <--> Upper limit of integration of the non-central f-density. + Input range: [0, +infinity). + Search range: [0,1E300] + + DFN < --> Degrees of freedom of the numerator sum of squares. + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + DFD < --> Degrees of freedom of the denominator sum of squares. + Must be in range: (0, +infinity). + Input range: (0, +infinity). + Search range: [ 1E-300, 1E300] + + PNONC <-> The non-centrality parameter + Input range: [0,infinity) + Search range: [0,1E4] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.6.20 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to compute the cumulative + distribution function. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + WARNING + + The computation time required for this routine is proportional + to the noncentrality parameter (PNONC). Very large values of + this parameter can consume immense computer resources. This is + why the search range is bounded by 10,000. + + WARNING + + The value of the cumulative noncentral F distribution is not + necessarily monotone in either degrees of freedom. There thus + may be two values that provide a given CDF value. This routine + assumes monotonicity and will find an arbitrary one of the two + values. + +**********************************************************************/ +{ +#define tent4 1.0e4 +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define one (1.0e0-1.0e-16) +#define inf 1.0e300 +static double K1 = 0.0e0; +static double K3 = 0.5e0; +static double K4 = 5.0e0; +static double fx,cum,ccum; +static unsigned long qhi,qleft; +static double T2,T5,T6,T7,T8,T9,T10,T11,T12,T13,T14,T15,T16,T17; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 5)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 5.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > one)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = one; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 2) goto S90; +/* + F +*/ + if(!(*f < 0.0e0)) goto S80; + *bound = 0.0e0; + *status = -4; + return; +S90: +S80: + if(*which == 3) goto S110; +/* + DFN +*/ + if(!(*dfn <= 0.0e0)) goto S100; + *bound = 0.0e0; + *status = -5; + return; +S110: +S100: + if(*which == 4) goto S130; +/* + DFD +*/ + if(!(*dfd <= 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -6; + return; +S130: +S120: + if(*which == 5) goto S150; +/* + PHONC +*/ + if(!(*phonc < 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -7; + return; +S150: +S140: +/* + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + cumfnc(f,dfn,dfd,phonc,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating F +*/ + *f = 5.0e0; + T2 = inf; + T5 = atol; + T6 = tol; + dstinv(&K1,&T2,&K3,&K3,&K4,&T5,&T6); + *status = 0; + dinvr(status,f,&fx,&qleft,&qhi); +S160: + if(!(*status == 1)) goto S170; + cumfnc(f,dfn,dfd,phonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,f,&fx,&qleft,&qhi); + goto S160; +S170: + if(!(*status == -1)) goto S200; + if(!qleft) goto S180; + *status = 1; + *bound = 0.0e0; + goto S190; +S180: + *status = 2; + *bound = inf; +S200: +S190: + ; + } + else if(3 == *which) { +/* + Calculating DFN +*/ + *dfn = 5.0e0; + T7 = zero; + T8 = inf; + T9 = atol; + T10 = tol; + dstinv(&T7,&T8,&K3,&K3,&K4,&T9,&T10); + *status = 0; + dinvr(status,dfn,&fx,&qleft,&qhi); +S210: + if(!(*status == 1)) goto S220; + cumfnc(f,dfn,dfd,phonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,dfn,&fx,&qleft,&qhi); + goto S210; +S220: + if(!(*status == -1)) goto S250; + if(!qleft) goto S230; + *status = 1; + *bound = zero; + goto S240; +S230: + *status = 2; + *bound = inf; +S250: +S240: + ; + } + else if(4 == *which) { +/* + Calculating DFD +*/ + *dfd = 5.0e0; + T11 = zero; + T12 = inf; + T13 = atol; + T14 = tol; + dstinv(&T11,&T12,&K3,&K3,&K4,&T13,&T14); + *status = 0; + dinvr(status,dfd,&fx,&qleft,&qhi); +S260: + if(!(*status == 1)) goto S270; + cumfnc(f,dfn,dfd,phonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,dfd,&fx,&qleft,&qhi); + goto S260; +S270: + if(!(*status == -1)) goto S300; + if(!qleft) goto S280; + *status = 1; + *bound = zero; + goto S290; +S280: + *status = 2; + *bound = inf; +S300: +S290: + ; + } + else if(5 == *which) { +/* + Calculating PHONC +*/ + *phonc = 5.0e0; + T15 = tent4; + T16 = atol; + T17 = tol; + dstinv(&K1,&T15,&K3,&K3,&K4,&T16,&T17); + *status = 0; + dinvr(status,phonc,&fx,&qleft,&qhi); +S310: + if(!(*status == 1)) goto S320; + cumfnc(f,dfn,dfd,phonc,&cum,&ccum); + fx = cum-*p; + dinvr(status,phonc,&fx,&qleft,&qhi); + goto S310; +S320: + if(!(*status == -1)) goto S350; + if(!qleft) goto S330; + *status = 1; + *bound = 0.0e0; + goto S340; +S330: + *status = 2; + *bound = tent4; +S340: + ; + } +S350: + return; +#undef tent4 +#undef tol +#undef atol +#undef zero +#undef one +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdfgam(int *which,double *p,double *q,double *x,double *shape, + double *scale,int *status,double *bound) +/********************************************************************** + + void cdfgam(int *which,double *p,double *q,double *x,double *shape, + double *scale,int *status,double *bound) + + Cumulative Distribution Function + GAMma Distribution + + + Function + + + Calculates any one parameter of the gamma + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next four argument + values is to be calculated from the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from X,SHAPE and SCALE + iwhich = 2 : Calculate X from P,Q,SHAPE and SCALE + iwhich = 3 : Calculate SHAPE from P,Q,X and SCALE + iwhich = 4 : Calculate SCALE from P,Q,X and SHAPE + + P <--> The integral from 0 to X of the gamma density. + Input range: [0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + X <--> The upper limit of integration of the gamma density. + Input range: [0, +infinity). + Search range: [0,1E300] + + SHAPE <--> The shape parameter of the gamma density. + Input range: (0, +infinity). + Search range: [1E-300,1E300] + + SCALE <--> The scale parameter of the gamma density. + Input range: (0, +infinity). + Search range: (1E-300,1E300] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + 10 if the gamma or inverse gamma routine cannot + compute the answer. Usually happens only for + X and SHAPE very large (gt 1E10 or more) + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Cumulative distribution function (P) is calculated directly by + the code associated with: + + DiDinato, A. R. and Morris, A. H. Computation of the incomplete + gamma function ratios and their inverse. ACM Trans. Math. + Softw. 12 (1986), 377-393. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + + + Note + + + + The gamma density is proportional to + T**(SHAPE - 1) * EXP(- SCALE * T) + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define inf 1.0e300 +static int K1 = 1; +static double K5 = 0.5e0; +static double K6 = 5.0e0; +static double xx,fx,xscale,cum,ccum,pq,porq; +static int ierr; +static unsigned long qhi,qleft,qporq; +static double T2,T3,T4,T7,T8,T9; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S130; +/* + X +*/ + if(!(*x < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -4; + return; +S130: +S120: + if(*which == 3) goto S150; +/* + SHAPE +*/ + if(!(*shape <= 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -5; + return; +S150: +S140: + if(*which == 4) goto S170; +/* + SCALE +*/ + if(!(*scale <= 0.0e0)) goto S160; + *bound = 0.0e0; + *status = -6; + return; +S170: +S160: + if(*which == 1) goto S210; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S200; + if(!(pq < 0.0e0)) goto S180; + *bound = 0.0e0; + goto S190; +S180: + *bound = 1.0e0; +S190: + *status = 3; + return; +S210: +S200: + if(*which == 1) goto S240; +/* + Select the minimum of P or Q +*/ + qporq = *p <= *q; + if(!qporq) goto S220; + porq = *p; + goto S230; +S220: + porq = *q; +S240: +S230: +/* + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + *status = 0; + xscale = *x**scale; + cumgam(&xscale,shape,p,q); + if(porq > 1.5e0) *status = 10; + } + else if(2 == *which) { +/* + Computing X +*/ + T2 = -1.0e0; + gaminv(shape,&xx,&T2,p,q,&ierr); + if(ierr < 0.0e0) { + *status = 10; + return; + } + else { + *x = xx/ *scale; + *status = 0; + } + } + else if(3 == *which) { +/* + Computing SHAPE +*/ + *shape = 5.0e0; + xscale = *x**scale; + T3 = zero; + T4 = inf; + T7 = atol; + T8 = tol; + dstinv(&T3,&T4,&K5,&K5,&K6,&T7,&T8); + *status = 0; + dinvr(status,shape,&fx,&qleft,&qhi); +S250: + if(!(*status == 1)) goto S290; + cumgam(&xscale,shape,&cum,&ccum); + if(!qporq) goto S260; + fx = cum-*p; + goto S270; +S260: + fx = ccum-*q; +S270: + if(!(qporq && cum > 1.5e0 || !qporq && ccum > 1.5e0)) goto S280; + *status = 10; + return; +S280: + dinvr(status,shape,&fx,&qleft,&qhi); + goto S250; +S290: + if(!(*status == -1)) goto S320; + if(!qleft) goto S300; + *status = 1; + *bound = zero; + goto S310; +S300: + *status = 2; + *bound = inf; +S320: +S310: + ; + } + else if(4 == *which) { +/* + Computing SCALE +*/ + T9 = -1.0e0; + gaminv(shape,&xx,&T9,p,q,&ierr); + if(ierr < 0.0e0) { + *status = 10; + return; + } + else { + *scale = xx/ *x; + *status = 0; + } + } + return; +#undef tol +#undef atol +#undef zero +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdfnbn(int *which,double *p,double *q,double *s,double *xn, + double *pr,double *ompr,int *status,double *bound) +/********************************************************************** + + void cdfnbn(int *which,double *p,double *q,double *s,double *xn, + double *pr,double *ompr,int *status,double *bound) + + Cumulative Distribution Function + Negative BiNomial distribution + + + Function + + + Calculates any one parameter of the negative binomial + distribution given values for the others. + + The cumulative negative binomial distribution returns the + probability that there will be F or fewer failures before the + XNth success in binomial trials each of which has probability of + success PR. + + The individual term of the negative binomial is the probability of + S failures before XN successes and is + Choose( S, XN+S-1 ) * PR^(XN) * (1-PR)^S + + + Arguments + + + WHICH --> Integer indicating which of the next four argument + values is to be calculated from the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from S,XN,PR and OMPR + iwhich = 2 : Calculate S from P,Q,XN,PR and OMPR + iwhich = 3 : Calculate XN from P,Q,S,PR and OMPR + iwhich = 4 : Calculate PR and OMPR from P,Q,S and XN + + P <--> The cumulation from 0 to S of the negative + binomial distribution. + Input range: [0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + S <--> The upper limit of cumulation of the binomial distribution. + There are F or fewer failures before the XNth success. + Input range: [0, +infinity). + Search range: [0, 1E300] + + XN <--> The number of successes. + Input range: [0, +infinity). + Search range: [0, 1E300] + + PR <--> The probability of success in each binomial trial. + Input range: [0,1]. + Search range: [0,1]. + + OMPR <--> 1-PR + Input range: [0,1]. + Search range: [0,1] + PR + OMPR = 1.0 + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + 4 if PR + OMPR .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.5.26 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce calculation of + the cumulative distribution function to that of an incomplete + beta. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define inf 1.0e300 +#define one 1.0e0 +static int K1 = 1; +static double K2 = 0.0e0; +static double K4 = 0.5e0; +static double K5 = 5.0e0; +static double K11 = 1.0e0; +static double fx,xhi,xlo,pq,prompr,cum,ccum; +static unsigned long qhi,qleft,qporq; +static double T3,T6,T7,T8,T9,T10,T12,T13; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S130; +/* + S +*/ + if(!(*s < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -4; + return; +S130: +S120: + if(*which == 3) goto S150; +/* + XN +*/ + if(!(*xn < 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -5; + return; +S150: +S140: + if(*which == 4) goto S190; +/* + PR +*/ + if(!(*pr < 0.0e0 || *pr > 1.0e0)) goto S180; + if(!(*pr < 0.0e0)) goto S160; + *bound = 0.0e0; + goto S170; +S160: + *bound = 1.0e0; +S170: + *status = -6; + return; +S190: +S180: + if(*which == 4) goto S230; +/* + OMPR +*/ + if(!(*ompr < 0.0e0 || *ompr > 1.0e0)) goto S220; + if(!(*ompr < 0.0e0)) goto S200; + *bound = 0.0e0; + goto S210; +S200: + *bound = 1.0e0; +S210: + *status = -7; + return; +S230: +S220: + if(*which == 1) goto S270; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S260; + if(!(pq < 0.0e0)) goto S240; + *bound = 0.0e0; + goto S250; +S240: + *bound = 1.0e0; +S250: + *status = 3; + return; +S270: +S260: + if(*which == 4) goto S310; +/* + PR + OMPR +*/ + prompr = *pr+*ompr; + if(!(fabs(prompr-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S300; + if(!(prompr < 0.0e0)) goto S280; + *bound = 0.0e0; + goto S290; +S280: + *bound = 1.0e0; +S290: + *status = 4; + return; +S310: +S300: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + cumnbn(s,xn,pr,ompr,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating S +*/ + *s = 5.0e0; + T3 = inf; + T6 = atol; + T7 = tol; + dstinv(&K2,&T3,&K4,&K4,&K5,&T6,&T7); + *status = 0; + dinvr(status,s,&fx,&qleft,&qhi); +S320: + if(!(*status == 1)) goto S350; + cumnbn(s,xn,pr,ompr,&cum,&ccum); + if(!qporq) goto S330; + fx = cum-*p; + goto S340; +S330: + fx = ccum-*q; +S340: + dinvr(status,s,&fx,&qleft,&qhi); + goto S320; +S350: + if(!(*status == -1)) goto S380; + if(!qleft) goto S360; + *status = 1; + *bound = 0.0e0; + goto S370; +S360: + *status = 2; + *bound = inf; +S380: +S370: + ; + } + else if(3 == *which) { +/* + Calculating XN +*/ + *xn = 5.0e0; + T8 = inf; + T9 = atol; + T10 = tol; + dstinv(&K2,&T8,&K4,&K4,&K5,&T9,&T10); + *status = 0; + dinvr(status,xn,&fx,&qleft,&qhi); +S390: + if(!(*status == 1)) goto S420; + cumnbn(s,xn,pr,ompr,&cum,&ccum); + if(!qporq) goto S400; + fx = cum-*p; + goto S410; +S400: + fx = ccum-*q; +S410: + dinvr(status,xn,&fx,&qleft,&qhi); + goto S390; +S420: + if(!(*status == -1)) goto S450; + if(!qleft) goto S430; + *status = 1; + *bound = 0.0e0; + goto S440; +S430: + *status = 2; + *bound = inf; +S450: +S440: + ; + } + else if(4 == *which) { +/* + Calculating PR and OMPR +*/ + T12 = atol; + T13 = tol; + dstzr(&K2,&K11,&T12,&T13); + if(!qporq) goto S480; + *status = 0; + dzror(status,pr,&fx,&xlo,&xhi,&qleft,&qhi); + *ompr = one-*pr; +S460: + if(!(*status == 1)) goto S470; + cumnbn(s,xn,pr,ompr,&cum,&ccum); + fx = cum-*p; + dzror(status,pr,&fx,&xlo,&xhi,&qleft,&qhi); + *ompr = one-*pr; + goto S460; +S470: + goto S510; +S480: + *status = 0; + dzror(status,ompr,&fx,&xlo,&xhi,&qleft,&qhi); + *pr = one-*ompr; +S490: + if(!(*status == 1)) goto S500; + cumnbn(s,xn,pr,ompr,&cum,&ccum); + fx = ccum-*q; + dzror(status,ompr,&fx,&xlo,&xhi,&qleft,&qhi); + *pr = one-*ompr; + goto S490; +S510: +S500: + if(!(*status == -1)) goto S540; + if(!qleft) goto S520; + *status = 1; + *bound = 0.0e0; + goto S530; +S520: + *status = 2; + *bound = 1.0e0; +S530: + ; + } +S540: + return; +#undef tol +#undef atol +#undef inf +#undef one +} /* END */ + +/***=====================================================================***/ +static void cdfnor(int *which,double *p,double *q,double *x,double *mean, + double *sd,int *status,double *bound) +/********************************************************************** + + void cdfnor(int *which,double *p,double *q,double *x,double *mean, + double *sd,int *status,double *bound) + + Cumulative Distribution Function + NORmal distribution + + + Function + + + Calculates any one parameter of the normal + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which of the next parameter + values is to be calculated using values of the others. + Legal range: 1..4 + iwhich = 1 : Calculate P and Q from X,MEAN and SD + iwhich = 2 : Calculate X from P,Q,MEAN and SD + iwhich = 3 : Calculate MEAN from P,Q,X and SD + iwhich = 4 : Calculate SD from P,Q,X and MEAN + + P <--> The integral from -infinity to X of the normal density. + Input range: (0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + X < --> Upper limit of integration of the normal-density. + Input range: ( -infinity, +infinity) + + MEAN <--> The mean of the normal density. + Input range: (-infinity, +infinity) + + SD <--> Standard Deviation of the normal density. + Input range: (0, +infinity). + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + + + A slightly modified version of ANORM from + + Cody, W.D. (1993). "ALGORITHM 715: SPECFUN - A Portabel FORTRAN + Package of Special Function Routines and Test Drivers" + acm Transactions on Mathematical Software. 19, 22-32. + + is used to calulate the cumulative standard normal distribution. + + The rational functions from pages 90-95 of Kennedy and Gentle, + Statistical Computing, Marcel Dekker, NY, 1980 are used as + starting values to Newton's Iterations which compute the inverse + standard normal. Therefore no searches are necessary for any + parameter. + + For X < -15, the asymptotic expansion for the normal is used as + the starting value in finding the inverse standard normal. + This is formula 26.2.12 of Abramowitz and Stegun. + + + Note + + + The normal density is proportional to + exp( - 0.5 * (( X - MEAN)/SD)**2) + +**********************************************************************/ +{ +static int K1 = 1; +static double z,pq; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + *status = 0; + if(!(*which < 1 || *which > 4)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 4.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p <= 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p <= 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 1) goto S150; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S140; + if(!(pq < 0.0e0)) goto S120; + *bound = 0.0e0; + goto S130; +S120: + *bound = 1.0e0; +S130: + *status = 3; + return; +S150: +S140: + if(*which == 4) goto S170; +/* + SD +*/ + if(!(*sd <= 0.0e0)) goto S160; + *bound = 0.0e0; + *status = -6; + return; +S170: +S160: +/* + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Computing P +*/ + z = (*x-*mean)/ *sd; + cumnor(&z,p,q); + } + else if(2 == *which) { +/* + Computing X +*/ + z = dinvnr(p,q); + *x = *sd*z+*mean; + } + else if(3 == *which) { +/* + Computing the MEAN +*/ + z = dinvnr(p,q); + *mean = *x-*sd*z; + } + else if(4 == *which) { +/* + Computing SD +*/ + z = dinvnr(p,q); + *sd = (*x-*mean)/z; + } + return; +} /* END */ + +/***=====================================================================***/ +static void cdfpoi(int *which,double *p,double *q,double *s,double *xlam, + int *status,double *bound) +/********************************************************************** + + void cdfpoi(int *which,double *p,double *q,double *s,double *xlam, + int *status,double *bound) + + Cumulative Distribution Function + POIsson distribution + + + Function + + + Calculates any one parameter of the Poisson + distribution given values for the others. + + + Arguments + + + WHICH --> Integer indicating which argument + value is to be calculated from the others. + Legal range: 1..3 + iwhich = 1 : Calculate P and Q from S and XLAM + iwhich = 2 : Calculate A from P,Q and XLAM + iwhich = 3 : Calculate XLAM from P,Q and S + + P <--> The cumulation from 0 to S of the poisson density. + Input range: [0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + S <--> Upper limit of cumulation of the Poisson. + Input range: [0, +infinity). + Search range: [0,1E300] + + XLAM <--> Mean of the Poisson distribution. + Input range: [0, +infinity). + Search range: [0,1E300] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.4.21 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the computation + of the cumulative distribution function to that of computing a + chi-square, hence an incomplete gamma function. + + Cumulative distribution function (P) is calculated directly. + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define inf 1.0e300 +static int K1 = 1; +static double K2 = 0.0e0; +static double K4 = 0.5e0; +static double K5 = 5.0e0; +static double fx,cum,ccum,pq; +static unsigned long qhi,qleft,qporq; +static double T3,T6,T7,T8,T9,T10; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 3)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 3.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p < 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p < 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 2) goto S130; +/* + S +*/ + if(!(*s < 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -4; + return; +S130: +S120: + if(*which == 3) goto S150; +/* + XLAM +*/ + if(!(*xlam < 0.0e0)) goto S140; + *bound = 0.0e0; + *status = -5; + return; +S150: +S140: + if(*which == 1) goto S190; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S180; + if(!(pq < 0.0e0)) goto S160; + *bound = 0.0e0; + goto S170; +S160: + *bound = 1.0e0; +S170: + *status = 3; + return; +S190: +S180: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Calculating P +*/ + cumpoi(s,xlam,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Calculating S +*/ + *s = 5.0e0; + T3 = inf; + T6 = atol; + T7 = tol; + dstinv(&K2,&T3,&K4,&K4,&K5,&T6,&T7); + *status = 0; + dinvr(status,s,&fx,&qleft,&qhi); +S200: + if(!(*status == 1)) goto S230; + cumpoi(s,xlam,&cum,&ccum); + if(!qporq) goto S210; + fx = cum-*p; + goto S220; +S210: + fx = ccum-*q; +S220: + dinvr(status,s,&fx,&qleft,&qhi); + goto S200; +S230: + if(!(*status == -1)) goto S260; + if(!qleft) goto S240; + *status = 1; + *bound = 0.0e0; + goto S250; +S240: + *status = 2; + *bound = inf; +S260: +S250: + ; + } + else if(3 == *which) { +/* + Calculating XLAM +*/ + *xlam = 5.0e0; + T8 = inf; + T9 = atol; + T10 = tol; + dstinv(&K2,&T8,&K4,&K4,&K5,&T9,&T10); + *status = 0; + dinvr(status,xlam,&fx,&qleft,&qhi); +S270: + if(!(*status == 1)) goto S300; + cumpoi(s,xlam,&cum,&ccum); + if(!qporq) goto S280; + fx = cum-*p; + goto S290; +S280: + fx = ccum-*q; +S290: + dinvr(status,xlam,&fx,&qleft,&qhi); + goto S270; +S300: + if(!(*status == -1)) goto S330; + if(!qleft) goto S310; + *status = 1; + *bound = 0.0e0; + goto S320; +S310: + *status = 2; + *bound = inf; +S320: + ; + } +S330: + return; +#undef tol +#undef atol +#undef inf +} /* END */ + +/***=====================================================================***/ +static void cdft(int *which,double *p,double *q,double *t,double *df, + int *status,double *bound) +/********************************************************************** + + void cdft(int *which,double *p,double *q,double *t,double *df, + int *status,double *bound) + + Cumulative Distribution Function + T distribution + + + Function + + + Calculates any one parameter of the t distribution given + values for the others. + + + Arguments + + + WHICH --> Integer indicating which argument + values is to be calculated from the others. + Legal range: 1..3 + iwhich = 1 : Calculate P and Q from T and DF + iwhich = 2 : Calculate T from P,Q and DF + iwhich = 3 : Calculate DF from P,Q and T + + P <--> The integral from -infinity to t of the t-density. + Input range: (0,1]. + + Q <--> 1-P. + Input range: (0, 1]. + P + Q = 1.0. + + T <--> Upper limit of integration of the t-density. + Input range: ( -infinity, +infinity). + Search range: [ -1E300, 1E300 ] + + DF <--> Degrees of freedom of the t-distribution. + Input range: (0 , +infinity). + Search range: [1e-300, 1E10] + + STATUS <-- 0 if calculation completed correctly + -I if input parameter number I is out of range + 1 if answer appears to be lower than lowest + search bound + 2 if answer appears to be higher than greatest + search bound + 3 if P + Q .ne. 1 + + BOUND <-- Undefined if STATUS is 0 + + Bound exceeded by parameter number I if STATUS + is negative. + + Lower search bound if STATUS is 1. + + Upper search bound if STATUS is 2. + + + Method + + + Formula 26.5.27 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the computation + of the cumulative distribution function to that of an incomplete + beta. + + Computation of other parameters involve a seach for a value that + produces the desired value of P. The search relies on the + monotinicity of P with the other parameter. + +**********************************************************************/ +{ +#define tol (1.0e-8) +#define atol (1.0e-50) +#define zero (1.0e-300) +#define inf 1.0e300 +#define maxdf 1.0e10 +static int K1 = 1; +static double K4 = 0.5e0; +static double K5 = 5.0e0; +static double fx,cum,ccum,pq; +static unsigned long qhi,qleft,qporq; +static double T2,T3,T6,T7,T8,T9,T10,T11; +/* + .. + .. Executable Statements .. +*/ +/* + Check arguments +*/ + if(!(*which < 1 || *which > 3)) goto S30; + if(!(*which < 1)) goto S10; + *bound = 1.0e0; + goto S20; +S10: + *bound = 3.0e0; +S20: + *status = -1; + return; +S30: + if(*which == 1) goto S70; +/* + P +*/ + if(!(*p <= 0.0e0 || *p > 1.0e0)) goto S60; + if(!(*p <= 0.0e0)) goto S40; + *bound = 0.0e0; + goto S50; +S40: + *bound = 1.0e0; +S50: + *status = -2; + return; +S70: +S60: + if(*which == 1) goto S110; +/* + Q +*/ + if(!(*q <= 0.0e0 || *q > 1.0e0)) goto S100; + if(!(*q <= 0.0e0)) goto S80; + *bound = 0.0e0; + goto S90; +S80: + *bound = 1.0e0; +S90: + *status = -3; + return; +S110: +S100: + if(*which == 3) goto S130; +/* + DF +*/ + if(!(*df <= 0.0e0)) goto S120; + *bound = 0.0e0; + *status = -5; + return; +S130: +S120: + if(*which == 1) goto S170; +/* + P + Q +*/ + pq = *p+*q; + if(!(fabs(pq-0.5e0-0.5e0) > 3.0e0*spmpar(&K1))) goto S160; + if(!(pq < 0.0e0)) goto S140; + *bound = 0.0e0; + goto S150; +S140: + *bound = 1.0e0; +S150: + *status = 3; + return; +S170: +S160: + if(!(*which == 1)) qporq = *p <= *q; +/* + Select the minimum of P or Q + Calculate ANSWERS +*/ + if(1 == *which) { +/* + Computing P and Q +*/ + cumt(t,df,p,q); + *status = 0; + } + else if(2 == *which) { +/* + Computing T + .. Get initial approximation for T +*/ + *t = dt1(p,q,df); + T2 = -inf; + T3 = inf; + T6 = atol; + T7 = tol; + dstinv(&T2,&T3,&K4,&K4,&K5,&T6,&T7); + *status = 0; + dinvr(status,t,&fx,&qleft,&qhi); +S180: + if(!(*status == 1)) goto S210; + cumt(t,df,&cum,&ccum); + if(!qporq) goto S190; + fx = cum-*p; + goto S200; +S190: + fx = ccum-*q; +S200: + dinvr(status,t,&fx,&qleft,&qhi); + goto S180; +S210: + if(!(*status == -1)) goto S240; + if(!qleft) goto S220; + *status = 1; + *bound = -inf; + goto S230; +S220: + *status = 2; + *bound = inf; +S240: +S230: + ; + } + else if(3 == *which) { +/* + Computing DF +*/ + *df = 5.0e0; + T8 = zero; + T9 = maxdf; + T10 = atol; + T11 = tol; + dstinv(&T8,&T9,&K4,&K4,&K5,&T10,&T11); + *status = 0; + dinvr(status,df,&fx,&qleft,&qhi); +S250: + if(!(*status == 1)) goto S280; + cumt(t,df,&cum,&ccum); + if(!qporq) goto S260; + fx = cum-*p; + goto S270; +S260: + fx = ccum-*q; +S270: + dinvr(status,df,&fx,&qleft,&qhi); + goto S250; +S280: + if(!(*status == -1)) goto S310; + if(!qleft) goto S290; + *status = 1; + *bound = zero; + goto S300; +S290: + *status = 2; + *bound = maxdf; +S300: + ; + } +S310: + return; +#undef tol +#undef atol +#undef zero +#undef inf +#undef maxdf +} /* END */ + +/***=====================================================================***/ +static void cumbet(double *x,double *y,double *a,double *b,double *cum, + double *ccum) +/* +********************************************************************** + + void cumbet(double *x,double *y,double *a,double *b,double *cum, + double *ccum) + + Double precision cUMulative incomplete BETa distribution + + + Function + + + Calculates the cdf to X of the incomplete beta distribution + with parameters a and b. This is the integral from 0 to x + of (1/B(a,b))*f(t)) where f(t) = t**(a-1) * (1-t)**(b-1) + + + Arguments + + + X --> Upper limit of integration. + X is DOUBLE PRECISION + + Y --> 1 - X. + Y is DOUBLE PRECISION + + A --> First parameter of the beta distribution. + A is DOUBLE PRECISION + + B --> Second parameter of the beta distribution. + B is DOUBLE PRECISION + + CUM <-- Cumulative incomplete beta distribution. + CUM is DOUBLE PRECISION + + CCUM <-- Compliment of Cumulative incomplete beta distribution. + CCUM is DOUBLE PRECISION + + + Method + + + Calls the routine BRATIO. + + References + + Didonato, Armido R. and Morris, Alfred H. Jr. (1992) Algorithim + 708 Significant Digit Computation of the Incomplete Beta Function + Ratios. ACM ToMS, Vol.18, No. 3, Sept. 1992, 360-373. + +********************************************************************** +*/ +{ +static int ierr; +/* + .. + .. Executable Statements .. +*/ + if(!(*x <= 0.0e0)) goto S10; + *cum = 0.0e0; + *ccum = 1.0e0; + return; +S10: + if(!(*y <= 0.0e0)) goto S20; + *cum = 1.0e0; + *ccum = 0.0e0; + return; +S20: + bratio(a,b,x,y,cum,ccum,&ierr); +/* + Call bratio routine +*/ + return; +} /* END */ + +/***=====================================================================***/ +static void cumbin(double *s,double *xn,double *pr,double *ompr, + double *cum,double *ccum) +/* +********************************************************************** + + void cumbin(double *s,double *xn,double *pr,double *ompr, + double *cum,double *ccum) + + CUmulative BINomial distribution + + + Function + + + Returns the probability of 0 to S successes in XN binomial + trials, each of which has a probability of success, PBIN. + + + Arguments + + + S --> The upper limit of cumulation of the binomial distribution. + S is DOUBLE PRECISION + + XN --> The number of binomial trials. + XN is DOUBLE PRECISIO + + PBIN --> The probability of success in each binomial trial. + PBIN is DOUBLE PRECIS + + OMPR --> 1 - PBIN + OMPR is DOUBLE PRECIS + + CUM <-- Cumulative binomial distribution. + CUM is DOUBLE PRECISI + + CCUM <-- Compliment of Cumulative binomial distribution. + CCUM is DOUBLE PRECIS + + + Method + + + Formula 26.5.24 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the binomial + distribution to the cumulative beta distribution. + +********************************************************************** +*/ +{ +static double T1,T2; +/* + .. + .. Executable Statements .. +*/ + if(!(*s < *xn)) goto S10; + T1 = *s+1.0e0; + T2 = *xn-*s; + cumbet(pr,ompr,&T1,&T2,ccum,cum); + goto S20; +S10: + *cum = 1.0e0; + *ccum = 0.0e0; +S20: + return; +} /* END */ + +/***=====================================================================***/ +static void cumchi(double *x,double *df,double *cum,double *ccum) +/* +********************************************************************** + + void cumchi(double *x,double *df,double *cum,double *ccum) + CUMulative of the CHi-square distribution + + + Function + + + Calculates the cumulative chi-square distribution. + + + Arguments + + + X --> Upper limit of integration of the + chi-square distribution. + X is DOUBLE PRECISION + + DF --> Degrees of freedom of the + chi-square distribution. + DF is DOUBLE PRECISION + + CUM <-- Cumulative chi-square distribution. + CUM is DOUBLE PRECISIO + + CCUM <-- Compliment of Cumulative chi-square distribution. + CCUM is DOUBLE PRECISI + + + Method + + + Calls incomplete gamma function (CUMGAM) + +********************************************************************** +*/ +{ +static double a,xx; +/* + .. + .. Executable Statements .. +*/ + a = *df*0.5e0; + xx = *x*0.5e0; + cumgam(&xx,&a,cum,ccum); + return; +} /* END */ + +/***=====================================================================***/ +static void cumchn(double *x,double *df,double *pnonc,double *cum, + double *ccum) +/* +********************************************************************** + + void cumchn(double *x,double *df,double *pnonc,double *cum, + double *ccum) + + CUMulative of the Non-central CHi-square distribution + + + Function + + + Calculates the cumulative non-central chi-square + distribution, i.e., the probability that a random variable + which follows the non-central chi-square distribution, with + non-centrality parameter PNONC and continuous degrees of + freedom DF, is less than or equal to X. + + + Arguments + + + X --> Upper limit of integration of the non-central + chi-square distribution. + X is DOUBLE PRECISION + + DF --> Degrees of freedom of the non-central + chi-square distribution. + DF is DOUBLE PRECISION + + PNONC --> Non-centrality parameter of the non-central + chi-square distribution. + PNONC is DOUBLE PRECIS + + CUM <-- Cumulative non-central chi-square distribution. + CUM is DOUBLE PRECISIO + + CCUM <-- Compliment of Cumulative non-central chi-square distribut + CCUM is DOUBLE PRECISI + + + Method + + + Uses formula 26.4.25 of Abramowitz and Stegun, Handbook of + Mathematical Functions, US NBS (1966) to calculate the + non-central chi-square. + + + Variables + + + EPS --- Convergence criterion. The sum stops when a + term is less than EPS*SUM. + EPS is DOUBLE PRECISIO + + NTIRED --- Maximum number of terms to be evaluated + in each sum. + NTIRED is INTEGER + + QCONV --- .TRUE. if convergence achieved - + i.e., program did not stop on NTIRED criterion. + QCONV is LOGICAL + + CCUM <-- Compliment of Cumulative non-central + chi-square distribution. + CCUM is DOUBLE PRECISI + +********************************************************************** +*/ +{ +#define dg(i) (*df+2.0e0*(double)(i)) +#define qsmall(xx) (int)(sum < 1.0e-20 || (xx) < eps*sum) +#define qtired(i) (int)((i) > ntired) +static double eps = 1.0e-5; +static int ntired = 1000; +static double adj,centaj,centwt,chid2,dfd2,lcntaj,lcntwt,lfact,pcent,pterm,sum, + sumadj,term,wt,xnonc; +static int i,icent,iterb,iterf; +static double T1,T2,T3; +/* + .. + .. Executable Statements .. +*/ + if(!(*x <= 0.0e0)) goto S10; + *cum = 0.0e0; + *ccum = 1.0e0; + return; +S10: + if(!(*pnonc <= 1.0e-10)) goto S20; +/* + When non-centrality parameter is (essentially) zero, + use cumulative chi-square distribution +*/ + cumchi(x,df,cum,ccum); + return; +S20: + xnonc = *pnonc/2.0e0; +/* +********************************************************************** + The following code calcualtes the weight, chi-square, and + adjustment term for the central term in the infinite series. + The central term is the one in which the poisson weight is + greatest. The adjustment term is the amount that must + be subtracted from the chi-square to move up two degrees + of freedom. +********************************************************************** +*/ + icent = fifidint(xnonc); + if(icent == 0) icent = 1; + chid2 = *x/2.0e0; +/* + Calculate central weight term +*/ + T1 = (double)(icent+1); + lfact = alngam(&T1); + lcntwt = -xnonc+(double)icent*log(xnonc)-lfact; + centwt = exp(lcntwt); +/* + Calculate central chi-square +*/ + T2 = dg(icent); + cumchi(x,&T2,&pcent,ccum); +/* + Calculate central adjustment term +*/ + dfd2 = dg(icent)/2.0e0; + T3 = 1.0e0+dfd2; + lfact = alngam(&T3); + lcntaj = dfd2*log(chid2)-chid2-lfact; + centaj = exp(lcntaj); + sum = centwt*pcent; +/* +********************************************************************** + Sum backwards from the central term towards zero. + Quit whenever either + (1) the zero term is reached, or + (2) the term gets small relative to the sum, or + (3) More than NTIRED terms are totaled. +********************************************************************** +*/ + iterb = 0; + sumadj = 0.0e0; + adj = centaj; + wt = centwt; + i = icent; + goto S40; +S30: + if(qtired(iterb) || qsmall(term) || i == 0) goto S50; +S40: + dfd2 = dg(i)/2.0e0; +/* + Adjust chi-square for two fewer degrees of freedom. + The adjusted value ends up in PTERM. +*/ + adj = adj*dfd2/chid2; + sumadj += adj; + pterm = pcent+sumadj; +/* + Adjust poisson weight for J decreased by one +*/ + wt *= ((double)i/xnonc); + term = wt*pterm; + sum += term; + i -= 1; + iterb += 1; + goto S30; +S50: + iterf = 0; +/* +********************************************************************** + Now sum forward from the central term towards infinity. + Quit when either + (1) the term gets small relative to the sum, or + (2) More than NTIRED terms are totaled. +********************************************************************** +*/ + sumadj = adj = centaj; + wt = centwt; + i = icent; + goto S70; +S60: + if(qtired(iterf) || qsmall(term)) goto S80; +S70: +/* + Update weights for next higher J +*/ + wt *= (xnonc/(double)(i+1)); +/* + Calculate PTERM and add term to sum +*/ + pterm = pcent-sumadj; + term = wt*pterm; + sum += term; +/* + Update adjustment term for DF for next iteration +*/ + i += 1; + dfd2 = dg(i)/2.0e0; + adj = adj*chid2/dfd2; + sumadj += adj; + iterf += 1; + goto S60; +S80: + *cum = sum; + *ccum = 0.5e0+(0.5e0-*cum); + return; +#undef dg +#undef qsmall +#undef qtired +} /* END */ + +/***=====================================================================***/ +static void cumf(double *f,double *dfn,double *dfd,double *cum,double *ccum) +/* +********************************************************************** + + void cumf(double *f,double *dfn,double *dfd,double *cum,double *ccum) + CUMulative F distribution + + + Function + + + Computes the integral from 0 to F of the f-density with DFN + and DFD degrees of freedom. + + + Arguments + + + F --> Upper limit of integration of the f-density. + F is DOUBLE PRECISION + + DFN --> Degrees of freedom of the numerator sum of squares. + DFN is DOUBLE PRECISI + + DFD --> Degrees of freedom of the denominator sum of squares. + DFD is DOUBLE PRECISI + + CUM <-- Cumulative f distribution. + CUM is DOUBLE PRECISI + + CCUM <-- Compliment of Cumulative f distribution. + CCUM is DOUBLE PRECIS + + + Method + + + Formula 26.5.28 of Abramowitz and Stegun is used to reduce + the cumulative F to a cumulative beta distribution. + + + Note + + + If F is less than or equal to 0, 0 is returned. + +********************************************************************** +*/ +{ +#define half 0.5e0 +#define done 1.0e0 +static double dsum,prod,xx,yy; +static int ierr; +static double T1,T2; +/* + .. + .. Executable Statements .. +*/ + if(!(*f <= 0.0e0)) goto S10; + *cum = 0.0e0; + *ccum = 1.0e0; + return; +S10: + prod = *dfn**f; +/* + XX is such that the incomplete beta with parameters + DFD/2 and DFN/2 evaluated at XX is 1 - CUM or CCUM + YY is 1 - XX + Calculate the smaller of XX and YY accurately +*/ + dsum = *dfd+prod; + xx = *dfd/dsum; + if(xx > half) { + yy = prod/dsum; + xx = done-yy; + } + else yy = done-xx; + T1 = *dfd*half; + T2 = *dfn*half; + bratio(&T1,&T2,&xx,&yy,ccum,cum,&ierr); + return; +#undef half +#undef done +} /* END */ + +/***=====================================================================***/ +static void cumfnc(double *f,double *dfn,double *dfd,double *pnonc, + double *cum,double *ccum) +/* +********************************************************************** + + F -NON- -C-ENTRAL F DISTRIBUTION + + + + Function + + + COMPUTES NONCENTRAL F DISTRIBUTION WITH DFN AND DFD + DEGREES OF FREEDOM AND NONCENTRALITY PARAMETER PNONC + + + Arguments + + + X --> UPPER LIMIT OF INTEGRATION OF NONCENTRAL F IN EQUATION + + DFN --> DEGREES OF FREEDOM OF NUMERATOR + + DFD --> DEGREES OF FREEDOM OF DENOMINATOR + + PNONC --> NONCENTRALITY PARAMETER. + + CUM <-- CUMULATIVE NONCENTRAL F DISTRIBUTION + + CCUM <-- COMPLIMENT OF CUMMULATIVE + + + Method + + + USES FORMULA 26.6.20 OF REFERENCE FOR INFINITE SERIES. + SERIES IS CALCULATED BACKWARD AND FORWARD FROM J = LAMBDA/2 + (THIS IS THE TERM WITH THE LARGEST POISSON WEIGHT) UNTIL + THE CONVERGENCE CRITERION IS MET. + + FOR SPEED, THE INCOMPLETE BETA FUNCTIONS ARE EVALUATED + BY FORMULA 26.5.16. + + + REFERENCE + + + HANDBOOD OF MATHEMATICAL FUNCTIONS + EDITED BY MILTON ABRAMOWITZ AND IRENE A. STEGUN + NATIONAL BUREAU OF STANDARDS APPLIED MATEMATICS SERIES - 55 + MARCH 1965 + P 947, EQUATIONS 26.6.17, 26.6.18 + + + Note + + + THE SUM CONTINUES UNTIL A SUCCEEDING TERM IS LESS THAN EPS + TIMES THE SUM (OR THE SUM IS LESS THAN 1.0E-20). EPS IS + SET TO 1.0E-4 IN A DATA STATEMENT WHICH CAN BE CHANGED. + +********************************************************************** +*/ +{ +#define qsmall(x) (int)(sum < 1.0e-20 || (x) < eps*sum) +#define half 0.5e0 +#define done 1.0e0 +static double eps = 1.0e-4; +static double dsum,dummy,prod,xx,yy,adn,aup,b,betdn,betup,centwt,dnterm,sum, + upterm,xmult,xnonc; +static int i,icent,ierr; +static double T1,T2,T3,T4,T5,T6; +/* + .. + .. Executable Statements .. +*/ + if(!(*f <= 0.0e0)) goto S10; + *cum = 0.0e0; + *ccum = 1.0e0; + return; +S10: + if(!(*pnonc < 1.0e-10)) goto S20; +/* + Handle case in which the non-centrality parameter is + (essentially) zero. +*/ + cumf(f,dfn,dfd,cum,ccum); + return; +S20: + xnonc = *pnonc/2.0e0; +/* + Calculate the central term of the poisson weighting factor. +*/ + icent = xnonc; + if(icent == 0) icent = 1; +/* + Compute central weight term +*/ + T1 = (double)(icent+1); + centwt = exp(-xnonc+(double)icent*log(xnonc)-alngam(&T1)); +/* + Compute central incomplete beta term + Assure that minimum of arg to beta and 1 - arg is computed + accurately. +*/ + prod = *dfn**f; + dsum = *dfd+prod; + yy = *dfd/dsum; + if(yy > half) { + xx = prod/dsum; + yy = done-xx; + } + else xx = done-yy; + T2 = *dfn*half+(double)icent; + T3 = *dfd*half; + bratio(&T2,&T3,&xx,&yy,&betdn,&dummy,&ierr); + adn = *dfn/2.0e0+(double)icent; + aup = adn; + b = *dfd/2.0e0; + betup = betdn; + sum = centwt*betdn; +/* + Now sum terms backward from icent until convergence or all done +*/ + xmult = centwt; + i = icent; + T4 = adn+b; + T5 = adn+1.0e0; + dnterm = exp(alngam(&T4)-alngam(&T5)-alngam(&b)+adn*log(xx)+b*log(yy)); +S30: + if(qsmall(xmult*betdn) || i <= 0) goto S40; + xmult *= ((double)i/xnonc); + i -= 1; + adn -= 1.0; + dnterm = (adn+1.0)/((adn+b)*xx)*dnterm; + betdn += dnterm; + sum += (xmult*betdn); + goto S30; +S40: + i = icent+1; +/* + Now sum forwards until convergence +*/ + xmult = centwt; + if(aup-1.0+b == 0) upterm = exp(-alngam(&aup)-alngam(&b)+(aup-1.0)*log(xx)+ + b*log(yy)); + else { + T6 = aup-1.0+b; + upterm = exp(alngam(&T6)-alngam(&aup)-alngam(&b)+(aup-1.0)*log(xx)+b* + log(yy)); + } + goto S60; +S50: + if(qsmall(xmult*betup)) goto S70; +S60: + xmult *= (xnonc/(double)i); + i += 1; + aup += 1.0; + upterm = (aup+b-2.0e0)*xx/(aup-1.0)*upterm; + betup -= upterm; + sum += (xmult*betup); + goto S50; +S70: + *cum = sum; + *ccum = 0.5e0+(0.5e0-*cum); + return; +#undef qsmall +#undef half +#undef done +} /* END */ + +/***=====================================================================***/ +static void cumgam(double *x,double *a,double *cum,double *ccum) +/* +********************************************************************** + + void cumgam(double *x,double *a,double *cum,double *ccum) + Double precision cUMulative incomplete GAMma distribution + + + Function + + + Computes the cumulative of the incomplete gamma + distribution, i.e., the integral from 0 to X of + (1/GAM(A))*EXP(-T)*T**(A-1) DT + where GAM(A) is the complete gamma function of A, i.e., + GAM(A) = integral from 0 to infinity of + EXP(-T)*T**(A-1) DT + + + Arguments + + + X --> The upper limit of integration of the incomplete gamma. + X is DOUBLE PRECISION + + A --> The shape parameter of the incomplete gamma. + A is DOUBLE PRECISION + + CUM <-- Cumulative incomplete gamma distribution. + CUM is DOUBLE PRECISION + + CCUM <-- Compliment of Cumulative incomplete gamma distribution. + CCUM is DOUBLE PRECISIO + + + Method + + + Calls the routine GRATIO. + +********************************************************************** +*/ +{ +static int K1 = 0; +/* + .. + .. Executable Statements .. +*/ + if(!(*x <= 0.0e0)) goto S10; + *cum = 0.0e0; + *ccum = 1.0e0; + return; +S10: + gratio(a,x,cum,ccum,&K1); +/* + Call gratio routine +*/ + return; +} /* END */ + +/***=====================================================================***/ +static void cumnbn(double *s,double *xn,double *pr,double *ompr, + double *cum,double *ccum) +/* +********************************************************************** + + void cumnbn(double *s,double *xn,double *pr,double *ompr, + double *cum,double *ccum) + + CUmulative Negative BINomial distribution + + + Function + + + Returns the probability that it there will be S or fewer failures + before there are XN successes, with each binomial trial having + a probability of success PR. + + Prob(# failures = S | XN successes, PR) = + ( XN + S - 1 ) + ( ) * PR^XN * (1-PR)^S + ( S ) + + + Arguments + + + S --> The number of failures + S is DOUBLE PRECISION + + XN --> The number of successes + XN is DOUBLE PRECISIO + + PR --> The probability of success in each binomial trial. + PR is DOUBLE PRECISIO + + OMPR --> 1 - PR + OMPR is DOUBLE PRECIS + + CUM <-- Cumulative negative binomial distribution. + CUM is DOUBLE PRECISI + + CCUM <-- Compliment of Cumulative negative binomial distribution. + CCUM is DOUBLE PRECIS + + + Method + + + Formula 26.5.26 of Abramowitz and Stegun, Handbook of + Mathematical Functions (1966) is used to reduce the negative + binomial distribution to the cumulative beta distribution. + +********************************************************************** +*/ +{ +static double T1; +/* + .. + .. Executable Statements .. +*/ + T1 = *s+1.e0; + cumbet(pr,ompr,xn,&T1,cum,ccum); + return; +} /* END */ + +/***=====================================================================***/ +static void cumnor(double *arg,double *result,double *ccum) +/* +********************************************************************** + + void cumnor(double *arg,double *result,double *ccum) + + + Function + + + Computes the cumulative of the normal distribution, i.e., + the integral from -infinity to x of + (1/sqrt(2*pi)) exp(-u*u/2) du + + X --> Upper limit of integration. + X is DOUBLE PRECISION + + RESULT <-- Cumulative normal distribution. + RESULT is DOUBLE PRECISION + + CCUM <-- Compliment of Cumulative normal distribution. + CCUM is DOUBLE PRECISION + + Renaming of function ANORM from: + + Cody, W.D. (1993). "ALGORITHM 715: SPECFUN - A Portabel FORTRAN + Package of Special Function Routines and Test Drivers" + acm Transactions on Mathematical Software. 19, 22-32. + + with slight modifications to return ccum and to deal with + machine constants. + +********************************************************************** + Original Comments: +------------------------------------------------------------------ + + This function evaluates the normal distribution function: + + / x + 1 | -t*t/2 + P(x) = ----------- | e dt + sqrt(2 pi) | + /-oo + + The main computation evaluates near-minimax approximations + derived from those in "Rational Chebyshev approximations for + the error function" by W. J. Cody, Math. Comp., 1969, 631-637. + This transportable program uses rational functions that + theoretically approximate the normal distribution function to + at least 18 significant decimal digits. The accuracy achieved + depends on the arithmetic system, the compiler, the intrinsic + functions, and proper selection of the machine-dependent + constants. + +******************************************************************* +******************************************************************* + + Explanation of machine-dependent constants. + + MIN = smallest machine representable number. + + EPS = argument below which anorm(x) may be represented by + 0.5 and above which x*x will not underflow. + A conservative value is the largest machine number X + such that 1.0 + X = 1.0 to machine precision. +******************************************************************* +******************************************************************* + + Error returns + + The program returns ANORM = 0 for ARG .LE. XLOW. + + + Intrinsic functions required are: + + ABS, AINT, EXP + + + Author: W. J. Cody + Mathematics and Computer Science Division + Argonne National Laboratory + Argonne, IL 60439 + + Latest modification: March 15, 1992 + +------------------------------------------------------------------ +*/ +{ +static double a[5] = { + 2.2352520354606839287e00,1.6102823106855587881e02,1.0676894854603709582e03, + 1.8154981253343561249e04,6.5682337918207449113e-2 +}; +static double b[4] = { + 4.7202581904688241870e01,9.7609855173777669322e02,1.0260932208618978205e04, + 4.5507789335026729956e04 +}; +static double c[9] = { + 3.9894151208813466764e-1,8.8831497943883759412e00,9.3506656132177855979e01, + 5.9727027639480026226e02,2.4945375852903726711e03,6.8481904505362823326e03, + 1.1602651437647350124e04,9.8427148383839780218e03,1.0765576773720192317e-8 +}; +static double d[8] = { + 2.2266688044328115691e01,2.3538790178262499861e02,1.5193775994075548050e03, + 6.4855582982667607550e03,1.8615571640885098091e04,3.4900952721145977266e04, + 3.8912003286093271411e04,1.9685429676859990727e04 +}; +static double half = 0.5e0; +static double p[6] = { + 2.1589853405795699e-1,1.274011611602473639e-1,2.2235277870649807e-2, + 1.421619193227893466e-3,2.9112874951168792e-5,2.307344176494017303e-2 +}; +static double one = 1.0e0; +static double q[5] = { + 1.28426009614491121e00,4.68238212480865118e-1,6.59881378689285515e-2, + 3.78239633202758244e-3,7.29751555083966205e-5 +}; +static double sixten = 1.60e0; +static double sqrpi = 3.9894228040143267794e-1; +static double thrsh = 0.66291e0; +static double root32 = 5.656854248e0; +static double zero = 0.0e0; +static int K1 = 1; +static int K2 = 2; +static int i; +static double del,eps,temp,x,xden,xnum,y,xsq,min; +/* +------------------------------------------------------------------ + Machine dependent constants +------------------------------------------------------------------ +*/ + eps = spmpar(&K1)*0.5e0; + min = spmpar(&K2); + x = *arg; + y = fabs(x); + if(y <= thrsh) { +/* +------------------------------------------------------------------ + Evaluate anorm for |X| <= 0.66291 +------------------------------------------------------------------ +*/ + xsq = zero; + if(y > eps) xsq = x*x; + xnum = a[4]*xsq; + xden = xsq; + for(i=0; i<3; i++) { + xnum = (xnum+a[i])*xsq; + xden = (xden+b[i])*xsq; + } + *result = x*(xnum+a[3])/(xden+b[3]); + temp = *result; + *result = half+temp; + *ccum = half-temp; + } +/* +------------------------------------------------------------------ + Evaluate anorm for 0.66291 <= |X| <= sqrt(32) +------------------------------------------------------------------ +*/ + else if(y <= root32) { + xnum = c[8]*y; + xden = y; + for(i=0; i<7; i++) { + xnum = (xnum+c[i])*y; + xden = (xden+d[i])*y; + } + *result = (xnum+c[7])/(xden+d[7]); + xsq = fifdint(y*sixten)/sixten; + del = (y-xsq)*(y+xsq); + *result = exp(-(xsq*xsq*half))*exp(-(del*half))**result; + *ccum = one-*result; + if(x > zero) { + temp = *result; + *result = *ccum; + *ccum = temp; + } + } +/* +------------------------------------------------------------------ + Evaluate anorm for |X| > sqrt(32) +------------------------------------------------------------------ +*/ + else { + *result = zero; + xsq = one/(x*x); + xnum = p[5]*xsq; + xden = xsq; + for(i=0; i<4; i++) { + xnum = (xnum+p[i])*xsq; + xden = (xden+q[i])*xsq; + } + *result = xsq*(xnum+p[4])/(xden+q[4]); + *result = (sqrpi-*result)/y; + xsq = fifdint(x*sixten)/sixten; + del = (x-xsq)*(x+xsq); + *result = exp(-(xsq*xsq*half))*exp(-(del*half))**result; + *ccum = one-*result; + if(x > zero) { + temp = *result; + *result = *ccum; + *ccum = temp; + } + } + if(*result < min) *result = 0.0e0; +/* +------------------------------------------------------------------ + Fix up for negative argument, erf, etc. +------------------------------------------------------------------ +----------Last card of ANORM ---------- +*/ + if(*ccum < min) *ccum = 0.0e0; +} /* END */ + +/***=====================================================================***/ +static void cumpoi(double *s,double *xlam,double *cum,double *ccum) +/* +********************************************************************** + + void cumpoi(double *s,double *xlam,double *cum,double *ccum) + CUMulative POIsson distribution + + + Function + + + Returns the probability of S or fewer events in a Poisson + distribution with mean XLAM. + + + Arguments + + + S --> Upper limit of cumulation of the Poisson. + S is DOUBLE PRECISION + + XLAM --> Mean of the Poisson distribution. + XLAM is DOUBLE PRECIS + + CUM <-- Cumulative poisson distribution. + CUM is DOUBLE PRECISION + + CCUM <-- Compliment of Cumulative poisson distribution. + CCUM is DOUBLE PRECIS + + + Method + + + Uses formula 26.4.21 of Abramowitz and Stegun, Handbook of + Mathematical Functions to reduce the cumulative Poisson to + the cumulative chi-square distribution. + +********************************************************************** +*/ +{ +static double chi,df; +/* + .. + .. Executable Statements .. +*/ + df = 2.0e0*(*s+1.0e0); + chi = 2.0e0**xlam; + cumchi(&chi,&df,ccum,cum); + return; +} /* END */ + +/***=====================================================================***/ +static void cumt(double *t,double *df,double *cum,double *ccum) +/* +********************************************************************** + + void cumt(double *t,double *df,double *cum,double *ccum) + CUMulative T-distribution + + + Function + + + Computes the integral from -infinity to T of the t-density. + + + Arguments + + + T --> Upper limit of integration of the t-density. + T is DOUBLE PRECISION + + DF --> Degrees of freedom of the t-distribution. + DF is DOUBLE PRECISIO + + CUM <-- Cumulative t-distribution. + CCUM is DOUBLE PRECIS + + CCUM <-- Compliment of Cumulative t-distribution. + CCUM is DOUBLE PRECIS + + + Method + + + Formula 26.5.27 of Abramowitz and Stegun, Handbook of + Mathematical Functions is used to reduce the t-distribution + to an incomplete beta. + +********************************************************************** +*/ +{ +static double K2 = 0.5e0; +static double xx,a,oma,tt,yy,dfptt,T1; +/* + .. + .. Executable Statements .. +*/ + tt = *t**t; + dfptt = *df+tt; + xx = *df/dfptt; + yy = tt/dfptt; + T1 = 0.5e0**df; + cumbet(&xx,&yy,&T1,&K2,&a,&oma); + if(!(*t <= 0.0e0)) goto S10; + *cum = 0.5e0*a; + *ccum = oma+*cum; + goto S20; +S10: + *ccum = 0.5e0*a; + *cum = oma+*ccum; +S20: + return; +} /* END */ + +/***=====================================================================***/ +static double dbetrm(double *a,double *b) +/* +********************************************************************** + + double dbetrm(double *a,double *b) + Double Precision Sterling Remainder for Complete + Beta Function + + + Function + + + Log(Beta(A,B)) = Lgamma(A) + Lgamma(B) - Lgamma(A+B) + where Lgamma is the log of the (complete) gamma function + + Let ZZ be approximation obtained if each log gamma is approximated + by Sterling's formula, i.e., + Sterling(Z) = LOG( SQRT( 2*PI ) ) + ( Z-0.5 ) * LOG( Z ) - Z + + Returns Log(Beta(A,B)) - ZZ + + + Arguments + + + A --> One argument of the Beta + DOUBLE PRECISION A + + B --> The other argument of the Beta + DOUBLE PRECISION B + +********************************************************************** +*/ +{ +static double dbetrm,T1,T2,T3; +/* + .. + .. Executable Statements .. +*/ +/* + Try to sum from smallest to largest +*/ + T1 = *a+*b; + dbetrm = -dstrem(&T1); + T2 = fifdmax1(*a,*b); + dbetrm += dstrem(&T2); + T3 = fifdmin1(*a,*b); + dbetrm += dstrem(&T3); + return dbetrm; +} /* END */ + +/***=====================================================================***/ +static double devlpl(double a[],int *n,double *x) +/* +********************************************************************** + + double devlpl(double a[],int *n,double *x) + Double precision EVALuate a PoLynomial at X + + + Function + + + returns + A(1) + A(2)*X + ... + A(N)*X**(N-1) + + + Arguments + + + A --> Array of coefficients of the polynomial. + A is DOUBLE PRECISION(N) + + N --> Length of A, also degree of polynomial - 1. + N is INTEGER + + X --> Point at which the polynomial is to be evaluated. + X is DOUBLE PRECISION + +********************************************************************** +*/ +{ +static double devlpl,term; +static int i; +/* + .. + .. Executable Statements .. +*/ + term = a[*n-1]; + for(i= *n-1-1; i>=0; i--) term = a[i]+term**x; + devlpl = term; + return devlpl; +} /* END */ + +/***=====================================================================***/ +static double dexpm1(double *x) +/* +********************************************************************** + + double dexpm1(double *x) + Evaluation of the function EXP(X) - 1 + + + Arguments + + + X --> Argument at which exp(x)-1 desired + DOUBLE PRECISION X + + + Method + + + Renaming of function rexp from code of: + + DiDinato, A. R. and Morris, A. H. Algorithm 708: Significant + Digit Computation of the Incomplete Beta Function Ratios. ACM + Trans. Math. Softw. 18 (1993), 360-373. + +********************************************************************** +*/ +{ +static double p1 = .914041914819518e-09; +static double p2 = .238082361044469e-01; +static double q1 = -.499999999085958e+00; +static double q2 = .107141568980644e+00; +static double q3 = -.119041179760821e-01; +static double q4 = .595130811860248e-03; +static double dexpm1,w; +/* + .. + .. Executable Statements .. +*/ + if(fabs(*x) > 0.15e0) goto S10; + dexpm1 = *x*(((p2**x+p1)**x+1.0e0)/((((q4**x+q3)**x+q2)**x+q1)**x+1.0e0)); + return dexpm1; +S10: + w = exp(*x); + if(*x > 0.0e0) goto S20; + dexpm1 = w-0.5e0-0.5e0; + return dexpm1; +S20: + dexpm1 = w*(0.5e0+(0.5e0-1.0e0/w)); + return dexpm1; +} /* END */ + +/***=====================================================================***/ +static double dinvnr(double *p,double *q) +/* +********************************************************************** + + double dinvnr(double *p,double *q) + Double precision NoRmal distribution INVerse + + + Function + + + Returns X such that CUMNOR(X) = P, i.e., the integral from - + infinity to X of (1/SQRT(2*PI)) EXP(-U*U/2) dU is P + + + Arguments + + + P --> The probability whose normal deviate is sought. + P is DOUBLE PRECISION + + Q --> 1-P + P is DOUBLE PRECISION + + + Method + + + The rational function on page 95 of Kennedy and Gentle, + Statistical Computing, Marcel Dekker, NY , 1980 is used as a start + value for the Newton method of finding roots. + + + Note + + + If P or Q .lt. machine EPS returns +/- DINVNR(EPS) + +********************************************************************** +*/ +{ +#define maxit 100 +#define eps (1.0e-13) +#define r2pi 0.3989422804014326e0 +#define nhalf (-0.5e0) +#define dennor(x) (r2pi*exp(nhalf*(x)*(x))) +static double dinvnr,strtx,xcur,cum,ccum,pp,dx; +static int i; +static unsigned long qporq; +/* + .. + .. Executable Statements .. +*/ +/* + FIND MINIMUM OF P AND Q +*/ + qporq = *p <= *q; + if(!qporq) goto S10; + pp = *p; + goto S20; +S10: + pp = *q; +S20: +/* + INITIALIZATION STEP +*/ + strtx = stvaln(&pp); + xcur = strtx; +/* + NEWTON INTERATIONS +*/ + for(i=1; i<=maxit; i++) { + cumnor(&xcur,&cum,&ccum); + dx = (cum-pp)/dennor(xcur); + xcur -= dx; + if(fabs(dx/xcur) < eps) goto S40; + } + dinvnr = strtx; +/* + IF WE GET HERE, NEWTON HAS FAILED +*/ + if(!qporq) dinvnr = -dinvnr; + return dinvnr; +S40: +/* + IF WE GET HERE, NEWTON HAS SUCCEDED +*/ + dinvnr = xcur; + if(!qporq) dinvnr = -dinvnr; + return dinvnr; +#undef maxit +#undef eps +#undef r2pi +#undef nhalf +#undef dennor +} /* END */ + +/***=====================================================================***/ +static void E0000(int IENTRY,int *status,double *x,double *fx, + unsigned long *qleft,unsigned long *qhi,double *zabsst, + double *zabsto,double *zbig,double *zrelst, + double *zrelto,double *zsmall,double *zstpmu) +{ +#define qxmon(zx,zy,zz) (int)((zx) <= (zy) && (zy) <= (zz)) +static double absstp,abstol,big,fbig,fsmall,relstp,reltol,small,step,stpmul,xhi, + xlb,xlo,xsave,xub,yy; +static int i99999; +static unsigned long qbdd,qcond,qdum1,qdum2,qincr,qlim,qok,qup; + switch(IENTRY){case 0: goto DINVR; case 1: goto DSTINV;} +DINVR: + if(*status > 0) goto S310; + qcond = !qxmon(small,*x,big); + if(qcond){ ftnstop("SMALL,X,BIG nonmonotone in E0000"); *status=-1; return;} + xsave = *x; +/* + See that SMALL and BIG bound the zero and set QINCR +*/ + *x = small; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 1; + goto S300; +S10: + fsmall = *fx; + *x = big; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 2; + goto S300; +S20: + fbig = *fx; + qincr = fbig > fsmall; + if(!qincr) goto S50; + if(fsmall <= 0.0e0) goto S30; + *status = -1; + *qleft = *qhi = 1; + return; +S30: + if(fbig >= 0.0e0) goto S40; + *status = -1; + *qleft = *qhi = 0; + return; +S40: + goto S80; +S50: + if(fsmall >= 0.0e0) goto S60; + *status = -1; + *qleft = 1; + *qhi = 0; + return; +S60: + if(fbig <= 0.0e0) goto S70; + *status = -1; + *qleft = 0; + *qhi = 1; + return; +S80: +S70: + *x = xsave; + step = fifdmax1(absstp,relstp*fabs(*x)); +/* + YY = F(X) - Y + GET-FUNCTION-VALUE +*/ + i99999 = 3; + goto S300; +S90: + yy = *fx; + if(!(yy == 0.0e0)) goto S100; + *status = 0; + qok = 1; + return; +S100: + qup = qincr && yy < 0.0e0 || !qincr && yy > 0.0e0; +/* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + HANDLE CASE IN WHICH WE MUST STEP HIGHER +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +*/ + if(!qup) goto S170; + xlb = xsave; + xub = fifdmin1(xlb+step,big); + goto S120; +S110: + if(qcond) goto S150; +S120: +/* + YY = F(XUB) - Y +*/ + *x = xub; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 4; + goto S300; +S130: + yy = *fx; + qbdd = qincr && yy >= 0.0e0 || !qincr && yy <= 0.0e0; + qlim = xub >= big; + qcond = qbdd || qlim; + if(qcond) goto S140; + step = stpmul*step; + xlb = xub; + xub = fifdmin1(xlb+step,big); +S140: + goto S110; +S150: + if(!(qlim && !qbdd)) goto S160; + *status = -1; + *qleft = 0; + *qhi = !qincr; + *x = big; + return; +S160: + goto S240; +S170: +/* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + HANDLE CASE IN WHICH WE MUST STEP LOWER +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +*/ + xub = xsave; + xlb = fifdmax1(xub-step,small); + goto S190; +S180: + if(qcond) goto S220; +S190: +/* + YY = F(XLB) - Y +*/ + *x = xlb; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 5; + goto S300; +S200: + yy = *fx; + qbdd = qincr && yy <= 0.0e0 || !qincr && yy >= 0.0e0; + qlim = xlb <= small; + qcond = qbdd || qlim; + if(qcond) goto S210; + step = stpmul*step; + xub = xlb; + xlb = fifdmax1(xub-step,small); +S210: + goto S180; +S220: + if(!(qlim && !qbdd)) goto S230; + *status = -1; + *qleft = 1; + *qhi = qincr; + *x = small; + return; +S240: +S230: + dstzr(&xlb,&xub,&abstol,&reltol); +/* +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + IF WE REACH HERE, XLB AND XUB BOUND THE ZERO OF F. +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +*/ + *status = 0; + goto S260; +S250: + if(!(*status == 1)) goto S290; +S260: + dzror(status,x,fx,&xlo,&xhi,&qdum1,&qdum2); + if(!(*status == 1)) goto S280; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 6; + goto S300; +S280: +S270: + goto S250; +S290: + *x = xlo; + *status = 0; + return; +DSTINV: + small = *zsmall; + big = *zbig; + absstp = *zabsst; + relstp = *zrelst; + stpmul = *zstpmu; + abstol = *zabsto; + reltol = *zrelto; + return; +S300: +/* + TO GET-FUNCTION-VALUE +*/ + *status = 1; + return; +S310: + switch((int)i99999){case 1: goto S10;case 2: goto S20;case 3: goto S90;case + 4: goto S130;case 5: goto S200;case 6: goto S270;default: break;} +#undef qxmon +} /* END */ + +/***=====================================================================***/ +static void dinvr(int *status,double *x,double *fx, + unsigned long *qleft,unsigned long *qhi) +/* +********************************************************************** + + void dinvr(int *status,double *x,double *fx, + unsigned long *qleft,unsigned long *qhi) + + Double precision + bounds the zero of the function and invokes zror + Reverse Communication + + + Function + + + Bounds the function and invokes ZROR to perform the zero + finding. STINVR must have been called before this routine + in order to set its parameters. + + + Arguments + + + STATUS <--> At the beginning of a zero finding problem, STATUS + should be set to 0 and INVR invoked. (The value + of parameters other than X will be ignored on this cal + + When INVR needs the function evaluated, it will set + STATUS to 1 and return. The value of the function + should be set in FX and INVR again called without + changing any of its other parameters. + + When INVR has finished without error, it will return + with STATUS 0. In that case X is approximately a root + of F(X). + + If INVR cannot bound the function, it returns status + -1 and sets QLEFT and QHI. + INTEGER STATUS + + X <-- The value of X at which F(X) is to be evaluated. + DOUBLE PRECISION X + + FX --> The value of F(X) calculated when INVR returns with + STATUS = 1. + DOUBLE PRECISION FX + + QLEFT <-- Defined only if QMFINV returns .FALSE. In that + case it is .TRUE. If the stepping search terminated + unsucessfully at SMALL. If it is .FALSE. the search + terminated unsucessfully at BIG. + QLEFT is LOGICAL + + QHI <-- Defined only if QMFINV returns .FALSE. In that + case it is .TRUE. if F(X) .GT. Y at the termination + of the search and .FALSE. if F(X) .LT. Y at the + termination of the search. + QHI is LOGICAL + +********************************************************************** +*/ +{ + E0000(0,status,x,fx,qleft,qhi,NULL,NULL,NULL,NULL,NULL,NULL,NULL); +} /* END */ + +/***=====================================================================***/ +static void dstinv(double *zsmall,double *zbig,double *zabsst, + double *zrelst,double *zstpmu,double *zabsto, + double *zrelto) +/* +********************************************************************** + void dstinv(double *zsmall,double *zbig,double *zabsst, + double *zrelst,double *zstpmu,double *zabsto, + double *zrelto) + + Double Precision - SeT INverse finder - Reverse Communication + Function + Concise Description - Given a monotone function F finds X + such that F(X) = Y. Uses Reverse communication -- see invr. + This routine sets quantities needed by INVR. + More Precise Description of INVR - + F must be a monotone function, the results of QMFINV are + otherwise undefined. QINCR must be .TRUE. if F is non- + decreasing and .FALSE. if F is non-increasing. + QMFINV will return .TRUE. if and only if F(SMALL) and + F(BIG) bracket Y, i. e., + QINCR is .TRUE. and F(SMALL).LE.Y.LE.F(BIG) or + QINCR is .FALSE. and F(BIG).LE.Y.LE.F(SMALL) + if QMFINV returns .TRUE., then the X returned satisfies + the following condition. let + TOL(X) = MAX(ABSTOL,RELTOL*ABS(X)) + then if QINCR is .TRUE., + F(X-TOL(X)) .LE. Y .LE. F(X+TOL(X)) + and if QINCR is .FALSE. + F(X-TOL(X)) .GE. Y .GE. F(X+TOL(X)) + Arguments + SMALL --> The left endpoint of the interval to be + searched for a solution. + SMALL is DOUBLE PRECISION + BIG --> The right endpoint of the interval to be + searched for a solution. + BIG is DOUBLE PRECISION + ABSSTP, RELSTP --> The initial step size in the search + is MAX(ABSSTP,RELSTP*ABS(X)). See algorithm. + ABSSTP is DOUBLE PRECISION + RELSTP is DOUBLE PRECISION + STPMUL --> When a step doesn't bound the zero, the step + size is multiplied by STPMUL and another step + taken. A popular value is 2.0 + DOUBLE PRECISION STPMUL + ABSTOL, RELTOL --> Two numbers that determine the accuracy + of the solution. See function for a precise definition. + ABSTOL is DOUBLE PRECISION + RELTOL is DOUBLE PRECISION + Method + Compares F(X) with Y for the input value of X then uses QINCR + to determine whether to step left or right to bound the + desired x. the initial step size is + MAX(ABSSTP,RELSTP*ABS(S)) for the input value of X. + Iteratively steps right or left until it bounds X. + At each step which doesn't bound X, the step size is doubled. + The routine is careful never to step beyond SMALL or BIG. If + it hasn't bounded X at SMALL or BIG, QMFINV returns .FALSE. + after setting QLEFT and QHI. + If X is successfully bounded then Algorithm R of the paper + 'Two Efficient Algorithms with Guaranteed Convergence for + Finding a Zero of a Function' by J. C. P. Bus and + T. J. Dekker in ACM Transactions on Mathematical + Software, Volume 1, No. 4 page 330 (DEC. '75) is employed + to find the zero of the function F(X)-Y. This is routine + QRZERO. +********************************************************************** +*/ +{ + E0000(1,NULL,NULL,NULL,NULL,NULL,zabsst,zabsto,zbig,zrelst,zrelto,zsmall, + zstpmu); +} /* END */ + +/***=====================================================================***/ +static double dlanor(double *x) +/* +********************************************************************** + + double dlanor(double *x) + Double precision Logarith of the Asymptotic Normal + + + Function + + + Computes the logarithm of the cumulative normal distribution + from abs( x ) to infinity for abs( x ) >= 5. + + + Arguments + + + X --> Value at which cumulative normal to be evaluated + DOUBLE PRECISION X + + + Method + + + 23 term expansion of formula 26.2.12 of Abramowitz and Stegun. + The relative error at X = 5 is about 0.5E-5. + + + Note + + + ABS(X) must be >= 5 else there is an error stop. + +********************************************************************** +*/ +{ +#define dlsqpi 0.91893853320467274177e0 +static double coef[12] = { + -1.0e0,3.0e0,-15.0e0,105.0e0,-945.0e0,10395.0e0,-135135.0e0,2027025.0e0, + -34459425.0e0,654729075.0e0,-13749310575.e0,316234143225.0e0 +}; +static int K1 = 12; +static double dlanor,approx,correc,xx,xx2,T2; +/* + .. + .. Executable Statements .. +*/ + xx = fabs(*x); + if(xx < 5.0e0){ ftnstop("Argument too small in DLANOR"); return 66.6; } + approx = -dlsqpi-0.5e0*xx*xx-log(xx); + xx2 = xx*xx; + T2 = 1.0e0/xx2; + correc = devlpl(coef,&K1,&T2)/xx2; + correc = dln1px(&correc); + dlanor = approx+correc; + return dlanor; +#undef dlsqpi +} /* END */ + +/***=====================================================================***/ +static double dln1mx(double *x) +/* +********************************************************************** + + double dln1mx(double *x) + Double precision LN(1-X) + + + Function + + + Returns ln(1-x) for small x (good accuracy if x .le. 0.1). + Note that the obvious code of + LOG(1.0-X) + won't work for small X because 1.0-X loses accuracy + + + Arguments + + + X --> Value for which ln(1-x) is desired. + X is DOUBLE PRECISION + + + Method + + + If X > 0.1, the obvious code above is used ELSE + The Taylor series for 1-x is expanded to 20 terms. + +********************************************************************** +*/ +{ +static double dln1mx,T1; +/* + .. + .. Executable Statements .. +*/ + T1 = -*x; + dln1mx = dln1px(&T1); + return dln1mx; +} /* END */ + +/***=====================================================================***/ +static double dln1px(double *a) +/* +********************************************************************** + + double dln1px(double *a) + Double precision LN(1+X) + + + Function + + + Returns ln(1+x) + Note that the obvious code of + LOG(1.0+X) + won't work for small X because 1.0+X loses accuracy + + + Arguments + + + X --> Value for which ln(1-x) is desired. + X is DOUBLE PRECISION + + + Method + + + Renames ALNREL from: + DiDinato, A. R. and Morris, A. H. Algorithm 708: Significant + Digit Computation of the Incomplete Beta Function Ratios. ACM + Trans. Math. Softw. 18 (1993), 360-373. + +********************************************************************** +----------------------------------------------------------------------- + EVALUATION OF THE FUNCTION LN(1 + A) +----------------------------------------------------------------------- +*/ +{ +static double p1 = -.129418923021993e+01; +static double p2 = .405303492862024e+00; +static double p3 = -.178874546012214e-01; +static double q1 = -.162752256355323e+01; +static double q2 = .747811014037616e+00; +static double q3 = -.845104217945565e-01; +static double dln1px,t,t2,w,x; +/* + .. + .. Executable Statements .. +*/ + if(fabs(*a) > 0.375e0) goto S10; + t = *a/(*a+2.0e0); + t2 = t*t; + w = (((p3*t2+p2)*t2+p1)*t2+1.0e0)/(((q3*t2+q2)*t2+q1)*t2+1.0e0); + dln1px = 2.0e0*t*w; + return dln1px; +S10: + x = 1.e0+*a; + dln1px = log(x); + return dln1px; +} /* END */ + +/***=====================================================================***/ +static double dlnbet(double *a0,double *b0) +/* +********************************************************************** + + double dlnbet(a0,b0) + Double precision LN of the complete BETa + + + Function + + + Returns the natural log of the complete beta function, + i.e., + + ln( Gamma(a)*Gamma(b) / Gamma(a+b) + + + Arguments + + + A,B --> The (symmetric) arguments to the complete beta + DOUBLE PRECISION A, B + + + Method + + + Renames BETALN from: + DiDinato, A. R. and Morris, A. H. Algorithm 708: Significant + Digit Computation of the Incomplete Beta Function Ratios. ACM + Trans. Math. Softw. 18 (1993), 360-373. + +********************************************************************** +----------------------------------------------------------------------- + EVALUATION OF THE LOGARITHM OF THE BETA FUNCTION +----------------------------------------------------------------------- + E = 0.5*LN(2*PI) +-------------------------- +*/ +{ +static double e = .918938533204673e0; +static double dlnbet,a,b,c,h,u,v,w,z; +static int i,n; +static double T1; +/* + .. + .. Executable Statements .. +*/ + a = fifdmin1(*a0,*b0); + b = fifdmax1(*a0,*b0); + if(a >= 8.0e0) goto S100; + if(a >= 1.0e0) goto S20; +/* +----------------------------------------------------------------------- + PROCEDURE WHEN A .LT. 1 +----------------------------------------------------------------------- +*/ + if(b >= 8.0e0) goto S10; + T1 = a+b; + dlnbet = gamln(&a)+(gamln(&b)-gamln(&T1)); + return dlnbet; +S10: + dlnbet = gamln(&a)+algdiv(&a,&b); + return dlnbet; +S20: +/* +----------------------------------------------------------------------- + PROCEDURE WHEN 1 .LE. A .LT. 8 +----------------------------------------------------------------------- +*/ + if(a > 2.0e0) goto S40; + if(b > 2.0e0) goto S30; + dlnbet = gamln(&a)+gamln(&b)-gsumln(&a,&b); + return dlnbet; +S30: + w = 0.0e0; + if(b < 8.0e0) goto S60; + dlnbet = gamln(&a)+algdiv(&a,&b); + return dlnbet; +S40: +/* + REDUCTION OF A WHEN B .LE. 1000 +*/ + if(b > 1000.0e0) goto S80; + n = a-1.0e0; + w = 1.0e0; + for(i=1; i<=n; i++) { + a -= 1.0e0; + h = a/b; + w *= (h/(1.0e0+h)); + } + w = log(w); + if(b < 8.0e0) goto S60; + dlnbet = w+gamln(&a)+algdiv(&a,&b); + return dlnbet; +S60: +/* + REDUCTION OF B WHEN B .LT. 8 +*/ + n = b-1.0e0; + z = 1.0e0; + for(i=1; i<=n; i++) { + b -= 1.0e0; + z *= (b/(a+b)); + } + dlnbet = w+log(z)+(gamln(&a)+(gamln(&b)-gsumln(&a,&b))); + return dlnbet; +S80: +/* + REDUCTION OF A WHEN B .GT. 1000 +*/ + n = a-1.0e0; + w = 1.0e0; + for(i=1; i<=n; i++) { + a -= 1.0e0; + w *= (a/(1.0e0+a/b)); + } + dlnbet = log(w)-(double)n*log(b)+(gamln(&a)+algdiv(&a,&b)); + return dlnbet; +S100: +/* +----------------------------------------------------------------------- + PROCEDURE WHEN A .GE. 8 +----------------------------------------------------------------------- +*/ + w = bcorr(&a,&b); + h = a/b; + c = h/(1.0e0+h); + u = -((a-0.5e0)*log(c)); + v = b*alnrel(&h); + if(u <= v) goto S110; + dlnbet = -(0.5e0*log(b))+e+w-v-u; + return dlnbet; +S110: + dlnbet = -(0.5e0*log(b))+e+w-u-v; + return dlnbet; +} /* END */ + +/***=====================================================================***/ +static double dlngam(double *a) +/* +********************************************************************** + + double dlngam(double *a) + Double precision LN of the GAMma function + + + Function + + + Returns the natural logarithm of GAMMA(X). + + + Arguments + + + X --> value at which scaled log gamma is to be returned + X is DOUBLE PRECISION + + + Method + + + Renames GAMLN from: + DiDinato, A. R. and Morris, A. H. Algorithm 708: Significant + Digit Computation of the Incomplete Beta Function Ratios. ACM + Trans. Math. Softw. 18 (1993), 360-373. + +********************************************************************** +----------------------------------------------------------------------- + EVALUATION OF LN(GAMMA(A)) FOR POSITIVE A +----------------------------------------------------------------------- + WRITTEN BY ALFRED H. MORRIS + NAVAL SURFACE WARFARE CENTER + DAHLGREN, VIRGINIA +-------------------------- + D = 0.5*(LN(2*PI) - 1) +-------------------------- +*/ +{ +static double c0 = .833333333333333e-01; +static double c1 = -.277777777760991e-02; +static double c2 = .793650666825390e-03; +static double c3 = -.595202931351870e-03; +static double c4 = .837308034031215e-03; +static double c5 = -.165322962780713e-02; +static double d = .418938533204673e0; +static double dlngam,t,w; +static int i,n; +static double T1; +/* + .. + .. Executable Statements .. +*/ + if(*a > 0.8e0) goto S10; + dlngam = gamln1(a)-log(*a); + return dlngam; +S10: + if(*a > 2.25e0) goto S20; + t = *a-0.5e0-0.5e0; + dlngam = gamln1(&t); + return dlngam; +S20: + if(*a >= 10.0e0) goto S40; + n = *a-1.25e0; + t = *a; + w = 1.0e0; + for(i=1; i<=n; i++) { + t -= 1.0e0; + w = t*w; + } + T1 = t-1.0e0; + dlngam = gamln1(&T1)+log(w); + return dlngam; +S40: + t = pow(1.0e0/ *a,2.0); + w = (((((c5*t+c4)*t+c3)*t+c2)*t+c1)*t+c0)/ *a; + dlngam = d+w+(*a-0.5e0)*(log(*a)-1.0e0); + return dlngam; +} /* END */ + +/***=====================================================================***/ +static double dstrem(double *z) +{ +/* +********************************************************************** + double dstrem(double *z) + Double precision Sterling Remainder + Function + Returns Log(Gamma(Z)) - Sterling(Z) where Sterling(Z) is + Sterling's Approximation to Log(Gamma(Z)) + Sterling(Z) = LOG( SQRT( 2*PI ) ) + ( Z-0.5 ) * LOG( Z ) - Z + Arguments + Z --> Value at which Sterling remainder calculated + Must be positive. + DOUBLE PRECISION Z + Method + If Z >= 6 uses 9 terms of series in Bernoulli numbers + (Values calculated using Maple) + Otherwise computes difference explicitly +********************************************************************** +*/ +#define hln2pi 0.91893853320467274178e0 +#define ncoef 10 +static double coef[ncoef] = { + 0.0e0,0.0833333333333333333333333333333e0, + -0.00277777777777777777777777777778e0,0.000793650793650793650793650793651e0, + -0.000595238095238095238095238095238e0, + 0.000841750841750841750841750841751e0,-0.00191752691752691752691752691753e0, + 0.00641025641025641025641025641026e0,-0.0295506535947712418300653594771e0, + 0.179644372368830573164938490016e0 +}; +static int K1 = 10; +static double dstrem,sterl,T2; +/* + .. + .. Executable Statements .. +*/ +/* + For information, here are the next 11 coefficients of the + remainder term in Sterling's formula + -1.39243221690590111642743221691 + 13.4028640441683919944789510007 + -156.848284626002017306365132452 + 2193.10333333333333333333333333 + -36108.7712537249893571732652192 + 691472.268851313067108395250776 + -0.152382215394074161922833649589D8 + 0.382900751391414141414141414141D9 + -0.108822660357843910890151491655D11 + 0.347320283765002252252252252252D12 + -0.123696021422692744542517103493D14 +*/ + if(*z <= 0.0e0){ ftnstop("nonpositive argument in DSTREM"); return 66.6; } + if(!(*z > 6.0e0)) goto S10; + T2 = 1.0e0/pow(*z,2.0); + dstrem = devlpl(coef,&K1,&T2)**z; + goto S20; +S10: + sterl = hln2pi+(*z-0.5e0)*log(*z)-*z; + dstrem = dlngam(z)-sterl; +S20: + return dstrem; +#undef hln2pi +#undef ncoef +} /* END */ + +/***=====================================================================***/ +static double dt1(double *p,double *q,double *df) +/* +********************************************************************** + + double dt1(double *p,double *q,double *df) + Double precision Initalize Approximation to + INVerse of the cumulative T distribution + + + Function + + + Returns the inverse of the T distribution function, i.e., + the integral from 0 to INVT of the T density is P. This is an + initial approximation + + + Arguments + + + P --> The p-value whose inverse from the T distribution is + desired. + P is DOUBLE PRECISION + + Q --> 1-P. + Q is DOUBLE PRECISION + + DF --> Degrees of freedom of the T distribution. + DF is DOUBLE PRECISION + +********************************************************************** +*/ +{ +static double coef[4][5] = { + 1.0e0,1.0e0,0.0e0,0.0e0,0.0e0,3.0e0,16.0e0,5.0e0,0.0e0,0.0e0,-15.0e0,17.0e0, + 19.0e0,3.0e0,0.0e0,-945.0e0,-1920.0e0,1482.0e0,776.0e0,79.0e0 +}; +static double denom[4] = { + 4.0e0,96.0e0,384.0e0,92160.0e0 +}; +static int ideg[4] = { + 2,3,4,5 +}; +static double dt1,denpow,sum,term,x,xp,xx; +static int i; +/* + .. + .. Executable Statements .. +*/ + x = fabs(dinvnr(p,q)); + xx = x*x; + sum = x; + denpow = 1.0e0; + for(i=0; i<4; i++) { + term = devlpl(&coef[i][0],&ideg[i],&xx)*x; + denpow *= *df; + sum += (term/(denpow*denom[i])); + } + if(!(*p >= 0.5e0)) goto S20; + xp = sum; + goto S30; +S20: + xp = -sum; +S30: + dt1 = xp; + return dt1; +} /* END */ + +/***=====================================================================***/ +static void E0001(int IENTRY,int *status,double *x,double *fx, + double *xlo,double *xhi,unsigned long *qleft, + unsigned long *qhi,double *zabstl,double *zreltl, + double *zxhi,double *zxlo) +{ +#define ftol(zx) (0.5e0*fifdmax1(abstol,reltol*fabs((zx)))) +static double a,abstol,b,c,d,fa,fb,fc,fd,fda,fdb,m,mb,p,q,reltol,tol,w,xxhi,xxlo; +static int ext,i99999; +static unsigned long first,qrzero; + switch(IENTRY){case 0: goto DZROR; case 1: goto DSTZR;} +DZROR: + if(*status > 0) goto S280; + *xlo = xxlo; + *xhi = xxhi; + b = *x = *xlo; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 1; + goto S270; +S10: + fb = *fx; + *xlo = *xhi; + a = *x = *xlo; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 2; + goto S270; +S20: +/* + Check that F(ZXLO) < 0 < F(ZXHI) or + F(ZXLO) > 0 > F(ZXHI) +*/ + if(!(fb < 0.0e0)) goto S40; + if(!(*fx < 0.0e0)) goto S30; + *status = -1; + *qleft = *fx < fb; + *qhi = 0; + return; +S40: +S30: + if(!(fb > 0.0e0)) goto S60; + if(!(*fx > 0.0e0)) goto S50; + *status = -1; + *qleft = *fx > fb; + *qhi = 1; + return; +S60: +S50: + fa = *fx; + first = 1; +S70: + c = a; + fc = fa; + ext = 0; +S80: + if(!(fabs(fc) < fabs(fb))) goto S100; + if(!(c != a)) goto S90; + d = a; + fd = fa; +S90: + a = b; + fa = fb; + *xlo = c; + b = *xlo; + fb = fc; + c = a; + fc = fa; +S100: + tol = ftol(*xlo); + m = (c+b)*.5e0; + mb = m-b; + if(!(fabs(mb) > tol)) goto S240; + if(!(ext > 3)) goto S110; + w = mb; + goto S190; +S110: + tol = fifdsign(tol,mb); + p = (b-a)*fb; + if(!first) goto S120; + q = fa-fb; + first = 0; + goto S130; +S120: + fdb = (fd-fb)/(d-b); + fda = (fd-fa)/(d-a); + p = fda*p; + q = fdb*fa-fda*fb; +S130: + if(!(p < 0.0e0)) goto S140; + p = -p; + q = -q; +S140: + if(ext == 3) p *= 2.0e0; + if(!(p*1.0e0 == 0.0e0 || p <= q*tol)) goto S150; + w = tol; + goto S180; +S150: + if(!(p < mb*q)) goto S160; + w = p/q; + goto S170; +S160: + w = mb; +S190: +S180: +S170: + d = a; + fd = fa; + a = b; + fa = fb; + b += w; + *xlo = b; + *x = *xlo; +/* + GET-FUNCTION-VALUE +*/ + i99999 = 3; + goto S270; +S200: + fb = *fx; + if(!(fc*fb >= 0.0e0)) goto S210; + goto S70; +S210: + if(!(w == mb)) goto S220; + ext = 0; + goto S230; +S220: + ext += 1; +S230: + goto S80; +S240: + *xhi = c; + qrzero = fc >= 0.0e0 && fb <= 0.0e0 || fc < 0.0e0 && fb >= 0.0e0; + if(!qrzero) goto S250; + *status = 0; + goto S260; +S250: + *status = -1; +S260: + return; +DSTZR: + xxlo = *zxlo; + xxhi = *zxhi; + abstol = *zabstl; + reltol = *zreltl; + return; +S270: +/* + TO GET-FUNCTION-VALUE +*/ + *status = 1; + return; +S280: + switch((int)i99999){case 1: goto S10;case 2: goto S20;case 3: goto S200; + default: break;} +#undef ftol +} /* END */ + +/***=====================================================================***/ +static void dzror(int *status,double *x,double *fx,double *xlo, + double *xhi,unsigned long *qleft,unsigned long *qhi) +/* +********************************************************************** + + void dzror(int *status,double *x,double *fx,double *xlo, + double *xhi,unsigned long *qleft,unsigned long *qhi) + + Double precision ZeRo of a function -- Reverse Communication + + + Function + + + Performs the zero finding. STZROR must have been called before + this routine in order to set its parameters. + + + Arguments + + + STATUS <--> At the beginning of a zero finding problem, STATUS + should be set to 0 and ZROR invoked. (The value + of other parameters will be ignored on this call.) + + When ZROR needs the function evaluated, it will set + STATUS to 1 and return. The value of the function + should be set in FX and ZROR again called without + changing any of its other parameters. + + When ZROR has finished without error, it will return + with STATUS 0. In that case (XLO,XHI) bound the answe + + If ZROR finds an error (which implies that F(XLO)-Y an + F(XHI)-Y have the same sign, it returns STATUS -1. In + this case, XLO and XHI are undefined. + INTEGER STATUS + + X <-- The value of X at which F(X) is to be evaluated. + DOUBLE PRECISION X + + FX --> The value of F(X) calculated when ZROR returns with + STATUS = 1. + DOUBLE PRECISION FX + + XLO <-- When ZROR returns with STATUS = 0, XLO bounds the + inverval in X containing the solution below. + DOUBLE PRECISION XLO + + XHI <-- When ZROR returns with STATUS = 0, XHI bounds the + inverval in X containing the solution above. + DOUBLE PRECISION XHI + + QLEFT <-- .TRUE. if the stepping search terminated unsucessfully + at XLO. If it is .FALSE. the search terminated + unsucessfully at XHI. + QLEFT is LOGICAL + + QHI <-- .TRUE. if F(X) .GT. Y at the termination of the + search and .FALSE. if F(X) .LT. Y at the + termination of the search. + QHI is LOGICAL + +********************************************************************** +*/ +{ + E0001(0,status,x,fx,xlo,xhi,qleft,qhi,NULL,NULL,NULL,NULL); +} /* END */ + +/***=====================================================================***/ +static void dstzr(double *zxlo,double *zxhi,double *zabstl,double *zreltl) +/* +********************************************************************** + void dstzr(double *zxlo,double *zxhi,double *zabstl,double *zreltl) + Double precision SeT ZeRo finder - Reverse communication version + Function + Sets quantities needed by ZROR. The function of ZROR + and the quantities set is given here. + Concise Description - Given a function F + find XLO such that F(XLO) = 0. + More Precise Description - + Input condition. F is a double precision function of a single + double precision argument and XLO and XHI are such that + F(XLO)*F(XHI) .LE. 0.0 + If the input condition is met, QRZERO returns .TRUE. + and output values of XLO and XHI satisfy the following + F(XLO)*F(XHI) .LE. 0. + ABS(F(XLO) .LE. ABS(F(XHI) + ABS(XLO-XHI) .LE. TOL(X) + where + TOL(X) = MAX(ABSTOL,RELTOL*ABS(X)) + If this algorithm does not find XLO and XHI satisfying + these conditions then QRZERO returns .FALSE. This + implies that the input condition was not met. + Arguments + XLO --> The left endpoint of the interval to be + searched for a solution. + XLO is DOUBLE PRECISION + XHI --> The right endpoint of the interval to be + for a solution. + XHI is DOUBLE PRECISION + ABSTOL, RELTOL --> Two numbers that determine the accuracy + of the solution. See function for a + precise definition. + ABSTOL is DOUBLE PRECISION + RELTOL is DOUBLE PRECISION + Method + Algorithm R of the paper 'Two Efficient Algorithms with + Guaranteed Convergence for Finding a Zero of a Function' + by J. C. P. Bus and T. J. Dekker in ACM Transactions on + Mathematical Software, Volume 1, no. 4 page 330 + (Dec. '75) is employed to find the zero of F(X)-Y. +********************************************************************** +*/ +{ + E0001(1,NULL,NULL,NULL,NULL,NULL,NULL,NULL,zabstl,zreltl,zxhi,zxlo); +} /* END */ + +/***=====================================================================***/ +static double erf1(double *x) +/* +----------------------------------------------------------------------- + EVALUATION OF THE REAL ERROR FUNCTION +----------------------------------------------------------------------- +*/ +{ +static double c = .564189583547756e0; +static double a[5] = { + .771058495001320e-04,-.133733772997339e-02,.323076579225834e-01, + .479137145607681e-01,.128379167095513e+00 +}; +static double b[3] = { + .301048631703895e-02,.538971687740286e-01,.375795757275549e+00 +}; +static double p[8] = { + -1.36864857382717e-07,5.64195517478974e-01,7.21175825088309e+00, + 4.31622272220567e+01,1.52989285046940e+02,3.39320816734344e+02, + 4.51918953711873e+02,3.00459261020162e+02 +}; +static double q[8] = { + 1.00000000000000e+00,1.27827273196294e+01,7.70001529352295e+01, + 2.77585444743988e+02,6.38980264465631e+02,9.31354094850610e+02, + 7.90950925327898e+02,3.00459260956983e+02 +}; +static double r[5] = { + 2.10144126479064e+00,2.62370141675169e+01,2.13688200555087e+01, + 4.65807828718470e+00,2.82094791773523e-01 +}; +static double s[4] = { + 9.41537750555460e+01,1.87114811799590e+02,9.90191814623914e+01, + 1.80124575948747e+01 +}; +static double erf1,ax,bot,t,top,x2; +/* + .. + .. Executable Statements .. +*/ + ax = fabs(*x); + if(ax > 0.5e0) goto S10; + t = *x**x; + top = (((a[0]*t+a[1])*t+a[2])*t+a[3])*t+a[4]+1.0e0; + bot = ((b[0]*t+b[1])*t+b[2])*t+1.0e0; + erf1 = *x*(top/bot); + return erf1; +S10: + if(ax > 4.0e0) goto S20; + top = ((((((p[0]*ax+p[1])*ax+p[2])*ax+p[3])*ax+p[4])*ax+p[5])*ax+p[6])*ax+p[ + 7]; + bot = ((((((q[0]*ax+q[1])*ax+q[2])*ax+q[3])*ax+q[4])*ax+q[5])*ax+q[6])*ax+q[ + 7]; + erf1 = 0.5e0+(0.5e0-exp(-(*x**x))*top/bot); + if(*x < 0.0e0) erf1 = -erf1; + return erf1; +S20: + if(ax >= 5.8e0) goto S30; + x2 = *x**x; + t = 1.0e0/x2; + top = (((r[0]*t+r[1])*t+r[2])*t+r[3])*t+r[4]; + bot = (((s[0]*t+s[1])*t+s[2])*t+s[3])*t+1.0e0; + erf1 = (c-top/(x2*bot))/ax; + erf1 = 0.5e0+(0.5e0-exp(-x2)*erf1); + if(*x < 0.0e0) erf1 = -erf1; + return erf1; +S30: + erf1 = fifdsign(1.0e0,*x); + return erf1; +} /* END */ + +/***=====================================================================***/ +static double erfc1(int *ind,double *x) +/* +----------------------------------------------------------------------- + EVALUATION OF THE COMPLEMENTARY ERROR FUNCTION + + ERFC1(IND,X) = ERFC(X) IF IND = 0 + ERFC1(IND,X) = EXP(X*X)*ERFC(X) OTHERWISE +----------------------------------------------------------------------- +*/ +{ +static double c = .564189583547756e0; +static double a[5] = { + .771058495001320e-04,-.133733772997339e-02,.323076579225834e-01, + .479137145607681e-01,.128379167095513e+00 +}; +static double b[3] = { + .301048631703895e-02,.538971687740286e-01,.375795757275549e+00 +}; +static double p[8] = { + -1.36864857382717e-07,5.64195517478974e-01,7.21175825088309e+00, + 4.31622272220567e+01,1.52989285046940e+02,3.39320816734344e+02, + 4.51918953711873e+02,3.00459261020162e+02 +}; +static double q[8] = { + 1.00000000000000e+00,1.27827273196294e+01,7.70001529352295e+01, + 2.77585444743988e+02,6.38980264465631e+02,9.31354094850610e+02, + 7.90950925327898e+02,3.00459260956983e+02 +}; +static double r[5] = { + 2.10144126479064e+00,2.62370141675169e+01,2.13688200555087e+01, + 4.65807828718470e+00,2.82094791773523e-01 +}; +static double s[4] = { + 9.41537750555460e+01,1.87114811799590e+02,9.90191814623914e+01, + 1.80124575948747e+01 +}; +static int K1 = 1; +static double erfc1,ax,bot,e,t,top,w; +/* + .. + .. Executable Statements .. +*/ +/* + ABS(X) .LE. 0.5 +*/ + ax = fabs(*x); + if(ax > 0.5e0) goto S10; + t = *x**x; + top = (((a[0]*t+a[1])*t+a[2])*t+a[3])*t+a[4]+1.0e0; + bot = ((b[0]*t+b[1])*t+b[2])*t+1.0e0; + erfc1 = 0.5e0+(0.5e0-*x*(top/bot)); + if(*ind != 0) erfc1 = exp(t)*erfc1; + return erfc1; +S10: +/* + 0.5 .LT. ABS(X) .LE. 4 +*/ + if(ax > 4.0e0) goto S20; + top = ((((((p[0]*ax+p[1])*ax+p[2])*ax+p[3])*ax+p[4])*ax+p[5])*ax+p[6])*ax+p[ + 7]; + bot = ((((((q[0]*ax+q[1])*ax+q[2])*ax+q[3])*ax+q[4])*ax+q[5])*ax+q[6])*ax+q[ + 7]; + erfc1 = top/bot; + goto S40; +S20: +/* + ABS(X) .GT. 4 +*/ + if(*x <= -5.6e0) goto S60; + if(*ind != 0) goto S30; + if(*x > 100.0e0) goto S70; + if(*x**x > -exparg(&K1)) goto S70; +S30: + t = pow(1.0e0/ *x,2.0); + top = (((r[0]*t+r[1])*t+r[2])*t+r[3])*t+r[4]; + bot = (((s[0]*t+s[1])*t+s[2])*t+s[3])*t+1.0e0; + erfc1 = (c-t*top/bot)/ax; +S40: +/* + FINAL ASSEMBLY +*/ + if(*ind == 0) goto S50; + if(*x < 0.0e0) erfc1 = 2.0e0*exp(*x**x)-erfc1; + return erfc1; +S50: + w = *x**x; + t = w; + e = w-t; + erfc1 = (0.5e0+(0.5e0-e))*exp(-t)*erfc1; + if(*x < 0.0e0) erfc1 = 2.0e0-erfc1; + return erfc1; +S60: +/* + LIMIT VALUE FOR LARGE NEGATIVE X +*/ + erfc1 = 2.0e0; + if(*ind != 0) erfc1 = 2.0e0*exp(*x**x); + return erfc1; +S70: +/* + LIMIT VALUE FOR LARGE POSITIVE X + WHEN IND = 0 +*/ + erfc1 = 0.0e0; + return erfc1; +} /* END */ + +/***=====================================================================***/ +static double esum(int *mu,double *x) +/* +----------------------------------------------------------------------- + EVALUATION OF EXP(MU + X) +----------------------------------------------------------------------- +*/ +{ +static double esum,w; +/* + .. + .. Executable Statements .. +*/ + if(*x > 0.0e0) goto S10; + if(*mu < 0) goto S20; + w = (double)*mu+*x; + if(w > 0.0e0) goto S20; + esum = exp(w); + return esum; +S10: + if(*mu > 0) goto S20; + w = (double)*mu+*x; + if(w < 0.0e0) goto S20; + esum = exp(w); + return esum; +S20: + w = *mu; + esum = exp(w)*exp(*x); + return esum; +} /* END */ + +/***=====================================================================***/ +static double exparg(int *l) +/* +-------------------------------------------------------------------- + IF L = 0 THEN EXPARG(L) = THE LARGEST POSITIVE W FOR WHICH + EXP(W) CAN BE COMPUTED. + + IF L IS NONZERO THEN EXPARG(L) = THE LARGEST NEGATIVE W FOR + WHICH THE COMPUTED VALUE OF EXP(W) IS NONZERO. + + NOTE... ONLY AN APPROXIMATE VALUE FOR EXPARG(L) IS NEEDED. +-------------------------------------------------------------------- +*/ +{ +static int K1 = 4; +static int K2 = 9; +static int K3 = 10; +static double exparg,lnb; +static int b,m; +/* + .. + .. Executable Statements .. +*/ + b = ipmpar(&K1); + if(b != 2) goto S10; + lnb = .69314718055995e0; + goto S40; +S10: + if(b != 8) goto S20; + lnb = 2.0794415416798e0; + goto S40; +S20: + if(b != 16) goto S30; + lnb = 2.7725887222398e0; + goto S40; +S30: + lnb = log((double)b); +S40: + if(*l == 0) goto S50; + m = ipmpar(&K2)-1; + exparg = 0.99999e0*((double)m*lnb); + return exparg; +S50: + m = ipmpar(&K3); + exparg = 0.99999e0*((double)m*lnb); + return exparg; +} /* END */ + +/***=====================================================================***/ +static double fpser(double *a,double *b,double *x,double *eps) +/* +----------------------------------------------------------------------- + + EVALUATION OF I (A,B) + X + + FOR B .LT. MIN(EPS,EPS*A) AND X .LE. 0.5. + +----------------------------------------------------------------------- + + SET FPSER = X**A +*/ +{ +static int K1 = 1; +static double fpser,an,c,s,t,tol; +/* + .. + .. Executable Statements .. +*/ + fpser = 1.0e0; + if(*a <= 1.e-3**eps) goto S10; + fpser = 0.0e0; + t = *a*log(*x); + if(t < exparg(&K1)) return fpser; + fpser = exp(t); +S10: +/* + NOTE THAT 1/B(A,B) = B +*/ + fpser = *b/ *a*fpser; + tol = *eps/ *a; + an = *a+1.0e0; + t = *x; + s = t/an; +S20: + an += 1.0e0; + t = *x*t; + c = t/an; + s += c; + if(fabs(c) > tol) goto S20; + fpser *= (1.0e0+*a*s); + return fpser; +} /* END */ + +/***=====================================================================***/ +static double gam1(double *a) +/* + ------------------------------------------------------------------ + COMPUTATION OF 1/GAMMA(A+1) - 1 FOR -0.5 .LE. A .LE. 1.5 + ------------------------------------------------------------------ +*/ +{ +static double s1 = .273076135303957e+00; +static double s2 = .559398236957378e-01; +static double p[7] = { + .577215664901533e+00,-.409078193005776e+00,-.230975380857675e+00, + .597275330452234e-01,.766968181649490e-02,-.514889771323592e-02, + .589597428611429e-03 +}; +static double q[5] = { + .100000000000000e+01,.427569613095214e+00,.158451672430138e+00, + .261132021441447e-01,.423244297896961e-02 +}; +static double r[9] = { + -.422784335098468e+00,-.771330383816272e+00,-.244757765222226e+00, + .118378989872749e+00,.930357293360349e-03,-.118290993445146e-01, + .223047661158249e-02,.266505979058923e-03,-.132674909766242e-03 +}; +static double gam1,bot,d,t,top,w,T1; +/* + .. + .. Executable Statements .. +*/ + t = *a; + d = *a-0.5e0; + if(d > 0.0e0) t = d-0.5e0; + T1 = t; + if(T1 < 0) goto S40; + else if(T1 == 0) goto S10; + else goto S20; +S10: + gam1 = 0.0e0; + return gam1; +S20: + top = (((((p[6]*t+p[5])*t+p[4])*t+p[3])*t+p[2])*t+p[1])*t+p[0]; + bot = (((q[4]*t+q[3])*t+q[2])*t+q[1])*t+1.0e0; + w = top/bot; + if(d > 0.0e0) goto S30; + gam1 = *a*w; + return gam1; +S30: + gam1 = t/ *a*(w-0.5e0-0.5e0); + return gam1; +S40: + top = (((((((r[8]*t+r[7])*t+r[6])*t+r[5])*t+r[4])*t+r[3])*t+r[2])*t+r[1])*t+ + r[0]; + bot = (s2*t+s1)*t+1.0e0; + w = top/bot; + if(d > 0.0e0) goto S50; + gam1 = *a*(w+0.5e0+0.5e0); + return gam1; +S50: + gam1 = t*w/ *a; + return gam1; +} /* END */ + +/***=====================================================================***/ +static void gaminv(double *a,double *x,double *x0,double *p,double *q, + int *ierr) +/* + ---------------------------------------------------------------------- + INVERSE INCOMPLETE GAMMA RATIO FUNCTION + + GIVEN POSITIVE A, AND NONEGATIVE P AND Q WHERE P + Q = 1. + THEN X IS COMPUTED WHERE P(A,X) = P AND Q(A,X) = Q. SCHRODER + ITERATION IS EMPLOYED. THE ROUTINE ATTEMPTS TO COMPUTE X + TO 10 SIGNIFICANT DIGITS IF THIS IS POSSIBLE FOR THE + PARTICULAR COMPUTER ARITHMETIC BEING USED. + + ------------ + + X IS A VARIABLE. IF P = 0 THEN X IS ASSIGNED THE VALUE 0, + AND IF Q = 0 THEN X IS SET TO THE LARGEST FLOATING POINT + NUMBER AVAILABLE. OTHERWISE, GAMINV ATTEMPTS TO OBTAIN + A SOLUTION FOR P(A,X) = P AND Q(A,X) = Q. IF THE ROUTINE + IS SUCCESSFUL THEN THE SOLUTION IS STORED IN X. + + X0 IS AN OPTIONAL INITIAL APPROXIMATION FOR X. IF THE USER + DOES NOT WISH TO SUPPLY AN INITIAL APPROXIMATION, THEN SET + X0 .LE. 0. + + IERR IS A VARIABLE THAT REPORTS THE STATUS OF THE RESULTS. + WHEN THE ROUTINE TERMINATES, IERR HAS ONE OF THE FOLLOWING + VALUES ... + + IERR = 0 THE SOLUTION WAS OBTAINED. ITERATION WAS + NOT USED. + IERR.GT.0 THE SOLUTION WAS OBTAINED. IERR ITERATIONS + WERE PERFORMED. + IERR = -2 (INPUT ERROR) A .LE. 0 + IERR = -3 NO SOLUTION WAS OBTAINED. THE RATIO Q/A + IS TOO LARGE. + IERR = -4 (INPUT ERROR) P + Q .NE. 1 + IERR = -6 20 ITERATIONS WERE PERFORMED. THE MOST + RECENT VALUE OBTAINED FOR X IS GIVEN. + THIS CANNOT OCCUR IF X0 .LE. 0. + IERR = -7 ITERATION FAILED. NO VALUE IS GIVEN FOR X. + THIS MAY OCCUR WHEN X IS APPROXIMATELY 0. + IERR = -8 A VALUE FOR X HAS BEEN OBTAINED, BUT THE + ROUTINE IS NOT CERTAIN OF ITS ACCURACY. + ITERATION CANNOT BE PERFORMED IN THIS + CASE. IF X0 .LE. 0, THIS CAN OCCUR ONLY + WHEN P OR Q IS APPROXIMATELY 0. IF X0 IS + POSITIVE THEN THIS CAN OCCUR WHEN A IS + EXCEEDINGLY CLOSE TO X AND A IS EXTREMELY + LARGE (SAY A .GE. 1.E20). + ---------------------------------------------------------------------- + WRITTEN BY ALFRED H. MORRIS, JR. + NAVAL SURFACE WEAPONS CENTER + DAHLGREN, VIRGINIA + ------------------- +*/ +{ +static double a0 = 3.31125922108741e0; +static double a1 = 11.6616720288968e0; +static double a2 = 4.28342155967104e0; +static double a3 = .213623493715853e0; +static double b1 = 6.61053765625462e0; +static double b2 = 6.40691597760039e0; +static double b3 = 1.27364489782223e0; +static double b4 = .036117081018842e0; +static double c = .577215664901533e0; +static double ln10 = 2.302585e0; +static double tol = 1.e-5; +static double amin[2] = { + 500.0e0,100.0e0 +}; +static double bmin[2] = { + 1.e-28,1.e-13 +}; +static double dmin[2] = { + 1.e-06,1.e-04 +}; +static double emin[2] = { + 2.e-03,6.e-03 +}; +static double eps0[2] = { + 1.e-10,1.e-08 +}; +static int K1 = 1; +static int K2 = 2; +static int K3 = 3; +static int K8 = 0; +static double am1,amax,ap1,ap2,ap3,apn,b,c1,c2,c3,c4,c5,d,e,e2,eps,g,h,pn,qg,qn, + r,rta,s,s2,sum,t,u,w,xmax,xmin,xn,y,z; +static int iop; +static double T4,T5,T6,T7,T9; +/* + .. + .. Executable Statements .. +*/ +/* + ****** E, XMIN, AND XMAX ARE MACHINE DEPENDENT CONSTANTS. + E IS THE SMALLEST NUMBER FOR WHICH 1.0 + E .GT. 1.0. + XMIN IS THE SMALLEST POSITIVE NUMBER AND XMAX IS THE + LARGEST POSITIVE NUMBER. +*/ + e = spmpar(&K1); + xmin = spmpar(&K2); + xmax = spmpar(&K3); + *x = 0.0e0; + if(*a <= 0.0e0) goto S300; + t = *p+*q-1.e0; + if(fabs(t) > e) goto S320; + *ierr = 0; + if(*p == 0.0e0) return; + if(*q == 0.0e0) goto S270; + if(*a == 1.0e0) goto S280; + e2 = 2.0e0*e; + amax = 0.4e-10/(e*e); + iop = 1; + if(e > 1.e-10) iop = 2; + eps = eps0[iop-1]; + xn = *x0; + if(*x0 > 0.0e0) goto S160; +/* + SELECTION OF THE INITIAL APPROXIMATION XN OF X + WHEN A .LT. 1 +*/ + if(*a > 1.0e0) goto S80; + T4 = *a+1.0e0; + g = Xgamm(&T4); + qg = *q*g; + if(qg == 0.0e0) goto S360; + b = qg/ *a; + if(qg > 0.6e0**a) goto S40; + if(*a >= 0.30e0 || b < 0.35e0) goto S10; + t = exp(-(b+c)); + u = t*exp(t); + xn = t*exp(u); + goto S160; +S10: + if(b >= 0.45e0) goto S40; + if(b == 0.0e0) goto S360; + y = -log(b); + s = 0.5e0+(0.5e0-*a); + z = log(y); + t = y-s*z; + if(b < 0.15e0) goto S20; + xn = y-s*log(t)-log(1.0e0+s/(t+1.0e0)); + goto S220; +S20: + if(b <= 0.01e0) goto S30; + u = ((t+2.0e0*(3.0e0-*a))*t+(2.0e0-*a)*(3.0e0-*a))/((t+(5.0e0-*a))*t+2.0e0); + xn = y-s*log(t)-log(u); + goto S220; +S30: + c1 = -(s*z); + c2 = -(s*(1.0e0+c1)); + c3 = s*((0.5e0*c1+(2.0e0-*a))*c1+(2.5e0-1.5e0**a)); + c4 = -(s*(((c1/3.0e0+(2.5e0-1.5e0**a))*c1+((*a-6.0e0)**a+7.0e0))*c1+( + (11.0e0**a-46.0)**a+47.0e0)/6.0e0)); + c5 = -(s*((((-(c1/4.0e0)+(11.0e0**a-17.0e0)/6.0e0)*c1+((-(3.0e0**a)+13.0e0)* + *a-13.0e0))*c1+0.5e0*(((2.0e0**a-25.0e0)**a+72.0e0)**a-61.0e0))*c1+(( + (25.0e0**a-195.0e0)**a+477.0e0)**a-379.0e0)/12.0e0)); + xn = (((c5/y+c4)/y+c3)/y+c2)/y+c1+y; + if(*a > 1.0e0) goto S220; + if(b > bmin[iop-1]) goto S220; + *x = xn; + return; +S40: + if(b**q > 1.e-8) goto S50; + xn = exp(-(*q/ *a+c)); + goto S70; +S50: + if(*p <= 0.9e0) goto S60; + T5 = -*q; + xn = exp((alnrel(&T5)+gamln1(a))/ *a); + goto S70; +S60: + xn = exp(log(*p*g)/ *a); +S70: + if(xn == 0.0e0) goto S310; + t = 0.5e0+(0.5e0-xn/(*a+1.0e0)); + xn /= t; + goto S160; +S80: +/* + SELECTION OF THE INITIAL APPROXIMATION XN OF X + WHEN A .GT. 1 +*/ + if(*q <= 0.5e0) goto S90; + w = log(*p); + goto S100; +S90: + w = log(*q); +S100: + t = sqrt(-(2.0e0*w)); + s = t-(((a3*t+a2)*t+a1)*t+a0)/((((b4*t+b3)*t+b2)*t+b1)*t+1.0e0); + if(*q > 0.5e0) s = -s; + rta = sqrt(*a); + s2 = s*s; + xn = *a+s*rta+(s2-1.0e0)/3.0e0+s*(s2-7.0e0)/(36.0e0*rta)-((3.0e0*s2+7.0e0)* + s2-16.0e0)/(810.0e0**a)+s*((9.0e0*s2+256.0e0)*s2-433.0e0)/(38880.0e0**a* + rta); + xn = fifdmax1(xn,0.0e0); + if(*a < amin[iop-1]) goto S110; + *x = xn; + d = 0.5e0+(0.5e0-*x/ *a); + if(fabs(d) <= dmin[iop-1]) return; +S110: + if(*p <= 0.5e0) goto S130; + if(xn < 3.0e0**a) goto S220; + y = -(w+gamln(a)); + d = fifdmax1(2.0e0,*a*(*a-1.0e0)); + if(y < ln10*d) goto S120; + s = 1.0e0-*a; + z = log(y); + goto S30; +S120: + t = *a-1.0e0; + T6 = -(t/(xn+1.0e0)); + xn = y+t*log(xn)-alnrel(&T6); + T7 = -(t/(xn+1.0e0)); + xn = y+t*log(xn)-alnrel(&T7); + goto S220; +S130: + ap1 = *a+1.0e0; + if(xn > 0.70e0*ap1) goto S170; + w += gamln(&ap1); + if(xn > 0.15e0*ap1) goto S140; + ap2 = *a+2.0e0; + ap3 = *a+3.0e0; + *x = exp((w+*x)/ *a); + *x = exp((w+*x-log(1.0e0+*x/ap1*(1.0e0+*x/ap2)))/ *a); + *x = exp((w+*x-log(1.0e0+*x/ap1*(1.0e0+*x/ap2)))/ *a); + *x = exp((w+*x-log(1.0e0+*x/ap1*(1.0e0+*x/ap2*(1.0e0+*x/ap3))))/ *a); + xn = *x; + if(xn > 1.e-2*ap1) goto S140; + if(xn <= emin[iop-1]*ap1) return; + goto S170; +S140: + apn = ap1; + t = xn/apn; + sum = 1.0e0+t; +S150: + apn += 1.0e0; + t *= (xn/apn); + sum += t; + if(t > 1.e-4) goto S150; + t = w-log(sum); + xn = exp((xn+t)/ *a); + xn *= (1.0e0-(*a*log(xn)-xn-t)/(*a-xn)); + goto S170; +S160: +/* + SCHRODER ITERATION USING P +*/ + if(*p > 0.5e0) goto S220; +S170: + if(*p <= 1.e10*xmin) goto S350; + am1 = *a-0.5e0-0.5e0; +S180: + if(*a <= amax) goto S190; + d = 0.5e0+(0.5e0-xn/ *a); + if(fabs(d) <= e2) goto S350; +S190: + if(*ierr >= 20) goto S330; + *ierr += 1; + gratio(a,&xn,&pn,&qn,&K8); + if(pn == 0.0e0 || qn == 0.0e0) goto S350; + r = rcomp(a,&xn); + if(r == 0.0e0) goto S350; + t = (pn-*p)/r; + w = 0.5e0*(am1-xn); + if(fabs(t) <= 0.1e0 && fabs(w*t) <= 0.1e0) goto S200; + *x = xn*(1.0e0-t); + if(*x <= 0.0e0) goto S340; + d = fabs(t); + goto S210; +S200: + h = t*(1.0e0+w*t); + *x = xn*(1.0e0-h); + if(*x <= 0.0e0) goto S340; + if(fabs(w) >= 1.0e0 && fabs(w)*t*t <= eps) return; + d = fabs(h); +S210: + xn = *x; + if(d > tol) goto S180; + if(d <= eps) return; + if(fabs(*p-pn) <= tol**p) return; + goto S180; +S220: +/* + SCHRODER ITERATION USING Q +*/ + if(*q <= 1.e10*xmin) goto S350; + am1 = *a-0.5e0-0.5e0; +S230: + if(*a <= amax) goto S240; + d = 0.5e0+(0.5e0-xn/ *a); + if(fabs(d) <= e2) goto S350; +S240: + if(*ierr >= 20) goto S330; + *ierr += 1; + gratio(a,&xn,&pn,&qn,&K8); + if(pn == 0.0e0 || qn == 0.0e0) goto S350; + r = rcomp(a,&xn); + if(r == 0.0e0) goto S350; + t = (*q-qn)/r; + w = 0.5e0*(am1-xn); + if(fabs(t) <= 0.1e0 && fabs(w*t) <= 0.1e0) goto S250; + *x = xn*(1.0e0-t); + if(*x <= 0.0e0) goto S340; + d = fabs(t); + goto S260; +S250: + h = t*(1.0e0+w*t); + *x = xn*(1.0e0-h); + if(*x <= 0.0e0) goto S340; + if(fabs(w) >= 1.0e0 && fabs(w)*t*t <= eps) return; + d = fabs(h); +S260: + xn = *x; + if(d > tol) goto S230; + if(d <= eps) return; + if(fabs(*q-qn) <= tol**q) return; + goto S230; +S270: +/* + SPECIAL CASES +*/ + *x = xmax; + return; +S280: + if(*q < 0.9e0) goto S290; + T9 = -*p; + *x = -alnrel(&T9); + return; +S290: + *x = -log(*q); + return; +S300: +/* + ERROR RETURN +*/ + *ierr = -2; + return; +S310: + *ierr = -3; + return; +S320: + *ierr = -4; + return; +S330: + *ierr = -6; + return; +S340: + *ierr = -7; + return; +S350: + *x = xn; + *ierr = -8; + return; +S360: + *x = xmax; + *ierr = -8; + return; +} /* END */ + +/***=====================================================================***/ +static double gamln(double *a) +/* +----------------------------------------------------------------------- + EVALUATION OF LN(GAMMA(A)) FOR POSITIVE A +----------------------------------------------------------------------- + WRITTEN BY ALFRED H. MORRIS + NAVAL SURFACE WARFARE CENTER + DAHLGREN, VIRGINIA +-------------------------- + D = 0.5*(LN(2*PI) - 1) +-------------------------- +*/ +{ +static double c0 = .833333333333333e-01; +static double c1 = -.277777777760991e-02; +static double c2 = .793650666825390e-03; +static double c3 = -.595202931351870e-03; +static double c4 = .837308034031215e-03; +static double c5 = -.165322962780713e-02; +static double d = .418938533204673e0; +static double gamln,t,w; +static int i,n; +static double T1; +/* + .. + .. Executable Statements .. +*/ + if(*a > 0.8e0) goto S10; + gamln = gamln1(a)-log(*a); + return gamln; +S10: + if(*a > 2.25e0) goto S20; + t = *a-0.5e0-0.5e0; + gamln = gamln1(&t); + return gamln; +S20: + if(*a >= 10.0e0) goto S40; + n = *a-1.25e0; + t = *a; + w = 1.0e0; + for(i=1; i<=n; i++) { + t -= 1.0e0; + w = t*w; + } + T1 = t-1.0e0; + gamln = gamln1(&T1)+log(w); + return gamln; +S40: + t = pow(1.0e0/ *a,2.0); + w = (((((c5*t+c4)*t+c3)*t+c2)*t+c1)*t+c0)/ *a; + gamln = d+w+(*a-0.5e0)*(log(*a)-1.0e0); + return gamln; +} /* END */ + +/***=====================================================================***/ +static double gamln1(double *a) +/* +----------------------------------------------------------------------- + EVALUATION OF LN(GAMMA(1 + A)) FOR -0.2 .LE. A .LE. 1.25 +----------------------------------------------------------------------- +*/ +{ +static double p0 = .577215664901533e+00; +static double p1 = .844203922187225e+00; +static double p2 = -.168860593646662e+00; +static double p3 = -.780427615533591e+00; +static double p4 = -.402055799310489e+00; +static double p5 = -.673562214325671e-01; +static double p6 = -.271935708322958e-02; +static double q1 = .288743195473681e+01; +static double q2 = .312755088914843e+01; +static double q3 = .156875193295039e+01; +static double q4 = .361951990101499e+00; +static double q5 = .325038868253937e-01; +static double q6 = .667465618796164e-03; +static double r0 = .422784335098467e+00; +static double r1 = .848044614534529e+00; +static double r2 = .565221050691933e+00; +static double r3 = .156513060486551e+00; +static double r4 = .170502484022650e-01; +static double r5 = .497958207639485e-03; +static double s1 = .124313399877507e+01; +static double s2 = .548042109832463e+00; +static double s3 = .101552187439830e+00; +static double s4 = .713309612391000e-02; +static double s5 = .116165475989616e-03; +static double gamln1,w,x; +/* + .. + .. Executable Statements .. +*/ + if(*a >= 0.6e0) goto S10; + w = ((((((p6**a+p5)**a+p4)**a+p3)**a+p2)**a+p1)**a+p0)/((((((q6**a+q5)**a+ + q4)**a+q3)**a+q2)**a+q1)**a+1.0e0); + gamln1 = -(*a*w); + return gamln1; +S10: + x = *a-0.5e0-0.5e0; + w = (((((r5*x+r4)*x+r3)*x+r2)*x+r1)*x+r0)/(((((s5*x+s4)*x+s3)*x+s2)*x+s1)*x + +1.0e0); + gamln1 = x*w; + return gamln1; +} /* END */ + +/***=====================================================================***/ +static double Xgamm(double *a) +/* +----------------------------------------------------------------------- + + EVALUATION OF THE GAMMA FUNCTION FOR REAL ARGUMENTS + + ----------- + + GAMMA(A) IS ASSIGNED THE VALUE 0 WHEN THE GAMMA FUNCTION CANNOT + BE COMPUTED. + +----------------------------------------------------------------------- + WRITTEN BY ALFRED H. MORRIS, JR. + NAVAL SURFACE WEAPONS CENTER + DAHLGREN, VIRGINIA +----------------------------------------------------------------------- +*/ +{ +static double d = .41893853320467274178e0; +static double pi = 3.1415926535898e0; +static double r1 = .820756370353826e-03; +static double r2 = -.595156336428591e-03; +static double r3 = .793650663183693e-03; +static double r4 = -.277777777770481e-02; +static double r5 = .833333333333333e-01; +static double p[7] = { + .539637273585445e-03,.261939260042690e-02,.204493667594920e-01, + .730981088720487e-01,.279648642639792e+00,.553413866010467e+00,1.0e0 +}; +static double q[7] = { + -.832979206704073e-03,.470059485860584e-02,.225211131035340e-01, + -.170458969313360e+00,-.567902761974940e-01,.113062953091122e+01,1.0e0 +}; +static int K2 = 3; +static int K3 = 0; +static double Xgamm,bot,g,lnx,s,t,top,w,x,z; +static int i,j,m,n,T1; +/* + .. + .. Executable Statements .. +*/ + Xgamm = 0.0e0; + x = *a; + if(fabs(*a) >= 15.0e0) goto S110; +/* +----------------------------------------------------------------------- + EVALUATION OF GAMMA(A) FOR ABS(A) .LT. 15 +----------------------------------------------------------------------- +*/ + t = 1.0e0; + m = fifidint(*a)-1; +/* + LET T BE THE PRODUCT OF A-J WHEN A .GE. 2 +*/ + T1 = m; + if(T1 < 0) goto S40; + else if(T1 == 0) goto S30; + else goto S10; +S10: + for(j=1; j<=m; j++) { + x -= 1.0e0; + t = x*t; + } +S30: + x -= 1.0e0; + goto S80; +S40: +/* + LET T BE THE PRODUCT OF A+J WHEN A .LT. 1 +*/ + t = *a; + if(*a > 0.0e0) goto S70; + m = -m-1; + if(m == 0) goto S60; + for(j=1; j<=m; j++) { + x += 1.0e0; + t = x*t; + } +S60: + x += (0.5e0+0.5e0); + t = x*t; + if(t == 0.0e0) return Xgamm; +S70: +/* + THE FOLLOWING CODE CHECKS IF 1/T CAN OVERFLOW. THIS + CODE MAY BE OMITTED IF DESIRED. +*/ + if(fabs(t) >= 1.e-30) goto S80; + if(fabs(t)*spmpar(&K2) <= 1.0001e0) return Xgamm; + Xgamm = 1.0e0/t; + return Xgamm; +S80: +/* + COMPUTE GAMMA(1 + X) FOR 0 .LE. X .LT. 1 +*/ + top = p[0]; + bot = q[0]; + for(i=1; i<7; i++) { + top = p[i]+x*top; + bot = q[i]+x*bot; + } + Xgamm = top/bot; +/* + TERMINATION +*/ + if(*a < 1.0e0) goto S100; + Xgamm *= t; + return Xgamm; +S100: + Xgamm /= t; + return Xgamm; +S110: +/* +----------------------------------------------------------------------- + EVALUATION OF GAMMA(A) FOR ABS(A) .GE. 15 +----------------------------------------------------------------------- +*/ + if(fabs(*a) >= 1.e3) return Xgamm; + if(*a > 0.0e0) goto S120; + x = -*a; + n = x; + t = x-(double)n; + if(t > 0.9e0) t = 1.0e0-t; + s = sin(pi*t)/pi; + if(fifmod(n,2) == 0) s = -s; + if(s == 0.0e0) return Xgamm; +S120: +/* + COMPUTE THE MODIFIED ASYMPTOTIC SUM +*/ + t = 1.0e0/(x*x); + g = ((((r1*t+r2)*t+r3)*t+r4)*t+r5)/x; +/* + ONE MAY REPLACE THE NEXT STATEMENT WITH LNX = ALOG(X) + BUT LESS ACCURACY WILL NORMALLY BE OBTAINED. +*/ + lnx = log(x); +/* + FINAL ASSEMBLY +*/ + z = x; + g = d+g+(z-0.5e0)*(lnx-1.e0); + w = g; + t = g-w; + if(w > 0.99999e0*exparg(&K3)) return Xgamm; + Xgamm = exp(w)*(1.0e0+t); + if(*a < 0.0e0) Xgamm = 1.0e0/(Xgamm*s)/x; + return Xgamm; +} /* END */ + +/***=====================================================================***/ +static void grat1(double *a,double *x,double *r,double *p,double *q, + double *eps) +{ +static int K2 = 0; +static double a2n,a2nm1,am0,an,an0,b2n,b2nm1,c,cma,g,h,j,l,sum,t,tol,w,z,T1,T3; +/* + .. + .. Executable Statements .. +*/ +/* +----------------------------------------------------------------------- + EVALUATION OF THE INCOMPLETE GAMMA RATIO FUNCTIONS + P(A,X) AND Q(A,X) + IT IS ASSUMED THAT A .LE. 1. EPS IS THE TOLERANCE TO BE USED. + THE INPUT ARGUMENT R HAS THE VALUE E**(-X)*X**A/GAMMA(A). +----------------------------------------------------------------------- +*/ + if(*a**x == 0.0e0) goto S120; + if(*a == 0.5e0) goto S100; + if(*x < 1.1e0) goto S10; + goto S60; +S10: +/* + TAYLOR SERIES FOR P(A,X)/X**A +*/ + an = 3.0e0; + c = *x; + sum = *x/(*a+3.0e0); + tol = 0.1e0**eps/(*a+1.0e0); +S20: + an += 1.0e0; + c = -(c*(*x/an)); + t = c/(*a+an); + sum += t; + if(fabs(t) > tol) goto S20; + j = *a**x*((sum/6.0e0-0.5e0/(*a+2.0e0))**x+1.0e0/(*a+1.0e0)); + z = *a*log(*x); + h = gam1(a); + g = 1.0e0+h; + if(*x < 0.25e0) goto S30; + if(*a < *x/2.59e0) goto S50; + goto S40; +S30: + if(z > -.13394e0) goto S50; +S40: + w = exp(z); + *p = w*g*(0.5e0+(0.5e0-j)); + *q = 0.5e0+(0.5e0-*p); + return; +S50: + l = rexp(&z); + w = 0.5e0+(0.5e0+l); + *q = (w*j-l)*g-h; + if(*q < 0.0e0) goto S90; + *p = 0.5e0+(0.5e0-*q); + return; +S60: +/* + CONTINUED FRACTION EXPANSION +*/ + a2nm1 = a2n = 1.0e0; + b2nm1 = *x; + b2n = *x+(1.0e0-*a); + c = 1.0e0; +S70: + a2nm1 = *x*a2n+c*a2nm1; + b2nm1 = *x*b2n+c*b2nm1; + am0 = a2nm1/b2nm1; + c += 1.0e0; + cma = c-*a; + a2n = a2nm1+cma*a2n; + b2n = b2nm1+cma*b2n; + an0 = a2n/b2n; + if(fabs(an0-am0) >= *eps*an0) goto S70; + *q = *r*an0; + *p = 0.5e0+(0.5e0-*q); + return; +S80: +/* + SPECIAL CASES +*/ + *p = 0.0e0; + *q = 1.0e0; + return; +S90: + *p = 1.0e0; + *q = 0.0e0; + return; +S100: + if(*x >= 0.25e0) goto S110; + T1 = sqrt(*x); + *p = erf1(&T1); + *q = 0.5e0+(0.5e0-*p); + return; +S110: + T3 = sqrt(*x); + *q = erfc1(&K2,&T3); + *p = 0.5e0+(0.5e0-*q); + return; +S120: + if(*x <= *a) goto S80; + goto S90; +} /* END */ + +/***=====================================================================***/ +static void gratio(double *a,double *x,double *ans,double *qans,int *ind) +/* + ---------------------------------------------------------------------- + EVALUATION OF THE INCOMPLETE GAMMA RATIO FUNCTIONS + P(A,X) AND Q(A,X) + + ---------- + + IT IS ASSUMED THAT A AND X ARE NONNEGATIVE, WHERE A AND X + ARE NOT BOTH 0. + + ANS AND QANS ARE VARIABLES. GRATIO ASSIGNS ANS THE VALUE + P(A,X) AND QANS THE VALUE Q(A,X). IND MAY BE ANY INTEGER. + IF IND = 0 THEN THE USER IS REQUESTING AS MUCH ACCURACY AS + POSSIBLE (UP TO 14 SIGNIFICANT DIGITS). OTHERWISE, IF + IND = 1 THEN ACCURACY IS REQUESTED TO WITHIN 1 UNIT OF THE + 6-TH SIGNIFICANT DIGIT, AND IF IND .NE. 0,1 THEN ACCURACY + IS REQUESTED TO WITHIN 1 UNIT OF THE 3RD SIGNIFICANT DIGIT. + + ERROR RETURN ... + ANS IS ASSIGNED THE VALUE 2 WHEN A OR X IS NEGATIVE, + WHEN A*X = 0, OR WHEN P(A,X) AND Q(A,X) ARE INDETERMINANT. + P(A,X) AND Q(A,X) ARE COMPUTATIONALLY INDETERMINANT WHEN + X IS EXCEEDINGLY CLOSE TO A AND A IS EXTREMELY LARGE. + ---------------------------------------------------------------------- + WRITTEN BY ALFRED H. MORRIS, JR. + NAVAL SURFACE WEAPONS CENTER + DAHLGREN, VIRGINIA + -------------------- +*/ +{ +static double alog10 = 2.30258509299405e0; +static double d10 = -.185185185185185e-02; +static double d20 = .413359788359788e-02; +static double d30 = .649434156378601e-03; +static double d40 = -.861888290916712e-03; +static double d50 = -.336798553366358e-03; +static double d60 = .531307936463992e-03; +static double d70 = .344367606892378e-03; +static double rt2pin = .398942280401433e0; +static double rtpi = 1.77245385090552e0; +static double third = .333333333333333e0; +static double acc0[3] = { + 5.e-15,5.e-7,5.e-4 +}; +static double big[3] = { + 20.0e0,14.0e0,10.0e0 +}; +static double d0[13] = { + .833333333333333e-01,-.148148148148148e-01,.115740740740741e-02, + .352733686067019e-03,-.178755144032922e-03,.391926317852244e-04, + -.218544851067999e-05,-.185406221071516e-05,.829671134095309e-06, + -.176659527368261e-06,.670785354340150e-08,.102618097842403e-07, + -.438203601845335e-08 +}; +static double d1[12] = { + -.347222222222222e-02,.264550264550265e-02,-.990226337448560e-03, + .205761316872428e-03,-.401877572016461e-06,-.180985503344900e-04, + .764916091608111e-05,-.161209008945634e-05,.464712780280743e-08, + .137863344691572e-06,-.575254560351770e-07,.119516285997781e-07 +}; +static double d2[10] = { + -.268132716049383e-02,.771604938271605e-03,.200938786008230e-05, + -.107366532263652e-03,.529234488291201e-04,-.127606351886187e-04, + .342357873409614e-07,.137219573090629e-05,-.629899213838006e-06, + .142806142060642e-06 +}; +static double d3[8] = { + .229472093621399e-03,-.469189494395256e-03,.267720632062839e-03, + -.756180167188398e-04,-.239650511386730e-06,.110826541153473e-04, + -.567495282699160e-05,.142309007324359e-05 +}; +static double d4[6] = { + .784039221720067e-03,-.299072480303190e-03,-.146384525788434e-05, + .664149821546512e-04,-.396836504717943e-04,.113757269706784e-04 +}; +static double d5[4] = { + -.697281375836586e-04,.277275324495939e-03,-.199325705161888e-03, + .679778047793721e-04 +}; +static double d6[2] = { + -.592166437353694e-03,.270878209671804e-03 +}; +static double e00[3] = { + .25e-3,.25e-1,.14e0 +}; +static double x00[3] = { + 31.0e0,17.0e0,9.7e0 +}; +static int K1 = 1; +static int K2 = 0; +static double a2n,a2nm1,acc,am0,amn,an,an0,apn,b2n,b2nm1,c,c0,c1,c2,c3,c4,c5,c6, + cma,e,e0,g,h,j,l,r,rta,rtx,s,sum,t,t1,tol,twoa,u,w,x0,y,z; +static int i,iop,m,max,n; +static double wk[20],T3; +static int T4,T5; +static double T6,T7; +/* + .. + .. Executable Statements .. +*/ +/* + -------------------- + ****** E IS A MACHINE DEPENDENT CONSTANT. E IS THE SMALLEST + FLOATING POINT NUMBER FOR WHICH 1.0 + E .GT. 1.0 . +*/ + e = spmpar(&K1); + if(*a < 0.0e0 || *x < 0.0e0) goto S430; + if(*a == 0.0e0 && *x == 0.0e0) goto S430; + if(*a**x == 0.0e0) goto S420; + iop = *ind+1; + if(iop != 1 && iop != 2) iop = 3; + acc = fifdmax1(acc0[iop-1],e); + e0 = e00[iop-1]; + x0 = x00[iop-1]; +/* + SELECT THE APPROPRIATE ALGORITHM +*/ + if(*a >= 1.0e0) goto S10; + if(*a == 0.5e0) goto S390; + if(*x < 1.1e0) goto S160; + t1 = *a*log(*x)-*x; + u = *a*exp(t1); + if(u == 0.0e0) goto S380; + r = u*(1.0e0+gam1(a)); + goto S250; +S10: + if(*a >= big[iop-1]) goto S30; + if(*a > *x || *x >= x0) goto S20; + twoa = *a+*a; + m = fifidint(twoa); + if(twoa != (double)m) goto S20; + i = m/2; + if(*a == (double)i) goto S210; + goto S220; +S20: + t1 = *a*log(*x)-*x; + r = exp(t1)/Xgamm(a); + goto S40; +S30: + l = *x/ *a; + if(l == 0.0e0) goto S370; + s = 0.5e0+(0.5e0-l); + z = rlog(&l); + if(z >= 700.0e0/ *a) goto S410; + y = *a*z; + rta = sqrt(*a); + if(fabs(s) <= e0/rta) goto S330; + if(fabs(s) <= 0.4e0) goto S270; + t = pow(1.0e0/ *a,2.0); + t1 = (((0.75e0*t-1.0e0)*t+3.5e0)*t-105.0e0)/(*a*1260.0e0); + t1 -= y; + r = rt2pin*rta*exp(t1); +S40: + if(r == 0.0e0) goto S420; + if(*x <= fifdmax1(*a,alog10)) goto S50; + if(*x < x0) goto S250; + goto S100; +S50: +/* + TAYLOR SERIES FOR P/R +*/ + apn = *a+1.0e0; + t = *x/apn; + wk[0] = t; + for(n=2; n<=20; n++) { + apn += 1.0e0; + t *= (*x/apn); + if(t <= 1.e-3) goto S70; + wk[n-1] = t; + } + n = 20; +S70: + sum = t; + tol = 0.5e0*acc; +S80: + apn += 1.0e0; + t *= (*x/apn); + sum += t; + if(t > tol) goto S80; + max = n-1; + for(m=1; m<=max; m++) { + n -= 1; + sum += wk[n-1]; + } + *ans = r/ *a*(1.0e0+sum); + *qans = 0.5e0+(0.5e0-*ans); + return; +S100: +/* + ASYMPTOTIC EXPANSION +*/ + amn = *a-1.0e0; + t = amn/ *x; + wk[0] = t; + for(n=2; n<=20; n++) { + amn -= 1.0e0; + t *= (amn/ *x); + if(fabs(t) <= 1.e-3) goto S120; + wk[n-1] = t; + } + n = 20; +S120: + sum = t; +S130: + if(fabs(t) <= acc) goto S140; + amn -= 1.0e0; + t *= (amn/ *x); + sum += t; + goto S130; +S140: + max = n-1; + for(m=1; m<=max; m++) { + n -= 1; + sum += wk[n-1]; + } + *qans = r/ *x*(1.0e0+sum); + *ans = 0.5e0+(0.5e0-*qans); + return; +S160: +/* + TAYLOR SERIES FOR P(A,X)/X**A +*/ + an = 3.0e0; + c = *x; + sum = *x/(*a+3.0e0); + tol = 3.0e0*acc/(*a+1.0e0); +S170: + an += 1.0e0; + c = -(c*(*x/an)); + t = c/(*a+an); + sum += t; + if(fabs(t) > tol) goto S170; + j = *a**x*((sum/6.0e0-0.5e0/(*a+2.0e0))**x+1.0e0/(*a+1.0e0)); + z = *a*log(*x); + h = gam1(a); + g = 1.0e0+h; + if(*x < 0.25e0) goto S180; + if(*a < *x/2.59e0) goto S200; + goto S190; +S180: + if(z > -.13394e0) goto S200; +S190: + w = exp(z); + *ans = w*g*(0.5e0+(0.5e0-j)); + *qans = 0.5e0+(0.5e0-*ans); + return; +S200: + l = rexp(&z); + w = 0.5e0+(0.5e0+l); + *qans = (w*j-l)*g-h; + if(*qans < 0.0e0) goto S380; + *ans = 0.5e0+(0.5e0-*qans); + return; +S210: +/* + FINITE SUMS FOR Q WHEN A .GE. 1 + AND 2*A IS AN INTEGER +*/ + sum = exp(-*x); + t = sum; + n = 1; + c = 0.0e0; + goto S230; +S220: + rtx = sqrt(*x); + sum = erfc1(&K2,&rtx); + t = exp(-*x)/(rtpi*rtx); + n = 0; + c = -0.5e0; +S230: + if(n == i) goto S240; + n += 1; + c += 1.0e0; + t = *x*t/c; + sum += t; + goto S230; +S240: + *qans = sum; + *ans = 0.5e0+(0.5e0-*qans); + return; +S250: +/* + CONTINUED FRACTION EXPANSION +*/ + tol = fifdmax1(5.0e0*e,acc); + a2nm1 = a2n = 1.0e0; + b2nm1 = *x; + b2n = *x+(1.0e0-*a); + c = 1.0e0; +S260: + a2nm1 = *x*a2n+c*a2nm1; + b2nm1 = *x*b2n+c*b2nm1; + am0 = a2nm1/b2nm1; + c += 1.0e0; + cma = c-*a; + a2n = a2nm1+cma*a2n; + b2n = b2nm1+cma*b2n; + an0 = a2n/b2n; + if(fabs(an0-am0) >= tol*an0) goto S260; + *qans = r*an0; + *ans = 0.5e0+(0.5e0-*qans); + return; +S270: +/* + GENERAL TEMME EXPANSION +*/ + if(fabs(s) <= 2.0e0*e && *a*e*e > 3.28e-3) goto S430; + c = exp(-y); + T3 = sqrt(y); + w = 0.5e0*erfc1(&K1,&T3); + u = 1.0e0/ *a; + z = sqrt(z+z); + if(l < 1.0e0) z = -z; + T4 = iop-2; + if(T4 < 0) goto S280; + else if(T4 == 0) goto S290; + else goto S300; +S280: + if(fabs(s) <= 1.e-3) goto S340; + c0 = ((((((((((((d0[12]*z+d0[11])*z+d0[10])*z+d0[9])*z+d0[8])*z+d0[7])*z+d0[ + 6])*z+d0[5])*z+d0[4])*z+d0[3])*z+d0[2])*z+d0[1])*z+d0[0])*z-third; + c1 = (((((((((((d1[11]*z+d1[10])*z+d1[9])*z+d1[8])*z+d1[7])*z+d1[6])*z+d1[5] + )*z+d1[4])*z+d1[3])*z+d1[2])*z+d1[1])*z+d1[0])*z+d10; + c2 = (((((((((d2[9]*z+d2[8])*z+d2[7])*z+d2[6])*z+d2[5])*z+d2[4])*z+d2[3])*z+ + d2[2])*z+d2[1])*z+d2[0])*z+d20; + c3 = (((((((d3[7]*z+d3[6])*z+d3[5])*z+d3[4])*z+d3[3])*z+d3[2])*z+d3[1])*z+ + d3[0])*z+d30; + c4 = (((((d4[5]*z+d4[4])*z+d4[3])*z+d4[2])*z+d4[1])*z+d4[0])*z+d40; + c5 = (((d5[3]*z+d5[2])*z+d5[1])*z+d5[0])*z+d50; + c6 = (d6[1]*z+d6[0])*z+d60; + t = ((((((d70*u+c6)*u+c5)*u+c4)*u+c3)*u+c2)*u+c1)*u+c0; + goto S310; +S290: + c0 = (((((d0[5]*z+d0[4])*z+d0[3])*z+d0[2])*z+d0[1])*z+d0[0])*z-third; + c1 = (((d1[3]*z+d1[2])*z+d1[1])*z+d1[0])*z+d10; + c2 = d2[0]*z+d20; + t = (c2*u+c1)*u+c0; + goto S310; +S300: + t = ((d0[2]*z+d0[1])*z+d0[0])*z-third; +S310: + if(l < 1.0e0) goto S320; + *qans = c*(w+rt2pin*t/rta); + *ans = 0.5e0+(0.5e0-*qans); + return; +S320: + *ans = c*(w-rt2pin*t/rta); + *qans = 0.5e0+(0.5e0-*ans); + return; +S330: +/* + TEMME EXPANSION FOR L = 1 +*/ + if(*a*e*e > 3.28e-3) goto S430; + c = 0.5e0+(0.5e0-y); + w = (0.5e0-sqrt(y)*(0.5e0+(0.5e0-y/3.0e0))/rtpi)/c; + u = 1.0e0/ *a; + z = sqrt(z+z); + if(l < 1.0e0) z = -z; + T5 = iop-2; + if(T5 < 0) goto S340; + else if(T5 == 0) goto S350; + else goto S360; +S340: + c0 = ((((((d0[6]*z+d0[5])*z+d0[4])*z+d0[3])*z+d0[2])*z+d0[1])*z+d0[0])*z- + third; + c1 = (((((d1[5]*z+d1[4])*z+d1[3])*z+d1[2])*z+d1[1])*z+d1[0])*z+d10; + c2 = ((((d2[4]*z+d2[3])*z+d2[2])*z+d2[1])*z+d2[0])*z+d20; + c3 = (((d3[3]*z+d3[2])*z+d3[1])*z+d3[0])*z+d30; + c4 = (d4[1]*z+d4[0])*z+d40; + c5 = (d5[1]*z+d5[0])*z+d50; + c6 = d6[0]*z+d60; + t = ((((((d70*u+c6)*u+c5)*u+c4)*u+c3)*u+c2)*u+c1)*u+c0; + goto S310; +S350: + c0 = (d0[1]*z+d0[0])*z-third; + c1 = d1[0]*z+d10; + t = (d20*u+c1)*u+c0; + goto S310; +S360: + t = d0[0]*z-third; + goto S310; +S370: +/* + SPECIAL CASES +*/ + *ans = 0.0e0; + *qans = 1.0e0; + return; +S380: + *ans = 1.0e0; + *qans = 0.0e0; + return; +S390: + if(*x >= 0.25e0) goto S400; + T6 = sqrt(*x); + *ans = erf1(&T6); + *qans = 0.5e0+(0.5e0-*ans); + return; +S400: + T7 = sqrt(*x); + *qans = erfc1(&K2,&T7); + *ans = 0.5e0+(0.5e0-*qans); + return; +S410: + if(fabs(s) <= 2.0e0*e) goto S430; +S420: + if(*x <= *a) goto S370; + goto S380; +S430: +/* + ERROR RETURN +*/ + *ans = 2.0e0; + return; +} /* END */ + +/***=====================================================================***/ +static double gsumln(double *a,double *b) +/* +----------------------------------------------------------------------- + EVALUATION OF THE FUNCTION LN(GAMMA(A + B)) + FOR 1 .LE. A .LE. 2 AND 1 .LE. B .LE. 2 +----------------------------------------------------------------------- +*/ +{ +static double gsumln,x,T1,T2; +/* + .. + .. Executable Statements .. +*/ + x = *a+*b-2.e0; + if(x > 0.25e0) goto S10; + T1 = 1.0e0+x; + gsumln = gamln1(&T1); + return gsumln; +S10: + if(x > 1.25e0) goto S20; + gsumln = gamln1(&x)+alnrel(&x); + return gsumln; +S20: + T2 = x-1.0e0; + gsumln = gamln1(&T2)+log(x*(1.0e0+x)); + return gsumln; +} /* END */ + +/***=====================================================================***/ +static double psi(double *xx) +/* +--------------------------------------------------------------------- + + EVALUATION OF THE DIGAMMA FUNCTION + + ----------- + + PSI(XX) IS ASSIGNED THE VALUE 0 WHEN THE DIGAMMA FUNCTION CANNOT + BE COMPUTED. + + THE MAIN COMPUTATION INVOLVES EVALUATION OF RATIONAL CHEBYSHEV + APPROXIMATIONS PUBLISHED IN MATH. COMP. 27, 123-127(1973) BY + CODY, STRECOK AND THACHER. + +--------------------------------------------------------------------- + PSI WAS WRITTEN AT ARGONNE NATIONAL LABORATORY FOR THE FUNPACK + PACKAGE OF SPECIAL FUNCTION SUBROUTINES. PSI WAS MODIFIED BY + A.H. MORRIS (NSWC). +--------------------------------------------------------------------- +*/ +{ +static double dx0 = 1.461632144968362341262659542325721325e0; +static double piov4 = .785398163397448e0; +static double p1[7] = { + .895385022981970e-02,.477762828042627e+01,.142441585084029e+03, + .118645200713425e+04,.363351846806499e+04,.413810161269013e+04, + .130560269827897e+04 +}; +static double p2[4] = { + -.212940445131011e+01,-.701677227766759e+01,-.448616543918019e+01, + -.648157123766197e+00 +}; +static double q1[6] = { + .448452573429826e+02,.520752771467162e+03,.221000799247830e+04, + .364127349079381e+04,.190831076596300e+04,.691091682714533e-05 +}; +static double q2[4] = { + .322703493791143e+02,.892920700481861e+02,.546117738103215e+02, + .777788548522962e+01 +}; +static int K1 = 3; +static int K2 = 1; +static double psi,aug,den,sgn,upper,w,x,xmax1,xmx0,xsmall,z; +static int i,m,n,nq; +/* + .. + .. Executable Statements .. +*/ +/* +--------------------------------------------------------------------- + MACHINE DEPENDENT CONSTANTS ... + XMAX1 = THE SMALLEST POSITIVE FLOATING POINT CONSTANT + WITH ENTIRELY INTEGER REPRESENTATION. ALSO USED + AS NEGATIVE OF LOWER BOUND ON ACCEPTABLE NEGATIVE + ARGUMENTS AND AS THE POSITIVE ARGUMENT BEYOND WHICH + PSI MAY BE REPRESENTED AS ALOG(X). + XSMALL = ABSOLUTE ARGUMENT BELOW WHICH PI*COTAN(PI*X) + MAY BE REPRESENTED BY 1/X. +--------------------------------------------------------------------- +*/ + xmax1 = ipmpar(&K1); + xmax1 = fifdmin1(xmax1,1.0e0/spmpar(&K2)); + xsmall = 1.e-9; + x = *xx; + aug = 0.0e0; + if(x >= 0.5e0) goto S50; +/* +--------------------------------------------------------------------- + X .LT. 0.5, USE REFLECTION FORMULA + PSI(1-X) = PSI(X) + PI * COTAN(PI*X) +--------------------------------------------------------------------- +*/ + if(fabs(x) > xsmall) goto S10; + if(x == 0.0e0) goto S100; +/* +--------------------------------------------------------------------- + 0 .LT. ABS(X) .LE. XSMALL. USE 1/X AS A SUBSTITUTE + FOR PI*COTAN(PI*X) +--------------------------------------------------------------------- +*/ + aug = -(1.0e0/x); + goto S40; +S10: +/* +--------------------------------------------------------------------- + REDUCTION OF ARGUMENT FOR COTAN +--------------------------------------------------------------------- +*/ + w = -x; + sgn = piov4; + if(w > 0.0e0) goto S20; + w = -w; + sgn = -sgn; +S20: +/* +--------------------------------------------------------------------- + MAKE AN ERROR EXIT IF X .LE. -XMAX1 +--------------------------------------------------------------------- +*/ + if(w >= xmax1) goto S100; + nq = fifidint(w); + w -= (double)nq; + nq = fifidint(w*4.0e0); + w = 4.0e0*(w-(double)nq*.25e0); +/* +--------------------------------------------------------------------- + W IS NOW RELATED TO THE FRACTIONAL PART OF 4.0 * X. + ADJUST ARGUMENT TO CORRESPOND TO VALUES IN FIRST + QUADRANT AND DETERMINE SIGN +--------------------------------------------------------------------- +*/ + n = nq/2; + if(n+n != nq) w = 1.0e0-w; + z = piov4*w; + m = n/2; + if(m+m != n) sgn = -sgn; +/* +--------------------------------------------------------------------- + DETERMINE FINAL VALUE FOR -PI*COTAN(PI*X) +--------------------------------------------------------------------- +*/ + n = (nq+1)/2; + m = n/2; + m += m; + if(m != n) goto S30; +/* +--------------------------------------------------------------------- + CHECK FOR SINGULARITY +--------------------------------------------------------------------- +*/ + if(z == 0.0e0) goto S100; +/* +--------------------------------------------------------------------- + USE COS/SIN AS A SUBSTITUTE FOR COTAN, AND + SIN/COS AS A SUBSTITUTE FOR TAN +--------------------------------------------------------------------- +*/ + aug = sgn*(cos(z)/sin(z)*4.0e0); + goto S40; +S30: + aug = sgn*(sin(z)/cos(z)*4.0e0); +S40: + x = 1.0e0-x; +S50: + if(x > 3.0e0) goto S70; +/* +--------------------------------------------------------------------- + 0.5 .LE. X .LE. 3.0 +--------------------------------------------------------------------- +*/ + den = x; + upper = p1[0]*x; + for(i=1; i<=5; i++) { + den = (den+q1[i-1])*x; + upper = (upper+p1[i+1-1])*x; + } + den = (upper+p1[6])/(den+q1[5]); + xmx0 = x-dx0; + psi = den*xmx0+aug; + return psi; +S70: +/* +--------------------------------------------------------------------- + IF X .GE. XMAX1, PSI = LN(X) +--------------------------------------------------------------------- +*/ + if(x >= xmax1) goto S90; +/* +--------------------------------------------------------------------- + 3.0 .LT. X .LT. XMAX1 +--------------------------------------------------------------------- +*/ + w = 1.0e0/(x*x); + den = w; + upper = p2[0]*w; + for(i=1; i<=3; i++) { + den = (den+q2[i-1])*w; + upper = (upper+p2[i+1-1])*w; + } + aug = upper/(den+q2[3])-0.5e0/x+aug; +S90: + psi = aug+log(x); + return psi; +S100: +/* +--------------------------------------------------------------------- + ERROR RETURN +--------------------------------------------------------------------- +*/ + psi = 0.0e0; + return psi; +} /* END */ + +/***=====================================================================***/ +static double rcomp(double *a,double *x) +/* + ------------------- + EVALUATION OF EXP(-X)*X**A/GAMMA(A) + ------------------- + RT2PIN = 1/SQRT(2*PI) + ------------------- +*/ +{ +static double rt2pin = .398942280401433e0; +static double rcomp,t,t1,u; +/* + .. + .. Executable Statements .. +*/ + rcomp = 0.0e0; + if(*a >= 20.0e0) goto S20; + t = *a*log(*x)-*x; + if(*a >= 1.0e0) goto S10; + rcomp = *a*exp(t)*(1.0e0+gam1(a)); + return rcomp; +S10: + rcomp = exp(t)/Xgamm(a); + return rcomp; +S20: + u = *x/ *a; + if(u == 0.0e0) return rcomp; + t = pow(1.0e0/ *a,2.0); + t1 = (((0.75e0*t-1.0e0)*t+3.5e0)*t-105.0e0)/(*a*1260.0e0); + t1 -= (*a*rlog(&u)); + rcomp = rt2pin*sqrt(*a)*exp(t1); + return rcomp; +} /* END */ + +/***=====================================================================***/ +static double rexp(double *x) +/* +----------------------------------------------------------------------- + EVALUATION OF THE FUNCTION EXP(X) - 1 +----------------------------------------------------------------------- +*/ +{ +static double p1 = .914041914819518e-09; +static double p2 = .238082361044469e-01; +static double q1 = -.499999999085958e+00; +static double q2 = .107141568980644e+00; +static double q3 = -.119041179760821e-01; +static double q4 = .595130811860248e-03; +static double rexp,w; +/* + .. + .. Executable Statements .. +*/ + if(fabs(*x) > 0.15e0) goto S10; + rexp = *x*(((p2**x+p1)**x+1.0e0)/((((q4**x+q3)**x+q2)**x+q1)**x+1.0e0)); + return rexp; +S10: + w = exp(*x); + if(*x > 0.0e0) goto S20; + rexp = w-0.5e0-0.5e0; + return rexp; +S20: + rexp = w*(0.5e0+(0.5e0-1.0e0/w)); + return rexp; +} /* END */ + +/***=====================================================================***/ +static double rlog(double *x) +/* + ------------------- + COMPUTATION OF X - 1 - LN(X) + ------------------- +*/ +{ +static double a = .566749439387324e-01; +static double b = .456512608815524e-01; +static double p0 = .333333333333333e+00; +static double p1 = -.224696413112536e+00; +static double p2 = .620886815375787e-02; +static double q1 = -.127408923933623e+01; +static double q2 = .354508718369557e+00; +static double rlog,r,t,u,w,w1; +/* + .. + .. Executable Statements .. +*/ + if(*x < 0.61e0 || *x > 1.57e0) goto S40; + if(*x < 0.82e0) goto S10; + if(*x > 1.18e0) goto S20; +/* + ARGUMENT REDUCTION +*/ + u = *x-0.5e0-0.5e0; + w1 = 0.0e0; + goto S30; +S10: + u = *x-0.7e0; + u /= 0.7e0; + w1 = a-u*0.3e0; + goto S30; +S20: + u = 0.75e0**x-1.e0; + w1 = b+u/3.0e0; +S30: +/* + SERIES EXPANSION +*/ + r = u/(u+2.0e0); + t = r*r; + w = ((p2*t+p1)*t+p0)/((q2*t+q1)*t+1.0e0); + rlog = 2.0e0*t*(1.0e0/(1.0e0-r)-r*w)+w1; + return rlog; +S40: + r = *x-0.5e0-0.5e0; + rlog = r-log(*x); + return rlog; +} /* END */ + +/***=====================================================================***/ +static double rlog1(double *x) +/* +----------------------------------------------------------------------- + EVALUATION OF THE FUNCTION X - LN(1 + X) +----------------------------------------------------------------------- +*/ +{ +static double a = .566749439387324e-01; +static double b = .456512608815524e-01; +static double p0 = .333333333333333e+00; +static double p1 = -.224696413112536e+00; +static double p2 = .620886815375787e-02; +static double q1 = -.127408923933623e+01; +static double q2 = .354508718369557e+00; +static double rlog1,h,r,t,w,w1; +/* + .. + .. Executable Statements .. +*/ + if(*x < -0.39e0 || *x > 0.57e0) goto S40; + if(*x < -0.18e0) goto S10; + if(*x > 0.18e0) goto S20; +/* + ARGUMENT REDUCTION +*/ + h = *x; + w1 = 0.0e0; + goto S30; +S10: + h = *x+0.3e0; + h /= 0.7e0; + w1 = a-h*0.3e0; + goto S30; +S20: + h = 0.75e0**x-0.25e0; + w1 = b+h/3.0e0; +S30: +/* + SERIES EXPANSION +*/ + r = h/(h+2.0e0); + t = r*r; + w = ((p2*t+p1)*t+p0)/((q2*t+q1)*t+1.0e0); + rlog1 = 2.0e0*t*(1.0e0/(1.0e0-r)-r*w)+w1; + return rlog1; +S40: + w = *x+0.5e0+0.5e0; + rlog1 = *x-log(w); + return rlog1; +} /* END */ + +/***=====================================================================***/ +static double spmpar(int *i) +/* +----------------------------------------------------------------------- + + SPMPAR PROVIDES THE SINGLE PRECISION MACHINE CONSTANTS FOR + THE COMPUTER BEING USED. IT IS ASSUMED THAT THE ARGUMENT + I IS AN INTEGER HAVING ONE OF THE VALUES 1, 2, OR 3. IF THE + SINGLE PRECISION ARITHMETIC BEING USED HAS M BASE B DIGITS AND + ITS SMALLEST AND LARGEST EXPONENTS ARE EMIN AND EMAX, THEN + + SPMPAR(1) = B**(1 - M), THE MACHINE PRECISION, + + SPMPAR(2) = B**(EMIN - 1), THE SMALLEST MAGNITUDE, + + SPMPAR(3) = B**EMAX*(1 - B**(-M)), THE LARGEST MAGNITUDE. + +----------------------------------------------------------------------- + WRITTEN BY + ALFRED H. MORRIS, JR. + NAVAL SURFACE WARFARE CENTER + DAHLGREN VIRGINIA +----------------------------------------------------------------------- +----------------------------------------------------------------------- + MODIFIED BY BARRY W. BROWN TO RETURN DOUBLE PRECISION MACHINE + CONSTANTS FOR THE COMPUTER BEING USED. THIS MODIFICATION WAS + MADE AS PART OF CONVERTING BRATIO TO DOUBLE PRECISION +----------------------------------------------------------------------- +*/ +{ +static int K1 = 4; +static int K2 = 8; +static int K3 = 9; +static int K4 = 10; +static double spmpar,b,binv,bm1,one,w,z; +static int emax,emin,ibeta,m; +/* + .. + .. Executable Statements .. +*/ + if(*i > 1) goto S10; + b = ipmpar(&K1); + m = ipmpar(&K2); + spmpar = pow(b,(double)(1-m)); + return spmpar; +S10: + if(*i > 2) goto S20; + b = ipmpar(&K1); + emin = ipmpar(&K3); + one = 1.0; + binv = one/b; + w = pow(b,(double)(emin+2)); + spmpar = w*binv*binv*binv; + return spmpar; +S20: + ibeta = ipmpar(&K1); + m = ipmpar(&K2); + emax = ipmpar(&K4); + b = ibeta; + bm1 = ibeta-1; + one = 1.0; + z = pow(b,(double)(m-1)); + w = ((z-one)*b+bm1)/(b*z); + z = pow(b,(double)(emax-2)); + spmpar = w*z*b*b; + return spmpar; +} /* END */ + +/***=====================================================================***/ +static double stvaln(double *p) +/* +********************************************************************** + + double stvaln(double *p) + STarting VALue for Neton-Raphon + calculation of Normal distribution Inverse + + + Function + + + Returns X such that CUMNOR(X) = P, i.e., the integral from - + infinity to X of (1/SQRT(2*PI)) EXP(-U*U/2) dU is P + + + Arguments + + + P --> The probability whose normal deviate is sought. + P is DOUBLE PRECISION + + + Method + + + The rational function on page 95 of Kennedy and Gentle, + Statistical Computing, Marcel Dekker, NY , 1980. + +********************************************************************** +*/ +{ +static double xden[5] = { + 0.993484626060e-1,0.588581570495e0,0.531103462366e0,0.103537752850e0, + 0.38560700634e-2 +}; +static double xnum[5] = { + -0.322232431088e0,-1.000000000000e0,-0.342242088547e0,-0.204231210245e-1, + -0.453642210148e-4 +}; +static int K1 = 5; +static double stvaln,sign,y,z; +/* + .. + .. Executable Statements .. +*/ + if(!(*p <= 0.5e0)) goto S10; + sign = -1.0e0; + z = *p; + goto S20; +S10: + sign = 1.0e0; + z = 1.0e0-*p; +S20: + y = sqrt(-(2.0e0*log(z))); + stvaln = y+devlpl(xnum,&K1,&y)/devlpl(xden,&K1,&y); + stvaln = sign*stvaln; + return stvaln; +} /* END */ + +/***=====================================================================***/ +static double fifdint(double a) +/************************************************************************ +FIFDINT: +Truncates a double precision number to an integer and returns the +value in a double. +************************************************************************/ +/* a - number to be truncated */ +{ + return (double) ((int) a); +} /* END */ + +/***=====================================================================***/ +static double fifdmax1(double a,double b) +/************************************************************************ +FIFDMAX1: +returns the maximum of two numbers a and b +************************************************************************/ +/* a - first number */ +/* b - second number */ +{ + if (a < b) return b; + else return a; +} /* END */ + +/***=====================================================================***/ +static double fifdmin1(double a,double b) +/************************************************************************ +FIFDMIN1: +returns the minimum of two numbers a and b +************************************************************************/ +/* a - first number */ +/* b - second number */ +{ + if (a < b) return a; + else return b; +} /* END */ + +/***=====================================================================***/ +static double fifdsign(double mag,double sign) +/************************************************************************ +FIFDSIGN: +transfers the sign of the variable "sign" to the variable "mag" +************************************************************************/ +/* mag - magnitude */ +/* sign - sign to be transfered */ +{ + if (mag < 0) mag = -mag; + if (sign < 0) mag = -mag; + return mag; + +} /* END */ + +/***=====================================================================***/ +static long fifidint(double a) +/************************************************************************ +FIFIDINT: +Truncates a double precision number to a long integer +************************************************************************/ +/* a - number to be truncated */ +{ + if (a < 1.0) return (long) 0; + else return (long) a; +} /* END */ + +/***=====================================================================***/ +static long fifmod(long a,long b) +/************************************************************************ +FIFMOD: +returns the modulo of a and b +************************************************************************/ +/* a - numerator */ +/* b - denominator */ +{ + return a % b; +} /* END */ + +/***=====================================================================***/ +static void ftnstop(char* msg) +/************************************************************************ +FTNSTOP: +Prints msg to standard error and then exits +************************************************************************/ +/* msg - error message */ +{ + if (msg != NULL) fprintf(stderr,"*** CDFLIB ERROR: %s\n",msg); + /** exit(1); **/ /** RWCox - DON'T EXIT */ +} /* END */ + +/***=====================================================================***/ +static int ipmpar(int *i) +/* +----------------------------------------------------------------------- + + IPMPAR PROVIDES THE INTEGER MACHINE CONSTANTS FOR THE COMPUTER + THAT IS USED. IT IS ASSUMED THAT THE ARGUMENT I IS AN INTEGER + HAVING ONE OF THE VALUES 1-10. IPMPAR(I) HAS THE VALUE ... + + INTEGERS. + + ASSUME INTEGERS ARE REPRESENTED IN THE N-DIGIT, BASE-A FORM + + SIGN ( X(N-1)*A**(N-1) + ... + X(1)*A + X(0) ) + + WHERE 0 .LE. X(I) .LT. A FOR I=0,...,N-1. + + IPMPAR(1) = A, THE BASE. + + IPMPAR(2) = N, THE NUMBER OF BASE-A DIGITS. + + IPMPAR(3) = A**N - 1, THE LARGEST MAGNITUDE. + + FLOATING-POINT NUMBERS. + + IT IS ASSUMED THAT THE SINGLE AND DOUBLE PRECISION FLOATING + POINT ARITHMETICS HAVE THE SAME BASE, SAY B, AND THAT THE + NONZERO NUMBERS ARE REPRESENTED IN THE FORM + + SIGN (B**E) * (X(1)/B + ... + X(M)/B**M) + + WHERE X(I) = 0,1,...,B-1 FOR I=1,...,M, + X(1) .GE. 1, AND EMIN .LE. E .LE. EMAX. + + IPMPAR(4) = B, THE BASE. + + SINGLE-PRECISION + + IPMPAR(5) = M, THE NUMBER OF BASE-B DIGITS. + + IPMPAR(6) = EMIN, THE SMALLEST EXPONENT E. + + IPMPAR(7) = EMAX, THE LARGEST EXPONENT E. + + DOUBLE-PRECISION + + IPMPAR(8) = M, THE NUMBER OF BASE-B DIGITS. + + IPMPAR(9) = EMIN, THE SMALLEST EXPONENT E. + + IPMPAR(10) = EMAX, THE LARGEST EXPONENT E. + +----------------------------------------------------------------------- + + TO DEFINE THIS FUNCTION FOR THE COMPUTER BEING USED REMOVE + THE COMMENT DELIMITORS FROM THE DEFINITIONS DIRECTLY BELOW THE NAME + OF THE MACHINE + +*** RWCox: at this time, the IEEE parameters are enabled. + +----------------------------------------------------------------------- + + IPMPAR IS AN ADAPTATION OF THE FUNCTION I1MACH, WRITTEN BY + P.A. FOX, A.D. HALL, AND N.L. SCHRYER (BELL LABORATORIES). + IPMPAR WAS FORMED BY A.H. MORRIS (NSWC). THE CONSTANTS ARE + FROM BELL LABORATORIES, NSWC, AND OTHER SOURCES. + +----------------------------------------------------------------------- + .. Scalar Arguments .. +*/ +{ +static int imach[11]; +static int outval ; +/* MACHINE CONSTANTS FOR AMDAHL MACHINES. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 16; + imach[5] = 6; + imach[6] = -64; + imach[7] = 63; + imach[8] = 14; + imach[9] = -64; + imach[10] = 63; +*/ +/* MACHINE CONSTANTS FOR THE AT&T 3B SERIES, AT&T + PC 7300, AND AT&T 6300. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR THE BURROUGHS 1700 SYSTEM. */ +/* + imach[1] = 2; + imach[2] = 33; + imach[3] = 8589934591; + imach[4] = 2; + imach[5] = 24; + imach[6] = -256; + imach[7] = 255; + imach[8] = 60; + imach[9] = -256; + imach[10] = 255; +*/ +/* MACHINE CONSTANTS FOR THE BURROUGHS 5700 SYSTEM. */ +/* + imach[1] = 2; + imach[2] = 39; + imach[3] = 549755813887; + imach[4] = 8; + imach[5] = 13; + imach[6] = -50; + imach[7] = 76; + imach[8] = 26; + imach[9] = -50; + imach[10] = 76; +*/ +/* MACHINE CONSTANTS FOR THE BURROUGHS 6700/7700 SYSTEMS. */ +/* + imach[1] = 2; + imach[2] = 39; + imach[3] = 549755813887; + imach[4] = 8; + imach[5] = 13; + imach[6] = -50; + imach[7] = 76; + imach[8] = 26; + imach[9] = -32754; + imach[10] = 32780; +*/ +/* MACHINE CONSTANTS FOR THE CDC 6000/7000 SERIES + 60 BIT ARITHMETIC, AND THE CDC CYBER 995 64 BIT + ARITHMETIC (NOS OPERATING SYSTEM). */ +/* + imach[1] = 2; + imach[2] = 48; + imach[3] = 281474976710655; + imach[4] = 2; + imach[5] = 48; + imach[6] = -974; + imach[7] = 1070; + imach[8] = 95; + imach[9] = -926; + imach[10] = 1070; +*/ +/* MACHINE CONSTANTS FOR THE CDC CYBER 995 64 BIT + ARITHMETIC (NOS/VE OPERATING SYSTEM). */ +/* + imach[1] = 2; + imach[2] = 63; + imach[3] = 9223372036854775807; + imach[4] = 2; + imach[5] = 48; + imach[6] = -4096; + imach[7] = 4095; + imach[8] = 96; + imach[9] = -4096; + imach[10] = 4095; +*/ +/* MACHINE CONSTANTS FOR THE CRAY 1, XMP, 2, AND 3. */ +/* + imach[1] = 2; + imach[2] = 63; + imach[3] = 9223372036854775807; + imach[4] = 2; + imach[5] = 47; + imach[6] = -8189; + imach[7] = 8190; + imach[8] = 94; + imach[9] = -8099; + imach[10] = 8190; +*/ +/* MACHINE CONSTANTS FOR THE DATA GENERAL ECLIPSE S/200. */ +/* + imach[1] = 2; + imach[2] = 15; + imach[3] = 32767; + imach[4] = 16; + imach[5] = 6; + imach[6] = -64; + imach[7] = 63; + imach[8] = 14; + imach[9] = -64; + imach[10] = 63; +*/ +/* MACHINE CONSTANTS FOR THE HARRIS 220. */ +/* + imach[1] = 2; + imach[2] = 23; + imach[3] = 8388607; + imach[4] = 2; + imach[5] = 23; + imach[6] = -127; + imach[7] = 127; + imach[8] = 38; + imach[9] = -127; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE HONEYWELL 600/6000 + AND DPS 8/70 SERIES. */ +/* + imach[1] = 2; + imach[2] = 35; + imach[3] = 34359738367; + imach[4] = 2; + imach[5] = 27; + imach[6] = -127; + imach[7] = 127; + imach[8] = 63; + imach[9] = -127; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE HP 2100 + 3 WORD DOUBLE PRECISION OPTION WITH FTN4 */ +/* + imach[1] = 2; + imach[2] = 15; + imach[3] = 32767; + imach[4] = 2; + imach[5] = 23; + imach[6] = -128; + imach[7] = 127; + imach[8] = 39; + imach[9] = -128; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE HP 2100 + 4 WORD DOUBLE PRECISION OPTION WITH FTN4 */ +/* + imach[1] = 2; + imach[2] = 15; + imach[3] = 32767; + imach[4] = 2; + imach[5] = 23; + imach[6] = -128; + imach[7] = 127; + imach[8] = 55; + imach[9] = -128; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE HP 9000. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -126; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR THE IBM 360/370 SERIES, + THE ICL 2900, THE ITEL AS/6, THE XEROX SIGMA + 5/7/9 AND THE SEL SYSTEMS 85/86. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 16; + imach[5] = 6; + imach[6] = -64; + imach[7] = 63; + imach[8] = 14; + imach[9] = -64; + imach[10] = 63; +*/ +/* MACHINE CONSTANTS FOR THE IBM PC. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR THE MACINTOSH II - ABSOFT + MACFORTRAN II. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR THE MICROVAX - VMS FORTRAN. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -127; + imach[7] = 127; + imach[8] = 56; + imach[9] = -127; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE PDP-10 (KA PROCESSOR). */ +/* + imach[1] = 2; + imach[2] = 35; + imach[3] = 34359738367; + imach[4] = 2; + imach[5] = 27; + imach[6] = -128; + imach[7] = 127; + imach[8] = 54; + imach[9] = -101; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE PDP-10 (KI PROCESSOR). */ +/* + imach[1] = 2; + imach[2] = 35; + imach[3] = 34359738367; + imach[4] = 2; + imach[5] = 27; + imach[6] = -128; + imach[7] = 127; + imach[8] = 62; + imach[9] = -128; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE PDP-11 FORTRAN SUPPORTING + 32-BIT INTEGER ARITHMETIC. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -127; + imach[7] = 127; + imach[8] = 56; + imach[9] = -127; + imach[10] = 127; +*/ +/* MACHINE CONSTANTS FOR THE SEQUENT BALANCE 8000. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR THE SILICON GRAPHICS IRIS-4D + SERIES (MIPS R3000 PROCESSOR). */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; +*/ +/* MACHINE CONSTANTS FOR IEEE ARITHMETIC MACHINES, SUCH AS THE AT&T + 3B SERIES, MOTOROLA 68000 BASED MACHINES (E.G. SUN 3 AND AT&T + PC 7300), AND 8087 BASED MICROS (E.G. IBM PC AND AT&T 6300). */ + + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -125; + imach[7] = 128; + imach[8] = 53; + imach[9] = -1021; + imach[10] = 1024; + +/* MACHINE CONSTANTS FOR THE UNIVAC 1100 SERIES. */ +/* + imach[1] = 2; + imach[2] = 35; + imach[3] = 34359738367; + imach[4] = 2; + imach[5] = 27; + imach[6] = -128; + imach[7] = 127; + imach[8] = 60; + imach[9] = -1024; + imach[10] = 1023; +*/ +/* MACHINE CONSTANTS FOR THE VAX 11/780. */ +/* + imach[1] = 2; + imach[2] = 31; + imach[3] = 2147483647; + imach[4] = 2; + imach[5] = 24; + imach[6] = -127; + imach[7] = 127; + imach[8] = 56; + imach[9] = -127; + imach[10] = 127; +*/ + outval = imach[*i]; + return outval ; +} + +/*************************************************************************/ +/*************************************************************************/ +/************************ End of cdflib inclusion ************************/ +/*************************************************************************/ +/*************************************************************************/ + +/*-----------------------------------------------------------------------*/ +typedef struct { double p,q ; } pqpair ; /* for returning p=cdf q=1-cdf */ +/*-----------------------------------------------------------------------*/ +#undef BIGG +#define BIGG 9.99e+37 /* a really big number (duh) */ +/*-----------------------------------------------------------------------*/ + +/*************************************************************************/ +/******** Internal functions for various statistical computations ********/ +/*************************************************************************/ + +/*--------------------------------------------------------------- + F statistic +-----------------------------------------------------------------*/ + +static double fstat_pq2s( pqpair pq , double dofnum , double dofden ) +{ + int which , status ; + double p , q , f , dfn , dfd , bound ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return BIGG ; + f = 0.0 ; + dfn = dofnum ; + dfd = dofden ; + + cdff( &which , &p , &q , &f , &dfn , &dfd , &status , &bound ) ; + return f ; +} + +/*------------------------------*/ + +static pqpair fstat_s2pq( double ff , double dofnum , double dofden ) +{ + int which , status ; + double p , q , f , dfn , dfd , bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + f = ff ; if( f <= 0.0 ) return pq; + dfn = dofnum ; if( dfn <= 0.0 ) return pq ; + dfd = dofden ; if( dfd <= 0.0 ) return pq ; + + cdff( &which , &p , &q , &f , &dfn , &dfd , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*--------------------------------------------------------------- + noncentral F statistic +-----------------------------------------------------------------*/ + +static double fnonc_pq2s( pqpair pq , double dofnum , double dofden , double nonc ) +{ + int which , status ; + double p , q , f , dfn , dfd , bound , pnonc ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return BIGG ; + f = 0.0 ; + dfn = dofnum ; + dfd = dofden ; + pnonc = nonc ; + + cdffnc( &which , &p , &q , &f , &dfn , &dfd , &pnonc , &status , &bound ) ; + return f ; +} + +/*------------------------------*/ + +static pqpair fnonc_s2pq( double ff , double dofnum , double dofden , double nonc ) +{ + int which , status ; + double p , q , f , dfn , dfd , bound , pnonc ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + f = ff ; if( f <= 0.0 ) return pq ; + dfn = dofnum ; if( dfn <= 0.0 ) return pq ; + dfd = dofden ; if( dfd <= 0.0 ) return pq ; + pnonc = nonc ; if( pnonc < 0.0 ) return pq ; + + cdffnc( &which , &p , &q , &f , &dfn , &dfd , &pnonc , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*--------------------------------------------------------------- + Standard Normal distribution +-----------------------------------------------------------------*/ + +static pqpair normal_s2pq( double zz ) +{ + double p , q , x=zz ; + pqpair pq ; + + cumnor( &x, &p, &q ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double normal_pq2s( pqpair pq ) +{ + double p=pq.p , q=pq.q ; + + if( p <= 0.0 ) return -BIGG ; + if( q <= 0.0 ) return BIGG ; + return dinvnr( &p,&q ) ; +} + +/*---------------------------------------------------------------- + Chi-square +------------------------------------------------------------------*/ + +static pqpair chisq_s2pq( double xx , double dof ) +{ + int which , status ; + double p,q,x,df,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + x = xx ; if( x <= 0.0 ) return pq ; + df = dof ; if( dof <= 0.0 ) return pq ; + + cdfchi( &which , &p , &q , &x , &df , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double chisq_pq2s( pqpair pq , double dof ) +{ + int which , status ; + double p,q,x,df,bound ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return BIGG ; + x = 0.0 ; + df = dof ; + + cdfchi( &which , &p , &q , &x , &df , &status , &bound ) ; + return x ; +} + +/*---------------------------------------------------------------- + noncentral Chi-square +------------------------------------------------------------------*/ + +static pqpair chsqnonc_s2pq( double xx , double dof , double nonc ) +{ + int which , status ; + double p,q,x,df,bound , pnonc ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + x = xx ; if( x <= 0.0 ) return pq ; + df = dof ; if( df <= 0.0 ) return pq ; + pnonc = nonc ; if( pnonc < 0.0 ) return pq ; + + cdfchn( &which , &p , &q , &x , &df , &pnonc , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double chsqnonc_pq2s( pqpair pq , double dof , double nonc ) +{ + int which , status ; + double p,q,x,df,bound , pnonc ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return BIGG ; + x = 0.0 ; + df = dof ; + pnonc = nonc ; + + cdfchn( &which , &p , &q , &x , &df , &pnonc , &status , &bound ) ; + return x ; +} + +/*---------------------------------------------------------------- + Beta distribution +------------------------------------------------------------------*/ + +static pqpair beta_s2pq( double xx , double aa , double bb ) +{ + int which , status ; + double p,q,x,y,a,b,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + x = xx ; if( x <= 0.0 ) return pq ; + y = 1.0 - xx ; if( y <= 0.0 ){ pq.p=1.0; pq.q=0.0; return pq; } + a = aa ; if( a < 0.0 ) return pq ; + b = bb ; if( b < 0.0 ) return pq ; + + cdfbet( &which , &p , &q , &x , &y , &a , &b , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double beta_pq2s( pqpair pq , double aa , double bb ) +{ + int which , status ; + double p,q,x,y,a,b,bound ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return 1.0 ; + x = 0.0 ; + y = 1.0 ; + a = aa ; + b = bb ; + + cdfbet( &which , &p , &q , &x , &y , &a , &b , &status , &bound ) ; + return x ; +} + +/*---------------------------------------------------------------- + Binomial distribution + (that is, the probability that more than ss out of ntrial + trials were successful). +------------------------------------------------------------------*/ + +static pqpair binomial_s2pq( double ss , double ntrial , double ptrial ) +{ + int which , status ; + double p,q, s,xn,pr,ompr,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + s = ss ; if( s < 0.0 ) return pq ; + xn = ntrial ; if( xn <= 0.0 ) return pq ; + pr = ptrial ; if( pr < 0.0 ) return pq ; + ompr = 1.0 - ptrial ; + + cdfbin( &which , &p , &q , &s , &xn , &pr , &ompr , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double binomial_pq2s( pqpair pq , double ntrial , double ptrial ) +{ + int which , status ; + double p,q, s,xn,pr,ompr,bound ; + + which = 2 ; + p = pq.p ; + q = pq.q ; + s = 0.0 ; + xn = ntrial ; + pr = ptrial ; + ompr = 1.0 - ptrial ; + + cdfbin( &which , &p , &q , &s , &xn , &pr , &ompr , &status , &bound ) ; + return s ; +} + +/*---------------------------------------------------------------- + Gamma distribution. +------------------------------------------------------------------*/ + +static pqpair gamma_s2pq( double xx , double sh , double sc ) +{ + int which , status ; + double p,q, x,shape,scale,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + x = xx ; if( x <= 0.0 ) return pq ; + shape = sh ; if( shape <= 0.0 ) return pq ; + scale = sc ; if( scale <= 0.0 ) return pq ; + + cdfgam( &which , &p , &q , &x , &shape , &scale , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double gamma_pq2s( pqpair pq , double sh , double sc ) +{ + int which , status ; + double p,q, x,shape,scale,bound ; + + which = 2 ; + p = pq.p ; if( p <= 0.0 ) return 0.0 ; + q = pq.q ; if( q <= 0.0 ) return BIGG ; + x = 0.0 ; + shape = sh ; + scale = sc ; + + cdfgam( &which , &p , &q , &x , &shape , &scale , &status , &bound ) ; + return x ; +} + +/*---------------------------------------------------------------- + Poisson distribution +------------------------------------------------------------------*/ + +static pqpair poisson_s2pq( double xx , double lambda ) +{ + int which , status ; + double p,q, s,xlam,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + s = xx ; if( s < 0.0 ) return pq ; + xlam = lambda ; if( xlam < 0.0 ) return pq ; + + cdfpoi( &which , &p , &q , &s , &xlam , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double poisson_pq2s( pqpair pq , double lambda ) +{ + int which , status ; + double p,q, s,xlam,bound ; + + which = 2 ; + p = pq.p ; + q = pq.q ; + s = 0.0 ; + xlam = lambda ; + + cdfpoi( &which , &p , &q , &s , &xlam , &status , &bound ) ; + return s ; +} + +/*---------------------------------------------------------------- + T distribution. +------------------------------------------------------------------*/ + +static pqpair student_s2pq( double xx , double dof ) +{ + int which , status ; + double p,q, s,xlam,bound ; + pqpair pq={0.0,1.0} ; + + which = 1 ; + p = 0.0 ; + q = 1.0 ; + s = xx ; + xlam = dof ; if( xlam <= 0.0 ) return pq ; + + cdft( &which , &p , &q , &s , &xlam , &status , &bound ) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +double student_pq2s( pqpair pq , double dof ) +{ + int which , status ; + double p,q, s,xlam,bound ; + + which = 2 ; + p = pq.p ; + q = pq.q ; + s = 0.0 ; + xlam = dof ; + + cdft( &which , &p , &q , &s , &xlam , &status , &bound ) ; + return s ; +} + +/****************************************************************************/ +/* For the distributions below here, cdflib can't do what we want directly. */ +/****************************************************************************/ + +/*---------------------------------------------------------------- + Null correlation distribution. + Let x = (rr+1)/2; then x is Beta(dof/2,dof/2). +------------------------------------------------------------------*/ + +static pqpair correl_s2pq( double rr , double dof ) /* fake it with cdflib */ +{ + return beta_s2pq( 0.5*(rr+1.0) , 0.5*dof , 0.5*dof ) ; +} + +/*------------------------------*/ + +static double correl_pq2s( pqpair pq , double dof ) +{ + double xx = beta_pq2s( pq , 0.5*dof , 0.5*dof ) ; + return (2.0*xx-1.0) ; +} + +/*---------------------------------------------------------------- + Uniform U(0,1) distribution. +------------------------------------------------------------------*/ + +static pqpair uniform_s2pq( double xx ) /* this isn't too hard */ +{ + pqpair pq ; + if( xx <= 0.0 ) pq.p = 0.0 ; + else if( xx >= 1.0 ) pq.p = 1.0 ; + else pq.p = xx ; + pq.q = 1.0-xx ; return pq ; +} + +/*------------------------------*/ + +static double uniform_pq2s( pqpair pq ) +{ + return pq.p ; /* that was easy */ +} + +/*---------------------------------------------------------------- + standard Logistic distribution. +------------------------------------------------------------------*/ + +static pqpair logistic_s2pq( double xx ) /* this isn't hard, either */ +{ + pqpair pq ; + if( xx >= 0.0 ){ pq.q = 1.0/(1.0+exp( xx)); pq.p = 1.0-pq.q; } + else { pq.p = 1.0/(1.0+exp(-xx)); pq.q = 1.0-pq.p; } + return pq ; +} + +/*------------------------------*/ + +static double logistic_pq2s( pqpair pq ) +{ + if( pq.p <= 0.0 ) return -BIGG ; + else if( pq.q <= 0.0 ) return BIGG ; + + if( pq.p < pq.q ) return -log(1.0/pq.p-1.0) ; + else return log(1.0/pq.q-1.0) ; +} + +/*---------------------------------------------------------------- + standard Laplace distribution. +------------------------------------------------------------------*/ + +static pqpair laplace_s2pq( double xx ) /* easy */ +{ + pqpair pq ; + + if( xx >= 0.0 ){ pq.q = 0.5*exp(-xx) ; pq.p = 1.0-pq.q ; } + else { pq.p = 0.5*exp( xx) ; pq.q = 1.0-pq.p ; } + return pq ; +} + +/*------------------------------*/ + +static double laplace_pq2s( pqpair pq ) +{ + if( pq.p <= 0.0 ) return -BIGG ; + else if( pq.q <= 0.0 ) return BIGG ; + + if( pq.p < pq.q ) return log(2.0*pq.p) ; + else return -log(2.0*pq.q) ; +} + +/*---------------------------------------------------------------- + noncentral T distribution = hard calculation +------------------------------------------------------------------*/ + +/**************************************************************************** + Noncentral t distribution function by + Professor K. Krishnamoorthy + Department of Mathematics + University of Louisiana at Lafayette + Manually translated from Fortran by RWC. +*****************************************************************************/ + +#if 0 +static double alng( double x ) /* log(Gamma(x)) from K */ +{ + int indx ; + double xx,fterm,sum,valg ; + double b[9] = { 0.0 , + 8.33333333333333e-2, 3.33333333333333e-2, + 2.52380952380952e-1, 5.25606469002695e-1, + 1.01152306812684e0, 1.51747364915329e0, + 2.26948897420496e0, 3.00991738325940e0 } ; + + if( x < 8.0 ){ xx = x + 8.0 ; indx = 1 ; } + else { xx = x ; indx = 0 ; } + + fterm = (xx-0.5)*log(xx) - xx + 9.1893853320467e-1 ; + sum = b[1]/(xx+b[2]/(xx+b[3]/(xx+b[4]/(xx+b[5]/(xx+b[6]/ + (xx+b[7]/(xx+b[8]))))))) ; + valg = sum + fterm ; + if(indx) + valg = valg-log(x+7.0)-log(x+6.0)-log(x+5.0) + -log(x+4.0)-log(x+3.0)-log(x+2.0)-log(x+1.0)-log(x) ; + return valg ; +} +#else +static double alng( double x ) /*-- replace with cdflib function --*/ +{ + double xx=x ; return alngam( &xx ) ; +} +#endif + +/*---------------------------------------------------------------------------*/ + +#if 0 +static double gaudf( double x ) /* N(0,1) cdf from K */ +{ + static double p0=913.16744211475570 , p1=1024.60809538333800, + p2=580.109897562908800, p3=202.102090717023000, + p4=46.0649519338751400, p5=6.81311678753268400, + p6=6.047379926867041e-1,p7=2.493381293151434e-2 ; + static double q0=1826.33488422951125, q1=3506.420597749092, + q2=3044.77121163622200, q3=1566.104625828454, + q4=523.596091947383490, q5=116.9795245776655, + q6=17.1406995062577800, q7=1.515843318555982, + q8=6.25e-2 ; + static double sqr2pi=2.506628274631001 ; + int check ; + double reslt,z , first,phi ; + + if(x > 0.0){ z = x ; check = 1 ; } + else { z =-x ; check = 0 ; } + + if( z > 32.0 ) return (x > 0.0) ? 1.0 : 0.0 ; + + first = exp(-0.5*z*z) ; + phi = first/sqr2pi ; + + if (z < 7.0) + reslt = first* (((((((p7*z+p6)*z+p5)*z+p4)*z+p3)*z+p2)*z+p1)*z+p0) + /((((((((q8*z+q7)*z+q6)*z+q5)*z+q4)*z+q3)*z+q2)*z+q1)*z+q0); + else + reslt = phi/(z+1.0/(z+2.0/(z+3.0/(z+4.0/(z+6.0/(z+7.0)))))) ; + + if(check) reslt = 1.0 - reslt ; + return reslt ; +} +#else +static double gaudf( double x ) /*-- replace with cdflib func --*/ +{ + double xx=x , p,q ; + cumnor( &xx, &p, &q ); return p; +} +#endif + +/*---------------------------------------------------------------------------*/ + +#if 0 +static double betadf( double x , double p , double q ) /* Beta cdf from K */ +{ + int check , ns ; + double result,betf,psq,xx,cx,pp,qq ; + double term,ai,rx,temp ; + + if( x >= 1.0 ) return 1.0 ; + if( x <= 0.0 ) return 0.0 ; + + betf = alng(p)+alng(q)-alng(p+q) ; + result=x ; + psq=p+q ; + cx=1.0-x ; + if(p < psq*x){ xx=cx ; cx=x ; pp=q ; qq=p ; check=1 ; } + else { xx=x ; pp=p ; qq=q ; check=0 ; } + + term=1.0 ; + ai=1.0 ; + result=1.0 ; + ns=(int)(qq+cx*psq) ; + rx=xx/cx ; +L3: + temp=qq-ai ; + if(ns == 0) rx=xx ; +L4: + term=term*temp*rx/(pp+ai) ; + result=result+term ; + temp=fabs(term) ; + if(temp <= 1.e-14 && temp <= 1.e-14*result) goto L5 ; + ai=ai+1.0 ; + ns=ns-1 ; + if(ns >= 0) goto L3 ; + temp=psq ; + psq=psq+1.0 ; + goto L4 ; + +L5: + result=result*exp(pp*log(xx)+(qq-1.0)*log(cx)-betf)/pp ; + if(check) result=1.0-result ; + return result ; +} +#else +static double betadf( double x , double p , double q ) /*-- cdflib func --*/ +{ + double xx=x,yy=1.0-x , aa=p,bb=q , pp,qq ; + cumbet( &xx,&yy , &aa,&bb , &pp,&qq ) ; return pp ; +} +#endif + +/*---------------------------------------------------------------------------*/ +/* Krishnamoorthy's function for cdf of noncentral t, for df > 0, + translated into C by RW Cox [Mar 2004]. + Note the original fails for delta=0, so we call the cdflib func for this. + A couple of other minor fixes are also included. +-----------------------------------------------------------------------------*/ + +static pqpair tnonc_s2pq( double t , double df , double delta ) +{ + int indx , k , i ; + double x,del,tnd,ans,y,dels,a,b,c ; + double pkf,pkb,qkf,qkb , pgamf,pgamb,qgamf,qgamb ; + double pbetaf,pbetab,qbetaf,qbetab ; + double ptermf,qtermf,ptermb,qtermb,term ; + double rempois,delosq2,sum,cons,error ; + + pqpair pq={0.0,1.0} ; /* will be return value */ + double ab1 ; + + /*-- stupid user? --*/ + + if( df <= 0.0 ) return pq ; + + /*-- non-centrality = 0? --*/ + + if( fabs(delta) < 1.e-8 ) return student_s2pq(t,df) ; + + /*-- start K's code here --*/ + + if( t < 0.0 ){ x = -t ; del = -delta ; indx = 1 ; } /* x will be */ + else { x = t ; del = delta ; indx = 0 ; } /* positive */ + + ans = gaudf(-del) ; /* prob that x <= 0 = Normal cdf */ + + /*-- the nearly trivial case of x=0 --*/ + + if( x == 0.0 ){ pq.p = ans; pq.q = 1.0-ans; return pq; } + + if( df == 1.0 ) df = 1.0000001 ; /** df=1 is BAD **/ + + y = x*x/(df+x*x) ; /* between 0 and 1 */ + dels = 0.5*del*del ; /* will be positive */ + k = (int)dels ; /* 0, 1, 2, ... */ + a = k+0.5 ; /* might be as small as 0.5 */ + c = k+1.0 ; + b = 0.5*df ; /* might be as small as 0.0 */ + + pkf = exp(-dels+k*log(dels)-alng(k+1.0)) ; + pkb = pkf ; + qkf = exp(-dels+k*log(dels)-alng(k+1.0+0.5)) ; + qkb = qkf ; + + pbetaf = betadf(y, a, b) ; + pbetab = pbetaf ; + qbetaf = betadf(y, c, b) ; + qbetab = qbetaf ; + + ab1 = a+b-1.0 ; /* might be as small as -0.5 */ + + /*-- RWCox: if a+b-1 < 0, log(Gamma(a+b-1)) won't work; + instead, use Gamma(a+b-1)=Gamma(a+b)/(a+b-1) --*/ + + if( ab1 > 0.0 ) + pgamf = exp(alng(ab1)-alng(a)-alng(b)+(a-1.0)*log(y)+b*log(1.0-y)) ; + else + pgamf = exp(alng(a+b)-alng(a)-alng(b)+(a-1.0)*log(y)+b*log(1.0-y))/ab1 ; + + pgamb = pgamf*y*(ab1)/a ; + + /*-- we can't have c+b-1 < 0, so the above patchup isn't needed --*/ + + qgamf = exp(alng(c+b-1.0)-alng(c)-alng(b)+(c-1.0)*log(y) + b*log(1.0-y)) ; + qgamb = qgamf*y*(c+b-1.0)/c ; + + rempois = 1.0 - pkf ; + delosq2 = del/1.4142135623731 ; + sum = pkf*pbetaf+delosq2*qkf*qbetaf ; + cons = 0.5*(1.0 + 0.5*fabs(delta)) ; + i = 0 ; +L1: + i = i + 1 ; + pgamf = pgamf*y*(a+b+i-2.0)/(a+i-1.0) ; + pbetaf = pbetaf - pgamf ; + pkf = pkf*dels/(k+i) ; + ptermf = pkf*pbetaf ; + qgamf = qgamf*y*(c+b+i-2.0)/(c+i-1.0) ; + qbetaf = qbetaf - qgamf ; + qkf = qkf*dels/(k+i-1.0+1.5) ; + qtermf = qkf*qbetaf ; + term = ptermf + delosq2*qtermf ; + sum = sum + term ; + error = rempois*cons*pbetaf ; + rempois = rempois - pkf ; + + if( i > k ){ + if( error <= 1.e-12 || i >= 9999 ) goto L2 ; + goto L1 ; + } else { + pgamb = pgamb*(a-i+1.0)/(y*(a+b-i)) ; + pbetab = pbetab + pgamb ; + pkb = (k-i+1.0)*pkb/dels ; + ptermb = pkb*pbetab ; + qgamb = qgamb*(c-i+1.0)/(y*(c+b-i)) ; + qbetab = qbetab + qgamb ; + qkb = (k-i+1.0+0.5)*qkb/dels ; + qtermb = qkb*qbetab ; + term = ptermb + delosq2*qtermb ; + sum = sum + term ; + rempois = rempois - pkb ; + if (rempois <= 1.e-12 || i >= 9999) goto L2 ; + goto L1 ; + } +L2: + tnd = 0.5*sum + ans ; + + /*-- return a pqpair, not just the cdf --*/ + + if( indx ){ pq.p = 1.0-tnd; pq.q = tnd ; } + else { pq.p = tnd ; pq.q = 1.0-tnd; } + return pq ; +} + +/*------------------------------*/ +/* Inverse to above function; + uses cdflib dstinv()/dinvr() + to solve the equation. +--------------------------------*/ + +static double tnonc_pq2s( pqpair pq , double dof , double nonc ) +{ + double t ; /* will be result */ + double tbot,ttop , dt ; + double T6=1.e-50,T7=1.e-8 ; + double K4=0.5,K5=5.0 ; + double fx ; + unsigned long qhi,qleft ; + int status , qporq , ite ; + pqpair tpq ; + + if( dof <= 0.0 ) return BIGG ; /* bad user */ + if( pq.p <= 0.0 ) return -BIGG ; + if( pq.q <= 0.0 ) return BIGG ; + + t = student_pq2s(pq,dof) ; /* initial guess */ + + if( fabs(nonc) < 1.e-8 ) return t ; + + t += 0.5*nonc ; /* adjust up or down */ + + dt = 0.1 * fabs(t) ; if( dt < 1.0 ) dt = 1.0 ; /* stepsize */ + + /* scan down for lower bound, below which cdf is < p */ + + tbot = t ; + for( ite=0 ; ite < 1000 ; ite++ ){ + tpq = tnonc_s2pq( tbot , dof , nonc ) ; + if( tpq.p <= pq.p ) break ; + tbot -= dt ; + } + if( ite >= 1000 ) return -BIGG ; + + /* scan up for upper bound, above which cdf is > p */ + + ttop = tbot+0.5*dt ; + for( ite=0 ; ite < 1000 ; ite++ ){ + tpq = tnonc_s2pq( ttop , dof , nonc ) ; + if( tpq.p >= pq.p ) break ; + ttop += dt ; + } + if( ite >= 1000 ) return BIGG ; + + t = 0.5*(tbot+ttop) ; /* initial guess in middle */ + + /* initialize searching parameters */ + + dstinv(&tbot,&ttop,&K4,&K4,&K5,&T6,&T7); + + status = 0 ; qporq = (pq.p <= pq.q) ; + + while(1){ + + dinvr(&status,&t,&fx,&qleft,&qhi) ; + + if( status != 1 ) return t ; /* done! */ + + tpq = tnonc_s2pq( t , dof , nonc ) ; /* get cdf */ + + /* goal of dinvr is to drive fx to zero */ + + fx = (qporq) ? pq.p-tpq.p : pq.q-tpq.q ; + } + + return BIGG ; /* unreachable */ +} + +/*---------------------------------------------------------------- + Chi distribution (sqrt of chi-squared, duh). +------------------------------------------------------------------*/ + +static pqpair chi_s2pq( double xx , double dof ) +{ + pqpair pq={0.0,1.0} ; + + if( xx <= 0.0 || dof <= 0.0 ) return pq ; + return chisq_s2pq( xx*xx , dof ) ; +} + +/*------------------------------*/ + +static double chi_pq2s( pqpair pq , double dof ) +{ + if( pq.p <= 0.0 ) return 0.0 ; + if( pq.q <= 0.0 ) return BIGG ; + return sqrt(chisq_pq2s(pq,dof)) ; +} + +/*---------------------------------------------------------------- + Extreme value type I: cdf(x) = exp(-exp(-x)). +------------------------------------------------------------------*/ + +static pqpair extval1_s2pq( double x ) +{ + double p,q,y ; pqpair pq ; + + if( x > -5.0 ){ y = exp(-x) ; p = exp(-y) ; } + else { y = 1.0 ; p = 0.0 ; } + + if( y >= 1.e-4 ) q = 1.0-p ; + else q = y*(1.0+y*(-0.5+y*(1.0/6.0-y/24.0))) ; + pq.p = p ; pq.q = q ; return pq ; +} + +/*------------------------------*/ + +static double extval1_pq2s( pqpair pq ) +{ + if( pq.p <= 0.0 ) return -BIGG ; + else if( pq.p >= 1.0 ) return BIGG ; + return -log(-log(pq.p)) ; +} + +/*---------------------------------------------------------------- + Weibull distribution: cdf(x) = 1 - exp( -x^c ) for x>0 and c>0. +------------------------------------------------------------------*/ + +static pqpair weibull_s2pq( double x , double c ) +{ + double y ; + pqpair pq={0.0,1.0} ; + + if( x <= 0.0 || c <= 0.0 ) return pq ; + + y = pow(x,c) ; pq.q = exp(-y) ; + if( y >= 1.e-4 ) pq.p = 1.0-pq.q ; + else pq.p = y*(1.0+y*(-0.5+y*(1.0/6.0-y/24.0))) ; + return pq ; +} + +/*------------------------------*/ + +static double weibull_pq2s( pqpair pq , double c ) +{ + if( pq.p <= 0.0 || c <= 0.0 ) return 0.0 ; + else if( pq.q <= 0.0 ) return BIGG ; + return pow( -log(pq.q) , 1.0/c ) ; +} + +/*---------------------------------------------------------------- + Inverse Gaussian: + density proportional to exp(-0.5*c(x+1/x))/x^1.5 (x,c >0). +------------------------------------------------------------------*/ + +static pqpair invgauss_s2pq( double x, double c ) +{ + double y , p1,q1 , p2,q2 , v ; + pqpair pq={0.0,1.0} ; + + if( x <= 0.0 || c <= 0.0 ) return pq ; + + y = sqrt(c/x) ; + v = y*(x-1.0) ; cumnor( &v , &p1,&q1 ) ; + v = -y*(x+1.0) ; cumnor( &v , &p2,&q2 ) ; + pq.p = p1 ; + if( p2 > 0.0 ) pq.p += exp(2.0*c+log(p2)) ; + pq.q = 1.0-pq.p ; return pq ; +} + +/*------------------------------*/ +/* Inverse to above function; + uses cdflib dstinv()/dinvr() + to solve the equation. +--------------------------------*/ + +static double invgauss_pq2s( pqpair pq , double c ) +{ + double t ; /* will be result */ + double tbot,ttop , dt ; + double T6=1.e-50,T7=1.e-8 ; + double K4=0.5,K5=5.0 ; + double fx ; + unsigned long qhi,qleft ; + int status , qporq , ite ; + pqpair tpq ; + + if( c <= 0.0 ) return BIGG ; /* bad user */ + if( pq.p <= 0.0 ) return 0.0 ; + if( pq.q <= 0.0 ) return BIGG ; + + /* initial guess is t=1; scan down for lower bound */ + + tbot = 1.01 ; dt = 0.9 ; + for( ite=0 ; ite < 1000 ; ite++ ){ + tpq = invgauss_s2pq( tbot , c ) ; + if( tpq.p <= pq.p ) break ; + tbot *= dt ; + } + if( ite >= 1000 ) return 0.0 ; + + /* scan up for upper bound */ + + dt = 1.1 ; ttop = tbot*dt ; + for( ite=0 ; ite < 1000 ; ite++ ){ + tpq = invgauss_s2pq( ttop , c ) ; + if( tpq.p >= pq.p ) break ; + ttop *= dt ; + } + if( ite >= 1000 ) return BIGG ; + + t = sqrt(tbot*ttop) ; /* start at geometric mean */ + + /* initialize searching parameters */ + + dstinv(&tbot,&ttop,&K4,&K4,&K5,&T6,&T7); + + status = 0 ; qporq = (pq.p <= pq.q) ; + + while(1){ + + dinvr(&status,&t,&fx,&qleft,&qhi) ; + + if( status != 1 ) return t ; /* done! */ + + tpq = invgauss_s2pq( t , c ) ; + + /* goal is to drive fx to zero */ + + fx = (qporq) ? pq.p-tpq.p : pq.q-tpq.q ; + } + + return BIGG ; /* unreachable */ +} + +/*--------------------------------------------------------------------------*/ +/*! Given a value, calculate both its cdf and reversed cdf (1.0-cdf). + If an error occurs, you'll probably get back {0.0,1.0}. + All the actual work is done in utility functions for each distribution. +----------------------------------------------------------------------------*/ + +static pqpair stat2pq( double val, int code, double p1,double p2,double p3 ) +{ + pqpair pq={0.0,1.0} ; + + switch( code ){ + + case NIFTI_INTENT_CORREL: pq = correl_s2pq ( val, p1 ) ; break; + case NIFTI_INTENT_TTEST: pq = student_s2pq ( val, p1 ) ; break; + case NIFTI_INTENT_FTEST: pq = fstat_s2pq ( val, p1,p2 ) ; break; + case NIFTI_INTENT_ZSCORE: pq = normal_s2pq ( val ) ; break; + case NIFTI_INTENT_CHISQ: pq = chisq_s2pq ( val, p1 ) ; break; + case NIFTI_INTENT_BETA: pq = beta_s2pq ( val, p1,p2 ) ; break; + case NIFTI_INTENT_BINOM: pq = binomial_s2pq( val, p1,p2 ) ; break; + case NIFTI_INTENT_GAMMA: pq = gamma_s2pq ( val, p1,p2 ) ; break; + case NIFTI_INTENT_POISSON: pq = poisson_s2pq ( val, p1 ) ; break; + case NIFTI_INTENT_FTEST_NONC: pq = fnonc_s2pq ( val, p1,p2,p3 ); break; + case NIFTI_INTENT_CHISQ_NONC: pq = chsqnonc_s2pq( val, p1,p2 ); break; + case NIFTI_INTENT_TTEST_NONC: pq = tnonc_s2pq ( val, p1,p2 ) ; break; + case NIFTI_INTENT_CHI: pq = chi_s2pq ( val, p1 ) ; break; + + /* these distributions are shifted and scaled copies of a standard case */ + + case NIFTI_INTENT_INVGAUSS: + if( p1 > 0.0 && p2 > 0.0 ) pq = invgauss_s2pq( val/p1,p2/p1 ) ; break; + + case NIFTI_INTENT_WEIBULL: + if( p2 > 0.0 && p3 > 0.0 ) pq = weibull_s2pq ((val-p1)/p2,p3) ; break; + + case NIFTI_INTENT_EXTVAL: + if( p2 > 0.0 ) pq = extval1_s2pq ( (val-p1)/p2 ) ; break; + + case NIFTI_INTENT_NORMAL: + if( p2 > 0.0 ) pq = normal_s2pq ( (val-p1)/p2 ) ; break; + + case NIFTI_INTENT_LOGISTIC: + if( p2 > 0.0 ) pq = logistic_s2pq( (val-p1)/p2 ) ; break; + + case NIFTI_INTENT_LAPLACE: + if( p2 > 0.0 ) pq = laplace_s2pq ( (val-p1)/p2 ) ; break; + + case NIFTI_INTENT_UNIFORM: + if( p2 > p1 ) pq = uniform_s2pq((val-p1)/(p2-p1)); break; + + /* this case is trivial */ + + case NIFTI_INTENT_PVAL: pq.p = 1.0-val ; pq.q = val ; break; + } + + return pq ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a pq value (cdf and 1-cdf), compute the value that gives this. + If an error occurs, you'll probably get back a BIGG number. + All the actual work is done in utility functions for each distribution. +----------------------------------------------------------------------------*/ + +static double pq2stat( pqpair pq, int code, double p1,double p2,double p3 ) +{ + double val=BIGG ; + + if( pq.p < 0.0 || pq.q < 0.0 || pq.p > 1.0 || pq.q > 1.0 ) return val ; + + switch( code ){ + + case NIFTI_INTENT_CORREL: val = correl_pq2s ( pq , p1 ) ; break; + case NIFTI_INTENT_TTEST: val = student_pq2s ( pq , p1 ) ; break; + case NIFTI_INTENT_FTEST: val = fstat_pq2s ( pq , p1,p2 ) ; break; + case NIFTI_INTENT_ZSCORE: val = normal_pq2s ( pq ) ; break; + case NIFTI_INTENT_CHISQ: val = chisq_pq2s ( pq , p1 ) ; break; + case NIFTI_INTENT_BETA: val = beta_pq2s ( pq , p1,p2 ) ; break; + case NIFTI_INTENT_BINOM: val = binomial_pq2s( pq , p1,p2 ) ; break; + case NIFTI_INTENT_GAMMA: val = gamma_pq2s ( pq , p1,p2 ) ; break; + case NIFTI_INTENT_POISSON: val = poisson_pq2s ( pq , p1 ) ; break; + case NIFTI_INTENT_FTEST_NONC: val = fnonc_pq2s ( pq , p1,p2,p3 ); break; + case NIFTI_INTENT_CHISQ_NONC: val = chsqnonc_pq2s( pq , p1,p2 ); break; + case NIFTI_INTENT_TTEST_NONC: val = tnonc_pq2s ( pq , p1,p2 ) ; break; + case NIFTI_INTENT_CHI: val = chi_pq2s ( pq , p1 ) ; break; + + /* these distributions are shifted and scaled copies of a standard case */ + + case NIFTI_INTENT_INVGAUSS: + if( p1 > 0.0 && p2 > 0.0 ) val = p1*invgauss_pq2s ( pq,p2/p1); break; + + case NIFTI_INTENT_WEIBULL: + if( p2 > 0.0 && p3 > 0.0 ) val = p1+p2*weibull_pq2s ( pq, p3 ) ; break; + + case NIFTI_INTENT_EXTVAL: + if( p2 > 0.0 ) val = p1+p2*extval1_pq2s ( pq ) ; break; + + case NIFTI_INTENT_NORMAL: + if( p2 > 0.0 ) val = p1+p2*normal_pq2s ( pq ) ; break; + + case NIFTI_INTENT_LOGISTIC: + if( p2 > 0.0 ) val = p1+p2*logistic_pq2s( pq ) ; break; + + case NIFTI_INTENT_LAPLACE: + if( p2 > 0.0 ) val = p1+p2*laplace_pq2s ( pq ) ; break; + + case NIFTI_INTENT_UNIFORM: + if( p2 > p1 ) val = p1+(p2-p1)*uniform_pq2s(pq) ; break; + + /* this case is trivial */ + + case NIFTI_INTENT_PVAL: val = pq.q ; break; + } + + return val ; +} + +/****************************************************************************/ +/*[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]*/ +/*..........................................................................*/ +/*............. AT LAST! Functions to be called by the user! ..............*/ +/*..........................................................................*/ +/*[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]*/ +/****************************************************************************/ + +/**************************************************************************** + Statistical codes implemented here: + + NIFTI_INTENT_CORREL = correlation statistic + NIFTI_INTENT_TTEST = t statistic (central) + NIFTI_INTENT_FTEST = F statistic (central) + NIFTI_INTENT_ZSCORE = N(0,1) statistic + NIFTI_INTENT_CHISQ = Chi-squared (central) + NIFTI_INTENT_BETA = Beta variable (central) + NIFTI_INTENT_BINOM = Binomial variable + NIFTI_INTENT_GAMMA = Gamma distribution + NIFTI_INTENT_POISSON = Poisson distribution + NIFTI_INTENT_FTEST_NONC = noncentral F statistic + NIFTI_INTENT_CHISQ_NONC = noncentral chi-squared + NIFTI_INTENT_TTEST_NONC = noncentral t statistic + NIFTI_INTENT_CHI = Chi statistic (central) + NIFTI_INTENT_INVGAUSS = inverse Gaussian variable + NIFTI_INTENT_WEIBULL = Weibull distribution + NIFTI_INTENT_EXTVAL = Extreme value type I + NIFTI_INTENT_NORMAL = N(mu,variance) normal + NIFTI_INTENT_LOGISTIC = Logistic distribution + NIFTI_INTENT_LAPLACE = Laplace distribution + NIFTI_INTENT_UNIFORM = Uniform distribution + NIFTI_INTENT_PVAL = "p-value" +*****************************************************************************/ + +static char *inam[]={ NULL , NULL , + "CORREL" , "TTEST" , "FTEST" , "ZSCORE" , + "CHISQ" , "BETA" , "BINOM" , "GAMMA" , + "POISSON" , "NORMAL" , "FTEST_NONC" , "CHISQ_NONC" , + "LOGISTIC" , "LAPLACE" , "UNIFORM" , "TTEST_NONC" , + "WEIBULL" , "CHI" , "INVGAUSS" , "EXTVAL" , + "PVAL" , + NULL } ; + +#include +#include + +/*--------------------------------------------------------------------------*/ +/*! Given a string name for a statistic, return its integer code. + Returns -1 if not found. +----------------------------------------------------------------------------*/ + +int nifti_intent_code( char *name ) +{ + char *unam , *upt ; + int ii ; + + if( name == NULL || *name == '\0' ) return -1 ; + + unam = strdup(name) ; + for( upt=unam ; *upt != '\0' ; upt++ ) *upt = (char)toupper(*upt) ; + + for( ii=NIFTI_FIRST_STATCODE ; ii <= NIFTI_LAST_STATCODE ; ii++ ) + if( strcmp(inam[ii],unam) == 0 ) break ; + + free(unam) ; + return (ii <= NIFTI_LAST_STATCODE) ? ii : -1 ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a value, return its cumulative distribution function (cdf): + - val = statistic + - code = NIFTI_INTENT_* statistical code + - p1,p2,p3 = parameters of the distribution + + If an error occurs, you'll probably get back 0.0. +----------------------------------------------------------------------------*/ + +double nifti_stat2cdf( double val, int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + pq = stat2pq( val, code, p1,p2,p3 ) ; + return pq.p ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a value, return its reversed cumulative distribution function + (1-cdf): + - val = statistic + - code = NIFTI_INTENT_* statistical code + - p1,p2,p3 = parameters of the distribution + + If an error transpires, you'll probably get back 1.0. +----------------------------------------------------------------------------*/ + +double nifti_stat2rcdf( double val, int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + pq = stat2pq( val, code, p1,p2,p3 ) ; + return pq.q ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a cdf probability, find the value that gave rise to it. + - p = cdf; 0 < p < 1 + - code = NIFTI_INTENT_* statistical code + - p1,p2,p3 = parameters of the distribution + + If an error transpires, you'll probably get back a BIGG number. +----------------------------------------------------------------------------*/ + +double nifti_cdf2stat( double p , int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + pq.p = p ; pq.q = 1.0-p ; + return pq2stat(pq,code,p1,p2,p3) ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a reversed cdf probability, find the value that gave rise to it. + - q = 1-cdf; 0 < q < 1 + - code = NIFTI_INTENT_* statistical code + - p1,p2,p3 = parameters of the distribution + + If an error transpires, you'll probably get back a BIGG number. +----------------------------------------------------------------------------*/ + +double nifti_rcdf2stat( double q , int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + pq.p = 1.0-q ; pq.q = q ; + return pq2stat(pq,code,p1,p2,p3) ; +} + +/*--------------------------------------------------------------------------*/ +/*! Given a statistic, compute a z-score from it. That is, the output + is z such that cdf(z) of a N(0,1) variable is the same as the cdf + of the given distribution at val. +----------------------------------------------------------------------------*/ + +double nifti_stat2zscore( double val , int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + + if( code == NIFTI_INTENT_ZSCORE ) return val ; /* trivial */ + if( code == NIFTI_INTENT_NORMAL ) return (val-p1)/p2 ; /* almost so */ + + pq = stat2pq( val, code, p1,p2,p3 ) ; /* find cdf */ + return normal_pq2s( pq ) ; /* find z */ +} + +/*--------------------------------------------------------------------------*/ +/*! Given a statistic, compute a half-z-score from it. That is, the output + is z such that cdf(z) of a half-N(0,1) variable is the same as the cdf + of the given distribution at val. A half-N(0,1) variable has density + zero for z < 0 and twice the usual N(0,1) density for z > 0. +----------------------------------------------------------------------------*/ + +double nifti_stat2hzscore( double val, int code, double p1,double p2,double p3 ) +{ + pqpair pq ; + + pq = stat2pq( val, code, p1,p2,p3 ) ; /* find cdf */ + pq.q = 0.5*(1.0-pq.p) ; pq.p = 0.5*(1.0+pq.p) ; /* mangle it */ + return normal_pq2s( pq ) ; /* find z */ +} + +/****************************************************************************/ +/*[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[[]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]]*/ +/****************************************************************************/ + +/*--------------------------------------------------------------------------*/ +/* Sample program to test the above functions. Otherwise unimportant. +----------------------------------------------------------------------------*/ + +int main( int argc , char *argv[] ) +{ + double val , p , q , p1=0.0,p2=0.0,p3=0.0 ; + double vbot,vtop,vdel ; + int code , iarg=1 , doq=0 , dod=0 , doi=0 , doz=0 , doh=0 ; + + /*-- print some help for the pitiful user --*/ + + if( argc < 3 || strstr(argv[1],"help") != NULL ){ + int ii ; + printf("\n") ; + printf("Demo program for computing NIfTI statistical functions.\n") ; + printf("Usage: nifti_stats [-q|-d|-1|-z] val CODE [p1 p2 p3]\n") ; + printf(" val can be a single number or in the form bot:top:step.\n") ; + printf(" default ==> output p = Prob(statistic < val).\n") ; + printf(" -q ==> output is 1-p.\n") ; + printf(" -d ==> output is density.\n") ; + printf(" -1 ==> output is x such that Prob(statistic < x) = val.\n") ; + printf(" -z ==> output is z such that Normal cdf(z) = p(val).\n") ; + printf(" -h ==> output is z such that 1/2-Normal cdf(z) = p(val).\n"); + printf(" Allowable CODEs:\n") ; + for( ii=NIFTI_FIRST_STATCODE ; ii <= NIFTI_LAST_STATCODE ; ii++ ){ + printf(" %-10s",inam[ii]); if((ii-NIFTI_FIRST_STATCODE)%6==5)printf("\n"); + } + printf("\n") ; + printf(" Following CODE are distributional parameters, as needed.\n"); + printf("\n") ; + printf("Results are written to stdout, 1 number per output line.\n") ; + printf("Example (piping output into AFNI program 1dplot):\n") ; + printf(" nifti_stats -d 0:4:.001 INVGAUSS 1 3 | 1dplot -dx 0.001 -stdin\n"); + printf("\n") ; + printf("Author - RW Cox - SSCC/NIMH/NIH/DHHS/USA/EARTH - March 2004\n") ; + printf("\n") ; + exit(0) ; + } + + /*-- check first arg to see if it is an output option; + if so, set the appropriate output flag to determine what to compute --*/ + + if( strcmp(argv[iarg],"-q") == 0 ){ doq = 1 ; iarg++ ; } + else if( strcmp(argv[iarg],"-d") == 0 ){ dod = 1 ; iarg++ ; } + else if( strcmp(argv[iarg],"-1") == 0 ){ doi = 1 ; iarg++ ; } + else if( strcmp(argv[iarg],"-z") == 0 ){ doz = 1 ; iarg++ ; } + else if( strcmp(argv[iarg],"-h") == 0 ){ doh = 1 ; iarg++ ; } + + /*-- get the value(s) to process --*/ + + vbot=vtop=vdel = 0.0 ; + sscanf( argv[iarg++] , "%lf:%lf:%lf" , &vbot,&vtop,&vdel ) ; + if( vbot >= vtop ) vdel = 0.0 ; + if( vdel <= 0.0 ) vtop = vbot ; + + /*-- decode the CODE into the integer signifying the distribution --*/ + + code = nifti_intent_code(argv[iarg++]) ; + if( code < 0 ){ fprintf(stderr,"illegal code=%s\n",argv[iarg-1]); exit(1); } + + /*-- get the parameters, if present (defaults are 0) --*/ + + if( argc > iarg ) p1 = strtod(argv[iarg++],NULL) ; + if( argc > iarg ) p2 = strtod(argv[iarg++],NULL) ; + if( argc > iarg ) p3 = strtod(argv[iarg++],NULL) ; + + /*-- loop over input value(s), compute output, write to stdout --*/ + + for( val=vbot ; val <= vtop ; val += vdel ){ + if( doq ) /* output = 1-cdf */ + p = nifti_stat2rcdf( val , code,p1,p2,p3 ) ; + else if( dod ) /* output = density */ + p = 1000.0*( nifti_stat2cdf(val+.001,code,p1,p2,p3) + -nifti_stat2cdf(val ,code,p1,p2,p3)) ; + else if( doi ) /* output = inverse */ + p = nifti_cdf2stat( val , code,p1,p2,p3 ) ; + else if( doz ) /* output = z score */ + p = nifti_stat2zscore( val , code,p1,p2,p3 ) ; + else if( doh ) /* output = halfz score */ + p = nifti_stat2hzscore( val , code,p1,p2,p3 ) ; + else /* output = cdf */ + p = nifti_stat2cdf( val , code,p1,p2,p3 ) ; + + printf("%.9g\n",p) ; + if( vdel <= 0.0 ) break ; /* the case of just 1 value */ + } + + /*-- terminus est --*/ + + exit(0) ; +} + diff --git a/spm/nii_for_spm2/@nifti/private/nifti_stats.m b/spm/nii_for_spm2/@nifti/private/nifti_stats.m new file mode 100755 index 0000000..1f43961 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/nifti_stats.m @@ -0,0 +1,41 @@ +function varargout = nifti_stats(varargin) +% Conversion among various statistics +% FORMAT P = nifti_stats(VAL,CODE,OPT,PARAM) +% CODE can be one of +% 'CORREL' 'TTEST' 'FTEST' 'ZSCORE' +% 'CHISQ' 'BETA' 'BINOM' 'GAMMA' +% 'POISSON' 'NORMAL' 'FTEST_NONC' 'CHISQ_NONC' +% 'LOGISTIC' 'LAPLACE' 'UNIFORM' 'TTEST_NONC' +% 'WEIBULL' 'CHI' 'INVGAUSS' 'EXTVAL' +% 'PVAL' +% With only one input argument, CODE defaults to 'ZSCORE' +% +% OPT can be one of +% '-p' ==> output P = Prob(statistic < VAL). +% '-q' ==> output is 1-p. +% '-d' ==> output is probability density. +% '-1' ==> output is X such that Prob(statistic < x) = VAL. +% '-z' ==> output is Z such that Normal cdf(Z) = p(VAL). +% '-h' ==> output is Z such that 1/2-Normal cdf(Z) = p(VAL). +% With less than three input arguments, OPT defaults to '-p'. +% +% PARAM are up to three distribution parameters. +% These default to zero if unspecified. +% +% P is an array with the same dimensions as VAL. +% +%_______________________________________________________________________ +% 99.99% of the work by RW Cox - SSCC/NIMH/NIH/DHHS/USA/EARTH - March 2004 +% 0.01% of the work (the mex wrapper) by John Ashburner - FIL/ION/UCL +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: nifti_stats.m 253 2005-10-13 15:31:34Z guillaume $ + + +fprintf('******************************************\n'); +fprintf('Compile the nifti_stats function with\n'); +fprintf(' mex nifti_stats.c nifti_stats_mex.c -O\n'); +fprintf('******************************************\n'); + +error('nifti_stats is not compiled.'); diff --git a/spm/nii_for_spm2/@nifti/private/nifti_stats_mex.c b/spm/nii_for_spm2/@nifti/private/nifti_stats_mex.c new file mode 100755 index 0000000..76d7be7 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/nifti_stats_mex.c @@ -0,0 +1,124 @@ +#ifndef lint +static char svnid[] = "$Id: nifti_stats_mex.c 253 2005-10-13 15:31:34Z guillaume $"; +#endif +/* + * This is a Matlab mex interface for Bob Cox's extensive nifti_stats.c + * functionality. See nifti_stats.m for documentation. + */ + +#include +#include +#include +#include "mex.h" + +#include "nifti1.h" +extern int nifti_intent_code( char *name ); +extern double nifti_stat2cdf( double val, int code, double p1,double p2,double p3 ); +extern double nifti_stat2rcdf( double val, int code, double p1,double p2,double p3 ); +extern double nifti_stat2cdf( double val, int code, double p1,double p2,double p3 ); +extern double nifti_cdf2stat( double val, int code, double p1,double p2,double p3 ); +extern double nifti_stat2zscore( double val, int code, double p1,double p2,double p3 ); +extern double nifti_stat2hzscore( double val, int code, double p1,double p2,double p3 ); + +void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]) +{ + double *val, *p, p1=0.0,p2=0.0,p3=0.0 ; + int code=5, dop=1, doq=0, dod=0, doi=0, doz=0, doh=0 ; + int ndim, i, n; + const int *dim; + + if (nlhs>1) mexErrMsgTxt("Too many output arguments."); + if (nrhs<1) mexErrMsgTxt("Not enough input arguments."); + if (nrhs>4) mexErrMsgTxt("Too many input arguments."); + + /* VAL */ + if (!mxIsNumeric(prhs[0]) || !mxIsDouble(prhs[0]) || mxIsComplex(prhs[0])) + mexErrMsgTxt("Wrong datatype for 1st argument."); + ndim = mxGetNumberOfDimensions(prhs[0]); + dim = mxGetDimensions(prhs[0]); + n = 1; + for(i=0,n=1; i=2) + { + if (mxIsChar(prhs[1])) + { + int buflen; + char *buf; + buflen = mxGetN(prhs[1])*mxGetM(prhs[1])+1; + buf = (char *)mxCalloc(buflen,sizeof(char)); + mxGetString(prhs[1],buf,buflen); + code = nifti_intent_code(buf); + mxFree(buf); + } + else if (mxIsNumeric(prhs[1]) && mxIsDouble(prhs[1]) && !mxIsComplex(prhs[1])) + { + if (mxGetM(prhs[1])*mxGetN(prhs[1]) != 1) + mexErrMsgTxt("Wrong sized 2nd argument."); + code = (int)mxGetPr(prhs[1])[0]; + } + else mexErrMsgTxt("Wrong datatype for 2nd argument."); + if (codeNIFTI_LAST_STATCODE) + mexErrMsgTxt("Illegal Stat-Code."); + } + + /* OPT */ + if (nrhs>=3) + { + int buflen; + char *buf; + dop = 0; + if (!mxIsChar(prhs[2])) + mexErrMsgTxt("Wrong datatype for3rd argument."); + buflen = mxGetN(prhs[2])*mxGetM(prhs[2])+1; + buf = (char *)mxCalloc(buflen,sizeof(char)); + mxGetString(prhs[2],buf,buflen); + if ( strcmp(buf,"-p") == 0 ) dop = 1; + else if ( strcmp(buf,"-q") == 0 ) doq = 1; + else if ( strcmp(buf,"-d") == 0 ) dod = 1; + else if ( strcmp(buf,"-1") == 0 ) doi = 1; + else if ( strcmp(buf,"-z") == 0 ) doz = 1; + else if ( strcmp(buf,"-h") == 0 ) doh = 1; + else { mxFree(buf); mexErrMsgTxt("Unrecognised option."); } + mxFree(buf); + } + + /* PARAM */ + if (nrhs>=4) + { + int np; + if (!mxIsNumeric(prhs[3]) || !mxIsDouble(prhs[3]) || mxIsComplex(prhs[3])) + mexErrMsgTxt("Wrong datatype for 4th argument."); + np = mxGetM(prhs[3])*mxGetN(prhs[3]); + if (np>3) mexErrMsgTxt("Wrong sized 4th argument."); + if (np>=1) p1 = mxGetPr(prhs[3])[0]; + if (np>=2) p2 = mxGetPr(prhs[3])[1]; + if (np>=3) p3 = mxGetPr(prhs[3])[2]; + } + + /* P */ + plhs[0] = mxCreateNumericArray(ndim,dim,mxDOUBLE_CLASS,mxREAL); + p = mxGetData(plhs[0]); + + /* Call Bob's code */ + for(i=0; i7 + be = ~be; + fclose(fp); + if be, mach = 'ieee-be'; + else mach = 'ieee-le'; + end; + fp = fopen(hname,'r',mach); + if fp==-1 + hdr = []; + return; + end; +end; + +% Is it NIFTI or not +fseek(fp,0,'bof'); +fseek(fp,344,'bof'); +mgc = deblank(char(fread(fp,4,'uint8')')); +switch mgc +case {'ni1','n+1'} + org = niftistruc; +otherwise + org = mayostruc; +end; +fseek(fp,0,'bof'); +% Read the fields +for i=1:length(org) + tmp = fread(fp,org(i).len,['*' org(i).dtype.prec])'; + if length(tmp) ~= org(i).len +disp([length(tmp) org(i).len]); + tmp = org(i).def; + ok = false; + end; + tmp = feval(org(i).dtype.conv,tmp); + hdr.(org(i).label) = tmp; +end; + +fclose(fp); +if ~ok, + fprintf('There was a problem reading the header of\n'); + fprintf('"%s".\n', fname); + fprintf('It may be corrupted in some way.'); +end; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/write_extras.m b/spm/nii_for_spm2/@nifti/private/write_extras.m new file mode 100755 index 0000000..59aa818 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/write_extras.m @@ -0,0 +1,36 @@ +function extras = write_extras(fname,extras) +% Write extra bits of information +%_______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: write_extras.m 473 2006-03-08 18:11:59Z john $ + + +[pth,nam,ext] = fileparts(fname); +switch ext +case {'.hdr','.img','.nii'} + mname = fullfile(pth,[nam '.mat']); +case {'.HDR','.IMG','.NII'} + mname = fullfile(pth,[nam '.MAT']); +otherwise + mname = fullfile(pth,[nam '.mat']); +end +if isstruct(extras) && ~isempty(fieldnames(extras)), + savefields(mname,extras); +end; + +function savefields(fnam,p) +if length(p)>1, error('Can''t save fields.'); end; +fn = fieldnames(p); +for i_=1:length(fn), + eval([fn{i_} '= p.' fn{i_} ';']); +end; +if str2num(version('-release'))>=14, + fn = {'-V6',fn{:}}; +end; +if numel(fn)>0, + save(fnam,fn{:}); +end; +return; + diff --git a/spm/nii_for_spm2/@nifti/private/write_hdr_raw.m b/spm/nii_for_spm2/@nifti/private/write_hdr_raw.m new file mode 100644 index 0000000..cc9241c --- /dev/null +++ b/spm/nii_for_spm2/@nifti/private/write_hdr_raw.m @@ -0,0 +1,77 @@ +function ok = write_hdr_raw(fname,hdr,be) +% Write a NIFTI-1 .hdr file. +% FORMAT ok = write_hdr_raw(fname,hdr,be) +% fname - filename of image +% hdr - a structure containing hdr info +% be - whether big-endian or not +% ok - status (1=good, 0=bad) +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: write_hdr_raw.m 1059 2008-01-03 15:59:48Z guillaume $ + + +[pth,nam,ext] = fileparts(fname); +if isempty(pth), pth = pwd; end + +if isfield(hdr,'magic') + org = niftistruc; + switch deblank(hdr.magic) + case {'ni1'} + hname = fullfile(pth,[nam '.hdr']); + case {'n+1'} + hname = fullfile(pth,[nam '.nii']); + otherwise + error('Bad header.'); + end; +else + org = mayostruc; + hname = fullfile(pth,[nam '.hdr']); +end; + +if nargin >=3 + if be, mach = 'ieee-be'; + else mach = 'ieee-le'; + end; +else mach = 'native'; +end; + +ok = true; +if exist(hname,'file'), + fp = fopen(hname,'r+',mach); +else + fp = fopen(hname,'w+',mach); +end +if fp == -1, + ok = false; + return; +end + +for i=1:length(org) + if isfield(hdr,org(i).label), + dat = hdr.(org(i).label); + if length(dat) ~= org(i).len, + if length(dat)< org(i).len, + dat = [dat(:) ; zeros(org(i).len-length(dat),1)]; + else + dat = dat(1:org(i).len); + end; + end; + else + dat = org(i).def; + end; + % fprintf('%s=\n',org(i).label) + % disp(dat) + len = fwrite(fp,dat,org(i).dtype.prec); + if len ~= org(i).len, + ok = false; + end; +end; +fclose(fp); +if ~ok, + fprintf('There was a problem writing to the header of\n'); + fprintf('"%s"\n', fname); +end; +return; + diff --git a/spm/nii_for_spm2/@nifti/structn.m b/spm/nii_for_spm2/@nifti/structn.m new file mode 100755 index 0000000..aeac863 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/structn.m @@ -0,0 +1,20 @@ +function t = structn(obj) +% Convert a NIFTI-1 object into a form of struct +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: structn.m 253 2005-10-13 15:31:34Z guillaume $ + + +if numel(obj)~=1, + error('Too many elements to convert'); +end; +fn = fieldnames(obj); +for i=1:length(fn) + tmp = subsref(obj,struct('type','.','subs',fn{i})); + if ~isempty(tmp) + t.(fn{i}) = tmp; + end; +end; +return; diff --git a/spm/nii_for_spm2/@nifti/subsasgn.m b/spm/nii_for_spm2/@nifti/subsasgn.m new file mode 100755 index 0000000..4cb4770 --- /dev/null +++ b/spm/nii_for_spm2/@nifti/subsasgn.m @@ -0,0 +1,400 @@ +function obj = subsasgn(obj,subs,varargin) +% Subscript assignment +% See subsref for meaning of fields. +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: subsasgn.m 253 2005-10-13 15:31:34Z guillaume $ + + +switch subs(1).type, +case {'.'}, + if numel(obj)~=nargin-2, + error('The number of outputs should match the number of inputs.'); + end; + objs = struct(obj); + for i=1:length(varargin), + val = varargin{i}; + obji = class(objs(i),'nifti'); + obji = fun(obji,subs,val); + objs(i) = struct(obji); + end; + obj = class(objs,'nifti'); + +case {'()'}, + objs = struct(obj); + if length(subs)>1, + t = subsref(objs,subs(1)); + % A lot of this stuff is a little flakey, and may cause Matlab to bomb. + % + %if numel(t) ~= nargin-2, + % error('The number of outputs should match the number of inputs.'); + %end; + for i=1:numel(t), + val = varargin{1}; + obji = class(t(i),'nifti'); + obji = subsasgn(obji,subs(2:end),val); + t(i) = struct(obji); + end; + objs = subsasgn(objs,subs(1),t); + else + if numel(varargin)>1, + error('Illegal right hand side in assignment. Too many elements.'); + end; + val = varargin{1}; + if isa(val,'nifti'), + objs = subsasgn(objs,subs,struct(val)); + elseif isempty(val), + objs = subsasgn(objs,subs,[]); + else + error('Assignment between unlike types is not allowed.'); + end; + end; + obj = class(objs,'nifti'); + +otherwise + error('Cell contents reference from a non-cell array object.'); +end; +return; +%======================================================================= + +%======================================================================= +function obj = fun(obj,subs,val) +% Subscript referencing + +switch subs(1).type, +case {'.'}, + objs = struct(obj); + for ii=1:numel(objs) + obj = objs(ii); + + if any(strcmpi(subs(1).subs,{'dat'})), + if length(subs)>1, + val = subsasgn(obj.dat,subs(2:end),val); + end; + obj = assigndat(obj,val); + objs(ii) = obj; + continue; + end; + + if isempty(obj.hdr), obj.hdr = empty_hdr; end; + if ~isfield(obj.hdr,'magic'), error('Not a NIFTI-1 header'); end; + + if length(subs)>1, % && ~strcmpi(subs(1).subs,{'raw','dat'}), + val0 = subsref(class(obj,'nifti'),subs(1)); + val1 = subsasgn(val0,subs(2:end),val); + else + val1 = val; + end; + + switch(subs(1).subs) + case {'extras'} + if length(subs)>1, + obj.extras = subsasgn(obj.extras,subs(2:end),val); + else + obj.extras = val; + end; + + case {'mat0'} + if ~isnumeric(val1) || ndims(val1)~=2 || any(size(val1)~=[4 4]) || sum((val1(4,:)-[0 0 0 1]).^2)>1e-8, + error('"mat0" should be a 4x4 matrix, with a last row of 0,0,0,1.'); + end; + if obj.hdr.qform_code==0, obj.hdr.qform_code=2; end; + s = double(bitand(obj.hdr.xyzt_units,7)); + if s + d = findindict(s,'units'); + val1 = diag([[1 1 1]/d.rescale 1])*val1; + end; + obj.hdr = encode_qform0(double(val1), obj.hdr); + + case {'mat0_intent'} + if isempty(val1), + obj.hdr.qform_code = 0; + else + if ~ischar(val1) && ~(isnumeric(val1) && numel(val1)==1), + error('"mat0_intent" should be a string or a scalar.'); + end; + d = findindict(val1,'xform'); + if ~isempty(d) + obj.hdr.qform_code = d.code; + end; + end; + + case {'mat'} + if ~isnumeric(val1) || ndims(val1)~=2 || any(size(val1)~=[4 4]) || sum((val1(4,:)-[0 0 0 1]).^2)>1e-8 + error('"mat" should be a 4x4 matrix, with a last row of 0,0,0,1.'); + end; + if obj.hdr.sform_code==0, obj.hdr.sform_code=2; end; + s = double(bitand(obj.hdr.xyzt_units,7)); + if s + d = findindict(s,'units'); + val1 = diag([[1 1 1]/d.rescale 1])*val1; + end; + val1 = val1 * [eye(4,3) [1 1 1 1]']; + obj.hdr.srow_x = val1(1,:); + obj.hdr.srow_y = val1(2,:); + obj.hdr.srow_z = val1(3,:); + + case {'mat_intent'} + if isempty(val1), + obj.hdr.sform_code = 0; + else + if ~ischar(val1) && ~(isnumeric(val1) && numel(val1)==1), + error('"mat_intent" should be a string or a scalar.'); + end; + d = findindict(val1,'xform'); + if ~isempty(d), + obj.hdr.sform_code = d.code; + end; + end; + + case {'intent'} + if ~valid_fields(val1,{'code','param','name'}) + obj.hdr.intent_code = 0; + obj.hdr.intent_p1 = 0; + obj.hdr.intent_p2 = 0; + obj.hdr.intent_p3 = 0; + obj.hdr.intent_name = ''; + else + if ~isfield(val1,'code'), + val1.code = obj.hdr.intent_code; + end; + d = findindict(val1.code,'intent'); + if ~isempty(d), + obj.hdr.intent_code = d.code; + if isfield(val1,'param'), + prm = [double(val1.param(:)) ; 0 ; 0; 0]; + prm = [prm(1:length(d.param)) ; 0 ; 0; 0]; + obj.hdr.intent_p1 = prm(1); + obj.hdr.intent_p2 = prm(2); + obj.hdr.intent_p3 = prm(3); + end; + if isfield(val1,'name'), + obj.hdr.intent_name = val1.name; + end; + end; + end; + + case {'diminfo'} + if ~valid_fields(val1,{'frequency','phase','slice','slice_time'}) + tmp = obj.hdr.dim_info; + for bit=1:6, + tmp = bitset(tmp,bit,0); + end; + obj.hdr.dim_info = tmp; + obj.hdr.slice_start = 0; + obj.hdr.slice_end = 0; + obj.hdr.slice_duration = 0; + obj.hdr.slice_code = 0; + else + if isfield(val1,'frequency'), + tmp = val1.frequency; + if ~isnumeric(tmp) || numel(tmp)~=1 || tmp<0 || tmp>3, + error('Invalid frequency direction'); + end; + obj.hdr.dim_info = bitset(obj.hdr.dim_info,1,bitget(tmp,1)); + obj.hdr.dim_info = bitset(obj.hdr.dim_info,2,bitget(tmp,2)); + end; + + if isfield(val1,'phase'), + tmp = val1.phase; + if ~isnumeric(tmp) || numel(tmp)~=1 || tmp<0 || tmp>3, + error('Invalid phase direction'); + end; + obj.hdr.dim_info = bitset(obj.hdr.dim_info,3,bitget(tmp,1)); + obj.hdr.dim_info = bitset(obj.hdr.dim_info,4,bitget(tmp,2)); + end; + + if isfield(val1,'slice'), + tmp = val1.slice; + if ~isnumeric(tmp) || numel(tmp)~=1 || tmp<0 || tmp>3, + error('Invalid slice direction'); + end; + obj.hdr.dim_info = bitset(obj.hdr.dim_info,5,bitget(tmp,1)); + obj.hdr.dim_info = bitset(obj.hdr.dim_info,6,bitget(tmp,2)); + end; + + if isfield(val1,'slice_time') + tim = val1.slice_time; + if ~valid_fields(tim,{'start','end','duration','code'}), + obj.hdr.slice_code = 0; + obj.hdr.slice_start = 0; + obj.hdr.end_slice = 0; + obj.hdr.slice_duration = 0; + else + % sld = double(bitget(obj.hdr.dim_info,5)) + 2*double(bitget(obj.hdr.dim_info,6)); + + if isfield(tim,'start'), + ss = double(tim.start); + if isnumeric(ss) && numel(ss)==1 && ~rem(ss,1), % && ss>=1 && ss<=obj.hdr.dim(sld+1) + obj.hdr.slice_start = ss-1; + else + error('Inappropriate "slice_time.start".'); + end; + end; + + if isfield(tim,'end'), + ss = double(tim.end); + if isnumeric(ss) && numel(ss)==1 && ~rem(ss,1), % && ss>=1 && ss<=obj.hdr.dim(sld+1) + obj.hdr.slice_end = ss-1; + else + error('Inappropriate "slice_time.end".'); + end; + end; + + if isfield(tim,'duration') + sd = double(tim.duration); + if isnumeric(sd) && numel(sd)==1, + s = double(bitand(obj.hdr.xyzt_units,24)); + d = findindict(s,'units'); + if ~isempty(d) && d.rescale, sd = sd/d.rescale; end; + obj.hdr.slice_duration = sd; + else + error('Inappropriate "slice_time.duration".'); + end; + end; + + if isfield(tim,'code'), + d = findindict(tim.code,'sliceorder'); + if ~isempty(d), + obj.hdr.slice_code = d.code; + end; + end; + end; + end; + end; + + case {'timing'} + if ~valid_fields(val1,{'toffset','tspace'}), + obj.hdr.pixdim(5) = 0; + obj.hdr.toffset = 0; + else + s = double(bitand(obj.hdr.xyzt_units,24)); + d = findindict(s,'units'); + if isfield(val1,'toffset'), + if isnumeric(val1.toffset) && numel(val1.toffset)==1, + if d.rescale, + val1.toffset = val1.toffset/d.rescale; + end; + obj.hdr.toffset = val1.toffset; + else + error('"timing.toffset" needs to be numeric with 1 element'); + end; + end; + if isfield(val1,'tspace'), + if isnumeric(val1.tspace) && numel(val1.tspace)==1, + if d.rescale, + val1.tspace = val1.tspace/d.rescale; + end; + obj.hdr.pixdim(5) = val1.tspace; + else + error('"timing.tspace" needs to be numeric with 1 element'); + end; + end; + end; + + case {'descrip'} + if isempty(val1), val1 = char(val1); end; + if ischar(val1), + obj.hdr.descrip = val1; + else + error('"descrip" must be a string.'); + end; + + case {'cal'} + if isempty(val1), + obj.hdr.cal_min = 0; + obj.hdr.cal_max = 0; + else + if isnumeric(val1) && numel(val1)==2, + obj.hdr.cal_min = val1(1); + obj.hdr.cal_max = val1(2); + else + error('"cal" should contain two elements.'); + end; + end; + + case {'aux_file'} + if isempty(val1), val1 = char(val1); end; + if ischar(val1), + obj.hdr.aux_file = val1; + else + error('"aux_file" must be a string.'); + end; + + case {'hdr'} + error('hdr is a read-only field.'); + obj.hdr = val1; + + otherwise + error(['Reference to non-existent field ''' subs(1).subs '''.']); + end; + + objs(ii) = obj; + end + obj = class(objs,'nifti'); + +otherwise + error('This should not happen.'); +end; +return; +%======================================================================= + +%======================================================================= +function obj = assigndat(obj,val) +if isa(val,'file_array'), + sz = size(val); + if numel(sz)>8, + error('Too many dimensions in data.'); + end; + sz = [sz 1 1 1 1 1 1 1 1]; + sz = sz(1:8); + sval = struct(val); + d = findindict(sval.dtype,'dtype'); + if isempty(d) + error(['Unknown datatype (' num2str(double(sval.datatype)) ').']); + end; + + [pth,nam,suf] = fileparts(sval.fname); + if any(strcmp(suf,{'.img','.IMG'})) + val.offset = max(sval.offset,0); + obj.hdr.magic = 'ni1'; + elseif any(strcmp(suf,{'.nii','.NII'})) + val.offset = max(sval.offset,352); + obj.hdr.magic = 'n+1'; + else + error(['Unknown filename extension (' suf ').']); + end; + val.offset = (ceil(val.offset/16))*16; + obj.hdr.vox_offset = val.offset; + + obj.hdr.dim(2:(numel(sz)+1)) = sz; + nd = max(find(obj.hdr.dim(2:end)>1)); + if isempty(nd), nd = 3; end; + obj.hdr.dim(1) = nd; + obj.hdr.datatype = sval.dtype; + obj.hdr.bitpix = d.size*8; + if ~isempty(sval.scl_slope), obj.hdr.scl_slope = sval.scl_slope; end; + if ~isempty(sval.scl_inter), obj.hdr.scl_inter = sval.scl_inter; end; + obj.dat = val; +else + error('"raw" must be of class "file_array"'); +end; +return; + +function ok = valid_fields(val,allowed) +if isempty(val), ok = false; return; end; +if ~isstruct(val), + error(['Expecting a structure, not a ' class(val) '.']); +end; +fn = fieldnames(val); +for ii=1:length(fn), + if ~any(strcmpi(fn{ii},allowed)), + fprintf('Allowed fieldnames are:\n'); + for i=1:length(allowed), fprintf(' %s\n', allowed{i}); end; + error(['"' fn{ii} '" is not a valid fieldname.']); + end +end +ok = true; +return; diff --git a/spm/nii_for_spm2/@nifti/subsref.m b/spm/nii_for_spm2/@nifti/subsref.m new file mode 100755 index 0000000..f561f2a --- /dev/null +++ b/spm/nii_for_spm2/@nifti/subsref.m @@ -0,0 +1,241 @@ +function varargout = subsref(opt,subs) +% Subscript referencing +% +% Fields are: +% dat - a file-array representing the image data +% mat0 - a 9-parameter affine transform (from qform0) +% Note that the mapping is from voxels (where the first +% is considered to be at [1,1,1], to millimetres. See +% mat0_interp for the meaning of the transform. +% mat - a 12-parameter affine transform (from sform0) +% Note that the mapping is from voxels (where the first +% is considered to be at [1,1,1], to millimetres. See +% mat1_interp for the meaning of the transform. +% mat_intent - intention of mat. This field may be missing/empty. +% mat0_intent - intention of mat0. This field may be missing/empty. +% intent - interpretation of image. When present, this structure +% contains the fields +% code - name of interpretation +% params - parameters needed to interpret the image +% diminfo - MR encoding of different dimensions. This structure may +% contain some or all of the following fields +% frequency - a value of 1-3 indicating frequency direction +% phase - a value of 1-3 indicating phase direction +% slice - a value of 1-3 indicating slice direction +% slice_time - only present when "slice" field is present. +% Contains the following fields +% code - ascending/descending etc +% start - starting slice number +% end - ending slice number +% duration - duration of each slice acquisition +% Setting frequency, phase or slice to 0 will remove it. +% timing - timing information. When present, contains the fields +% toffset - acquisition time of first volume (seconds) +% tspace - time between sucessive volumes (seconds) +% descrip - a brief description of the image +% cal - a two-element vector containing cal_min and cal_max +% aux_file - name of an auxiliary file +% _______________________________________________________________________ +% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience + +% +% $Id: subsref.m 253 2005-10-13 15:31:34Z guillaume $ + + +varargout = rec(opt,subs); +return; + +function c = rec(opt,subs) +switch subs(1).type, +case {'.'}, + c = {}; + opts = struct(opt); + for ii=1:numel(opts) + opt = class(opts(ii),'nifti'); + %if ~isstruct(opt) + % error('Attempt to reference field of non-structure array.'); + %end; + + h = opt.hdr; + if isempty(h), + %error('No header.'); + h = empty_hdr; + end; + + % NIFTI-1 FORMAT + switch(subs(1).subs) + case 'extras', + t = opt.extras; + + case 'raw', % A hidden field + if isa(opt.dat,'file_array'), + tmp = struct(opt.dat); + tmp.scl_slope = []; + tmp.scl_inter = []; + t = file_array(tmp); + else + t = opt.dat; + end; + + case 'dat', + t = opt.dat; + + case 'mat0', + t = decode_qform0(h); + s = double(bitand(h.xyzt_units,7)); + if s + d = findindict(s,'units'); + if ~isempty(d) + t = diag([d.rescale*[1 1 1] 1])*t; + end; + end; + + case 'mat0_intent', + d = findindict(h.qform_code,'xform'); + if isempty(d) || d.code==0, + t = ''; + else + t = d.label; + end; + + case 'mat', + if h.sform_code > 0 + t = double([h.srow_x ; h.srow_y ; h.srow_z ; 0 0 0 1]); + t = t * [eye(4,3) [-1 -1 -1 1]']; + else + t = decode_qform0(h); + end + s = double(bitand(h.xyzt_units,7)); + if s + d = findindict(s,'units'); + t = diag([d.rescale*[1 1 1] 1])*t; + end; + + case 'mat_intent', + if h.sform_code>0, + t = h.sform_code; + else + t = h.qform_code; + end; + d = findindict(t,'xform'); + if isempty(d) || d.code==0, + t = ''; + else + t = d.label; + end; + + case 'intent', + d = findindict(h.intent_code,'intent'); + if isempty(d) || d.code == 0, + %t = struct('code','UNKNOWN','param',[]); + t = []; + else + t = struct('code',d.label,'param',... + double([h.intent_p1 h.intent_p2 h.intent_p3]), 'name',deblank(h.intent_name)); + t.param = t.param(1:length(d.param)); + end + + case 'diminfo', + t = []; + tmp = bitand( h.dim_info ,3); if tmp, t.frequency = double(tmp); end; + tmp = bitand(bitshift(h.dim_info,-2),3); if tmp, t.phase = double(tmp); end; + tmp = bitand(bitshift(h.dim_info,-4),3); if tmp, t.slice = double(tmp); end; + % t = struct('frequency',bitand( h.dim_info ,3),... + % 'phase',bitand(bitshift(h.dim_info,-2),3),... + % 'slice',bitand(bitshift(h.dim_info,-4),3)) + if isfield(t,'slice') + sc = double(h.slice_code); + ss = double(h.slice_start)+1; + se = double(h.slice_end)+1; + ss = max(ss,1); + se = min(se,double(h.dim(t.slice+1))); + + sd = double(h.slice_duration); + s = double(bitand(h.xyzt_units,24)); + d = findindict(s,'units'); + if d.rescale, sd = sd*d.rescale; end; + + ns = (se-ss+1); + d = findindict(sc,'sliceorder'); + if isempty(d) + label = 'UNKNOWN'; + else + label = d.label; + end; + t.slice_time = struct('code',label,'start',ss,'end',se,'duration',sd); + if 0, % Never + t.times = zeros(1,double(h.dim(t.slice+1)))+NaN; + switch sc, + case 0, % Unknown + t.times(ss:se) = zeros(1,ns); + case 1, % sequential increasing + t.times(ss:se) = (0:(ns-1))*sd; + case 2, % sequential decreasing + t.times(ss:se) = ((ns-1):-1:0)*sd; + case 3, % alternating increasing + t.times(ss:2:se) = (0:floor((ns+1)/2-1))*sd; + t.times((ss+1):2:se) = (floor((ns+1)/2):(ns-1))*sd; + case 4, % alternating decreasing + t.times(se:-2:ss) = (0:floor((ns+1)/2-1))*sd; + t.times(se:-2:(ss+1)) = (floor((ns+1)/2):(ns-1))*sd; + end; + end; + end; + + case 'timing', + to = double(h.toffset); + dt = double(h.pixdim(5)); + if to==0 && dt==0, + t = []; + else + s = double(bitand(h.xyzt_units,24)); + d = findindict(s,'units'); + if d.rescale, + to = to*d.rescale; + dt = dt*d.rescale; + end; + t = struct('toffset',to,'tspace',dt); + end; + + case 'descrip', + t = deblank(h.descrip); + msk = find(t==0); + if any(msk), t=t(1:(msk(1)-1)); end; + + case 'cal', + t = [double(h.cal_min) double(h.cal_max)]; + if all(t==0), t = []; end; + + case 'aux_file', + t = deblank(h.aux_file); + + case 'hdr', % Hidden field + t = h; + + otherwise + error(['Reference to non-existent field ''' subs(1).subs '''.']); + end; + if numel(subs)>1, + t = subsref(t,subs(2:end)); + end; + c{ii} = t; + end; +case {'{}'}, + error('Cell contents reference from a non-cell array object.'); +case {'()'}, + opt = struct(opt); + t = subsref(opt,subs(1)); + if length(subs)>1 + c = {}; + for i=1:numel(t), + ti = class(t(i),'nifti'); + ti = rec(ti,subs(2:end)); + c = {c{:}, ti{:}}; + end; + else + c = {class(t,'nifti')}; + end; + +otherwise + error('This should not happen.'); +end; diff --git a/spm/nii_for_spm2/spm_conv_vol.mexa64 b/spm/nii_for_spm2/spm_conv_vol.mexa64 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ee(:,1)=e(:,ibar); + ee(:,2)=0; + elseif isnan(orient) + ee(:,1)=(1-sign(y(:,ibar))).*e(:,ibar); + ee(:,2)=(1+sign(y(:,ibar))).*e(:,ibar); + else + ee(:,1)= e(:,ibar); + ee(:,2)=-e(:,ibar); + + end + + try + if verLessThan('matlab', '7') % str2num(version('-release'))<=13 + h=errorbar(xe,y(:,ibar), ee(:,1), ee(:,2) ,'.k'); + else + h=errorbar('v6', xe,y(:,ibar),ee(:,1), ee(:,2) ,'.k'); + end + catch + h=errorbar('v6', xe,y(:,ibar),ee(:,1), ee(:,2) ,'.k'); + end + delete(h(2)); + + + % set(h(2), 'marker', 'none') + he(ibar)=h(1); + c=get(hb(ibar), 'FaceColor'); + if isnumeric(c) + set(he(ibar), 'Color', c); + else + c=get(hb(ibar), 'EdgeColor'); + if isnumeric(c) + set(he(ibar), 'Color', c); + end + end +end +hold off +% p=get(gca, 'Children'); +% set(gca, 'Children', p([end-1 end 1:end-2])); +% flipud(get(gca, 'Children'))) +if nargout > 0 + handles=[hb,he]; +end \ No newline at end of file diff --git a/barstem.m b/barstem.m new file mode 100644 index 0000000..5246c71 --- /dev/null +++ b/barstem.m @@ -0,0 +1,84 @@ +function h = barstem(x,y,z,bw) +%BARSTEM - 3D bar version of stem3 +% [] = barstem(x,y,z,barwidth) +% +% Example +% >> h=barstem(rand(15,1), rand(1,15), randn(1,15)); +% >> shading interp; set(h, 'CData', get(h, 'ZData'),'EdgeColor', 'k') +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-23 Creation +% +% ----------------------------- Script History --------------------------------- +[n] = numel(y); + + +if numel(x) ~= numel(y) + if numel(x)==1 || numel(y)==1 + x = x(:,ones(1,numel(y))); + y = y(:,ones(1,numel(x))); + end +end + +% Remove y values to 0 where y is NaN; +k = find(isnan(y)); +if ~isempty(k), y(k) = 0; end + +x=x(:)'; +y=y(:)'; +z=z(:)'; + +if nargin<4 + bw = [ min(diff(sort(x))) min(diff(sort(y))) ]; + bw = triu(sqrt((meshgrid(x)-meshgrid(x)').^2 + (meshgrid(y)-meshgrid(y)').^2 ),1); + bw(bw==0)=Inf; + bw=min(min(bw))*sqrt(1/2)/2; + %bw = bw*.95; + +end + +if numel(bw)==1 + bw=[bw bw]; +end + +zz = zeros(6*4,n); +yy = zz; +xx = zz; + +zz([6 7 10 11],:) = repmat(z, 4,1); +xx = kron(ones(6,1), kron([x-bw(1) ; x+bw(1) ], [1;1])); +yy = kron([y-bw(2) ; y+bw(2) ; y-bw(2)],ones(8,1)); +i = [1 4 13 16 17 20 21 22 23 24 ]; +zz(i,:) = nan; +yy(i,:) = nan; +xx(i,:) = nan; + +cc = repmat(z,24,1); + + +zz = reshape(zz, 4, [])'; +yy = reshape(yy, 4, [])'; +xx = reshape(xx, 4, [])'; + +cc = reshape(cc, 4, [])'; + + +edgec = get(gcf,'defaultaxesxcolor'); +facec = 'flat'; +h=[]; +h = [surf(... + 'xdata',xx,... + 'ydata',yy, ... + 'zdata',zz,... + 'CData',cc,... + 'FaceColor',facec,... + 'EdgeColor',edgec,... + 'tag',mfilename)]; \ No newline at end of file diff --git a/barweb.m b/barweb.m new file mode 100644 index 0000000..f7210fc --- /dev/null +++ b/barweb.m @@ -0,0 +1,170 @@ +function handles = barweb(barvalues, errors, width, groupnames, bw_title, bw_xlabel, bw_ylabel, bw_colormap, gridstatus, bw_legend) + +% +% Usage: handles = barweb(barvalues, errors, width, groupnames, bw_title, bw_xlabel, bw_ylabel, bw_colormap, gridstatus, bw_legend) +% +% Ex: handles = barweb(my_barvalues, my_errors, [], [], [], [], [], bone, [], bw_legend) +% +% barweb is the m-by-n matrix of barvalues to be plotted. +% barweb calls the MATLAB bar function and plots m groups of n bars using the width and bw_colormap parameters. +% If you want all the bars to be the same color, then set bw_colormap equal to the RBG matrix value ie. (bw_colormap = [1 0 0] for all red bars) +% barweb then calls the MATLAB errorbar function to draw barvalues with error bars of length error. +% groupnames is an m-length cellstr vector of groupnames (i.e. groupnames = {'group 1'; 'group 2'}). For no groupnames, enter [] or {} +% The errors matrix is of the same form of the barvalues matrix, namely m group of n errors. +% Gridstatus is either 'x','xy', 'y', or 'none' for no grid. +% No legend will be shown if the legend paramter is not provided +% +% The following default values are used if parameters are left out or skipped by using []. +% width = 1 (0 < width < 1; widths greater than 1 will produce overlapping bars) +% groupnames = '1', '2', ... number_of_groups +% bw_title, bw_xlabel, bw_ylabel = [] +% bw_color_map = jet +% gridstatus = 'none' +% bw_legend = [] +% +% A list of handles are returned so that the user can change the properties of the plot +% handles.curr_axis: handle to current axis +% handles.bars: handle to bar plot +% handles.errors: a vector of handles to the error plots, with each handle corresponding to a column in the error matrix +% handles.title: handle to plot title +% handles.xlabel: handle to xlabel +% handles.ylabel: handle to ylabel +% handles.legend: handle to legend +% handles.ca: handle to current axis +% +% +% See the MATLAB functions bar and errorbar for more information +% +% Author: Bolu Ajiboye +% Created: October 18, 2005 (ver 1.0) +% Updated: Dec 07, 2006 (ver 2.1) + +% Get function arguments +if nargin < 2 + error('Must have at least the first two arguments: barweb(barvalues, errors, width, groupnames, bw_title, bw_xlabel, bw_ylabel, bw_colormap, gridstatus, bw_legend)'); +elseif nargin == 2 + width = 1; + groupnames = 1:size(barvalues,1); + bw_title = []; + bw_xlabel = []; + bw_ylabel = []; + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 3 + groupnames = 1:size(barvalues,1); + bw_title = []; + bw_xlabel = []; + bw_ylabel = []; + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 4 + bw_title = []; + bw_xlabel = []; + bw_ylabel = []; + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 5 + bw_xlabel = []; + bw_ylabel = []; + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 6 + bw_ylabel = []; + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 7 + bw_colormap = jet; + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 8 + gridstatus = 'none'; + bw_legend = []; +elseif nargin == 9 + bw_legend = []; +end + +change_axis = 0; + +if size(barvalues,1) ~= size(errors,1) || size(barvalues,2) ~= size(errors,2) + error('barvalues and errors matrix must be of same dimension'); +else + if size(barvalues,2) == 1 + barvalues = barvalues'; + errors = errors'; + end + if size(barvalues,1) == 1 + barvalues = [barvalues; zeros(1,length(barvalues))]; + errors = [errors; zeros(1,size(barvalues,2))]; + change_axis = 1; + end + numgroups = size(barvalues, 1); % number of groups + numbars = size(barvalues, 2); % number of bars in a group + if isempty(width) + width = 1; + end + + % Plot bars and errors + handles.bars = bar(barvalues, width); hold on + if length(bw_colormap) + colormap(bw_colormap); + else + colormap(jet); + end + groupwidth = min(0.8, numbars/(numbars+1.5)); + for i = 1:numbars + x = (1:numgroups) - groupwidth/2 + (2*i-1) * groupwidth / (2*numbars); + handles.errors(i) = errorbar(x, barvalues(:,i), errors(:,i), 'k', 'linestyle', 'none'); + end + set(gcf, 'color', 'white') + + if ~isempty(bw_title) + handles.title = title(bw_title, 'fontsize',14); + else + handles.title = []; + end + if ~isempty(bw_xlabel) + handles.xlabel =xlabel(bw_xlabel, 'fontsize',12); + else + handles.xlabel = []; + end + if ~isempty(bw_ylabel) + handles.ylabel =ylabel(bw_ylabel, 'fontsize',12); + else + handles.ylabel = []; + end + + set(gca, 'xticklabel', groupnames, 'box', 'off', 'ticklength', [0 0], 'fontsize', 12, 'xtick',1:numgroups); + if isequal(gridstatus, 'x') + set(gca,'xgrid','on'); + set(gca,'ygrid','off'); + elseif isequal(gridstatus, 'y') + set(gca,'xgrid','off'); + set(gca,'ygrid','on'); + elseif isequal(gridstatus, 'xy') + set(gca,'xgrid','on'); + set(gca,'ygrid','on'); + else + set(gca,'xgrid','off'); + set(gca,'ygrid','off'); + end + + xlim([0.5 numgroups-change_axis+0.5]); + + if ~isempty(bw_legend) + handles.legend = legend(bw_legend, 'location', 'best', 'fontsize',12); + legend boxoff; + else + handles.legend = []; + end + + handles.ca = gca; + + hold off +end + +return \ No newline at end of file diff --git a/baseline_correction.m b/baseline_correction.m new file mode 100644 index 0000000..63d3ba8 --- /dev/null +++ b/baseline_correction.m @@ -0,0 +1,33 @@ +function [F]=baseline_correction(F,dc_offsetb,dc_offsete,Time,TimeDim) +%baseline_correction - DC offset, etc. +% [F]=baseline_correction(F,dc_offset_begin,dc_offset_end, TimeVector,TimeDim) +% +% TimeDim designate the dimension on which to perform the baseline +% correction. +% NB: if TimeDim=2 (or unset), F is assumed to be N channel x T samples x... +% (BrainStorm convention) + + +if nargin<5 + TimeDim=2; +end +F=permute(F, [TimeDim 1:TimeDim-1 TimeDim+1:ndims(F)]); +sF=size(F); +if nargin<4 + Time=1:sF(1); +end + +if dc_offsetb < Time(1) + fprintf(2,['WARNING: Time parameter inferior to first valid' ... + ' latency (%f), setting it to %f\n'], dc_offsetb, Time(1)) +end + +if dc_offsete > Time(end) + fprintf(2,'WARNING: Time parameter superior to the last valid latency (%f), setting it to %f', dc_offsete, Time(end)); +end +dc_offsetb=findclosest(dc_offsetb, Time); +dc_offsete=findclosest(dc_offsete, Time); + +mF=repmat(mean(F(dc_offsetb:dc_offsete,:),1), [sF(1), 1]); +F=F-reshape(mF,sF); +F=ipermute(F, [TimeDim 1:TimeDim-1 TimeDim+1:ndims(F)]); \ No newline at end of file diff --git a/beamformerkernel.m b/beamformerkernel.m new file mode 100644 index 0000000..b689bba --- /dev/null +++ b/beamformerkernel.m @@ -0,0 +1,25 @@ +function = beamformerkernel(input,varargin) +%BEAMFORMERKERNEL - One line description goes here. +% [] = beamformerkernel(input) +% +% Example +% >> beamformerkernel +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-04 Creation +% +% ----------------------------- Script History --------------------------------- + + + bst_message_window('Calculating the spatial filter. . .'); + spatialFilter = Kernel'*Cm_inv; + ImagingKernel= (spatialFilter) ./ repmat(source_power_inv', 1,size(spatialFilter,2)); diff --git a/between.m b/between.m new file mode 100644 index 0000000..6b8a387 --- /dev/null +++ b/between.m @@ -0,0 +1,41 @@ +function tf = between(x,ab,mode) +%BETWEEN - One line description goes here. +% +% [TF] = between(x,[a b]) is TRUE if and only if x is between a and b or +% x is equal to any of the two, independently whether a <= b or a >= b +% +% [TF] = between(x,[a b],'strict') is TRUE if and only if x is between a and +% b but not equal to any of the two (again whether a>b or b> between(5, [12,0]) returns TRUE (1) +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2008 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2008-10-10 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<2 + error([mfilename '() requires 3 arguments']); +end + +a = min(ab(:)); +b = max(ab(:)); + +if nargin<3 + mode=[]; +end +if isequal(mode, 'strict') + tf= (a')+18; pauth1=pauth1(1); + pauth2 = strfind(rem(pauth1:min(end,(pauth1+500))),'')-1; pauth2=pauth2(1); + authstring = lower(rem(pauth1:(pauth1+pauth2-1))); % list of authors of the paper + authstring = strrep(authstring,'',''); + authstring = strrep(authstring,'',''); + authstring = strrep(authstring,'…','...'); + + % check that the required name is indeed in the author list. + paperok=0; + pos=strfind(authstring,name); + if length(pos), + pos=pos(1); + paperok=1; + if pos>1, + % check for wrong initials (eg, 'ga einstein' should not + % match for 'a einstein') + pl=authstring(pos-1); + if ((pl>='a')&&(pl<='z'))||(pl=='-'), + paperok=0; + end; + end; + if pos<(length(authstring)-length(name)), + % check for wrong 'suffix' (eg, 'einstein-joliot' should not + % match for 'einstein') + nl=authstring(pos+length(name)); + if ((nl>='a')&&(nl<='z'))||(nl=='-'), + paperok=0; + end; + end; + end; + + if paperok, % if the required name is indeed in the author list + ncit = ncit+1; + ncitinthispage = ncitinthispage +1; + p=strfind(rem,'Cited by ')+9; p=p(1); + substr=rem(p:(p+5)); + pend=strfind(substr,'<'); pend=pend(1); + ncited(ncit)=str2double(substr(1:(pend-1))); + rem=rem((p+2):end); + if any(strncmpi(varargin,'verb',1)) + disp(['#' num2str(ncit) ': (' num2str(ncited(ncit)) '), ' authstring]); + end; + else + if any(strncmpi(varargin,'verb',1)) + disp(['rejected: ' authstring]); + end; + p=strfind(rem,'Cited by ')+9; p=p(1); + rem=rem((p+2):end); + end; + end; + if any(strncmpi(varargin,'verb',1)) + disp(' '); + end; + if ncit==0, + seenextpage=0; + else + if ((ncited(ncit)<2)||(~length(findstr(rem,'Next')))), + seenextpage=0; + end; + end; +end; % while seenextpage + +if length(ncited), + % sort the list (it should be sorted, but sometimes GS produces unsorted results) + ncited=sort(ncited); ncited=ncited(ncit:-1:1); + + % computes the H-factor: + h=sum(ncited>=(1:ncit)); + + % plot the 'Cited by' number: + if any(strncmpi(varargin,'plot',1)) + loglog(1:ncit,ncited,'.-',1:ncit,1:ncit,'--',h,h,'o'); + xlabel('Paper rank'); ylabel('Number of citations'); + title(['h-index plot for ''' name ''' (h=' num2str(h) ')']); + end; + + % some displays if no output argument: + if nargout==0, + disp(['Number of cited papers: ' num2str(length(ncited))]); + disp(['''Cited by'' list: ' num2str(ncited)]); + disp(['Total number of citations: ' num2str(sum(ncited))]); + disp(['h-index = ' num2str(h)]); + clear h; + end; +else + h=0; + if nargout==0, + disp('No result found'); + clear h; + end; +end; diff --git a/bibliography/pmid2bib.m b/bibliography/pmid2bib.m new file mode 100644 index 0000000..388fe61 --- /dev/null +++ b/bibliography/pmid2bib.m @@ -0,0 +1,16 @@ +function t=p2b(pmid) +if nargin<1 + pmid = 20070959; +end +if isnumeric(pmid) + pmid = sprintf('%d',pmid); +end +pubmed = @(pmid) urlread('http://www.ncbi.nlm.nih.gov/sites/entrez', 'post', { 'cmd' 'search' 'db' 'pubmed' 'term' sprintf('%s[pmid]',pmid) 'doptcmdl' 'medline' 'dispmax' '200' 'tool' 'resource'}) +t= pubmed(pmid); +t = strread(t, '%s', 'delimiter', '\n') +au=strrep(t(strmatch('AU', t)), 'AU - ', ''); +au = sprintf('%s%s.', sprintf('%s, ', au{1:end-1}), au{end}) +ti= regexprep(t{strmatch('TI', t)}, '.*- ', '') +so = regexprep(t{strmatch('SO', t)}, '.*- ', '') + +t=sprintf('%s %s. %s',au,ti,so) \ No newline at end of file diff --git a/bit.m b/bit.m new file mode 100644 index 0000000..a9fbbd6 --- /dev/null +++ b/bit.m @@ -0,0 +1,12 @@ +function [v]=bit(x,n,b) +% bit - get the n-th bit of a number x +% [v]=bit(x,n,b) +% b cannot yet be other than 2 +if nargin<3 + b=2; +elseif ~isequal(b,2) + error('Only base-2 bits available ') +end +v=rem(floor(x(:)*pow2(-(n))),2); +return + diff --git a/bitget2.m b/bitget2.m new file mode 100644 index 0000000..81000f3 --- /dev/null +++ b/bitget2.m @@ -0,0 +1,26 @@ +function C = bitget2(A,BITS) +%BITGET2 - Get bit values (also from arrays) +% [C] = bitget2(A,BITS) returns a N-by-B array +% where N = numel(A) and B=numel(BITS) +% +% Example +% >> bitget2([1 5 3 15], [1:3]) +% +% See also: bitget + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-03-31 Creation +% +% ----------------------------- Script History --------------------------------- + +A=A(:); +for i=1:numel(A) + C(i,:)=bitget(A(i),BITS); +end \ No newline at end of file diff --git a/blackguis.m b/blackguis.m new file mode 100644 index 0000000..bf43d45 --- /dev/null +++ b/blackguis.m @@ -0,0 +1,15 @@ +function [ output_args ] = blackguis( hf ) +%blackguis - Make the (Figure and Axes) black +if nargin<1 + hf=gcf; +end +for ihf=1:length(hf) + + set(hf(ihf), 'color', 'k') + ha=get(hf(ihf), 'children') + set(ha, 'color', 'k') + set(ha, 'Xcolor', 'w') + set(ha, 'Ycolor', 'w') + set(ha, 'Zcolor', 'w') + +end \ No newline at end of file diff --git a/bootstrap.m b/bootstrap.m new file mode 100644 index 0000000..f597a65 --- /dev/null +++ b/bootstrap.m @@ -0,0 +1,47 @@ +function [biais, variance, fboot] = bootstrap(f, X, B, P1, P2, P3) +%BOOTSTRAP Bootstrap estimates of bias and variance. +% +% [BIAS VAR Fboot] = BOOTSTRAP('f', X, B) gives the following elements +% calculated by the bootstrap method using B replications: +% - bias of f(X), +% - variance of f(X), +% - corrected f(X). +% The data in X must be organised in rows (see function CORRCOEF) +% The bias formula is the standard one (not .632). +% +% [BIAS VAR Fboot] = BOOTSTRAP('f', X, B, opt1, opt2, opt3) allows to +% pass up to 3 additional arguments to 'f'. +% +% BOOTSTRAP needs the AVEVAR function. +% (c) 1997, C. Goutte. +% See also: JACKKNIFE. + +if (nargin < 3) | (nargin > 6) + error('BOOTSTRAP: wrong number of arguments.') ; +end + +[N P] = size(X) ; +if (N < 2) + error('BOOTSTRAP: not enough samples.') +end +evalstr = [f, '(X_i'] ; +for i = 1:(nargin - 3) + evalstr = [evalstr, ',P', int2str(i)] ; +end +evalstr = [evalstr, ')'] ; + +f_i = zeros(B,1) ; +X_i = X ; +fhat = eval(evalstr) ; + +for i = 1:B + idx_i = ceil(rand(1,N)*N) ; +% disp(idx_i) + X_i = X(idx_i, :) ; + f_i(i) = eval(evalstr) ; +end +[fboot, variance] = avevar(f_i) ; +biais = (fboot - fhat) ; +fboot = 2 * fhat - fboot ; + +% (c) 16/05/97, CG. diff --git a/brainstorm/bst_lighting.m b/brainstorm/bst_lighting.m new file mode 100644 index 0000000..6d50e90 --- /dev/null +++ b/brainstorm/bst_lighting.m @@ -0,0 +1,81 @@ +function []=bst_lighting(varargin) +% bst_lighting - nice viewing parameters for 3D surfaces + +Referential='CTF'; % not: 'AIMS' nor 'SPM' + +% Process inputs (or no input!) & link to handles +[hp,ha,hf]=findTessellationHandles(varargin{:}); + +if not(isempty(hp)) + verts=get(hp,'Vertices'); + % [k,k]=sort(max(verts)-min(verts)); + % if isequal(k,[3 2 1]) + + % If the frontal pole is lower (in Z) than the vertex + if mean(verts(:,3)) > median(verts(:,3)) + Referential='MNI'; + elseif verts(imax(verts(:,1)),3) < max(verts(:,3)) + Referential='CTF'; + else + Referential='AIMS'; + end +end + +% Lighting +hl=findobj(ha, 'type', 'light'); +delete(hl) +clear hl; +switch Referential + case 'CTF' + % hl(1) = light('Position', [1 1 1 ]); + % hl(2) = light('Position', [1 -1 1 ]); + % hl(3) = light('Position', [-1 0 0 ]); + % hl(4) = light('Position', [0 1 -.2 ]); + % hl(5) = light('Position', [0 -1 -.2 ]); + hl(1) = camlight(30,30 ); + hl(2) = camlight(120,30); + hl(3) = camlight(90,-60); + hl(3) = camlight(0, 90); + hl(4) = camlight(-65, -20, 'infinite'); % light('Position', [0 -.2 1]); + hl(5) = camlight(-115, -20, 'infinite'); % light('Position', [0 -.2 -1]); + set(hl,'color',[.8 1 1]/3/.7); % mute the intensity of the lights + + case 'AIMS' + hl(1) = light('Position', [1 1 -1 ]); + hl(2) = light('Position', [1 -1 -1 ]); + hl(3) = light('Position', [-1 0 0 ]); + hl(4) = light('Position', [0 1 .2 ]); + hl(5) = light('Position', [0 -1 .2 ]); + set(ha, 'Zdir', 'reverse') + % hl(1) = camlight(-20,30); + % hl(2) = camlight(20,30); + % hl(3) = camlight(-20,-30); + % hl(4) = light('Position', [0 -.2 1]); + % hl(5) = light('Position', [0 -.2 -1]); + set(hl,'color',[.8 1 1]/3/.7); % mute the intensity of the lights + + case 'MNI' + hl(1) = light('Position', [ 1 1 1 ]); + hl(2) = light('Position', [-1 1 1 ]); + hl(3) = light('Position', [ 0 -1 0 ]); + hl(4) = light('Position', [ 1 0 -.2 ]); + hl(5) = light('Position', [-1 0 -.2 ]); + % hl(1) = camlight(-20,30); + % hl(2) = camlight(20,30); + % hl(3) = camlight(-20,-30); + % hl(4) = light('Position', [0 -.2 1]); + % hl(5) = light('Position', [0 -.2 -1]); + set(hl,'color',[.8 1 1]/3/.7); % mute the intensity of the lights + +end + +% Viewing parameters +% if isequal(Referential, 'CTF') & mean(verts(:,3)) < 0 +% set(ha, 'Zdir', 'reverse') +% end +% view(2) +% view([0 180 0]) +% view(140,20); +axis off +axis image +% rotate3daxes(ha,'on') diff --git a/brainstorm/bst_struct2fv.m b/brainstorm/bst_struct2fv.m new file mode 100755 index 0000000..fc80d2b --- /dev/null +++ b/brainstorm/bst_struct2fv.m @@ -0,0 +1,35 @@ +function fv = bst_surf2fv(s) +%BST_SURF2FV - One line description goes here. +% [fv] = bst_surf2fv(s) +% will remove extra fields of s to keep only the "Vertices" and "Faces" ones +% Note: Upper case/lower case discrepancies are ignored. +% +% Example +% >> bst_surf2fv +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-09-18 Creation +% +% ----------------------------- Script History --------------------------------- + +fv=[]; +for f={'faces', 'vertices'} + if isfield(s, f{1}) + fv=setfield(fv, f{1}, getfield(s, f{1})); + elseif isfield(s, lower(f{1})) + fv=setfield(fv, f{1}, getfield(s, lower(f{1}))); + elseif isfield(s, [upper(f{1}(1)) upper(f{1}(2:end))]) + fv=setfield(fv, f{1}, getfield(s, [upper(f{1}(1)) upper(f{1}(2:end))])); + else + warning(sprintf('No field %f in the structure', f{1})) + end +end \ No newline at end of file diff --git a/brainstorm/bst_surface2fv.m b/brainstorm/bst_surface2fv.m new file mode 100755 index 0000000..f254861 --- /dev/null +++ b/brainstorm/bst_surface2fv.m @@ -0,0 +1,44 @@ +function fv = bst_surface2fv(s) +%BST_SURFACE2FV - One line description goes here. +% [fv] = bst_surface2fv(s) +% will remove extra fields of s to keep only the "Vertices" and "Faces" ones +% Note: Upper case/lower case discrepancies are ignored. +% +% Example +% >> bst_surface2fv +% +% See also: + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2009 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2009-09-18 Creation +% +% ----------------------------- Script History --------------------------------- + +fv=[]; +FIELDS={'faces', 'vertices'}; +for iField=1:2 + f=FIELDS{iField}; + if ~isfield(s, f) + f = [upper(f(1)) f(2:end)]; + if ~isfield(s,f) + f=NaN; + end + end + if isnan(f) + warning(sprintf('No field %s in the structure', f)) + else + fv=setfield(fv,FIELDS{iField}, getfield(s,f)); + if iField==2 + if size(fv.vertices,2) ~= 3 && size(fv.vertices,1) == 3 + fv.vertices=fv.vertices'; + end + end + end +end \ No newline at end of file diff --git a/brainstorm/bst_trimSurface.m b/brainstorm/bst_trimSurface.m new file mode 100644 index 0000000..6359d7b --- /dev/null +++ b/brainstorm/bst_trimSurface.m @@ -0,0 +1,41 @@ +function []=bst_trimSurface(h,xyz) +if (nargin<2) + xyz=h; + h=findTessellationHandles +end + +iSurf=1; +TessInfo(iSurf)=get(h); +TessInfo(iSurf).trimXYZ=[xyz(1) xyz(2) xyz(3)]; +TessInfo(iSurf).alpha=.5; +vertices = get(h,'vertices'); +FaceVertexAlphaData = get(h,'FaceVertexAlphaData'); + +if isempty(FaceVertexAlphaData) + FaceVertexAlphaData = TessInfo(iSurf).alpha*ones(size(vertices,1),1); +end + + +iNoModif = []; +for iCoord = 1:3 + vertx = vertices(:,iCoord)'; + vertx = vertx-mean(vertx); + vertx = vertx/max(abs(vertx)); + if TessInfo(iSurf).trimXYZ(iCoord) > 0 + iNoModif = [iNoModif,find(vertx < TessInfo(iSurf).trimXYZ(iCoord))]; + elseif TessInfo(iSurf).trimXYZ(iCoord) < 0 + iNoModif = [iNoModif,find(vertx > TessInfo(iSurf).trimXYZ(iCoord))]; + else + %doNothing + end + +end + +if isempty(iNoModif) + set(h,'alphadatamapping','scaled','FaceVertexAlphaData',TessInfo(iSurf).alpha*ones(size(vertices,1),1),'FaceAlpha',TessInfo(iSurf).alpha,... + 'backfacelighting','lit') +else + FaceVertexAlphaData(unique(iNoModif)) = TessInfo(iSurf).alpha; + FaceVertexAlphaData(setdiff(1:end,iNoModif)) = 0; + set(h,'alphadatamapping','none','FaceVertexAlphaData',FaceVertexAlphaData,'FaceAlpha','interp','backfacelighting','unlit') +end \ No newline at end of file diff --git a/brainstorm/carto_cortex.m b/brainstorm/carto_cortex.m new file mode 100644 index 0000000..2741d82 --- /dev/null +++ b/brainstorm/carto_cortex.m @@ -0,0 +1,153 @@ +function [h]=carto_cortex(faces,varargin) +% carto_cortex - Plot cortical surface +% +% [h]=carto_cortex(FV) +% carto_cortex(faces,vertices) +% carto_cortex(FV, values) +% carto_cortex(faces,vertices,values) +% carto_cortex(FV,values, 'Option', OptionValue,...) +% INPUTS: +% FV : is a struct with .faces and .vertices, see PATCH +% OUPUT: +% h : a handle to the patch + +options={}; +if nargin>1 + dataname=inputname(2); +else + dataname=''; +end +data=[]; +if nargin==1 && ~isstruct(faces) && isvector(faces) + data=faces; + dataname=inputname(1); + global faces + p.faces=faces; + global vertices + p.vertices=vertices; +elseif isstruct(faces) && ... + ((isfield(faces, 'faces') | isfield(faces, 'Faces')) && (isfield(faces, 'vertices') | isfield(faces, 'Vertices'))) + p=faces; + + if ~isfield(p, 'vertices') && isfield(p, 'Vertices') + if iscell(p.Vertices) + if sum(cellfun('isempty',p.Vertices))==1 + p.vertices=p.Vertices{~cellfun('isempty',Vertices)}; + elseif nargin>2 && ~isempty(data) + p.vertices=p.Vertices{cellfun('prodofsize',Vertices)/3==length(data)}; + end + else + p.vertices=p.Vertices; + end + end + + if ~isfield(p, 'faces') && isfield(p, 'Faces') + if iscell(p.Faces) + if sum(cellfun('isempty',p.Faces))==1 + p.faces=p.Faces{~cellfun('isempty',Faces)}; + elseif ~isempty(data) + p.faces=p.Faces{cellfun('prodofsize',p.Vertices)/3==length(data)}; + end + else + p.faces=p.Faces; + end + end + + + +elseif iscell(faces) + p.vertices=faces{1}; + p.faces=faces{2}; + +else + if nargin>2 + dataname=inputname(3); + end + if max(faces(:))==max(size(varargin{1})) + p.faces=faces; + p.vertices=varargin{1}; + elseif max(varargin{1}(:))==max(size(faces)) + p.vertices=faces; + p.faces=varargin{1}; + faces = []; + elseif max(faces(:))==max(size(varargin{1}))-1 + p.faces=faces+1; + p.vertices=varargin{1}; + end + varargin(1)=[]; +end + + +if(size(p.vertices,2) > 3), % assume transposed + p.vertices = p.vertices'; % if the assumption is wrong, will crash below anyway +end + +if nargin>=2 & ~isempty(varargin) + if isnumeric(varargin{1}) + p.data=varargin{1}; + % if not(all(size(data) == [size(vertices, 1) 1])) + % error('Data should be the same length as vertex number') + % return + % end + varargin(1)=[]; + end + options=varargin(1:end); +end + +if ~isfield(p, 'data') + p.data=[]; +end + +if isempty(get(0, 'CurrentFigure')) | isempty(get(gcf, 'CurrentAxes')) + NewAxes=1; +else + NewAxes=0; +end + +h = patch('Faces',p.faces,'Vertices',p.vertices); + +if ~isempty(p.data) + if prod(size(p.data))==size(p.vertices, 1) + p.data=p.data(:); + elseif size(p.data,1)==size(p.vertices, 1) && size(p.data, 2)>3 +v error('Data are not a vector: you might want to use view_MNEresults instead!') + return + end + + set(h,'FaceVertexCData',p.data); + if size(p.data,2)==1 + set(h,'FaceColor','interp'); + end +else + set(h,'facecolor',rand(1,3)); +end +NewAxes = NewAxes || isequal(get(gca, 'NextPlot'), 'replace'); +set(h, 'FaceLighting','Gouraud','EdgeLighting','none','EdgeColor','none'); +set(h, 'Tag', 'Cortex'); + +% Material of the surface +material(h, [0.3, 0.8, .10, 10, .50]) +p.h=h; +set(h, 'UserData', p); + +if ~isempty(options) + set(h, options{:}); +end + +if NewAxes + try + view(140,20); + bst_lighting(h); + rotate3d on + catch + set(gcf, 'renderer', 'zbuffer') + view(140,20); + bst_lighting(h); + rotate3d on + end + if ~isempty(dataname) + title(dataname) + end + colorbar + meeg_menu(h); +end diff --git a/brainstorm/carto_flatcap.m b/brainstorm/carto_flatcap.m new file mode 100644 index 0000000..70cf64d --- /dev/null +++ b/brainstorm/carto_flatcap.m @@ -0,0 +1,209 @@ +function [hs,hp,hc,hl,hn] = carto_flatcap(Channel, data, Contours,DrawLines,DrawNose,BackgroundColor) +%CARTO_DISC - Display M/EEG scalp data on a 2D projection of sensors +% +% [hs,hp] = carto_flatcap(Channel, data) +% [hs,hp,hc,hl,hn]= carto_flatcap(Channel, data,Contours,DrawLines,DrawNose) +% +% Contours: either the number of contours or their levels (use [X X] for +% single value) + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-21 Creation +% +% ----------------------------- Script History --------------------------------- +if nargin<6 + BackgroundColor = [ 1 1 1 ]; +end +if nargin<5 + DrawNose=1; +end +if nargin<4 + DrawLines=0; +end +if nargin<3 + Contours=6; +end +if ~exist('data','var') + data=[]; +end + +if ~isvector(data) && prod(size(data)) == max(size(data)) + data=data(:); +end +if ~isvector(data) + error('Data must be 1-D') +end + +% I'm tricky, i draw the line in white on white background! +set(gcf, 'color',BackgroundColor) + +if isempty(data) + data(1:length(Channel)) = 0; +end +data=data(:); +%isens=1:min(size(data,1),length(Channel)); +isens=1:size(data,1); +if isfield(Channel, 'Loc') + for i=1:length(isens) + sensloc(i,1:3)=Channel(isens(i)).Loc(:,1)'; + end + Channel=Channel(isens); +else + sensloc=Channel(isens,:); + Channel=[]; +end +CONTOURNUM = 0; + + + +nans=find(isnan(data)); +sensloc(nans,:)=[]; +data(nans)=[]; +nmes = size(sensloc,1); +[TH,PHI,R] = cart2sph(sensloc(:,1),sensloc(:,2),sensloc(:,3)-max(sensloc(:,3))); +R2 = R./cos(PHI).^.2; +[Y,X] = pol2cart(TH,R2); +tri = delaunay(Y,X); +% h=patch('faces',tri,'vertices',[Y,X,0.*X],'CData',cdata,'edgecolor','none','FaceColor','interp'); +xmax=max(X); +xmin=min(X); +ymax=max(Y); +ymin=min(Y); +rmax2=max(xmax,abs(xmin)).^2 + max(ymax,abs(ymin)).^2; + +%% Surface +cla +hp=patch('faces',tri,'vertices',[Y,X,0.*X],'FaceVertexCData',data,'edgecolor','none','FaceColor','interp'); +axis image +hold on + +set(hp,'ButtonDownFcn','subarray(get(gcbo,''CData''),imax(-edist(mean(get(get(gcbo,''Parent''),''CurrentPoint'')),nd2array(cat(3,get(gcbo,''Xdata''),get(gcbo,''Ydata''),get(gcbo,''Zdata'')),3)'')),Inf)') + +%% UI menu +cmenu = uicontextmenu; +set(hp, 'uiContextMenu', cmenu) +uimenu(cmenu,'Label', 'Show markers of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensor''),''Visible'',''on'')') +uimenu(cmenu,'Label', 'Hide markers of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensor''),''Visible'',''off'')') +uimenu(cmenu,'Label', 'Show name of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensorlabel''),''Visible'',''on'')') +uimenu(cmenu,'Label', 'Hide name of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensorlabel''),''Visible'',''off'')') +uimenu(cmenu,'Label', 'Sensors value (sorted)', 'callback', 'for i=findobj(gcbf,''tag'',''sensor''); end;') +%% Sensors +for i=1:length(data) + hs(i)=plot3(Y(i),X(i),min(abs(sensloc(:,3))),'o'); + set(hs(i),'markerfacecolor',[.2 1 .2],'markersize',3,'Tag','sensor'); + if isfield(Channel, 'Name') + ch=setdiff(1:length(Channel), nans); + %set(hs(i), 'ButtonDownFcn', sprintf('fprintf(''%s (%d)'');try;fprintf('' = '');end;fprintf(''\\n'');', Channel(ch(i)).Name,i)); + set(hs(i), 'ButtonDownFcn', 'fprintf(''%s (%d)'', getappdata(gcbo,''Label''), getappdata(gcbo,''Index''));try;fprintf('' = '');end;fprintf(''\n'');'); + setappdata(hs(i), 'Label', Channel(ch(i)).Name); + setappdata(hs(i), 'Index', i); + h = text(Y(i),X(i), Channel(ch(i)).Name, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'top'); + set(h, 'tag', 'sensorlabel', 'visible', 'off') + end +end + + +%% Nose & Ears +if DrawNose + rmax=max(X); + headl = 0:2*pi/100:2*pi; + basex = .18*rmax; + tip = rmax*1.15; + base = rmax-.004*rmax/.1; + HLINEWIDTH = 2; + HCOLOR = [1 1 1]- get(gcf, 'color'); + z_level = -min(abs(sensloc(:,3))); + hold on + hn=plot3([base;tip;base],[.18*rmax;0;-.18*rmax],[base;tip;base].*0+z_level); % plot nose + LE = [ + 0.0216 0.1455 + 0.0368 0.1523 + 0.0368 0.1565 + 0.0334 0.1622 + 0.0271 0.1633 + 0.0123 0.1565 + 0.0040 0.1535 + -0.0063 0.1548 + -0.0164 0.1582 + -0.0249 0.1607 + -0.0294 0.1575 + -0.0308 0.1514 + -0.0247 0.1441 + -0.0139 0.1422 + -0.0029 0.1422 + ]./.15; + LE(end+1,:)=LE(1,:); + LE = LE*rmax; + hn(2) = plot3(LE(:,1), LE(:,2), LE(:,1).*0+z_level); + hn(3) = plot3(LE(:,1), -LE(:,2), LE(:,1).*0+z_level); + set(hn, 'Color',HCOLOR,'LineWidth',HLINEWIDTH) +end + + +%% Contours +if length(Contours)>0 + GRID_SCALE = 100; % 67 in original + xi = linspace(xmin,xmax,GRID_SCALE); % x-axis description (row vector) + yi = linspace(xmin,ymax,GRID_SCALE); % y-axis description (row vector) + INTERPOLATION = 'cubic'%'v4'; + [Xi,Yi,Zi] = griddata(Y,X,data,yi',xi,INTERPOLATION); % Interpolate data + % remove points which fall out of the head plot + for i=1:length(Zi) + if rmax2<(Xi(i)^2+Yi(i)^2) + Zi(i)=NaN; + end + end + + if any(Contours<0) || any(rem(Contours, 1)~=0) || length(Contours)>1 || isequal(Contours,0) + CONTOURLEVELS = Contours; + CONTOURNUM = length(CONTOURLEVELS); + else + CONTOURNUM = Contours; + CONTOURLEVELS=max(abs(data))/(CONTOURNUM/2+1); + if mod(CONTOURNUM,2) + CONTOURLEVELS=CONTOURLEVELS.*[ceil(-CONTOURNUM/2):floor(CONTOURNUM/2)]; + else + CONTOURLEVELS=CONTOURLEVELS.*[setdiff((-CONTOURNUM/2):(CONTOURNUM/2),0)]; + end + end + for i=1:CONTOURNUM + [c,hc(i)]=contour(Xi,Yi,Zi,CONTOURLEVELS(i),'w'); + end + set(hc, 'tag', [mfilename ':contour'] , 'color', get(gcf, 'color')) + colorbar +end + +%% Colors +colorbar + +view(-90,90); +hold off +axis tight +axis off +% Believe it or not the scribe code for colorbar is buggy when used with +% contour plots in the picture... See line 228, in scribe.colorbar +caxis(max(abs(data))*[-1 1]) +ha=colorbar; +% KND 2009-11-12 changed child=get(ha,'children'); +child=findobj(get(ha,'children'), 'Type', 'image'); +set(ha, 'YLim', caxis); +set(child, 'ydata', caxis); +axes(ha) +if DrawLines & CONTOURNUM>0 + hl=line((get(ha,'Xlim'))'*ones(1,CONTOURNUM),ones(2,1)*get(hc, 'LevelList')); + set(hl,'LineStyle', '-') + set(hl,'Color', get(hc(1),'color')) +end +axes(get(hp, 'Parent')) +hold off +return + + + diff --git a/brainstorm/carto_flatdisc.m b/brainstorm/carto_flatdisc.m new file mode 100644 index 0000000..9eaaaa9 --- /dev/null +++ b/brainstorm/carto_flatdisc.m @@ -0,0 +1,346 @@ +function h = carto_flatdisc(Channel, data, Contours, DrawLines,DrawNose,BackgroundColor) +%CARTO_DISC - Display M/EEG scalp data on a 2D disc +% [] = carto_flatdisc(input) +% +%Syntax: +% [sensors] = carto_flatdisc(Channel,data) +% [sensors] = carto_flatdisc(Channel,data,Contours,DrawLines,DrawNose,BackgroundColor) +% + + +% Author: K. N'Diaye (kndiaye01yahoo.fr) +% Copyright (C) 2006 +% This program is free software; you can redistribute it and/or modify it +% under the terms of the GNU General Public License as published by the +% Free Software Foundation; either version 2 of the License, or (at your +% option) any later version: http://www.gnu.org/copyleft/gpl.html +% +% ----------------------------- Script History --------------------------------- +% KND 2006-02-21 Creation +% KND 2010-03-25 +contours +% ----------------------------- Script History --------------------------------- + +if nargin<6 + BackgroundColor = [ 1 1 1 ]; +end +if nargin<5 + DrawNose=1; +end +if nargin<4 + DrawLines=0; +end +if nargin<3 + Contours=6; +end +% Guess that inputs may have been inverted: +if isfield(data, 'Loc') || (~isvector(data) && isvector(Channel)) + tmp = data; + data = Channel; + Channel = tmp; + clear tmp; +end + +if prod(size(data))>max(size(data)) && ~isvector(data) + error('Data must be 1-D') +end + +% I'm tricky, i draw the line in white on white background! +set(gcf, 'color',BackgroundColor) + +data=data(:); +isens=1:min(size(data,1),length(Channel)); +if isfield(Channel, 'Loc') + for i=1:length(isens) + sensloc(i,1:3)=Channel(isens(i)).Loc(:,1)'; + end + Channel=Channel(isens); +else + sensloc=Channel(isens,:); + Channel=[]; +end +CONTOURNUM = 0; + + +%% Some Geometry... + +% [TH,PHI,R] = cart2sph(sensloc(:,1),sensloc(:,2),sensloc(:,3)-max(sensloc(:,3))); +% R2 = R./cos(PHI).^.2; +% [Y,X] = pol2cart(TH,R2); +% tri = delaunay(Y,X); +% % h=patch('faces',tri,'vertices',[Y,X,0.*X],'CData',cdata,'edgecolor','none','FaceColor','interp'); +% + +center=[0 0 0]; + +nans=find(isnan(data)); +sensloc(nans,:)=[]; +data(nans)=[]; +nmes = size(sensloc,1); + + +[teta,phi,R] = cart2sph(sensloc(:,1)-center(1),sensloc(:,2)-center(2),sensloc(:,3)-center(3)); +R = mean(R); +phimin = min(phi); +phimax = max(phi); +tetamin = min(teta); +tetamax = max(teta); +[x y z] = sph2cart(teta,phi,R*ones(size(phi))); +[xt yt zt] = sph2cart(teta,phi,R*1.0*ones(size(phi))); +N = 25; +phi = (phimin:(pi/2 - phimin)/N:pi/2)'*ones(1,N+1); +teta= (0: 2*pi/N : 2*pi )'*ones(1,N+1); +xs = cos(teta').*cos(phi); +ys = sin(teta').*cos(phi); +zs = sin(phi); +xs=xs(:)*R; +ys=ys(:)*R; +zs=zs(:)*R; + +[TH,PHI,R] = cart2sph(xs,ys,zs-max(zs)); +R2 = R./cos(PHI).^.2; +[Y,X] = pol2cart(TH,R2); + +%% Surface +tri = delaunay(Y,X); +cdata = griddata(xt,yt,data,X,Y,'invdist'); +hp=patch('faces',tri,'vertices',[Y,X,0.*X],'CData',cdata,'edgecolor','none','FaceColor','interp'); + +axis image +hold on + +set(hp,'ButtonDownFcn','subarray(get(gcbo,''CData''),imax(-edist(mean(get(get(gcbo,''Parent''),''CurrentPoint'')),nd2array(cat(3,get(gcbo,''Xdata''),get(gcbo,''Ydata''),get(gcbo,''Zdata'')),3)'')),Inf)') + +[TH,PHI,R] = cart2sph(sensloc(:,1),sensloc(:,2),sensloc(:,3)-max(sensloc(:,3))); +R2 = R./cos(PHI).^.2; +[Y,X] = pol2cart(TH,R2); +tri = delaunay(Y,X); +xmax=max(X); +xmin=min(X); +ymax=max(Y); +ymin=min(Y); +rmax2=max(xmax,abs(xmin)).^2 + max(ymax,abs(ymin)).^2; + + +%% UI menu +cmenu = uicontextmenu; +set(hp, 'uiContextMenu', cmenu) +uimenu(cmenu,'Label', 'Show markers of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensor''),''Visible'',''on'')') +uimenu(cmenu,'Label', 'Hide markers of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensor''),''Visible'',''off'')') +uimenu(cmenu,'Label', 'Show name of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensorlabel''),''Visible'',''on'')') +uimenu(cmenu,'Label', 'Hide name of sensors', 'callback', 'set(findobj(gcbf,''tag'',''sensorlabel''),''Visible'',''off'')') +uimenu(cmenu,'Label', 'Sensors value (sorted)', 'callback', 'for i=findobj(gcbf,''tag'',''sensor''); end;') +%% Sensors +for i=1:length(data) + hs(i)=plot3(Y(i),X(i),min(abs(sensloc(:,3))),'o'); + set(hs(i),'markerfacecolor',[.2 1 .2],'markersize',3,'Tag','sensor'); + if isfield(Channel, 'Name') + ch=setdiff(1:length(Channel), nans); + %set(hs(i), 'ButtonDownFcn', sprintf('fprintf(''%s (%d)'');try;fprintf('' = '');end;fprintf(''\\n'');', Channel(ch(i)).Name,i)); + set(hs(i), 'ButtonDownFcn', 'fprintf(''%s (%d)'', getappdata(gcbo,''Label''), getappdata(gcbo,''Index''));try;fprintf('' = '');end;fprintf(''\n'');'); + setappdata(hs(i), 'Label', Channel(ch(i)).Name); + setappdata(hs(i), 'Index', i); + h = text(Y(i),X(i), Channel(ch(i)).Name, 'HorizontalAlignment', 'center', 'VerticalAlignment', 'top'); + set(h, 'tag', 'sensorlabel', 'visible', 'off') + end +end + + +%% Nose & Ears +if DrawNose + rmax=max(X); + headl = 0:2*pi/100:2*pi; + basex = .18*rmax; + tip = rmax*1.15; + base = rmax-.004*rmax/.1; + HLINEWIDTH = 2; + HCOLOR = [1 1 1]- get(gcf, 'color'); + z_level = -min(abs(sensloc(:,3))); + hold on + hn=plot3([base;tip;base],[.18*rmax;0;-.18*rmax],[base;tip;base].*0+z_level); % plot nose + LE = [ + 0.0216 0.1455 + 0.0368 0.1523 + 0.0368 0.1565 + 0.0334 0.1622 + 0.0271 0.1633 + 0.0123 0.1565 + 0.0040 0.1535 + -0.0063 0.1548 + -0.0164 0.1582 + -0.0249 0.1607 + -0.0294 0.1575 + -0.0308 0.1514 + -0.0247 0.1441 + -0.0139 0.1422 + -0.0029 0.1422 + ]./.15; + LE(end+1,:)=LE(1,:); + LE = LE*rmax; + hn(2) = plot3(LE(:,1), LE(:,2), LE(:,1).*0+z_level); + hn(3) = plot3(LE(:,1), -LE(:,2), LE(:,1).*0+z_level); + set(hn, 'Color',HCOLOR,'LineWidth',HLINEWIDTH) +end + + +%% Contours +if length(Contours)>0 + GRID_SCALE = 100; % 67 in original + xi = linspace(xmin,xmax,GRID_SCALE); % x-axis description (row vector) + yi = linspace(xmin,ymax,GRID_SCALE); % y-axis description (row vector) + INTERPOLATION = 'v4'; + [Xi,Yi,Zi] = griddata(Y,X,data,yi',xi,INTERPOLATION); % Interpolate data + % remove points which fall out of the head plot + for i=1:length(Zi) + if rmax2<(Xi(i)^2+Yi(i)^2) + Zi(i)=NaN; + i + end + end + + if length(Contours)>1 || isequal(Contours,0) + CONTOURLEVELS = Contours; + CONTOURNUM = length(CONTOURLEVELS); + else + CONTOURNUM = Contours; + CONTOURLEVELS=max(abs(data))/(CONTOURNUM/2+1); + if mod(CONTOURNUM,2) + CONTOURLEVELS=CONTOURLEVELS.*[ceil(-CONTOURNUM/2):floor(CONTOURNUM/2)]; + else + CONTOURLEVELS=CONTOURLEVELS.*[setdiff((-CONTOURNUM/2):(CONTOURNUM/2),0)]; + end + end + [c,hc]=contour(Xi,Yi,Zi,CONTOURLEVELS,'w'); + set(hc, 'tag', mfilename, 'color', get(gcf, 'color')) + colorbar + hold off +end + +%% Colors +colorbar + +view(-90,90); +hold off +axis tight +axis off +% Believe it or not the scribe code for colorbar is buggy when used with +% contour plots in the picture... See line 228, in scribe.colorbar +caxis(max(abs(data))*[-1 1]) +ha=colorbar; +% KND 2009-11-12 changed child=get(ha,'children'); +child=findobj(get(ha,'children'), 'Type', 'image'); +set(ha, 'YLim', caxis); +set(child, 'ydata', caxis); +axes(ha) +if DrawLines & CONTOURNUM>0 + hl=line((get(ha,'Xlim'))'*ones(1,CONTOURNUM),ones(2,1)*get(hc, 'LevelList')); + set(hl,'LineStyle', '-') + set(hl,'Color', get(hc(1),'color')) +end +axes(get(hp, 'Parent')) +hold off + +return + + +%% + +isens=isens(:); +if nargin==2 + data=isens; + isens=1:size(data,1); +end +if size(data,1)~=length(isens) %& all(ismember(isens, 1:size(data,1))) + data=data(isens); +end +if isfield(Channel, 'Loc') + for i=1:length(isens) + sensloc(i,1:3)=Channel(isens(i)).Loc(:,1)'; + end + Channel=Channel(isens); +else + sensloc=Channel(isens,:); + Channel=[]; +end + +center=[0 0 0]; + + +nans=find(isnan(data)); +sensloc(nans,:)=[]; +data(nans)=[]; +nmes = size(sensloc,1); +% CTF xyz system is not classical +sensloc=sensloc(:,[2 1 3]); +[teta,phi,R] = cart2sph(sensloc(:,1)-center(1),sensloc(:,2)-center(2),sensloc(:,3)-center(3)); +R = mean(R); +phimin = min(phi); +phimax = max(phi); +tetamin = min(teta); +tetamax = max(teta); +[x y z] = sph2cart(teta,phi,R*ones(size(phi))); +[xt yt zt] = sph2cart(teta,phi,R*1.0*ones(size(phi))); +N = 25; +phi = (phimin:(pi/2 - phimin)/N:pi/2)'*ones(1,N+1); +teta= (0: 2*pi/N : 2*pi )'*ones(1,N+1); +xs = cos(teta').*cos(phi); +ys = sin(teta').*cos(phi); +zs = sin(phi); +xs=xs(:)*R; +ys=ys(:)*R; +zs=zs(:)*R; +[TH,PHI,R] = cart2sph(xs,ys,zs-max(zs)); +R2 = R./cos(PHI).^.2; +[Y,X] = pol2cart(TH,R2); + +tri = delaunay(Y,X); +cdata = griddata(xt,yt,data,X,Y,'invdist'); +h=patch('faces',tri,'vertices',[Y,X,0.*X],'CData',cdata,'edgecolor','none','FaceColor','interp'); + +return + +if OPTIONS.ShowContours % Add contour plot + n = sqrt(size(PlotHandles.TopoPlot(mod).Yo{iSet},1)); + PlotHandles.TopoPlot(mod).Yo{iSet} = reshape(PlotHandles.TopoPlot(mod).Yo{iSet},n,n); + PlotHandles.TopoPlot(mod).Xo{iSet} = reshape(PlotHandles.TopoPlot(mod).Xo{iSet},n,n); + [PlotHandles.TopoPlot(mod).Contour{iSet}.C,PlotHandles.TopoPlot(mod).Contour{iSet}.H] = contour(PlotHandles.TopoPlot(mod).Yo{iSet},... + PlotHandles.TopoPlot(mod).Xo{iSet},... + CData,'w-'); +end + + +return + +if datatype == 1 + CData = DisplayStruct.TopoPlot(k).Wmat{iSet} * Disp.TimeSeries{iSet}(data.Measures.Display.SelectedChannels{k},tindx); + CData = reshape(CData,sqrt(length(CData)),sqrt(length(CData))); + CData = CData * max(abs(Disp.TimeSeries{iSet}(data.Measures.Display.SelectedChannels{k},tindx)))/max(abs(CData(:))); % properly rescale to data amplitude +elseif datatype == 2 + F = data.Results.IndepTopo(:,iSet)*data.Results.TimeSeries(:,iSet)'; + CData = DisplayStruct.TopoPlot(k).Wmat{iSet} * F(:,tindx); + CData = reshape(CData,sqrt(length(CData)),sqrt(length(CData))); + CData = CData * max(abs(F(:,tindx)))/max(abs(CData(:))); % properly rescale to data amplitude +end + +set(DisplayStruct.TopoPlot(k).surf{iSet},'CData',CData) + +if data.Measures.Display.Flags.ShowContours %& ishandle(DisplayStruct.TopoPlot(k).Contour{iSet}.H) % Add contour plot + + axes(DisplayStruct.TopoPlot(k).axes{iSet}); + %hc=findobj(gcf,'type','hggroup');%DisplayStruct.TopoPlot(k).Contour{iSet}.H;%;(ishandle(DisplayStruct.TopoPlot(k).Contour{iSet}.H)); % Contour handle + try + delete(DisplayStruct.TopoPlot(k).Contour{iSet}.H); + waitfor(DisplayStruct.TopoPlot(k).Contour{iSet}.H); % Make sure the (deletion) work is done catch + [DisplayStruct.TopoPlot(k).Contour{iSet}.C,DisplayStruct.TopoPlot(k).Contour{iSet}.H] = contour(DisplayStruct.TopoPlot(k).Yo{iSet},DisplayStruct.TopoPlot(k).Xo{iSet},CData,'w-'); + catch % an error can occur when user keeps pressing the time slider; contour cannot follow at the required pace and finally that produces an error + % doing nothing while user is + % holding the mouse button is just + % ensuring that contours will be + % updated only when button is + % released and no error is shown in + % command window. + bst_message_window('wrap','Contour map cannot be refreshed at that pace; please release the mouse button and do several mouse clicks instead') + end + + drawnow + +end \ No newline at end of file diff --git a/brainstorm/cortex_menu.m b/brainstorm/cortex_menu.m new file mode 100644 index 0000000..20baf64 --- /dev/null +++ b/brainstorm/cortex_menu.m @@ -0,0 +1,473 @@ +function [varargout]= cortex_menu(action, varargin) +% cortex_menu - Menu related to cortical surface processing +% +% cortex_menu('action') with following possible actions: +% create +% vertconn_state(ho,hctx) +% compute_vertconn(hctx) +% smooth_surface(hctx,a, nIterations) +% trimsurface +% curvature +% extent_threshold(hctx,z) +% move_hemi_away(hctx) +% move_hemi_closer(hctx) +% open_hemi(hctx) +% move_hemi_closer(hctx) +% hide_hemi(hctx) + +if nargin==0 + action='create'; +end +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + +return + +function [hmenu]=action_create +delete(findobj(gcf, 'Tag', mfilename)) +hmenu = uimenu('Label','Surface processing','Tag',mfilename); +cback='o=findTessellationHandles; uhp=get(o, ''UserData''); if isempty(uhp); uhp.vertices=get(o, ''Vertices''); uhp.faces=get(o, ''Faces''); uhp.h=o; end;'; + +set(hmenu, 'Callback',[ ... + 'cortex_menu(''vertconn_state'', gcbf);'... + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Vertex Connectivity',... + 'CallBack',[ ... + sprintf('%s(''%s'',gcbo);',mfilename,'compute_vertconn') + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Smooth surface',... + 'CallBack',[ sprintf('%s(''%s'',gcbo);',mfilename,'smooth_surface') ]); + +t = uimenu('Parent',hmenu,... + 'Label','Adv. Smooth surface',... + 'CallBack',[ cback ... + 'vals=inputdlg({''Smoothing factor'',''Iterations''}, ''Smooting parameters'', 1 , {''.3'', ''20''});'... + sprintf('%s(''%s'',gcbo,str2num(vals{1}),str2num(vals{2}));',mfilename,'smooth_surface')... + 'clear uhp p vals;'... + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Move hemispheres apart','Enable', 'on',... + 'CallBack',[ ... + sprintf('%s(''%s'',gcbo);',mfilename,'move_hemi_away') + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Put closer hemispheres','Enable', 'on',... + 'CallBack',[ ... + sprintf('%s(''%s'',gcbo);',mfilename,'move_hemi_closer') + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Open hemispheres','Enable', 'on',... + 'CallBack',[ ... + sprintf('%s(''%s'',gcbo);',mfilename,'open_hemi') + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Back to original surface',... + 'CallBack',[ cback ... + sprintf('%s(''%s'',gcbo);',mfilename,'revert_surface') + ]); + +t = uimenu('Parent',hmenu,... + 'Label','Add surface curvature',... + 'CallBack',[ ... + 'cs=curvature_cortex(uhp,uhp.vertconn,.1,0);'... %'cs=blend_anatomy_data(cs, uhp.data);'... + 'set(uhp.h, ''FaceVertexCData'', cs);'... + 'clear cs uhp;'... + ],'Enable', 'off'); + + +t = uimenu('Parent',hmenu,... + 'Label','Trim surface',... + 'Separator', 'on', ... + 'CallBack',[ cback ... + 'trimsurface_gui(uhp.h);'... + 'clear vuhp;'... + ],'Enable', 'on'); + + + +t = uimenu('Parent',hmenu,... + 'Label','Hide/show hemispheres',... + 'Separator', 'on', ... + 'CallBack',[ ... + sprintf('%s(''%s'',gcbo);',mfilename,'hide_hemi') + ],'Enable', 'on'); + + +t = uimenu('Parent',hmenu,... + 'Label','Remove small clusters',... + 'Separator', 'on', ... + 'CallBack',[ sprintf('%s(''%s'',gcbo);',mfilename,'extent_threshold') ],'Enable', 'on'); + + + +return + +function []=action_revert_surface(ho,hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +set(uhp.h, 'Vertices', uhp.vertices); + +function []=action_vertconn_state(ho,hctx) +if ~exist('tess_vertices_connectivity') + try + figure + addpath('~/mtoolbox/brainstorm3/toolbox/misc/') + addpath('/mtoolbox/brainstorm3/toolbox/misc/') + end + if ~exist('tess_vertices_connectivity') + errordlg({... + 'You need to add the path of the BrainStorm Toolbox' ... + 'E.g.:' ... + ' >> addpath(''C:/BrainStorm/Toolbox'')'}, 'No BrainStorm found') + return + end +end +set(findobj(gcbo, 'Label', 'Vertex Connectivity'), 'Checked', 'off'); +set(findobj(gcbo, 'Label', 'Vertex Connectivity'), 'Enable', 'off'); +set(findobj(gcbo, 'Label', 'Smooth surface'), 'Enable','off'); +set(findobj(gcbo, 'Label', 'Adv. Smooth surface'), 'Enable', 'off'); +if nargin<2 + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +set(findobj(gcbo, 'Label', 'Vertex Connectivity'), 'Enable', 'on'); +if isfield(uhp, 'vertconn'), + state='on'; +else + state='off'; +end; +set(findobj(gcbo, 'Label', 'Vertex Connectivity'), 'Checked', state); +set(findobj(gcbo, 'Label', 'Smooth surface'), 'Enable',state); +set(findobj(gcbo, 'Label', 'Adv. Smooth surface'), 'Enable', state); +clear uhp; + + +function []=action_compute_vertconn(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +uhp.vertconn=tess_vertices_connectivity(uhp); +set(uhp.h, 'UserData', uhp); +h=uhp.h +clear uhp; +action_vertconn_state(get(h, 'parent'), h); + + + +function action_smooth_surface(hctx,a, nIterations) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +if nargin<3 + nIterations=10; +end +if nargin<2 + a = .3; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +p=handle2struct(uhp.h); +p=lowerfields(p.properties); +if ~isfield(uhp,'vertconn') + action_compute_vertconn(hctx) + uhp=get(hctx, 'UserData'); +end +[v]=tess_smooth(p.vertices',a, nIterations,uhp.vertconn); +set(uhp.h, 'Vertices', v'); + + +function [curvature,curvature_sigmoid]=compute_curvature(hctx,VertConn,sigmoid_const) +if nargin<3 + sigmoid_const=0.1; +end +FV=get(hctx); +normals=get(hctx,'VertexNormals'); +nVertices=size(normals,1); +%Make the normals unit norm +[nrm,normalsnrm]=colnorm(normals'); +%compute average angle on each vertex +curvature=zeros(nVertices,1); +curvature_sigmoid=zeros(nVertices,1); +for i=1:nVertices %for all vertices + nNeighbours=length(VertConn{i}); %number of neighbours + edgevector=FV.Vertices(VertConn{i},:)-repmat(FV.Vertices(i,:),nNeighbours,1); %vectors joining vertex with neighbours + [nrm,edgevector]=colnorm(edgevector'); + curvature(i)=mean(acos(normalsnrm(:,i)'*edgevector))-pi/2; + curvature_sigmoid(i)= 1./(1+exp(-curvature(i).*sigmoid_const))-0.5; +end + + + +function []=spatialextent(ho,hctx) +uhp=get(findTessellationHandles, 'UserData'); +if isempty(uhp); return; end; + + +function action_trimsurface +uhp=get(findTessellationHandles, 'UserData'); +trimsurface_gui(uhp.h) + +function action_curvature + + +function []=action_extent_threshold(hctx,z) +if nargin==0 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +c=colormap; +fv=get(uhp.h, 'FaceVertexCData'); +if prod(caxis)>=0 + fv(abs(fv)<=min(caxis))=0; +else + cb=c(ceil(length(c)/2),:); + cb=repmat(cb,length(c),1); + fv(abs(fv)=z); +fv(setdiff(1:length(fv),[clu{:}]))=0; +set(uhp.h, 'FaceVertexCData',fv) + +function []=action_move_hemi_away(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); + uhp.h = hctx; + %return; +end; +v=get(uhp.h, 'Vertices'); +if size(v,1)==10774 || size(v,1)==12045 + fprintf('MNI4Yann cortex'); + v(1:5418,1)=v(1:5418,1)+1/2*mean(v(1:5418,1)); + v(5419:10774,1)=v(5419:10774,1)+1/2*mean(v(5419:10774,1)); + if size(v,1)==12045 + v(10774:end,3)=v(10774:end,3)-1/2*mean(v(10774:end,3)); + end +elseif size(v,1)==15028 + nR = 7509;% first right + fprintf('Brainstorm Default Subject\n'); + v(1:nR,2)=v(1:nR,2)+1/2*mean(v(1:nR,2)); + v(nR+1:end,2)=v(nR+1:end,2)+1/2*mean(v(nR+1:end,2)); + % Open with a given angle + % a= -75/360*2*pi; % in deg/rad + % t = exp(j*a)*(v(1:nR,2)+j*(v(1:nR,1)+.07)); + % v(1:nR,2) = real(t); + % v(1:nR,1) = imag(t)-.07; + % % +else + f=get(uhp.h, 'Faces'); + %try to guess which is the orthosagittal axis + m=median(v); + % it should be the one where as few faces as possible cross the + % median plane + for i=1:3 + left = v(:,i)m(i); + s(i) = sum(any(right(f),2) & any(left(f),2)); + end + [min_s,lr_dim] = min(s); + % Now we have it, we must found the position of the sagittal plane + fun = @(m) sum(any(reshape(v(f,lr_dim),size(f,1),3)>m,2)&any(reshape(v(f,lr_dim),size(f,1),3)m; + v(:,lr_dim)=v(:,lr_dim)+(max(v(:,lr_dim))-min(v(:,lr_dim)))/4*right; +end +set(uhp.h, 'Vertices', v); +axis image + +function []=action_move_hemi_closer(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +v=get(uhp.h, 'Vertices'); +if size(v,1)==10774 || size(v,1)==12045 + v(1:5418,1)=v(1:5418,1)-1/2*mean(v(1:5418,1)); + v(5419:10774,1)=v(5419:10774,1)-1/2*mean(v(5419:10774,1)); + if size(v,1)==12045 + v(10774:end,3)=v(10774:end,3)+1/2*mean(v(10774:end,3)); + end +elseif size(v,1)==15028 + nR = 7509; + fprintf('Brainstorm Default Subject'); + v(1:nR,2)=v(1:nR,2)-1/2*mean(v(1:nR,2)); + v(nR+1:end,2)=v(nR+1:end,2)-1/2*mean(v(nR+1:end,2)); + +else + v(:,1)=v(:,1)+10*(-1+2*(v(:,1)>0)); +end +set(uhp.h, 'Vertices', v); +axis image + +function []=action_open_hemi(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); + uhp.h = hctx; + %return; +end; +v=get(uhp.h, 'Vertices'); +if size(v,1)==10774 || size(v,1)==12045 + fprintf('MNI4Yann cortex'); + v(1:5418,1)=v(1:5418,1)+1/2*mean(v(1:5418,1)); + v(5419:10774,1)=v(5419:10774,1)+1/2*mean(v(5419:10774,1)); + if size(v,1)==12045 + v(10774:end,3)=v(10774:end,3)-1/2*mean(v(10774:end,3)); + end +elseif size(v,1)==15028 + nR = 7509;% first right + fprintf('Brainstorm Default Subject\n'); + % v(1:nR,2)=v(1:nR,2)+1/2*mean(v(1:nR,2)); + %v(nR+1:end,2)=v(nR+1:end,2)+1/2*mean(v(nR+1:end,2)); + % Open with a given angle + a= -60/360*2*pi; % in deg/rad + t = exp(j*a)*(v(1:nR,2)+j*(v(1:nR,1)+.07)); + v(1:nR,2) = real(t); + v(1:nR,1) = imag(t)-.07; + % +else + f=get(uhp.h, 'Faces'); + %try to guess which is the orthosagittal axis + m=median(v); + % it should be the one where as few faces as possible cross the + % median plane + for i=1:3 + left = v(:,i)m(i); + s(i) = sum(any(right(f),2) & any(left(f),2)); + end + [min_s,lr_dim] = min(s); + % Now we have it, we must found the position of the sagittal plane + fun = @(m) sum(any(reshape(v(f,lr_dim),size(f,1),3)>m,2)&any(reshape(v(f,lr_dim),size(f,1),3)m; + v(:,lr_dim)=v(:,lr_dim)+(max(v(:,lr_dim))-min(v(:,lr_dim)))/4*right; +end +set(uhp.h, 'Vertices', v); +axis image + + + +function []=action_move_hemi_closer(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); return; end; +v=get(uhp.h, 'Vertices'); +if size(v,1)==10774 || size(v,1)==12045 + v(1:5418,1)=v(1:5418,1)-1/2*mean(v(1:5418,1)); + v(5419:10774,1)=v(5419:10774,1)-1/2*mean(v(5419:10774,1)); + if size(v,1)==12045 + v(10774:end,3)=v(10774:end,3)+1/2*mean(v(10774:end,3)); + end +elseif size(v,1)==15028 + nR = 7509; + fprintf('Brainstorm Default Subject'); + v(1:nR,2)=v(1:nR,2)-1/2*mean(v(1:nR,2)); + v(nR+1:end,2)=v(nR+1:end,2)-1/2*mean(v(nR+1:end,2)); + +else + v(:,1)=v(:,1)+10*(-1+2*(v(:,1)>0)); +end +set(uhp.h, 'Vertices', v); +axis image + +function []=action_hide_hemi(hctx) +if nargin<1 || ~isequal(get(hctx, 'type'), 'patch') + hctx=findTessellationHandles; +end +uhp=get(hctx, 'UserData'); +if isempty(uhp); + uhp.h = hctx; + %return; +end; +v=get(uhp.h, 'Vertices'); +if size(v,1)==10774 || size(v,1)==12045 + fprintf('MNI4Yann cortex'); + LR = [ones(1,5418) 2*ones(1,5356) ]; + if size(v,1)==12045 + % cerebellum + LR = [LR zeros(1,1272)]; + end +elseif size(v,1)==15028 + LR = [ones(1,7509) 2*ones(1,7519) ]; +else + f=get(uhp.h, 'Faces'); + %try to guess which is the orthosagittal axis + m=median(v); + % it should be the one where as few faces as possible cross the + % median plane + for i=1:3 + left = v(:,i)m(i); + s(i) = sum(any(right(f),2) & any(left(f),2)); + end + [min_s,lr_dim] = min(s); + % Now we have it, we must found the position of the sagittal plane + fun = @(m) sum(any(reshape(v(f,lr_dim),size(f,1),3)>m,2)&any(reshape(v(f,lr_dim),size(f,1),3)m; + v(:,lr_dim)=v(:,lr_dim)+(max(v(:,lr_dim))-min(v(:,lr_dim)))/4*right; +end +alpha = get(uhp.h,'FaceVertexAlphaData'); +if alpha(find(LR==1,1)) == 0 + alpha(LR==1) = 1; + alpha(LR==2) = 0; +elseif alpha(find(LR==2,1)) == 0 + alpha(LR==1) = 1; + alpha(LR==2) = 1; +else + alpha(LR==1) = 0; + alpha(LR==2) = 1; +end +if all(alpha==1) + set(uhp.h,'alphadatamapping','none',... + 'FaceVertexAlphaData',alpha,.... + 'FaceAlpha','flat',... + 'backfacelighting','unlit') +else + set(uhp.h,'alphadatamapping','scaled',... + 'FaceVertexAlphaData',alpha,.... + 'FaceAlpha','interp',... + 'backfacelighting','lit') +end +%set(uhp.h, 'VerticesAlphaDapa', v); + + diff --git a/brainstorm/ctf_readClassFile.m b/brainstorm/ctf_readClassFile.m new file mode 100644 index 0000000..e69de29 diff --git a/brainstorm/ds2brainstorm.m b/brainstorm/ds2brainstorm.m new file mode 100644 index 0000000..05a01b9 --- /dev/null +++ b/brainstorm/ds2brainstorm.m @@ -0,0 +1,1258 @@ +function [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time,RunTitle] = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS, TIME, NO_TRIALS, DCOffset); +%DS2BRAINSTORM Convert a DS CTF dataset into BrainStorm format +% function [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time,RunTitle] = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS, DCOffset); +% [F,Channel,imegsens,ieegsens,iothersens,irefsens,grad_order_no,no_trials,filter,Time, RunTitle] +% ... = ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS, DCOffset); +% Reads CTF Systems Inc. Data and Resource file formats (4.1 MEG Data Format) +% +% INPUTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% DS_DIRECTORY: full path to the .ds directory containing the orginal data set +% +% VERBOSE = 1 : Toggle VERBOSE mode ON +% -> Activate screen display +% -> Save channel information in channel_file.txt +% -> Save coefficient information in coef_file.txt +% +% VERBOSE = 0 : Toggle VERBOSE mode OFF +% +%---> The rest of the input parameters are optionnal (more specific to data block extraction) +% +% READRES = 0: Do not read the original .res4 file assuming it has been read previously. +% Read _res4.mat instead. If _res4.mat does not exist, automatic switch to READRES = 1. +% READRES = 1: Read the original .res4 file and writes out a file called **_res4.mat in the .ds folder, +% which is a shortened version of the CTF resources file .res4. +% MEG/EEG data are also read from the .meg4 file ONLY IF other input arguments are specified +% READRES = 2: Same as READRES = 1, without the long reading of coefficient information +% but reads ONLY a short version of data information and returns them in F as a structure. +% MEG/EEG data are nor read from the .meg4 file. +% This is useful for display in importdata_gui for instance. +% READRES = 3: Do not read .meg4 file (useful when data need to be kept in native file format when importing into BrainStorm) +% F is then a string indicating the name of the corresponding .ds folder. +% +% +% Set READRES to 0 when you want to extract another block of data after you have already read one block with READRES = 1. +% +% If READRES is left blank, the whole data are read - ATTENTION when data set is large - possible 'out of memory' issues +% +% If the optional fields below are left blank, ds2brainstorm only reads the res4 file and generates a *_res4.mat file in the current .ds folder +% with all useful information regarding EEG, MEG channels etc. for subsequent data extraction. +% +% CHANNELS: the indices of the channels to be extracted as in IEEGSENS, IMEGSENS or IREFSENS +% If you don't know what are the indices of these channels, run ds2brainstorm with READRES = 1 first. +% +% TIME: the time window to be extracted in seconds within a trial; ie a subset of Time, a vector saved in **_res4.mat (see above) +% +% NO_TRIALS: a vector containing the number(s) of the trial(s) to be extracted. +% +% DCOffset: A flag indicating whether DC offset needs to be removed from every MEG channel. +% Acceptable values: +% 0 - DC offset is not removed from MEG channels (DEFAULT) +% 1 - DC offset is removed from MEG channels based on the entire trial length +% 2 - DC offset is removed from MEG channels based on pretigger time period +% +% Example; ds2brainstorm('tipouic.ds',1,0,[10:30],[-.5 3],2) +% .. extracts in VERBOSE mode from tipouic.ds, assuming tipouic_res4.mat was already created during a previous call to ds2brainstorm with READRES = 1 +% channels 10 to 30 (could be MEG or other -> check IEEGSENS and IMEGSENS first), between -0.5sec and 3sec, in trial 2. +% +% % +% OUTPUTS %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% +% CHANNEL - MEG,EEG, REFERENCE and OTHER channel information +% CHANNEL is a cell array of structures following the BrainStorm data format. +% F - Data Matrix: One sensor per row; one time sample per column / alternatively a structure containing all data information +% (resources contained in .res4 file). +% IMEGSENS - Indices of the MEG data rows in F +% IEEGSENS - Indices of the EEG data rows in F +% IOTHERSENS - Indices of the OTHER data rows (not including reference coils) in F +% IREFSENS - Indices of the REFERENCE data rows in F +% GRAD_ORDER_NO - Order of the gradient correction to be taken into account in the forward model only +% NO_TRIALS - Number of trials in the .ds folder. +% FILTER - An array of structures; each structure containing information related to each filter +% TIME - A vector containing the time instants at every data sample +% RUNTITLE - A character array labelling the current run. +% +% Please refer to CTF Systems Inc. Technical Note #1 for details on DataSet file formats + +% ---------------------- 15-Dec-2003 16:09:01 ----------------------- +% --------- Automatically Generated Comments Block Using AUTO_COMMENTS --------- +% +% CATEGORY: Data Processing +% +% Alphabetical list of external functions (non-Matlab): +% toolbox\bst_message_window.m +% toolbox\findclosest.m +% toolbox\good_channel.m +% +% Subfunctions in this file, in order of occurrence in file: +% PrintCoilPos(channel_file, CoilRec_ext,nCoils) ; +% save_sensor_locs(Channel,SensorLocFile) +% +% At Check-in: $Author: Mosher $ $Revision: 23 $ $Date: 12/15/03 2:48p $ +% +% Overall BrainStorm authors are: +% ** Dr. John C. Mosher, Los Alamos National Laboratory +% ** Dr. Sylvain Baillet, CNRS Cognitive Neuroscience & Brain Imaging Laboratory +% +% Copyright (c) 2003 BrainStorm MMIII by the University of Southern California +% Principal Investigator: +% ** Professor Richard M. Leahy, USC Signal & Image Processing Institute +% +% Source code may not be distributed in original or altered form. +% For license and copyright notices, type 'bst_splashscreen' in Matlab, +% or see BrainStorm website at http://neuroimage.usc.edu, +% or email Professor Richard M. Leahy at leahy@sipi.usc.edu +% for further information and permissions. +% ------------------------ 15-Dec-2003 16:09:01 ----------------------- + + +% /---Script Authors-------------------------------------\ +% | | +% | *** Sylvain Baillet, Ph.D. | +% | Cognitive Neuroscience & Brain Imaging Laboratory | +% | CNRS UPR640 - LENA | +% | Hopital de la Salpetriere, Paris, France | +% | sylvain.baillet@chups.jussieu.fr | +% | | +% | *** John C. Mosher, Ph.D. | +% | Design Technology Group | +% | Los Alamos National Laboratory | +% | Los Alamos, New Mexico, USA | +% | mosher@lanl.gov | +% | | +% | -> with contributions from | +% | Line Garnero, Ph.D. and Antoine Ducorps, Ph.D. | +% | MEG Center & | +% | Cognitive Neuroscience | +% | & Brain Imaging Laboratory - CNRS | +% | La Salpetriere Hospital, Paris - France | +% \------------------------------------------------------/ + +% Script History ---------------------------------------------------------------------------------------- +% +% 11/28/00 - SB : Updated to read the 3rd-order gradient information +% 03/09/01 - SB : Data block extraction +% 15/11/01 - SB : Extraction of the ADC Input channels in iothersens, combined with the STIM channel +% 19/11/01 - SB : Save iothersens indices in the _res4.mat file +% JCM 06-Jun-2002 : made waitbar update less often, autocomments +% SB 26-Jul-2002 : Added the READRES = 2 condition to read basic file information for display importdata_gui. +% .............. Removed creation of channel_file.txt. +% SB 27-Jul-2002 : Minor alterations in the READRES conditions - see help header. +% SB 28-Jul-2002 : When CHANNELS is emptu, all channels, including reference channels are read. +% .............. Changed name of sensor location result file (for visualization in MRITool or 3DViewer) +% SB 10-Sep-2002 : Minor layout editing. +% SB 07-Nov-2002 : Display all progress information into bst_message_window +% SB 15-Nov-2002 : EEG channel .loc field is now only 3x1 (was 3x2, second column filled with zeros). +% Added DCOffset input argurment to remove DC Offset from MEG channels. +% SB 20-Nov-2002 : Assign "MEG REF" type to MEG reference channels for fast retrieval with GOOD_CHANNEL +% Removed .Gcoef and .i*sens fields form Channel structure. +% SB 23-Dec-2002 : Time now returns only the time window on which data has been extracted (not the whole original time span of data) +% SB 21-Jan-2003 : Fixed 1-sample bug for total Time length +% SB 23-Jan-2003 : Added READRES = 3 option. +% SB 06-Feb-2003 : Fixed bug when accessing data with multiple trials specificied in NO_TRIALS +% From the second NO_TRIALS entry on, data was always read from beguinning of trial +% not from the first entry specified in TIME. +% JCM 10-Dec-2003 : Added additional blank SensorNames to account for type "17" in the 275 channel arrays. Moved around +% redundant definitions of SensorNames. Thanks to Fred Carver NIMH for finding this. +% JCM 11-Dec-2003 : Updating SensorNames based on email from CTF, +% plus correcting 0 indexing scheme +% KND 01-Jun-2004 : Added a quick & dirty test for virtual MEG channels +% KND 02-Jun-2004 : Modified Check input arguments, so that 4 arguments is ok [173-183] +% Bug: TIME was defined as a 1xN array (=Time) instead of a [BeginLatency EndLatency] +% -------------------------------------------------------------------------------------------------------- + +% Check input arguments + +if nargin == 2 + READRES = 1; + DCOffset = 0; +elseif nargin==5 % No Marker file and marker range are defined + MARKER_FILE = 0; + MARKER_RANGE = []; + DCOffset = 0; +% KND: +elseif nargin==4 + % if READRES ~= 1 | READRES ~= 2 + % READRES = 2; % Read data information only. + % end + MARKER_FILE = 0; + MARKER_RANGE = []; + TIME = []; + NO_TRIALS = []; + DCOffset = 0; +% -- KND +elseif nargin==3 + % Read only file information. + % Check that READRES has acceptable values - if not, the whole file could be read + % which could end-up in loading very large files into Matlab format + % and cause memory crash. + if READRES ~= 1 | READRES ~= 2 + READRES = 2; % Read data information only. + end + MARKER_FILE = 0; + MARKER_RANGE = []; + CHANNELS = []; + TIME = []; + NO_TRIALS = []; + DCOffset = 0; +end + + +% SensorNames ={'Ref Magnetometer','Ref Gradiometer' ,'' , '' , '' ,'MEG Sensor','' , '', '','EEG Sensor','ADC Input','Stimulation input',''}; % CHEAT - added the 13th '' ofor testing purposes +% 10 December 2003 Fred Carver at NIMH found that 275 channel arrays had a type 17. Added extra blanks to account for. +% 11 December 2003, based on email directly from Dough McKenzie at CTF: +% Comments on types, email of 10 December 2003: +%The new types are +% +% SAM Sensor -- Synthetic electrode channel from SAM +% Virtual Channel -- Linear combination of sensor channels +% System Clock -- 32 bit counter incremented at 12,000 +% ticks per second for Omega 2000 system +% ( new systems like NIMH ) +% and incremented at 12,500 ticks per +% second for older systems. +% +% Video Time -- A 32 bit encoded value that can be recorded from +% a SONY Video time output from a video player or +% recorder +% +% The format is 'hhmmssff' where each byte contains +% hh hours in decimal ( 0-- +% mm minutes ( 0 ~ 59 ) +% ss seconds ( 0 ~ 59 ) +% ff frames ( 0 ~ 29 ) +% +% ADC Input Voltage -- Used if the ADC channels are measuring +% voltage. == 11 if measuring current +% +%NOTE: There will be some additional channels types defined +% mid next year. +SensorNames ={... + 'Ref Magnetometer',... % Sensor Type Index of 0 + 'Ref Gradiometer' ,... % Index of 1 + '' ,... % 2 + '' ,... % 3 + '' ,... % 4 + 'MEG Sensor',... % 5 + '' ,... % 6 + '',... % 7 + '',... % 8 + 'EEG Sensor',... % 9 + 'ADC Input Current',...% 10 ADC Input Current (Amps) + 'Stimulation input',...% 11 + 'Video Time',... % 12 + '',... % 13 + '',... % 14 + 'SAM Sensor',... % 15 + 'Virtual Channel',... % 16 + 'System Clock',... % 17 System Time Ref + 'ADC Input Voltage',...% 18 ADC Input Voltage (Volts) + }; + + +%% Checking files +cd(ds_directory) +[path,rootname] = fileparts(ds_directory); +meg4file = [rootname,'.meg4']; +rec4file = [rootname,'.res4']; +if isdir('BrainStorm') % Was a BrainStorm directory created in .ds folder ? Yes if ds2brainstorm called from importdata + res4_mat = fullfile('BrainStorm',[rootname,'_res4.mat']); +else + res4_mat = [rootname,'_res4.mat']; +end + +if ~exist(rec4file,'file') | ~exist(meg4file,'file') + errordlg([rec4file ' or ' meg4file ' missing']) + return +end + +% If .mat version of the .res4 does not exist while we supposed it did - read it. +if ~exist(res4_mat,'file') & READRES == 0 + % Force reading of original .res4 + READRES = 1; +end + +if VERBOSE + bst_message_window(['Working in...',ds_directory ]) +end + + +%********************************************* + +if READRES > 0 % Read the .res4 file + + %% Define constants + MAX_COILS = 8; + MAX_BALANCING = 50; + SENSOR_LABEL = 31; + MAX_AVERAGE_BINS = 8; + + %***** nfSetUp **** Data Structure + gSetUp = struct('no_samples',[],'no_channels',[],'sample_rate',[],... + 'epoch_time',[],'no_trials',[],'preTrigPts',[],'no_trials_done',[],'no_trials_display',[],... + 'save_trials',[],'primaryTrigger',[],'secondaryTrigger',[],'triggerPolarityMask',[],... + 'trigger_mode',[],'accept_reject_Flag',[],'run_time_display',[],'zero_Head_Flag',[],... + 'artifact_mode',[]); + + nfSetUp = struct('nf_run_name','','nf_run_title','','nf_instruments','','nf_collectdescriptor','',... + 'nf_subject_id','','nf_operator','','nf_sensorFileName',''); + + GenRes4 = struct('appName','','dataOrigin','','dataDescription','',... + 'no_trials_avgd',[],'data_time',[],'data_date',[],'gSetUp',gSetUp,'nfSetUp',nfSetUp,'rdlen',[]); + + %********************************************* + + + %% Reading Resources------------------------------------------------------------------------ + [rec,message] = fopen(rec4file,'rb','s'); % Big-endian byte ordering + if rec < 0 + errordlg(message) + return + end + + % Read HEADER + header = fread(rec,8,'char')'; + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> %s file format',char(header))... + }) + end + + + % Read nfSetUp + GenRes4.appName = char(fread(rec,256,'char')'); + GenRes4.dataOrigin = char(fread(rec,256,'char')'); + GenRes4.dataDescription = char(fread(rec,256,'char')'); + + GenRes4.no_trials_avgd = (fread(rec,1,'int16')'); + GenRes4.data_time = char(fread(rec,255,'char')'); + GenRes4.data_date = char(fread(rec,255,'char')'); + + gSetUp.no_samples = (fread(rec,1,'int32')'); + gSetUp.no_channels = (fread(rec,1,'int16')'); + + fseek(rec,ceil(ftell(rec)/8)*8,-1); + gSetUp.sample_rate = (fread(rec,1,'double')'); + fseek(rec,ceil(ftell(rec)/8)*8,-1); + gSetUp.epoch_time = (fread(rec,1,'double')'); + gSetUp.no_trials = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.preTrigPts = (fread(rec,1,'int32')'); + gSetUp.no_trials_done = (fread(rec,1,'int16')'); + gSetUp.no_trials_bst_message_windowlay = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.save_trials = (fread(rec,1,'int32')'); + gSetUp.primaryTrigger = char(fread(rec,1,'uchar')'); + gSetUp.secondaryTrigger = char(fread(rec,MAX_AVERAGE_BINS,'uchar')'); + gSetUp.triggerPolarityMask = char(fread(rec,1,'uchar')'); + + gSetUp.trigger_mode = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.accept_reject_Flag = (fread(rec,1,'int32')'); + gSetUp.run_time_bst_message_windowlay = (fread(rec,1,'int16')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.zero_Head_Flag = (fread(rec,1,'int32')'); + fseek(rec,ceil(ftell(rec)/4)*4,-1); + gSetUp.artifact_mode = (fread(rec,1,'int32')'); + gSetUp.padding = (fread(rec,1,'int32')'); + + + nfSetUp.nf_run_name = char(fread(rec,32,'char')'); + nfSetUp.nf_run_title = char(fread(rec,256,'char')'); + + RunTitle = nfSetUp.nf_run_title ; + + nfSetUp.nf_instruments = char(fread(rec,32,'char')'); + nfSetUp.nf_collect_descriptor = char(fread(rec,32,'char')'); + nfSetUp.nf_subject_id = char(fread(rec,32,'char')'); + nfSetUp.nf_operator = char(fread(rec,32,'char')'); + tmp = fread(rec,60,'char')'; + tmp(tmp<0) = 0; % prevent out of range character conversion warning + nfSetUp.nf_sensorFileName = tmp; clear tmp + + fseek(rec,ceil(ftell(rec)/4)*4,-1); + nfSetUp.rdlen = fread(rec,1,'int32')'; + + GenRes4.gSetUp = gSetUp; + GenRes4.nfSetUp = nfSetUp; + + + % Time span of data record + Time = linspace(-GenRes4.gSetUp.preTrigPts/GenRes4.gSetUp.sample_rate,... + GenRes4.gSetUp.epoch_time/GenRes4.gSetUp.no_trials-(GenRes4.gSetUp.preTrigPts+1)/GenRes4.gSetUp.sample_rate,... + GenRes4.gSetUp.no_samples); + % + %---------------------------------------------------------------------------------------- + + if VERBOSE + ON_OFF = {'Off','On'}; + bst_message_window({... + sprintf('ds2brainstorm -> Header information'),... + sprintf(' Collected %s starting at %s', GenRes4.data_date, GenRes4.data_time),... + sprintf(' Run Name: %s', nfSetUp.nf_run_name),... + sprintf(' Run Title: %s', nfSetUp.nf_run_title),... + sprintf(' Col Desc: %s', nfSetUp.nf_collect_descriptor),... + sprintf(' Run Desc: %s', GenRes4.dataDescription),... + sprintf(' Operator: %s', nfSetUp.nf_operator),... + sprintf(' Subject : %s', nfSetUp.nf_subject_id),... + sprintf(' Channels: %d',gSetUp.no_channels),... + sprintf(' Samples : %d per trial', gSetUp.no_samples),... + sprintf(' Rate : %g samples/sec', gSetUp.sample_rate),... + sprintf(' Trials : %d (average of %d)', gSetUp.no_trials, GenRes4.no_trials_avgd),... + sprintf(' Duration: %g seconds/trial', gSetUp.epoch_time/gSetUp.no_trials),... + sprintf(' Pre-trig: %g samples', gSetUp.preTrigPts),... + sprintf(' Sensor file name : %s', nfSetUp.nf_sensorFileName),... + sprintf(' Head zeroing: %s', ON_OFF{gSetUp.zero_Head_Flag+1}),... + sprintf('_________________')... + }) + end + + + %------------------------------------------------------------------------------- + + %----------------------------------READ FILTERS--------------------------------- + + fseek(rec,1844,-1); + + % Run Description + rundescript = char(fread(rec,nfSetUp.rdlen,'char')); + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Run Description: %s', rundescript )... + }) + end + + classType = {'CLASSERROR','BUTTERWORTH'}; + filtType = {'TYPERROR','LOWPASS','HIGHPASS','NOTCH'}; + + + % Number of filters + no_filters = fread(rec,1,'int16'); + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Filter information',... + sprintf('Number of filters: %d', no_filters)... + }) + end + + % JCM fixes 10/26/00, each of these should be looped through, not read in bulk + % old + if(0) + filter.freq = fread(rec,no_filters,'double'); + filter.fClass = classType{fread(rec,no_filters,'int32')+1}; + filter.fType = filtType{fread(rec,no_filters,'int32')+1}; + filter.numParam = fread(rec,no_filters,'int16'); + + filter.params = []; + for fi = 1:no_filters + for p = 1: filter(fi).numParam + filter(fi).params= fread(rec,filter(fi).numParam,'double'); + end + end + else % new + [filter(1:no_filters)] = struct('freq',[],'fClass',[],'fType',[],'numParam',[],'params',[]); + for fi = 1:no_filters, + filter(fi).freq = fread(rec,1,'double'); + filter(fi).fClass = classType{fread(rec,1,'int32')+1}; + filter(fi).fType = filtType{fread(rec,1,'int32')+1}; + filter(fi).numParam = fread(rec,1,'int16'); + filter(fi).params= fread(rec,filter(fi).numParam,'double'); + end + end + + if VERBOSE + for fi = 1:no_filters + bst_message_window({... + sprintf(' Filter - %d',fi),... + sprintf(' -> Frequency: %g Hz',filter(fi).freq),... + sprintf(' -> Class: %s',filter(fi).fClass),... + sprintf(' -> Type: %s',filter(fi).fType),... + sprintf(' -> Number of parameters: %d',filter(fi).numParam)... + }) + + if ~isempty(filter(fi).params) + bst_message_window({... + sprintf(' -> Parameter Value(s): %g',filter(fi).params)... + }) + end + end + + bst_message_window({... + sprintf('ds2brainstorm -> Reading Filter Information - DONE'),... + sprintf('ds2brainstorm -> Reading Channel Information. . .')... + }) + end + + % Channel Names + for chan = 1:gSetUp.no_channels + channel_name{chan} = fread(rec,32,'char')'; + tmp = channel_name{chan}; + tmp(tmp>127) = 0; + tmp(tmp<0) = 0; + channel_name{chan} = strtok(tmp,char(0)); + ChannelName{chan} = char(strtok(channel_name{chan},'-')); + end + + % Sensor Resources + CoilType = {'CIRCULAR','SQUARE','???'}; + + for chan = 1:gSetUp.no_channels + oldtell = ftell(rec); + SensorRes(chan).sensorTypeIndex = fread(rec,1,'int16'); + SensorRes(chan).originalRunNum = fread(rec,1,'int16'); + + id = fread(rec,1,'int32')+1; + + if isempty(id) + id = -1; + end + + if id > 3 | id <0 + id = 3; + end + + SensorRes(chan).coilShape = CoilType{id}; + + SensorRes(chan).properGain = fread(rec,1,'double'); + SensorRes(chan).qGain = fread(rec,1,'double'); + SensorRes(chan).ioGain= fread(rec,1,'double'); + SensorRes(chan).ioOffset = fread(rec,1,'double'); + SensorRes(chan).numCoils = fread(rec,1,'int16'); + SensorRes(chan).grad_order_no = fread(rec,1,'int16'); + + padding = fread(rec,1,'int32'); + + for coil = 1:MAX_COILS + SensorRes(chan).coilTbl(coil).position.x = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.y = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.z = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).position.junk = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.x = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.y = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.z = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).orient.junk = fread(rec,1,'double'); + SensorRes(chan).coilTbl(coil).numturns = fread(rec,1,'int16'); + padding = fread(rec,1,'int32'); + padding = fread(rec,1,'int16'); + SensorRes(chan).coilTbl(coil).area = fread(rec,1,'double'); + end + + for coil = 1:MAX_COILS + SensorRes(chan).HdcoilTbl(coil).position.x = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.y = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.z = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).position.junk = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.x = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.y = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.z = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).orient.junk = fread(rec,1,'double'); + SensorRes(chan).HdcoilTbl(coil).numturns = fread(rec,1,'int16'); + padding = fread(rec,1,'int32'); + padding = fread(rec,1,'int16'); + SensorRes(chan).HdcoilTbl(coil).area = fread(rec,1,'double'); + end + + end + + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Reading Channel Information - DONE',... + 'ds2brainstorm -> Converting Channel Information. . .'... + }) + + end + + nchan= length(channel_name); % Number of channels + + % Explode data according to channel type + imegsens = find([SensorRes.sensorTypeIndex] == 5); % Indices of MEG sensors + ieegsens = find([SensorRes.sensorTypeIndex] == 9); % Indices of EEG sensors + iothersens = [find([SensorRes.sensorTypeIndex] == 11),find([SensorRes.sensorTypeIndex] == 10)]; % Indices of OTHER sensors ('Stimulation input' and 'ADC') + irefsens = find([SensorRes.sensorTypeIndex] == 0); % Reference Channels + irefsens = [irefsens,find([SensorRes.sensorTypeIndex] == 1)]; % Reference Channels + + if READRES == 2 % Enough data information - send it out of here + % Initialize output arguments + [F,Channel,grad_order_no,no_trials,Time, RunTitle] = deal([]); + F = GenRes4; + F.filter = filter; + F.imegsens = imegsens; + F.ieegsens = ieegsens; + F.irefsens = irefsens; + F.iothersens = iothersens; + F.ChannelNames = char(ChannelName); + F.grad_order_no = [SensorRes(:).grad_order_no]; + F.nchan = length([imegsens,ieegsens,irefsens,iothersens]); + F.Time = Time; + return + end + + ieeg = 0; imeg = 0; + iother = 0; + iother2 = 0; + eegID = []; + otherID = []; + other2ID = []; + megID = []; + + iref = 0; + refID = []; + + chaneeg = [];% Index of EEG channels + chanmeg = [];chanother = []; + + [Channel(1:nchan)] = deal(struct('Loc',[],'Orient',[],'Comment',[],'Weight',[],'Type',[],'Name','')); + + for chan = 1:nchan + switch SensorRes(chan).sensorTypeIndex + case {0,1} %'References coils + iref = iref+1; + MAX_COILS = 2; % Take only into account the 2 first coils for every sensor + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100; % In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + tmp = [SensorRes(chan).HdcoilTbl(:).orient]; + tmpx = [tmp(1:MAX_COILS).x]; + tmpy = [tmp(1:MAX_COILS).y]; + tmpz = [tmp(1:MAX_COILS).z]; + + Channel(chan).Orient = ... + [tmpx;tmpy;tmpz]; + + + % Reorient along the outward pointing normal + loc = Channel(chan).Loc'; + ps1=sum((loc(1,:).*Channel(chan).Orient(:,1)')')'; + ps2=sum((loc(2,:).*Channel(chan).Orient(:,2)')')'; + Channel(chan).Orient(:,1) = (sign(ps1)*ones(1,3).*Channel(chan).Orient(:,1)')'; + Channel(chan).Orient(:,2) = (sign(ps2)*ones(1,3).*Channel(chan).Orient(:,2)')'; + + Channel(chan).Comment = ''; % SB 20-Nov-2002 + Channel(chan).Name = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)];% SB 20-Nov-2002 + Channel(chan).Type = 'MEG REF'; % SB 20-Nov-2002 + + % Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + % if isempty(deblank(Channel(chan).Type)) + % Channel(chan).Type = 'MEG REF'; + % end + + chanmeg = [chanmeg,chan]; + refID(iref) = chan; + Channel(chan).Weight = [1 -1] ; + + case 5 % MEG + % KND: + % Quick & dirty test for possible Virtual MEG channel + % To detect Virtual ones, we could also use + % Head Coil Position = (0,0,0) + % ie. SensorRes(chanNumber).HdcoilTbl(1).position.x=0 + % SensorRes(chanNumber).HdcoilTbl(1).position.y=0 + % SensorRes(chanNumber).HdcoilTbl(1).position.z=0 + + if SensorRes(chan).coilTbl(1).area > 0 + % Not a virtual one... I guess ! + % -- KND + + imeg = imeg+1; + MAX_COILS = 2; % Take only into account the 2 first coils for every sensor + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100; % In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + tmp = [SensorRes(chan).HdcoilTbl(:).orient]; + tmpx = [tmp(1:MAX_COILS).x]; + tmpy = [tmp(1:MAX_COILS).y]; + tmpz = [tmp(1:MAX_COILS).z]; + + Channel(chan).Orient = ... + [tmpx;tmpy;tmpz]; + + % Reorient along the outward pointing normal + loc = Channel(chan).Loc'; + ps1=sum((loc(1,:).*Channel(chan).Orient(:,1)')')'; + ps2=sum((loc(2,:).*Channel(chan).Orient(:,2)')')'; + Channel(chan).Orient(:,1) = (sign(ps1)*ones(1,3).*Channel(chan).Orient(:,1)')'; + Channel(chan).Orient(:,2) = (sign(ps2)*ones(1,3).*Channel(chan).Orient(:,2)')'; + + Channel(chan).Comment = ' ';%[SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Type = 'MEG';%SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + + chanmeg = [chanmeg,chan]; + megID(imeg) = chan; + Channel(chan).Weight = [1 -1] ; + Channel(chan).Name = ChannelName{chan}; %char(strtok(channel_name{chan},'-')); + else + %KND : + % Virtual Channel Specifications + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Type = 'VirtualMEG'; + Channel(chan).Weight = [] ; + Channel(chan).Name = char(strtok(channel_name{chan},'-')); + iother = iother+1; + chanother = [chanother,chan]; + otherID(iother) = chan; + %remove it from imegsens + imegsens=setdiff(imegsens, chan); + end + % -- KND + case 9 % EEG + ieeg = ieeg + 1; + MAX_COILS = 1; % Take only into account the first sensor location for EEG (second pseudo-coil location is [0 0 0] as writtent in .ds files) + tmp = [SensorRes(chan).HdcoilTbl(:).position]; + tmpx = [tmp(1:MAX_COILS).x]/100;% In meters + tmpy = [tmp(1:MAX_COILS).y]/100; + tmpz = [tmp(1:MAX_COILS).z]/100; + + Channel(chan).Loc = ... + [tmpx;tmpy;tmpz]; + + Channel(chan).Orient = []; + + Channel(chan).Type = 'EEG';%SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + Channel(chan).Comment = ' ';%[SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + Channel(chan).Name = ChannelName{chan}; %char(strtok(channel_name{chan},'-'));%int2str(ieeg) ; + chaneeg = [chaneeg,chan]; + eegID(ieeg) = chan; + + case 11 % STIM + iother = iother+1; + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + if isempty(deblank(Channel(chan).Type )) + Channel(chan).Type = 'STIM'; + end + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + chanother = [chanother,chan]; + otherID(iother) = chan; + + otherwise + % KND: + % for MicroMed EEG dataHandled... + % iother2 = iother2+1; + iother = iother+1; + % -- KND + Channel(chan).Loc = []; + Channel(chan).Orient = []; + Channel(chan).Type = SensorNames{SensorRes(chan).sensorTypeIndex+1} ; + if isempty(deblank(Channel(chan).Type )) + Channel(chan).Type = 'OTHER'; + end + Channel(chan).Comment = [SensorNames{SensorRes(chan).sensorTypeIndex+1},' ',int2str(chan)]; + Channel(chan).Weight = []; + chanother = [chanother,chan]; + other2ID(iother) = chan; + + end + end + + if VERBOSE + bst_message_window('ds2brainstorm -> Converting Channel Information - DONE') + end + %------------------------------------------------------------------------------- + + + %----------------------------------READ Coefficients--------------------------------- + + % Number of coefficient records + nrec = fread(rec,1,'int16'); + + channel_name = cellstr(char(channel_name{:})); + hexadef = {'00000000','47314252','47324252','47334252','47324f49','47334f49'}; + strdef = {'NOGRAD','G1BR','G2BR','G3BR','G2OI','G3OI'}; + + CoefInfo = cell(length(channel_name),length(strdef)-1); + + %SensorCoefResRec + if VERBOSE + h = waitbar(0,'Reading Coefficient Information...'); + end + + for k = 1:nrec + SensorCoefResRec(k).sensorName = char(fread(rec,32,'char')'); + SensorCoefResRec(k).coefType = (fread(rec,1,'bit32')); + padding = fread(rec,1,'int32'); + SensorCoefResRec(k).CoefResRec.num_of_coefs = fread(rec,1,'int16'); + + SensorCoefResRec(k).CoefResRec.sensor_list = char(fread(rec,[SENSOR_LABEL,MAX_BALANCING],'uchar')'); + SensorCoefResRec(k).CoefResRec.coefs_list = fread(rec,MAX_BALANCING,'double'); + + cchannel = strmatch( deblank(SensorCoefResRec(k).sensorName),channel_name); + CoefType = find(hex2dec(hexadef)==(SensorCoefResRec(k).coefType)); + + if CoefType > 0 + + CoefInfo{cchannel,CoefType-1}.num_of_coefs = SensorCoefResRec(k).CoefResRec.num_of_coefs; + + for i=1:CoefInfo{cchannel,CoefType-1}.num_of_coefs + CoefInfo{cchannel,CoefType-1}.sensor_list(i) = irefsens(strmatch(strtok(SensorCoefResRec(k).CoefResRec.sensor_list(i,:),char(0)),channel_name(irefsens))); + CoefInfo{cchannel,CoefType-1}.coefs(i) = SensorCoefResRec(k).CoefResRec.coefs_list(i); + end + end + if VERBOSE + if(~rem(k,floor(nrec/10))), % only occasionally + waitbar(k/nrec); + end + end + + end + + if VERBOSE + delete(h) + end + + % Channel Gains + gain_chan = zeros(size(channel_name,1),1); + gain_chan(imegsens) = ([SensorRes(imegsens).properGain]'.*[SensorRes(imegsens).qGain]'); + gain_chan(irefsens) = ([SensorRes(irefsens).properGain]'.*[SensorRes(irefsens).qGain]'); + % gain_chan(ieegsens) = 1./([SensorRes(ieegsens).qGain]'*1e-6); + gain_chan(ieegsens) = 1./([SensorRes(ieegsens).qGain]'); + gain_chan(iothersens) = ([SensorRes(iothersens).qGain]'); % Don't know exactly which gain to apply here + + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Coefficient Information',... + sprintf(' Number of coefficient records = %d ', nrec)... + }) + + % [coef_file, message] = fopen('coef_file.txt','wt+'); + % + % if coef_file < 0 + % errordlg(message) + % return + % end + % + % fprintf(coef_file,'Number of coefficient records = %d \n', nrec); + % + % for k = 1:nrec + % coefType = dec2hex(SensorCoefResRec(k).coefType); + % coefType = strdef{hex2dec(hexadef)==hex2dec(coefType)}; + % + % fprintf(coef_file,'Channel %s type %s, ',SensorCoefResRec(k).sensorName, coefType); + % + % num_of_coefs = SensorCoefResRec(k).CoefResRec.num_of_coefs; + % fprintf(coef_file,'number = %d:\n', num_of_coefs); + % if 0 + % for j=1:num_of_coefs + % fprintf(coef_file,' %s ', SensorCoefResRec(k).CoefResRec.sensor_list{j}); + % fprintf(coef_file,' %g ',SensorCoefResRec(k).CoefResRec.coefs_list(j)); + % end + % fprintf(coef_file,'\n'); + % end + % end + % + % bst_message_window({... + % sprintf('ds2brainstorm -> Coefficient Information saved in coef_file.txt'),... + % sprintf('ds2brainstorm -> Reading Coefficient Information - DONE'),... + % ' '... + % }) + bst_message_window({... + sprintf('ds2brainstorm -> Reading Coefficient Information - DONE'),... + ' '... + }) + end + + + % Calculus of the matrix for nth-order gradient correction + % Coefficients for unused reference channels are weigthed by zeros in + % the correction matrix. + Gcoef = zeros(length(imegsens),length(min(irefsens):max(irefsens))); + grad_order_no = [SensorRes(:).grad_order_no]; + for k = 1:length(imegsens) + + % Reference coils for channel k + if grad_order_no(imegsens(k)) == 0 + %Data is saved as RAW + %Save 3rd order gradient sensor-list for subsequent correction if requested later by the user + [refs] = (CoefInfo{imegsens(k),3}.sensor_list); + Gcoef(k,refs-min(irefsens)+1) = CoefInfo{imegsens(k),3}.coefs ... + .* gain_chan(refs)'/gain_chan(imegsens(k)); + else + [refs] = (CoefInfo{imegsens(k),grad_order_no(imegsens(k))}.sensor_list); + Gcoef(k,refs-min(irefsens)+1) = CoefInfo{imegsens(k),grad_order_no(imegsens(k))}.coefs ... + .* gain_chan(refs)'/gain_chan(imegsens(k)); + end + + end + + if ~isempty(imegsens) + Channel(imegsens(1)).Comment = Gcoef; + end + % Channel(imegsens(1)).imegsens = imegsens; + % Channel(imegsens(1)).ieegsens = imegsens; + % Channel(imegsens(1)).irefsens = irefsens; + % Channel(imegsens(1)).RefChannel = Channel; % Store MEG reference information for future call to MEG forward routines and proper processing of gradient correction + + SensorLocFile = strrep(ds_directory,[fileparts(ds_directory),filesep],''); + SensorLocFile = strrep(SensorLocFile,'.ds','_SensorLoc_Results.mat'); + save_sensor_locs(Channel,SensorLocFile) + + if VERBOSE + bst_message_window('wrap',... + sprintf('ds2brainstorm -> Sensor locations can be visualized with the MRI Tool by loading the file: %s',SensorLocFile)... + ) + end + + fclose('all'); + + % Create the BrainStorm res4 file for subsequent fast access to the data file + no_channels = length(Channel); + gain_chan(ieegsens)=1./gain_chan(ieegsens); + no_trials = [1:gSetUp.no_trials]; + + save(res4_mat,'gSetUp','meg4file','ieegsens','irefsens', 'iothersens', 'imegsens','Time','no_channels','gain_chan','channel_name','Channel','grad_order_no','filter','RunTitle','no_trials'); + + if READRES == 1 + READRES = 0; %read the res4.mat file just created and read the data by block. + if nargin == 2 % Stop there + return + %CHANNELS = 1:length(Channel); % With all available channels... + %TIME = Time; % whole time duration... + %NO_TRIALS = 1:gSetUp.no_trials; % All trials + elseif nargin > 2 + % Fill empty arguments + if isempty(CHANNELS) + CHANNELS = 1:length(Channel); % Read all available channels + end + if isempty(TIME) + % KND: + % Bug in the following line? + % TIME = Time; % Read entire trial duration + TIME=[Time(1) Time(end)]; + % -- KND + + end + if isempty(NO_TRIALS) + NO_TRIALS = 1:gSetUp.no_trials; % Read all trials + end + end + end + +else % READRES == 0 + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Loading resources : %s',res4_mat),... + }) + end + load(res4_mat); + + % KND: + if isempty(TIME) + TIME = [Time(1) Time(end)]; % Read entire trial duration + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Whole trial will be read: Time window: %f %f', TIME(1),TIME(2))... + }) + end + end + % -- KND +end + + +%--------------------------- Readind DATA FILE ------------------------------ + +if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Reading Data')... + }) +end + +if nargin == 2 & READRES ~= 3 % Read entire block of data + + no_trials = gSetUp.no_trials; + + [meg,message] = fopen(meg4file,'rb','s'); % Big-endian byte ordering + if meg < 0 + errordlg(message) + return + end + + F = cell(gSetUp.no_trials,1); % allocate space for the data array % ASSUME SINGLE TRIAL FOR THE MOMENT - ie enough memory space + header = char(fread(meg,8,'char')'); + + nref=length(irefsens); + + for trial = 1:gSetUp.no_trials + + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Trial %d/%d',trial,gSetUp.no_trials)... + }) + end + + F{trial} = zeros(gSetUp.no_channels,gSetUp.no_samples); + F{trial} = fread(meg,[gSetUp.no_samples gSetUp.no_channels],'int32')'; + + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Done')... + }) + end + % IMPORTANT NOTICE : Applying Gradient Correction + % Data are saved in a given nth-order gradient correction + % Applying gradient correction si only needed for forward model computation + % or if it is desired to reverse to lower-order gradient correction (see importdata.m for instance). + + % Apply channel gains + F{trial}(ieegsens,:) = diag(1./gain_chan(ieegsens))*F{trial}(ieegsens,:) ; %To get Microvolts->already inverted when saved _res4.mat + F{trial}(imegsens,:) = diag(1./gain_chan(imegsens))*F{trial}(imegsens,:) ; + + % Removing DC Offset + switch(DCOffset) + case {1,2} + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Removing DC offset'... + }) + end + + if DCOffset == 1 % Based on entire trial length + F{trial}(imegsens,:) = F{trial}(imegsens,:) - repmat(mean(F{trial}(imegsens,:)')',1,size(F{trial},2)); + F{trial}(irefsens,:) = F{trial}(irefsens,:) - repmat(mean(F{trial}(irefsens,:)')',1,size(F{trial},2)); + else % Based on pretrigger + TimeNeg = TIME(TIME<0); % Find pretrigger time points + if ~isempty(TimeNeg) + F{trial}(imegsens,:) = F{trial}(imegsens,:) - repmat(mean(F{trial}(imegsens,TimeNeg)')',1,size(F{trial},2)); + F{trial}(irefsens,:) = F{trial}(irefsens,:) - repmat(mean(F{trial}(irefsens,TimeNeg)')',1,size(F{trial},2)); + else + % Do nothing + end + end + + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Removing DC offset - DONE'... + }) + end + + otherwise + % Do nothing + end + + F{trial}(irefsens,:) = diag(1./gain_chan(irefsens))*F{trial}(irefsens,:) ; + F{trial}(iothersens,:) = diag(1./gain_chan(iothersens))*F{trial}(iothersens,:) ; + + end + + fclose('all'); + + %------------------------------------------------------------------------------------------------------------------------------------ + +else % Reads sub-block of data + + + if READRES == 3 + + F = ds_directory; + + if isempty(NO_TRIALS) % argument NO_TRIALS not defined + no_trials = [1:gSetUp.no_trials]; + else + no_trials = [NO_TRIALS]; + end + + else + + %ds2brainstorm(ds_directory,VERBOSE,READRES,CHANNELS,TIME, NO_TRIALS); + if isempty(NO_TRIALS) % argument NO_TRIALS not defined + no_trials = [1:gSetUp.no_trials]; + else + no_trials = [NO_TRIALS]; + end + + if isempty(CHANNELS) + CHANNELS = [1:length(Channel)]; + end + + fclose('all'); + [meg,message] = fopen(meg4file,'rb','s'); % Big-endian byte ordering + if meg < 0 + errordlg(message) + return + end + + % no_samples = round((TIME(end)-TIME(1))*gSetUp.sample_rate) +1; % Number of time samples in a trial + + F = cell(length(no_trials),1); % allocate space for the data array % ASSUME SINGLE TRIAL FOR THE MOMENT - ie enough memory space + % Adjust time range to the closest time samples; + if isempty(TIME) + return + end + + header = char(fread(meg,8,'char')'); + implicit.sample_rate = 1/(Time(2) - Time(1)); % i.e. the one used in the data file given the time begin_time end period. + % t_in = round((TIME(1)-Time(1))*implicit.sample_rate) +1; % Sample time offset since the beginning of the trial: beginning of the time window TIME + % + % no_samples = round((TIME(end)-TIME(1))*implicit.sample_rate)+1; % Number of time samples to extract + % t_out = t_in + no_samples - 1; + + tmp = findclosest([TIME],Time'); + t_in = tmp(1); + t_out = tmp(2); + no_samples = length(t_in:t_out); + + try + Time = Time(t_in:t_out); % SB 23-Dec-2002 + catch + error(... + sprintf('Data time ranges from %3.1f to %3.2f ms. Please adjust time extraction window',Time(1),Time(end))); + end + + diff_trials = diff(no_trials)-1; % Number of trials between each selected trials (useful when skipping a few trials) + + ByteSizeOfTrial= no_channels*gSetUp.no_samples*4; % Byte size of a single trial of data (Int32 coding) + + samples_skip = gSetUp.no_samples-no_samples; %Number of time samples to skip per channel + + LastChannelSkip = (no_channels - max(CHANNELS))*gSetUp.no_samples*4; % Skip data from last channels + + channels = [min(CHANNELS):max(CHANNELS)]; % Block of channels to extract. + + FirstChannelSkip = (min(CHANNELS)-1)*gSetUp.no_samples*4; % Skip data from first channels + no_channels = length(channels); + + itrial = 0; + + for trial = no_trials + itrial = itrial+1; + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Trial %d / %d',itrial,length(no_trials))... + }) + end + + F{itrial} = zeros(no_channels,no_samples); + + if trial == no_trials(1) % Read first trial + fseek(meg,(trial-1)*ByteSizeOfTrial + FirstChannelSkip + (t_in-1)*4 ,0); + else % just shift from the size of a trial + fseek(meg,LastChannelSkip + diff_trials(itrial-1)*ByteSizeOfTrial + FirstChannelSkip + (t_in-1)*4 ,0); + end + + F{itrial} = fread(meg,[no_samples no_channels],[num2str(no_samples),'*int32=>int32'], samples_skip*4)'; + F{itrial} = F{itrial}(CHANNELS-min(CHANNELS)+1,:); + + % IMPORTANT NOTICE : Applying Gradient Correction + % Data are saved in a given nth-order gradient correction + % Applying gradient correction is only needed for forward model computation + % or if it is desired to reverse to lower-order gradient correction (see importdata.m for instance). + + % Apply channel gains + F{itrial} = diag(1./gain_chan(CHANNELS))*double(F{itrial}); + + % Removing DC Offset + if isempty(DCOffset) + DCOffset = 0; + end + switch(DCOffset) + case {1,2} + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Removing DC offset'... + }) + end + + if DCOffset == 1 % Based on entire trial length + F{itrial}(imegsens,:) = F{itrial}(imegsens,:) - repmat(mean(F{itrial}(imegsens,:)')',1,size(F{itrial},2)); + F{itrial}(irefsens,:) = F{itrial}(irefsens,:) - repmat(mean(F{itrial}(irefsens,:)')',1,size(F{itrial},2)); + else % Based on pretrigger + TimeNeg = intersect(find(Time(t_in:t_out) >= TIME(1)),find(Time(t_in:t_out)<0)); % Find pretrigger time points + if ~isempty(TimeNeg) + F{itrial}(imegsens,:) = F{itrial}(imegsens,:) - repmat(mean(F{itrial}(imegsens,TimeNeg)')',1,size(F{itrial},2)); + F{itrial}(irefsens,:) = F{itrial}(irefsens,:) - repmat(mean(F{itrial}(irefsens,TimeNeg)')',1,size(F{itrial},2)); + else + % Do nothing + end + end + + if VERBOSE + bst_message_window({... + 'ds2brainstorm -> Removing DC offset - DONE'... + }) + end + + otherwise + % Do nothing + end + + + if VERBOSE + bst_message_window({... + sprintf('ds2brainstorm -> Done')... + }) + end + + end + + fclose('all'); + end + +end + + +function PrintCoilPos(channel_file, CoilRec_ext,nCoils) ; + +% Subroutine to DS2BRAINSTORM +% Formatted output of channel locations in a file (channel_file is the pointer to this file) +% as defined in theCoilRec_ext structure, according to the number of coils nCoils for every gradiometer + +for coil=1:nCoils + fprintf(channel_file,'Coil %d:', coil); + fprintf(channel_file,' pX %g,', CoilRec_ext(coil).position.x); + fprintf(channel_file,' pY %g,', CoilRec_ext(coil).position.y); + fprintf(channel_file,' pZ %g ', CoilRec_ext(coil).position.z); + fprintf(channel_file,'-'); + fprintf(channel_file,' oX %g,', CoilRec_ext(coil).orient.x); + fprintf(channel_file,' oY %g,', CoilRec_ext(coil).orient.y); + fprintf(channel_file,' oZ %g ', CoilRec_ext(coil).orient.z); + fprintf(channel_file,'-'); + fprintf(channel_file,' turns %d,', CoilRec_ext(coil).numturns); + fprintf(channel_file,' area %g', CoilRec_ext(coil).area); + + if coil < nCoils + fprintf(channel_file,' --- '); + end + + fprintf(channel_file,'\n'); +end + +return + +function save_sensor_locs(Channel,SensorLocFile) +% Save Channel location in a pseudo-result file for visualization in the MRITool + +nchan = length(Channel); +meg = good_channel(Channel,ones(nchan,1),'MEG'); +eeg = good_channel(Channel,ones(nchan,1),'EEG'); + +nchan= length([meg,eeg]); +SourceLoc = cell(1,nchan); + +i = 0; +for k = [meg,eeg] + i = i+1; + SourceLoc{i} = Channel(k).Loc(:,1); + SourceOrder(i) = -1; + Comment = 'Sensor Locations'; +end +DataFlag = 'Sensors'; +if isdir('BrainStorm') + save(fullfile('BrainStorm',SensorLocFile),'SourceLoc','SourceOrder','DataFlag','Comment') +else + save sensor_result SourceLoc SourceOrder DataFlag Comment +end + +return diff --git a/brainstorm/getChannelLocs.m b/brainstorm/getChannelLocs.m new file mode 100755 index 0000000..5f4125b --- /dev/null +++ b/brainstorm/getChannelLocs.m @@ -0,0 +1,4 @@ +function [pos]=getChannelLocs(Channel) +for i=1:length(Channel) + pos(i,1:3)=reshape(Channel(i).Loc(1:3), 1,3); +end \ No newline at end of file diff --git a/brainstorm/getPositionChannel.m b/brainstorm/getPositionChannel.m new file mode 100755 index 0000000..88ef2f1 --- /dev/null +++ b/brainstorm/getPositionChannel.m @@ -0,0 +1,4 @@ +function [pos]=getPositionChannel(Channel) +for i=1:length(Channel) + pos(i,1:3)=reshape(Channel(i).Loc(1:3), 1,3); +end \ No newline at end of file diff --git a/brainstorm/meeg_menu.m b/brainstorm/meeg_menu.m new file mode 100644 index 0000000..60da259 --- /dev/null +++ b/brainstorm/meeg_menu.m @@ -0,0 +1,21 @@ +function [hmenu] = meeg_menu( varargin ) +%MEEG_MENU - Add a MEEG related menu + +[hp,ha,hf]=findTessellationHandles(varargin{:}); +uhp=get(hp, 'UserData'); + +% Remove previous instances +hmenu=findobj(hf, 'Type', 'uimenu', 'Label', 'MEEG'); +delete(hmenu); + +hmenu=uimenu('Label', 'MEEG', 'Parent', hf); +t1 = cortex_menu; +set(t1, 'Parent', hmenu); +t1 = meegui_menu; +set(t1, 'Parent', hmenu, 'Separator', 'on'); +t1 = viewpoint_menu('create',hp); +set(t1, 'Parent', hmenu, 'Separator', 'on'); +t1 = scout_menu('create',hp); +set(t1, 'Parent', hmenu, 'Separator', 'on'); + +return diff --git a/brainstorm/meegui_menu.m b/brainstorm/meegui_menu.m new file mode 100644 index 0000000..92f14c8 --- /dev/null +++ b/brainstorm/meegui_menu.m @@ -0,0 +1,39 @@ +function [hmenu]= meegui_menu(action, varargin) +% cortex_menu - Menu related to cortical surface processing + +if nargin==0 + action='create'; +end +switch lower(action) + case 'create' + hmenu=action_create(varargin); +end +return + + +function [hmenu]=action_create(varargin) +hmenu = uimenu('Label','MEEG Gui'); +cback='uhp=get(findTessellationHandles, ''UserData'');if isempty(uhp); return; end;'; +t = uimenu('Parent',hmenu,... + 'Label','Display GUIs',... + 'Checked', 'on',... + 'CallBack', [... + 'if isempty(get(gcbo, ''UserData'')),'... + 'set(gcbo, ''UserData'', findobj(gcbf, ''type'', ''uicontrol''));'... + 'set(findobj(gcbf, ''type'', ''uicontrol''), ''Visible'', ''off'');'... + 'set(gcbo, ''Checked'', ''off'');'... + 'else,'... + 'set(get(gcbo, ''UserData''), ''Visible'', ''on'');'... + 'set(gcbo, ''UserData'', []);'... + 'set(gcbo, ''Checked'', ''on'');'... + 'end;']); + +t = uimenu('Parent',hmenu,... + 'Label','Rotate 3D axes',... + 'Checked', 'off',... + 'CallBack', [... + 'rotate3daxes(get(findTessellationHandles, ''Parent''));'... + 'set(gcbo, ''Checked'',get(findall(gcbf,''Tag'',''figToolRotate3DAxes''),''State''));'... + ]); + + diff --git a/brainstorm/mybrainstorm_toolbar.m b/brainstorm/mybrainstorm_toolbar.m new file mode 100644 index 0000000..b31af28 --- /dev/null +++ b/brainstorm/mybrainstorm_toolbar.m @@ -0,0 +1,134 @@ +function [] = mybrainstorm_toolbar + +hToolbar = findobj(gcf, 'tag', mfilename) +delete(hToolbar) +% Create the toolbar +hToolbar = uitoolbar(gcf, 'tag', mfilename); +th =hToolbar; + +% Add a push tool to the toolbar +a = [.20:.05:0.95] +img1(:,:,1) = repmat(a,16,1)' +img1(:,:,2) = repmat(a,16,1); +img1(:,:,3) = repmat(flipdim(a,2),16,1); +pth = uipushtool(th,'CData',img1,... + 'TooltipString','My push tool',... + 'HandleVisibility','off') +% Add a toggle tool to the toolbar +img2 = im2cdata('~/yomega/img/sci/brain-icons/iconTiny_KnowYourBrain.png') + +tth = uitoggletool(th,'CData',img2,'Separator','on',... + 'TooltipString','Your toggle tool',... + 'HandleVisibility','off', 'callback', '') + + + +% Matlab icons +filename = fullfile(matlabroot,'/toolbox/matlab/icons/greenarrowicon.gif'); +cdataRedo = im2cdata(filename) +cdataUndo = cdataRedo(:,[16:-1:1],:); + +% Add the icon (and its mirror image = undo) to the latest toolbar +hUndo = uipushtool('cdata',cdataUndo, 'tooltip','undo', 'ClickedCallback','uiundo(gcbf,''execUndo'')'); +hRedo = uipushtool('cdata',cdataRedo, 'tooltip','redo', 'ClickedCallback','uiundo(gcbf,''execRedo'')'); + +hToolbar = findall(hFig,'tag','FigureToolBar'); +%hToolbar = get(hUndo,'Parent'); % an alternative +hButtons = findall(hToolbar); +set(hToolbar,'children',hButtons([4:end-4,2,3,end-3:end])); +set(hUndo,'Separator','on'); + +% Retrieve redo/undo object +undoObj = getappdata(hFig,'uitools_FigureToolManager'); +if isempty(undoObj) + undoObj = uitools.FigureToolManager(hFig); + setappdata(hFig,'uitools_FigureToolManager',undoObj); +end + +% Customize the toolbar buttons +latestUndoAction = undoObj.CommandManager.peekundo; +if isempty(latestUndoAction) + set(hUndo, 'Tooltip','', 'Enable','off'); +else + tooltipStr = ['undo' latestUndoAction.Name]; + set(hUndo, 'Tooltip',tooltipStr, 'Enable','on'); +end + +return + +% Add undo dropdown list to the toolbar +jToolbar = get(get(hToolbar,'JavaContainer'),'ComponentPeer'); +if ~isempty(jToolbar) + undoActions = get(undoObj.CommandManager.UndoStack,'Name'); + jCombo = javax.swing.JComboBox(undoActions(end:-1:1)); + set(jCombo, 'ActionPerformedCallback', @myUndoCallbackFcn); + jToolbar(1).add(jCombo,5); %5th position, after printer icon + jToolbar(1).repaint; + jToolbar(1).revalidate; +end + +end +% Drop-down (combo-box) callback function +function myUndoCallbackFcn(hCombo,hEvent) +itemIndex = get(hCombo,'SelectedIndex'); % 0=topmost item +itemName = get(hCombo,'SelectedItem'); +% user processing needs to be placed here +end + + +function [ho]=action_mni(vp,ho) +% Change viewpoint (vp) for object ho (which can be a patch handle or a +% menu handle) +if nargin<2 + ho=[]; + hmnu=[]; +end +if isequal(get(ho, 'type'), 'uimenu') + hmnu=ho; + ho=get(get(ho, 'Parent'), 'UserData'); +end +[ho,ha]=findTessellationHandles(ho); +switch lower(vp) + case 'top' + view(ha,[0 0 1]) + case 'bottom' + view(ha,[0 0 -1]) + case 'left' + view(ha,[-1 0 0]) + case 'right' + view(ha,[1 0 0]) + case 'front' + view(ha,[0 1 0]) + case 'back' + view(ha,[0 -1 0]) + case 'zflip' + if z + set(ha, 'zdir', 'reverse') + set(hmnu, 'Checked', 'on') + else + set(ha, 'zdir', 'normal') + set(hmnu, 'Checked', 'off') + end +end +end + +function cdata=im2cdata(filename) + +% Load the icon +[cdata,map] = imread(filename); + +if ~isempty(map) +% Convert white pixels into a transparent background +map(find(map(:,1)+map(:,2)+map(:,3)==3)) = NaN; + +% Convert white pixels into a transparent background +map(find(map(:,1)+map(:,2)+map(:,3)==0)) = NaN; + + +% Convert into 3D RGB-space +cdata = ind2rgb(cdata,map); +elseif isinteger(cdata) + cdata=double(cdata)./255; +end + +end \ No newline at end of file diff --git a/brainstorm/scout_button.m b/brainstorm/scout_button.m new file mode 100644 index 0000000..1adffd1 --- /dev/null +++ b/brainstorm/scout_button.m @@ -0,0 +1,147 @@ +function [varargout]= scout_button(action,varargin) +% Add a GUI button on a figure to click scouts etc. +% scout_button; +% [hbtn] = scout_button; +% [hbtn] = scout_button('action', 'Property1', ...); +% e.g. scout_button('init','Position', [x y dx dy]) +% scout_button('set','UserData', handle_cortex) +% scout_button('click', handle_cortex) +% +if nargin==0 + action='init'; +end +switch(action) + case 'init' + hbtn=action_init(varargin{:}); + if nargout>0 + varargout={hbtn}; + end + case 'click' + [idx_scout,hctx,hbtn]=action_click(varargin{:}); + if nargout>0 + varargout={idx_scout,hctx,hbtn}; + else + ns = numel(idx_scout); + z=get(hctx, 'FaceVertexCData'); + assignin('base', 'ans', idx_scout); + for i=1:min(ns,10) + fprintf('\nScout #:%d', idx_scout(i)); + if ~isempty(z) + fprintf('\tValue:%g', z(idx_scout(i))); + end + fprintf(' (variable ans has been changed)\n'); + end + if ns>1 && ~isempty(z) + fprintf('... %d scouts in the cluster ...\n',ns); + fprintf('Mean value : %g \n',mean(z(idx_scout))); + end + end +end + +function [hbtn]=action_init(varargin) +delete(findobj(gcf, 'Tag', mfilename, 'Style', 'pushbutton')) +hbtn=uicontrol('Style', 'pushbutton','Tag', mfilename); +test_select3d; +set(hbtn, 'String', 'Scout'); +set(hbtn, 'Units', 'normalized'); +set(hbtn, 'Callback', 'scout_button(''click'', gcbo);'); +action_set(hbtn, varargin{:}); + +function b=test_select3d +if exist('select3d')<2 + warning('Function needs BrainStorm/PublicToolbox/OtherTools/select3D.m') + b=0; +else + b=1; +end + + +function[hbtn]=action_set(hbtn,varargin) +if nargin==2 + set(hbtn, 'UserData', varargin{1}); +elseif nargin>1 && mod(nargin-1,2)==0 + set(hbtn, varargin{:}); +end + + +function [vi,hctx,hbtn]=action_click(varargin) +if ~test_select3d + return +end +hctx=[]; +if nargin==0 + hbtn=gcbo; +else + if isequal(get(varargin{1}, 'Tag'), mfilename) + hbtn=varargin{1}; + hctx=get(hbtn, 'UserData'); + else + hctx=varargin{1}; + hbtn=[]; + end +end +if isempty(hctx) + try + hctx=findTessellationHandles; + catch + end +end +if isempty(hctx) + error('No surface found'); + return +end +ax=get(hctx, 'Parent'); +axes(ax); +[x, y, button] = ginput(1); +[p v vi f fi]=select3d(hctx);; + +% +ctx=getappdata(hctx); +if button > 1 + if isempty(fieldnames(ctx)) + fv.faces = get(hctx,'Faces'); + fv.vertices = get(hctx,'Vertices'); + vc=tess_vertices_connectivity(fv); + f=get(hctx,'FaceVertexCData'); + + if size(f,2)==3 + % try to guess what appears "activated" + [v,n]=histk(f,'rows'); + v=v(n>.25*size(f,1),:); + f = ~ismember(f,v, 'rows'); + end + if all(f) + fprintf('Using Color threshold, based on CLim') + % use CLim + f=f.*(f>min(get(ax,'Clim'))); + end + end + + [c,sz,mc,v2c] = clustering(f,vc); + if v2c(vi) == 0 + vi = [] + else + vi = c{v2c(vi)}; + end + hold on + hplot=plot3(fv.vertices(vi,1),fv.vertices(vi,2),fv.vertices(vi,3),'.'); + drawnow; + pause(1) + delete(hplot) + hold off +end +if not(isfield(ctx, 'tex')) + % warning('No texture (''AppData''.tex) is associated with this cortical surface') + return +end +figure('Name', sprintf('Vertex %d [%0.2g %0.2g %0.2g]', vi, v)); +if ~isfield(ctx, 'time') + ctx.time=1:size(ctx.tex,2); +end +plot(ctx.time, ctx.tex(vi,:)); +hold on; +if isfield(ctx, 'htime') + stem(ctx.time(get(ctx.htime, 'Value')), ctx.tex(vi,get(ctx.htime, 'Value')), '.r'); +end +% psh_scout_cbk=['ginput(1);' scout_cbk]; + diff --git a/brainstorm/scout_menu.m b/brainstorm/scout_menu.m new file mode 100644 index 0000000..a37ef93 --- /dev/null +++ b/brainstorm/scout_menu.m @@ -0,0 +1,125 @@ +function [hmenu]= scouts_menu(action, varargin) +% cortex_menu - Menu related to cortical surface processing + +if nargin==0 + action='init'; +end +switch(action) + case {'init', 'create'} + hmenu=action_init(varargin{:}); + if nargout>0 + varargout={hmenu}; + end + case 'click' + [idx_scout,hctx,hbtn]=action_click(varargin{:}); + if nargout>0 + varargout={idx_scout,hctx,hbtn}; + else + z=get(hctx, 'FaceVertexCData'); + assignin('base', 'ans', idx_scout); + disp(sprintf('Scout #:%d Value:%g', idx_scout, z(idx_scout))); + end +end + + +function [hbtn]=action_init(varargin) +hmenu = uimenu('Label','Scout manager'); +cback='uhp=get(findTessellationHandles, ''UserData'');'; +% delete(findobj(gcf, 'Tag', mfilename, 'Style', 'pushbutton')) +% hbtn=uicontrol('Style', 'pushbutton','Tag', mfilename); +hbtn=uimenu('Label','Pick one...', 'Parent', hmenu, 'Tag', mfilename); +test_select3d; +set(hbtn, 'Callback', 'scout_menu(''click'', gcbo);'); +action_set(hbtn, varargin{:}); + +% set(hmenu, 'Callback',[ cback ... +% 'if isfield(uhp, ''vertconn''), state=''on''; else state=''off''; end;'... +% 'set(findobj(gcbo, ''Label'', ''Smooth surface''), ''Enable'',state);'... +% 'set(findobj(gcbo, ''Label'', ''Adv. Smooth surface''), ''Enable'', state);'... +% ]); + +% t1 = uimenu('Parent',hmenu,... +% 'Label','Define scout',... +% + +function b=test_select3d +if exist('select3d')<2 + warning('Function needs BrainStorm/PublicToolbox/OtherTools/select3D.m') + b=0; +else + b=1; +end + +function[hbtn]=action_set(hbtn,varargin) +if nargin==2 + set(hbtn, 'UserData', varargin{1}); +elseif nargin>1 && mod(nargin-1,2)==0 + set(hbtn, varargin{:}); +end + + +function [vi,hctx,hbtn]=action_click(varargin) +if ~test_select3d + return +end +hctx=[]; +if nargin==0 + hbtn=gcbo; +else + if isequal(get(varargin{1}, 'Tag'), mfilename) + hbtn=varargin{1}; + hctx=get(hbtn, 'UserData'); + else + hctx=varargin{1}; + hbtn=[]; + end +end +if isempty(hctx) + try + hctx=findTessellationHandles; + catch + end +end +if isempty(hctx) + error('No surface found'); + return +end +ax=get(hctx, 'Parent'); +axes(ax); +[x, y, button] = ginput(1); +[p v vi f fi]=select3d(hctx);; + +figure('Name', sprintf('Vertex %d [%0.2g %0.2g %0.2g]', vi, v)); +ctx=getappdata(hctx) +if button > 1 + if isempty(fieldnames(ctx)) + fv.faces = get(hctx,'Faces'); + fv.vertices = get(hctx,'Vertices'); + vc=tess_vertices_connectivity(fv); + f=get(hctx,'FaceVertexCData'); + if all(f) + % use CLim + f=f.*(f>min(get(ax,'Clim'))); + end + + end +end + + +if not(isfield(ctx, 'tex')) +% warning('No texture (''AppData''.tex) is associated with this cortical surface') + return +end +if ~isfield(ctx, 'time') + ctx.time=1:size(ctx.tex,2); +end +plot(ctx.time, ctx.tex(vi,:)); +hold on; +if isfield(ctx, 'htime') + stem(ctx.time(get(ctx.htime, 'Value')), ctx.tex(vi,get(ctx.htime, 'Value')), '.r'); +end +% psh_scout_cbk=['ginput(1);' scout_cbk]; + + + + diff --git a/brainstorm/scout_swell.m b/brainstorm/scout_swell.m new file mode 100644 index 0000000..87d353b --- /dev/null +++ b/brainstorm/scout_swell.m @@ -0,0 +1,30 @@ +function newverts = scout_swell(iverts,vconn,depth); +%scout_swell - find neighboring vertices of a scout/patch +% [newverts]=scout_swell(iverts,vconn) +% [newverts]=scout_swell(iverts,vconn,depth) + +if nargin<3 + depth=1; +end +iverts=unique(iverts); +newverts=swell(iverts,vconn,depth); +return + + +function [nv]=swell(iv,vc,d) +if d==0 + nv=iv; + return +end +if iscell(vc) + nv=[vc{iv}]; + vc(iv)={[]}; +else + nv=[find(any(vc(iv,:),1))]; + vc(iv,nv)=0; + vc(nv,iv)=0; +end +nv = [nv(:) ; iv(:)]; +nv=unique(nv(:)'); +nv=unique([nv swell(nv,vc,d-1)]); +return diff --git a/brainstorm/scouts_menu.m b/brainstorm/scouts_menu.m new file mode 100644 index 0000000..0dd8bab --- /dev/null +++ b/brainstorm/scouts_menu.m @@ -0,0 +1,26 @@ +function [hmenu]= scouts_menu(action, varargin) +% cortex_menu - Menu related to cortical surface processing + +if nargin==0 + action='create'; +end +switch lower(action) + + case 'create' + hmenu = uimenu('Label','Scout manager'); + + cback='uhp=get(findTessellationHandles, ''UserData'');'; + +% set(hmenu, 'Callback',[ cback ... +% 'if isfield(uhp, ''vertconn''), state=''on''; else state=''off''; end;'... +% 'set(findobj(gcbo, ''Label'', ''Smooth surface''), ''Enable'',state);'... +% 'set(findobj(gcbo, ''Label'', ''Adv. Smooth surface''), ''Enable'', state);'... +% ]); + +% t1 = uimenu('Parent',hmenu,... +% 'Label','Define scout',... +% + + + return +end diff --git a/brainstorm/vertconn2adjacency.m b/brainstorm/vertconn2adjacency.m new file mode 100644 index 0000000..de297cd --- /dev/null +++ b/brainstorm/vertconn2adjacency.m @@ -0,0 +1,61 @@ +function [A]=vertconn2adjacency(vc,VERBOSE) +% vertconn2adjacency - compute the adjacency patrix +% [A]=vertconn2adjacency(vc,VERBOSE) +% +% vc: vertex connectivity, cell array of indices OR patch structure +% A: (sparse) adjacency matrix + +if nargin<2 + VERBOSE=0; +end + +if isfield(vc, 'faces') + VertConn=0; + nv=size(vc.vertices,1); +elseif iscell(vc) + VertConn=1; + nv=length(vc); +else + error('Wrong type of inputs') +end +% Could think of preallocating I and J +% with an a priori ratio of the number of vertices... +% but (sigh)... +I=[]; +J=[]; + +if VERBOSE + h=timebar('Building adjacency matrix','Adjacency'); +end + +if VertConn + l=[0; cellfun('length', vc)]; + cl=cumsum(l); + I=zeros(cl(end),1); + J=[vc{:}]'; + for i=1:nv + I(cl(i)+[1:l(i+1)])=i; + if VERBOSE + timebar(h,i/nv) + end + end +else + % I J should be preallocated + for i=1:nv; + adj=setdiff(unique(vc.faces(find(any(vc.faces==i,2)))),i); + adj=adj(:)'; + adj=double(adj); + n=length(adj); + I=[I i*ones(1,n)]; + J=[J adj]; + if VERBOSE + timebar(h,i/nv) + end + end +end +A=sparse(I,J,ones(length(I),1),nv,nv); +A=A|A'; + +if VERBOSE + close(h); +end diff --git a/brainstorm/view_MNEresults.m b/brainstorm/view_MNEresults.m new file mode 100644 index 0000000..d66fabb --- /dev/null +++ b/brainstorm/view_MNEresults.m @@ -0,0 +1,336 @@ +function [ varargout ] = view_MNEresults(action,varargin) +% view_MNEresults - Diplays BrainStorm results +% +% [ hf ] = view_MNEresults(fv,cdata) +% [ hf ] = view_MNEresults(faces,verts,cdata) +% [ hf ] = view_MNEresults(fv,cdata,time) + +if nargin<1 + error('No data!') +elseif nargin==1 || ~ischar(action) + varargin=[{action} varargin ]; + action='init'; +end + +try + varargout={eval(sprintf('action_%s(varargin{:});',action))}; +catch + eval(sprintf('action_%s(varargin{:});',action)); +end + +%__________________________________________________________________________ +% +%% ACTION INIT +% +function [hf]=action_init(varargin) +if isfield(varargin{1}, 'faces') + ctx=varargin{1}; + varargin(1)=[]; +else + if nargin>=3 + ctx.faces=varargin{1}; + ctx.vertices=varargin{2}; + varargin([1 2])=[]; + else + error('not enough inputs!') + end +end +if ~isempty(varargin) + if isnumeric(varargin{1}) + ctx.tex=varargin{1}; + if length(varargin)>1 + if isnumeric(varargin{2}) + ctx.time=varargin{2}; + end + end + end +end + +if(size(ctx.vertices,2) ~= 3), % assume transposed + ctx.vertices = ctx.vertices'; % if the assumption is wrong, will crash below anyway +end + +if size(ctx.vertices,1) ~= size(ctx.tex,1) + if size(ctx.vertices,1) == size(ctx.tex,2) + ctx.tex=ctx.tex'; + else + error(sprintf('Data provided are ill-shaped\nVertices: %d\nData: %s',size(ctx.vertices,1),sprintf('%d ',size(ctx.tex)))) + return; + end +end + +nsamples=size(ctx.tex,2); + +if isfield(ctx, 'time') + if length(ctx.time) ~= nsamples + error('Incorrect time vector (bad nuimber of samples)') + end + u.time=ctx.time; +else + u.time=[1:nsamples]; +end + +if ~isfield(ctx,'tex') + warning('No data provided. Distance to origin is used') + ctx.tex = rownorm(ctx.vertices); +end + +hf=figure; +hp=carto_cortex(ctx, ctx.tex(:,1)); +u.hpax=get(hp, 'parent'); +ha=u.hpax; +if any(ctx.tex(:)>0) & any(ctx.tex(:)<0) + u.cmap=jet(256); + u.cmapsym=0; +else + u.cmap=hot(256); + u.cmapsym=1; +end +colormap(u.cmap) + +hcbar=colorbar; +hcmap=uicontrol('Style', 'slider'); +set(hcmap, 'Units', get(hcbar, 'Units')); +set(hcmap, 'Min', min(0,-(log10(size(ctx.tex,1)))+2) , 'Max', 2, 'Value', 2); +set(hcmap, 'Position', get(hcbar, 'Position')*[1 0 0 0; 0 1 0 0; 1.7 0 .5 0 ;0 0 0 1 ]); +set(hcmap, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'cmap')); + +hcmap2=uicontrol('Style', 'slider'); +set(hcmap2, 'Units', get(hcbar, 'Units')); +set(hcmap2, 'Max', 1 , 'Min', 0 , 'Value', 1); +set(hcmap2, 'Position', get(hcmap, 'Position')*[1 0 0 0; 0 1 0 0; 1.1 0 1 0 ;0 0 0 1 ]); +set(hcmap2, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'cmap2')); + +%Tick box above & below colormap slider +hcmaptop=uicontrol('Style', 'checkbox', 'Units', 'normalized'); +set(hcmaptop, 'Position', get(hcmap, 'position')*[1 0 0 0; 0 1 0 0; 0 0 1 1 ; 0 1 0 0]) +hcmapbot=uicontrol('Style', 'checkbox', 'Units', 'normalized'); +set(hcmapbot, 'Position', get(hcmap, 'position')*[1 0 0 0; 0 1 0 0; 0 -1 1 1 ; 0 0 0 0]) +set([hcmapbot hcmaptop] , 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'cmap')); + +% Number of active sources (with the colormap) +hcmaptxt=uicontrol('Style', 'edit'); +set(hcmaptxt, 'Units', 'normalized') +set(hcmaptxt, 'Position', get(hcmapbot, 'Position')*[1 0 0 0; 0 1 0 0; -2 0 0 0; 0 0 0 0]+[0 -0.07 0.1 0.05 ]) +set(hcmaptxt, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'cmaptxt')); + +% Slider to control the time +htime=uicontrol('Style', 'slider', 'Value', 1, 'Min', 1, 'Max', 1+eps); +if nsamples>1 + set(htime, 'SliderStep', [1/ceil(nsamples-1) min(.05, 100/ceil(nsamples-1))]); + set(htime, 'Max', nsamples); +else + set(htime, 'SliderStep', [1 1]); +end +set(htime, 'Units', 'normalized') +set(htime, 'Position', [ .02 .045 .8 .045]) +set(htime, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'timeslider')); + +% Label to display Time (in time units) +htimetxtu=uicontrol('Style', 'edit'); +set(htimetxtu, 'Units', 'normalized') +set(htimetxtu, 'Position', get(htime, 'Position')*[1 0 0 0; 0 1 0 0; 0 0 0 0; 0 1 0 1]+[0 0 0.1 0]) +set(htimetxtu, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'timetxtu')); + +% Label to display Time (in samples) +htimetxts=uicontrol('Style', 'edit'); +set(htimetxts, 'Units', 'normalized') +set(htimetxts, 'Position', get(htimetxtu, 'Position')*[1 0 0 0; 0 1 0 0; 0 0 1 0; 0 1.3 0 1]) +set(htimetxts, 'Callback', sprintf('%s(''%s'',gcbf)',mfilename,'timetxts')); + + +% To point a scout +hscout=scout_button('init','Position', [.7 .1 .1 .05]); +set(hscout, 'callback', [... + '[vi,hctx]=scout_button(''click'', gcbo); '... + 'figure(''Tag'', ''scout:plot'', ''Name'', sprintf(''Scout: #%d'', vi));'... + 'plot(getfield(get(gcbf, ''UserData''), ''time''),subarray(getfield(get(hctx, ''UserData''), ''tex''),vi))'... + ]); +% Set user data in the figure +u.hp=hp; +u.hcmap=hcmap; +u.hcmaptop=hcmaptop; +u.hcmapbot=hcmapbot; +u.hcmaptxt=hcmaptxt; +u.hcmap2=hcmap2; + +u.htime=htime; +u.htimetxtu=htimetxtu; +u.htimetxts=htimetxts; +set(hf, 'UserData', u); + +% Add tooltips +set(u.htime, 'TooltipString', 'Time') +set(u.htimetxtu, 'TooltipString', 'Time (in samples)') +set(u.htimetxts, 'TooltipString', 'Time (in sec)') +set(u.hcmaptxt, 'TooltipString', 'Number of active sources') +set(u.hcmap, 'TooltipString', 'Percentage of active sources') + +% set(u.hp, 'ButtonDownFcn', 'rotate3d on'); +rotate3d(hf, 'on') + +meeg_menu + +return + + +%__________________________________________________________________________ +% +%% ACTION COLORMAP FROM SLIDER +% +function []=action_cmap(hf,ho) +u=get(hf, 'UserData'); +n=power(10,get(u.hcmap, 'Value')); +s=get(u.hcmaptop, 'Value')-get(u.hcmapbot, 'Value'); +if s==0 && ~get(u.hcmaptop, 'Value') + s=u.cmapsym; +end +n=action_colormap(u.hp,n,s); +set(u.hcmaptxt, 'String',num2str(n)); +colorbar('peer', u.hpax); +%rotate3d; +return +%__________________________________________________________________________ +% +%% ACTION COLORMAP FROM TEXT +% +function []=action_cmaptxt(hf,ho) +u=get(hf, 'UserData'); +cdata=get(u.hp, 'FaceVertexCData'); +set(u.hcmap, 'Value', log10(100*str2num(get(u.hcmaptxt, 'String'))/size(cdata,1))); +action_cmap(hf) +return +%__________________________________________________________________________ +% +%% ACTION COLORMAP APPLY +% +function [n]=action_colormap(hp,n,s) +n=showpercent(n,hp,[],[],s); +return +%__________________________________________________________________________ +% +%% ACTION COLORMAP CROP +% +function []=action_cmap2(hf,ho) +u=get(hf, 'UserData'); +ctx=get(u.hp, 'UserData'); +s=get(u.hcmaptop, 'Value')-get(u.hcmapbot, 'Value'); +v=ctx.tex(:,get(u.htime, 'Value')); +% q=power(10,get(u.hcmap2, 'Value')) +q=get(u.hcmap2, 'Value'); +% Slider is more ergonomic as we may want to use to remove one or few +% outliers +q=(q)^(1/6); +t=get(u.hpax,'CLim'); +if s==0 + cmap=colormap(u.hpax); + n=size(cmap,1); + x=sum(all(cmap==repmat(cmap(ceil(n/2),:),n,1),2)); + v(abs(v)0 + v(vt(2))=[]; + t(1)=quantile(v,q); +end +set(u.hpax,'Clim',[t]) +colorbar('peer', u.hpax); +% action_cmap(hf) +return + + + + + +%__________________________________________________________________________ +% +%% ACTION SCOUT BUTTON (scoutbtn) +% +function [h]=action_scoutbtn(hf) +u=get(hf, 'UserData'); +[p v vi f fi]=select3d(u.hp); +figure('Name', sprintf('Scout: Vert#%d [%0.2g %0.2g %0.2g]', vi, v)); +ctx=get(u.hp, 'UserData'); +h=plot(u.time, ctx.tex(vi,:)); +hold on; +stem(u.time(get(u.htime, 'Value')), ctx.tex(vi,get(u.htime, 'Value')), '.r'); +assignin('caller', 'vi', vi) + + +%__________________________________________________________________________ +% +%% ACTION TIME SLIDER (timeslider) +% +function []=action_timeslider(hf) +u=get(hf, 'UserData'); +set(u.htime, 'Value',round(get(u.htime, 'Value'))); +ctx=get(u.hp, 'UserData'); +set(u.hp, 'FaceVertexCData',ctx.tex(:,get(u.htime, 'Value'))); +set(u.htimetxts, 'String', num2str(get(u.htime, 'Value'))); +set(u.htimetxtu, 'String', num2str(u.time(get(u.htime, 'Value')))); +colorbar('peer', u.hpax); +rotate3d; + + +%__________________________________________________________________________ +% +%% ACTION TIME TEXT IN TIME UNITS (timetxtu) +% +function [h]=action_timetxtu(hf) +u=get(hf, 'UserData'); +t=get(u.htime, 'Value'); +set(u.htime, 'Value', whichTime(str2num(get(u.htimetxtu, 'String')),u.time)); +if t~=get(u.htime, 'Value'); + action_timeslider(hf) + rotate3d; +end + +%__________________________________________________________________________ +% +%% ACTION TIME TEXT IN SAMPLES (timetxts) +% +function [h]=action_timetxts(hf) +u=get(hf, 'UserData'); +t=get(u.htime, 'Value'); +set(u.htime, 'Value', str2num(get(u.htimetxts, 'String'))); +if t~=get(u.htime, 'Value'); + action_timeslider(hf) + rotate3d; +end +return + +F=gcf; +% t0 = findobj(get(F,'Children'),'Flat','Label','&Help'); +% set(findobj(t0,'Position',1),'Separator','on'); +% t0=uimenu('Label', 'test') +% t0 = uicontextmenu('Parent',F,'HandleVisibility','CallBack'); + +t0=uimenu('Label', 'test') +t1 = uimenu('Parent',t0,'Position',1,... + 'Label','SPM web',... + 'CallBack','web(''http://www.fil.ion.ucl.ac.uk/spm'');'); +t1 = uimenu('Parent',t0,'Position',1,... + 'Label','SPM help','ForegroundColor',[0 1 0],... + 'CallBack','spm_help'); + +t0=uimenu('Parent', F,'Label','Colours','HandleVisibility','off'); +t1=uimenu('Parent',t0,'Label','ColorMap'); +t2=uimenu('Parent',t1,'Label','Gray','CallBack','spm_figure(''ColorMap'',''gray'')'); +t2=uimenu('Parent',t1,'Label','Hot','CallBack','spm_figure(''ColorMap'',''hot'')'); +t2=uimenu('Parent',t1,'Label','Pink','CallBack','spm_figure(''ColorMap'',''pink'')'); +t2=uimenu('Parent',t1,'Label','Gray-Hot','CallBack','spm_figure(''ColorMap'',''gray-hot'')'); +t2=uimenu('Parent',t1,'Label','Gray-Pink','CallBack','spm_figure(''ColorMap'',''gray-pink'')'); +t1=uimenu('Parent',t0,'Label','Effects'); +t2=uimenu('Parent',t1,'Label','Invert','CallBack','spm_figure(''ColorMap'',''invert'')'); +t2=uimenu('Parent',t1,'Label','Brighten','CallBack','spm_figure(''ColorMap'',''brighten'')'); +t2=uimenu('Parent',t1,'Label','Darken','CallBack','spm_figure(''ColorMap'',''darken'')'); +t0=uimenu('Parent', F,'Label','Clear','HandleVisibility','off','CallBack','spm_figure(''Clear'',gcbf)'); +t0=uimenu('Parent', F,'Label','SPM-Print','HandleVisibility','off','CallBack','spm_figure(''Print'',gcbf)'); + + + +return diff --git a/brainstorm/viewpoint_menu.m b/brainstorm/viewpoint_menu.m new file mode 100644 index 0000000..0ffea69 --- /dev/null +++ b/brainstorm/viewpoint_menu.m @@ -0,0 +1,199 @@ +function [h]=viewpoint_menu(action, varargin) +% viewpoint_menu - Add a menu to (easily) set viewpoint +% +% viewpoint_menu(h) adds a menu in the figure containing the patch h +% viewpoint_menu(action, ... ) runs various callbacks. +% +% viewpoint_menu(ref,ori) change orientation +% ref: ctf|mni|aims +% ori: top|bottom|left|right|front|back +% Example: +% >> viewpoint_menu('mni', 'top') +% +% viewpoint_menu(ref,ori,h) change orientation for handle h + +if nargin==0 + action='create'; +end +if ~ischar(action) + varargin=[{action}, varargin]; + action='create'; +end +%try + h=feval(sprintf('action_%s', lower(action)), varargin{:}); + %catch + % warning(sprintf('Unknown action: %s', action)); + %end +return + +function [hmenu]=action_create(hp) +if nargin<1 + hp=[]; +end +[hp,ha,hf]=findTessellationHandles(hp); + +% Remove previous instances +hmenu=findobj('Type', 'uimenu', 'Tag', mfilename, 'UserData', hp); +delete(hmenu); + +hmenu = uimenu('Label',['Viewpoints'], 'Tag', mfilename); +set(hmenu, 'UserData', hp); +set(hmenu, 'Callback', 'set(findobj(gcbo, ''Label'', ''Z-flip''), ''checked'', iff(strncmp(get(get(get(gcbo,''UserData''), ''Parent''), ''Zdir''),''r'',1),''on'',''off''))'); + +vp={'Top', 'Bottom', 'Left', 'Right', 'Front', 'Back','Front Right','Front Left','Back Right','Back Left' }; + +t = uimenu('Parent',hmenu,'Label','CTF'); +for i=1:length(vp) + uimenu('Parent', t, 'Label', vp{i}, 'Callback', [ mfilename '(''ctf'', ''' lower(vp{i}) ''',gcbo);']); +end + +t = uimenu('Parent',hmenu,'Label','MNI'); +vp={'Top', 'Bottom', 'Left', 'Right', 'Front', 'Back'}; +for i=1:length(vp) + uimenu('Parent', t, 'Label', vp{i}, 'Callback', [ mfilename '(''mni'', ''' lower(vp{i}) ''',gcbo);']); +end + +t = uimenu('Parent',hmenu,'Label','AIMS'); +vp={'Top', 'Bottom', 'Left', 'Right', 'Front', 'Back'}; +for i=1:length(vp) + uimenu('Parent', t, 'Label', vp{i}, 'Callback', [ mfilename '(''aims'', ''' lower(vp{i}) ''',gcbo);']); +end + +t=uimenu('Parent', hmenu, 'Label', 'Z-flip', 'Separator', 'on', ... + 'Callback',[ mfilename '(''zflip'',gcbo);'] ); +if strncmp(get(ha, 'zdir'), 'r',1); + set(t, 'Checked', 'on'); +end + +return + + +function [ho]=action_zflip(ho) +if nargin<1 + ho=[]; + hmnu=[]; +end +if isequal(get(ho, 'type'), 'uimenu') + hmnu=ho; + ho=get(get(ho, 'Parent'), 'UserData'); +end +[ho,ha]=findTessellationHandles(ho); +if strncmp(get(ha, 'zdir'), 'normal',1); + set(ha, 'zdir', 'reverse') + set(hmnu, 'Checked', 'on') +else + set(ha, 'zdir', 'normal') + set(hmnu, 'Checked', 'off') +end + + +function [ho]=action_ctf(vp,ho) +% Change viewpoint (vp) for object ho (which can be a patch handle or a +% menu handle) +if nargin<2 + ho=[]; + hmnu=[]; +end +if isequal(get(ho, 'type'), 'uimenu') + hmnu=ho; + ho=get(get(ho, 'Parent'), 'UserData'); +end +[ho,ha]=findTessellationHandles(ho); +z=strncmp(get(ha, 'zdir'), 'n',1); +switch lower(vp) + case 'top' + view(ha,[0,0,1]) + % view(ha,180*(1-z),90*(1-2*z)) + case 'bottom' + view(ha,[0,0,-1]) + % view(ha,180*z,-90*(1-2*z)) + case 'left' + view(ha,[0,1,0]) + % view(ha, 90+180*z,0) + case 'right' + view(ha,[0,-1,0]) + % view(ha,-90+180*z,0) + case 'front' + view(ha,[1,0,0]) + % view(ha,0,0) + case 'back' + view(ha,[-1,0,0]) + % view(ha,180,0) + case 'front left' + view(ha,[90+40 15]) + case 'front right' + view(ha,[40 15]) + % view(ha,180,0) + case 'back left' + view(ha,[-90-40 15]) + % view(ha,180,0) + case 'back right' + view(ha,[-40 15]) + % view(ha,180,0) + +end + + + +function [ho]=action_mni(vp,ho) +% Change viewpoint (vp) for object ho (which can be a patch handle or a +% menu handle) +if nargin<2 + ho=[]; + hmnu=[]; +end +if isequal(get(ho, 'type'), 'uimenu') + hmnu=ho; + ho=get(get(ho, 'Parent'), 'UserData'); +end +[ho,ha]=findTessellationHandles(ho); +switch lower(vp) + case 'top' + view(ha,[0 0 1]) + case 'bottom' + view(ha,[0 0 -1]) + case 'left' + view(ha,[-1 0 0]) + case 'right' + view(ha,[1 0 0]) + case 'front' + view(ha,[0 1 0]) + case 'back' + view(ha,[0 -1 0]) + case 'zflip' + if z + set(ha, 'zdir', 'reverse') + set(hmnu, 'Checked', 'on') + else + set(ha, 'zdir', 'normal') + set(hmnu, 'Checked', 'off') + end +end + + +function [ho]=action_aims(vp,ho) +% Change viewpoint (vp) for object ho (which can be a patch handle or a +% menu handle) +if nargin<2 + ho=[]; + hmnu=[]; +end +if isequal(get(ho, 'type'), 'uimenu') + hmnu=ho; + ho=get(get(ho, 'Parent'), 'UserData'); +end +[ho,ha]=findTessellationHandles(ho); +switch lower(vp) + case 'top' + view(ha,[0 0 1]) + case 'bottom' + view(ha,[0 0 -1]) + case 'left' + view(ha,[-1 0 0]) + case 'right' + view(ha,[1 0 0]) + case 'front' + view(ha,[0 1 0]) + case 'back' + view(ha,[0 -1 0]) +end diff --git a/brainstorm3.m b/brainstorm3.m new file mode 100644 index 0000000..4dbe5b7 --- /dev/null +++ b/brainstorm3.m @@ -0,0 +1,26 @@ +DIRS = { + 'I:/mtoolbox/brainstorm3', + 'e:/mtoolbox/brainstorm3', + '/mount/usb/mtoolbox/brainstorm3', + '\\Serveur_meg\homes\mtoolbox\brainstorm3', + '~/mtoolbox/brainstorm3' }; + +for i=1:length(DIRS) + if exist(DIRS{i}, 'dir') + addpath(DIRS{i}) + break; + end + i=i+1; +end + +if i>length(DIRS) + % try to guess where that folder could be + DIRS{i} = fullfile(fileparts(fileparts(mfilename('fullpath'))),'mtoolbox','brainstorm3'); + if exist(DIRS{i},'dir') + addpath(DIRS{i}); + else + error('No directory found for brainstorm3') + end +end +disp(['Launching Brainstorm from: ' DIRS{i}]) +brainstorm \ No newline at end of file diff --git a/brainstorm3/ExtThreshold.zip b/brainstorm3/ExtThreshold.zip new file mode 100644 index 0000000000000000000000000000000000000000..64391c9d2ff045b89a3a8a9217ddaa28d48b9d38 GIT binary patch literal 83824 zcmV)WK(4<~O9KQH0000800vx1J1U)*Kz2O<05etr01yBb0Ah1=UuR`>LvL<$Wq5Qh zZBBog8n4k|>*Z z5~U)k-E28qE{Ggbh)I9}K+B46_qSj7yuShDE8XS!#xO=o42 zrP2GFqCCmcl6)?^5&RyebMl$~nrv_AA3sNL@XrrRA_}&nPjMdS%Os6DPo71`lj(=I zgXziTXgc`w^eB2u$|#PG^EgS1GRxOdQRdrOxy?xrN>6W-B3cOa@OxX3c~oXm3`p{L zRz~G5iSFWi_&2716huKNqBzGtvz*KU8o;}r^xqDmBlz`(KGErLJUE$Nj)#K@fAx?D 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